A Republican appointee sitting with two Democratic appointees votes about as liberally as a Democratic appointee sitting with two Republicans, making the two essentially indistinguishable—a striking testimony to the power of social influence over ideology.

There is no evidence of prediction markets seriously failing in domains where dispersed information exists; attempts to inflate prices for candidates like Pat Buchanan and Hillary Clinton on the Iowa Electronic Markets failed because traders saw the inflation and profitably bet against it, straightening prices out.

A survey or prediction market inside the CIA on whether Iraq had weapons of mass destruction would likely have produced a less confident answer than the official government position, because there was substantial dispersed information within the agency about the difficulty of that question.

Federal judicial voting demonstrates group polarization with real (non-experimental) data: Democratic appointees vote much more liberally on all-Democratic three-judge panels than when a Republican is present, and Republicans likewise vote far more conservatively on all-Republican panels, with each becoming more moderate when an opposing appointee is present.

The best way to structure a deliberating group is to have members state their views anonymously and privately before deliberation, so the deliberative process cannot strip members of the independent conclusions they held beforehand.

Sunstein's behavioral critique of Hayek is that the same problems that make deliberation go wrong can make the price system go wrong—producing fads, fashions, and mispricing for non-trivial periods (as Shiller's 'Irrational Exuberance' argues)—but markets have correctives that make such errors less enduring, and prediction markets specifically show no empirical evidence of such failures.

Crowd wisdom fails when there is a systematic bias—for example, when people systematically underestimate the number of times the Supreme Court invalidated laws because salient examples are few, or systematically overestimate the share of the workforce earning minimum wage.

There is strikingly little difference in predictive power between high-incentive real-money prediction markets and low-incentive 'virtual' markets, suggesting that reputation, honor, and self-conception motivate participants to get it right even without large financial stakes.

Deliberating groups often amplify cognitive errors rather than just propagate them—groups can be worse victims of biases like the availability heuristic than individuals—so 'garbage in' leads to even more 'garbage out.'

Deliberating groups tend to emphasize information that everyone already shares while neglecting uniquely-held information that only one member possesses, producing 'hidden profiles' where crucial private knowledge is downplayed and the group marches in the direction indicated by common knowledge.

The best-functioning companies, boards, and investment clubs deliberately cultivate dissent and disagreement and take institutional steps to counteract group polarization, demonstrating that deliberation can be structured to work better rather than being abandoned.

Deliberation works well on 'Eureka' problems where, once the answer is announced, everyone immediately recognizes it as correct—which is why large groups can solve crossword puzzles better than small groups.

The Supreme Court's diversity (nine justices) and the strength of will of its members serve as a safeguard against the polarization, hidden-profile, and cascade problems that afflict other government agencies and businesses.

Hayek's 1945 article 'The Use of Knowledge in Society' established that information is profoundly dispersed—each person holds a bit of it—and that the price system is a marvel because it aggregates this dispersed information into a single signal, an insight whose implications have yet to be adequately exploited.

When you ask a large group to estimate an objective quantity (like the weight of an ox or a horse, or beans in a jar), the statistical average of their independent judgments is often uncannily accurate and frequently better than any individual member, even an expert.

The Condorcet Jury Theorem shows that if each member of a group is more likely than not to get the right answer, the probability that the majority gets it right approaches 100% as group size grows; but if the group suffers a systematic bias making them more likely wrong than right, that probability falls to 0% as the group grows.

The important point is the mechanism, not the example: when a large group of people are mostly more likely than not to get it right, statistical aggregation outperforms picking the single expert you trust most, which is why statistical collections of experts typically outperform individual experts in forecasting business and economic outcomes.

Prediction markets improve on surveys by giving participants an incentive to enter only when they have confidence in their judgment, and by allowing prices to dynamically self-correct over time; at Google, prediction-market prices function as accurate probabilities (events priced at 80% occur about 80% of the time).

After deliberation, people typically end up holding a more extreme version of what they thought before the discussion began (group polarization), and this is close to an iron law of social interactions, demonstrated in controlled experiments such as the Colorado study where Boulder liberals became more pro-affirmative-action and Colorado Springs conservatives more anti.

Government should make much greater use of prediction markets—for example the EPA on climate change and environmental problems, and the FCC on the effects of deregulating cross-ownership rules on program content—because they are the most successful mechanism for compiling dispersed information.