CAN WE FORESEE TO DISAGREE?
Robin Hanson, George Mason University
Fri, Apr 25, 12:00-1:30 pm
3 Cambridge Center, MIT Building NE20, Room 336 Conference Room

Abstract
Nobel winner Robert Aumann (Economics 2005) showed in 1976 that Bayesians with a common prior could not "agree to disagree," i.e., have common knowledge of exact yet differing opinions.  Aumann made strong  assumptions, but similar results follow from much weaker assumptions: Bayesian wannabes who believe in symmetric prior origins cannot have common belief of one of them foreseeing how another will later disagree.  I review this literature, illustrate with concrete examples, and discuss the disturbing implications for the honesty and rationality of familiar human disagreement.

Speaker bio
Robin Hanson is an associate professor of economics at George Mason University, and a research associate at the Future of Humanity Institute of Oxford University. After receiving his Ph.D. in social science from the California Institute of Technology in 1997, Robin was a Robert Wood Johnson Foundation health policy scholar at the University of California at Berkeley. In 1984, Robin received a masters in physics and a masters in the philosophy of science from the University of Chicago, and afterward spent nine years researching artificial intelligence, Bayesian statistics, and hypertext publishing at Lockheed, NASA, and independently.

Robin has pioneered prediction markets, also known as information markets or idea futures, since 1988. He was the first to write in detail about people creating and subsidizing markets in order to gain better estimates on those topics. Robin was a principal architect of the first internal corporate markets, at Xanadu in 1990, of the first web markets, the Foresight Exchange since 1994, and of DARPA's Policy Analysis Market, from 2001 to 2003.

Robin has diverse research interests, with papers on spatial product competition, health incentive contracts, group insurance, product bans, evolutionary psychology and bioethics of health care, voter information incentives, incentives to fake expertize, Bayesian classification, agreeing to disagree, self-deception in disagreement, probability elicitation, wiretaps, image reconstruction, the history of science prizes, reversible computation, the origin of life, the survival of humanity, very long term economic growth, growth given machine intelligence, and interstellar colonization.