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, ISBN 978-0385503860,
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 their individual
guesses were averaged (the average was closer to the ox's true
butchered weight than the estimates of most crowd members, and also
closer than any of the separate estimates made by cattle
experts).
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, but
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
- Thinking and information Processing
- 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 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.
- 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 (groups) 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's just
an eccentric interpretation of the known facts. |
| Independence |
People's opinions aren't 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 judgments into a
collective decision. |
Failures of crowd intelligence
Surowiecki studies situations (such as
rational 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 systematic
flaw.
Surowiecki asserts that what happens when the
decision-making environment is
not set up to accept the crowd, is that the benefits of individual
judgments and private
information are
lost and that the crowd can only do as well as its smartest member,
rather than perform better (as he shows is otherwise possible).
Detailed case histories of such failures include:
Extremity
| 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
Columbia shuttle
disaster, which he blames on a hierarchical NASA management
bureaucracy that was totally closed to the wisdom of low-level
engineers. |
| Division |
The
US 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 (of intelligence analyst in this case) work best when
they choose for themselves what to work on and what information
they need. (He cites the SARS-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.)
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
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.
Tim O’Reilly and others also discuss the success of
Google,
wikis,
blogging, and
Web 2.0 in the
context of the wisdom of crowds.
Applications
Surowiecki is a very 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 (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 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 its thesis, he says that his publisher are able to
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 the wisdom of a much broader 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."
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
(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.
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. 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. Those companies include
Piqqem,
Cake Financial,
Covestor,
Predictify, and the
Motley
Fool (with its Fool CAPS product).
Delphi methods
The Delphi method is a systematic, interactive
forecasting 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.
Criticism
In his book Embracing the Wide Sky,
Daniel
Tammet finds fault with this notion. He explains that this
notion may work in the Who Wants to be a Millionaire scenario
because audience members have various levels of knowledge that can
be coordinated to provide a correct answer in aggregate: Some
persons will know the correct answer, others will know what are not
the right answers and some will have no clue. Those who know the
right answer will choose it, and the others will choose among what
might seem the possible answers. The result will be to give a
slight edge to the correct answer, even if only a few actually know
the correct answer.
However, Tammet points out the potential for problems in systems
which have less well defined means of pooling knowledge: Subject
matter experts can be overruled and even wrongly punished by less
knowledgeable persons in systems like Wikipedia, citing a case of
this on Wikipedia. Furthermore, Tammet mentions the assessment of
the
accuracy of Wikipedia
as described in a study mentioned in Nature 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 the "Kasparov vs. the World," an online
competition that pitted the brainpower of tens of thousands of
online chess players choosing moves in a match against
Gary Kasparov, which was won by Kasparov, not
the "crowd."
See also
References
- Introduction (page XII): Although Surowiecki's description of
the "averaging" calculation (page XIII) implies that Galton first
calculated the mean,
inspection of the original 1907 paper indicates that Galton
considered the median the best reflection of the crowd's
estimate. ( ). 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 ( ); he thinks
the median, which is analogous to the 50% +1 vote, particularly
democratic.
- Sushil Bikhchandani, David Hirshleifer, Ivo Welch. October
1992. "A Theory of Fads, Fashion, Custom, and Cultural Change as
Informational Cascades." Journal of Political Economy,
Vol. 100, No. 5, pp. 992-1026.
- Independent Individuals and Wise Crowds, or Is It
Possible to Be Too Connected? at the 2005 Emerging Technology
Conference
- O'Reilly -- What Is Web 2.0
Further reading
- Bikhchandani, Sushil, David
Hirshleifer, and Ivo Welch. "A Theory
of Fads, Fashion, Custom, and Cultural Change as Informational Cascades." Journal
of Political Economy, Vol. 100, No.5, pp. 992-1026,
1992.
- Ivanov, Kristo (1972).
Quality-control of information: On the concept of accuracy of
information in data banks and in management information systems:
The University of Stockholm and The Royal Institute of Technology.
(Doctoral diss. Diss. Abstracts Int. 1974, Vol 35A, 3,
p. 1611-A. Nat. Techn. Info. Service NTIS order No. PB-219297
at fax +1 703 6056900, see summary [126522], orders@ntis.gov, [126523])
- Johnson, Steven, Emergence:
the connected lives of ants, brains, cities and software
(2002) Scribner, ISBN 0-684-86876-8
- Le Bon, Gustave. (1895), The
Crowd: A Study of the Popular Mind. Available from Project Gutenberg at [126524].
- Lee, Gerald Stanley. (1913). Crowds. A
moving-picture of democracy. Doubleday, Page & Company.
Available from Project Gutenberg
at [126525], retrieved May 2005.
- Sunstein, Cass R.,
Infotopia: How Many Minds Produce Knowledge (2006) Oxford
University Press, ISBN 0195189280
- Surowiecki, James (2004).
The Wisdom of Crowds: Why the Many Are Smarter Than the Few and
How Collective Wisdom Shapes Business, Economies, Societies and
Nations Little, Brown ISBN 0-316-86173-1
- Tarde, Gabriel (2001, orig. 1901).
L'opinion et la foule. BookSurge Publishing, ISBN
0543970833
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