2011 : WHAT SCIENTIFIC CONCEPT WOULD IMPROVE EVERYBODY'S COGNITIVE TOOLKIT?

I recently posted a question in this space asking people to name their favorite example of a wrong scientific belief. One of my favorite answers came from Clay Shirky. Here is an excerpt:

The existence of ether, the medium through which light (was thought to) travel. It was believed to be true by analogy — waves propagate through water, and sound waves propagate through air, so light must propagate through X, and the name of this particular X was ether.

It's also my favorite because it illustrates how hard it is to accumulate evidence for deciding something doesn't exist. Ether was both required by 19th century theories and undetectable by 19th century apparatus, so it accumulated a raft of negative characteristics: it was odorless, colorless, inert, and so on.

Several other entries (such as the "force of gravity") shared the primary function of ether: they were convenient fictions that were able to "explain" some otherwise ornery facts. Consider this quote from Max Pettenkofer, the German chemist and physician, is disputing the role of bacteria as a cause of the cholera. "Germs are of no account in cholera! The important thing is the disposition of the individual."

So in answer to the current question I am proposing that we now change the usage of the word Aether, using the old spelling, since there is no need for a term that refers to something that does not exist. Instead, I suggest we use that term to describe the role of any free parameter used in a similar way: that is, Aether is the thing that makes my theory work. Replace the word disposition with Aether in Pettenkofer's sentence above to see how it works.

Often Aetherists (theorists who rely on an Aether variable) think that their use of the Aether concept renders the theory untestable. This belief is often justified during their lifetimes, but then along comes clever empiricists such as Michelson and Morley and last year's tautology become this year's example of a wrong theory.

Aether variables are extremely common in my own field of economics. Utility is the thing you must be maximizing in order to render your choice rational.

Both risk and risk aversion are concepts that were once well defined, but are now in danger of becoming Aetherized. Stocks that earn surprisingly high returns are labeled as risky, because in the theory, excess returns must be accompanied by higher risk. If, inconveniently, the traditional measures of risk such as variance or covariance with the market are not high, then the Aetherists tell us there must be some other risk; we just don't know what it is.

Similarly, traditionally the concept of risk aversion was taken to be a primitive; each person had a parameter, gamma, that measured her degree of risk aversion. Now risk aversion is allowed to be time varying, and Aetherists can say with a straight face that the market crashes of 2001 and 2008 were caused by sudden increases in risk aversion. (Note the direction of the causation. Stocks fell because risk aversion spiked, not vice versa.)

So, the next time you are confronted with such a theory, I suggest substituting the word Aether for the offending concept. Personally, I am planning to refer to the time-varying variety of risk aversion as Aether aversion.

Not all concepts wielded by professional scientists would improve everybody's cognitive toolkit. We are here not looking for tools with which research scientists might benefit their science. We are looking for tools to help non-scientists understand science better, and equip them to make better judgments throughout their lives.

Why do half of all Americans believe in ghosts, three quarters believe in angels, a third believe in astrology, three quarters believe in Hell? Why do a quarter of all Americans and believe that the President of the United States was born outside the country and is therefore ineligible to be President? Why do more than 40 percent of Americans think the universe began after the domestication of the dog?

Let's not give the defeatist answer and blame it all on stupidity. That's probably part of the story, but let's be optimistic and concentrate on something remediable: lack of training in how to think critically, and how to discount personal opinion, prejudice and anecdote, in favour of evidence. I believe that the double-blind control experiment does double duty. It is more than just an excellent research tool. It also has educational, didactic value in teaching people how to think critically. My thesis is that you needn't actually do double-blind control experiments in order to experience an improvement in your cognitive toolkit. You only need to understand the principle, grasp why it is necessary, and revel in its elegance.

If all schools taught their pupils how to do a double-blind control experiment, our cognitive toolkits would be improved in the following ways:

1. We would learn not to generalise from anecdotes.

2. We would learn how to assess the likelihood that an apparently important effect might have happened by chance alone.

3. We would learn how extremely difficult it is to eliminate subjective bias, and that subjective bias does not imply dishonesty or venality of any kind. This lesson goes deeper. It has the salutary effect of undermining respect for authority, and respect for personal opinion.

4. We would learn not to be seduced by homeopaths and other quacks and charlatans, who would consequently be put out of business.

5. We would learn critical and sceptical habits of thought more generally, which not only would improve our cognitive toolkit but might save the world.

Physicists created the term "phase transition" to describe a change of state in a physical system, such as liquid to gas. The concept has since been applied in a variety of academic circles to describe other types of systems, from social transformations (think hunter-gatherer to farmer) to statistics (think abrupt changes in algorithm performance as parameters change), but has not yet emerged as part of the common lexicon.

One interesting aspect of the concept of the phrase transition is that it describes a shift to a state seemingly unrelated to the previous one, and hence provides a model for phenomena that challenge our intuition. With only knowledge of water as a liquid, who would have imagined a conversion to gas with the application of heat? The mathematical definition of a phase transition in the physical context is well-defined, but even without this precision I argue this idea can be usefully extrapolated to describe a much broader class of phenomena today, particularly those that change abruptly and unexpectedly with an increase in scale.

Imagine points in 2 dimensions — a spray of dots on a sheet of paper. Now imagine a point cloud in three dimensions, say, dots hovering in the interior of a cube. Even if we could imagine points in four dimensions would we have guessed that all these points lie on the convex hull of this point cloud? In dimensions greater than three they always do. There hasn't been a phase transition in the mathematical sense, but as dimension is scaled up the system shifts in a way we don't intuitively expect.

I call these types of changes "scale transitions:" unexpected outcomes resulting from increases in scale. For example, increases in the number of people interacting in a system can produce unforeseen outcomes: the operation of markets at large scales is often counterintuitive, think of the restrictive effect rent control laws can have on the supply of affordable rental housing or how minimum wage laws can reduce the availability of low wage jobs (James Flynn gives  "markets" as an example of a "shorthand abstraction," here I am interested in the often counterintuitive operation of a market system at large scale); the serendipitous effects of enhanced communication, for example collaboration and interpersonal connection generating unexpected new ideas and innovation; or the counterintuitive effect of massive computation in science reducing experimental reproducibility as data and code have proved harder to share than their descriptions. The concept of the scale transition is purposefully loose, designed as a framework for understanding when our natural intuition leads us astray in large scale situations.

This contrasts from Merton's concept of "unanticipated consequences" in that a scale transition refers both to a system, rather than individual purposeful behavior, and is directly tied to the notion of changes due to scale increases. Our intuition regularly seems to break down with scale and we need a way of conceptualizing the resulting counterintuitive shifts in the world around us. Perhaps the most salient feature of the digital age is its facilitation of massive increases in scale, in data storage, processing power, connectivity, thus permitting us to address an unparalleled number of problems on an unparalleled scale. As technology becomes increasingly pervasive I believe scale transitions will become commonplace.

We need to extend our time-horizons. Especially, we need deeper and wider awareness that far more time lies ahead than has elapsed up till now.

Our present biosphere is the outcome of more than four billion years of evolution; and we can trace cosmic history right back to a "big bang" that happened about 13.7 billion years ago. The stupendous time-spans of the evolutionary past are now part of common culture and understanding — even though the concept may not yet have percolated all parts of Kansas, and Alaska.

But the immense time-horizons that stretch ahead — though familiar to every astronomer — haven't permeated our culture to the same extent. Our Sun is less than half way through its life. It formed 4.5 billion years ago, but it's got 6 billion more before the fuel runs out. It will then flare up, engulfing the inner planets and vaporising any life that might then remain on Earth. But even after the Sun's demise, the expanding universe will continue — perhaps for ever — destined to become ever colder, ever emptier. That, at least, is the best long range forecast that cosmologists can offer, though few would lay firm odds on what may happen beyond a few tens of billions of years.

Awareness of the "deep time" lying ahead is still not pervasive. Indeed, most people — and not only those for whom this view is enshrined in religious beliefs —envisage humans as in some sense the culmination of evolution. But no astronomer could believe this; on the contrary, it would be equally plausible to surmise that we are not even at the halfway stage. There is abundant time for posthuman evolution, here on Earth or far beyond, organic or inorganic, to give rise to far more diversity, and even greater qualitative changes, than those that have led from single-celled organisms to humans. Indeed this conclusion is strengthened when we realise that future evolution will proceed not on the million-year timescale characteristic of Darwinian selection, but at the much accelerated rate allowed by genetic modification and the advance of machine intelligence (and forced by the drastic environmental pressures that would confront any humans who were to construct habitats beyond the Earth.

Darwin himself realised that "No living species will preserve its unaltered likeness into a distant futurity". We now know that "futurity" extends far further, and alterations can occur far faster — than Darwin envisioned. And we know that the cosmos, through which life could spread, is far more extensive and varied than he envisaged. So humans are surely not the terminal branch of an evolutionary tree, but a species that emerged early in cosmic history, with special promise for diverse evolution. But this is not to diminish their status. We humans are entitled to feel uniquely important as the first known species with the power to mould its evolutionary legacy.

To sustain progress on a finite planet that is increasingly under human sway, but also full of surprises, what is needed is a strong dose ofanthropophilia. I propose this word as shorthand for a rigorous and dispassionate kind of self regard, even self appreciation, to be employed when individuals or communities face consequential decisions attended by substantial uncertainty and polarizing disagreement.
 
The term is an intentional echo of Ed Wilson's valuable effort to nurturebiophilia, the part of humanness that values and cares for the facets of the non-human world we call nature. What's been missing too long is an effort to fully consider, even embrace, the human role within nature and — perhaps more important still — to consider our own inner nature, as well.
 
Historically, many efforts to propel a durable human approach to advancement were shaped around two organizing ideas: "woe is me" and "shame on us," with a good dose of "shame on you" thrown in.
 
The problem?
 
Woe is paralytic, while blame is both divisive and often misses the real target. (Who's the bad guy, BP or those of us who drive and heat with oil?)
 
Discourse framed around those concepts too often produces policy debates that someone once described to me, in the context of climate, as "blah, blah, blah bang." The same phenomenon can as easily be seen in the unheeded warnings leading to the most recent financial implosion and the attack on the World Trade Center.
 
More fully considering our nature — both the "divine and felonious" sides, as Bill Bryson has summed us up — could help identify certain kinds of challenges that we know we'll tend to get wrong.
 
The simple act of recognizing such tendencies could help refine how choices are made — at least giving slightly better odds of getting things a little less wrong the next time.  At the personal level, I know when I cruise into the kitchen tonight I'll tend to prefer to reach for a cookie instead of an apple. By pre-considering that trait, I might have a slightly better chance of avoiding a couple of hundred unnecessary calories.
 
Here are a few instances where this concept is relevant on larger scales.
 
There's a persistent human pattern of not taking broad lessons from localized disasters. When China's Sichuan province was rocked by a severe earthquake, tens of thousands of students (and their teachers) died in collapsed schools. Yet the American state of Oregon, where more than a thousand schools are already known to be similarly vulnerable when the great Cascadia fault off the Northwest Coast next heaves, still lags terribly in speeding investments in retrofitting.
 
Sociologists understand with quite a bit of empirical backing why this disconnect exists even though the example was horrifying and the risk in Oregon is about as clear as any scientific assessment can be. But does that knowledge of human biases toward the "near and now" get taken seriously in the realms where policies are shaped and the money to carry them out is authorized? Rarely, it seems.
 
Social scientists also know, with decent rigor, that the fight over human-driven global warming — both over the science and policy choices — is largely cultural. As in many other disputes (consider health care) the battle is between two quite fundamental subsets of human communities — communitarians (aka, liberals) and individualists (aka, libertarians). In such situations, a compelling body of research has emerged showing how information is fairly meaningless. Each group selects information to reinforce a position and there are scant instances where information ends up shifting a position.
 
That's why no one should expect the next review of climate science from the Intergovernmental Panel on Climate Change to suddenly create a harmonious path forward.
 
The more such realities are recognized, the more likely it is that innovative approaches to negotiation can build from the middle, instead of arguing endlessly from the edge. The same body of research on climate attitudes, for example, shows far less disagreement on the need for advancing the world's limited menu of affordable energy choices.
 
Murray Gell-Mann has spoken often of the need, when faced with multi-dimensional problems, to take a "crude look at the whole" — a process he has even given an acronym, CLAW. It's imperative, where possible, for that look to include an honest analysis of the species doing the looking, as well.
 
There will never be a way to invent a replacement for, say, the United Nations or the House of Representatives. But there is a ripe opportunity to try new approaches to constructive discourse and problem solving, with the first step being an acceptance of our humanness, for better and worse.
 
That's anthropophilia.

Since different visiting teachers had promoted contradictory philosophies, the villagers asked the Buddha whom they should believe. The Buddha advised: “When you know for yourselves ... these things, when performed and undertaken, conduce to well-being and happiness — then live and act accordingly.” Such empirical advice might sound surprising coming from a religious leader, but not from a scientist.

“See for yourself” is an unspoken credo of science. It is not enough to run an experiment and report the findings. Others who repeat that experiment must find the same thing. Repeatable experiments are called “replicable.” Although scientists implicitly respect replicability, they do not typically explicitly reward it.

To some extent, ignoring replicability comes naturally. Human nervous systems are designed to respond to rapid changes, ranging from subtle visual flickers to pounding rushes of ecstasy. Fixating on fast change makes adaptive sense — why spend limited energy on opportunities or threats that have already passed? But in the face of slowly growing problems, “change fixation” can prove disastrous (think of lobsters in the cooking pot or people under greenhouse gases).

Cultures can also promote change fixation. In science, some high profile journals and even entire fields emphasize novelty, consigning replications to the dustbin of the unremarkable and unpublishable. More formally, scientists are often judged based on their work’s novelty rather than replicability. The increasingly popular “h-index” quantifies impact by assigning a number (h) which indicates that an investigator has published h papers that have been cited h or more times (so, Joe Blow has an h-index of 5 if he has published 5 papers, each of which others have cited 5 or more times). While impact factors correlate with eminence in some fields (e.g., physics), problems can arise. For instance, Doctor Blow might boost his impact factor by publishing controversial (thus, cited) but unreplicable findings.

Why not construct a replicability (or “r”) index to complement impact factors? As with h, r could indicate that a scientist has originally documented r separate effects that independently replicate r or more times (so, Susie Sharp has an r-index of 5 if she has published 5 independent effects, each of which others have replicated 5 or more times). Replication indices would necessarily be lower than citation indices, since effects have to first be published before they can be replicated, but might provide distinct information about research quality. As with citation indices, replication indices might even apply to journals and fields, providing a measure that can combat biases against publishing and publicizing replications.

A replicability index might prove even more useful to nonscientists. Most investigators who have spent significant time in the salt mines of the laboratory already intuit that most ideas don’t pan out, and those that do sometimes result from chance or charitable interpretations. Conversely, they also recognize that replicability means they’re really on to something. Not so for the general public, who instead encounter scientific advances one cataclysmic media-filtered study at a time. As a result, laypeople and journalists are repeatedly surprised to find the latest counterintuitive finding overturned by new results. Measures of replicability could help channel attention towards cumulative contributions. Along these lines, it is interesting to consider applying replicability criteria to public policy interventions designed to improve health, enhance education, or curb violence. Individuals might even benefit from using replicability criteria to optimize their personal habits (e.g., more effectively dieting, exercising, working, etc.).

Replication should be celebrated rather than denigrated. Often taken for granted, replicability may be the exception rather than the rule. As running water resolves rock from mud, so can replicability highlight the most reliable findings, investigators, journals, and even fields. More broadly, replicability may provide an indispensable tool for evaluating both personal and public policies. As suggested in the Kalama Sutta, replicability might even help us decide whom to believe.

The ability to reason clearly in the face of uncertainty.  

If everybody could learn to deal better with the unknown, then it would improve not only their individual cognitive toolkit (to be placed in a slot right next to the ability to operate a remote control, perhaps), but the chances for humanity as a whole.

A well-developed scientific method for dealing with the unknown has existed for many years — the mathematical theory of probability. Probabilities are numbers whose values reflect how likely different events are to take place. People are bad at assessing probabilities. They are bad at it not just because they are bad at addition and multiplication.  Rather, people are bad at probability in a deep, intuitive level: they overestimate the probability of rare but shocking events -- a burglar breaking into your bedroom while you're asleep, say. Conversely, they underestimate the probability of common, but quiet and insidious events   — the slow accretion of globules of fat on the walls of an artery, or another ton of carbon dioxide pumped into the atmosphere.  

I can't say that I'm very optimistic about the odds that people will learn to understand the science of odds. When it comes to understanding probability, people basically suck. Consider the following example, based on a true story, and reported by Joel Cohen of Rockefeller University. A group of graduate students note that women have an significantly lower chance of admission than men to the graduate programs at a major university. The data are unambiguous: women applicants are only two thirds as likely as male applicants to be admitted. The graduate students file suit against the university, alleging discrimination on the basis of gender.  When admissions data are examined on a department by department basis, however, a strange fact emerges: within each department, women are MORE likely to be admitted than men. How can this possibly be?  

The answer turns out to be simple, if counterintuitive. More women are applying to departments that have few positions. These departments admit only a small percentage of applicants, men or women. Men, by contrast, are applying to departments that have more positions and that admit a higher percentage of applicants. Within each department, women have a better chance of admission than men — it's just that few women apply to the departments that are easy to get into.  

This counterintuitive result indicates that the admissions committees in the different departments are not discriminating against women. That doesn't mean that bias is absent. The number of graduate fellowships available in a particular field is determined largely by the federal government, which chooses how to allocate reserach funds to different fields. It is not university that is guilty of sexual discrimination, but the society as a whole, which chose to devote more resources — and so more graduate fellowships — to the fields preferred by men.

Of course, some people are good at probability. A car insurance company that can't accurately determine the probabilities of accidents will go broke. In effect, when we pay out premiums to insure ourselves against a rare event, we are buying into the insurance company's estimate of just how likely that event is. Driving a car is one of those common but dangerous processes where human beings habitually understimate the odds of something bad happening, however. Accordingly, some are disinclined to obtain car insurance (perhaps not suprising when the considerable majority of people rate themselves as better than average drivers). When a state government requires its citizens to buy car insurance, it does so because it figures, rightly, that people are underestimating the odds of an accident.  

Let's consider the debate over whether health insurance should be required by law. Living, like driving, is a common but dangerous process where people habitually underestimate risk, despite that fact that, with probability equal to one, living is fatal.

Like others whose early life experiences were punctuated with trauma, my memory has holes. Some of those holes are as wide as years. Others, just big enough to swallow painful incidents that lasted moments, but reverberated for decades.

The brain-record of those experiences sometimes submerges, then resurfaces, sometimes submerging again over time. As I grow older, stronger, and more capable of contending with memory, I become more aware of how different my own internal record may be from others who lived the identical moment.

Each of us commit our experiences to memory and permanence differently. Time and human experience are not linear, nor is there one and only one neutral record of each lived moment. Human beings are impossibly complex tarballs of muscle, blood, bone, breath, and electrical pulses that travel through nerves and neurons; we are bundles of electrical pulses carrying payloads, pings hitting servers. And our identities are inextricably connected to our environments: no story can be told without a setting.

My generation is the last generation of human beings who were born into a pre-internet world, but who matured in tandem with that great, networked hive-mind. In the course of my work online, committing new memories to network mind each day, I have come to understand that our shared memory of events, of truths, of biography, and of fact-- all of this shifts and ebbs and flows, just as our most personal memories do.

Ever-edited Wikipedia replaces paper encyclopedias. The chatter of Twitter eclipses fixed-form and hierarchical communication. The news flow we remember from our childhoods, a single voice of authority on one of three channels, is replaced by something hyper-evolving, chaotic, and less easily defined. Even the formal histories of State may be rewritten by the likes of Wikileaks, and its yet-unlaunched children.

Facts are more fluid than in the days of our grandfathers. In our networked mind, the very act of observation--reporting or tweeting or amplifying some piece of experience--changes the story. The trajectory of information, the velocity of this knowledge on the network, changes the very nature of what is remembered, who remembers it, and for how long it remains part of our shared archive. There are no fixed states.

So must our notion of memory and record evolve.

The history we are creating now is alive. Let us find new ways of recording memory, new ways of telling the story, that reflect life. Let us embrace this infinite complexity as we commit new history to record.

Let us redefine what it means to remember.

The concept of cause and effect is better understood as the flow of information between two connected events, from the earlier event to the later one. Saying "A causes B" sounds precise, but is actually very vague. I would specify much more by saying "with the information that A has happened, I can compute with almost total confidence* that B will happen." The latter rules out the possibility that other factors could prevent B even if A does happen, but allows the possibility that other factors could cause B even if A doesn't happen.

As shorthand, we can say that one set of information "specifies" another if the latter can be deduced or computed from the former.  Note that this doesn't only apply to one-bit sets of information, like the occurrence of a specific event. It can also apply to symbolic variables (given the state of the Web, the results you get from a search engine are specified by your query), numeric variables (the number read off a precise thermometer is specified by the temperature of the sensor), or even behavioral variables (the behavior of a computer is specified by the bits loaded in its memory).

But let's take a closer look at the assumptions we're making. Astute readers may have noticed that in one of my examples, I assumed that the entire state of the Web was a constant. How ridiculous! In mathematical parlance, assumptions are known as "priors," and in a certain widespread school of statistical thought, they are considered the most important aspect of any process involving information. What we really want to know is if, given a set of existing priors, adding one piece of information (A) would allow us to update our estimate of the likelihood of another piece of information (B). Of course, this depends on the priors — for instance, if our priors include absolute knowledge of B, then an update will not be possible.

If, for most reasonable sets of priors, information about A would allow us to update our estimate of B, then it would seem there is some sort of causal connection between the two. But the form of the causal connection is unspecified — a principle often called "correlation does not imply causation." The reason for this is that the essence of causation as a concept rests on our tendency to have information about earlier events before we have information about later events. (The full implications of this concept on human consciousness, the second law of thermodynamics, and the nature of time are interesting, but sadly outside the scope of this essay.)

If information about all events always came in the order they occurred, then correlation would indeed imply causation. But, in the real world, not only are we limited to observing events in the past, but we may also discover information about those events out of order.  Thus, the correlations we observe could be reverse causes (information about A allows us to update our estimate of B, although B happened first and thus was the cause of A) or even more complex situations (e.g. information about A allows us to update our estimate of B, but is also giving us information about C, which happened before either A or B and caused both).

Information flow is symmetric: if information about A were to allow us to update our estimate of B, then information about B would allow us to update our estimate of A. But since we cannot change the past or know the future, these constraints are only useful to us when contextualized temporally and arranged in order of occurrence. Information flow is always from the past to the future, but in our minds, some of the arrows may be reversed. Resolving this ambiguity is essentially the problem that science was designed to solve. If you can master the technique of visualizing all information flow and keeping track of your priors, then the full power of the scientific method — and more — is yours to wield from your personal cognitive toolkit.

* In our universe, too many things are interconnected for absolute statements of any kind, so we usually relax our criteria; for instance, "total confidence" might be relaxed from a 0% chance of being wrong to, say, a 1 in 3 quadrillion chance of being wrong — about the chance that, as you finish this sentence, all of humanity will be wiped out by a meteor.

We humans are terrible at dealing with probability. We are not merely bad at it, but seem hardwired to be incompetent, in spite of the fact that we encounter innumerable circumstances every day which depend on accurate probabilistic calculations for our wellbeing. This incompetence is reflected in our language, in which the common words used to convey likelihood are "probably" and "usually" — vaguely implying a 50% to 100% chance. Going beyond crude expression requires awkwardly geeky phrasing, such as "with 70% certainty," likely only to raise the eyebrow of a casual listener bemused by the unexpected precision. This blind spot in our collective consciousness — the inability to deal with probability — may seem insignificant, but it has dire practical consequences. We are afraid of the wrong things, and we are making bad decisions.

Imagine the typical emotional reaction to seeing a spider: fear, ranging from minor trepidation to terror. But what is the likelihood of dying from a spider bite? Fewer than four people a year (on average) die from spider bites, establishing the expected risk of death-by-spider at lower than one in a hundred million. This risk is so minuscule that it is actually counterproductive to worry about it! Millions of people die each year from stress-related illnesses.

The startling implication is that the risk of being bitten and killed by a spider is less than the risk that being afraid of spiders will kill you from increased stress. Our irrational fears and inclinations are costly. The typical reaction to seeing a sugary donut is the desire to consume it. But, given the potential negative impact of that donut, including the increased risk of heart disease and reduction in overall health, our reaction should rationally be one of fear and revulsion. It may seem absurd to fear a donut — or, even more dangerous, a cigarette — but this reaction rationally reflects the potential negative impact on our lives.

We are especially ill-equipped to manage risk when dealing with small likelihoods of major events. This is evidenced by the success of lotteries and casinos at taking peoples' money, but there are many other examples. The likelihood of being killed by terrorism is extremely low, yet we have instituted actions to counter terrorism that significantly reduce our quality of life. As a recent example, x-ray body scanners could increase the risk of cancer to a degree greater than the risk from terrorism — the same sort of counterproductive overreaction as the one to spiders. This does not imply we should let spiders, or terrorists, crawl all over us — but the risks need to be managed rationally.

Socially, the act of expressing uncertainty is a display of weakness. But our lives are awash in uncertainty, and rational consideration of contingencies and likelihoods is the only sound basis for good decisions. As another example, a federal judge recently issued an injunction blocking stem cell research funding. The shallowly viewed implication is that some scientists won't be getting money; but what is really at stake is much more important. The probability that stem cell research will quickly lead to life saving medicine is low, but, if successful, the positive impact could be huge. If one considers outcomes and approximates the probabilities, the conclusion is that the judge's decision destroyed the lives of thousands of people, based on probabilistic expectation.

How do we make rational decisions based on contingencies? That judge didn't actually cause thousands of people to die... or did he? If we follow the "many worlds" interpretation of quantum physics — the most direct interpretation of its mathematical description — then our universe is continually branching into all possible contingencies, and there is a world in which stem cell research saves millions of lives, and another world in which people die because of the judge's decision. Using the "frequentist" method of calculating probability, we have to add the probabilities of the worlds in which an event occurs to obtain the probability of that event. 

Quantum mechanics dictates that the world we experience will happen according to this probability — the likelihood of the event. In this bizarre way, quantum mechanics reconciles the frequentist and "Bayesian" points of view, equating the frequency of an event over many possible worlds with its likelihood. An "expectation value," such as the expected number of people killed by the judge's decision, is the number of people killed in the various contingencies, weighted by their probabilities. This expected value is not necessarily likely to happen, but is the weighted average of the expected outcomes — useful information when making decisions. In order to make good decisions about risk we need to become better at these mental gymnastics, improve our language, and retrain our intuition.

Perhaps the best arena for honing our skills and making precise probabilistic assessments would be a betting market — an open site for betting on the outcomes of many quantifiable and socially significant events. In making good bets, all the tools and shorthand abstractions of Bayesian inference come into play — translating directly to the ability to make good decisions. With these skills, the risks we face in everyday life would become clearer, and we would develop more rational intuitive responses to uncalculated risks, based on collective rational assessment and social conditioning.

We might get over our excessive fear of spiders, and develop a healthy aversion to donuts, cigarettes, television, and stressful full-time employment. We would become more aware of the low cost compared to probable rewards of research, including research into improving the quality and duration of human life. And, more subtly, as we became more aware and apprehensive of ubiquitous vague language, such as "probably" and "usually," our standards of probabilistic description would improve.

Making good decisions requires concentrated mental effort; and if we overdo it we run the risk of being counterproductive through increased stress and wasted time. So it's best to balance, and play, and take healthy risks — as the greatest risk is that we'll get to the end of our lives having never risked them on anything.

The Gibbs Landscape

Biology is rarely wasteful. Sure, on the individual organism level there is plenty of waste involved with reproduction and other activities (think of all the fruit on a tree or the millions of sperm that loose out in the race to the egg). But on the ecosystem level one bug's trash is another bug's treasure — provided that some useful energy can still be extracted by reacting that trash with something else in the environment. The food chain is not a simple linear staircase of predator-prey relationships; it is a complex fabric of organisms large, small, and microscopic interacting with each other and with the environment to tap every possible energetic niche.

Geobiologists and astrobiologists can measure and map this energy —  referred to as the Gibbs free energy. Doing so is useful for assessing the energetic limits of life on Earth and for assessing potentially habitable regions on other worlds. In an ecosystem Gibbs free energy —  named for it's discoverer, the late 19th century scientist J. Willard Gibbs —  is the energy in a biochemical reaction that is available to do work. It's the energy left over after producing some requisite waste heat and a dollop or two of entropy. This energy to do work is harnessed by biological systems for activities like making repairs, growing, and reproducing. For a given metabolic pathway used by life, e.g. reacting carbohydrates with oxygen, we can measure how many Joules are available to do work per mole of reactants. Humans and essentially all the animals you know and love typically harness a couple thousand kiloJoules per mole by burning food with oxygen. Microbes have figured out all sorts of ways to harness the Gibbs free energy by combining various gases, liquids, and rocks. Measurements by Tori Hoehler and colleagues at NASA Ames Research Center on methane-generating and sulfate-eating microbes indicate that the limit for life may be about 10 kiloJoules per mole. Within a given environment there may be many chemical pathways in operation and if there is an open energetic niche, chances are life will find a way to fill it. Biological ecosystems can be mapped as a landscape of reactions and pathways for harnessing energy; this is the Gibbs landscape.

Civilizations and the rise of industrial and technological ecosystems bring a new challenge to our understanding of the dynamic between energy needs and energy resources. The Gibbs landscape provides a short-hand abstraction for conceptualizing this dynamic. We can imagine any given city, country, or continent overlain with a map of energy available to do work. This includes, but extends beyond the chemical energy framework used in the context of biological ecosystems. For instance, automobiles with internal combustion engines metabolize gasoline with air. Buildings eat the electricity supplied by power plants or rooftop solar panels. Every component in modern industrial society occupies some niche in the landscape.

But importantly, many of the Gibbs landscapes in place today are ripe with unoccupied niches. The systems we have designed and built are inefficient and incomplete in the utilization of energy to do the work of civilization's ecosystems. Much of what we have designed excels at producing waste heat with little concern for optimizing work output. From lights that remain on all night to landfills that contain discarded resources, the Gibbs landscapes of today offer much room for technological innovation and evolution. The Gibbs landscape also provides a way for visualizing untapped capacity to do work — wind, solar, hydroelectric, tides and geothermal, these are just a few of the layers. Taken together, all of these layers show us where and how we can work to close the loops and connect the dangling threads of our nascent technological civilization.

When you start to view the world around you with Gibbsian eyes you see the untapped potential in so many of our modern technological and industrial ecosystems. It's disturbing at first because we've done such a poor job, but the marriage between civilization and technology is young. The landscape provides much reason for hope as we continue to innovate and strive to reach the balance and continuity that has served complex biological ecosystems so well for billions of years on Earth.

For far too long we have laboured under a faulty conception of the senses. Ask anyone you know how many senses we have and they will probably say five; unless they start talking to you about a sixth sense. But why pick five? What of the sense of balance provided by the vestibular system, telling you whether you are going up or down in a lift, forwards or backwards on a train, or side to side on a boat? What about proprioception that gives you a firm sense of where your limbs are when you close your eyes? What about feeling pain, hot and cold? Are these just part of touch, like feeling velvet or silk? And why think of sensory experiences like seeing, hearing, tasting, touching and smelling as being produced by a single sense?

Contemporary neuroscientists have postulated two visual systems — one responsible for how things look to us, the other for controlling action — that operate independently of one another. The eye may fall for visual illusions but the hand does not, reaching smoothly for a shape that looks larger than it is to the observer.

And it doesn't stop here. There is good reason to think that we have two senses of smell: an external sense of smell, orthonasal olfaction, produced by inhaling, that enables us to detect things in the environment such food, predators or smoke; and internal sense, retronasal olfaction, produced by exhaling, that enables us to detect the quality of what we have just eaten, allowing us to decide whether we want any more or should expel it.

Associated with each sense of smell is a distinct hedonic response. Orthonasal olfaction gives rise to the pleasure of anticipation. Retronasal olfaction gives rise to the pleasure of reward. Anticipation is not always matched by reward. Have you ever noticed how the enticing aromas of freshly brewed coffee are never quite matched by the taste? There is always a little disappointment. Interestingly, the one food where the intensity of orthonsally and retronasally judged aromas match perfectly is chocolate. We get just what we expected, which may explain why chocolate is such a powerful stimulus.

Besides the proliferation of the senses in contemporary neuroscience, another major change is taking place. We used to study the senses in isolation, with the greatest majority of researchers focusing on vision. Things are rapidly changing. We now know that the senses do not operate in isolation, but combine at both early and late stages of processing to produce our rich perceptual experiences of our surroundings. It is almost never the case that our experience presents us with just sights or sounds. We are always enjoying conscious experiences made up of sights and sounds, smells, the feel of our body, the taste in our mouths; and yet these are not presented as separate sensory parcels. We simply take in the rich and complex scene without giving much thought to how the different contributors produce the whole experience.

We give little thought to how smell provides a background to every conscious waking moment. People who lose their sense of smell can be plunged into depression and show less sign of recovery a year later than people who lose their sight. This is because familiar places no longer smell the same, and people no longer have their reassuring olfactory signature. Also, patients who lose their smell believe they have lost their sense of taste. When tested, they acknowledge that that can taste sweet, sour, salt, bitter savoury, and metallic. But everything else, missing from the taste of what they are eating, is due to retronasal smell.

What we call taste is one of the most fascinating case studies for how inaccurate our view of our senses is: it is not produced by the tongue alone but is always an amalgam of taste, touch and smell. Touch contributes to sauces tasting creamy, and other foods tasting chewy, crisp, or stale. The only difference between potato chips, which "taste" fresh or stale, is a difference in texture. The largest part of what we call "taste" is in fact smell in the form of retronasal olfaction, which is why people who lose their ability to smell say they can no longer taste anything. Taste, touch and smell are not merely combined to produce experiences of foods of liquids, rather the information from the separate sensory channels is fused into a unified experience of that we call taste and food scientists call flavour.

Flavour perception is the result of multi-sensory integration of gustatory, olfactory and oral somatosenory information into a single experience whose components we are unable to distinguish. It is one of the most multi-sensory experiences we have and can be influenced by both sight and sound. The colours of wines and the sounds food make when we bite or chew them can have large impacts on our resulting appreciation and assessment, and irritation of the trigeminal nerve in the face will make chillies feel "hot" and menthol feel "cool" in the mouth without any actual change in temperature.

In sensory perception, multi-sensory integration is the rule not the exception. In audition, we don't just hear with our ears, we use our eyes to locate the apparent sources of sounds in the cinema where we "hear" the voices coming from the actors' mouths on the screen although the sounds are coming from the sides of the theatre. This is known as the ventriloquism effect. Similarly, retronasal odours detected by olfactory receptors in the nose are experienced as tastes in the mouth. The sensations get re-located to the mouth because oral sensations of chewing or swallowing capture our attention, making us think these olfactory experiences are occurring in the same place.

Other surprising collaboration among the senses are due to cross-modal effects, where stimulation of one sense boosts activity in another. Looking at someone's lips across a crowded room can improve our ability to hear what they are saying, and the smell of vanilla can make a liquid we sip "taste" sweeter, and less sour. This is why we say vanilla is sweet smelling, although sweet is a taste, and pure vanilla is not sweet at all. Industrial manufacturers know about these effects and exploit them. Certain aromas in shampoos, for example, can make the hair "feel" softer; and red coloured drinks "taste" sweet, while drinks with a light green colour "taste" sour. In many of these interactions vision will dominate; but not in every case

. For anyone unlucky enough to have disturbance in their vestibular system they will feel the world is spinning although cues from the eyes and the body should be telling them everything is still. Instead, the brain goes with the combined picture and vision and proprioception fall in line. Luckily, our senses cooperate and we get us around the world, and the world we inhabit is not a sensory, but a multisensory world.

Statistically significant difference — It is a simple phrase that is essential to science and that has become common parlance among educated adults. These three words convey a basic understanding of the scientific process, random events, and the laws of probability. The term appears almost everywhere that research is discussed — in newspaper articles, advertisements for "miracle" diets, research publications, and student laboratory reports, to name just a few of the many diverse contexts where the term is used. It is a short hand abstraction for a sequence of events that includes an experiment (or other research design), the specification of a null and alternative hypothesis, (numerical) data collection, statistical analysis, and the probability of an unlikely outcome. That is a lot of science conveyed in a few words.

It would be difficult to understand the outcome from any research without at least a rudimentary understanding of what is meant by the conclusion that the researchers found or did not find evidence of a "statistically significant difference." Unfortunately, the old saying that "a little knowledge is a dangerous thing" applies to the partial understanding of this term. One problem is that "significant" has a different meaning when used in everyday speech than when used to report research findings.

Most of the time, the word "significant" means that something important happened. For example, if a physician told you that you would feel significantly better following surgery, you would correctly infer that your pain would be reduced by a meaningful amount—you would feel less pain. But, when used in "statistically significant difference," the term "significant" means that the results are unlikely to be due to chance (if the null hypothesis were true); the results may or may not be important. In addition, sometimes, the conclusion will be wrong because researcher can only assert their conclusion at some level of probability. "Statistically significant difference" is a core concept in research and statistics, but as anyone who was taught undergraduate statistics or research methods can tell you, it is not an intuitive idea.

Despite the fact that "statistically significant difference" communicates a cluster of ideas that are essential to the scientific process, there are many pundits who would like to see it removed from our vocabulary because it is frequently misunderstood. Its use underscores the marriage of science and probability theory, and despite its popularity, or perhaps because of it, some experts have called for a divorce because the term implies something that it does not, and the public is often misled. In fact, experts are often misled as well. Consider this hypothetical example: In a well-done study that compares the effectiveness of two drugs relative to a placebo, it is possible that Drug X is statistically significantly different from a placebo and Drug Y is not, yet Drugs X and Y might not be statistically significant different from each other. This could result when Drug X is statistically different from placebo at a probability level of p < .04, but Drug Y is statistically significantly different from a placebo only at a probability level of p < .06, which is higher than most a priori levels used to test for statistical significance. If just reading about this makes your head hurt, you are among the masses who believe they understand this critical shorthand phrase which is at the heart of the scientific method, but actually may have a shallow-level of understanding.

There are many critically important ways that findings of "statistically significant difference" can be misleading. But, even though there are real problems with understanding this term, it is firmly entrenched in everyday discussions of research, and for the general public, it shows some knowledge of the process of science.

A better understanding of the pitfalls associated with this term would go a long way toward improving our "cognitive toolkits." If common knowledge of what this term means included the ideas that a) the findings may not be important and b) conclusions based on finding or failure to find statistically significant differences may be wrong, then we would have significantly advanced general knowledge. When people read or use the term "statistically significant difference," it is an affirmation of the scientific process, which, for all of its limitations and misunderstandings, is a significant advance over alternative ways of knowing about the world. If we could just add two more key concepts to the meaning of that phrase, we could improve how the general public thinks about science.

The Dece(i)bo Effect — think portmanteau of Deceive and Placebo — refers to the facile application of constructs, without unpackaging the concept and the assumptions on which it relies, in a fashion that, rather than benefiting thinking, leads reasoning astray.  

Words and phrases enter common parlance, that capture a concept: Occam's razor, placebo, Hawthorne effect. Such phrases and code-words in principle facilitate discourse — and can indeed do so. Deploying the word or catchphrase adds efficiency to the interchange, by obviating the need for pesky review of the principles and assumptions encapsulated in the word.

Unfortunately, bypassing the need to articulate the conditions and assumptions on which validity of the construct rests, may lead to bypassing consideration of whether these conditions and assumptions legitimately apply. Use of the term can then, far from fostering sound discourse, serve to undermine it.

Take, for example, the "placebo," and "placebo effects." Unpackaging the terms, a "placebo" is in principle something that is physiologically "inert" — but believed by the recipient to be active, or possibly so. The term "placebo effect" refers to improvement of a condition when persons have been placed on a placebo, due to effects of expectation/suggestion.

With these terms well ensconced in the vernacular, Dece(i)bo Effects associated with them are much in evidence.  Key presumptions regarding placebos and placebo effects are more typically wrong than not.

1. When hearing the word "placebo," scientists often presume "inert" - without stopping to ask: what is that allegedly physiologically inert substance? Indeed, even in principle, what could it be??

There isn't anything known to be physiologically inert. There are no regulations about what constitute placebos; and their composition — commonly determined by the manufacturer of the drug under study — is typically undisclosed.  Among the uncommon cases where placebo composition has been noted, there are documented instances in which the placebo composition apparently produced spurious effects. Two studies used corn oil and olive oil placebos for cholesterol-lowering drugs: one noted that the "unexpectedly" low rate of heart attacks in the control group may have contributed to failure to see a benefit from the cholesterol drug. Another study noted "unexpected" benefit of a drug to gastrointestinal symptoms in cancer patients. But cancer patients bear increased likelihood of lactose intolerance — and the placebo was lactose, a "sugar pill." When the term "placebo" substitutes for actual ingredients, any thinking about how the composition of the control agent may have influenced the study is circumvented.

2. Because there are many settings in which persons with a problem, given placebo, report sizeable improvement on average when they are re-queried (see 3), many scientists have accepted that "placebo effects" — of suggestion — are both large in magnitude and widespread in the scope of what they benefit.

The Danish researcher Asbjørn Hróbjartsson conducted a systematic review of studies that compared a placebo to no treatment. He found that the placebo generally does: nothing. In most instances, there is no placebo effect. Mild "placebo effects" are seen, in the short term, for pain and anxiety. Placebo effects for pain are reported to be blocked by naloxone, an opiate antagonist — specifically implicating endogenous opiates in pain placebo effects, which would not be expected to benefit every possible outcome that might be measured.

3. When hearing that persons with a problem placed on a "placebo" report improvement, scientists commonly presume this must be due to the "placebo effect" - the effect of expectation/suggestion.

However, the effects are usually something else entirely. For instance: natural history of the disease, and regression to the mean. Consider a distribution, such as a bell-shape. Whether the outcome of interest is pain, blood pressure, cholesterol, or other, persons are classically selected for treatment if they are at one end of the distribution - say, the high end. But these outcomes are quantities that vary (for instance from physiological variation, natural history, measurement error...), and on average the high values will vary back down — a phenomenon termed "regression to the mean" that operates, placebo or no. (Hence, Hróbjartsson's findings.)

A different dece(i)bo problem beset Ted Kaptchuk's recent Harvard study in which researchers gave a "placebo," or nothing, to people afflicted with irritable bowel syndrome. They administered the placebo in a bottle boldly labeled "Placebo," and advised patients they were receiving placebos, which were known to be potent. The thesis was that one might harness the effects of expectation honestly, without deception, by telling subjects how powerful placebos in fact were - and by developing a close relationship with subjects. Researchers met repeatedly with subjects, gained subjects' appreciation for their concern and listening (as the researchers made clear), and repeatedly told subjects that placebos are powerful. Those placed on placebo obliged the researchers by telling them they had gotten better, moreso than those on nothing. The scientists attributed this to a placebo effect.

But what's to say patients weren't simply telling the scientists what they thought the scientists wished to hear? Such desire to please (a form, perhaps, of "social approval" reporting bias) had fertile grounds in which to operate and create what was interpreted as a placebo effect — which implies actual subjective benefit to symptoms. One wonders if so great an error of presumption would operate were there not an existing term, "placebo effect," to signify the interpretation the Harvard group chose.

Another explanation consistent with these results is specific physiological benefit. The study used a nonabsorbed fiber — microcrystalline cellulose — as the "Placebo" that subjects were told would be effective. The authors are applauded for disclosing its composition. But other nonabsorbed fibers benefit both constipation and diarrhea — symptoms of irritable bowel — and are prescribed for that purpose; psyllium is an example. Thus, specific physiological benefit of the "Placebo" to symptoms cannot be excluded.

Together these points illustrate that the term "placebo" cannot be presumed to imply "inert" (and generally does not); and that when studies see large benefit to symptoms in patients treated with "placebo" (expected from distribution considerations alone), one cannot infer these arose from large benefits of suggestion to symptoms (which evidence indicates may seldom operate).

Thus, rather than facilitating sound reasoning, evidence suggests that in many cases, including high stakes settings in which inferences may propagate to medical practice, substitution of a term — here, "placebo," "placebo effect" — for the concepts they are intended to convey, may actually thwart or bypass critical thinking about key issues, with implications to fundamental concerns for us all.

Everyone should know what proof feels like. It reduces all other species of belief to a distant second-class status. Proof is the far end on a cognitive scale of confidence that varies through levels of doubt. And most people never experience it. 

Feeling proof comes from finishing a proof. It does not come from pointing at a proof in a book or in the brain of an instructor. It comes when the prover himself takes the last logical step on the deductive staircase. Then he gets to celebrate that logical feat by declaring "Q. E. D." or "Quod Erat Demonstrandum" or just "Quite Easily Done." Q. E. D. states that he has proven or demonstrated the claim that he wanted to prove. The proof need not be original or surprising. It just needs to be logically correct to produce a Q. E. D. moment. A proof of the Pythagorean Theorem has always sufficed.

The only such proofs that warrant the name are those in mathematics and formal logic. Each logical step has to come with a logically sufficient justification. That way each logical step comes with binary certainty. Then the final result itself follows with binary certainty. It is as if the prover multiplied the number 1 by itself for each step in the proof. The result is still the number 1. That is why the final result warrants a declaration of Q. E. D. That is also why the process comes to an unequivocal halt if the prover cannot justify a step. Any act of faith or guesswork or cutting corners will destroy the proof and its demand for binary certainty.

The catch is that we can really only prove tautologies.

The great binary truths of mathematics are still logically equivalent to the tautology "1 = 1" or "green is green." This differs from the factual statements we make about the real world — statements such as "Pine needles are green" or "Chlorophyll molecules reflect green light."

These factual statements are approximations. They are technically vague or fuzzy. And they often come juxtaposed with probabilistic uncertainty: "Pine needles are green with high probability." Note that this last statement involves triple uncertainty. There is first the vagueness of green pine needles because there is no bright line between greenness and non-greenness. It is a matter of degree. There is second only a probability whether pine needles have the vague property of greenness. And there is last the magnitude of the probability itself. The magnitude is the vague or fuzzy descriptor "high" because here too there is no bright line between high probability and not-high probability.

No one has ever produced a statement of fact that has the same 100% binary truth status as a mathematical theorem. Even the most accurate energy predictions of quantum mechanics hold only out to a few decimal places. Binary truth would require getting it right out to infinitely many decimal places.

Most scientists know this and rightly sweat it. The logical premises of a math model only approximately match the world that the model purports to model. It is not at all clear how such grounding mismatches propagate through to the model's predictions. Each infected inferential step tends to degrade the confidence of the conclusion as if multiplying fractions less than one. Modern statistics can appeal to confidence bounds if there are enough samples and if the samples sufficiently approximate the binary assumptions of the model. That at least makes us pay in the coin of data for an increase in certainty.

It is a big step down from such imperfect scientific inference to the approximate syllogistic reasoning of the law. There the disputant insists that similar premises must lead to similar conclusions. But this similarity involves its own approximate pattern matching of inherently vague patterns of causal conduct or hidden mental states such as intent or foreseeability. The judge's final ruling of "granted" or "denied" resolves the issue in practice. But it is technically a non sequitir. The product of any numbers between zero and one is again always less than one. So the confidence of the conclusion can only fall as the steps in the deductive chain increase. The clang of the gavel is no substitute for proof.

Such approximate reasoning may be as close as we can come to a Q. E. D. moment when using natural language. The everyday arguments that buzz in our brains hit far humbler logical highs. That is precisely why we all need to prove something at least once — to experience at least one true Q. E. D. moment. Those rare but god-like tastes of ideal certainty can help keep us from mistaking it for anything else.

The phrase "correlation is not a cause" (CINAC) may be familiar to every scientist but has not found its way into everyday language, even though critical thinking and scientific understanding would improve if more people had this simple reminder in their mental toolkit.

One reason for this lack is that CINAC can be surprisingly difficult to grasp. I learned just how difficult when teaching experimental design to nurses, physiotherapists and other assorted groups. They usually understood my favourite example: imagine you are watching at a railway station. More and more people arrive until the platform is crowded, and then — hey presto — along comes a train. Did the people cause the train to arrive (A causes B)? Did the train cause the people to arrive (B causes A)? No, they both depended on a railway timetable (C caused both A and B).

I soon discovered that this understanding tended to slip away again and again, until I began a new regime, and started every lecture with an invented example to get them thinking.

"Right", I might say "Suppose it's been discovered (I don't mean it's true) that children who eat more tomato ketchup do worse in their exams. Why could this be?" They would argue that it wasn't true (I'd explain the point of thought experiments again). "But there'd be health warnings on ketchup if it's poisonous" (Just pretend it's true for now please) and then they'd start using their imaginations.

"There's something in the ketchup that slows down nerves", "Eating ketchup makes you watch more telly instead of doing your homework", "Eating more ketchup means eating more chips and that makes you fat and lazy". Yes, yes, probably wrong but great examples of A causes B — go on. And so to "Stupid people have different taste buds and don't like ketchup", "Maybe if you don't pass your exams your Mum gives you ketchup". And finally " "Poorer people eat more junk food and do less well at school".

Next week: "Suppose we find that the more often people consult astrologers or psychics the longer they live." "But it can't be true — astrology's bunkum" (Sigh … just pretend it's true for now please.) OK. "Astrologers have a special psychic energy that they radiate to their clients", "Knowing the future means you can avoid dying", "Understanding your horoscope makes you happier and healthier" Yes, yes, excellent ideas, go on. "The older people get the more often they go to psychics", "Being healthy makes you more spiritual and so you seek out spiritual guidance". Yes, yes, keep going, all testable ideas, and finally "Women go to psychics more often and also live longer than men."

The point is that once you greet any new correlation with "CINAC" your imagination is let loose. Once you listen to every new science story Cinacally (which conveniently sounds like "cynically") you find yourself thinking: OK, if A doesn't cause B, could B cause A? Could something else cause them both or could they both be the same thing even though they don't appear to be? What's going on? Can I imagine other possibilities? Could I test them? Could I find out which is true? Then you can be critical of the science stories you hear. Then you are thinking like a scientist.

Stories of health scares and psychic claims may get people's attention but understanding that a correlation is not a cause could raise levels of debate over some of today's most pressing scientific issues. For example, we know that global temperature rise correlates with increasing levels of atmospheric carbon dioxide but why? Thinking Cinacally means asking which variable causes which or whether something else causes both, with important consequences for social action and the future of life on earth.

Some say that the greatest mystery facing science is the nature of consciousness. We seem to be independent selves having consciousness and free will, and yet the more we understand how the brain works, the less room there seems to be for consciousness to do anything. A popular way of trying to solve the mystery is the hunt for the "neural correlates of consciousness". For example, we know that brain activity in parts of the motor cortex and frontal lobes correlates with conscious decisions to act. But do our conscious decisions cause the brain activity, does the brain activity cause our decisions, or are both caused by something else?

The fourth possibility is that brain activity and conscious experiences are really the same thing, just as light turned out not to be caused by electromagnetic radiation but to be electromagnetic radiation, or heat turned out to be the movement of molecules in a fluid. At the moment we have no inkling of how consciousness could be brain activity but my guess is that it will turn out that way. Once we clear away some of our delusions about the nature of our own minds, we may finally see why there is no deep mystery and our conscious experiences simply are what is going on inside our brains. If this is right then there are no neural correlates of consciousness. But whether it is or not, remembering CINAC and working slowly from correlations to causes is likely to be how this mystery is finally solved.

As someone who just spent a term teaching freshman introductory biology, and will be doing it again in the coming months, I have to say that the first thing that leapt to my mind as an essential skill everyone should have was algebra. And elementary probability and statistics. That sure would make my life easier, anyway — there's something terribly depressing about seeing bright students tripped up by a basic math skill that they should have mastered in grade school.

But that isn't enough. Elementary math skills are an essential tool that we ought to be able to take for granted in a scientific and technological society. What idea should people grasp to better understand their place in the universe?

I'm going to recommend the mediocrity principle. It's fundamental to science, and it's also one of the most contentious, difficult concepts for many people to grasp — and opposition to the mediocrity principle is one of the major linchpins of religion and creationism and jingoism and failed social policies. There are a lot of cognitive ills that would be neatly wrapped up and easily disposed of if only everyone understood this one simple idea.

The mediocrity principle simply states that you aren't special. The universe does not revolve around you, this planet isn't privileged in any unique way, your country is not the perfect product of divine destiny, your existence isn't the product of directed, intentional fate, and that tuna sandwich you had for lunch was not plotting to give you indigestion. Most of what happens in the world is just a consequence of natural, universal laws — laws that apply everywhere and to everything, with no special exemptions or amplifications for your benefit — given variety by the input of chance. Everything that you as a human being consider cosmically important is an accident. The rules of inheritance and the nature of biology meant that when your parents had a baby, it was anatomically human and mostly fully functional physiologically, but the unique combination of traits that make you male or female, tall or short, brown-eyed or blue-eyed were the result of a chance shuffle of genetic attributes during meiosis, a few random mutations, and the luck of the draw in the grand sperm race at fertilization.

Don't feel bad about that, though, it's not just you. The stars themselves form as a result of the properties of atoms, the specific features of each star set by the chance distribution of ripples of condensation through clouds of dust and gas. Our sun wasn't required to be where it is, with the luminosity it has — it just happens to be there, and our existence follows from this opportunity. Our species itself is partly shaped by the force of our environment through selection, and partly by fluctuations of chance. If humans had gone extinct 100,000 years ago, the world would go on turning, life would go on thriving, and some other species would be prospering in our place — and most likely not by following the same intelligence-driven technological path we did.

And if you understand the mediocrity principle, that's OK.

The reason this is so essential to science is that it's the beginning of understanding how we came to be here and how everything works. We look for general principles that apply to the universe as a whole first, and those explain much of the story; and then we look for the quirks and exceptions that led to the details. It's a strategy that succeeds and is useful in gaining a deeper knowledge. Starting with a presumption that a subject of interest represents a violation of the properties of the universe, that it was poofed uniquely into existence with a specific purpose, and that the conditions of its existence can no longer apply, means that you have leapt to an unfounded and unusual explanation with no legitimate reason. What the mediocrity principle tells us is that our state is not the product of intent, that the universe lacks both malice and benevolence, but that everything does follow rules — and that grasping those rules should be the goal of science.

I invite you to pay attention to anything — the sight of this text, the sensation of breathing, the feeling of your body resting against your chair — for a mere sixty seconds without getting distracted by discursive thought. It sounds simple enough: Just pay attention. The truth, however, is that you will find the task impossible. If the lives of your children depended on it, you could not focus on anything — even the feeling of a knife at your throat — for more than a few seconds, before your awareness would be submerged again by the flow of thought. This forced plunge into unreality is a problem. In fact, it is the problem from which every other problem in human life appears to be made.

I am by no means denying the importance of thinking. Linguistic thought is indispensable to us. It is the basis for planning, explicit learning, moral reasoning, and many other capacities that make us human. Thinking is the substance of every social relationship and cultural institution we have. It is also the foundation of science. But our habitual identification with the flow of thought — that is, our failure to recognize thoughts as thoughts, as transient appearances in consciousness — is a primary source of human suffering and confusion.

Our relationship to our own thinking is strange to the point of paradox, in fact. When we see a person walking down the street talking to himself, we generally assume that he is mentally ill. But we all talk to ourselves continuously — we just have the good sense to keep our mouths shut. Our lives in the present can scarcely be glimpsed through the veil of our discursivity: We tell ourselves what just happened, what almost happened, what should have happened, and what might yet happen. We ceaselessly reiterate our hopes and fears about the future. Rather than simply exist as ourselves, we seem to presume a relationship with ourselves. It's as though we are having a conversation with an imaginary friend possessed of infinite patience. Who are we talking to?

While most of us go through life feeling that we are the thinker of our thoughts and the experiencer of our experience, from the perspective of science we know that this is a distorted view. There is no discrete self or ego lurking like a minotaur in the labyrinth of the brain. There is no region of cortex or pathway of neural processing that occupies a privileged position with respect to our personhood. There is no unchanging "center of narrative gravity" (to use Daniel Dennett's phrase). In subjective terms, however, there seems to be one — to most of us, most of the time.

Our contemplative traditions (Hindu, Buddhist, Christian, Muslim, Jewish, etc.) also suggest, to varying degrees and with greater or lesser precision, that we live in the grip of a cognitive illusion. But the alternative to our captivity is almost always viewed through the lens of religious dogma. A Christian will recite the Lord's Prayer continuously over a weekend, experience a profound sense of clarity and peace, and judge this mental state to be fully corroborative of the doctrine of Christianity; A Hindu will spend an evening singing devotional songs to Krishna, feel suddenly free of his conventional sense of self, and conclude that his chosen deity has showered him with grace; a Sufi will spend hours whirling in circles, pierce the veil of thought for a time, and believe that he has established a direct connection to Allah.

The universality of these phenomena refutes the sectarian claims of any one religion. And, given that contemplatives generally present their experiences of self-transcendence as inseparable from their associated theology, mythology, and metaphysics, it is no surprise that scientists and nonbelievers tend to view their reports as the product of disordered minds, or as exaggerated accounts of far more common mental states — like scientific awe, aesthetic enjoyment, artistic inspiration, etc.

Our religions are clearly false, even if certain classically religious experiences are worth having. If we want to actually understand the mind, and overcome some of the most dangerous and enduring sources of conflict in our world, we must begin thinking about the full spectrum of human experience in the context of science.

But we must first realize that we are lost in thought.

Paradoxes arise when one or more convincing truths contradiction either each other, clash with other convincing truths, or violate unshakeable intuitions. They are frustrating, yet beguiling. Many see virtue in avoiding, glossing over, or dismissing them. Instead we should seek them out, if we find one sharpen it, push it to the extreme, and hope that the resolution will reveal itself, for with that resolution will invariably come a dose of Truth.

History is replete with examples, and with failed opportunities. One of my favorites is Olber's paradox. Suppose the universe were filled with an eternal roughly uniform distribution of shining stars. Faraway stars would look dim because they take up a tiny angle on the sky; but within that angle they are as bright as the Sun's surface. Yet in an eternal and infinite (or finite but unbounded) space, every direction would lie within the angle taken up by some star. The sky would be alight like the surface of the sun. Thus, a simple glance at the dark night sky reveals that the universe must be dynamic: expanding, or evolving. Astronomers grappled with this paradox for several centuries, devising unworkable schemes for its resolution. Despite at least one correct view (by Edgar Allen Poe!), the implications never really permeated even the small community of people thinking about the fundamental structure of the universe. And so it was that Einstein, when he went to apply his new theory to the universe, sought an eternal and static model that could never make sense, introduced a term into his equations which he called his greatest blunder, and failed to invent the big-bang theory of cosmology.

Nature appears to contradict itself with the utmost rarity, and so a paradox can be opportunity for us to lay bare our cherished assumptions, and discover which of them we must let go. But a good paradox can take us farther, to reveal that the not just the assumptions but the very modes of thinking we employed in creating the paradox must be replaced. Particles and waves? Not truth, just convenient models. The same number of integers as perfect squares of integers? Not crazy, though you might be if you invent cardinality. This sentence is false. And so, says Godel, might be the foundations of any formal system that can refer to itself. The list goes on.

What next? I've got a few big ones I'm wrestling with. How can thermodynamics' second law arise unless cosmological initial conditions are fine-tuned in a way we would never accept in any other theory or explanation of anything? How do we do science if the universe is infinite, and every outcome of every experiment occurs infinitely many times?

What impossibility is nagging at you?

The Oracle of Delphi famously pronounced Socrates to be "the most intelligent man in the world because he knew that he knew nothing". Over 2000 years later the physicist-turned-historian Jacob Bronowski would emphasize — in the last episode of his landmark 1970s television series the "Ascent of Man" — the danger of our all-too-human conceit of thinking we know something. What Socrates knew and what Bronowski had come to appreciate is that knowledge — true knowledge — is difficult, maybe even impossible, to come buy, it is prone to misunderstanding and counterfactuals, and most importantly it can never be acquired with exact precision, there will always be some element of doubt about anything we come to "know"' from our observations of the world.

What is it that adds doubt to our knowledge? It is not just the complexity of life: uncertainty is built in to anything we measure. No matter how well you can measure something, you might be wrong by up to ½ of the smallest unit you can discern.

If you tell me I am 6 feet tall, and you can measure to the nearest inch, I might actually be 5' 11 and ½" or 6' and ½" and you (and I) won't know the difference. If something is really small you won't even be able to measure it, and if it is really really small a light microscope (and thus your eye, both of which can only see objects larger than the shortest wavelength of visible light) won't even know it is there. What if you measure something repeatedly?

This helps, but consider the plight of those charged with international standards of weights and measures. There is a lump of metal stored under a glass case in Sèvres, France. It is, by the decree of Le Système International d'Unités, the definition a kilogram. How much does it weigh? Well, by definition whatever it weighs is a kilogram. But the fascinating thing is that it has never weighed exactly the same twice. On those days it weighs less than a kilogram you are not getting such a good deal at the grocery store. On other days you are.

The often blithe way in which scientific "findings" are reported by the popular press can mask just how difficult it is to acquire reliable knowledge. Height and weight are — as far as we know — single dimensions. Consider then how much more difficult it is to measure something like intelligence, the risk of getting cancer from eating too much meat, whether cannibas should be legalized, whether the climate is warming and why, what a "shorthand abstraction" or even "science" is, the risk of developing psychosis from drug abuse, the best way to lose weight, whether it is better to force people receiving state benefits to work, whether prisons work, how to quit smoking, whether a glass of wine every day is good for you, whether it will hurt your children's eyes to use 3D glasses, or even just the best way to brush your teeth. In each case, what was actually measured, or who was measured, who were they compared to, for how long, are they like you and me, were there other factors that could explain the outcome?

The elusive nature of knowledge should remind us to be humble when interpreting it and acting on it, and this should grant us both a tolerance and skepticism towards others and their interpretations:knowledge should always be treated as a hypothesis.

It has only just recently emerged that Bronowski himself was involved in the Second World War project to design nuclear weapons — vicious projectiles of death that don't discriminate between good guys and bad guys. Maybe Bronowski's later humility was borne of this realization — that our views can be wrong and they can have consequences for others' lives.

Eager detractors of science as a way of understanding the world will jump on these ideas with glee, waving them about as proof that "nothing is real" and that science and its outputs are as much a human construct as art or religion. This is facile, ignorant and naïve.

Measurement and the "science" or theories it spawns must be treated with humility precisely because they are powerful ways of understanding and manipulating the world. Their observations can be replicated — even if imperfectly — and others can agree on how to make the measurements on which they depend, be they of intelligence, the mass of the Higgs boson, poverty, the speed at which proteins can fold into their three dimensional structures, or how big gorillas are.

No other system for acquiring knowledge even comes close to science, but this is precisely why we must treat its conclusions with humility. Einstein knew this when he said "all our science measured against reality is primitive and childlike" and yet he added "it is the most precious thing we have".

At every level in the vast and dynamic world of living things lies diversity.  From biomes to biomarkers, the complex array of solutions to the most basic problems regarding survival in a given environment afforded to us by nature is riveting. In the world of humans alone, diversity is apparent in the genome, in the brain and in our behavior. 

The mark of multiple populations lies in the fabric of our DNA. The signature of selfhood in the brain holds dual frames, one for thinking about one's self as absolute, the other in context of others. From this biological diversity in humans arises cultural diversity directly observable in nearly every aspect of how people think, feel and behavior. From classrooms to conventions across continents, the range and scope of human activities is stunning. 

Recent centuries have seen the scientific debate regarding the nature of human nature cast as a dichotomy between diversity on the one hand and universalism on the other. Yet a seemingly paradoxical, but tractable, scientific concept that may enhance our cognitive toolkit over time is the simple notion that diversity is universal.

To improve everybody's cognitive toolkit, the required scientific concept has to be applicable to all humans. It needs to make a difference to us as a species, or, more to the point I am going to make, as a key factor in defining our collective role. This concept must impact the way we perceive who we are and why we are here. Hopefully, it will redefine the way we live our lives and plan for our collective future. This concept must make it clear that we matter.

A concept that might grow into this life-redefining powerhouse is the notion that we, humans in a rare planet, are unique and uniquely important. But what of Copernicanism — the notion that the more we learn about the universe the less important we become? I will argue that modern science, traditionally considered guilty of reducing our existence to a pointless accident in an indifferent universe, is actually saying the opposite. While it does say that we are an accident in an indifferent universe, it also says that we are a rare accident and thus not pointless.

But wait! Isn't it the opposite? Shouldn't we expect life to be common in the cosmos and us to be just one of many creatures out there? After all, as we discover more and more worlds circling other suns, the so-called exoplanets, we find an amazing array of possibilities. Also, given that the laws of physics and chemistry are the same across the universe, we should expect life to be ubiquitous: if it happened here, it must've happened in many other places. So why am I claiming that we are unique?

There is an enormous difference between life and intelligent life. By intelligent life I don't mean clever crows or dolphins, but minds capable of self-awareness and the ability to develop advanced technologies, that is, not just use what is at hand but transform materials into new devices that can perform a multitude of tasks. Keeping this definition in mind, I agree that single-celled life, although dependent on a multitude of physical and biochemical factors, shouldn't be an exclusive property of our planet. First, because life on Earth appeared almost as quickly as it could, no more than a few hundred million years after things quieted down enough; second, due to the existence of extremophiles, life forms capable of surviving in extreme conditions (very hot or cold, very acidic or/and radioactive, no oxygen, etc.), showing that life is very resilient and spreads into every niche that it can.

However, the existence of single-celled organisms doesn't necessarily lead to that of multicellular ones, much less to that of intelligent multicellular ones. Life is in the business of surviving the best way it can in a given environment. If the environment changes, those creatures that can survive under the new conditions will. Nothing in this dynamics supports the notion that once there is life all you have to do is wait long enough and puff, there pops a clever creature. (This smells of biological teleology, the concept that life's purpose is to create intelligent life, a notion that seduces many people for obvious reasons: it makes us the special outcome of some grand plan.) The history of life on Earth doesn't support this evolution toward intelligence: there have been many transitions toward greater complexity, none of them obvious: prokaryotic to eukaryotic unicellular creatures (and nothing more for 3 billion years!), unicellular to multicellular, sexual reproduction, mammals, intelligent mammals, edge.org...Play the movie differently, and we wouldn't be here.

As we look at planet Earth and the factors that came into play for us to be here, we quickly realize that our planet is very special. Here is a short list: the long-term existence of a protective and oxygen-rich atmosphere; Earth's axial tilt, stabilized by a single large moon; the ozone layer and the magnetic field that jointly protect surface creatures from lethal cosmic radiation; plate tectonics that regulate the levels of carbon dioxide and keep the global temperature stable; the fact that our sun is a smallish, fairly stable star not too prone to releasing huge plasma burps. Consequently, it's rather naive to expect life — at the complexity level that exists here — to be ubiquitous across the universe.

A further point: even if there is intelligent life elsewhere and, of course, we can't rule that out (science is much better at finding things that exist than at ruling out things that don't), it will be so remote that for all practical purposes we are alone. Even if SETI finds evidence of other cosmic intelligences, we are not going to initiate a very intense collaboration. And if we are alone, and alone have the awareness of what it means to be alive and of the importance of remaining alive, we gain a new kind of cosmic centrality, very different — and much more meaningful — from the religiously-inspired one of pre-Copernican days, when Earth was the center of Creation: we matter because we are rare and we know it.

The joint realization that we live in a remarkable cosmic cocoon and that we are able to create languages and rocket ships in an otherwise apparently dumb universe ought to be transformative. Until we find other self-aware intelligences, we are how the universe thinks. We might as well start enjoying each other's company.

We are powerfully influenced by irrational processes such as unconscious priming, conformity, groupthink, and self-serving biases. These affect the most trivial aspects of our lives, such as how quickly we walk down a city street, and the most important, such as who we choose to marry. The political and moral realms are particularly vulnerable to such influences. While many of us would like to think that our views on climate change or torture or foreign policy are the result of rational deliberation, we are more affected than we would like to admit by considerations that have nothing to do with reason. 

But this is not inevitable. Consider science. Plainly, scientists are human and possess the standard slate of biases and prejudices and mindbugs. This is what skeptics emphasize when they say that science is "just another means of knowing" or "just like religion". But science also includes procedures — such as replicable experiments and open debate — that cultivate the capacity for human reason. Scientists can reject common wisdom, they can be persuaded by data and argument to change their minds. It is through these procedures that we have discovered extraordinary facts about the world, such as the structure of matter and the evolutionary relationship between monkey and man.

The cultivation of reason isn't unique to science; other disciplines such as mathematics and philosophy possess it as well. But it is absent in much of the rest of life. So I admit to twisting the question a bit: The concept that people need to add to their toolkit isn't a scientific discovery; it is science itself. Wouldn't the world be better off if, as we struggle with moral and political and social problems, we adopted those procedures that make science so successful?

We are shockingly ignorant of the causes of our own behavior. The explanations that we provide are sometimes wholly fabricated, and certainly never complete. Yet, that is not how it feels. Instead it feels like we know exactly what we're doing and why. This is confabulation: Guessing at plausible explanations for our behavior, and then regarding those guesses as introspective certainties. Every year psychologists use dramatic examples to entertain their undergraduate audiences. Confabulation is funny, but there is a serious side, too. Understanding it can help us act better and think better in everyday life.

Some of the most famous examples of confabulation come "split-brain" patients, whose left and right brain hemispheres have been surgically disconnected for medical treatment. Neuroscientists have devised clever experiments in which information is provided to the right hemisphere (for instance, pictures of naked people), causing a change in behavior (embarrassed giggling). Split-brain individuals are then asked to explain their behavior verbally, which relies on the left hemisphere. Realizing that their body is laughing, but unaware of the nude images, the left hemisphere will confabulate an excuse for the body's behavior ("I keep laughing because you ask such funny questions, Doc!").

Wholesale confabulations in neurological patients can be jaw-dropping, but in part that is because they do not reflect ordinary experience. Most of the behaviors that you or I perform are not induced by crafty neuroscientists planting subliminal suggestions in our right hemisphere. When we are outside the laboratory — and when our brains have all the usual connections — most behaviors that we perform are the product of some combination of deliberate thinking and automatic action.

Ironically, that is exactly what makes confabulation so dangerous. If we routinely got the explanation for our behavior totally wrong — as completely wrong as split-brain patients sometimes do — we would probably be much more aware that there are pervasive, unseen influences on our behavior. The problem is that we get all of our explanations partly right, correctly identifying the conscious and deliberate causes of our behavior. Unfortunately, we mistake "party right" for "completely right", and thereby fail to recognize the equal influence of the unconscious, or to guard against it.

A choice of job, for instance, depends partly on careful deliberation about career interests, location, income, and hours. At the same time, research reveals that choice to be influenced by a host of factors of which we are unaware. People named Dennis or Denise are more likely to be dentists, while people named Virginia are more likely to locate to (you guessed it) Virginia. Less endearingly, research suggests that on average people will take a job with fewer benefits, a longer commute and a smaller income if it allows them to avoid having a female boss. Surely most people do not want to choose a job based on the sound of their name, nor do they want to sacrifice job quality in order to perpetuate old gender norms. Indeed, most people have no awareness that these factors influence their own choices. When you ask them why they took the job, they are likely to reference their conscious thought processes: "I've always loved making ravioli, the Lira is on the rebound and Rome is for lovers…"  That answer is partly right, but it is also partly wrong, because it misses the deep reach of automatic processes on human behavior.

People make harsher moral judgments in foul-smelling rooms, reflecting the role of disgust as a moral emotion. Women are less likely to call their fathers (but equally likely to call their mothers) during the fertile phase of their menstrual cycle, reflecting a means of incest avoidance. Students indicate greater political conservatism when polled near a hand-sanitizing station during a flu epidemic, reflecting the influence of a threatening environment on ideology. They also indicate a closer bond to their mother when holding hot coffee versus iced coffee, reflecting the metaphor of a "warm" relationship.

Automatic behaviors can be remarkably organized, and even goal-driven. For example, research shows that people tend to cheat just as much as they can without realizing that they are cheating. This is a remarkable phenomenon: Part of you is deciding how much to cheat, calibrated at just the level that keeps another part of you from realizing it.

One of the ways that people pull off this trick is with innocent confabulations: When self-grading an exam, students think, "Oh, I was going to circle e, I really knew that answer!" This isn't a lie, any more than it's a lie to say you have always loved your mother (latte in hand), but don't have time to call your dad during this busy time of the month. These are just incomplete explanations, confabulations that reflect our conscious thoughts while ignoring the unconscious ones.

This brings me to the central point, the part that makes confabulation an important concept in ordinary life and not just a trick pony for college lectures. Perhaps you have noticed that people have an easier time sniffing out unseemly motivations for other's behavior than recognizing the same motivations for their own behavior. Others avoided female bosses (sexist) and inflated their grades (cheaters), while we chose Rome and really meant to say that Anne was the third Brontë. There is a double tragedy in this double standard.

First, we jump to the conclusion that others' behaviors reflect their bad motives and poor judgment, attributing conscious choice to behaviors that may have been influenced unconsciously. Second, we assume that our own choices were guided solely by the conscious explanations that we conjure, and reject or ignore the possibility of our own unconscious biases.

By understanding confabulation we can begin to remedy both faults. We can hold others responsible for their behavior without necessarily impugning their conscious motivations. And, we can hold ourselves more responsible by inspecting our own behavior for its unconscious influences, as unseen as they are unwanted.

It's been over 150 years since Charles Darwin published the Origin of Species, but we still have trouble appreciating the simple, brilliant insight at its core. That is, life's diversity does not exist because it is necessary for living things. Birds did not get wings so that they could fly. We do not have eyes so that we can read. Instead, eyes, wings, and the rest of life's wonder has come about as a side effect of life itself. Living things struggle to survive, they reproduce, and they don't do a perfect job of replicating themselves. Evolution spins off of that loop, like heat coming off an engine. We're so used to seeing agents behind everything that we struggle to recognize life as a side effect. I think everyone would do well do overcome that urge to see agents where there are none. It would even help us to understand why we are so eager to see agents in the first place.

We could become far more intelligent than we are by adding to our stock of concepts, and by forcing ourselves to use them even when we don't like what they are telling us. This will be nearly always, because they generally tell us that our self-evidently superior selves and ingroups are error-besotted. We all start from radical ignorance in a world that is endlessly strange, vast, complex, intricate, and surprising. Deliverance from ignorance lies in good concepts — inference fountains that geyser out insights that organize and increase the scope of our understanding. We are drawn to them by the fascination of the discoveries they afford, but resist using them well and freely because they would reveal too many of our apparent achievements to be embarrassing or tragic failures. Those of us who are non-mythical lack the spine that Oedipus had — the obsidian resolve that drove him to piece together shattering realizations despite portents warning him off. Because of our weakness, "to see what is in front of one's nose needs a constant struggle" as Orwell says. So why struggle? Better instead to have one's nose and what lies beyond shift out of focus — to make oneself hysterically blind as convenience dictates, rather than to risk ending up like Oedipus, literally blinding oneself in horror at the harvest of an exhausting, successful struggle to discover what is true.

Alternatively, even modest individual-level improvements in our conceptual toolkit can have transformative effects on our collective intelligence, promoting incandescent intellectual chain reactions among multitudes of interacting individuals. If this promise of intelligence-amplification through conceptual tools seems like hyperbole, consider that the least inspired modern engineer, equipped with the conceptual tools of calculus, can understand, plan and build things far beyond what da Vinci or the mathematics-revering Plato could have achieved without it. We owe a lot to the infinitesimal, Newton's counterintuitive conceptual hack — something greater than zero but less than any finite magnitude. Far simpler conceptual innovations than calculus have had even more far reaching effects — the experiment (a danger to authority), zero, entropy, Boyle's atom, mathematical proof, natural selection, randomness, particulate inheritance, Dalton's element, distribution, formal logic, culture, Shannon's definition of information, the quantum…

Here are three simple conceptual tools that might help us see in front of our noses: nexus causality, moral warfare, and misattribution arbitrage. Causality itself is an evolved conceptual tool that simplifies, schematizes, and focuses our representation of situations. This cognitive machinery guides us to think in terms of the cause — of an outcome having a single cause. Yet for enlarged understanding, it is more accurate to represent outcomes as caused by an intersection or nexus of factors (including the absence of precluding conditions). InWar and Peace, Tolstoy asks "When an apple ripens and falls, why does it fall? Because of its attraction to the earth, because its stem withers, because it is dried by the sun, because it grows heavier, because the wind shakes it….?" — with little effort any modern scientist could extend Tolstoy's list endlessly. We evolved, however, as cognitively improvisational tool-users, dependent on identifying actions we could take that lead to immediate payoffs. So, our minds evolved to represent situations in a way that highlighted the element in the nexus that we could manipulate to bring about a favored outcome. Elements in the situation that remained stable and that we could not change (like gravity or human nature) were left out of our representation of causes. Similarly, variable factors in the nexus (like the wind blowing) that we could not control, but that predicted an outcome (the apple falling), were also useful to represent as causes, in order to prepare ourselves to exploit opportunities or avoid dangers. So the reality of the causal nexus is cognitively ignored in favor of the cartoon of single causes. While useful for a forager, this machinery impoverishes our scientific understanding, rendering discussions (whether elite, scientific, or public) of the "causes" — of cancer, war, violence, mental disorders, infidelity, unemployment, climate, poverty, and so on — ridiculous.

Similarly, as players of evolved social games, we are designed to represent others' behavior and associated outcomes as caused by free will (by intentions). That is, we evolved to view "man" as Aristotle put it, as "the originator of his own actions." Given an outcome we dislike, we ignore the nexus, and trace "the" causal chain back to a person. We typically represent the backward chain as ending in — and the outcome as originating in — the person. Locating the "cause" (blame) in one or more persons allows us to punitively motivate others to avoid causing outcomes we don't like (or to incentivize outcomes we do like). More despicably, if something happens that many regard as a bad outcome, this gives us the opportunity to sift through the causal nexus for the one thread that colorably leads back to our rivals (where the blame obviously lies). Lamentably, much of our species' moral psychology evolved for moral warfare, a ruthless zero-sum game. Offensive play typically involves recruiting others to disadvantage or eliminate our rivals by publically sourcing them as the cause of bad outcomes. Defensive play involves giving our rivals no ammunition to mobilize others against us.

The moral game of blame attribution is only one subtype of misattribution arbitrage. For example, epidemiologists estimate that it was not until 1905 that you were better off going to a physician. (Semelweiss noticed that doctors doubled the mortality rate of mothers at delivery). For thousands of years, the role of the physician pre-existed its rational function, so why were there physicians? Economists, forecasters, and professional portfolio managers typically do no better than chance, yet command immense salaries for their services. Food prices are driven up to starvation levels in underdeveloped countries, based on climate models that cannot successfully retrodict known climate history. Liability lawyers win huge sums for plaintiffs who get diseases at no higher rates than others not exposed to "the" supposed cause. What is going on? The complexity and noise permeating any real causal nexus generates a fog of uncertainty. Slight biases in causal attribution, or in blameworthiness (e.g., sins of commission are worse than sins of omission) allow a stable niche for extracting undeserved credit or targeting undeserved blame. If the patient recovers, it was due to my heroic efforts; if not, the underlying disease was too severe. If it weren't for my macroeconomic policy, the economy would be even worse. The abandonment of moral warfare, and a wider appreciation of nexus causality and misattribution arbitrage would help us all shed at least some of the destructive delusions that cost humanity so much.

From the dawn of civilisation until 2003, Eric Schmidt is fond of saying, humankind generated five exabytes of data. Now we produce five exabytes every two days — and the pace is accelerating. In our post-privacy world of pervasive social-media sharing, GPS tracking, cellphone-tower triangulation, wireless sensor monitoring, browser-cookie targeting, face-recognition detecting, consumer-intention profiling, and endless other means by which our personal presence is logged in databases far beyond our reach, citizens are largely failing to benefit from the power of all this data to help them make smarter decisions. It's time to reclaim the concept of data mining from the marketing industry's microtargeting of consumers, the credit-card companies' anti-fraud profiling, the intrusive surveillance of state-sponsored Total Information Awareness. We need to think more about mining our own output to extract patterns that turn our raw personal datastream into predictive, actionable information. All of us would benefit if the idea of personal data mining were to enter popular discourse.

Microsoft saw the potential back in September 2006, when it filed United States Patent application number 20,080,082,393 for a system of "personal data mining". Having been fed personal data provided by users themselves or gathered by third parties, the technology would then analyse it to "enable identification of opportunities and/or provisioning of recommendations to increase user productivity and/or improve quality of life". You can decide for yourself whether you trust Redmond with your lifelog, but it's hard to fault the premise: the personal data mine, the patent states, would be a way "to identify relevant information that otherwise would likely remain undiscovered".

Both I as a citizen and society as a whole would gain if individuals' personal datastreams could be mined to extract patterns upon which we could act. Such mining would turn my raw data into predictive information that can anticipate my mood and improve my efficiency, make me healthier and more emotionally intuitive, reveal my scholastic weaknesses and my creative strengths. I want to find the hidden meanings, the unexpected correlations that reveal trends and risk factors of which I had been unaware. In an era of oversharing, we need to think more about data-driven self-discovery.

A small but fast-growing self-tracking movement is already showing the potential of such thinking, inspired by Kevin Kelly's quantified self and Gary Wolf's data-driven life. With its mobile sensors and apps and visualisations, this movement is tracking and measuring exercise, sleep, alertness, productivity, pharmaceutical responses, DNA, heartbeat, diet, financial expenditure — and then sharing and displaying its findings for greater collective understanding. It is using its tools for clustering, classifying and discovering rules in raw data, but mostly is simply quantifying that data to extract signals — information — from the noise.

The cumulative rewards of such thinking will be altruistic rather than narcissistic, whether in pooling personal data for greater scientific understanding (23andMe) or in propagating user-submitted data to motivate behaviour change in others (Traineo). Indeed, as the work of Daniel Kahneman, Daniel Gilbert, and Christakis and Fowler demonstrate so powerfully, accurate individual-level data-tracking is key to understanding how human happiness can be quantified, how our social networks affect our behaviour, how diseases spread through groups.

The data is already out there. We just need to encourage people to tap it, share it, and corral it into knowledge.

Depth is what you do not see immediately at the surface of things. Depth is what is below that surface: a body of water below the surface of a lake, the rich life of a soil below the dirt or the spectacular line of reasoning behind a simple statement.

Depth is a straightforward aspect of the physical world. Gravity stacks stuff and not everything can be at the top. Below there is more and you can dig for it.

Depth acquired a particular meaning with the rise of complexity science a quarter of a century ago: What is characteristic of something complex? Very orderly things like crystals are not complex. They are simple. Very messy things like a pile of litter are very difficult to describe: They hold a lot of information. Information is a measure of how difficult something is to describe. Disorder has a high information content and order has a low one. All the interesting stuff in life is in-between: Living creatures, thoughts and conversations. Not a lot of information, but neither a little. So information content does not lead us to what is interesting or complex. The marker is rather the information that is not there, but was somehow involved in creating the object of interest. The history of the object is more relevant than the object itself, if we want to pin-point what is interesting to us.

It is not the informational surface of the thing, but its informational depth that attracts our curiosity. It took a lot to bring it here, before our eyes. It is not what is there, but what used to be there, that matters. Depth is about that.

The concept of depth in complexity science was expressed in different ways: You could talk about the actual amount of physical information that was involved in bringing about something — the thermodynamic depth — or the amount of computation it took to arrive at a result— the logical depth. Both express the notion that the process behind is more important than the eventual product.

This idea can also be applied to human communication.

When you say "yes" at a wedding it (hopefully) re-presents a huge amount of conversation, coexistence and fun that you have had with that other person present. And a lot of reflection upon it. There is not a lot of information in the "yes" (one bit, actually), but the statement has depth. Most conversational statements have some kind of depth: There is more than meets the ear, something that happened between the ears of the person talking — before a statement was made. When you understand the statement, the meaning of what is being said, you "dig it", you get the depth, what is below and behind. What is not said, but meant — the exformation content, information processed and thrown away before the actual production of explicit information.

2 + 2 = 4. This is a simple computation. The result, 4, hold less information than the problem, 2 + 2 (essentially because the problem could also have been 3 + 1 and yet the result would still be 4). Computation is wonderful as a method for throwing away information, getting rid of it. You do computations to ignore all the details, to get an overview, an abstraction, a result.

What you want is a way to distinguish between a very deep "yes" and a very shallow one: Did the guy actually think about what he said? Was the result 4 actually the result of a meaningful calculation? Is there in fact water below that surface? Does it have depth?

Most human interaction is about that question: Is this bluff or for real? Is there sincere depth in the affection? Does the result stem from intense analysis or is it just an estimate? Is there anything between the lines?

Signaling is all about this question: fake or depth? In biology the past few decades have seen the rise of studies of how animals prove to each other that there is depth behind the signal. The handicap principle of sexual selection is about a way to prove that you signal has depth: If a peacock has long, spectacular feathers it proves that it can survive its predators even though the fancy plumage represents a disadvantage, a handicap. Hence, the peahen can know that the individual displaying the huge tail is a strong one, or else it could not survive with that extreme tail.

Amongst humans you have what economists call costly signals: Ways to show that you have something of value. The phenomenon conspicuous consumption was observed by sociologist Thorstein Veblen already in 1899: If you want to prove that you have a lot of money, you have to waste them. That is: Use them in a way that is absurd and idiotic, because only the rich guy can do so. But do it conspicuously, so that other people will know. Waste is a costly signal of the depth of pile of money. Poor people have to use their money in functional way.

Handicaps, costly signals, intense eye contact and rhetorical gestures are all about proving that what seems so simple really has a lot of depth.

That is also the point with abstractions: We want them to be shorthand for a lot of information that was digested in the process leading to the use of the abstraction, but is not present when we use it. Such abstractions have depth. We love them. Other abstraction have no depth. They are shallow and just used to impress the other guy. They do not help us. We hate them.

Intellectual life is very much about the ability to distinguish between the shallow and the deep abstractions. You need to know if there is any depth before you make that headlong dive and jump into it.

The Game of Life is a cellular automaton, invented by the British mathematician John Horton Conway in 1970.

Many will already be acquainted with Conway's invention. For those aren't, the best way to familiarize oneself with it is to experiment with one of the many free implementations that can be found on the Internet (or better yet, if you have at least rudimentary programming skills, make one yourself).

Basically, there is a grid and each cell can be in either of two states: dead or alive. One starts by seeding the grid with some initial distribution of live cells. Then one lets the system evolve according to three simple rules.

Why is this interesting? Certainly, the Game of Life is not biologically realistic. It doesn't do anything useful. It isn't even really game in the ordinary sense of the word.

But it's a brilliant demonstration platform for several important concepts — a virtual 'philosophy of science laboratory'. (The philosopher Daniel Dennett has expressed the view that it should be incumbent on every philosophy student to be acquainted with it.) It gives us the microcosm, simple enough that we can easily understand how things are happening, yet with sufficient generative power to produce interesting phenomena.

By playing with the Game of Life for an hour, one can develop an intuitive understanding of the following concepts and ideas:

• Emergent complexity — How complex patterns can arise from very simple rules.

• Basic dynamics concepts — such as the distinction between laws of nature and initial conditions.

• Levels of explanation — One quickly notices patterns arising that can be efficiently described in higher-level terms (such as "gliders", a specific kind of pattern that crawls across the screen) but that are quite cumbersome to describe in the language of the basic physics upon which the patterns supervene (i.e., in terms of individual pixels being alive or dead)

• Supervenience — This leads one to think about the relation between different sciences in the real world… Does chemistry, likewise, supervene on physics? Biology on chemistry? The mind on the brain?

• Concept formation, and carving nature at its joints — how and why we recognize certain types of pattern and give them names. For instance, in the Game of Life one distinguishes "still lives", small local patterns that are stable and unchanging; "oscillators", local patterns that perpetually cycle through a fixed sequence of states; "spaceships", patterns that move across the grid (such as gliders); "guns", stationary patterns that send out an incessant stream of spaceships; and "puffer trains", patterns that move themselves across the grid leaving debris behind. As one begins to form these and other concepts, the chaos on the screen gradually becomes more comprehensible. Developing concepts that carve nature at its joints is the first crucial step towards understanding, not only in the Game of Life but in science and in ordinary life as well.

At a more advanced level, one discovers that the Game of Life is Turing complete. That is, it's possible to build a pattern that acts like a universal Turing machine. Thus, any computable function could be implemented in the Game of Life — including perhaps a function that describes a universe like the one we inhabit. It's also possible to build a universal constructor in the Game of Life, a pattern which can build many types of complex objects, including copies of itself. Nonetheless, it seems that the structures that evolve into Game of Life are different from the ones who find in the real world: Game of Life structures tend to be very fragile in the sense that changing a single cell will often cause them to dissolve. It is interesting to try to figure out exactly what it is about the rules of the Game of Life and the laws of physics that govern our own universe that accounts for these differences.

Conway's Life is perhaps best viewed not as a single shorthand abstraction, but rather as a generator of such abstractions. We get a whole bunch of useful abstractions — or at least a recipe for how to generate them — all for the price of one.

And this, in fact, points us to one especially useful shorthand abstraction: the strategy of Looking for Generators. We confront many problems. We can try to solve them one by one. But alternatively, we can try to create a generator that produces solutions to multiple problems.

Consider, for example, the challenge of advancing scientific understanding. We might make progress by directly tackling some random scientific problem. But perhaps we can make more progress by Looking for Generators and focusing our efforts on certain subsets of scientific problems, namely those whose solutions would do most to facilitate the discovery of many other solutions. On this approach, we would pay most attention to innovations in methodology that can be widely applied; and to the development of scientific instruments that can enable many new experiments; and to improvements in institutional processes, such as peer review, that can make many decisions about whom to hire, fund, and promote more closely reflecting true merit.

In the same vein, we would be extremely interested in developing effective biomedical cognitive enhancers and other ways of improving the human thinker — the brain being, after all, the generator par excellence.

Half a century ago, while advising a UK Metals company, Elliott Jaques had a deep and controversial insight. He noticed that workers at different levels of the company had very different time horizons. Line workers focused on tasks that could be completed in a single shift, while managers devoted their energies to tasks requiring six months or more to complete. Meanwhile, their CEO was pursuing goals realizable only over the span of several years.

After several decades of empirical study, Jaques concluded that just as humans differ in intelligence, we differ in our ability to handle time-dependent complexity. We all have a natural time horizon we are comfortable with, what Jaques called "Time span of discretion," or the length of the longest task an individual can successfully undertake. Jaques observed that organizations implicitly recognize this fact in everything from titles to salary: line workers are paid hourly, managers annually, and senior executives compensated with longer-term incentives such as stock options.

Jaques also noted that effective organizations were comprised of workers of differing time spans of discretion, each working at a level of natural comfort. If a worker's job was beyond their natural time span of discretion, they would fail. If it was less, they would be insufficiently challenged, and thus unhappy.

Time span of discretion is about achieving intents that have explicit time frames. And in Jaques model, one can rank discretionary capacity in a tiered system. Level 1 encompasses jobs such as sales associates or line workers handling routine tasks with a time horizon of up to three months. Levels 2 to 4 encompass various managerial positions with time horizons between one to five years. Level 5 crosses over to five to 10 years and is the domain of small company CEOs and large company executive vice presidents. Beyond Level 5, one enters the realm of statesmen and legendary business leaders comfortable with innate time horizons of 20 years (Level 6), 50 years (Level 7) or beyond. Level 8 is the realm of 100 year thinkers like Henry Ford, while Level 9 is the domain of the Einsteins, Gandhis, and Galileos, individuals capable of setting grand tasks into motion that continue centuries into the future.

Jaques' ideas enjoyed currency into the 1970s and then fell into eclipse, assailed as unfair stereotyping or worse, a totalitarian stratification evocative of Huxley's Brave New World. It is now time to reexamine Jaques theories and revive time span of discretion as a tool for understanding our social structures and matching them to the overwhelming challenges facing global society. Perhaps problems like climate change are intractable because we have a political system that elects Level 2 thinkers to Congress when we really need Level 5s in office. As such, Jaques ideas might help us realize that the old saying, "he who thinks longest wins" is only half the story, and that the society in which everyone explicitly thinks about tasks in the context of time will be the most effective.

Think back to the world 10 years ago. Google had just gotten started; Facebook and Twitter didn't exist. There were no smart phones, no one remotely conceived of the possibility of the 100,000 iPhone apps that exist today. The few large impact technologies (versus slightly incremental advances in technologies) that occurred in the past 10 years were black swan technologies. In his book, Nassim Taleb defines a Black Swan as an event of low probability, extreme impact, and with only retrospective predictability. Black swans can be positive or negative in their impact and are found in every sector. Still, the most pressing reason I believe "black swan technology" is a conceptual tool that should be added to everyone's cognitive toolkit today is simply because the challenges of climate change and energy production we face today are too big to be tackled by known solutions and safe bets.

I recall fifteen years ago when we were starting Juniper networks, there was absolutely no interest in replacing traditional telecommunications infrastructure (ATM was the mantra) with Internet protocols. After all, there were hundreds of billions of dollars invested in the legacy infrastructure, and it looked as immovable as today's energy infrastructure. Conventional wisdom would say to make incremental improvement to maximize the potential of the existing infrastructure. The fundamental flaw in the conventional wisdom is the failure to acknowledge the possibility of a black swan. Improbable is not unimportant. I believe the likely future is not a traditional econometric forecast but rather one of today's improbable becoming tomorrow's conventional wisdom! Who would be crazy enough t forecast in 2000 that by 2010 almost twice as many people in India would have access to cell phones than latrines? Wireless phones were once only for the very rich. With a black swan technology shot you need not be constrained with the limits of the current infrastructure, projections or market. You simply change the assumptions.

Many argue that since we already have some alternative energy technology today, we should quickly deploy it. They fail to see the potential of the Black Swan technology possibilities; they discount them because they mistake improbable for unimportant and cannot imagine the art of the possible which technology enables. I believe doing this alone runs the risk of spending vast amounts of money on outdated conventional wisdom. Even more importantly, it won't solve the problems we face. Any time focused on short-term, incremental solutions will only distract from working on the homeruns that could change the assumptions around energy and society's resources. While there is no shortage of existing technology providing incremental improvements today — whether today's thin film solar cells, wind turbines, or lithium ion batteries — even summed, they are simply irrelevant to the scale of our problems. They may even make interesting and sometimes large businesses, but will not impact the prevailing energy and resource issues at scale. For that we must look for and invest in quantum jumps in technology with low probability of success; we must create in Black Swan technologies. We must enable the multiplication of resources that only technology can do.

So what are these next generation technologies, these black swan technologies of energy? These are risky investments that stand a high chance of failure, but enable larger technological leaps that promise earthshaking impact if successful: making solar power cheaper than coal or viable without subsidies, economically making lighting and air conditioning 80 percent more efficient. Consider 100 percent more efficient vehicle engines, ultra-cheap energy storage, and countless other technological leaps that we can't yet imagine. It's unlikely that any single shot works, of course. But even 10 Google-like disruptions out of 10,000 shots will completely upend conventional wisdom, econometric forecasts, and, most importantly, our energy future.

To do so we must reinvent the infrastructure of society by harnessing and motivating bright minds with a whole new set of future assumptions, asking "what could possibly be?" rather than "what is." We need to create a dynamic environment of creative contention and collective brilliance that will yield innovative ideas from across disciplines to allow innovation to triumph. We must encourage a social ecosystem that encourages taking risks on innovation. Popularization of the concept of the "Black Swan Technology," is essential to incorporate the right mindset into the minds of entrepreneurs, policymakers, investors and the public: that anything (maybe even everything) is possible. If we harness and motivate these bright new minds with the right market signals and encouragement, a whole new set of future assumptions, unimaginable today, will be tomorrow's conventional wisdom.

I first heard the words "absence of evidence is not evidence of absence" as a first-year archaeology undergraduate. I now know it was part of Carl Sagan's retort against evidence from ignorance, but at the time the non-ascribed quote was part of the intellectual toolkit offered by my professor to help us make sense of the process of excavation.

Philosophically this is a challenging concept, but at an archaeological site all became clear in the painstaking tasks of digging, brushing and trowelling. The concept was useful to remind us, as we scrutinised what was there, to take note of the possibility of what was not there. What we were finding, observing, and lifting, were the material remains, the artifacts which had survived, usually as a result of their material or the good fortune of their deposition. There were barely recordable traces of what was there — the charcoal layer of a prehistoric hearth for example — and others recovered in the washing, or the lab, but this was still tangible evidence. What the concept brought home to us was the invisible traces, the material which had gone from our reference point in time, but which still had a bearing in the context.

It was powerful stuff which stirred my imagination. I looked for more examples outside philosophy. I learned about the great near-Eastern archaeologist, Sir Leonard Woolley who, when excavating the 3rd millennium BC Mesopotamian palace at Ur, modern day Iraq. There, he conjured up musical instruments from their absence. The evidence was the holes left in the excavation layers, the ghosts of wooden objects which had long since disappeared into time. He used this absence to advantage by making casts of the holes and realising the instruments as reproductions. It struck me at the time that he was creating works of art. The absent lyres were installations which he rendered as interventions, and transformed into artifacts. More recently the British artist Rachel Whiteread has made her name through an understanding of the absent form, from the cast of a house to the undersides and spaces of domestic interiors.

Recognising the evidence of absence is not about forcing a shape on the intangible, but acknowledging a potency in the not-thereness. Taking the absence concept to be a positive idea, I suggest interesting things happen. For years middle-eastern archaeologists puzzled over the numerous, isolated bath-houses and other structures in the deserts of North Africa. Where was the evidence of habitation? The clue was in the absence: the buildings were used by nomads who left only camel prints in the sand. Their habitations were ephemeral, tents which, if not taken away with them, were of such material that they would too disappear into the sand. Observed again in this light, the ariel photos of desert ruins are hauntingly repopulated.

The absent evidence of ourselves is all around us, beyond the range of digital traces.

When my parents died and I inherited their house, the task of clearing their rooms was both emotional, and archaeological. The last mantelpiece in the sitting room had accreted over 35 years of married life, a midden of photos, ephemera, beach-combing trove and containers of odd buttons and old coins. I wondered what a stranger — maybe a forensic scientist, or traditional archaeologist — would make of this array if the narrative was woven simply from the tangible evidence. But as I took the assemblage apart in a charged moment, I felt there was a whole lot of no-thing which was coming away with it. Something invisible, and unquantifiable, which had been holding these objects in that context.

I recognised the feeling, and cast my memory back to my first archaeological excavation. It was of a long-limbed hound, one of those 'fine, hunting dogs' the classical writer, Strabo, described as being traded from ancient Britain into the Roman world. As I knelt in the 2000 year old grave, carefully removing each tiny bone, as if engaged with a sculptural process, I felt the presence of something absent. I could not quantify it, but it was that unseen 'evidence' which, it seemed, had given the dog its dog-ness.

To get rid of garbage is essential, also of mental garbage. Cognitive toolkits are filled with such garbage, simply because we are victims of ourselves. We should regularly empty this garbage can, or in case we enjoy to sit in garbage, we better check how "shorthand abstractions" (SHA's) limit our creativity (certainly an SHA). Why is the cognitive toolkit filled with garbage?

Let us look back in history (SHA): Modern science (SHA) can be said to have started in 1620 with "Novum Organum" ("New Instrument") by Francis Bacon. It should impress us today that his analysis (SHA) begins with a description (SHA) of four mistakes we run into when we do science. Unfortunately, we usually forget these warnings. Francis Bacon argued that we are — first — victims of evolution (SHA), i.e. that our genes (SHA), define constraints that necessarily limit insight (SHA). Second — we suffer from the constraints of imprinting (SHA); the culture (SHA) we live in provides a frame for epigenetic programs (SHA) that ultimately define the structure (SHA) of neuronal processing (SHA). Third — we are corrupted by language (SHA) as thoughts (SHA) cannot be easily transformed into verbal expressions . Fourth — we are guided or even controlled by theories (SHA), may they be explicit or implicit.

What are the implications for a cognitive toolkit? We are caught for instance in a language trap. On the basis of our evolutionary heritage we have the power of abstraction (SHA), but this has inspite of some advantages we brag about (to make us superior to other creatures) a disastrous consequence: Abstractions are usually represented in words; apparently we cannot do otherwise; we have to "ontologize"; we invent nouns to extract knowledge (SHA) from processes (SHA). ( I do not refer to the powerful pictorial shorthand abstractions). Abstraction is obviously complexity reduction (SHA). We make it simple. Why do we do this? Evolutionary heritage dictates to be fast. However, speed may give an advantage for a "survival toolkit", but not for a "cognitive toolkit". It is a categorical error (SHA) to confuse speed in action with speed in thinking. The selection pressure for speed invites to neglect the richness of facts. This pressure allows the invention (SHA) of a simple, clear, easy to understand, easy to refer to, easy to communicate shorthand abstraction. Thus, because we are a victim of our biological past and as a consequence a victim of ourselves we end up with shabby SHA's having left behind reality. If there is one disease all humans share, it is "monocausalitis", i.e. the motivation (SHA) to explain everything on the basis of just one cause. This may be a nice intellectual exercise but it is simply misleading.

Of course we depend on communication (SHA), and this requires verbal references usually tagged with language. But if we do not understand within the communicative frame or reference system (SHA) that we are a victim of ourselves by "ontologizing" and continuously creating "practical" SHA's, we simply use a cognitive toolkit of mental garbage. Is there a pragmatic way out other than to radically get rid of mental garbage? Yes, perhaps: Simply not using the the key SHA's explicitly in one's toolkit. Working on "consciousness", don't use (at least for one year) the SHA consciousness; if you work on the "self", never refer explicitly to self. Going through the own garbage one discovers many misleading SHA's, like just a few in my focus of attention (SHA): the brain as a net, localization of function, representation, inhibition, threshold, decision, the present, .... An easy way out is of course to refer to some of these SHA's as metaphors (SHA), but this again is evaiding the problem (SHA). I am aware of the fact (SHA) that I am also a victim of evolution, and to suggest "garbage" as a SHA also suffers from the same problem; even the concept of garbage required a discovery (SHA). But we cannot do otherwise than simply being aware of this challenge (SHA) that the content of the cognitive toolkit is characterized by self–referentiality (SHA), i.e. by the fact that the SHA's define themselves by their unreflected use.

I think that an important concept to understand why does life suck so often is Kakonomics, or the weird preference for Low-quality payoffs.

Standard game-theoretical approaches posit that, whatever people are trading (ideas, services, or goods), each one wants to receive High-quality work from others. Let's stylize the situation so that goods can be exchanged only at two qualitylevels: High and Low. Kakonomics describes cases where people not only have standard preferences to receive a High-quality good and deliver a Low-quality one (the standard sucker's payoff) but they actually prefer to deliver a Low-quality good and receive a Low-quality one, that is, they connive on a Low-Low exchange.

How can it ever be possible? And how can it be rational? Even when we are lazy, and prefer to deliver a Low-quality outcome (like prefer to write a piece for a mediocre journal provided that they do not ask one to do too much work), we still would have preferred to work less and receive more, that is deliver Low-quality and receive High-quality. Kakonomics is different: Here, we not only prefer to deliver a Low-quality good, but also, prefer to receive a Low-quality good in exchange!

Kakonomics is the strange — yet widespread — preference for mediocre exchanges insofar as nobody complains about. Kakonomic worlds are worlds in which people not only live with each other's laxness, but expect it: I trust you not to keep your promises in full because I want to be free not to keep mine and not to feel bad about it. What makes it an interesting and weird case is that, in all kakonomic exchanges, the two parties seem to have a double deal: an official pact in which both declare their intention to exchange at a High-quality level, and a tacit accord whereby discounts are not only allowed but expected. It becomes a form of tacit mutual connivance. Thus, nobody is free-riding:Kakonomics is regulated by a tacit social norm of discount on quality, a mutual acceptance for a mediocre outcome that satisfies both parties, as long as they go on saying publicly that the exchange is in fact at a High-quality level.

Take an example: A well-established best-seller author has to deliver his long overdue manuscript to his publisher. He has a large audience, and knows very well that people will buy his book just because of his name and anyway, the average reader doesn't read more than the first chapter. His publisher knows it as well…Thus, the author decides to deliver to the publisher the new manuscript with a stunning incipit and a mediocre plot (the Low-quality outcome): she is happy with it, congratulates him as she had received a masterpiece (the High-quality rhetoric) and they are both satisfied. The author's preference is not only to deliver a Low-quality work, but also that the publisher gives back the same, for example by avoiding to provide a too serious editing and going on publishing. They trust each other's untrustworthiness, and connive on a mutual advantageous Low outcome. Whenever there is a tacit deal to converge to Low-quality with mutual advantages, we are dealing with a case of Kakonomics.

Paradoxically, if one of the two parties delivers a High-quality outcome instead of the expected Low-quality one, the other party resents it as a breach of trust, even if he may not acknowledge it openly. In the example, the author may resent the publisher if she decides to deliver a High-quality editing. Her being trustworthy in this relation means to deliver Low-quality too. Contrary to the standard Prisoner Dilemma game, the willingness to repeat an interaction with someone is ensured if he or she delivers Low-quality too rather than High-quality.

Kakonomics is not always bad. Sometimes it allows a certain tacitly negotiated discount that makes life more relaxing for everybody. As one friend who was renovating a country house in Tuscany told me once: "Italian builders never deliver when they promise, but the good thing is they do not expect you to pay them when you promise either."

But the major problem of Kakonomics — that in ancient Greek means the economics of the worst — and the reason why it is a form of collective insanity so difficult to eradicate, is that each Low-quality exchange is a local equilibrium in which both parties are satisfied, but each of these exchanges erodes the overall system in the long run. So, the threat to good collective outcomes doesn't come only from free riders and predators, as mainstream social sciences teach us, but also from well-organized norms of Kakonomics that regulate exchanges for the worse. The cement of society is not just cooperation for the good: in order to understand why life sucks, we should look also at norms of cooperation for a local optimum and a common worse.

In an ideal world all people would spontaneously understand that what political scientists call path dependence explains much more of how the world works than is apparent. Path dependence refers to the fact that often, something that seems normal or inevitable today began with a choice that made sense at a particular time in the past, but survived despite the eclipse of the justification for that choice, because once established, external factors discouraged going into reverse to try other alternatives.

The paradigm example is the seemingly illogical arrangement of letters on typewriter keyboards. Why not just have the letters in alphabetical order, or arrange them so that the most frequently occurring ones are under the strongest fingers? In fact, the first typewriter tended to jam when typed on too quickly, so its inventor deliberately concocted an arrangement that put A under the ungainly little finger. In addition, the first row was provided with all of the letters in the word typewriter so that salesmen, new to typing, could wangle typing the word using just one row.

Quickly, however, mechanical improvements made faster typing possible, and new keyboards placing letters according to frequency were presented. But it was too late: there was no going back. By the 1890s typists across America were used to QWERTY keyboards, having learned to zip away on new versions of them that did not stick so easily, and retraining them would have been expensive and, ultimately, unnecessary. So QWERTY was passed down the generations, and even today we use the queer QWERTY configuration on computer keyboards where jamming is a mechanical impossibility.

The basic concept is simple, but in general estimation tends to be processed as the province of "cute" stories like the QWERTY one, rather than explaining a massive weight of scientific and historical processes. Instead, the natural tendency is to seek explanations for modern phenomena in present-day conditions.

One may assume that cats cover their waste out of fastidiousness, when the same creature will happily consume its own vomit and then jump on your lap. Cats do the burying as an instinct from their wild days when the burial helped avoid attracting predators, and there is no reason for them to evolve out of the trait now (to pet owners' relief). I have often wished there were a spontaneous impulse among more people to assume that path dependence-style explanations are as likely as jerry-rigged present-oriented ones.

For one, that the present is based on a dynamic mixture of extant and ancient conditions is simply more interesting than assuming that the present (mostly) all there is, with history as merely "the past," interesting only for seeing whether something that happened then could now happen again, which is different from path dependence.

For example, path dependence explains a great deal about language which is otherwise attributed to assorted just-so explanations. Much of the public embrace of the idea that one's language channels how one thinks is based on this kind of thing. Robert McCrum celebrates English as "efficient" in its paucity of suffixes of the kind that complexify most European languages. The idea is that this is rooted in something in its speakers' spirit, which would have propelled them to lead the world via exploration and the Industrial Revolution.

But English lost its suffixes starting in the eighth century, A.D. when Vikings invaded Britain and so many of them learned the language incompletely that children started speaking it that way. After that, you can't create gender and conjugation out of thin air — there's no going back until gradual morphing recreates such things over eons of time. That is, English's current streamlined syntax has nothing to do with any present-day condition of the spirit, nor with any even four centuries ago. The culprit is path dependence, as are most things about how a language is structured.

Or, we hear much lately about a crisis in general writing skills, suposedly due to email and texting. But there is a circularity here — why, precisely, could people not write emails and texts with the same "writerly" style that people used to couch letters in? Or, we hear of a vaguely defined effect of television, despite that kids were curled up endlessly in front of the tube starting in the fifties, long before the eighties when outcries of this kind first took on their current level of alarm in the report A Nation at Risk.

Once again, the presentist explanation does not cohere, whereas one based on an earlier historical development that there is no turning back from does. Public American English began a rapid shift from cosseted to less formal "spoken" style in the sixties, in the wake of cultural changes amidst the counterculture. This sentiment directly affected how language arts textbooks were composed, the extent to which any young person was exposed to an old-fashioned formal "speech," and attitudes towards the English language heritage in general. The result: a linguistic culture stressing the terse, demotic, and spontaneous. After just one generation minted in this context, there was no way to go back. Anyone who decided to communicate in the grandiloquent phraseology of yore would sound absurd and be denied influence or exposure. Path dependence, then, identifies this cultural shift as the cause of what dismays, delights, or just interests us in how English is currently used, and reveals television, email and other technologies as merely epiphenomenal.

Most of life looks path dependent to me. If I could create a national educational curriculum from scratch, I would include the concept as one taught to young people as early as possible.

Humanity's cognitive toolkit would greatly benefit from adoption of "interbeing," a concept that comes from Vietnamese Buddhist monk Thich Nhat Hanh. In his words:

"If you are a poet, you will see clearly that there is a cloud floating in [a] sheet of paper. Without a cloud, there will be no rain; without rain, the trees cannot grow; and without trees, we cannot make paper. The cloud is essential for the paper to exist. If the cloud is not here, the sheet of paper cannot be here either . . . "Interbeing" is a word that is not in the dictionary yet, but if we combine the prefix "inter-" with the verb to be," we have a new verb, inter-be. Without a cloud, we cannot have a paper, so we can say that the cloud and the sheet of paperinter-are. . . . "To be" is to inter-be. You cannot just be by yourself alone. You have to inter-be with every other thing. This sheet of paper is, because everything else is."

Depending on your perspective, the above passage may sound like profound wisdom or New Age mumbo-jumbo. I would like to propose that interbeing is a robust scientific fact — at least insomuch as such things exist — and, further, that this concept is exceptionally critical and timely.

Arguably the most cherished and deeply ingrained notion in the Western mindset is the separateness of our skin-encapsulated selves — the belief that we can be likened to isolated, static machines. Having externalized the world beyond our bodies, we are consumed with thoughts of furthering our own ends and protecting ourselves. Yet this deeply rooted notion of isolation is illusory, as evidenced by our constant exchange of matter and energy with the "outside" world. At what point did your last breath of air, sip of water, or bite of food cease to be part of the outside world and become you? Precisely when did your exhalations and wastes cease being you? Our skin is as much permeable membrane as barrier, so much so that, like a whirlpool, it is difficult to discern where "you" end and the remainder of the world begins. Energized by sunlight, life converts inanimate rock into nutrients, which then pass through plants, herbivores, and carnivores before being decomposed and returned to the inanimate Earth, beginning the cycle anew. Our internal metabolisms are intimately interwoven with this Earthly metabolism; one result is the replacement of every atom in our bodies every seven years or so.

You might counter with something like, "Ok, sure, everything changes over time. So what? At any given moment, you can still readily separate self from other."

Not quite. It turns out that "you" are not one life form — that is, one self — but many. Your mouth alone contains more than 700 distinctkinds of bacteria. Your skin and eyelashes are equally laden with microbes and your gut houses a similar bevy of bacterial sidekicks. Although this still leaves several bacteria-free regions in a healthy body — for example, brain, spinal cord, and blood stream — current estimates indicate that your physical self possesses about a trillion human cells and about 10 trillion bacterial cells. In other words, at any given moment, your body is about 90% nonhuman, home to many more life forms than the number of people presently living on Earth; more even than the number of stars in the Milky Way Galaxy! To make things more interesting still, microbiological research demonstrates that we are utterly dependent on this ever-changing bacterial parade for all kinds of "services," from keeping intruders at bay to converting food into useable nutrients.

So, if we continually exchange matter with the outside world, if our bodies are completely renewed every few years, and if each of us is a walking colony of trillions of largely symbiotic life forms, exactly what is this self that we view as separate? You are not an isolated being. Metaphorically, to follow current bias and think of your body as a machine is not only inaccurate but destructive. Each of us is far more akin to a whirlpool, a brief, ever-shifting concentration of energy in a vast river that's been flowing for billions of years. The dividing line between self and other is, in many respects, arbitrary; the "cut" can be made at many places, depending on the metaphor of self one adopts. We must learn to see ourselves not as isolated but as permeable and interwoven — selves within larger selves, including the species self (humanity) and the biospheric self (life). The interbeing perspective encourages us to view other life forms not as objects but subjects, fellow travelers in the current of this ancient river. On a still more profound level, it enables us to envision ourselves and other organisms not as static "things" at all, but as processes deeply and inextricably embedded in the background flow.

One of the greatest obstacles confronting science education is the fact that the bulk of the universe exists either at extremely large scales (e.g., planets, stars, and galaxies) or extremely small scales (e.g., atoms, genes, cells) well beyond the comprehension of our (unaided) senses. We evolved to sense only the middle ground, or "mesoworld," of animals, plants, and landscapes. Yet, just as we have learned to accept the non-intuitive, scientific insight that the Earth is not the center of the universe, so too must we now embrace the fact that we are not outside or above nature, but fully enmeshed within it. Interbeing, an expression of ancient wisdom backed by science, can help us comprehend this radical ecology, fostering a much-needed transformation in mindset.

It is one of the stranger ideas to emerge from recent physics. Take two theories that describe utterly dissimilar worlds — worlds with different numbers of dimensions, different geometries of spacetime, different building blocks of matter. Twenty years ago, we'd say those are indisputably disparate and mutually exclusive worlds. Today, there's another option: two radically different theories might be dual to one another — that is, they might be two very different manifestations of the same underlying reality.

Dualities are as counterintuitive a notion as they come, but physics is riddled with them. When physicists looking to unite quantum theory with gravity found themselves with five very different but equally plausible string theories, it was an embarrassment of riches — everyone was hoping for one "theory of everything", not five. But duality proved to be the key ingredient. Remarkably, all five string theories turned out to be dual to one another, different expressions of a single underlying theory.

Perhaps the most radical incarnation of duality was discovered in 1997 by Juan Maldacena. Maldacena found that a version of string theory in a bizarrely shaped universe with five large dimensions is mathematically dual to an ordinary quantum theory of particles living on that universe's four-dimensional boundary. Previously, one could argue that the world was made up of particles or that the world was made up of strings. Duality transformed or into and — mutually exclusive hypotheses, both equally true.

In everyday language, duality means something very different. It is used to connote a stark dichotomy: male and female, east and west, light and darkness. Embracing the physicist's meaning of duality, however, can provide us with a powerful new metaphor, a one-stop shorthand for the idea that two very different things might be equally true. As our cultural discourse is becoming increasingly polarized, the notion of duality is both more foreign and more necessary than ever. If accessible in our daily cognitive toolkit, it could serve as a potent antidote to our typically Boolean, two-valued, zero-sum thinking — where statements are either true or false, answers are yes or no, and if I'm right, then you are wrong. With duality, there's a third option. Perhaps my argument is right and yours is wrong; perhaps your argument is right and mine is wrong; or, just maybe, our opposing arguments are dual to one another. 

That's not to say that we ought to descend into some kind of relativism, or that there are no singular truths. It is to say, though, that truth is far more subtle than we once believed, and that it shows up in many guises. It is up to us to recognize it in all its varied forms.

Root cause analysis is an attractive concept for certain matters in industry, engineering and quality control. A classic application is to determine why a plane crashed by finding the proverbial "black box" — the tamper-proof event data recorder. Even though this box is usually bright orange, the term symbolizes the sense of dark matter, a container with critical information to help illuminate what happened. Getting the black box audio recording is just one component of a root cause analysis for why a plane goes down.

Man is gradually being morphed into an event data recorder by virtue of each person's digital identity and presence on the web. Not only do we post our own data, sometimes unwittingly, but also others post information about us, and all of this is permanently archived. In that way it is close to tamper-proof. With increasing use of biosensors, high-resolution imaging (just think of our current cameras and video recording, no less digital medical imaging), and DNA sequencing, the human data event recorder will be progressively enriched with data and information.  

In our busy, networked lives with constant communication, streaming and distraction, the general trend has moved away from acquiring deep knowledge for why something happened.  This is best exemplified in health and medicine. Physicians rarely seek root cause. If a patient has a common condition such as high blood pressure, diabetes, or asthma, he or she is put on some prescription drugs without any attempt at ascertaining why the individual crashed — certainly a new, chronic medical condition can be likened to such an event. There are usually specific reasons for these disorders but they are not hunted down. Taken to an extreme, when an individual dies and the cause is not known it is now exceedingly rare that an autopsy is ever performed. Doctors have generally caved in their quest to define root cause, and they are fairly representative of most of us. Ironically, this is happening at a time when there is unprecedented capability for finding the explanation. But we're just too busy.

So to tweak our cognitive performance in the digital world where there is certainly no shortage of data, it's time to use it and understand, as fully as possible, why unexpected or unfavorable things happen. Or even why something great transpired. It's a prototypic scientific concept that has all too often been left untapped. Each person is emerging as an extraordinary event recorder and part of the Internet of all things. Let's go deep. Nothing unexplained these days should go without a hunt.

When John Cabot came to the Grand Banks off Newfoundland in 1497 he was astonished at what he saw. Fish, so many fish — fish in numbers he could hardly comprehend. According to Farley Mowat, Cabot wrote that the waters were so "swarming with fish [that they] could be taken not only with a net but in baskets let down and [weighted] with a stone."

The fisheries boomed for five hundred years, but by 1992 it was all over. The Grand Banks cod fishery was destroyed, and the Canadian government was forced to close it entirely, putting 30,000 fishers out of work. It has never recovered.

What went wrong? Many things, from factory fishing to inadequate oversight, but much of it was aided and abetted by treating each step toward disaster as normal. The entire path, from plenitude to collapse, was taken as the status quo, right up until the fishery was essentially wiped out.

In 1995 fisheries scientist Daniel Pauly coined a phrase for this troubling ecological obliviousness — he called it "shifting baseline syndrome". Here is how Pauly first described the syndrome: "Each generation of fisheries scientist accepts as baseline the stock situation that occurred at the beginning of their careers, and uses this to evaluate changes. When the next generation starts its career, the stocks have further declined, but it is the stocks at that time that serve as a new baseline. The result obviously is a gradual shift of the baseline, a gradual accommodation of the creeping disappearance of resource species…"

It is blindness, stupidity, intergeneration data obliviousness. Most scientific disciplines have long timelines of data, but many ecological disciplines don't. We are forced to rely on second-hand and anecdotal information — we don't have enough data to know what is normal, so we convince ourselves that this is normal.

But it often isn't normal. Instead, it is a steadily and insidiously shifting baseline, no different than convincing ourselves that winters have always been this warm, or this snowy. Or convincing ourselves that there have always been this many deer in the forests of eastern North America. Or that current levels of energy consumption per capita in the developed world are normal. All of these are shifting baselines, where our data inadequacy, whether personal or scientific, provides dangerous cover for missing important longer-term changes in the world around us.

When you understand shifting baseline syndrome it forces you to continually ask what is normal. Is this? Was that? And, at least as importantly, it asks how we "know" that it's normal. Because, if it isn't, we need to stop shifting the baselines and do something about it before it's too late.

In the late 1960s, the psychologist Walter Mischel began a simple experiment with four-year old children. He invited the kids into a tiny room, containing a desk and a chair, and asked them to pick a treat from a tray of marshmallows, cookies, and pretzel sticks. Mischel then made the four-year olds an offer: they could either eat one treat right away or, if they were willing to wait while he stepped out for a few minutes, they could have two treats when he returned. Not surprisingly, nearly every kid chose to wait.

At the time, psychologists assumed that the ability to delay gratification — to get that second marshmallow or cookie — depended on willpower. Some people simply had more willpower than others, which allowed them to resist tempting sweets and save money for retirement.

However, after watching hundreds of kids participate in the marshmallow experiment, Mischel concluded that this standard model was wrong. He came to realize that willpower was inherently weak, and that children that tried to outlast the treat — gritting their teeth in the face of temptation — soon lost the battle, often within thirty seconds.

Instead, Mischel discovered something interesting when he studied the tiny percentage of kids who could successfully wait for the second treat. Without exception, these "high delayers" all relied on the same mental strategy: they found a way to keep themselves from thinking about the treat, directing their gaze away from the yummy marshmallow. Some covered their eyes or played hide-and-seek underneath the desk. Others sang songs from "Sesame Street," or repeatedly tied their shoelaces, or pretended to take a nap. Their desire wasn't defeated — it was merely forgotten.

Mischel refers to this skill as the "strategic allocation of attention," and he argues that it's the skill underlying self-control. Too often, we assume that willpower is about having strong moral fiber. But that's wrong — willpower is really about properly directing the spotlight of attention, learning how to control that short list of thoughts in working memory. It's about realizing that if we're thinking about the marshmallow we're going to eat it, which is why we need to look away.

What's interesting is that this cognitive skill isn't just a useful skill for dieters. Instead, it seems to be a core part of success in the real world. For instance, when Mischel followed up with the initial subjects 13 years later — they were now high school seniors — he realized that performance on the marshmallow task was highly predictive on a vast range of metrics. Those kids who struggled to wait at the age of four were also more likely to have behavioral problems, both in school and at home. They struggled in stressful situations, often had trouble paying attention, and found it difficult to maintain friendships. Most impressive, perhaps, were the academic numbers: The little kid who could wait fifteen minutes for their marshmallow had an S.A.T. score that was, on average, two hundred and ten points higher than that of the kid who could wait only thirty seconds.

These correlations demonstrate the importance of learning to strategically allocate our attention. When we properly control the spotlight, we can resist negative thoughts and dangerous temptations. We can walk away from fights and improve our odds against addiction. Our decisions are driven by the facts and feelings bouncing around the brain — the allocation of attention allows us to direct this haphazard process, as we consciously select the thoughts we want to think about.

Furthermore, this mental skill is only getting more valuable. We live, after all, in the age of information, which makes the ability to focus on the important information incredibly important. (Herbert Simon said it best: "A wealth of information creates a poverty of attention.") The brain is a bounded machine and the world is a confusing place, full of data and distractions — intelligence is the ability to parse the data so that it makes just a little bit more sense. Like willpower, this ability requires the strategic allocation of attention.

One final thought: In recent decades, psychology and neuroscience have severely eroded classical notions of free will. The unconscious mind, it turns out, is most of the mind. And yet, we can still control the spotlight of attention, focusing on those ideas that will help us succeed. In the end, this may be the only thing we can control. We don't have to look at the marshmallow.

Confluence of factors is highly influential in setting off changes in complex systems. A common example is in risk — the "Swiss cheese theory". Losses only occur if all controls fail — the holes in the Swiss cheese align.

Confluence, coincidence of events in a single setting, is well understood. Parallel developments, often in different settings or disciplines, can be influential in shaping events. A coincidence of similar logic and processes in seemingly unrelated activities provide indications of likely future developments and risks. The ability to better recognize"parallelism" would improve cognitive processes.

Economic forecasting is dismal, prompting John Kenneth Galbraith to remark that economists were only put on earth to make astrologers look good. Few economists anticipated the current financial problems, at least before they happened.

However, the art market proved remarkably accurate in anticipating developments, especially the market in the work of Damien Hirst — the best known of a group of artists dubbed yBAs (young British Artists).

Hirst's most iconic work — The Physical Impossibility of Death in the Mind of Someone Living — is a 14-foot (4.3 meter) tiger shark immersed in formaldehyde in a vitrine weighing over two tons. Charles Saatchi (the advertising guru) bought it for £50,000. In December 2004, Saatchi sold the work to Steve Cohen, founder and principal of the uber hedge fund — SAC Capital Advisers, which manages $20 billion. Cohen paid $12 million for The Physical Impossibility of Death in the Mind of Someone Living, although there are allegation that it was only $8 million.

In June 2007, Damien Hirst tried to sell a life size platinum cast of a human skull, encrusted with £15 million worth of 8,601 pave-set industrial diamonds, weighing 1,100 carats including a 52.4 carat pink diamond in the center of the forehead valued at £4 million. For the Love of God was a memento mori, in Latin remember you must die. The work was offered for sale at £50 million as part of Hirst's Beyond Belief show. In September 2007, For the Love of God was sold to Hirst and some investors for full price, for later resale.

The sale of The Physical Impossibility of Death in the Mind of Someone Living marked the final phase of the irresistible rise of markets. The failure of For the Love of God to sell marked its zenith as clearly as any economic marker.

Parallelism exposes common thought processes and similar valuation approaches to unrelated objects.

Hirst was the artist of choice for conspicuously consuming hedge fund managers, who were getting very rich managing money. Inflated prices suggested the presence of "irrational excess". The nature of sought after Hirst pieces and even their titles provided an insight into the hubristic self-image of financiers. With its jaws gaping, poised to swallow its prey,The Physical Impossibility of Death in the Mind of Someone Living mirrored the killer instincts of hedge funds, feared predators in financial markets. Cohen "… liked the whole fear factor."

The work of Japanese artist Takeshi Murakami provides confirmation. Inspired by Hokusai's famous 19th century woodblock print The Great Wave of Kanagawa, Murakami's 727 paintings showed Mr. DOB, a post nuclear Mickey Mouse character, as a god riding on a cloud or a shark surfing on a wave. The first 727 is owned by New York's Museum of Modern Art, the second by Steve Cohen.

Parallelism is also evident in the causes underlying several crises facing humanity. It is generally acknowledged that high levels of debt were a major factor in the ongoing global financial crisis. What is missed is that the logic of debt is similar to one underlying other problematic issues.

There is a striking similarity between the problems of the financial system, irreversible climate change and shortages of vital resources like oil, food and water. Economic growth and wealth was based on borrowed money. Debt allowed society to borrow from the future. It accelerated consumption, as debt is used to purchase something today against the uncertain promise of paying back the borrowing in the future. Society polluted the planet, creating changes in the environment which are difficult to reserve. Under-priced, natural finite resources were wantonly utilized, without proper concern about conservation.

In each area, society borrowed from and pushed problems into the future. Current growth and short-term profits were pursued at the expense of risks which were not evident immediately and that would emerge later.

To dismiss this as short-term thinking and greed is disingenuous. A crucial cognitive factor underlying the approach was a similar process of problem solving — borrowing from or pushing problems further into the future. This was consistently applied across different problems, without consideration of either it relevance, applicability or desirability. Where such parallelism exists, it feeds on itself, potentially leading to total systemic collapse.

Recognition and understanding of parallelism is one way to improve cognitive thinking. It may provide a better mechanism for predicting specific trends. It may also enable people to increase the dialectic richness, drawing on different disciplines. It requires overcoming highly segmented and narrow educational disciplines, rigid institutional structures and restricted approaches to analysis or problem solving.

The "Cognitive Iceberg:" Humans Are Blind To Many Of The Processes That Shape Their Mental Lives

The human brain is an inconceivably complex tool, and while we're focusing on the business of daily life, our brains are processing multitudes of information below the surface of conscious awareness. Meanwhile, this peripheral information subtly shapes our thoughts, feelings and actions, and crafts some of our most critical life outcomes. This information takes many forms, but I'll illustrate the principle with three brief examples:

1. Color

Color is a ubiquitous feature of the environment, though we rarely notice colors unless they're particularly bright or deviate dramatically from our expectations. Nonetheless, colors have the capacity to shape a range of outcomes: men are ever so slightly more attractive to women when they wear red colored shirts (rather than shirts of another color); the same effect applies to women, who seem more attractive to men when their pictures are bounded by a red colored border. Red signals both romantic intent and dominance amongst lower-order species, and this same signal applies to men and women. This same relationship between red and dominance explains why sporting teams that wear red are more aggressive and tend to dominate sporting teams that wear other colors; meanwhile, sports referees and umpires assign more points to teams wearing red uniforms, which may explain in part why those teams tend to outperform teams wearing other colors. But, red isn't always beneficial: we've come to associate red with errors and caution, which makes people avoidant and in turn limits their creativity (though it also improves their attention to detail). These effects have sound bases in biology and human psychology, but that doesn't make them any less remarkable or surprising to the lay population.

2. Weather and Ambient Temperature

No one's surprised that the sunny warmth of summer makes people happy, but weather conditions and ambient temperature have other more surprising effects on our mental lives. Rainy weather makes us more introspective and thoughtful, which in turn improves our memory — in one study, people remembered the features of a store with greater accuracy on rainy days than on sunny days. On a grander scale, the stock market tends to rise on fine, sunny days, while cooler, rainy days prompt sluggishness and brief downturns. More surprising, still, is the relationship between changes in weather and various accidents, suicide, depression and irritability, all of which are claimed to respond to changes in the electrical state of the atmosphere. The metaphor between warmth and human kindness is also more than a metaphor, as recent studies have shown that people find strangers more likable when they form their first impressions while holding a cup of warm coffee. The warmth-kindness metaphor extends to social exclusion, as people literally feel colder when they've been socially excluded. The simple relationship between fine weather and happiness is joined by a series of more surprising and complicated relationships between weather and warmth on the one hand, and a range of important life outcomes on the other.

3. Symbols and Images

Urban landscapes are populated by thousands of symbols and images that unwittingly influence how we think and behave. Self-identified Christians tend to behave more honestly when they're exposed to an image of the crucifix, even when they have no conscious memory of seeing the crucifix in the first place. Honesty is a virtue, but another experiment showed that Christians held lower opinions of themselves after they were subliminally exposed to an image of then Pope John Paul II. On a brighter note, people think more creatively when they're exposed to the Apple Computers logo, or when they witness the illumination of an incandescent light bulb; both the Apple logo and the illuminated light bulb are popularly associated with creativity, and deeply ingrained metaphors once activated have the capacity to shape actual behavior. Similar associative logic suggests that national flags should prompt unity, and indeed a sample of left-wing and right-wing Israelis were more accommodating of opposing political views when they were subliminally exposed to an image of the Israeli flag. Likewise, a sample of Americans responded more favorably to Muslims when seated in front of a large U.S. flag.

These three cues — colors, weather conditions, and symbols and images — are joined by dozens of others that have a surprising capacity to influence how we think, feel, behave, and decide. Once we understand what those cues are and how they shape our mental lives, we're better equipped to harness them to our advantage.

The recent controversy about the potential dangers to health of the back-scatter radiation devices being introduced at the nation's airports and the intrusive pat-downs offered as the only alternative by the TSA might well have been avoided had citizens been aware of, and understood, the probabilistic notion of base rate.

Whenever a statistician wants to predict the likelihood of some event based on the available evidence, there are two main sources of information that have to be taken into account:

1. The evidence itself, for which a reliability figure has to be calculated;

2. The likelihood of the event calculated purely in terms of relative incidence.

The second figure here is the base rate. Since it is just a number, obtained by the seemingly dull process of counting, it frequently gets overlooked when there is new information, particularly if that new information is obtained by "clever experts" using expensive equipment. In cases where the event is dramatic and scary, like a terrorist attack on an airplane, failure to take account of the base rate can result in wasting massive amounts of effort on money trying to prevent something that is very unlikely.

For example, suppose that you undergo a medical test for a relatively rare cancer. The cancer has an incidence of 1% among the general population. (That is the base rate.) Extensive trials have shown that the reliability of the test is 79%. More precisely, although the test does not fail to detect the cancer when it is present, it gives a positive result in 21% of the cases where no cancer is present — what is known as a "false positive." When you are tested, the test produces a positive diagnosis. The question is: What is the probability that you have the cancer?

If you are like most people, you will assume that if the test has a reliability rate of nearly 80%, and you test positive, then the likelihood that you do indeed have the cancer is about 80% (i.e., the probability is approximately 0.8). Are you right?

The answer is no. You have focused on the test and its reliability, and overlooked the base rate, Given the scenario just described, the likelihood that you have the cancer is a mere 4.6% (i.e., the probability is 0.046). That's right, there is a less than 5% chance that you have the cancer. Still a worrying possibility, of course. But hardly the scary 80% you thought at first.

In the case of the back-scatter radiation devices at the airports, the base rate for dying in a terrorist attack is lower than many other things we do every day without hesitation. In fact, according to some reports, it is about the same as the likelihood of getting cancer as a result of going through the device.

You see the pattern everywhere: the top 1% of the population control 35% of the wealth. On Twitter, the top 2% of users send 60% of the messages. In the health care system, the treatment for the most expensive fifth of patients create four-fifths of the overall cost. These figures are always reported as shocking, as if the normal order of things has been disrupted, as if the appearance of anything other than a completely linear distribution of money, or messages, or effort, is a surprise of the highest order.

It's not. Or rather, it shouldn't be.

The Italian economist Vilfredo Pareto undertook a study of market economies a century ago, and discovered that no matter what the country, the richest quintile of the population controlled most of the wealth. The effects of this Pareto Distribution go by many names — the80/20 Rule, Zipfs Law, the Power Law distribution, Winner-Take-All — but the basic shape of the underlying distribution is always the same: the richest or busiest or most connected participants in a system will account for much much more wealth, or activity, or connectedness than average.

Furthermore, this pattern is recursive. Within the top 20% of a system that exhibits a Pareto distribution, the top 20% of that slice will also account for disproportionately more of whatever is being measured, and so on. The most highly ranked element of such a system will be much more highly weighted than even the #2 item in the same chart. (The word "the" is not only the commonest word in English, it appears twice as often the second most common, "of".)

This pattern was so common, Pareto called it a "predictable imbalance"; despite this bit of century-old optimism, however, we are still failing to predict it, even though it is everywhere.

Part of our failure to expect the expected is that we have been taught that the paradigmatic distribution of large systems is the Gaussian distribution, commonly known as the bell curve. In a bell curve distribution like height, say, the average and the median (the middle point in the system) are the same — the average height of a hundred American women selected at random will be about 5'4", and the height of the 50th woman, ranked in height order, will also be 5'4".

Pareto distributions are nothing like that — the recursive 80/20 weighting means that the average is far from the middle. This in turn means that in such systems most people (or whatever is being measured) are below average, a pattern encapsulated in the old economics joke: "Bill Gates walks into a bar and makes everybody a millionaire, on average."

The Pareto distribution shows up in a remarkably wide array of complex systems. Together, "the" and "of" account for 10% of all words used in English. The most volatile day in the history of a stock market will typically be twice that of the second-most volatile, and ten times the tenth-most. Tag frequency on Flickr photos obeys a Pareto distribution, as does the magnitude of earthquakes, the popularity of books, the size of asteroids, and the social connectedness of your friends. The Pareto Principle is so basic to the sciences that special graph paper that shows Pareto distributions as straight lines rather than as steep curves is manufactured by the ream.

And yet, despite a century of scientific familiarity, samples drawn from Pareto distributions are routinely presented to the public as anomalies, which prevents us from thinking clearly about the world. We should stop thinking that average family income and the income of the median family have anything to do with one another, or that enthusiastic and normal users of communications tools are doing similar things, or that extroverts should be only moderately more connected than normal people. We should stop thinking that the largest future earthquake or market panic will be as large as the largest historical one; the longer a system persists, the likelier it is that an event twice as large as all previous ones is coming.

This doesn't mean that such distributions are beyond our ability to affect them. A Pareto curve's decline from head to tail can be more or less dramatic, and in some cases, political or social intervention can affect that slope — tax policy can raise or lower the share of income of the top 1% of a population, just as there are ways to constrain the overall volatility of markets, or to reduce the band in which health care costs can fluctuate.

However, until we assume such systems are Pareto distributions, and will remain so even after any such intervention, we haven't even started thinking about them in the right way; in all likelihood, we're trying to put a Pareto peg in a Gaussian hole. A hundred years after the discovery of this predictable imbalance, we should finish the job and actually start expecting it.

Findex (n): The degree to which a desired piece of information can be found online.

We are the first humans in history to be able to form just about any question in our minds and know that very likely the answer can be before us in minutes, if not seconds. This omnipresent information abundance is a cognitive toolkit entirely in itself. The actuality of this continues to astonish me.

Although some have written about information overload, data smog, and the like, my view has always been the more information online, the better, so long as good search tools are available. Sometimes this information is found by directed search using a web search engine, sometimes by serendipty by following links, and sometimes by asking hundreds of people in our social network or hundreds of thousands of people on a question answering website such as Answers.com, Quora, or Yahoo Answers.

I do not actually know of a real findability index, but tools in the field of information retrieval could be applied to develop one. One of the unsolved problems in the field is how to help the searcher to determine if the information simply is not available.

We can learn nearly as much from an experiment that does not work as from one that does. Failure is not something to be avoided but rather something to be cultivated. That's a lesson from science that benefits not only laboratory research, but design, sport, engineering, art, entrepreneurship, and even daily life itself. All creative avenues yield the maximum when failures are embraced. A great graphic designer will generate lots of ideas knowing that most will be aborted. A great dancer realizes most new moves will not succeed. Ditto for any architect, electrical engineer, sculptor, marathoner, startup maven, or microbiologist. What is science, after all, but a way to learn from things that don't work rather than just those that do? What this tool suggests is that you should aim for success while being prepared to learn from a series of failures. More so, you should carefully but deliberately press your successful investigations or accomplishments to the point that they break, flop, stall, crash, or fail.

Failure was not always so noble. In fact much of the world today failure is still not embraced as a virtue. It is a sign of weakness, and often a stigmata that prohibits second chances. Children in many parts of the world are taught that failure brings disgrace, and that one should do everything in one's power to succeed without failure. The rise of the West is in many respects due to the rise in tolerating failure. Indeed many immigrants trained in a failure-intolerant culture may blossom out of stagnancy once moved into a failure-tolerant culture. Failure liberates success.

The chief innovation that science brought to the state of defeat is a way to manage mishaps. Blunders are kept small, manageable, constant, and trackable. Flops are not quite deliberate, but they are channeled so that something is learned each time things fell. It becomes a matter of failing forward.

Science itself is learning how to better exploit negative results. Due to the problems of costly distribution most negative results have not been shared, thus limiting their potential to speed learning for others. But increasingly published negative results (which include experiments that succeed in showing no effects) are becoming another essential tool in the scientific method.

Wrapped up in the idea of embracing failure is the related notion of breaking things to make them better, particularly complex things. Often the only way to improve a complex system is to probe its limits by forcing it to fail in various ways. Software, among the most complex things we make, is usually tested for quality by employing engineers to systematically find ways to crash it. Similarly, one way to troubleshoot a complicated device that is broken is to deliberately force negative results (temporary breaks) in its multiple functions in order to locate the actual disfunction. Great engineers have a respect for breaking things that sometimes surprises non-engineers, just as scientists have a patience with failures that often perplexes outsiders. But the habit of embracing negative results is one of the most essential tricks to gaining success.

Most of us have a good reputation with ourselves. That's the gist of a sometimes amusing and frequently perilous phenomenon that social psychologists call self-serving bias. 

Accepting more responsibility for success than failure, for good deeds than bad.

In experiments, people readily accept credit when told they have succeeded (attributing such to their ability and effort). Yet they attribute failure to external factors such as bad luck or the problem's "impossibility." When we win at Scrabble it's because of our verbal dexterity. When we lose it's because "I was stuck with a Q but no U." 

Self-serving attributions have been observed with athletes (after victory or defeat), students (after high or low exam grades), drivers (after accidents), and managers (after profits and losses). The question, "What have I done to deserve this?" is one we ask of our troubles, not our successes.

The better-than-average phenomenon: How do I love me? Let me count the ways. 

It's not just in Lake Wobegon that all the children are above average. In one College Board survey of 829,000 high school seniors, zero percent rated themselves below average in "ability to get along with others," 60 percent rated themselves in the top 10 percent, and 25 percent rated themselves in the top 1 percent. Compared to our average peer, most of us fancy ourselves as more intelligent, better looking, less prejudiced, more ethical, healthier, and likely to live longer — a phenomenon recognized in Freud's joke about the man who told his wife, "If one of us should die, I shall move to Paris."

In everyday life, more than 9 in 10 drivers are above average drivers, or so they presume. In surveys of college faculty, 90 percent or more have rated themselves as superior to their average colleague (which naturally leads to some envy and disgruntlement when one's talents are underappreciated). When husbands and wives estimate what percent of the housework they contribute, or when work team members estimate their contributions, their self-estimates routinely sum to more than 100 percent.

Studies of self-serving bias and its cousins — illusory optimism, self-justification, and ingroup bias — remind us of what literature and religion have taught: pride often goes before a fall. Perceiving ourselves and our groups favorably protects us against depression, buffers stress, and sustains our hopes. But it does so at the cost of marital discord, bargaining impasses, condescending prejudice, national hubris, and war. Being mindful of self-serving bias beckons us not to false modesty, but to a humility that affirms our genuine talents and virtues, and likewise those of others.

When it comes to common resources, a failure to cooperate is a failure to control consumption. In Hardin's classic tragedy, everyone overconsumes and equally contributes to the detriment of the commons. But a relative few can also ruin a resource for the rest of us.

Biologists are familiar with the term 'keystone species', coined in 1969 after Bob Paine's intertidal exclusion experiments. Paine found that by removing the few five-limbed carnivores, Pisaster ochraceus, from the seashore, he could cause an overabundance of its prey, mussels, and a sharp decline in diversity. Without seastars, mussels outcompeted sponges. No sponges, no nudibranchs. Anenomes were also starved out because they eat what the seastars dislodge. Pisaster was the keystone that kept the intertidal community together. Without it, there were only mussels, mussels, mussels. The term keystone species, inspired by the purple seastar, refers to a species that has a disproportionate effect relative to its abundance.

In human ecology, I imagine diseases and parasites play a similar role to Pisaster in Paine's experiment. Remove disease (and increase food) and Homo sapiens takeover. Humans inevitably restructure their environment. But not all human beings consume equally. While a keystone species refers to a specific species that structures an ecosystem, I consider keystone consumers to be a specific group of humans that structures a market for a particular resource. Intense demand by a few individuals can bring flora and fauna to the brink.  

There are keystone consumers in the markets for caviar, slipper orchids, tiger penises, plutonium, pet primates, diamonds, antibiotics, Hummers, and seahorses. Niche markets for frog legs in pockets of the U.S., Europe, and Asia are depleting frog populations in Indonesia, Ecuador, and Brazil. Seafood lovers in high-end restaurants are causing stocks of long-lived fish species like Orange roughy or toothfish in Antarctica to crash. The desire for shark fin soup by wealthy Chinese consumers has led to the collapse of several shark species.

One in every four mammals (1,141 of the 5,487 mammals on Earth) is threatened with extinction. At least 76 mammals have become extinct since the 16th century, many, like the Tasmanian tiger, the great auk, and the Steller sea cow, due to hunting by a relatively small group. It is possible for a small minority of humans to precipitate the disappearance of an entire species.

The consumption of non-living resources is also imbalanced. The 15% of the world's population that lives in North America, Western Europe, Japan and Australia consumes 32 times more resources, like fossil fuels and metals, and produces 32 times more pollution than the developing world, where the remaining 85% of humans live. City-dwellers consume more than people living in the countryside. A recent study determined the ecological footprint for an average resident of Vancouver, British Columbia was 13 times higher than his suburban/rural counterpart.

Developed nations, urbanites, ivory collectors: the keystone consumer depends on the resource in question. In the case of water, agriculture accounts for 80% of use in the U.S., i.e. large-scale farms are the keystone consumers. So why do many conservation efforts focus on households rather than water efficiency on farms? The keystone consumer concept helps focus conservation efforts where returns on investments are highest.  

Like keystone species, keystone consumers also have a disproportionate impact relative to their abundance.  Biologists identify keystone species as conservation priorities because their disappearance could cause the loss of many other species. In the marketplace, keystone consumers should be priorities because their disappearance could lead to the recovery of the resource. Humans should protect keystone species and curb keystone consumption. The lives of others depend on it.

ARISE, or Adaptive Regression In the Service of the Ego, is a psychoanalytic concept recognized for decades, but little appreciated today. It is one of the ego functions which, depending on who you ask, may number anywhere from a handful to several dozen. They include reality testing, stimulus regulation, defensive function and synthetic integration. For simplicity, we can equate the ego with the self (though ARISS doesn't quite roll off the tongue).

In most fields, including psychiatry, regression is not considered a good thing. Regression implies a return to an earlier and inferior state of being and functioning. But the key here is not the regression, but rather whether the regression is maladaptive or adaptive.

There are numerous vital experiences that cannot be achieved without adaptive regression: The creation and appreciation of art, music, literature and food; the ability to sleep; sexual fulfillment; falling in love; and, yes, the ability to free associate and tolerate psychoanalysis or psychodynamic therapy without getting worse. Perhaps the most important element in adaptive regression is the ability to fantasize, to daydream. The person who has access to their unconscious processes and can mine them, without getting mired in them, can try new approaches, can begin to see things in new ways and, perhaps, can achieve mastery of their pursuits.

In a word: Relax.

It was ARISE that allowed Friedrich August Kekulé to use a daydream about a snake eating its tail as inspiration for his formulation of the structure of the benzene ring. It's what allowed Richard Feynman to simply drop an O-ring into a glass of ice water, show that when cold the ring is subject to distortion, and thereby explain the cause of the Space Shuttle Challenger disaster. Sometimes it takes a genius to see that a fifth grade science experiment is all that is needed to solve a problem.

In another word: Play.

Sometimes in order to progress you need to regress. Sometimes you just have to let go and ARISE.

The archenemy of scientific thinking is conversation. As in typical human conversational discourse, much of which is BS. Personally I have become rather fed up with talking to people. Seriously, it is something a problem. Fact is, folks are prone to getting pet opinions into their heads and then actually thinking they are true to the point of obstinacy, even when they have little or no idea of what they are talking about in the first place. We all do it. It is part of how the sloppy mind generating piece of meat between our ears we call the human brain is prone to work. Humans may be the most rational beings on the planet these days — but that's not saying much considering that the next most rational are chimpanzees.

Take creationism. Along with the global climate issue and parental fear of vaccination, the fact that a big chunk of the American body politic deny evolutionary and paleontological science and actually think a god created humans in near historical times is causing scientists to wonder just what is wrong with the thinking of so many people — mass creationism has been used as a classic example of mass anti-scientific thinking by others responding to this question. But I am not going to focus so much on the usual problem of why creationism is popular, but more on what many who promote science over creationism think they know about those who deny the reality of Darwin's theory.

A few years back an anti-creationist documentary came out, A Flock of Dodos. Nicely done in many regards, it scored some points against the anti-evolution crowd, and when it came to trying to explain why many Americans are repelled by evolution was way off base. The reason it was so wrong was because the creator of the film, Randy Olson, went to the wrong people to find out where the problem lies. A (seeming) highlight of the picture featured a bunch of poker playing Harvard evolutionary scientists gathered around a table to converse and opine on why the yahoos don't like the results of their research. This was a very bad mistake for the simple reason that evolutionary scientists are truly knowledgeable only about their area of expertise, evolutionary science.

If you really want to know why regular folk think the way they do then you go to the experts on that subject, sociologists. Because A Flock of Dodos never does that, its viewers never find out why creationism thrives in the age of science, and what needs to be done to tame the pseudoscientific beast.

This is not an idle problem. In the last decade big strides have been made in understanding the psychosociology of popular creationism — basically, it flourishes only in seriously dysfunctional societies, and the one sure why to suppress the errant belief is to run countries well enough that the religion creationism depends upon withers to minority status, dragging creationism down with it.

In other words better societies result in mass acceptance of evolution. Yet getting the word out is proving disturbingly difficult. So the chatty pet theories abut why creationism is a problem and what to do about it continue to dominant the national conversation, and pro-creationist opinion remains rock steady (although those who favor evolution without a God is rising along with the general increase of nonbelievers).

It's not just evolution. A classic example of conversational thinking by a scientist causing trouble was Linus Pauling's obsession with vitamin C. Many ordinary citizens are skeptical of scientists in general. When researchers offer up poorly sustained opinions on matters outside their firm knowledge base it does not help the general situation.

So what can be done? In principle it is simple enough. Scientists should be scientists. We should know better than to cough up committed but dubious opinion on subjects outside our expertise. This does not mean a given scientist has to limit their observations solely to their official field of research. Say a scientist is also a self-taught authority on baseball. By all means ardently discuss that subject the way Stephen Gould used to.

I have long had an intense interest in the myths of World War II, and can offer an excellent discourse on why the atom bombing of Hiroshima and Nagasaki had pretty much nothing to do with ending the war in case you are interested (it was the Soviet attack on Japan that forced Hirohito to surrender to save his war criminal's neck and keep Japan from being split into occupation zones like Germany and Korea). But if a scientist finds him or herself being asked about something they do not know a lot about either decline to opine, or qualify the observations by stating that the opinion is tentative and nonexpert.

In practical terms the problem is, of course, that scientists are human beings like everyone else. So I am not holding my breath waiting for us to achieve a level of factual discourse that will spread enlightenment to the masses. It's too bad but very human. I have tried to cut down on throwing out idle commentary without qualifying its questionable reality, while being ardent about my statements only when I know I can back them up. Me thinks I am fairly successful in this endeavor, and it does seem to keep me out of trouble.

Some people like to build sand castles, and some like to tear them apart. There can be much joy in the latter. But it is the former that interests me. You can take a bunch of minute silica crystals, pounded for thousands of years by the waves, use your hands, and make an ornate tower. Tiny physical forces govern how each particle interacts with its neighbors, keeping the castle together, at least until the force majeur of a foot appears.

But, having built the castle, this is the part that I like the most: you step back and look at it. Across the expanse of beach, here is something new, something not present before among the endless sand grains, something risen from the ground, something that reflects the scientific principle of holism.

Holism is colloquially summarized as "the whole is greater than the sum of its parts." What is interesting to me, however, are not the artificial instantiations of this principle — when we deliberately form sand into ornate castles or metal into airborne planes or ourselves into corporations — but rather the natural instantiations. The examples are widespread and stunning. Perhaps the most impressive one is that carbon, hydrogen, oxygen, nitrogen, sulfur, phosphorus, iron, and a few other elements, when mixed in just the right way, yield life. And life has emergent properties not present in — nor predictable from — these constituent parts. There is a kind of awesome synergy between the parts.

Hence, I think that the scientific concept that would improve everyone's cognitive toolkit is holism: the abiding recognition that wholes have properties not present in the parts and not reducible to the study of the parts.

For example, carbon atoms have particular, knowable physical and chemical properties. But the atoms can be combined in different ways to make, say, graphite or diamond. The properties of those substances — properties such as darkness and softness and clearness and hardness — are not properties of the carbon atoms, but rather properties of the collection of carbon atoms. Moreover, which particular properties the collection of atoms has depends entirely on how they are assembled — into sheets or pyramids. The properties arise because of the connections between the parts. I think grasping this insight is crucial for a proper scientific perspective on the world. You could know everything about isolated neurons and not be able to say how memory works, or where desire originates.

It is also the case that the whole has a complexity that rises faster than the number of its parts. Consider social networks as a simple illustration. If we have ten people in a group, there are a maximum of 10x9/2=45 possible connections between them. If we increase the number of people to 1,000, the number of possible ties increases to 1,000x999/2=499,500. So, while the number of people has increased by 100-fold (from 10 to 1,000), the number of possible ties (and hence, this one measure of the complexity of the system), has increased by over 10,000-fold.

Holism does not come naturally. It is an appreciation not of the simple, but of the complex, or at least of the simplicity and coherence in complex things. Moreover, unlike curiosity or empiricism, say, holism takes a while to acquire and to appreciate. It is a very grown-up disposition. Indeed, for the last few centuries, the Cartesian project in science has been to break matter down into ever smaller bits, in the pursuit of understanding. And this works, to some extent. We can understand matter by breaking it down to atoms, then protons and electrons and neutrons, then quarks, then gluons, and so on. We can understand organisms by breaking them down into organs, then tissues, then cells, then organelles, then proteins, then DNA, and so on.

But putting things back together in order to understand them is harder, and typically comes later in the development of a scientist or in the development of science. Think of the difficulties in understanding how all the cells in our bodies work together, as compared with the study of the cells themselves. Whole new fields of neuroscience and systems biology and network science are arising to accomplish just this. And these fields are arising just now, after centuries of stomping on castles in order to figure them out.

Although it seems obvious that there is a single "you" inside your head, research from several subdisciplines of psychology suggests that this is an illusion. The "you" who makes a seemingly rational and "self-interested" decision to discontinue a relationship with a friend who fails to return your phone calls, borrows thousands of dollars he doesn't pay back, and lets you pick up the tab in the restaurant is not the same "you" who makes very different calculations about a son, about a lover, or about a business partner.

Three decades ago cognitive scientist Colin Martindale advanced the idea that each of us has several subselves, and he connected his idea to emerging ideas in cognitive science. Central to Martindale's thesis were a few fairly simple ideas, such as selective attention, lateral inhibition, state-dependent memory, and cognitive dissociation. Although all the neurons in our brains are firing all the time, we'd never be able to put one foot in front of the other if we were unable to consciously ignore almost all of that hyperabundant parallel processing going on in the background. When you walk down the street there are thousands of stimuli to stimulate your already overtaxed brain — hundreds of different people of different ages with different accents, different hair colors, different clothes, different ways of walking and gesturing, not to mention all the flashing advertisements, curbs to avoid tripping over, and automobiles running yellow lights as you try to cross at the intersection. Hence, attention is highly selective. The nervous system accomplishes some of that selectiveness by relying on the powerful principle of lateral inhibition — in which one group of neurons suppresses the activity of other neurons that might interfere with an important message getting up to the next level of processing. In the eye, lateral inhibition helps us notice potentially dangerous holes in the ground, as the retinal cells stimulated by light areas send messages suppressing the activity of neighboring neurons, producing a perceived bump in brightness and valley of darkness near any edge. Several of these local "edge detector" style mechanisms combine at a higher level to produce "shape detectors" — allowing us to discriminate a "b" from a "d" and a "p." Higher up in the nervous system, several shape detectors combine to allow us to discriminate words, and at a higher level, to discriminate sentences, and at a still higher level, place those sentences in context (thereby discriminating whether the statement "Hi, how are you today?" is a romantic pass or a prelude to a sales pitch).

State dependent memory helps sort out all that incoming information for later use, by categorizing new info according to context — if you learn a stranger's name after drinking a doppio espresso at the local java house, it will be easier to remember that name if you meet again at Starbucks than if the next encounter is at a local pub after a martini. For several months after I returned from Italy, I would start speaking Italian and making expansive hand gestures every time I drank a glass of wine.

At the highest level, Martindale argued that all of those processes of inhibition and dissociation lead us to suffer from an everyday version of dissociative disorder. In other words, we all have a number of executive subselves, and the only way we manage to accomplish anything in life is to allow only one subself to take the conscious driver's seat at any given time.

Martindale developed his notion of executive subselves before modern evolutionary approaches to psychology had become prominent, but the idea becomes especially powerful if you combine Martindale's cognitive model with the idea of functional modularity. Building on findings that animals and humans use multiple — and very different — mental processes to learn different things, evolutionarily informed psychologists have suggested that there is not a single information-processing organ inside our heads, but instead multiple systems dedicated to solving different adaptive problems. Thus, instead of having a random and idiosyncratic assortment of subselves inside my head, different from the assortment inside your head, each of us has a set of functional subselves — one dedicated to getting along with our friends, one dedicated to self-protection (protecting us from the bad guys), one dedicated to winning status, another to finding mates, a distinct one for keeping mates (which is a very different set of problems, as some of us have learned), and yet another to caring for our offspring.

Thinking of the mind as composed of several functionally independent adaptive subselves helps us understand many seeming inconsistencies and irrationalities in human behavior, such as why a decision that seems "rational" when it involves one's son seems eminently irrational when it involves a friend or a lover, for example.

When I first took up the piano, merely hitting each note required my concentrated attention. With practice, however, I began to work in phrases and chords. Eventually I was able to produce much better music with much less conscious effort.

Evidently, something powerful had happened in my brain.

That sort of experience is very common, of course. Something similar occurs whenever we learn a new language, master a new game, or get comfortable in a new environment. It seems very likely that a common mechanism is involvedf. I think it's possible to identify, in broad terms, what that mechanism is: We create hidden layers.

The scientific concept of a hidden layer arose from the study of neural networks. Here a little picture is worth a thousand words:

In this picture, the flow of information runs from top to bottom. Sensory neurons — the eyeballs at the top — take input from the external world and encode it into a convenient form (which is typically electrical pulse trains for biological neurons, and numerical data for the computer "neurons" of artificial neural networks). They distribute this encoded information to other neurons, in the next layer below. Effector neurons — the stars at the bottom — send their signals to output devices (which are typically muscles for biological neurons, and computer terminals for artificial neurons). In between are neurons that neither see nor act upon the outside world directly. These inter-neurons communicate only with other neurons. They are the hidden layers.

The earliest artificial neural networks lacked hidden layers. Their output was, therefore, a relatively simple function of their input. Those two-layer, input-output "perceptrons" had crippling limitations. For example, there is no way to design a perceptron that, faced with pictures of a few black circles on a white background, counts the number of circles. It took until the 1980s, decades after the pioneering work, for people to realize that including even one or two hidden layers could vastly enhance the capabilities of their neural networks. Nowadays such multilayer networks are used, for example, to distill patterns from the explosions of particles that emerge from high-energy collisions at the Large Hadron Collider. They do it much faster and more reliably than humans possibly could.

David Hubel and Torstein Wiesel were awarded the 1981 Nobel Prize in physiology or medicine for figuring out what neurons in the visual cortex are doing. They showed that successive hidden layers first extract features of visual scenes that are likely to be meaningful (for example, sharp changes in brightness or color, indicating the boundaries of objects), and then assemble them into meaningful wholes (the underlying objects).

In every moment of our adult waking life, we translate raw patterns of photons impacting our retinas — photons arriving every which way from a jumble of unsorted sources, and projected onto a two-dimensional surface — into the orderly, three-dimensional visual world we experience. Because it involves no conscious effort, we tend to take that everyday miracle for granted. But when engineers tried to duplicate it, in robotic vision, they got a hard lesson in humility. Robotic vision remains today, by human standards, primitive. Hubel and Wiesel exhibited the architecture of Nature's solution. It is the architecture of hidden layers.

Hidden layers embody, in a concrete physical form, the fashionable but rather vague and abstract idea of emergence. Each hidden layer neuron has a template. It becomes activated, and sends signals of its own to the next layer, precisely when the pattern of information it's receiving from the preceding layer matches (within some tolerance) that template. But this is just to say, in precision-enabling jargon, that the neuron defines, and thus creates, a new emergent concept.

In thinking about hidden layers, it's important to distinguish between the routine efficiency and power of a good network, once that network has been set up, and the difficult issue of how to set it up in the first place. That difference is reflected in the difference between playing the piano, say, or riding a bicycle, or swimming, once you've learned (easy), and learning to do those things in the first place (hard). Understanding exactly how new hidden layers get laid down in neural circuitry is a great unsolved problem of science. I'm tempted to say it's the greatest.

Liberated from its origin in neural networks, the concept of hidden layers becomes a versatile metaphor, with genuine explanatory power. For example, in my own work in physics I've noticed many times the impact of inventing names for things. When Murray Gell-Mann invented "quarks", he was giving a name to a paradoxical pattern of facts. Once that pattern was recognized, physicists faced the challenge of refining it into something mathematically precise and consistent; but identifying the problem was the crucial step toward solving it! Similar, when I invented "anyons" I knew I had put my finger on a coherent set of ideas, but I hardly anticipated how wonderfully those ideas would evolve and be embodied in reality. In cases like this, names create new nodes in hidden layers of thought.

I'm convinced that the general concept of hidden layers captures deep aspects of the way minds — whether human, animal, or alien; past, present, or future — do their work. Minds mobilize useful concepts by embodying them in a specific way, namely as features recognized by hidden layers. And isn't it pretty that "hidden layers" is itself a most useful concept, worthy to be included in hidden layers everywhere?

Barbara McClintock was ignored and ridiculed, by the scientific community, for thirty-two years before winning a Nobel Prize in 1984, for discovering "jumping genes." During the years of hostile treatment by her peers, McClintock didn't publish, preferring to avoid the rejection of the scientific community. Stanley Prusiner faced significant criticism from his colleagues until his prion theory was confirmed. He, too, went on to win a Nobel Prize in 1982.

Barry Marshall challenged the medical "fact" that stomach ulcers were caused by acid and stress; and presented evidence that H. Pylori bacteria is the cause. Marshall is quoted as saying, "Everyone was against me."

Progress in medicine was delayed while these "projective thinkers" persisted, albeit on a slower and lonelier course.

Projective thinking is a term coined by Edward de Bono to describe generative rather than reactive thinking. McClintock, Prusiner, and Marshall offered projective thinking; suspending their disbelief regarding accepted scientific views at the time.

Articulate, intelligent individuals can skillfully construct a convincing case to argue almost any point of view. This critical, reactive use of intelligence narrows our vision. In contrast, projective thinking is expansive, "open-ended" and speculative, requiring the thinker to create the context, concepts, and the objectives.

Twenty years of studying maize created a context within which McClintock could speculate. With her extensive knowledge and keen powers of observation, she deduced the significance of the changing color patterns of maize seed. This led her to propose the concept of gene regulation, which challenged the theory of the genome as a static set of instructions passed from one generation to the next.

The work McClintock first reported in 1950, the result of projective thinking, extensive research, persistence, and a willingness to suspend disbelief, wasn't understood or accepted until many years later.

Everything we know, our strongly held beliefs, and, in some cases, even what we consider to be "factual," creates the lens through which we see and experience the world, and can contribute to a critical, reactive orientation. This can serve us well: Fire is hot; it can burn if touched. It can also compromise our ability to observe and to think in an expansive, generative way.

When we cling rigidly to our constructs, as McClintock's peers did, we can be blinded to what's right in front of us. Can we support a scientific rigor that embraces generative thinking and suspension of disbelief? Sometimes science fiction does become scientific discovery.

The exponential explosion of information and our ability to access it make our ability to validate its truthfulness not only more important but also more difficult. Information has importance in proportion to its relevance and meaning. Its ultimate value is how we use it to make decisions and put it in a framework of knowledge

Our perceptions are crucial in appreciating truth. However, we do not apprehend objective reality. Perception is based on recognition and interpretation of sensory stimuli derived from patterns of electrical impulses. From this data, the brain creates analogues and models that simulate tangible, concrete objects in the real world. Experience, though, colors and influences all of our perceptions by anticipating and predicting everything we encounter and meet. It is the reason Goethe advised that "one must ask children and birds how cherries and strawberries taste." This preferential set of intuitions, feelings, and ideas, less poetically characterized by the term bias, poses a challenge to the ability to weigh evidence accurately to arrive at truth. Bias is the non-dispassionate thumb which experience puts on the scale.

Our brains evolved having to make the right bet with limited information. Fortune, it has been said, favors the prepared mind. Bias in the form of expectation, inclination and anticipatory hunches helped load the dice in our favor and for that reason is hardwired into our thinking.

Bias is an intuition, sensitivity, receptiveness which acts as a lens or filter on all our perceptions. "If the doors of perception were cleansed," Blake said, "everything would appear to man as it is, infinite." But without our biases to focus our attention, we would be lost in that endless and limitless expanse. We have at our disposal an immeasurable assortment of biases and their combination in each of us is as unique as a fingerprint. These biases mediate between our intellect and emotions to help congeal perception into opinion, judgment, category, metaphor, analogy, theory, and ideology which frame how we see the world.

Bias is tentative. Bias adjusts as the facts change. Bias is a provisional hypothesis. Bias is normal.

Although bias is normal in the sense that it is a product of how we select and perceive information, its influence on our thinking cannot be ignored. Medical science has long been aware of the inherent bias, which occurs in collecting and analyzing clinical data. The double blind, randomized controlled study, the gold standard of clinical design, was developed in an attempt to nullify its influence.

We live in the world, however, not in a laboratory and bias cannot be eliminated. Bias critically utilized sharpens the collection of data by knowing when to look, where to look, and how to look. It is fundamental to both inductive and deductive reasoning. Darwin didn't collect his data to formulate the theory of evolution randomly or disinterestedly. Bias is the nose for the story.

Truth needs continually to be validated against all evidence, which challenges it fairly and honestly. Science with its formal methodology of experimentation and reproducibility of its findings is available to anyone who plays by its rules. No ideology, religion, culture or civilization is awarded special privileges or rights. The truth, which survives this ordeal, has another burden to bear. Like the words in a multi-dimensional crossword puzzle, it has to fit together with all the other pieces already in place. The better and more elaborate the fit, the more certain the truth. Science permits no exceptions. It is inexorably revisionary, learning from its mistakes, erasing and rewriting, even their most sacred texts, until the puzzle is complete.

The notion of uncertainty is perhaps the least well understood concept in science. In the public parlance, uncertainty is a bad thing, implying a lack of rigor and predictability. The fact that global warming estimates are uncertain, for example, has been used by many to argue against any action at the present time.

In fact, however, uncertainty is a central component of what makes science successful. Being able to quantify uncertainty, and incorporate it into models, is what makes science quantitative, rather than qualitative. Indeed, no number, to measurement, no observable in science is exact. Quoting numbers without attaching an uncertainty to them implies they have, in essence, no meaning.

One of the things that makes uncertainty difficult for members of the public to appreciate is that the significance of uncertainty is relative. Take, for example, the distance between the earth and sun, 1.49597 x 108 km. This seems relatively precise, after all using six significant digits means I know the distance to an accuracy of one part in a million or so. However, if the next digit is uncertain, that means the uncertainty in knowing the precise earth-sun distance is larger than the distance between New York and Chicago!

Whether or not the quoted number is 'precise' therefore depends upon what I am intending to do with it. If I only care about what minute the Sun will rise tomorrow then the number quoted above is fine. If I want to send a satellite to orbit just above the Sun, however, then I would need to know distances more accurately.

This is why uncertainty is so important. Until we can quantify the uncertainty in our statements and our predictions, we have little idea of their power or significance. So too in the public sphere. Public policy performed in the absence of understanding quantitative uncertainties, or even understanding the difficulty of obtaining reliable estimates of uncertainties usually means bad public policy.

One of the most general shorthand abstractions that if adopted would improve the cognitive toolkit of humanity is to think bottom up, not top down. Almost everything important that happens in both nature and in society happens from the bottom up, not the top down. Water is a bottom up, self-organized emergent property of hydrogen and oxygen. Life is a bottom up, self-organized emergent property of organic molecules that coalesced into protein chains through nothing more than the input of energy into the system of Earth's early environment. The complex eukaryotic cells of which we are made are themselves the product of much simpler prokaryotic cells that merged together from the bottom up in a process of symbiosis that happens naturally when genomes are merged between two organisms. Evolution itself is a bottom up process of organisms just trying to make a living and get their genes into the next generation; out of that simple process emerges the diverse array of complex life we see today.

Analogously, an economy is a self-organized bottom up emergent process of people just trying to make a living and get their genes into the next generation, and out of that simple process emerges the diverse array of products and services available to us today. Likewise, democracy is a bottom up emergent political system specifically designed to displace top down kingdoms, theocracies, and dictatorships. Economic and political systems are the result of human action, not human design.

Most people, however, see the world from the top down instead of the bottom up. The reason is that our brains evolved to find design in the world, and our experience with designed objects is that they have a designer (us) who we consider to be intelligent. So most people intuitively sense that anything in nature that looks designed must be so from the top down, not the bottom up. Bottom up reasoning is counter intuitive. This is why so many people believe that life was designed from the top down, and why so many think that economies must be designed and that countries should be ruled from the top down.

One way to get people to adopt the bottom up shorthand abstraction as a cognitive tool is to find examples that we know evolved from the bottom up and were not designed from the top down. Language is an example. No one designed English to look and sound like it does today (in which teenagers use the word "like" every sentence). From Chaucer's time forward our language has evolved from the bottom up by native speakers adopting their own nuanced styles to fit their unique lives and cultures. Likewise, the history of knowledge production has been one long trajectory from top down to bottom up. From ancient priests and medieval scholars to academic professors and university publishers, the democratization of knowledge has struggled alongside the democratization of societies to free itself from the bondage of top down control. Compare the magisterial multi-volume encyclopedias of centuries past that held sway as the final authority for reliable knowledge, now displaced by individual encyclopedists employing wiki tools and making everyone their own expert.

Which is why the Internet is the ultimate bottom up self-organized emergent property of millions of computer users exchanging data across servers, and although there are some top-down controls involved—just as there are some in mostly bottom-up economic and political systems—the strength of digital freedom derives from the fact that no one is in charge. For the past 500 years humanity has gradually but ineluctably transitioned from top down to bottom up systems, for the simple reason that both information and people want to be free.

People like to think of technologies and media as neutral and that only their use or content determines their impact. Guns don't kill people, after all, people kill people. But guns are much more biased toward killing people than, say, pillows — even though many a pillow has been utilized to smother an aging relative or adulterous spouse.

Our widespread inability to recognize or even acknowledge the biases of the technologies we use renders us incapable of gaining any real agency through them. We accept our iPads, Facebook accounts and automobiles at face value — as pre-existing conditions — rather than tools with embedded biases.

Marshall McLuhan exhorted us to recognize that our media have impacts on us beyond whatever content is being transmitted through them. And while his message was itself garbled by the media through which he expressed it (the medium is the what?) it is true enough to be generalized to all technology. We are free to use any car we like to get to work — gasoline, diesel, electric, or hydrogen — and this sense of choice blinds us to the fundamental bias of the automobile towards distance, commuting, suburbs, and energy consumption.

Likewise, soft technologies from central currency to psychotherapy are biased in their construction as much as their implementation. No matter how we spend US dollars, we are nonetheless fortifying banking and the centralization of capital. Put a psychotherapist on his own couch and a patient in the chair, and the therapist will begin to exhibit treatable pathologies. It's set up that way, just as Facebook is set up to make us think of ourselves in terms of our "likes" and an iPad is set up to make us start paying for media and stop producing it ourselves.

If the concept that technologies have biases were to become common knowledge, we would put ourselves in a position to implement them consciously and purposefully. If we don't bring this concept into general awareness, our technologies and their effects will continue to threaten and confound us.

Given recent research about brain plasticity and the dangers of cognitive load, the most powerful tool in our cognitive arsenal may well be design.
Specifically, we can use design principles and discipline to shape our minds. This is different than learning and acquiring knowledge. It's about designing how each of us thinks, remembers and communicates — appropriately and effectively for the digital age.

Today's popular handwringing about its effects on cognition has some merit. But rather than predicting a dire future, perhaps we should be trying to achieve a new one.

New neuroscience discoveries give hope. We know that brains are malleable and can change depending on how they are used. The well-known study of London taxi drivers showed that a certain region in the brain involved in memory formation was physically larger than in non-taxi-driving individuals of a similar age. This effect did not extend to London bus drivers, supporting the conclusion that the requirement of London's taxi drivers to memorize the multitude of London streets drove structural brain changes in the hippocampus.

Results from studies like these support the notion that even among adults the persistent, concentrated use of one neighborhood of the brain real can increase its  size, and presumably also its capacity. Not only does intense use change adult brain regional structure and function, but temporary training and perhaps even mere mental rehearsal seem to have an effect as well. A series of studies showed that one can improve tactile (Braille character) discrimination among seeing people who are temporarily blindfolded. Brain scans revealed that participants' visual cortex responsiveness was heightened to auditory and tactile sensory input after only five days of blindfolding for over an hour each time.

The existence of lifelong neuroplasticity is no longer in doubt. The brain runs on a "use it or lose it" motto. So could we "use it to build it right?" Why don't we use the demands of our information-rich, multi-stimuli, fast-paced, multi-tasking, digital existence to expand our cognitive capability? Psychiatrist Dr. Stan Kutcher, an expert on adolescent mental health who has studied the effect of digital technology on brain development, says we probably can: "There is emerging evidence suggesting that exposure to new technologies may push the Net Generation [teenagers and young adults] brain past conventional capacity limitations."

When the straight A student is doing her homework at the same time as five other things online, she is not actually multi-tasking. Instead, she has developed better active working memory and better switching abilities. I can't read my email and listen to iTunes at the same time, but she can. Her brain has been wired to handle the demands of the digital age.

How could we use design thinking to change the way we think?  Good design typically begins with some principles and functional objectives. You might aspire to have a strong capacity to perceive and absorb information effectively, concentrate, remember, infer meaning, be creative, write, speak and communicate well, and to enjoy important collaborations and human relationships. How could you design your use (or abstinence) of media to achieve these goals?

Something as old-school as a speed-reading course could increase your input capacity without undermining comprehension. If it made sense in Evelyn Woods' day it is doubly important now and we've learned a lot since her day about how to read effectively.

Feeling distracted? The simple discipline of reading a few full articles per day rather than just the headlines and summaries could strengthen attention.

Want to be a surgeon? Become a gamer or rehearse while on the subway. Rehearsal can produce changes in the motor cortex as big as those induced by physical movement. One study a group of participants were asked to play a simple five-finger exercise on the piano while another group of participants were asked to think about playing the same "song" in their heads using the same finger movements, one note at a time. Both groups showed a change in their motor cortex, with differences among the group who mentally rehearsed the song as great as those who physically played the piano.

Losing retention? Decide how far you want to adopt Alfred Einstein's law of memory. When asked why he went to the phone book to get his number he replied that he only memorizes things he can't look up. There is a lot to remember these days. Between the dawn of civilization and 2003 there were 5 exabytes of data collected (an exabyte equals 1 quintillion bytes). Today 5 exabytes of data gets collected every two days! Soon there will be 5 exabytes every few minutes. Humans have a finite memory capacity. Can you develop criteria for which will be inboard and outboard?

Or want to strengthen your working memory and capability to multitask? Try reverse mentoring — learning with your teenager. This is the first time in history when children are authorities about something important, and the successful ones are pioneers of a new paradigm in thinking. Extensive research shows that people can improve cognitive function and brain efficiency through simple lifestyle changes, such as incorporating memory exercises into their daily routine.

Why don't schools and universities teach design thinking for thinking? We teach physical fitness. But rather than brain fitness we emphasize cramming young heads with information and testing their recall. Why not courses that emphasize designing a great brain?

Does this modest proposal raise the specter of "designer minds?" I don't think so. The design industry is something done to us. I'm proposing we each become designers. But I suppose "I love the way she thinks" could take on new meaning.

Most people tend to think of science in one of two ways. It is a body of knowledge and understanding about the world: gravity, photosynthesis and evolution. Or it is the technology that has emerged from the fruits of that knowledge: vaccines, computers and cars. Science is both of these things, yet as Carl Sagan so memorably explained in The Demon-Haunted World, it is something else besides. It is a way of thinking, the best approach yet devised (if still an imperfect one) to discovering progressively better approximations of how things really are.

Science is provisional, always open to revision in light of new evidence. It is anti-authoritarian: anybody can contribute, and anybody can be wrong. It seeks actively to test its propositions. And it is comfortable with uncertainty. These qualities give the scientific method unparalleled strength as a way of finding things out. Its power, however, is too often confined to an intellectual ghetto: those disciplines that have historically been considered "scientific".

Science as a method has great things to contribute to all sorts of pursuits beyond the laboratory. Yet it remains missing in action from far too much of public life. Politicians and civil servants too seldom appreciate how tools drawn from both the natural and social sciences can be used to design more effective policies, and even to win votes.
In education and criminal justice, for example, interventions are regularly undertaken without being subjected to proper evaluation. Both fields can be perfectly amenable to one of science's most potent techniques — the randomised controlled trial — yet these are seldom required before new initiatives are put into place. Pilots are often derisory in nature, failing even to collect useful evidence that could be used to evaluate a policy's success.

Sheila Bird of the Medical Research Council, for instance, has criticised the UK's introduction of a new community sentence called the Drug Treatment and Testing Order, following pilots designed so poorly as to be worthless. They included too few subjects; they were not randomised; they did not properly compare the orders with alternatives; and judges were not even asked to record how they would otherwise have sentenced offenders.

The culture of public service could also learn from the self-critical culture of science. As Jonathan Shepherd, of the University of Cardiff, has pointed out, policing, social care and education lack the cadre of practitioner-academics that has served medicine so well. There are those who do, and there are those who research: too rarely are they the same people. Police officers, teachers and social workers are simply not encouraged to examine their own methods in the same way as doctors, engineers and bench scientists. How many police stations run the equivalent of a journal club?

The scientific method and the approach to critical thinking it promotes are too useful to be kept back for "science" alone. If it can help us to understand the first microseconds of creation and the structure of the ribosome, it can surely improve understanding of how best to tackle the pressing social questions of our time.

One very old and pervasive habit of thought is to imagine that the true answer to whatever question we are wondering about lies out there in some eternal domain of "timeless truths." The aim of re-search is then to "discover" the answer or solution in that already existing timeless domain. For example, physicists often speak as if the final theory of everything already exists in a vast timeless Platonic space of mathematical objects. This is thinking outside of time.

Scientists are thinking in time when we conceive of our task as the invention of genuinely novel ideas to describe newly discovered phenomena, and novel mathematical structures to express them. If we think outside of time, we believe these ideas somehow "existed" before we invented them. If we think in time we see no reason to presume that.

The contrast between thinking in time and thinking outside of time can be seen in many domains of human thought and action. We are thinking outside of time when, faced with a technological or social problem to solve, we assume the possible approaches are already determined by a set of absolute pre-existing categories. We are thinking in time when we understand that progress in technology, society and science happens by the invention of genuinely novel ideas, strategies, and novel forms of social organization.

The idea that truth is timeless and resides outside the universe was the essence of Plato's philosophy, exemplified in the parable of the slave boy that was meant to argue that discovery is merely remembering. This is reflected in the philosophy of mathematics called Platonism, which is the belief that there are two ways of existing. Regular physical things exist in the universe and are subject to time and change, while mathematical objects exist in a timeless realm. The division of the world into a time-drenched Earthly realm of life, death, change and decay, surrounded by a heavenly sphere of perfect eternal truth, framed both ancient science and Christian religion.

If we imagine that the task of physics is the discovery of a timeless mathematical object that is isomorphic to the history of the world, then we imagine that the truth to the universe lies outside the universe. This is such a familiar habit of thought that we fail to see its absurdity: if the universe is all that exists then how can something exist outside of it for it to be isomorphic to?

On the other hand, if we take the reality of time as evident, then there can be no mathematical object that is perfectly isomorphic to the world, because one property of the real world that is not shared by any mathematical object is that it is always some moment. Indeed, as Charles Sanders Pierce first observed, the hypothesis that the laws of physics evolved through the history of the world is necessary if we are to have a rational understanding of why one particular set of laws hold, rather than others.

Thinking outside of time often implies the existence of an imagined realm outside the universe where the truth lies. This is a religious idea, because it means that explanations and justifications ultimately refer to something outside of the world we experience ourselves to be a part of. If we insist there is nothing outside the universe, not even abstract ideas or mathematical objects, we are forced to find the causes of phenomena entirely within our universe. So thinking in time is also thinking within the one universe of phenomena our observations show us to inhabit.

Among contemporary cosmologists and physicists, proponents of eternal inflation and timeless quantum cosmology are thinking outside of time. Proponents of evolutionary and cyclic cosmological scenarios are thinking in time. If you think in time you worry about time ending at space-time singularities. If you think outside of time this is an ignorable problem because you believe reality is the whole history of the world at once.

Darwinian evolutionary biology is the prototype for thinking in time because at its heart is the realization that natural processes developing in time can lead to the creation of genuinely novel structures. Even novel laws can emerge when the structures to which they apply come to exist. Evolutionary dynamics has no need of abstract and vast spaces like all the possible viable animals, DNA sequences, sets of proteins, or biological laws. Exaptations are too unpredictable and too dependent on the whole suite of living creatures to be analyzed and coded into properties of DNA sequences. Better, as Stuart Kauffman proposes, to think of evolutionary dynamics as the exploration, in time, by the biosphere, of the adjacent possible.

The same goes for the evolution of technologies, economies and societies. The poverty of the conception that economic markets tend to unique equilibria, independent of their histories, shows the danger of thinking outside of time. Meanwhile the path dependence that Brian Arthur and others show is necessary to understand real markets illustrates the kind of insights that are gotten by thinking in time.

Thinking in time is not relativism, it is a form of relationalism. Truth can be both time bound and objective, when it is about objects that only exist once they are invented, by evolution or human thought.

When we think in time we recognize the human capacity to invent genuinely novel constructions and solutions to problems. When we think about the organizations and societies we live and work in outside of time we unquestioningly accept their strictures, and seek to manipulate the levers of bureaucracy as if they had an absolute reason to be there. When we think about organizations in time we recognize that every feature of them is a result of their history and everything about them is negotiable and subject to improvement by the invention of novel ways of doing things.

An important part of my scientific toolkit is how to think about things in the world over a wide range of magnitudes and time scales. This involves first understanding powers of ten; second, visualizing data over a wide range of magnitudes on graphs using logarithmic scales; and third, appreciating the meaning of magnitude scales such as the decibel (dB) scale for the loudness of sounds and the Richter scale for the strengths of earthquakes.

This toolkit ought to be a part of everyone thinking, but sadly I have found that even well educated nonscientists are flummoxed by log scales and can only vaguely grasp the difference between an earthquake on a Richter scale of 6 and 8 (a thousand times more energy released). Thinking in powers of 10 is such a basic skill that it ought to be taught along with integers in elementary school.

Scaling laws are found throughout nature. Galileo in 1638 pointed out that large animals have disproportionately thicker leg bones than small animals to support the weight of the animal. The heavier the animal, the more stout their legs need to be. This leads to a prediction that the thickness of the leg bone should scale with the 3/2 power of the length of the bone.

Another interesting scaling law is that between the volume of the cortical white matter, corresponding to the long-distance wires between cortical areas, and the gray matter, where the computing takes place. For mammals ranging over 5 orders of magnitude in weight from a pygmy shrew to an elephant, the white matter scales as the 5/4 power of the gray matter. This means that the bigger the brain, the disproportionately larger the fraction of the volume taken up by cortical wiring used for communication compared to the computing machinery.

I am concerned that students I teach have lost the art of estimating with powers of 10. When I was a student I used a slide rule to compute, but students now use calculators. A slide rule lets you carry out a long series of multiplications and divisions by adding and subtracting the logs of numbers; but at the end you need to figure out the powers of 10 by making a rough estimate. A calculator keeps track of this for you, but if you make a mistake in keying in a number you can be off by 10 orders of magnitude, which happens to students who don't have a feeling for orders of magnitude.

A final reason why familiarity with powers of 10 would improve everyone's cognitive toolkit is that it helps us comprehend our life and the world in which we live:

How many seconds are there in a lifetime? 109 sec

A second is an arbitrary time unit, but one that is based on our experience. Our visual system is bombarded by snapshots at a rate of around 3 per second caused by rapid eye movements called saccades. Athletes often win or lose a race by a fraction of a second. If you earned a dollar for every second in your life you would be a billionaire. However, a second can feel like a minute in front of an audience and a quiet weekend can disappear in a flash. As a child, a summer seemed to last forever, but as an adult, summer is over almost before it begins. William James speculated that subjective time was measured in novel experiences, which become rarer as you get older. Perhaps life is lived on a logarithmic time scale, compressed toward the end.

What is the GDP of the world? $1014

A billion dollars was once worth a lot, but there is now a long list of multibillionaires. The US government recently stimulated the world economy by loaning several trillion dollars to banks. It is difficult to grasp how much a trillion dollars ($10[12] ) represents, but several clever videos on YouTube (key words: trillion dollars) illustrate this with physical comparisons (a giant pile of $100 bills) and what you can buy with it (10 years of US response to 9/11). When you start thinking about the world economy, the trillions of dollars add up. A trillion here, a trillion there, pretty soon your talking about real money. But so far there aren't any trillionaires.

How many synapses are there in the brain? 1015

Two neurons can communicate with each other at a synapse, which is the computational unit in the brain. The typical cortical synapse is less than a micron in diameter (10[-6] meter), near the resolution limit of the light microscope. If the economy of the world is a stretch for us to contemplate, thinking about all the synapses in your head is mind boggling. If I had a dollar for every synapse in your brain I could support the current economy of the world for 10 years. Cortical neurons on average fire once a second, which implies a bandwidth of around 10[15] bits per second, greater than the total bandwidth of the internet backbone.

How many seconds will the sun shine? 1017 sec

Our sun has shined for billions of years and will continue to shine for billions more. The universe seems to be standing still during our lifetime, but on longer time scales the universe is filled with events of enormous violence. The spatial scales are also immense. Our space-time trajectory is a very tiny part of the universe, but we can at least attach powers of 10 to it and put it into perspective.

Mistakes, errors, false starts — accept them all. The basis of creativity.

My reference point (as a playwright, not a scientist) was Keat's notion of negative capability (from his letters). Being able to exist with lucidity and calm amidst uncertainty, mystery and doubt, without "irritable (and always premature) reaching out" after fact and reason.

This toolkit notion of negative capability is a profound therapy for all manner of ills — intellectual, psychological, spiritual and political. I reflect it (amplify it) with Emerson's notion that "Art (any intellectual activity?) is (best thought of as but) the path of the creator to his work."

Bumpy, twisting roads. (New York City is about to repave my cobblestone street with smooth asphalt. Evil bureaucrats and tunnel-visioned 'scientists" — fast cars and more tacky up-scale stores in Soho.)

Wow! I'll bet my contribution is shorter than anyone else's. Is this my inadequacy or an important toolkit item heretofore overlooked?

Everyone is familiar with Digital Code, or the shorthand IT. Soon all may be discoursing about Life Code…

It took a while to learn how to read life code; Mendel's initial cookbook was largely ignored. Darwin knew but refused, for decades, to publish such controversial material. Even a term that now lies within every cheesy PR description of a firm, on jeans, and pop psych books…DNA… was largely ignored after its 1953 discovery. For close to a decade very few cited Watson and Crick. They were not even nominated, by anyone, for a Nobel till after 1960, despite the discovery of how life code is written.

First ignorance then controversy continued dogging life code as humanity moved from reading it to copying it. Tadpoles were cloned in 1952, but few focused until Dolly the sheep begat wonder, consternation, and fear. Much the same occurred with in vitro fertilization and Louise Brown, a breakthrough that got the Nobel in 2010, a mere 37 years after the first birth. Copying genes and dozens of species, leading to hundreds of thousands of almost identical animals is now commonplace. The latest controversy is no longer how do we deal with rare clones but should we eat them.

Much has occurred as we learned to read and copy life code, but there is still little understanding for what has occurred recently. But it is this third stage of life code, writing and re-writing, is by far the most important and profound change. 

Few realize, so far, that life code is spreading across industries, economies, countries, and cultures. As we begin to rewrite existing life, strange things evolve. Bacteria can be programmed to solve Sudoku puzzles. Viruses begin to create electronic circuits. As we write life from scratch, Venter, Smith et al. partner with Exxon to try to change the world's energy markets. Designer genes introduced by retroviruses, organs built from scratch, the first synthetic cells further examples of massive change.

We see more and more products, derived from life code, changing fields as diverse as energy, textiles, chemicals, IT, vaccines, medicines, space exploration, agriculture, fashion, finance, and real estate. And gradually, "life code" a concept that only got 559 Goggle hits in 2000, and fewer than 50,000 in 2009, becomes a part of the everyday public discourse.

Many of the Fortune 500 within the next decade will be companies based on the understanding and application of life code, much as has occurred over the past decades with digital code leading to the likes of Digital, Lotus, HP, IBM, Microsoft, Amazon, Google, and Facebook.

But this is just the beginning. The real change will become apparent as we re-write life code to morph the human species. We are already transitioning from a humanoid that is shaped by and shapes its own environment into a Homo evolutis, a species that directly and deliberately designs and shapes its own evolution and that of other species…

Our perceptions are neither true nor false. Instead, our perceptions of space and time and objects, the fragrance of a rose, the tartness of a lemon, are all a part of our "sensory desktop," which functions much like a computer desktop.

Graphical desktops for personal computers have existed for about three decades. Yet they are now such an integral part of daily life that we might easily overlook a useful concept that they embody. A graphical desktop is a guide to adaptive behavior. Computers are notoriously complex devices, more complex than most of us care to learn. The colors, shapes and locations of icons on a desktop shield us from the computer's complexity, and yet they allow us to harness its power by appropriately informing our behaviors, such as mouse movements and button clicks, that open, delete and otherwise manipulate files. In this way, a graphical desktop is a guide to adaptive behavior.

Graphical desktops make it easier to grasp the idea that guiding adaptive behavior is different than reporting truth. A red icon on a desktop does not report the true color of the file it represents. Indeed, a file has no color. Instead, the red color guides adaptive behavior, perhaps by signaling the relative importance or recent updating of the file. The graphical desktop guides useful behavior, and hides what is true but not useful. The complex truth about the computer's logic gates and magnetic fields is, for the purposes of most users, of no use.

Graphical desktops thus make it easier to grasp the nontrivial difference between utility and truth. Utility drives evolution by natural selection. Grasping the distinction between utility and truth is therefore critical to understanding a major force that shapes our bodies, minds and sensory experiences.

Consider, for instance, facial attractiveness. When we glance at a face we get an immediate feeling of its attractiveness, a feeling that usually falls somewhere between hot and not. That feeling can inspire poetry, evoke disgust, or launch a thousand ships. It certainly influences dating and mating. Research in evolutionary psychology suggests that this feeling of attractiveness is a guide to adaptive behavior. The behavior is mating, and the initial feeling of attractiveness towards a person is an adaptive guide because it correlates with the likelihood that mating with that person will lead to successful offspring.

Just as red does not report the true color of a file, so hotness does not report the true feeling of attractiveness of a face: Files have no intrinsic color, faces have no intrinsic feeling of attractiveness. The color of an icon is an artificial convention to represent aspects of the utility of a colorless file. The initial feeling of attractiveness is an artificial convention to represent mate utility.

The phenomenon of synesthesia can help to understand the conventional nature of our sensory experiences. In many cases of synesthesia, a stimulus that is normally experienced in one way, say as a sound, is also automatically experienced in another way, say as a color. Someone with sound-color synesthesia sees colors and simple shapes whenever they hear a sound. The same sound always occurs with the same colors and shapes. Someone with taste-touch synesthesia feels touch sensations in their hands every time they taste something with their mouth. The same taste always occurs with the same feeling of touch in their hands. The particular connections between sound and color that one sound-color synesthete experiences typically differ from the connections experienced by another such synesthete. In this sense, the connections are an arbitrary convention. Now imagine a sound-color synesthete who no longer has sound experiences to acoustic stimuli, and instead has only their synesthetic color experiences. Then this synesthete would only experience as colors what the rest of us experience as sounds. In principle they could get all the acoustic information the rest of us get, only in a color format rather than a sound format.

This leads to the concept of a sensory desktop. Our sensory experiences, such as vision, sound, taste and touch, can all be thought of as sensory desktops that have evolved to guide adaptive behavior, not to report objective truths. As a result, we should take our sensory experiences seriously. If something tastes putrid, we probably shouldn't eat it. If it sounds like a rattlesnake, we probably should avoid it. Our sensory experiences have been shaped by natural selection to guide such adaptive behaviors.

We must take our sensory experiences seriously, but not literally. This is one place where the concept of a sensory desktop is helpful. We take the icons on a graphical desktop seriously; we won't, for instance, carelessly drag an icon to the trash, for fear of losing a valuable file. But we don't take the colors, shapes or locations of the icons literally. They are not there to resemble the truth. They are there to facilitate useful behaviors.

Sensory desktops differ across species. A face that could launch a thousand ships probably has no attraction to a macaque monkey. The rotting carrion that tastes putrid to me might taste like a delicacy to a vulture. My taste experience guides behaviors appropriate for me: Eating rotten carrion could kill me. The vulture's taste experience guides behaviors appropriate to it: Carrion is its primary food source.

Much of evolution by natural selection can be understood as an arms race between competing sensory desktops. Mimicry and camouflage exploit limitations in the sensory desktops of predators and prey. A mutation that alters a sensory desktop to reduce such exploitation conveys a selective advantage. This cycle of exploiting and revising sensory desktops is a creative engine of evolution.

On a personal level, the concept of a sensory desktop can enhance our cognitive toolkit by refining our attitude towards our own perceptions. It is common to assume that the way I see the world is, at least in part, the way it really is. Because, for instance, I experience a world of space and time and objects, it is common to assume that these experiences are, or at least resemble, objective truths. The concept of a sensory desktop reframes all this. It loosens the grip of sensory experiences on the imagination. Space, time and objects might just be aspects of a sensory desktop that is specific to Homo sapiens. They might not be deep insights into objective truths, just convenient conventions that have evolved to allow us to survive in our niche. Our desktop is just a desktop.

There is a widely used notion that does plenty of damage: the notion of "scientifically proven". Nearly an oxymoron. The very foundation of science is to keep the door open to doubt. Precisely because we keep questioning everything, especially our own premises, we are always ready to improve our knowledge. Therefore a good scientist is never 'certain'. Lack of certainty is precisely what makes conclusions more reliable than the conclusions of those who are certain: because the good scientist will be ready to shift to a different point of view if better elements of evidence, or novel arguments emerge. Therefore certainty is not only something of no use, but is in fact damaging, if we value reliability.

Failure to appreciate the value of the lack of certainty is at the origin of much silliness in our society. Are we sure that the Earth is going to keep heating up, if we do not do anything? Are we sure of the details of the current theory of evolution? Are we sure that modern medicine is always a better strategy than traditional ones? No we are not, in none of these cases. But if from this lack of certainty we jump to the conviction that we better not care about global heating, that there is no evolution and the world was created six thousand years ago, or that traditional medicine must be more effective that the modern medicine, well, we are simply stupid. Still, many people do these silly inferences. Because the lack of certainty is perceived as a sign of weakness, instead of being what it is: the first source of our knowledge.

Every knowledge, even the most solid, carries a margin of uncertainty. (I am very sure about my own name ... but what if I just hit my head and got momentarily confused?) Knowledge itself is probabilistic in nature, a notion emphasized by some currents of philosophical pragmatism. Better understanding of the meaning of probability, and especially realizing that we never have, nor need, 'scientifically proven' facts, but only a sufficiently high degree of probability, in order to take decisions and act, would improve everybody' conceptual toolkit.

Do you know the PDF of your shampoo? A 'PDF' refers to a "partially diminished fraction of an ecosystem," and if your shampoo contains palm oil cultivated on clearcut jungle in Borneo, say, that value will be high. How about your shampoo's DALY? This measure comes from public health: "disability adjusted life years," the amount of one's life that will be lost to a disabling disease because of, say, a liftetime's cumulative exposure to a given industrial chemical. So if your favorite shampoo contains two common ingredients, the carcinogen 1,4 dioxane, or BHA , an endocrine disrupter, its DALY will be higher.

PDFs and DALYs are among myriad metrics for Anthropocene thinking, which views how human systems impact the global systems that sustain life. This way of perceiving interactions between the built and the natural worlds comes from the geological sciences. If adopted more widely this lens might usefully inform how we find solutions to the singular peril our species faces: the extinction of our ecological niche.

Beginning with cultivation and accelerating with the Industrial Revolution, our planet left the Holocene Age and entered what geologists call the Anthropocene Age, in which human systems erode the natural systems that support life. Through the Anthropocene lens, the daily workings of the energy grid, transportation, industry and commerce inexorably deteriorate global biogeochemical systems like the carbon, phosphorous and water cycles. The most troubling data suggests that since the 1950s, the human enterprise has led to an explosive acceleration that will reach criticality within the next few decades as different systems reach a point-of-no-return tipping point. For instance, about half the total rise in atmospheric CO2 concentration has occurred in just the last 30 years — and of all the global life-support systems, the carbon cycle is closest to no-return. While such "inconvenient truths" about the carbon cycle have been the poster child for our species' slow motion suicide, that's just part of a much larger picture, with all the eight global life-support systems under attack by our daily habits.

Anthropocene thinking tells us the problem is not necessarily inherent in the systems like commerce and energy that degrade nature; hopefully these can be modified to become self-sustaining with innovative advances and entrepreneurial energy. The real root of the Anthropocene dilemma lies in our neural architecture.

We approach the Anthropocene threat with brains shaped in evolution to survive the previous geological epoch, the Holocene, when dangers were signaled by growls and rustles in the bushes, and it served one well to reflexively abhor spiders and snakes. Our neural alarm systems still attune to this largely antiquated range of danger.

Add to that misattunement to threats our built-in perceptual blindspot: we have no direct neural register for the dangers of the Anthropocene age, which are too macro or micro for our sensory apparatus. We are oblivious to, say, our body burden, the lifetime build-up of damaging industrial chemicals in our tissues.

To be sure, we have methods for assessing CO2 buildups or blood levels of BHA. But for the vast majority of people those numbers have little to no emotional impact. Our amygdala shrugs.

Finding ways to counter the forces that feed the Anthropocene effect should count high in prioritizing scientific efforts. The earth sciences of course embrace the issue — but do not deal with the root of the problem, human behavior. The sciences that have most to offer have done the least Anthropocene thinking.

The fields that hold keys to solutions include economics, neuroscience, social psychology and cognitive science — and their various hybrids. With a focus on Anthropocene theory and practice they might well contribute species-saving insights. But first they have to engage this challenge, which for the most part has remained off their agenda.

When, for example, will neuroeconomics tackle the brain's perplexing indifference to the news about planetary meltdown, let alone how that neural blindspot might be patched? Might cognitive neuroscience one day offer some insight that might change our collective decision-making away from a lemmings' march to oblivion? Could any of the computer, behavioral or brain sciences come up with an information prosthetic that might reverse our course?

Paul Crutzen, the Dutch atmospheric chemist who won a Nobel for his work on ozone depletion, coined the term 'Anthropocene' ten years ago. As a meme, 'Anthropocene' has as yet little traction in scientific circles beyond geology and environmental science, let alone the wider culture: A Google check on 'anthropocene' shows 78,700 references (mainly in geoscience), while by contrast 'placebo', a once-esoteric medical term now well-established as a meme, has more than 18 million (and even the freshly coined 'vuvuzela' has 3,650,000).

The media cast about for the proximate causes of life's windfalls and disasters. The public demands blocks against the bad and pipelines to the good. Legislators propose new regulations, fruitlessly dousing last year's fires, forever betting on yesterday's winning horses.

A little-known truth: Every aspect of the world is fundamentally unpredictable. Computer scientists have long since proved this.

How so? To predict an event is to know a shortcut for foreseeing the outcome in advance. A simple counting argument shows there aren't enough shortcuts to go around. Therefore most processes aren't predictable. A deeper argument plays on the fact that, if you could predict your actions, you could deliberately violate your predictions which means the predictions were wrong after all.

We often suppose that unpredictability is caused by random inputs from higher spirits or from low-down quantum foam. But chaos theory and computer science tell us that non-random systems produce surprises on their own. The unexpected tornado, the cartoon safe that lands on Uncle George, the winning pull on a slot machine odd things pop out of a computation. The world can simultaneously be deterministic and unpredictable.

In the physical world, the only way to learn tomorrow's weather in detail is to wait twenty-four hours and see even if nothing is random at all. The universe is computing tomorrow's weather as rapidly and as efficiently as possible any smaller model is inaccurate, and the smallest error is amplified into large effects.

At a personal level, even if the world is as deterministic as a computer program, you still can't predict what you're going to do. This is because your prediction method would involve a mental simulation of you that produces its results slower than you. You can't think faster than you think. You can't stand on your own shoulders.

It's a waste to chase the pipedream of a magical tiny theory that allows us to make quick and detailed calculations about the future. We can't predict and we can't control. To accept this can be a source of liberation and inner peace. We're part of the unfolding world, surfing the chaotic waves.

Imagine you need to find the midpoint of a stick. You can measure its length, using a ruler (or making a ruler, using any available increment) and digitally compute the midpoint. Or, you can use a piece of string as an analog computer, matching the length of the stick to the string, and then finding the middle of the string by doubling it back upon itself. This will correspond, without any loss of accuracy due to rounding off to the nearest increment, to the midpoint of the stick. If you are willing to assume that mass scales linearly with length, you can use the stick itself as an analog computer, finding its midpoint by balancing it against the Earth's gravitational field.

There is no precise distinction between analog and digital computing, but, in general, digital computing deals with integers, binary sequences, and time that is idealized into discrete increments, while analog computing deals with real numbers and continuous variables, including time as it appears to exist in the real world. The past sixty years have brought such advances in digital computing that it may seem anachronistic to view analog computing as an important scientific concept, but, more than ever, it is.

Analog computing, once believed to be as extinct as the differential analyzer, has returned. Not for performing arithmetic — a task at which even a pocket calculator outperforms an analog computer — but for problems at which analog computing can do a better job not only of computing the answer, but of asking the questions and communicating the results. Who is friends with whom? For a small high school, you could construct a database to keep track of this, and update it every night to keep track of changes to the lists. If you want to answer this question, updated in real time, for 500 million people, your only hope is to build an analog computer. Sure, you may use digital components, but at a certain point the analog computing being performed by the system far exceeds the complexity of the digital code with which it is built. That's the genius that powers Facebook and its ilk. Your model of the social graph becomes the social graph, and updates itself.

In the age of all things digital, "Web 2.0" is our code word for the analog increasingly supervening upon the digital — reversing how digital logic was embedded in analog components, sixty years ago. The fastest-growing computers of 2010 — search engines and social networks — are analog computers in a big, new, and important way. Instead of meaningful information being encoded as unambiguous (and fault-intolerant) digital sequences referenced by precise numerical addressing, meaningful information is increasingly being encoded (and operated upon) as continuous (and noise-tolerant) variables such as frequencies (of connection or occurrence) and the topology of what connects where, with location being increasingly defined by fault-tolerant template rather than by unforgiving numerical address.

Complex networks — of molecules, people, or ideas — constitute their own simplest behavioral descriptions. This behavior can be more easily and accurately approximated by continuous, analog networks than it can be defined by digital, algorithmic codes. These analog networks may be composed of digital processors, but it is in the analog domain that the interesting computation is being performed.

Analog is back, and here to stay.

Some scientific concepts have been so ruined by our education system that it is necessary to explain about the ones that everyone thinks they know about when they really don't.

We learn about experimentation in school. What we learn is that scientists conduct experiments and if we copy exactly what they did in our high school labs we will get the results they got. We learn about the experiments that scientists do, usually about about the physical and chemical properties of things and we learn that they report their results in scientific journals. So, in effect we learn that experimentation is boring, is something done by scientists and has nothing to do with our daily lives.

And, this is a problem. Experimentation is something done by everyone all the time. Babies experiment with what might be good to put in their mouths. Toddlers experiment with various behaviors to see what they can get away with. Teenagers experiment with sex, drugs, and rock and roll. But because people don't really see these things as experiments nor as ways of collecting evidence in support or refutation of hypotheses, they don't learn to think about experimentation as something they constantly do and thus will need to learn to do better.

Every time we take a prescription drug we are conducting an experiment. But, we don't carefully record the results after each dose, and we don't run controls, and we mix up the variables by not changing only one behavior at a time, so that when we suffer from side effects we can't figure out what might have been the true cause. We do the same thing with personal relationships. When they go wrong, we can't figure out why because the conditions are different in each one.

Now, while it is difficult if not impossible to conduct controlled experiments in most aspects of our own lives, it is possible to come to understand that we are indeed conducting an experiment when we take a new job, or try a new tactic in a game we are playing, or when we pick a school to attend, or when we try and figure out how someone is feeling, or when we wonder why we ourselves feel the way we do.

Every aspect of life is an experiment that can be better understood if it is perceived in that way. But because we don't recognize this we fail to understand that we need to reason logically from evidence we gather, and that we need to carefully consider the conditions under which our experiments have been conducted, and that we need to decide when and how we might run the experiment again with better results.

In other words, the scientific activity that surrounds experimentation is about thinking clearly in the face of evidence obtained as the result of an experiment. But people who don't see their actions as experiments, and those who don't know how to reason carefully from data, will continue to learn less well from their own experiences than those who do.

Since most of us have learned the word "experiment" in the context of a boring ninth grade science class, most people have long since learned to discount science and experimentation as being relevant to their lives.

If school taught basic cognitive concepts such as experimentation in the context of everyday experience, and taught people how to carefully conduct experiments in their own lives instead of concentrating on using algebra as a way of teaching people how to reason, then people would be much more effective at thinking about politics, child raising, personal relationships, business, and every other aspect of daily life.

Understanding the concept of haecceity would improve everybody's cognitive toolkit because it succinctly captures most people's intuitions about authenticity that are increasingly threatened by the development of new technologies. Cloning, genetic modification and even digital reproduction are some examples of new innovations that alarm many members of the public because they appear to violate a belief in the integrity of objects

Haecceity is originally a metaphysical concept that is both totally obscure and yet very familiar to all of us. It is the psychological attribution of an unobservable property to an object that makes it unique among identical copies. All objects may be categorized into groups on the basis of some shared property but an object within a category is unique by virtual of its haecceity. It is haecceity that makes your wedding ring authentic and your spouse irreplaceable, even though such things could be copied exactly in a futuristic science fiction world where matter duplication had been solved.

Haecceity also explains why you can gradually replace every atom in an object so that it not longer contains any of the original material and yet psychologically, we consider it to be the same object. That transformation can be total but so long as it has been gradual, we consider it to be the same thing. It is haecceity that enables us to accept restoration of valuable works of art and antiquities as a continuous process of rejuvenation. Even when we discover that we replace most of the cellular structures of our bodies every couple of decades, haecceity enables us to consider the continuity of our own unique self.

Haecceity is an intellectually challenging concept attributable to the medieval Scottish philosopher, John Duns Scotus, who ironically is also the origin of the term for the intellectually challenged, "dunces." Duns Scotus coined haecceity to address the confusion in Greek metaphysics between the invisible property that defines the individual, as opposed to "quiddity" which is the unique property that defines the group.

Today, both haecceity and quiddity have been subsumed under the more recognizable term, "essentialism." Richard Dawkins has recently called essentialism, "the dead hand of Plato," because, as he points out, a intuitive belief in distinct identities is a major impediment to accepting the reality that all diverse life forms have a common biological ancestry. However drawing the distinction within essentialism is important. For example, it is probably intuitive quiddity that makes some people unhappy about genetic modification because they see this as a violation of integrity of the species as a group. On the other hand it is intuitive haecceity that forms our barrier to cloning, where the authenticity of the individual is compromised.

By reintroducing haecceity as a scientific concept, albeit one that captures a psychological construct, we can avoid the confusion over using the less constrained term of essentialism that is applied to hidden properties that define both the group and the individual identity. It also provides a term for that gut feeling that many of us have when the identity and integrity of objects we value are threatened and we can't find the word for describing our concerns.

I'm alone in my home, working in my study, when I hear the click of the front door, the sound of footsteps making their way toward me. Do I panic? That depends on what I — my attention instantaneously appropriated to the task and cogitating at high speed—infer as the best explanation for those sounds. My husband returning home, the house cleaners, a miscreant breaking and entering, the noises of our old building settling,  a supernatural manifestation? Additional details could make any one of these explanations, excepting the last, the best explanation for the circumstances. Why not the last? As Charles Sanders Peirce, who first drew attention to this type of reasoning, pointed out: "Facts cannot be explained by a hypothesis more extraordinary than these facts themselves; and of various hypotheses the least extraordinary must be adopted."

"Inference to the best explanation" is ubiquitously pursued, which doesn't mean that it is ubiquitously pursued well. The phrase, coined by the Princeton philosopher Gilbert Harmon as a substitute for Peirce's term "abduction," should be in everybody's toolkit, if only because it forces one to think about what makes for a good explanation. There is that judgmental phrase, the best, sitting out in the open, shamelessly invoking standards. Not all explanations are created equal; some are objectively better than others. And the phrasealso highlights another important fact. The best means the one that wins out over the alternatives, of which there are always many. Evidence calling for an explanation summons a great plurality (in fact an infinity) of possible explanations, the great mass of which can be eliminated on the grounds of violating Peirce's maxim. We decide among the remainder using such criteria as: which is the simpler, which does less violence to established beliefs, which is less ad hoc, which explains the most, which is the loveliest. There are times when these criteria clash with one another. Inference to the best explanation is certainly not as rule-bound as logical deduction, nor even as enumerative induction, which takes us from observed cases of all a's being b's to the probability that unobserved cases of a's are also b's. But inference to the best explanation also gets us a great deal more than either deduction or enumerative induction does.

It's inference to the best explanation that gives science the power to expand our ontology, giving us reasons to believe in things that we can't directly observe, from sub-atomic particles — or maybe strings — to the dark matter and dark energy of cosmology. It's inference to the best explanation that allows us to know something of what it's like to be other people on the basis of their behavior. I see the hand drawing too near the fire and then quickly pull away, tears starting in the eyes while an impolite word is uttered, and I know something of what that person is feeling. It's on the basis of inference to the best explanation that I can learn things from what authorities say and write, my inferring that the best explanation for their doing so is that they believe what they say or write. (Sometimes that's not the best explanation.) In fact, I'd argue that my right to believe in a world outside of my own solipsistic universe, confined to the awful narrowness of my own immediate experience, is based on inference to the best explanation. What best explains the vivacity and predictability of some of my representations of material bodies, and not others, if not the hypothesis of actual material bodies? Inference to the best explanation defeats mental-sapping skepticism.

Many of our most rancorous scientific debates — say, over string theory or  foundations of quantum mechanics — have been over which competing criteria for judging explanations the best ought to prevail. So, too, have debates that many of us have been having over scientific versus religious explanations. These debates could be sharpened by bringing to bear on them the rationality-steeped notion of inference to the best explanation, its invocation of the sorts of standards that make some explanations objectively better than others, beginning with Peirce's enjoiner that extraordinary hypotheses be ranked far away from the best.

In politics and society at large, important decision are all too often based on deeply held presuppositions,ideology or dogma — or, on the other hand, on headlong pragmatism without study of long-range consequences.

Therefore I suggest the adoption of Skeptical Empiricism, the kind that is exemplified by the carefully thought-out and tested research in science at its best. It differs from plain empiricism on the sort that characterized the writings of the scientist/philosopher Ernst Mach, who refused to believe in the existence of atoms because one could not "see" them.

To be sure, in politics and daily life, on some topics decisions have to be made very rapidly, on few or conflicting data. Yet, precisely for that reason it will be wise also to launch a more considerate program of skeptical empiricism on the same topic, if only to be better prepared for the consequences, intended or not, that followed from the quick decision.

One of the most widely-useful (but not widely-understood) scientific concepts is that of a possibility space. This is a way of thinking precisely about complex situations. Possibility spaces can be difficult to get your head around, but once you learn how to use them, they are a very powerful way to reason, because they allow you to sidestep thinking about causes and effects.

As an example of how a possibility space can help answer questions, I will use "the Monty Hall problem," which many people find confusing using our normal tools of thought. Here is the setup: A game-show host presents a guest with a choice of items hidden behind three curtains. Behind one is a valuable prize; behind the other two are disappointing duds. After the guest has made an initial choice, the host reveals what is behind one of the un-chosen curtains, showing that it would have been a dud. The guest is then offered the opportunity to change their mind. Should they change or stick with their original decision?

Plausible-sounding arguments can be made for different answers. For instance, one might argue that it does not matter whether the guest switches or not, since nothing has changed the probability that the original choice is correct. Such arguments can be very convincing, even when they are wrong. The possibility space approach, on the other hand, allows us skip reasoning about complex ideas like probabilities and what causes change. Instead, we use a kind of systematic bookkeeping that leads us directly to the answer. The trick is just to be careful to keep track of all of the possibilities. 

One of the best ways to generate all the possibilities is to find a set of independent pieces of information that tell you everything you could possibly need to know about what could happen. For example, in the case of the Monty Hall problem, it would be sufficient to know what choice the guests is going to make, whether the host will reveal the leftmost or rightmost dud, and where the prize is located. Knowing these three pieces of information would allow you to predict exactly what is going to happen. It is also important that these three pieces of information are completely independent, in the sense that knowing one of them tells you nothing about any of the others. The possibility space is constructed by creating every possible combination of these three unknowns.

In this case, the possibility space is three-dimensional, because there are three unknowns. Since there are three possible initial choices for the guest, two dud options for the host, and three possible locations for the prize, there are initially 3x2x3=18 possibilities in the space. (One might reasonably ask why we don't just call this a possibility table. In this simple case, we could. But, scientists generally work with possibility spaces that contain an infinity of possibilities in a multidimensional continuum, more like a kind of physical space space.) This particular possibility space starts out as three-dimensional, but once the guest makes their initial choice, twelve of the possibilities become impossible and it collapses to two dimensions.

Let's assume that the guest already knows what initial choice they are going to make. In that case they could model the situation as a two-dimensional possibility space, one representing the location of the prize, the other representing whether the host will reveal the rightmost or leftmost dud. In this case, the first dimension indicates which curtain hides the prize (1, 2 or 3), and the second represents the arbitrary choice of the host (left dud or right dud), so there are six points in the space, representing the six possibilities of reality. Another way to say this is that the guest can deduce that they may be living in one of six equally-possible worlds. By listing them all, they will see that in four of these six, it is to their advantage to switch from their initial choice. 

Example of a two-dimensional possibility space, when guest's initial Choice is 1

After the host makes his revelation, half of these possibilities become impossible, and the space collapses to three possibilities. It will still be true that in two out of three of these possible worlds it is to the guest's advantage to switch. (In fact, this was even true of the original three-dimensional possibility space, before the guest made their initial choice.)

This is a particularly simple example of a possibility space where it is practical to list all the possibilities in a table, but the concept is far more general. In fact one way of looking at quantum mechanics is that reality actually consists of a possibility space, with Schrödinger's equation assigning a probability to each possibility. This allows quantum mechanics to explain phenomena that are impossible to account for in terms of causes and effects. Even in normal life, possibility spaces give us a reliable way the solve problems when our normal methods of reasoning seem to give contradictory or paradoxical answers. As Sherlock Holmes would say,  "Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth." 

Einstein ranks extremely high not only among the all-time practitioners of science but also among the producers of aphorisms that place science in its real-world context. One of my favourites is "If we knew what we were doing, it wouldn't be called research." This disarming comment, like so many of the best quotes by experts in any field, embodies a subtle mix of sympathy and disdain for the difficulties that the great unwashed find in appreciating what those experts do.

One of the foremost challenges that face scientists today is to communicate the management of uncertainty. The public know that experts are, well, expert - that they know more than anyone else about the issue at hand. What is evidently far harder for most people to grasp is that "more than anyone else" does not mean "everything" - and especially that, given the possession of only partial knowledge, experts must also be expert at figuring out what is the best course of action. Moreover, those actions must be well judged whether in the lab, the newsroom or the policy-maker's office.

It must not, of course, be neglected that many experts are decidedly inexpert at communicating their work in lay terms. This remains a major issue largely because virtually all experts are called upon to engage in general-audience communication only very rarely, hence do not see it as a priority to gain such skills. Training and advice are available, often from university press offices, but even when experts take advantage of such opportunities it is generally too little and too late.

However, in my view that is a secondary issue. As a scientist with the luxury of communicating with the general public very frequently, I can report with confidence that experience only helps up to a point. A fundamental obstacle remains: that non-scientists harbour deep-seated instincts concerning the management of uncertainty in their everyday lives, which exist because they generally work, but which profoundly differ from the optimal strategy in science and technology. And of course it is technology that matters here, because technology is where the rubber hits the road - where science and the real world meet and must communicate effectively.

Examples of failure in this regard abound - so much so that they are hardly worthy of enumeration. Whether it be swine flu, bird flu, GM crops, stem cells: the public debate departs so starkly from the scientist's comfort zone that it is hard not to sympathise with the errors that scientists make, such as letting nuclear transfer be called "cloning", which end up holding critical research fields back for years.

One particular aspect of this problem stands out in its potential for public self-harm, however: risk-aversion. When uncertainty revolves around such areas as ethics (as with nuclear transfer) or economic policy (as with flu vaccination), the issues are potentially avoidable by appropriate forward planning. This is not the case when it comes to the public attitude to risk. The immense fall in uptake of vaccinations for major childhood diseases following a single, contentious study lining them to autism is a prime example. Another is the suspension of essentially all clinical trials of gene therapy for at least a year in response to the death of one person in a trial: a decision taken by regulatory bodies, yes, but one that was in line with public opinion.

These responses to the risk benefit ratio of cutting-edge technologies are examples of fear of the unknown - of an irrationally conservative prioritisation of the risks of change over the benefits, with unequivocally deleterious consequences in terms of quality and quantity of life in the future. Fear of the unknown is not remotely irrational in principle, when "fear of" is understood as a synonym for "caution about" - but it can be, and generally is, overdone. If the public could be brought to a greater understanding of how to evaluate the risks inherent in exploring future technology, and the merits of accepting some short-term risk in the interests of overwhelmingly greater expected long-term benefit, progress in all areas of technology — especially biomedial technology - would be greatly accelerated.

A zero-sum game is an interaction in which one party's gain equals the other party's loss — the sum of their gains and losses is zero. (More accurately, it is constant across all combinations of their courses of action.) Sports matches are quintessential examples of zero-sum games: winning isn't everything, it's the only thing, and nice guys finish last. A nonzero-sum game is an interaction in which some combinations of actions provide a net gain (positive-sum) or loss (negative sum) to the two of them. The trading of surpluses, as when herders and farmers exchange wool and milk for grain and fruit, is a quintessential example, as is the trading of favors, as when people take turns baby-sitting each others' children.

In a zero-sum game, a rational actor seeking the greatest gain for himself or herself will necessarily be seeking the maximum loss for the other actor. In a positive-sum game, a rational, self-interested actor may benefit the other guy with the same choice that benefits himself or herself. More colloquially, positive-sum games are called win-win situations, and are capture in the cliché "Everybody wins."

This family of concepts (zero-sum, nonzero-sum, positive-sum, negative-sum, constant-sum, and variable-sum games) was introduced by John von Neumann and Oskar Morgenstern when they invented the mathematical theory of games in 1944. The Google Books Ngram tool shows that the terms saw a steady increase in popularity beginning in the 1950s, and its colloquial relative "win-win" began a similar ascent in the 1970s.

[click to enlarge]

Once people are thrown together in an interaction, their choices don't determine whether they are in a zero- or nonzero-sum game; the game is a part of the world they live in. But people, by neglecting some of the options on the table, may perceive that they are in a zero-sum game when in fact they are in a nonzero-sum game. Moreover, they can change the world to make their interaction nonzero-sum. For these reasons, when people become consciously aware of the game-theoretic structure of their interaction (that is, whether it is positive-, negative-, or zero-sum), they can make choices that bring them valuable outcomes — like safety, harmony, and prosperity — without their having to become more virtuous, noble, or pure.

Some examples. Squabbling colleagues or relatives agree to swallow their pride, take their losses, or lump it to enjoy the resulting comity rather than absorbing the costs of continuous bickering in hopes of prevailing in a battle of wills. Two parties in a negotiation split the difference in their initial bargaining positions to "get to yes." A divorcing couple realizes that they can reframe their negotiations from each trying to get the better of the other while enriching their lawyers to trying to keep as much money for the two of them and out of the billable hours of Dewey, Cheatham, and Howe as possible. Populaces recognize that economic middlemen (particularly ethnic minorities who specialize in that niche such as Jews, Armenians, overseas Chinese, and expatriate Indians) are not social parasites whose prosperity comes at the expense of their hosts but positive-sum-game-creators who enrich everyone at once. Countries recognize that international trade doesn't benefit their trading partner to their own detriment but benefits them both, and turn away from beggar-thy-neighbor protectionism to open economies which (as classical economists noted) make everyone richer and which (as political scientists have recently shown) discourage war and genocide. Warring countries lay down their arms and split the peace dividend rather than pursuing Pyrrhic victories.

Granted, some human interactions really are zero-sum — competition for mates is a biologically salient example. And even in positive-sum games a party may pursue an individual advantage at the expense of joint welfare. But a full realization of the risks and costs of the game-theoretic structure of an interaction (particularly if it is repeated, so that the temptation to pursue an advantage in one round may be penalized when roles reverse in the next) can militate against various forms of short-sighted exploitation.

Has an increasing awareness of the zero- or nonzero-sumness of interactions in the decades since 1950 (whether referred to in those terms or not) actually led to increased peace and prosperity in the world? It's not implausible. International trade and membership in international organizations has soared in the decades that game-theoretic thinking has infiltrated popular discourse. And perhaps not coincidentally, the developed world has seen both spectacular economic growth and a historically unprecedented decline in several forms of institutionalized violence, such as war between great powers, war between wealthy states, genocides, and deadly ethnic riots. Since the 1990s these gifts have started to accrue to the developing world as well, in part because they have switched their foundational ideologies from ones that glorify zero-sum class and national struggle to ones that glorify positive-sum market cooperation. (All these claims can be documented from the literature in international studies.)

The enriching and pacifying effects of participation in positive-sum games long antedate the contemporary awareness of the concept. The biologists John Maynard Smith and Eörs Szathmáry have argued that an evolutionary dynamic which creates positive-sum games drove the major transitions in the history of life: the emergence of genes, chromosomes, bacteria, cells with nuclei, organisms, sexually reproducing organisms, and animal societies. In each transition, biological agents entered into larger wholes in which they specialized, exchanged benefits, and developed safeguards to prevent one from exploiting the rest to the detriment of the whole. The journalist Robert Wright sketched a similar arc in his book Nonzero and extended it to the deep history of human societies. An explicit recognition among literate people of the shorthand abstraction "positive-sum game" and its relatives may be extending a process in the world of human choices that has been operating in the natural world for billions of years.

My concept is important, useful, scientific and very appropriate for Edge, but it does not exist. It is: The Edge of the Circle.

We know that a circle has no edge, and we also know that, when you travel on a circle far enough to the right or to the left, you reach the same place. Today's world is gradually moving towards extremism in almost every area: Politics, law, religion, economics, education, ethics, you name it. This is probably due to the brevity of messages, the huge amounts of information flooding us, the time pressure to respond before you think and the electronic means (Twitter, text messages) which impose superficiality. Only extremist messages can be fully conveyed in one sentence.

In this world, it often appears that there are two corners of extremism: Atheism and religious fanaticism; Far right and far left in politics; Suffocating bureaucratic detailed regulatory rules or a complete laissez faire; No ethical restrictions in Biology research and absolute restrictions imposed by religion; one can continue with dozens of examples.

But, in reality, the extremists in the two edges always end up in the same place. Hitler and Stalin both murdered millions, and signed a friendship pact. Far left secular atheist demonstrators in the western world, including gays and feminists, support Islamic religious fanatics who treat women and gays as low animals. It has always been known that no income tax and 100% income tax yield the same result: no tax collected at all, as shown by the famous Laffer curve. This is the ultimate meeting point of the extremist supporters of tax increase and tax reduction.

Societies, preaching for absolute equality among their citizens, always end up with the largest economic gaps. Fanatic extremist proponents of developing only renewable energy sources, with no nuclear power, delay or prevent acceptable interim solutions to global energy issues, just as much as the oil producers. Misuse of animals in biology research is as damaging as the objections of fanatic animal right groups. One can go on and on with illustrations, which are more visible now than they were a decade or two ago. We live on the verge of an age of extremism.

So, the edge of the circle is the place where all of these extremists meet, live and preach. The military doctor who refuses to obey orders "because Obama was born in Africa" and the army doctor, who murdered 12 people in Texas, are both at the edge of the circle.

If you are a sensible moderate thinking person, open any newspaper and see how many times you will read news items or editorials, which will lead you to say: "Wow, these people are really at the edge of the circle" ...

You're sprawled on the couch in your living room, watching a new episode of Justified on the tube, when you think of something you need to do in the kitchen. You get up, take ten quick steps across the carpet, and then, just as you reach the kitchen door — poof! — you realize you've already forgotten what it was you got up to do. You stand befuddled for a moment, then shrug your shoulders and head back to the couch.

Such memory lapses happen so often that we don't pay them much heed. We write them off as "absentmindedness" or, if we're getting older, "senior moments." But the incidents reveal a fundamental limitation of our minds: the tiny capacity of our working memory. Working memory is what brain scientists call the short-term store of information where we hold the contents of our consciousness at any given moment — all the impressions and thoughts that flow into our mind as we go through a day. In the 1950s, Princeton psychologist George Miller famously argued that our brains can hold only about seven pieces of information simultaneously. Even that figure may be too high. Some brain researchers now believe that working memory has a maximum capacity of just three or four elements.

The amount of information entering our consciousness at any instant is referred to as our cognitive load. When our cognitive load exceeds the capacity of our working memory, our intellectual abilities take a hit. Information zips into and out of our mind so quickly that we never gain a good mental grip on it. (Which is why you can't remember what you went to the kitchen to do.) The information vanishes before we've had an opportunity to transfer it into our long-term memory and weave it into knowledge. We remember less, and our ability to think critically and conceptually weakens. An overloaded working memory also tends to increase our distractedness. After all, as the neuroscientist Torkel Klingberg has pointed out, "we have to remember what it is we are to concentrate on." Lose your hold on that, and you'll find "distractions more distracting."

Developmental psychologists and educational researchers have long used the concept of cognitive load in designing and evaluating pedagogical techniques. When you give a student too much information too quickly, they know, comprehension degrades and learning suffers. But now that all of us — thanks to the incredible speed and volume of modern digital communication networks and gadgets — are inundated with more bits and pieces of information than ever before, everyone would benefit from having an understanding of cognitive load and how it influences memory and thinking. The more aware we are of how small and fragile our working memory is, the more we'll be able to monitor and manage our cognitive load. We'll become more adept at controlling the flow of the information coming at us.

There are times when you want to be awash in messages and other info-bits. The resulting sense of connectedness and stimulation can be exciting and pleasurable. But it's important to remember that, when it comes to the way your brain works, information overload is not just a metaphor; it's a physical state. When you're engaged in a particularly important or complicated intellectual task, or when you simply want to savor an experience or a conversation, it's best to turn the information faucet down to a trickle.

Creativity is a fragile flower, but perhaps it can be fertilized with systematic doses of serendipity. Sarnoff Mednick showed decades ago that some people are better than others at detecting the associations that connect seemingly random concepts: Asked to name a fourth idea that links "wheel," "electric," and "high," people who score high on other measures of creativity will promptly answer "chair."

More recently, research in Mark Jung-Beeman's lab at Northwestern has found that sudden bursts of insight — the Aha! or Eureka! moment — comes when brain activity abruptly shifts its focus. The almost ecstatic sense that makes us cry "I see!" appears to come when the brain is able to shunt aside immediate or familiar visual inputs.

That may explain why so many of us close our eyes (often unwittingly) just before we exclaim "I see!" It also suggests, at least to me, that creativity can be enhanced deliberately through environmental variation. Two techniques seem promising: varying what you learn and varying where you learn it. I try each week to read a scientific paper in a field that is new to me — and to read it in a different place.

New associations often leap out of the air at me this way; more intriguingly, others seem to form covertly and then to lie in wait for the opportune moment when they can click into place. I do not try to force these associations out into the open; they are like shrinking mimosa plants that crumple if you touch them but bloom if you leave them alone.

Robert Merton argued that many of the greatest discoveries of science have sprung from serendipity. As a layman and an amateur, all I hope to accomplish by throwing myself in serendipity's path is to pick up new ideas, and combine old ones, in ways that haven't quite occurred to other people yet. So I let my curiosity lead me wherever it seems to want to go, like that heart-shaped piece of wood that floats across a Ouija board.

I do this remote-reading exercise on my own time, since it would be hard to justify to newspaper editors during the work day. But my happiest moments this autumn came as I reported an investigative article on how elderly investors are increasingly being scammed by elderly con artists. I later realized, to my secret delight, that the article had been enriched by a series of papers I had been reading on altruistic behavior among fish (Lambroides dimidiatus).

If I do my job right, my regular readers will never realize that I spend a fair amount of my leisure time reading Current Biology, the Journal of Neuroscience, and Organizational Behavior and Human Decision Processes. If that reading helps me find new ways to understand the financial world, as I suspect it does, my readers will indirectly be smarter for it. If not, the only harm done is my own spare time wasted.

In my view, we should each invest a few hours a week in reading research that ostensibly has nothing to do with our day jobs, in a setting that has nothing in common with our regular workspaces. This kind of structured serendipity just might help us become more creative, and I doubt that it can hurt.

The scientific concept of the "multiverse" has already entered popular imagination. But the full implications of the idea that every possible universe has been and will be actualised have yet to sink in. One of these, which could do more to change our view of things than anything is that we are all destined to be immortal.

This welcome news (if indeed it is welcome) follows on two quite different grounds. First, death normally occurs to human bodies in due time either as the result of some kind of macro-accident — for example a car crash, or a homicide; or a micro-one — a heart attack, a stroke; or, if those don't get us, a nano-one — accidental errors in cell division, cancer, old age. Yet, in the multiverse, where every alternative is realised, the wonderful truth is that there has to be at least one particular universe in which by sheer luck each of us as individuals have escaped any and all of these blows.

Second, we live in a world where scientists are, in any case, actively searching for ways of combatting all such accidents: seat belts to protect us in the crash, aspirin to prevent stroke, red wine oxidants to counter heart attacks, antibiotics against disease. And in one or more of the possible universes to come these measures will surely have succeeded in making continuing life rather than death the natural thing.

Taking these possibilities — nay certainties — together, we can reasonably conclude that there will surely be at least one universe in which I — and you — will still find ourselves living in a thousand years, or a million years time.

Then, when we get there, should we, the ultimate survivors, the one in a trillion chancers, mourn our alter-egos who never made it? No, probably no more than we do now. We are already, as individuals, statistically so improbable as to be a seeming miracle. Having made it so far, shouldn't we look forward to more of the same?

Each of us is ordinary, and yet one of a kind.

Each of us is standard-issue, conceived by the union of two germ cells, nurtured in a womb, and equipped with a developmental program that guides our further maturation and eventual decline.

Each of us is also unique, the possessor of a particular selection of gene variants from the collective human genome, and immersed in a particular family, culture, era, and peer group. With inborn tools for adaptation to the circumstances of our personal world we keep building our own ways of being and the sense of who we are.

This dual view of each of us, as both run-of-the-mill and special, has been so well established by biologists and behavioral scientists that it may now seem self-evident. But it still deserves conscious attention as a specific cognitive chunk because it has such important implications. Recognizing how much we share with others promotes compassion, humility, respect, and brotherhood. Recognizing that we are each unique promotes pride, self-development, creativity, and achievement.

Embracing these two aspects of our personal reality can enrich our daily experience. It allows us to simultaneously enjoy the comfort of being ordinary and the excitement of being one of a kind.

The world consists of things, which obey rules.  If you keep asking "why" questions about what happens in the universe, you ultimately reach the answer "because of the state of the universe and the laws of nature."

This isn't an obvious way for people to think.  Looking at the universe through our anthropocentric eyes, we can't help but view things in terms of causes, purposes, and natural ways of being.  In ancient Greece, Plato and Aristotle saw the world teleologically — rain falls because water wants to be lower than air, animals (and slaves) are naturally subservient to human citizens.

From the start, there were skeptics.  Democritus and Lucretius were early naturalists, who urged us to think in terms of matter obeying rules rather than chasing final causes and serving underlying purposes.  But it wasn't until our understanding of physics was advanced by thinkers such as Avicenna, Galileo, and Newton that it became reasonable to conceive of the universe evolving under its own power, free of guidance and support from anything beyond itself.

Theologians sometimes invoke "sustaining the world" as a function of God.  But we know better; the world doesn't need to be sustained, it can simply be.  Pierre-Simon Laplace articulated the very specific kind of rule that the world obeys:  if we specify the complete state of the universe (or any isolated part of it) at some particular instant, the laws of physics tell us what its state will be at the very next moment.  Applying those laws again, we can figure out what it will be a moment later.  And so on, until (in principle, obviously) we can build up a complete history of the universe.  This is not a universe that is advancing toward a goal; it is one that is caught in the iron grip of an unbreakable pattern.

This view of the processes at the heart of the physical world has important consequences for how we come to terms with the social world. Human beings like to insist that there are reasons why things happen. The death of a child, the crash of an airplane, or a random shooting must be explained in terms of the workings of a hidden plan.  When Pat Robertson suggested that Hurricane Katrina was caused in part by God's anger at America's failing morals, he was attempting to provide an explanatory context for a seemingly inexplicable event.

Nature teaches us otherwise.  Things happen because the laws of nature say they will — because they are the consequences of the state of the universe and the path of its evolution.  Life on Earth doesn't arise in fulfillment of a grand scheme, but rather as a byproduct of the increase of entropy in an environment very far from equilibrium.  Our impressive brains don't develop because life is guided toward greater levels of complexity and intelligence, but from the mechanical interactions between genes, organisms, and their surroundings.

None of which is to say that life is devoid of purpose and meaning. Only that these are things we create, not things we discover out there in the fundamental architecture of the world. The world keeps happening, in accordance with its rules; it's up to us to make sense of it and give it value.