Earlier this year, experts gathered at the hub of the universe (which is Harvard, it seems) to suggest and debate the big, unsolved problems in the social sciences, economics between them. From a press release:
Initiated and funded by the non-profit Indira Foundation, this effort was inspired by David Hilbert, who challenged the world to solve 23 fundamental mathematical problems in 1900. Since then, mathematicians have solved 10 of the now-famous ‘Hilbert Problems’, creating new fields of knowledge along the way.
“Hilbert made two powerful observations,” said Nicholas Nash, a member of the Indira Foundation. “First, having important, unsolved problems is essential to the vitality of a discipline. And, as important, by identifying those problems, we can inspire future generations to solve them.”
Taleb was there, not surprisingly, and suggested the ‘Black Swan problem’:
How can we be robust against “Black Swans”; that is, how can we (1) identify domains where these consequential rare events play a large role (these are too rare for any statistical models track them properly), and (2) instead of predicting Black Swans, build systems and societies that can resist their shocks.
King suggested the problem of international institutions:
What is the relationship between strong international institutions and international cooperation? Do strong international institutions lead to or result from international cooperation?
King also suggested a methodological problem:
A major methodological problem is how to avoid (or ameliorate) post-treatment bias in big social science questions. Post-treatment bias occurs when the causal ordering among predictors is ambiguous or wrong or when, in an attempt to control for confounding variables, one controls away a consequential variable.