Mathematics = Language of Interdisciplinarity?

Michael Mitzenmacher had an interesting post last week on his blog, my biased coin. Mitzenmacher is professor of computer science at Harvard University. He's written a few extremely interesting papers on power laws which we'll probably read later in the term.

Mitzenmacher was writing about attending the opening of Microsoft Research New England. The theme of the opening symposium was interdiscplinary research. Mitzenmacher writes that

a natural question was how such research should be encouraged. Nobody on the panel seemed to make what I thought was an obvious point: one way to encourage such research is to make sure people across the sciences are well trained in mathematics and (theoretical) computer science. Interdisciplinary research depends on finding a common language, which historically has been mathematics, but these days more and more involves algorithms, complexity, and programming.

Mitzenmachmer then goes on to describe a subsequent talk by Erik Demaine. The abstract of the talk is:

Theoretical computer science, and the algorithmic way of thinking, transcends our traditional boundaries. I believe that algorithms are relevant to every discipline of study, and will give eclectic examples from the arts and sciences to business and society. The examples span the spectrum from serious topics like protein folding and decoding Inka khipu to fun topics like juggling and magic.

There's a link to a video of Demaine's talk here, although I can't get the video to work right now.

I find myself quite intrigued by this and I'm not quite sure what to think, although I think I'm basically in agreement. Having a solid base in math, statistics, and some computer programming/computer science strikes me as almost indispensible for work in most sciences and social sciences. Quite generally, I think that having a strong understanding of these areas greatly expands the sort of scientific problems one can tackle. And it certainly increases the range of other scientists one can talk to and the depths that those conversations can go.

So as far as the sciences go, I'm basically quite comfortable with Mitzenmacher's statement. I wonder, though, how his statement might have to be ammended to apply to the humanities. Is there a "common language" that helps philosophers, anthopologists, historians, and literary theorists research together? Is this language broad enough to include political scientists, psychologists, or economists? My guess is that there is a semi-canonical body of thinkers or schools of thought that scholars in these areas would all be familiar with, and which could serve as a useful touchstone or frame of reference for interdisciplinary collaboration. But I'm not sure, as I'm not even close to an expert in these fields.

As for the centrality of computer science and mathematics for science, I worry sometimes that COA could be doing more to prepare students in these areas. We've graduated lots of students who are very well prepared in math and who have gone on to make good use of their math backgrounds in grad school. But I think we can do better. Part of the problem is that we could use a few more classes in math, statistics, and computer science. But I also think that there might be a subtle bias against mathematics, a perhaps unspoken idea that if you learn too much math you'll lose your sense of creativity and joy and acquire a simplistic and reductionist approach to everything. Needless to say, I disagree.

Anyway, partly inspired by Mitzenmacher, for the next two classes I want to attempt to present a sort of crash course or primer in interdisciplinary probability and stochastic processes. There are just some good, basic, widely applicable things about this area that I think (almost) every scientist and social scientist should know. We'll see how it goes. Fasten your seat belts...