
An indirect debiasing method: Priming a target attribute reduces judgmental biases in likelihood estimations
Author(s) -
Kelly Kiyeon Lee
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0212609
Subject(s) - debiasing , heuristics , commit , priming (agriculture) , cognitive bias , cognitive psychology , neglect , cognition , computer science , psychology , heuristic , process (computing) , social psychology , artificial intelligence , biology , botany , germination , database , neuroscience , psychiatry , operating system
Understanding the underlying psychological process that leads to a bias is crucial for developing remedies to correct or reduce the bias. As one of the psychological processes that underlie judgmental biases, attribute substitution provides an explanation as to why people rely on heuristics and commit judgmental biases. Attribute substitution occurs when people make a judgment that requires the use of a target attribute, but make the judgment using a heuristic attribute that comes more readily to mind. This substitution inevitably introduces systematic errors because these two attributes are different. The current work explores an indirect debiasing method—the priming of a target attribute. Across three experiments, we demonstrate that priming a target attribute in prior tasks reduces judgmental biases in likelihood estimations: ratio-bias and base-rate neglect. However, this outcome only occurs when participants have enough cognitive resources. When they experience cognitive load, the priming of the target attribute does not reduce their judgmental biases.