Foresight 2010 debate: Futarchy from Monica Anderson on Vimeo.

Download this post to watch the video —if your feed reader does not show it to you.

Who cares about that Mencius Moldbug anyway?

Previously.

Powered by MIT ideas — Much more useful than Robin Hanson’s decision-aid markets.

Great usability. I registered and tested it. They are onto something. Besides NetFlix, have you ever heard of other collective intelligence tool of this kind? Leave the URLs in the comments.

Find here a good review of “Predictocracy” —via Daniel Horowitz.

The term “decision analysis” has multiple meanings in Bayesian statistics. When we use the term here, we are not talking about problems of parameter estimation, squared error loss, etc. Rather, we use “decision analysis” to refer to the solution of particular decision problems (such as in medicine, public health, or business) by averaging over uncertainties as estimated from a probability model. (See here for an example.)

That said, decision analysis has fundamental difficulties, most notably that it requires one to set up a utility function, which on one hand can be said to represent subjective feelings but on the other hand is presumably solid enough that it is worth using as the basis for potentially elaborate calculations.

From a foundational perspective, this problem can be resolved using the concept of institutional decision analysis.

Go reading the rest.

And then you come back here, and you try to explain it to moi —because that sounds very, very smart.

[...] The hard part, the real hurdles to acceptance are (i) to get wide and consistent participation, (ii) to overcome the suspicion of decision makers who naturally don’t like to be second-guessed by subordinates, (iii) to get the organization to agree to ask important questions instead of trivial ones.

Go also read Paul Hewitt’s take on Emile’s latest paper.

In the conclusion of their introduction, Robert Hahn and Paul Tetlock wrote that they want their readers to contemplate the idea that prediction markets could make a “big” difference and “revolutionize public- and private-sector decision-making”. Well, 4 years later, it is clear that those big dreams didn’t pan out. Not a single mass media outlet has praised the public prediction markets for their work on the 2008 US presidential election (I am taking about a post-mortem analysis about Election Day, not the primaries). Not a single one. (Not even Justin Wolfers.) And the number of corporations using enterprise prediction markets is still minute. The thinkers who wrote this book (“Information Markets”) all made the mistake to put the emphasis on accuracy instead of efficiency. That was the foundation flaw. We should reset and reboot the field of prediction markets.

Previously: The truth about prediction markets