The thesis of the book, as the author states at the beginning:
under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them. Groups do not need to be dominated by exceptionally intelligent people in order to be smart.
The book begins with a series of examples of “crowd wisdom”, ranging from the TV show “Who Wants to be a Millionaire?” and its “ask the audience”, to the stock market indicating the company most likely to be at fault hours after the Challenger disaster. These cases all demonstrate the four conditions that comprise wise crowds - independence, diversity of opinion, decentralization, and a way to aggregate the results. Similar results are to be found in sports betting, and in Google’s results, determined by examining the number of links pointing to any given page. One way to take advantage of this wisdom of crowds is through the use of ”prediction markets”, such as the Iowa Electronic Markets, where people buy and sell probabilities as if they were stocks. In the right circumstances, prediction markets are an excellent way of turning the knowledge of many people into reasonably accurate predictions.
The importance of diversity is covered in the second chapter. A crowd can’t be wise if everyone always picks the same answer as everyone else. Examples include product markets, where there is usually an initial wide range of different attempts in a new market, which is quickly winnowed down to the successful designs; and honey bees, which send out scouts in all directions, but only return to those areas where flowers have been found. Diversity is important to “wise crowds”, because it expands the range of possible solutions proposed. In large groups, diversity comes naturally, but in smaller groups, it’s necessary to support and actively encourage it, to avoid the dangers of “groupthink”. When people give in to their conformist tendencies, and are afraid to stick their necks out, the quality of decisions suffers.
Independence of action and thought is important for the wisdom of crowds. If everyone thinks alike, then they’re less likely to arrive at a good answer to a given problem, because they’re less likely to fall into “groupthink”. “The more influence we exert on each other, the more likely it is that we will believe the same things and make the same mistakes”.
American Football coaching is cited an example of the “herd mentality”, based on the work of David Romer examining the “best 4th down strategy” (pdf). It turns out that statistically, most teams would be better off trying to make the touchdown or 1st down, rather than going for the field goal, in many cases. However, since the accepted wisdom is to kick, going against the grain of the relatively small pool of decision makers (professional football coaches) would not be an easy choice to make consistently, especially for the risk averse.
Herding behavior often occurs because people seek safety in numbers, but it can lead to problematic results when independence is required. “Information cascades” are what occurs when an initial decision is made by a few people, and then more or less accepted uncritically by more and more people. This isn’t necessarily a recipe for disaster, as we can’t all evaluate everything in our lives, but must trust others to come to good conclusions. However, at times, it can be disastrous when the original information and decisions were wrong, but continue to be accepted by an ever-wider circle. Luckily, for most people, the more important a decision is, the more likely they are to examine the facts themselves, rather than simply fall in line. Information cascades actually work reasonably well much of the time, but the basic problem is that they are a sequential, rather than parallel process. If you’re trying to harness the wisdom of crowds, you must attempt to have all decisions made at the same time, rather than one at a time.
The book’s web site: http://www.randomhouse.com/features/wisdomofcrowds/
Wikipedia page on the book: http://en.wikipedia.org/wiki/The_Wisdom_of_Crowds