Summary
The overconfidence effect is a well-established bias in which a person's subjective confidence in their judgments is reliably greater than the objective accuracy of those judgments, especially when confidence is relatively high. Overconfidence is one example of a miscalibration of subjective probabilities. Throughout the research literature, overconfidence has been defined in three distinct ways: (1) overestimation of one's actual performance; (2) overplacement of one's performance relative to others; and (3) overprecision in expressing unwarranted certainty in the accuracy of one's beliefs. The most common way in which overconfidence has been studied is by asking people how confident they are of specific beliefs they hold or answers they provide. The data show that confidence systematically exceeds accuracy, implying people are more sure that they are correct than they deserve to be. If human confidence had perfect calibration, judgments with 100% confidence would be correct 100% of the time, 90% confidence correct 90% of the time, and so on for the other levels of confidence. By contrast, the key finding is that confidence exceeds accuracy so long as the subject is answering hard questions about an unfamiliar topic. For example, in a spelling task, subjects were correct about 80% of the time, whereas they claimed to be 100% certain. Put another way, the error rate was 20% when subjects expected it to be 0%. In a series where subjects made true-or-false responses to general knowledge statements, they were overconfident at all levels. When they were 100% certain of their answer to a question, they were wrong 20% of the time. One manifestation of the overconfidence effect is the tendency to overestimate one's standing on a dimension of judgment or performance. This subsection of overconfidence focuses on the certainty one feels in their own ability, performance, level of control, or chance of success. This phenomenon is most likely to occur on hard tasks, hard items, when failure is likely or when the individual making the estimate is not especially skilled.
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