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People make for poor lie detectors. They have accuracy rates comparable to a coin toss, and come with a set of systematic biases that sway the judgment. This pessimistic view stands in contrast to research showing that people make informed decisions that adapt to the context they operate in. The current article proposes a new theoretical direction for lie detection research. I argue that lie detectors make informed, adaptive judgments in a low-diagnostic world. This Adaptive Lie Detector (ALIED) account is outlined by drawing on supporting evidence from across various psychological literatures. The account is contrasted with longstanding and more recent accounts of the judgment process, which propose that people fall back on default ways of thinking. Limitations of the account are considered, and future research directions are outlined.
|Number of pages||9|
|Journal||Journal of Applied Research in Memory and Cognition|
|Early online date||24 Jun 2015|
|Publication status||Published - 1 Dec 2015|
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Adaptive Lie Detector: How People Try (But Fail) to Tell Lies
Chris Street (Speaker)30 Jan 2017
Activity: Talk or presentation types › Invited talk
Society for Applied Research in Memory and Cognition
Chris Street (Chair)25 Jun 2015
Activity: Participating in or organising an event types › Participating in a conference, workshop, ...