Detecting and Punishing Unconscious Bias

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Management Papers
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Management Sciences and Quantitative Methods
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Tetlock, Philip E
Mitchell, Gregory
Anastasopoulos, Jason
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We present experimental results demonstrating how ideology shapes evaluations of technology aimed at detecting unconscious biases: (1) liberals supported use of the technology to detect unconscious racism but not unconscious anti-Americanism, whereas conservatives showed the reverse pattern, (2) liberals and conservatives opposed punishing individuals for unconscious bias but supported punishing organizations failing to use the technology to root out, respectively, racism or anti-Americanism, (3) concerns about researcher bias and false accusations mediated the effects of ideology on support for the technology, and (4) participants taking strong initial stands were likelier than moderates to reconsider their positions. Our findings demonstrate that there is substantial concern about penalizing unconscious bias at the individual level and that it will be difficult to generate broad support for regulation of unconscious bias at even the organizational level unless the technology is a reliable detector of unconscious biases that lead to frequent or serious antisocial behaviors.

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2013-01-01
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The Journal of Legal Studies
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