Known Unknowns: A Critical Determinant of Confidence and Calibration

• 成果类型: Article
• 署名作者: Walters, Daniel J.; Fernbach, Philip M.; Fox, Craig R.; Sloman, Steven A.
• 署名单位: University of California System; University of California Los Angeles; University of Colorado System; University of Colorado Boulder; Brown University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2016.2580
• 发表日期: 2017
• 页码: 4298-4307
• 关键词: behavioral decision making; overconfidence; calibration; JUDGMENT; Decision Analysis

摘要

We propose that an important determinant of judged confidence is the evaluation of evidence that is unknown or missing, and overconfidence is often driven by the neglect of unknowns. We contrast this account with prior research suggesting that overconfidence is due to biased processing of known evidence in favor of a focal hypothesis. In Study 1, we asked participants to list their thoughts as they answered two-alternative forced-choice trivia questions and judged the probability that their answers were correct. Participants who thought more about unknowns were less overconfident. In Studies 2 and 3, we asked participants to list unknowns before assessing their confidence. Considering the unknowns reduced overconfidence substantially and was more effective than the classic consider the alternative debiasing technique. Moreover, considering the unknowns selectively reduced confidence in domains where participants were overconfident but did not affect confidence in domains where participants were well-calibrated or underconfident.