the life logistic
At the start of the course, I recommended that you check out this extremely cool interactive guide to the evolution of trust by Nicky Case, a Canadian game developer who I wish someone would put in charge of the world’s educational systems. In this week’s tutorial, I’ve just about managed to contrive a valid excuse for playing two more of Case’s micro-masterpieces, so if anyone asks you to wash the dishes instead of sitting around playing games you can tell them this is educational, and actually yes it is from the same course as that psychedelic mushroom ape thing. Anyway:
Complexity science and chaos theory became a hot topic back in the 80s. There were a bunch reasons for this: across the natural and social sciences, for as long as those had been a thing, there has always been a strong pull towards reductionism, which is the idea that doing sciencey stuff involves breaking the thing you’re interested in up into smaller, simpler bits. Once you know what all the bits are, and what the bits do, then you’ve understood everything you need to know about the bigger thing you started with: the whole is the sum of its parts. If that’s how the world works, then language (for example) just reduces to psychology, and then psychology reduces to neuroscience, neuroscience reduces to biology, biology reduces to chemistry, and of course chemistry reduces to particle physics, which reduces to strings or something apparently. Of course, lots of people weren’t super happy about this general idea - it’s hard to see how things like the historical development of the english language can be explained by the physics of expanding gases whenever a physicst walks into your office by mistake. On the other hand, it had never been clear how to think about a general kind of science which works in the opposite direction, i.e. from smaller to bigger. Actually, a lot of people at different times and from different disciples (including physicists, of course) had thought a lot about this, but there was no way to connect this kind of stuff - in a general way - to things as different from each other as Micronesian sociopolitics and ocean reef ecology and cheesemaking - until complexity science hit the scene in a big way, with the idea that we could find common meaningful patterns across all the endless complex phenomena of the world. This fundamentally interdisciplinary idea promised all sorts of meaningful connections between every branch of science, and led to the creation of places like the Santa Fe Insitute. It also made great copy for journalists, who could interview physicists (of course) for their most speculative opinions on anything from the meaning of life to whether we all live in a giant simulation. Not only this, but complexity scientists loved to talk about something called chaos, which sounds even cooler than complexity science, and made all these awesome pictures of fractals which looked amazing on the front page, and you could even put them on a t-shirt - everybody wins.
The field has cooled down a lot since then: both because the hype machine moved on to the next big things like cyberspace and AI, but also it turned out that studying complexity was - and this came as a shock - really really hard. On the other hand, it really did open up the idea of interdisciplinarity as a thing respectable scientists do, rather than just people with very intense eyes who live in the woods and won’t stop talking about fungi. And without this kind of atmosphere, the recent emergence of the field of language evolution - which as you’ve seen is interdisciplinary in the extreme - would probably not have been possible.
But is language a complex adaptive system? These people argue that it is, and I’d be inclined to agree with them. On the other hand, how are we meant to put this perpective to any use? I’d argue that that’s what we’ve been doing throughout the course, just without saying so explicitly. But instead of banging on about complex systems and looking at groovy fractals (last week excepted), I think that one of the most useful things about a complex systems approach is exploring how to transfer knowledge from one discipline to another: biological evolution to culture and language, game theory to social interaction, and fungi to everything. Needless to say, this kind of approach is hit-and-miss. You have to be careful that your analogies makes sense, and about the assumptions you have to make, or how far to take your conclusions. But, done right, I think it can be extremely useful, and probably essential to making any progress. So let’s have a go ourselves!
Play these two games:
Afterwards, speculate wildly about how to apply these ideas to language evolution, and bring your theories to the tutorial and attempt to convince your group that you are a maverick genius whose ideas will change the world.