The Wisdom of Crowds
The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations, published in 2004, is a book written by James Surowiecki about the aggregation of information in groups, resulting in decisions that, he argues, are often better than could have been made by any single member of the group. The book presents numerous case studies and anecdotes to illustrate its argument, and touches on several fields, primarily economics and psychology.
The opening anecdote relates Francis Galton's surprise that the crowd at a county fair accurately guessed the weight of an ox when the median of their individual guesses was taken.
The book relates to diverse collections of independently deciding individuals, rather than crowd psychology as traditionally understood. Its central thesis, that a diverse collection of independently deciding individuals is likely to make certain types of decisions and predictions better than individuals or even experts, draws many parallels with statistical sampling; however, there is little overt discussion of statistics in the book.
Its title is an allusion to Charles Mackay's Extraordinary Popular Delusions and the Madness of Crowds, published in 1841.
Types of crowd wisdom
Surowiecki breaks down the advantages he sees in disorganized decisions into three main types, which he classifies as;Cognition: Thinking and information processing, such as market judgment, which he argues can be much faster, more reliable, and less subject to political forces than the deliberations of experts or expert committees.
;Coordination: Coordination of behavior includes optimizing the utilization of a popular bar and not colliding in moving traffic flows. The book is replete with examples from experimental economics, but this section relies more on naturally occurring experiments such as pedestrians optimizing the pavement flow or the extent of crowding in popular restaurants. He examines how common understanding within a culture allows remarkably accurate judgments about specific reactions of other members of the culture.
;Cooperation: How groups of people can form networks of trust without a central system controlling their behavior or directly enforcing their compliance. This section is especially pro free market.
Four elements required to form a wise crowd
Not all crowds are wise. Consider, for example, mobs or crazed investors in a stock market bubble. According to Surowiecki, these key criteria separate wise crowds from irrational ones:| Criteria | Description |
| Diversity of opinion | Each person should have private information even if it is just an eccentric interpretation of the known facts. |
| Independence | People's opinions are not determined by the opinions of those around them. |
| Decentralization | People are able to specialize and draw on local knowledge. |
| Aggregation | Some mechanism exists for turning private judgements into a collective decision. |
Based on Surowiecki's book, Oinas-Kukkonen captures the wisdom of crowds approach with the following eight conjectures:
- It is possible to describe how people in a group think as a whole.
- In some cases, groups are remarkably intelligent and are often smarter than the smartest people in them.
- The three conditions for a group to be intelligent are diversity, independence, and decentralization.
- The best decisions are a product of disagreement and contest.
- Too much communication can make the group as a whole less intelligent.
- Information aggregation functionality is needed.
- The right information needs to be delivered to the right people in the right place, at the right time, and in the right way.
- There is no need to chase the expert.
Failures of crowd intelligence
Causes and detailed case histories of such failures include:
| Extreme | Description |
| Homogeneity | Surowiecki stresses the need for diversity within a crowd to ensure enough variance in approach, thought process, and private information. |
| Centralization | The 2003 Space Shuttle Columbia disaster, which he blames on a hierarchical NASA management bureaucracy that was totally closed to the wisdom of low-level engineers. |
| Division | The United States Intelligence Community, the 9/11 Commission Report claims, failed to prevent the 11 September 2001 attacks partly because information held by one subdivision was not accessible by another. Surowiecki's argument is that crowds work best when they choose for themselves what to work on and what information they need. The Office of the Director of National Intelligence and the CIA have created a Wikipedia-style information sharing network called Intellipedia that will help the free flow of information to prevent such failures again. |
| Imitation | Where choices are visible and made in sequence, an "information cascade" can form in which only the first few decision makers gain anything by contemplating the choices available: once past decisions have become sufficiently informative, it pays for later decision makers to simply copy those around them. This can lead to fragile social outcomes. |
| Emotionality | Emotional factors, such as a feeling of belonging, can lead to peer pressure, herd instinct, and in extreme cases collective hysteria. |
Connection
At the 2005 O'Reilly Emerging Technology Conference Surowiecki presented a session entitled Independent Individuals and Wise Crowds, or Is It Possible to Be Too Connected?He recommends:
- Keep your ties loose.
- Keep yourself exposed to as many diverse sources of information as possible.
- Make groups that range across hierarchies.
Applications
Surowiecki is a strong advocate of the benefits of decision markets and regrets the failure of DARPA's controversial Policy Analysis Market to get off the ground. He points to the success of public and internal corporate markets as evidence that a collection of people with varying points of view but the same motivation can produce an accurate aggregate prediction. According to Surowiecki, the aggregate predictions have been shown to be more reliable than the output of any think tank. He advocates extensions of the existing futures markets even into areas such as terrorist activity and prediction markets within companies.To illustrate this thesis, he says that his publisher can publish a more compelling output by relying on individual authors under one-off contracts bringing book ideas to them. In this way, they are able to tap into the wisdom of a much larger crowd than would be possible with an in-house writing team.
Will Hutton has argued that Surowiecki's analysis applies to value judgments as well as factual issues, with crowd decisions that "emerge of our own aggregated free will
Applications of the wisdom-of-crowds effect exist in three general categories: Prediction markets, Delphi methods, and extensions of the traditional opinion poll.
Prediction markets
The most common application is the prediction market, a speculative or betting market created to make verifiable predictions. Surowiecki discusses the success of prediction markets. Similar to Delphi methods but unlike opinion polls, prediction markets ask questions like, "Who do you think will win the election?" and predict outcomes rather well. Answers to the question, "Who will you vote for?" are not as predictive.Assets are cash values tied to specific outcomes or parameters. The current market prices are interpreted as predictions of the probability of the event or the expected value of the parameter. Betfair is the world's biggest prediction exchange, with around $28 billion traded in 2007. NewsFutures is an international prediction market that generates consensus probabilities for news events. Intrade.com, which operated a person to person prediction market based in Dublin Ireland achieved very high media attention in 2012 related to the US Presidential Elections, with more than 1.5 million search references to Intrade and Intrade data. Several companies now offer enterprise class prediction marketplaces to predict project completion dates, sales, or the market potential for new ideas. A number of Web-based quasi-prediction marketplace companies have sprung up to offer predictions primarily on sporting events and stock markets but also on other topics. The principle of the prediction market is also used in project management software to let team members predict a project's "real" deadline and budget.