Douthat on the Humanities and Small Liberal Arts Colleges…

Today’s Douthat Column in the NYT is excellent. My readers may know that I attended Amherst College (mentioned in the column) during the 1970’s and can attest to the popularity of the humanities there, at that time. He points out the statistics that show the trend towards the other of C.P. Snow’s Two Cultures. Indeed, when I was at Amherst, I very much wanted to major in political science. It was my parents who pushed me to major in chemistry.

But….it strikes me that Douthat, in despair at the moral crisis of the West, is really just urging us to return, metaphorically, to the modern version of monastery retreats, as the Irish monks did during the Dark Ages when they purportedly saved western cultural tradition.

I don’t think that this will do. Climate Change will not wait for a future Renaissance to arrive. Neither will the thousands of nuclear warheads that sit on alert. It is vital that science and engineering thrive for the future of the planet and the humanities.

Two Cultures redux…

That’s CP Snow’s book, Two Cultures and its analysis of science versus the humanities. The lecture from which the book emerged took place in 1959. The battle still rages and the latest round can be found here. In the modern version its Steven Pinker versus Leon Wieseltier–enjoy!

C.P. Snow’s Two Cultures Revisited

I was sitting down with a colleague this morning–he’s a biochemist and I’m a neuroscientist–and the question came up of how hypotheses can be properly falsified in the social sciences and especially computational social science. This, to me, is an incredibly important question for the future of the social sciences, because, if you accept Karl Popper‘s requirement that scientific questions by definition, must contain falsifiable hypotheses, then social science can’t just be observational and inductive.

Now I’ve been familiar with Popperian-based social science since my training days in Ann Arbor (e.g. much of survey research is of this type). My problem is a deeper one. Given the complexity of human social relations, and our difficulty making measurements (of say the type we make in chemistry), how sure are we that the result of an experiment on social human beings can say anything definitive about an underlying hypothesis (much less falsify it).

Here I explicitly ignore trivial examples such as: all heads of state throughout history have been male (false).

Rather, I’m after the really non-trivial social science questions. The following is an example: human settlements (such as cities) follow a power law as far as population is concerned.

Even more importantly, as we create models for social systems in silico, we can conduct experiments on the models with Popperian rigor, but what really can we say about the relationship between a falsifiable hypothesis for a computational social science model and its corresponding hypothesis in the world of social human affairs?

Recently the new field of social neuroscience has opened up, led by John Cacioppo at the University of Chicago among others. Here at least, is the germ of an answer to my problem. Functional MRI measurements of human brains as they interact fulfills Popper’s requirements–within the caution that the fMRI BOLD signal is mismatched to both the spatial and temporal dimensions of the neural code (think neurons and action potentials to a first approximation).

The field of experimental economics, as pioneered by Vernon Smith, similarly, fulfills Popper.

Interestingly, the field of computational neuroscience requires a “validation” cycle with bench top neuroscience to be taken seriously: model results must be compared to bench top science. When the model and the bench top results don’t agree, we go with the bench top data and change the model.

Should there be a similar requirement for computational social science models?

Thinking about the Two Cultures

I’ve been thinking a lot about C.P. Snow’s Two Cultures lately. Snow, in his seminal mid-twentieth century lecture (followed by an article and two books) put forward the notion of a dialectic between the social sciences and the hard sciences. One of his most famous quotes concerns querying some literary friends about the 2nd Law of Thermodynamics in response to their complaints about the general ignorance of scientists about literature. The upshot is that they didn’t know about entropy or the 2nd Law.

Here at Krasnow, we have, only in recent years, become a true locus for advanced studies as we added, first a center for social complexity and second a department of computational social sciences to our existing center of mass in neuroscience (writ large). These days research at Krasnow spans Snow’s two cultures pretty effectively, but largely without the communications divide postulated in Two Cultures.

Why is this?

For one thing, I think it’s a result of an unspoken norm at Krasnow to strive mightily away from the technical jargon of one’s field. For another, it’s the result of another de facto agreement to actually communicate intellectually outside one’s comfort zone. Taken together, the result is what has been called a “third culture”. From my own perspective as Institute director, this third culture is one where intellectuals actively appreciate the connection between human creative and artistic expression and the neural activity of brains that produce those expressions. Hence high culture becomes an emergent of interacting human minds, rather than a no-go zone for those well-steeped in the hard disciplines. At the same time, intellectuals in the social sciences are willing to explore and leverage the tools of hard science (especially computation and complexity theory).

C.P. Snow’s Two Cultures–FT vs NPR

Somehow both the Financial Times and NPR’s Science Friday have both decided that it’s time to return to pondering C.P. Snow’s famous “Two Cultures” lecture in which he postulates a problematical divide between scientists and scholars in the humanities. Actually the occasion is the 50th anniversary of that seminal lecture. It’s never lost its relevance.

Jim