Having turned my back on propositions, I thought, what am I going to do about this? The area where it really comes up is when you start looking at the contents of consciousness, which is my number one topic. I like to quote Maynard Keynes on this. He was once asked, “Do you think in words or pictures?” to which he responded, “I think in thoughts.” It was a wonderful answer, but also wonderfully uninformative. What the hell’s a thought then? How does it carry information? Is it like a picture? Is it iconic in some way? Does it resemble what it’s about, or is it like a word that refers to what it’s about without resembling it? Are there third, fourth, fifth alternatives? Looking at information in the brain and then trying to trace it back to information in the genes that must be responsible for providing the design of the brain that can then carry information in other senses, you gradually begin to realize that this does tie in with Shannon's information theory. There’s a way of seeing information as "a difference that makes a difference," to quote Donald MacKay and Bateson.

Ever since then, I’ve been trying to articulate, with the help of Harvard evolutionary biologist David Haig, just what meaning is, what content is, and ultimately, in terms of biological information and physical information, the information presented in A Mathematical Theory of Communication by Shannon and Weaver. There’s a chapter in my latest book called “What is Information?” I stand by it, but it’s under revision. I’m already moving beyond it and realizing there’s a better way of tackling some of these issues.

DANIEL C. DENNETT is the Austin B. Fletcher Professor of Philosophy and co-director of the Center for Cognitive Studies at Tufts University. He is the author, most recently, of From Bacteria to Bach and Back: The Evolution of Minds. Daniel C. Dennett's Edge Bio page

It's very clear that in order to make progress in understanding some of the most challenging and important things about intelligence, studying the best example we have of an intelligent system is a way to do that. Often, people who argue against that make the analogy that if we were trying to understand how to build jet airplanes, then starting with birds is not necessarily a good way to do that.                                 

That analogy is pretty telling. The thing that's critical to both making jet airplanes work and making birds fly is the structure of the underlying problem that they're solving. That problem is keeping an object airborne, and the structure of that problem is constrained by aerodynamics. By studying how birds fly and the structure of their wings, you can learn something important about aerodynamics. And what you learn about aerodynamics is equally relevant to then being able to make jet engines.                                 

The kind of work that I do is focused on trying to identify the equivalent of aerodynamics for cognition. What are the real abstract mathematical principles that constrain intelligence? What can we learn about those principles by studying human beings? 

TOM GRIFFITHS is a professor of psychology and cognitive science and director of the Computational Cognitive Science Lab and the Institute of Cognitive and Brain Sciences at the University of California, Berkeley. He is co-author (with Brian Christian) of Algorithms to Live By. Tom Griffiths's Edge Bio page

Sometimes you think you understand something, and when you try to explain it to somebody else, you realize that maybe you gained some new insight that you didn't have before. Maybe you realize you didn't understand it as well as you thought you did. What I think is interesting about this process is that it’s a process of learning by thinking. When you're explaining to yourself or to somebody else without them providing feedback, insofar as you gain new insight or understanding, it isn't driven by that new information that they've provided. In some way, you've rearranged what was already in your head in order to get new insight.

The process of trying to explain to yourself is a lot like a thought experiment in science. For the most part, the way that science progresses is by going out, conducting experiments, getting new empirical data, and so on. But occasionally in the history of science, there've been these important episodes—Galileo, Einstein, and so on—where somebody will get some genuinely new insight from engaging in a thought experiment. 

TANIA LOMBROZO is a professor of psychology at the University of California, Berkeley, as well as an affiliate of the Department of Philosophy and a member of the Institute for Cognitive and Brain Sciences. She is a contributor to Psychology Today and the NPR blog 13.7: Cosmos and Culture. Tania Lombrozo's Edge Bio page

Contrary to the standard view of reason as a capacity that enhances the individual in his or her cognitive capacities—the standard image is of Rodin’s "Thinker," thinking on his own and discovering new ideas—what we say now is that the basic functions of reason are social. They have to do with the fact that we interact with each other’s bodies and with each other’s minds. And to interact with other’s minds is to be able to represent a representation that others have, and to have them represent our representations, and also to act on the representation of others and, in some cases, let others act on our own representations.

The kind of achievements that are often cited as the proof that reason is so superior, like scientific achievements, are not achievements of individual minds, not achievements of individual reason, they are collective achievements—typically a product of social interaction over generations. They are social, cultural products, where many minds had to interact in complex ways and progressively explore a lot of directions on which they hit, not because some were more reasonable than others, but because some were luckier than others in what they hit. And then they used their reason to defend what they hit by luck. Reason is a remarkable cognitive capacity, as are so many cognitive capacities in human and animals, but it’s not a superpower.

DAN SPERBER is a Paris-based social and cognitive scientist. He holds an emeritus research professorship at the French Centre National de la Recherche Scientifique (CNRS), Paris, and he is currently at Central European University, Budapest. He is the creator (with Deirdre Wilson) of "Relevance Theory," and coauthor (with Hugo Mercier) of The Enigma of Reason. Dan Sperber's Edge Bio Page

We know that in the physical ecosystem biodiversity is healthy and important. People can buy into that. We know that biodiversity fosters resistance to pathogens and invasive species. When you explain to someone that the human mind may not be so different, that it's important to have a diverse array of emotions—joy, sadness, love, admiration, guilt—and that these are all important pieces of our internal human emotional ecosystem, people can understand that. People appreciate that diversity is important, that maybe it's some sort of spice of mental life.

When you frame it that way, people are more readily able to not put such a premium on positive emotions and, in some situations, try to foster other kinds of experiences if they think it's part of a more diverse psychological life and repertoire. Framing it less as pushing positive emotions down, but as letting all emotions grow and thrive. They're all important sources of information for us and we have them for a reason. We have evolutionary goals; people can understand that. That's one way we've been thinking about trying to frame this. You don't just want to grow one kind of plant in your garden, you want to have a diverse array. 

JUNE GRUBER is an assistant professor of psychology at the University of Colorado, Boulder, and director of the Positive Emotion and Psychopathology Laboratory. June Gruber's Edge Bio Page

THE REALITY CLUB: Robert Provine