For those of you who called in asking, here’s an attempt to characterize my research interests. I’ll try to keep it short and sweet, but please keep in mind that doing so will involve a degree of garbling the finer points.
J.M Bernstein once said “When I say that philosophy is always historical and cultural, I’m saying that philosophy emerges from a crisis. Which is why you can always tell bad academic philosophy, because it doesn’t emerge from a crisis, it emerges from a puzzle.” I think that’s true. My crisis, the one that my work revolves around, is the crisis of complexity. This guy put it perfectly: complexity is a scientific crisis, and there are three stages to any crisis. First, those in authority ignore it. Next, they ridicule and downplay the crisis. Finally, they act as though they always cared about it. He thinks were just coming up on stage two – I suspect we’re well into two, and three is poking its head ’round the corner, as everybody and their dog seems to be talking about complexity these days.
By complexity I mean a few things. The simplest way of talking about it is just in terms of trying to understand systems with lots of parts (this is how Michael Strevens talks about it, for instance). That’s a good start, but doesn’t do much to clarify why anyone should think complexity constitutes a crisis. Things become a bit clearer if we add that the parts of a complex system should be related to each other in non-linear ways, so that the behaviour of the whole system becomes difficult to predict or understand in terms of adding up the parts. If I imagine a bowling ball is composed of thousands of tiny one-gram parts, I can still add up those parts and predict, using normal newtonian mechanics, how it will fly through the air if thrown. So from that perspective, bowling balls aren’t complex.
But suppose instead I want to know how a particular gene functions. Many genes participate in regulatory networks, meaning they turn each other on or off, or even make each other more or less active. To know what tweaking the activity of one gene will do, I may have to look at hundreds of other genes (and their level of activity), each of which may be influenced by and are influencing many other genes. If I’m an honest researcher, I’ll have to admit that I’ll potentially have to look at the whole damn genome to say anything rigorous about my single gene. Supposing something like that is true, the activity of the genome is truly complex.
This, I want to argue, poses a new kind of challenge for science. Science works by finding invariant relationships between kinds of things – invariance under variation. What that means is isolating some phenomenon of interest from its context, and making a generalization about it. If you do psychology, you want to categorize psychological states, and be able to say general things about each category: chronic stress causes problems for the adrenal system, addiction is a problem with dopamine regulation, etc. But when you have complexity, it looks like that nice categorical reasoning may not work properly. What if every person with mental illness was genuinely unique? The British Psychological Society recently critiqued the latest DSM (the set of categories psychiatrists use to diagnose and treat mental illness) on precisely those grounds.
So what the hell are we supposed to do with that kind of complexity? I sure don’t know. But I’m working on it.
The project that will occupy this summer is a comparison of the methodology of scientists with that of historians. Historical methodology, I propose, is perfectly suited to really messy complexity. In History, things only ever happen once. That is, every event is unique to an historian, and to understand anything is to set it in its proper context, looking at all the details that made up its environment. More detail is better, and no pretense is made of being able to make universal generalizations.
Scientists, on the other hand, can only treat events as potentially members of some category or other. They’re happiest if that category features in some universal law of nature. But one-off observations are no good to scientists. Take for example, the Wow! signal. In 1977, a SETI telescope detected a totally unprecedented narrowband radio signal, of an intensity no one had ever seen before. It’s never been seen again, and no one has any idea how to classify it. The Wow! signal is therefore scientifically useless – we can’t make any generalizations based on it, because we haven’t a clue what category it falls under.
I’ll argue that there are parts of biology that need to be treated as historical, in this sense. Because of the messy complexity of, for example, evolutionary history, some things can only be situated in their context – categorical reasoning about particular evolutionary events may not be appropriate. I’m calling it a dimension of the historicity of biology, in honour of the work of people like the philosopher John Beatty and his colleagues, who’ve already done interesting and important work on the relation between history and biology.
Complexity is a scientific crisis, I would argue, because the scientific method as we’ve always understood it since Francis Bacon, is set up to deal with clean, linear relations. But now we’re capable of and interested in studying systems with millions or billions of parts, interacting in ways that can’t just be averaged over. Thanks to the explosion of computing power, and knowledge generation, old ways of seeing the world are become obsolete faster than new ways are being developed. I hope to do my bit in getting a handle on what’s going on, and where we’re going.