Robin Hanson: My best idea was prediction markets.

Robin Hanson‘s auto-biography (i.e., how Our Master Of All Universes views HimSelf):

robin-hanson-drink

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Robin Hanson:

Do you find it hard to summarize yourself in a few words? Me too.

But I love the above quote. I have a passion, a sacred quest, to understand everything, and to save the world. I am addicted to “viewquakes”, insights which dramatically change my world view. I loved science fiction as a child, and have studied physics, philosophy, artificial intelligence, economics, and political science — all fields full of such insights. Unfortunately, this also tempted me to leave subjects after mastering their major insights.

I also have a rather critical style. I beat hard on new ideas, seek out critics, and then pledge my allegiance only to those still left standing. In conversation, I prefer to identify a claim at issue, and then focus on analyzing it, rather than the usual quick tours past hundreds of issues. I have always asked questions, even when I was very young.

I have little patience with those whose thinking is sloppy, small, or devoid of abstraction. And I’m not a joiner; I rebel against groups with “our beliefs”, especially when members must keep criticisms private, so as not to give ammunition to “them.”  I love to argue one on one, and common beliefs are not important for friendship — instead I value honesty and passion.

In ‘77 I began college (UCI) in engineering, but switched to physics to really understand the equations.  Two years in, when physics repeated the same concepts with more math,  I studied physics on my own, skipping the homework but acing the exams.  To dig deeper, I did philosophy of science grad school (U Chicago), switched back to physics, and was then seduced to Silicon Valley.

By day I did artificial intelligence (Lockheed, NASA), and by night I studied on my own (Stanford) and hung with Xanadu’s libertarian web pioneers and futurists.  I had a hobby of institution design; my best idea was idea futures, now know as prediction markets. Feeling stuck without contacts and credentials, I went for a Ph.D. in social science (Caltech).

The physicist in me respected only econ experiments at first, but I was soon persuaded econ theory was full of insight, and did a theory thesis, and a bit of futurism on the side.  I landed a health policy postdoc, where I was shocked to learn of medicine’s impotency.  I finally landed a tenure-track job (GMU), and also found the wide-ranging intellectual conversations I’d lacked since Xanadu.

My Policy Analysis Market project hit the press shit fan in ‘03, burying me in media attention for a while, and helping to kickstart the prediction market industry, which continues to grow and for which I continue to consult.  The press flap also tipped me over the tenure edge in ‘05; my colleagues liked my being denounced by Senators. :)   Tenure allowed me to maintain my diverse research agenda, and to start blogging at Overcoming Bias in November ‘06, about the same time I became a research associate at Oxford’s Future of Humanity Institute.

My more professional bio is here.

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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 over 70 publications, including articles in Applied Optics, Business Week, CATO Journal, Communications of the ACM, Economics Letters, Econometrica, Economics of Governance, Extropy, Forbes, Foundations of Physics, IEEE Intelligent Systems, Information Systems Frontiers, Innovations, International Joint Conference on Artificial Intelligence, Journal of Economic Behavior and Organization, Journal of Evolution and Technology, Journal of Law Economics and Policy, Journal of Political Philosophy, Journal of Prediction Markets, Journal of Public Economics, Medical Hypotheses, Proceedings of the Royal Society, Public Choice, Social Epistemology, Social Philosophy and Policy, Theory and Decision, and Wired.

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 developed new technologies for conditional, combinatorial, and intermediated trading, and has studied insider trading, manipulation, and other foul play. Robin has written and spoken widely on the application of idea futures to business and policy, being mentioned in over one hundred press articles on the subject, and advising many ventures, including Consensus Point, GuessNow, Newsfutures, Particle Financial, Prophet Street, Trilogy Advisors, XPree, YooNew, and undisclosable defense research projects.

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.

Are good blogs driven by author personalities or by well drilled topics?

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Justin Wolfers has escaped the Overcoming Bias purge, it seems. Justin Wolfers’-s 4 posts (published in 2007) remain archived on what is now Robin Hanson’-s QUOTE personal blog UNQUOTE. By contrast, Eliezer Yudkowsky’-s posts written for Overcoming Bias now redirect to locations at Less Wrong.

Justin Wolfers now blogs at Freakonomics (which is under the New York Times umbrella). By comparison to Overcoming His Bias, Freakonomics is a real group blog success. Years later after his creation, Freaknomics has a high degree of participation by his co-bloggers, and some brand-new guest bloggers were recently invited. Freakonomics is a sustainable group blog which develops one unique thematic —-economics. Sorry to burst our Master Of All Universes’-s bubble, but Freakonomics is the case-in-point that debunks the hypothesis that says that “-blogs are best defined not by topic but by lead author personalities”-.

As for Midas Oracle, who cares about Chris Masse’-s personality, as long as one gets his/her prediction market dope on a daily basis?

UPDATE:

Robin Hanson:

Chris, Eliezer was not “purged.” He requested to have his old posts moved to Less Wrong. No one else has made any similar request.

Eliezer was not “expelled”- he choose to move in order to build a community at Less Wrong using fancy comment karma software. The folks who wrote software for his new site also wrote the code at my new site.

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They love coding too much.

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- The people that Robin Hanson expelled from his blog are coding their own blogging software.

- As for Our Master Of All Universes, he codes his own WordPress theme (overcomingbias.com/wp-content/themes/overcoming-bias/) and inserts his own hacks into it.

UPDATE:

Robin Hanson:

Chris, Eliezer was not “purged.” He requested to have his old posts moved to Less Wrong. No one else has made any similar request.

Eliezer was not “expelled”- he choose to move in order to build a community at Less Wrong using fancy comment karma software. The folks who wrote software for his new site also wrote the code at my new site.

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Why CrowdCast ditched Robin Hansons MSR as the engine of its IAM software

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Dump

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Leslie Fine of CrowdCast:

Chris,

As Emile points out, in 2003 I started experimenting with (and empirically validating) alternatives to the traditional stock-market metaphor that will be more viable in corporate settings. We found the level of confusion and lack of interest in the usual fare led to a death spiral of disuse and inaccuracy. BRAIN was a first stake in the ground in prediction market mechanism design with usability as a fundamental premise.

When I joined Crowdcast (then Xpree) in August of 2008, Mat and the team already recognized the confusion around, and consequent poor adoption of, the MSR mechanism. The number of messages I fielded in my first month here asking me to explain pricing, shorting, how to make money, etc. was astounding. We all knew that we had to start from scratch, and rebuild a mechanism that was easy to use, expressive both in terms of the question one can ask and the message space in which one can answer, and provided a high level of user engagement. We have abandoned the MSR in favor of a new method that users are already finding much simpler and that requires a lower level of participation and sophistication than the usual stock market analogy.

I wish I could go into more detail. However, we need to keep a little bit of a lid on things for our upcoming launch. I can only beg your patience a little while longer, and I hope you will judge our offering worth the wait.

Regards,
Leslie

Nota Bene: IAM = information aggregation mechanism

UPDATE: They are out with their new collective forecasting mechanism.

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Robin Hanson has convinced Concensus Point to support combinatorial prediction markets.

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Robin Hanson:

I’-ve developed a combinatorial betting tech that lets a few or many users edit an always-coherent joint probability distribution over all value combinations of some set of base variables. Far futures base variables might include the years of important tech milestones, population, wealth, or mortality values at particular future dates, etc. Each user edit would be backed by a bet, a bet invested in assets paying competitive interest/returns. This combo bet tech worked well in published lab tests, several firms have used it, and I’-m now working with Consensus Point to deliver a robust commercial implementation. More on the tech here, here, and here.

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See the explainer from David Pennock, which we will link to, again, later on.

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The San Francisco conference on prediction markets

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I previously wrote that that San Francisco vendor conference is not worth the $400 they are asking. However, in all honesty to my readers, I shall notify that they have just made one (small) change that goes in the right direction. World’-s #1 prediction market researcher Robin Hanson is now scheduled to talk about combinatorial prediction markets (a very hot topic these days) —-instead of stuff about how to quantify prediction market value (a too much theoretical issue for business people).

A vendor conference with no editorial line is unlikely to be the receptacle of the truth about enterprise prediction markets. Vendors (4 will be present) do oversell.

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InTrade CEO John Delaney states that prediction markets can prevent the next financial cataclysms. Surely. Prediction markets can also restore womens virginity, and treat mens baldness.

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John Delaney states rightfully that the prediction markets are a mechanism that aggregates information dispersed among the population. Then, he goes on at full throttle and states that prediction markets can help “-avoiding future [financial] crisis.”-

Jesus, Mary, Joseph, that’-s quite an extraordinary statement.

John Delaney writes that crucial information is buried deep in the accounting books. That’-s true, but that’-s up to the financial analysts to decipher this problematic —-our event derivative traders can then just pick up on what those experts conclude. The financial experts were unable to prevent the current financial cataclysm. Adding more event derivative traders and more prediction markets won’-t solve any problem.

Prediction markets are only a reflection of the current knowledge of the best experts in town. At best, they are the best umpire you can get between, on one hand, the mass media or the politicians and, on the other hand, the best experts. But when nobody knows anything (or when nobody listens to Nouriel Roubini), the prediction markets are of no help.

What the prediction market industry needs right now is not an ill-informed, bragging rant.

What the prediction market industry needs is a way to discriminate between accuracy and utility.

What we need is more of Robin Hanson.

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UPDATE: