Book Review of The Wisdom of Crowds by James Surowiecki

This post may contains affiliate links. If you click and buy we may make a commission, at no additional charge to you. Please see our disclosure policy for more details.

This Book Review of The Wisdom of Crowds by James Surowiecki is brought to you from Clark Moody from the Titans of Investing.

Genre: Marketing & Consumer Behavior
Author: James Surowiecki
Title: The Wisdom of Crowds (Buy the Book)


In 1841 Charles Mackay wrote Extraordinary Popular Delusions and the Madness of Crowds. His book became a classic, and as a result, it is now conventional wisdom that crowds are poor decision makers. Is that conclusion accurate? James Surowiecki in his recent book The Wisdom of Crowds gives the answer. His conclusion is that when the proper conditions exist crowds are indeed very wise, and they will outperform experts and even the most intelligent within the crowd itself.

For crowds to be effective and wise, five conditions must be present:

  1. Diversity: Individuals have “private knowledge” and insights that stem from their varying levels of knowledge, personal experience and ways of thinking about the world. No one person should expect to be able to replicate that alone. Any single individual will often be unjustifiably overconfident and unable to properly calibrate his own judgment.
  2. Independence: Protecting independence of thought is vital to creating wisdom. Thus, the views of individuals in a diverse group are best gathered separately (outside a group session) before being aggregated. Using this method allows mistakes and errors in judgment to cancel out and prevents both herding and information cascading.
  3. Decentralization: People closest to the problem are the most likely to have the specialization and tacit knowledge required to solve the issue. Decentralized decision making to those closest to the problem and most accountable for the results will generally produce the wisest solutions. However, decentralization can also trap knowledge that would benefit the larger entity inside a single unit, and that should be avoided.
  4. Coordination: People are inherently good at coordinating themselves and producing nearly optimal solutions despite an absence of communication. This deals with the reasoning of groups, in addition to the reasoning of individuals.
  5. Aggregation: The best ideas of a diverse and independent group are useless in the absence of a proper aggregation method. Without proper aggregation, the information produced by crowds is nothing more than noise. Many times that aggregation is as simple as counting up the number of private guesses on the number of jelly beans in a jar and dividing them by the number of individual guesses to get their aggregated guess. In other cases, more sophisticated methods of aggregation, like Bayesian search theory, may be required.

The more evident these factors are the more likely that the crowd will unknowingly produce wise and efficient outcomes.

Financial markets and modern science are often excellent examples of this process. When these five factors exist, markets are efficient, and global science produces startling results. However, when they break down, crowds do in fact go “mad”.

Unfortunately, there are also areas where the exception proves the rule. Traffic patterns and politics are two examples. In politics, no answer is ever proven right or wrong, thus political decisions are not well suited to the cognitive wisdom of crowds. Unlike the free marketplace, political self-interest does not produce results toward the collective good.

In the end there are three ways to make decisions. In most cases, the wisest solutions are produced by the proper use of “crowds”. However, the worst two methods are the ones most often used: the power of a single individual or the use of a crowd (teamwork) in the absence of the five factors highlighted by Surowiecki.

Executive Summary

The word “crowd” evokes images of throngs of game day fans, packed commuter lanes and trains, or even unruly rioters. Can large groups of people produce good decisions? James Surowiecki argues that given the proper composition, circumstances, and framework, the group may surpass the decision-making capability of even its smartest member.

The Wisdom of Crowds is a title that pays homage to Charles Mackay’s 1841 book, Extraordinary Popular Delusions and the Madness of Crowds, yet challenges its premise.

Instead, the book addresses the three main tasks a crowd could confront: cognition, coordination, and cooperation.

Too many books for your bookshelf? You may need an  e-reader .

Surowiecki presents his case with a preponderance of anecdotal supporting evidence. The first part of the book elaborates upon the preconditions that facilitate wise crowds, namely diversity, independence, decentralization, coordination, and aggregation.

The second part delves into modern societal constructs involving crowds, exploring how they function, succeed, and fail in light of the wisdom of the crowd, or lack thereof. These examples include traffic, science, markets, companies, the Columbia disaster, and even democracy itself.

Examples of Crowd Wisdom

In 1906, British scientist Francis Galton conducted an experiment at the annual regional fair’s weight-judging competition. Participants were to estimate the dressed weight of an ox, and after the competition ended, Galton obtained the entries. Much to his surprise, the average of the group’s guesses, 1197 pounds, was almost exactly the weight of the dressed ox, which came in at 1198 pounds.

While Galton’s experiment proved that a crowd could solve a relatively simple task, in 1968, naval officer John Craven leveraged a diverse team when hunting for the Scorpion, a submarine that disappeared southwest of the Azores in the North Atlantic. Craven gathered a panel of experts to postulate the resting place of the Scorpion, but instead of staging a series of meetings intent upon reaching consensus, each member provided his best estimate independently.

Using Bayesian search theory to combine these guesses, he produced a final answer that was a mere 220 yards from the true location of the sub, which was submerged under 9800 feet of water. The combined guess was closer than any one of the estimates from the experts.

When a contestant on the popular television program, Who Wants to be a Millionaire?, was unsure of the answer, he or she was given one opportunity to phone a friend, ask the audience, or have two of four possible answers eliminated.

Analysis shows that when the contestant phoned a friend – presumably a smart friend – this “expert” knew the correct answer 65% of the time. However, when polling the audience, a diverse group of average people, its collective wisdom pegged the correct answer 91% of the time.

On the morning of January 28, 1986, the world witnessed the destruction of space shuttle Challenger live on television as it attempted to reach low-earth orbit. Eight minutes after the explosion, the first story hit the Dow Jones News Wire. Almost immediately, the stocks of the four major contractors involved in the Challenger launch began to plummet.

Rockwell International had built the shuttle orbiter and its main engines, Lockheed managed ground support, Martin Marietta manufactured the main fuel tank, and Morton Thiokol had built the solid rocket boosters. Twenty-one minutes later, Lockheed stock was off 5 percent, Martin Marietta was down 3 percent, and Rockwell had given up 6 percent.

However, Morton Thiokol suffered from such a lack of buyers that the exchanges halted trading, and by then end of the day the stock was down 12 percent. The other companies had recovered to around a 3 percent loss on the day. Incredibly, within a few hours, the market had assigned the majority of the blame on Morton Thiokol, a fact that would not surface until six months later when the Presidential Commission on the Challenger announced its findings. The O-ring seals between sections of the solid rocket boosters had become brittle in cold weather and had allowed hot gasses to burn through the main fuel tank.

There are many other examples of wise crowds. Sports betting pools are relatively efficient, especially at picking winners for horse races. Google’s Page Rank algorithm classifies and indexes billions of web pages according to a democratic process then delivers them to the user in a split second.

Decision markets such as the Iowa Electronic Markets and the Hollywood Stock Exchange have shown more accurate results than those produced by polling agencies. All of these examples of wise crowds show ways in which the group solves the cognition problem – picking the optimal solution in a given situation – and how the decisions of the group are often better than the brightest individual’s choices.

Diversity Matters, Don’t Chase the Expert

The first essential quality of wise crowds is a special kind of diversity, one that manifests itself as varying levels of knowledge and insight among the members of the group. Having an assortment of viewpoints expressed during the decision-making process allows the group to consider solutions that a smart member, such as an expert, might not offer.

This is not to say that gathering a throng of thoroughly uninformed participants will yield better results than consulting an expert. Rather, the value of diversity comes when each member of the crowd brings a bit of private knowledge and insight and is able to judge between potential outcomes.

At one point in American history, one-third of all automobiles on the road were electric.

Of course, steam-powered vehicles also had a sizeable market share too. The diversity of the entrepreneurs in the early days of the automobile gave the market an array of choices from which to pick the future of transportation.

Debating Prime Reading vs. Kindle Unlimited? We have the pro’s and con’s for you  here .

A diverse group of market participants – each with certain preferences, knowledge, and goals – was able to recognize the losers and vote them out. No centralized planning authority or panel of hand-picked experts chose the successful form of the automobile, yet the crowd’s solution remains the best after nearly a century.

Commonly, businesses view experts as their secret weapons. The company that assembles the smartest team is expected to surge ahead, but the reality is that experts have a dismal performance record. Take professional money managers: between 1984 and 1999, almost 90 percent of mutual-fund managers underperformed the Wilshire 5000 index, and over 95 percent of managed bond funds underperformed the market from 1999-2004. It seems that accuracy and expertise are uncorrelated. A series of studies found that experts lacked agreement with one another and even with themselves.

One study of medical pathology gauged internal consistency at 0.5.

This means that given the same evidence, a pathologist would come to a different conclusion half the time. Experts also suffer from overconfidence, and they are bad at “calibrating” their judgments. They have a poor sense of the accuracy of their own decisions.

Now, this does not mean that companies should not seek experts. Instead, the opinions of the experts should be pooled with those of others in a larger group, since it is unlikely that the decisions of one single person will be better than the group’s over time.

The Need for Independence

Intelligent decision making requires independence for two main reasons. First, the mistakes of independent individuals will be uncorrelated, meaning that errors in judgment will not sabotage the whole group. Second, independent individuals are more likely to process information through the filter of their own experience and understanding, rather than relying on common knowledge shared by the group.

When the group as a whole begins to think and act the same way, their behavior resembles the actions of animals that stay with the herd to increase their chances of survival.

People involved in “herding” behavior may have suffered from an information cascade, weighting the decisions of others more than their own private information. It is not necessarily the case that people caught up in information cascade are mindlessly following the crowd. Rather, they think they are learning valuable information from the example set by previous decisions. Protecting independence of thought is vital to maintaining the wisdom of the group.


Systems in which decision-making power does not fully reside in one location are decentralized. Individuals, instead of central authorities, make important decisions based on local, specific knowledge. Adam Smith saw the importance of specialization – matching individual skills and tasks – in 1776, and it remains an important feature of decentralization.

Also crucial to successful decentralized systems is what Friedrich Hayek called “tacit knowledge”, knowledge that is specific to a particular experience, job, or place. These two features, specialization and tacit knowledge, lead to the assumption at the heart of decentralization: the people closer to the problem will be more likely to have the knowledge and skills required to solve it.

One primary weakness of decentralization is that important information contained in one part of the network may not necessarily find its way to other parts of the network where it is needed.

Overcoming this weakness requires some centralization, but each organization must find a balance between local and global knowledge. The ultimate goal should be to make individual knowledge useful to the group without taking the decision-making power away from those closest to the problems.


The solution to a coordination problem requires reasoning about not only the individual’s decision but also about the decisions of the group. This challenge of coordination is unique, since each person’s decision influences the others in the crowd. Classic examples of coordination problems include pedestrians on a crowded sidewalk, flocks of birds in flight, and the El Farol problem.

El Farol is a local bar in Santa Fe, New Mexico, that inspired economist Brian Arthur to formulate a coordination problem to maximize the enjoyment of bar-goers. The problem states that if the bar is more than 60% full, none of the participants will have a good time and should have stayed home. Conversely, those at the bar when it is less than 60% full will have a great time.

The challenging part is that all potential bar-goers must decide whether to leave home simultaneously, without conferring with others. Through computer simulation of a diverse set of strategies, Arthur found that the average usage of the bar was exactly 60%. Thus, the collective judgment of the group was able to maximize the enjoyment of all participants.

In another set of experiments, engineers Ann Bell and William Sethares created a population of agents that followed the same rule: the decision to go to the bar depends on the agent’s previous experiences. Acting independently in this manner, the attendance at the bar settled to a little below 60%, a slightly sub-optimal solution. Interestingly, the participants in this simulation settled into two groups: regulars and occasional attendees. The El Farol bar problem shows that people are inherently good at coordinating, producing near-optimal solutions in challenging situations despite the absence of communication.


The best solutions and ideas of a diverse, independent crowd are useless in the absence of a proper aggregation method. Financial markets are excellent aggregators: one single number, namely the market price, captures the viewpoints of all participants. John Craven combined the views of various experts with Bayesian search theory during the hunt for the Scorpion submarine. Without proper aggregation, the decisions of the crowd are no more than noise.

Trust and Cooperation

When it comes to cooperation, the rational agent of economics simply looks after its own interests and free rides off the work of others whenever possible, yet real people cooperate.

Political scientist Robert Axelrod argues that “cooperation is the result of repeated interaction with the same people.”

As we deal with other people, we realize that it is best to deal fairly, since we know that others may punish us for dishonesty. Axelrod calls this the “shadow of the future.” We cooperate with others since we are reasonably sure of continued good relationships. However, we should be willing to punish uncooperative behavior when we encounter it.

If we cooperate based on repeat encounters, why do we cooperate with total strangers? Consider tipping: we tip the staff of local hotels and restaurants in order to ensure good service in the future or to gain better seating, but we also tip the waiters at restaurants in other states.

Perhaps we are afraid of public reprimand for under-tipping, or maybe we tip because of cultural expectation. The same could be said of paying taxes; the rational agent tries to avoid taxes at all costs while taking advantage of the public goods funded by taxpayers.

Capitalism itself is a monument to the value of cooperation and trust.

Under a proper, impartial legal framework, the rules of the game are set forth and applied equally to all. Over time, the participants in free market capitalism, though they may be competitors, learn that cooperation is simply the best way to get things done. This does not imply sharing profits with competitors, but it does mean that most companies and individuals enter into a transaction with the understanding that the other side is also playing by the rules.

In an economy based on trust, however, it becomes easy to take advantage of others. Most of the time, the market punishes firms who exploit another’s trust, inflicting legal action or even consumer rejection, but the late 1990s saw corporate accounting fraud writ large.

Historically cautious firms underwrote the public listings of laughable companies, and accountants simply stamped their approval. From 1997 to 2000, seven hundred companies were required to restate their earnings, compared with just three in 1981. Unfortunately, the market did not punish these firms, and the investments continued to pour in until there was a massive correction that hurt everyone.

Privileged C-suite executives skipped out in their golden parachutes while the average employee was left with no job, worthless stock options, and an empty retirement account. For markets to function properly in the long run, they must punish failing firms and those who break the rules. Trust must remain intact between the strangers who interact daily in capitalist economies, since, as Surowiecki puts it, “Trust marks the distinction between society and a bunch of people living together.”


Highway traffic is the quintessential coordination problem: a large crowd of drivers assembles on the roadways, each person has a different destination, and the effects of each decision are felt by all of the drivers. Each driver follows a simple set of rules: stay in the lane; do not hit the car in front; drive as fast as safely possible.

All the members of traffic want to reach the destination ahead of the others, but everyone wants traffic as a whole to move as fast as possible. So does the crowd come up with an intelligent solution? Not usually. Traffic jams occur often and may persist for hours, moving upstream against the flow.

To combat bad traffic, some cities have passed congestion taxes for cars entering the city center.

London has reduced congestion by 20% and increased speeds by 40% in its central business district after imposing a £5 all-day fee. Mexico City took the heavy-handed approach of allowing cars with even-numbered license plates to drive every other day, with odd-numbered plates alternating days. The goal there was to prevent pollution, but many drivers simply purchased a second car so they could drive every day. The problem with these methods is finding the right incentive structure to reduce congestion.

Though diversity lends itself to smarter crowds, in the case of traffic, it can be a liability, making the coordination problem harder. If only the cars on the road could communicate with one another and agree on an optimal solution. Roadway traffic would exist in what researchers call “coherent flow” where each car travels slower than it would like, but the traffic as a whole moves at the fastest possible speed in one large block.

To bring about this transportation utopia, some suggest that fully-automated robotic cars could ferry people around the roadways, but there may be significant hesitation from the drivers to hand over their lives to computer control. Other researchers urge advances in technology such as on-ramp signals to limit the rate at which traffic enters highways. The solution to the traffic problem eludes the wisdom of the crowd, but perhaps technological intervention could help.


Modern science is a prime example of a solution to the collaboration problem. Researchers are eager to share their insights and breakthroughs with the whole world in exchange for simple recognition, usually in the form of citations and offers of collaboration.

Since few modern scientists reach their conclusions without relying on work from both their predecessors and their contemporaries, successful collaboration makes each individual scientist more productive. Interestingly, more productive scientists collaborate more often.

The result of modern scientific collaboration is that even though each individual scientist works in a self-interested way to gain more recognition, the process produces published research that benefits the scientific community and society as a whole.

An example of the effectiveness of modern scientific collaboration is the discovery of the cause of sudden acute respiratory syndrome (SARS).

In early February 2003, Chinese health officials notified the World Health Organization (WHO) of a few hundred occurrences of a flu-like disease that had killed five in Guangdong Province. A few weeks later, cases of the disease began appearing in other countries, and the WHO issued a global warning.

On March 17, the WHO embarked upon a “collaborative multicenter research project” aimed at isolating the underlying causes of SARS. The involved research centers participated in daily teleconferences in which they shared their findings and progress. In this way, each center could investigate independently yet learn from the insights of all the others.

This process was remarkably effective, and in less than a week’s time, scientists at Hong Kong University had isolated a candidate virus. By April 16, less than a month after they began, the collaborating labs were confident enough to announce that the coronavirus was the cause of SARS.

During the SARS collaboration, no one was in charge, and no one person is credited with the discovery of the cause of SARS. The WHO simply created the framework and facilitated sharing of ideas and findings. Any one lab might have taken years to isolate the SARS coronavirus, but through collaboration and proper aggregation, a diverse and independent crowd came to a solution with great efficiency.

The Columbia Disaster

As the space shuttle Columbia entered the Earth’s atmosphere on February 1, 2003, hypersonic plasma entered its left wing through a hole in the leading edge and destroyed the vehicle, killing the crew of seven astronauts and scattering debris over parts of Texas and Louisiana. The event was tragic, but had the teams involved acted as wise crowds, they could have prevented it.

On January 21, the Debris Assessment Team (DAT) for the mission had requested on-orbit pictures of the shuttle orbiter to view a suspected foam strike that was not clearly visible in the launch videos.

The foam had broken away from the large external fuel tank and appeared to have struck the wing, but the DAT needed more information.

In a teleconference with the Mission Management Team (MMT), the DAT liaison, Don McCormack, failed to relay the seriousness of the situation, mentioning the foam strike two-thirds of the way through the meeting. The MMT leader’s reply was, “I really don’t think there is much we can do so it’s not really a factor during the flight because there is not much we can do about it.”

With the assumption that the foam strike had not caused serious damage, the teams met again on January 24. The DAT members’ opinion was that the shuttle was probably safe, but they emphasized that their analysis was woefully incomplete. In fact, the meeting room where they presented the findings to McCormack was full of other people anxious about the safety of the shuttle.

In a teleconference with the MMT later that day, McCormack focused on the conclusion of the team rather than stressing the concerns about incomplete information. There was no debate or minority opinion. In fact, not one member of the MMT asked a question about the findings of the DAT. When the conference call ended, the fate of Columbia was sealed.

The causes of the poor decisions on the part of NASA managers were specific for the most part to the culture of the agency. Although it was comprised of brilliant individuals, NASA was deeply hierarchical instead of functioning as a meritocracy. Information from lower levels, where the people were closer to the problems, did not reach higher ranks to the decision makers.

This lack of idea aggregation is costly to many organizations, but in this situation, it was deadly. While the NASA of the 1960s was composed of veterans of many other industries and government agencies, it had come to recruit much of its workforce directly out of graduate school. Thus, the agency experienced a large cognitive diversity deficit, and according to the author, “in small groups, diversity of opinion is the single best guarantee that the group will reap the benefits from face-to-face discussion.”

In fact, a single minority opinion could have sparked a proper debate and saved the crew of Columbia.

Instead, the absence of dissent reinforced the assumptions of the group of decision makers. For NASA, failing to maintain a diverse workforce led to an embarrassing and costly mistake.

The Paradox of the Corporation

The ideal corporation seeks many of the qualities of a smart crowd. First, it wishes to coordinate both its products with customer desires and the actions of its employees toward a common goal. Next, it should retain independent decision making within its distributed business units.

In addition, it attempts to aggregate the ideas of all employees, not just experts, when developing strategy. Finally, it compensates its managers in proportion to work performed rather than relative to expectations. The paradox of the corporation is that it reaches its goals through centralized plans, commands, and controls, yet it competes in the free marketplace.

Within corporations, crowd wisdom and conventional wisdom are at odds. Perhaps the biggest flaw in the minds of employees, investors, and the press is the extreme importance placed upon the CEO. Companies bestow massive compensation packages and completely unreasonable expectations on new chiefs, since it is natural to assume that successful people reached that status through some skill or quality, rather than through luck or circumstance.

Companies often place too much decision-making power in the hands of the chief executive, ignoring the wise-crowd principles of decentralization and aggregation.

Throughout the 1990s, corporate profit margins declined while executive compensation soared. Given the historical performance of new product launches, in which 80 percent fail within one year, and corporate mergers where two-thirds fail to increase shareholder value, it is clear to see that CEOs are sometimes not exceptional decision makers.

The wise-crowd approach is at least to consider the opinions of many when confronted with difficult decisions. Some companies deploy internal decision markets to facilitate aggregation, and employees wager money in an attempt to forecast product success and market trends. In fact, an internal decision market at Hewlett-Packard outperformed the company’s sales forecasts 75 percent of the time.

These markets have great value since they give individuals incentive to uncover and act on good information, and they provide a clear answer to forecasting questions. Though decision markets should not make decisions for a company outright, they should be considered. In theory, the board of directors makes important decisions anyway, not the CEO. Focusing on aggregation of a wide range of viewpoints may allow a company and its CEO to make wiser decisions.


Markets are effective aggregators of disparate knowledge and viewpoints, but the participants involved deviate from rationality on a regular basis. Investors are overconfident, holding onto losing positions with the misguided assumption that as long as they do not sell, they have not incurred real losses.

In addition, investors are susceptible to herding instead of making independent decisions. When participants become buyers or sellers predominantly, markets experience bubbles and crashes. The arrival of CNBC in the 1990s continued the assault on independence in the markets. Instead of simply reporting on the markets, it began to move them. Day trader Ken Wolff notes that “CNBC is a hot momentum-trading tool. We play it often.” The influence of CNBC was strong because it inundated investors with information about how other investors were thinking, forming dependence between them.

A great irony of modern markets is that the media and society demonize short sellers, those who sell securities short anticipating declining prices.

Jim Chanos, the head of the short fund Kynikos, says that short sellers “don’t have that steady drum beat of support behind you that you have if you’re buying stocks. You have a steady drum beat on your head.” Throughout history, many have blamed short sellers for crashes: Napoleon called them enemies of the state, Malaysian authorities in 1995 suggested caning as the punishment for short selling, and Congress blamed Depression Era short sellers for prolonging the downturn.

The public at large remains convinced that short sellers have the power to manipulate the market at will. With this much negative attention, it’s not a surprise that investors short only 2 percent of the shares on the New York Stock Exchange in any given year. The market may not function properly without more participants on the short side, since its success hinges not upon whether prices are moving steadily upward but upon whether prices are correct.

The lesson of the markets is that investors must strive to remain independent of the choices of others in order to bring a healthy amount of local knowledge and to avoid the harmful effects of bubbles and crashes.


In the 1960s, a group of economists known as public-choice theorists burst into the world of politics. Given their knowledge that free markets are driven by the self-interest of participants, these economists analyzed political actors – voters, politicians, and regulators – in this new light.

They found that voters choose candidates who will do the most for their well-being rather than doing what is best for the country as a whole. Politicians seek re-election above all else, so they vote in a way that ensures the best chance of another term, often giving into special interest lobbyists and pork-barrel politics.

Regulators wish to keep their jobs while controlling a larger share of resources.

Thus, they exaggerate the importance of their particular area and seek to expand the reach of their oversight. Unlike in the free marketplace, this political self-interest does not produce results toward the collective good.

Many of these new political economists saw a government that kept growing, making friends among the industries it regulated, and allowing special interests to write policy instead of addressing the concerns of the people.

From that point of view, some wondered why anyone even bothers to vote, especially given the effect that a single vote has on a major election. A series of studies in the 1980s showed that there was more correlation between the way people voted and their perception of the economy’s health than there was to their actual financial situation.

Economists argue that since most people are not, and will never be, wealthy, they should prefer to raise taxes on the rich and use the income for their own purposes, yet most are opposed to the idea. From this viewpoint, there remains only ideology, and not self-interest, to explain voting habits.

Coupled with a general frustration with politics and government is a glaring ignorance on the part of the average voter. In the midst of the Cold War, half of all Americans thought the USSR was a member of NATO. When asked whether we spend too much on foreign aid, most poll respondents agreed and suggested that the number should be $1 for every $3 we spend on defense.

In reality, we spend closer to $1 on foreign aid per $19 of defense spending.

Some might argue that the solution is to encourage rule by the technocratic elite making decisions in the public interest. However, it would be difficult to see how any person could look past his or her own ideology to find this mystical “public good.” In fact, one of the most difficult aspects of political decisions is that there is never a point at which one can conclude whether the decision was the right one or not.

In politics, no idea is ever proven right or wrong, thus political decisions are not best suited to the cognitive wisdom of the crowd. However, in the words of Winston Churchill, “It has been said that democracy is the worst form of government except all those other forms that have been tried from time to time.”

Instead of handing over our government to an elite class, we must continue to inject local knowledge and independent thought into the political process. Surowiecki concludes his discussion of democracy, and the book, by saying, “The decisions that democracies make may not demonstrate the wisdom of the crowd. The decision to make them democratically does.”


The wisdom of crowds enables diverse groups to solve the complex problems of cognition, coordination, and collaboration. From space flight to corporate boardrooms to tipping at restaurants, group psychology permeates the culture. Learning to harness this wisdom of the crowd could prove to be a pivotal decision in the life of a business; failing to recognize the emergence of harmful group behavior could be its downfall. Whether electing the government of a nation or trying to find the cause of a deadly disease, crowds of people make impressive, important decisions with global impact. would like to thank the Titans of Investing for allowing us to publish this content. Titans is a student organization founded by Britt Harris. Learn more about the organization and the man behind it by clicking either of these links.

Britt always taught us Titans that Wisdom is Cheap, and that we can find treasure troves of the good stuff in books. We hope this audience will also express their thanks to the Titans if the book review brought wisdom into their lives.

This post has been slightly edited to promote search engine accessibility.

Leave a Comment