 Cover of mass market edition by Anchor | |
| Author | James Surowiecki |
|---|---|
| Language | English |
| Publisher | Doubleday; Anchor |
Publication date | 2004 |
| Publication place | United States |
| Pages | 336 |
| ISBN | 978-0-385-50386-0 |
| OCLC | 61254310 |
| 303.3/8 22 | |
| LC Class | JC328.2 .S87 2005 |
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 byJames 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 andanecdotes to illustrate its argument, and touches on several fields, primarilyeconomics andpsychology.
The opening anecdote relatesFrancis Galton's surprise that the crowd at a county fair accurately guessed the weight of anox when the median of their individual guesses was taken (the median was closer to the ox's true butchered weight than the estimates of most crowd members).[1][2]
The book relates to diverse collections of independently deciding individuals, rather thancrowd 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 statisticalsampling; however, there is little overt discussion of statistics in the book.
Its title is an allusion toCharles Mackay'sExtraordinary Popular Delusions and the Madness of Crowds, published in 1841.[3]
Surowiecki breaks down the advantages he sees in disorganized decisions into three main types, which he classifies as
Not all crowds (groups) are wise. Consider, for example, mobs or crazed investors in astock market bubble. According to Surowiecki, these key criteria separate wise crowds from irrational ones:
| Criteria | Description |
|---|---|
| Diversity ofopinion | Each person should have private information even if it is just aneccentric interpretation of the known facts. (Chapter 2) |
| Independence | People's opinions are not determined by the opinions of those around them. (Chapter 3) |
| Decentralization | People are able to specialize and draw on local knowledge. (Chapter 4) |
| Aggregation | Some mechanism exists for turning private judgements into a collectivedecision. (Chapter 5) |
Based on Surowiecki's book, Oinas-Kukkonen[4] captures the wisdom of crowds approach with the following eight conjectures:
Surowiecki studies situations (such asrational bubbles) in which the crowd produces very bad judgment, and argues that in these types of situations their cognition or cooperation failed because (in one way or another) the members of the crowd were too conscious of the opinions of others and began to emulate each other and conform rather than think differently. Although he gives experimental details of crowds collectively swayed by a persuasive speaker, he says that the main reason that groups of people intellectually conform is that the system for making decisions has a systemic flaw.
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 | The2003 Space ShuttleColumbia disaster, which he blames on a hierarchicalNASA management bureaucracy that was totally closed to the wisdom of low-level engineers. |
| Division | TheUnited States Intelligence Community, the9/11 Commission Report claims, failed to prevent the11 September 2001 attacks partly because information held by one subdivision was not accessible by another. Surowiecki's argument is that crowds (ofintelligenceanalysts in this case) work best when they choose for themselves what to work on and what information they need. (He cites theSARS-virus isolation as an example in which the free flow of data enabled laboratories around the world to coordinate research without a central point of control.) TheOffice of the Director of National Intelligence and theCIA have created aWikipedia-style information sharing network calledIntellipedia 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"[5] 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 topeer pressure,herd instinct, and in extreme casescollective hysteria. |
At the 2005O'ReillyEmerging Technology Conference Surowiecki presented a session entitledIndependent Individuals and Wise Crowds, or Is It Possible to Be Too Connected?[6]
The question for all of us is, how can you have interaction withoutinformation cascades, without losing the independence that's such a key factor in group intelligence?
He recommends:
Tim O'Reilly[7] and others also discuss the success ofGoogle,wikis,blogging, andWeb 2.0 in the context of the wisdom of crowds.
Surowiecki is a strong advocate of the benefits of decision markets and regrets the failure ofDARPA's controversialPolicy 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 (to make a good guess) can produce an accurate aggregate prediction. According to Surowiecki, the aggregate predictions have been shown to be more reliable than the output of anythink tank. He advocates extensions of the existing futures markets even into areas such asterrorist 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 [being] astonishingly... decent". He concludes that "There's no better case for pluralism, diversity and democracy, along with a genuinely independent press."[8]
Applications of the wisdom-of-crowds effect exist in three general categories:Prediction markets,Delphi methods, and extensions of thetraditional opinion poll.
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 toDelphi methods but unlikeopinion polls, prediction (information) 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.[9]
Assets are cash values tied to specific outcomes (e.g., Candidate X will win the election) or parameters (e.g., Next quarter's revenue). 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.[citation needed] 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 inproject management software to let team members predict a project's "real" deadline and budget.
The Delphi method is a systematic, interactiveforecasting method which relies on a panel of independent experts. The carefully selected experts answer questionnaires in two or more rounds. After each round, a facilitator provides an anonymous summary of the experts' forecasts from the previous round as well as the reasons they provided for their judgments. Thus, participants are encouraged to revise their earlier answers in light of the replies of other members of the group. It is believed that during this process the range of the answers will decrease and the group will converge towards the "correct" answer. Many of the consensus forecasts have proven to be more accurate than forecasts made by individuals.
Designed as an optimized method for unleashing the wisdom of crowds, this approach implements real-time feedback loops around synchronous groups of users with the goal of achieving more accurate insights from fewer numbers of users. Human Swarming (sometimes referred to as Social Swarming) is modeled after biological processes in birds, fish, and insects, and is enabled among networked users by using mediating software such as theUNU collective intelligence platform. As published by Rosenberg (2015), such real-time control systems enable groups of human participants to behave as a unifiedcollective intelligence.[10] When logged into the UNU platform, for example, groups of distributed users can collectively answer questions, generate ideas, and make predictions as a singular emergent entity.[11][12] Early testing shows that human swarms can out-predict individuals across a variety of real-world projections.[13][14]
Hugo-winning writerJohn Brunner's 1975science fiction novelThe Shockwave Rider includes an elaborate planet-wide information futures andbetting pool called "Delphi" based on the Delphi method.
IllusionistDerren Brown claimed to use the 'Wisdom of Crowds' concept to explain how he correctly predicted theUK National Lottery results in September 2009. His explanation was met with criticism on-line, by people who argued that the concept was misapplied.[15] The methodology employed was too flawed; the sample of people could not have been totally objective and free in thought, because they were gathered multiple times and socialised with each other too much; a condition Surowiecki tells us is corrosive to pure independence and the diversity of mind required (Surowiecki 2004:38). Groups thus fall intogroupthink where they increasingly make decisions based on influence of each other and are thusless accurate. However, other commentators have suggested that, given the entertainment nature of the show, Brown's misapplication of the theory may have been a deliberate smokescreen to conceal his true method.[16][17]
This was also shown in the television series East of Eden where a social network of roughly 10,000 individuals came up with ideas to stop missiles in a very short span of time.[citation needed]
Wisdom of Crowds would have a significant influence on the naming of the crowdsourcing creative companyTongal, which is an anagram for Galton, the last name of the social-scientist highlighted in the introduction to Surowiecki's book.Francis Galton recognized the ability of a crowd's median weight-guesses for oxen to exceed the accuracy of experts.[18]
In his bookEmbracing the Wide Sky,Daniel Tammet finds fault with this notion. Tammet points out the potential for problems in systems which have poorly defined means of pooling knowledge: Subject matter experts can be overruled and even wrongly punished by less knowledgeable persons in crowd sourced systems, citing a case of this on Wikipedia. Furthermore, Tammet mentions the assessment of theaccuracy of Wikipedia as described in a study mentioned inNature in 2005, outlining several flaws in the study's methodology which included that the study made no distinction between minor errors and large errors.
Tammet also cites theKasparov versus the World, an online competition that pitted the brainpower of tens of thousands of online chess players choosing moves in a match againstGarry Kasparov, which was won by Kasparov, not the "crowd". Although Kasparov did say, "It is the greatest game in the history of chess. The sheer number of ideas, the complexity, and the contribution it has made to chess make it the most important game ever played."
In his bookYou Are Not a Gadget,Jaron Lanier argues that crowd wisdom is best suited for problems that involve optimization, but ill-suited for problems that require creativity or innovation. In the online articleDigital Maoism, Lanier argues that the collective is more likely to be smart only when
Lanier argues that only under those circumstances can a collective be smarter than a person. If any of these conditions are broken, the collective becomes unreliable or worse.
Iain Couzin, a professor in Princeton's Department of Ecology and Evolutionary Biology, and Albert Kao, his student, in a 2014article, in the journal Proceedings of the Royal Society, argue that "the conventional view of the wisdom of crowds may not be informative in complex and realistic environments, and that being in small groups can maximize decision accuracy across many contexts." By "small groups," Couzin and Kao mean fewer than a dozen people.They conclude and say that “the decisions of very large groups may be highly accurate when the information used is independently sampled, but they are particularly susceptible to the negative effects of correlated information, even when only a minority of the group uses such information.”
the middlemost estimate expresses the vox populi). Galton's quotation from the end of this paper (given by Surowiecki on page XIII) actually refers to the surprising proximity of the median and the measurement, and not to the (much closer) agreement of mean and measurement (which is the context Surowiecki gives it in). The mean (only 1 pound, rather than 9, from the ox's weight) was only calculated in Galton's subsequent reply to a letter from a reader, though he still advocates use of the median over any of the "several kinds" of mean (Galton, Francis (1907-03-28)."Letters to the Editor: The Ballot-Box".Nature.75 (1952): 509.doi:10.1038/075509e0.S2CID 3996739.
my proposal that juries should openly adopt the median when estimating damages, and councils when estimating money grants, has independent merits of its own); he thinks the median, which is analogous to the 50% +1 vote, particularly democratic.
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