The Strong Possibility That We've Got Everything Horribly Wrong
The thing I'm most optimistic about is the strong possibility that we've got everything horribly wrong. All of it. Badly.
Once, when I was a young child, I accompanied my father on a car journey around some twisty back lanes in England. Dad wasn't familiar with the area, so I helpfully took the map from him and navigated. Things seemed to be going pretty well for the first half hour, until we found ourselves staring helplessly at a field gate that should have been a major road junction. It turned out that I'd been navigating from entirely the wrong page of the map, and it was sheer coincidence that enough landmarks had matched my expectations for me to believe we were on track.
I learned a lesson from this. Science sometimes learns these lessons too. Thomas Kuhn put it much better than me when he introduced the concept of a paradigm shift. Sometimes we manage to convince ourselves that we have a handle on what is going on, when in fact we're just turning a blind eye to a mass of contradictory information. We discard it or ignore it (or can't get funded to look at it) because we don't understand it. It seems to make no sense, and it can take us a while before we realize that the problem doesn't lie with the facts but with our assumptions.
Paradigm shifts are wonderful things. Suddenly the mists clear, the sun comes out and we exclaim a collective "aha!" as everything begins to make sense. What makes me so optimistic about science right now is that there are plenty of these "aha" moments waiting in the wings, ready to burst energetically onto the stage. We've got so much completely wrong, but we're starting to look at the world in radically new ways – dynamical, nonlinear, self-organizing ways – and I think a lot of our standing ideas and assumptions about the world are about to turn inside-out, just as our much older, religious ideas did during the Enlightenment.
My guesses for prime candidates would include quantum theory and our understanding of matter, but those aren't my field and it's not my place to judge them. My field is artificial intelligence, but I'm sad to say that this subject started on the wrong page of the map many years ago and most of us haven't woken up to it yet. We keep our eyes firmly on the route and try not to look to left or right for fear of what we might see. In a way, Alan Turing was responsible for the error, since his first big idea in AI (that something vaguely reminiscent of human thought could be automated) turned out to be such a stonkingly good one, for other reasons entirely, that it eclipsed his later, more promising ideas about connectionist systems and self-organization. Since then, the digital computer has dominated the AI paradigm, through failure after dismal failure.
My great white hope for AI lies in neuroscience. The only working intelligent machine we know of is the brain, and it seems to me that almost everything we think we understand about the brain is wrong. We know an enormous amount about it now and just about none of it makes the slightest bit of sense. That's a good sign, I think. It shows us we've been looking at the wrong page of the map.
Let me try to illustrate this with a thought experiment: Suppose I give you a very complex system to study – not a brain but something equally perplexing. You discover quite quickly that one part of the system is composed of an array of elements, of three types. These elements emit signals that vary rapidly in intensity, so you name these the alpha, beta and gamma elements, and set out eagerly to study them. Placing a sensor onto examples of each type you find that their actual signal patterns are distressingly random and unpredictable, but with effort you discover that there are statistical regularities in their behaviour: beta and gamma elements are slightly more active than alpha elements; when betas are active, gammas in the same region tend to be suppressed; if one element changes in activity, its neighbours tend to change soon after; gammas at the top of the array are more active than those at the bottom, and so on. Eventually you amass an awful lot of information about these elements, but still none of it makes sense. You're baffled.
So allow me to reveal that the system you've been studying is a television set, and the alpha, beta and gamma elements are the red, green and blue phosphor dots on the screen. Does the evidence start to fit together now? Skies are blue and tend to be at the top, while fields are green and tend to be at the bottom; objects tend to move coherently across the picture. If you know what the entire TV image represents at any one moment, you'll be able to make valid predictions about which elements are likely to light up next. By looking at the entire array of dots at once, in the context of a good system-level theory of what's actually happening, all those seemingly random signals suddenly make sense. "Aha!"
The single-electrode recordings of the equivalent elements in the brain have largely been replaced by system-wide recordings made by fMRI now, but at the moment we still don't know what any of it means because we have the wrong model in our heads. We need an "aha" moment akin to learning that the phosphor dots above belong to a TV set, upon which images of natural scenes are being projected. Once we know what the fundamental operating principles are, everything will start to make sense very quickly. Painstaking deduction won't reveal this to us; I think it will be the result of a lucky hunch. But the circumstances are in place for that inductive leap to happen soon, and I find that tremendously exciting.
Isaac Newton once claimed that he'd done no more than stand on the shoulders of giants. He was being far too modest. It might be more accurate to say that he stayed down at child height, running between the giants' legs and exploring things in his own sweet way. That's what we Third Culturists are all about, and it's such a combination of artful playfulness and pan-disciplinary sources of analogy and inspiration that will turn our understanding of the world inside-out. I'm very optimistic about that.