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Reviewer: Srijith KrishnanNair

Surowiecki?s now-famous book examines one central question: Is a group "smarter than the smartest people in [it]__?__" If Surowiecki?s claim is to be believed, the crowd is indeed smarter. In this book, Surowiecki goes on to examine the conditions under which the crowd?s wisdom can peak, how its power can be tapped into, and how to avoid the pitfalls. Yet one thing that the book does not address in a thorough manner is the reason why such a counterintuitive result holds true. While most of the points being raised in the book may not be new to someone working in the field of group behavior and dynamics, the impact of the book stems from Surowiecki?s ability not only to transform results of academic studies into a series of anecdotes that can be understood by a lay audience, but to do so without going overboard, trying to twist them to say more than what they do. The book is written in a brisk and entertaining manner, jumping between studies of sociology, economics, and psychology with ease, while shifting through real-world cultural and business happenings. From the beginning, Surowiecki identifies four conditions to be met for a group to get its act right?diversity, independence, decentralization, and aggregation. Take any of these away and the crowd becomes a mob, taking extreme positions, susceptible to influence by a leader in the group, and reinforcing each other?s limited viewpoint. Surowiecki spends several of the book?s sections providing examples of how a group got it all wrong (for example, the Columbia accident investigation board and the Enron debacle), making the book well rounded. One of Surowiecki?s biggest fascinations is with the performance of prediction markets. These are speculative markets that bet on the possibility of occurrences of future events?political elections, box office hits, and so on. Surowiecki draws our attention to the Iowa Electronic Markets, which try to predict the outcome of presidential and congressional elections. Studies have shown that the market repeatedly outperforms all major opinion polls and is able to predict the outcome far in advance. Surowiecki champions the use of similar markets within a company to gauge public opinion, estimate product announcement dates by rival companies, and so on. Although several companies have started using such markets internally, they remain an exception, mainly because of the inherent structural dependence on a leader to make decisions. Although Surowiecki calls for providing more power to a group?s collective decision making capabilities, a more balanced and more readily accepted approach would be to use them as another guide to arrive at decisions rather than as a replacement for a leader. The book?s origins are in financial columns in The New Yorker , where Surowiecki works as a staff writer. This influences its easy-to-read, jargon-free style, but at the same time, at certain points, makes it repetitive. Since the target audience of the articles, and by extension, the book, is the general public, the scientific rigor is missing, though notes and pointers have been provided for anyone interested in following the various studies mentioned in the book. At times, Surowiecki tries to extrapolate the findings to cover moral and political issues like corporate corruption, which distract from his otherwise tight narrative. All in all, this is an engaging, mostly well-written book that should be read by anyone interested in exploring the power and dynamics of a group. Online Computing Reviews Service

Reviewer: Ed Harcourt

Can a crowd, as a whole, guess the weight of a cow better than any individual within that crowd__?__ Yes, and Surowiecki tells us that it is because of the wisdom of crowds (TWOC), a situation where a diverse set of individuals, each with their own private knowledge acting independently, arrives at a solution to a problem. This assumes that there is some way to combine the solutions of the individuals; in this example, taking an average of the guesses suffices. Surowiecki begins his book with this retelling of the cow weight-guessing experiment by Francis Galton in 1906 that highlights the necessary criteria of diversity and independence, either of which, when not present, can cause TWOC to be not so wise. A common example where the crowd is unwise is herding, when dependency creeps in and individuals start piggybacking and following others. The book covers a lot of ground, drawing on examples from politics, economics, psychology, general science, sociology, and computer science. This has become a popular business book, yet there is plenty in the book to keep the computer scientist smiling. Why does Google work so well__?__ Because a large number of diverse and independent Internet users continually "vote" on Web sites when they visit them, or link to them from other Web sites. Surowiecki provides a similar explanation for why Linux and the open source movement provide useful and robust software that is better than that of many corporations. Many of the examples discussed in the book are amenable to computer simulations, such as why birds flock, and why traffic can either flow smoothly or break down into a jam for no apparent reason. Much of the book concentrates on providing examples of why businesses succeed or fail, and why financial bubbles and crashes occur. Surowiecki provides numerous examples of where TWOC succeeds or fails, along with explanations relying on the conditions of independence and diversity. While the examples provide convincing evidence of TWOC, I was still left with a gnawing feeling that this is all a little magical. What are the fundamental underlying scientific or mathematical principles involved__?__ The book does not provide a rigorous explanation of this. Detailed notes at the end of the book provide ample references to the literature. This is a well-written and intense read. For computer scientists, TWOC is reminiscent of cellular automata, where independent agents interact with neighboring agents, often performing something useful, or with some emergent behavior. This book is useful as a rich source of computer science applications, and may even provide a framework in which to think about potential solutions to problems (think diversity and independence). Buried deep within the book are some popular accounts of classic computer science examples, including single-server and multiple-server queueing simulations, graph problems, and social networks.