When is a crowd wise?
Clintin Davis-Stober, David Budescu, Jason Dana, Stephen Broomell

TL;DR
This paper defines and analyzes the conditions under which crowds are collectively wise, showing that diversity and certain biases do not necessarily diminish crowd accuracy, which is robust under various conditions.
Contribution
It provides a general, formal framework for understanding when and why crowds are wise, challenging traditional assumptions about independence and bias.
Findings
Crowd wisdom is robust even with biased and correlated judgments.
Diversity among judgments enhances crowd accuracy.
Selecting only highly skilled judges offers little advantage over simple averaging.
Abstract
Numerous studies and anecdotes demonstrate the "wisdom of the crowd," the surprising accuracy of a group's aggregated judgments. Less is known, however, about the generality of crowd wisdom. For example, are crowds wise even if their members have systematic judgmental biases, or can influence each other before members render their judgments? If so, are there situations in which we can expect a crowd to be less accurate than skilled individuals? We provide a precise but general definition of crowd wisdom: A crowd is wise if a linear aggregate, for example a mean, of its members' judgments is closer to the target value than a randomly, but not necessarily uniformly, sampled member of the crowd. Building on this definition, we develop a theoretical framework for examining, a priori, when and to what degree a crowd will be wise. We systematically investigate the boundary conditions for…
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