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The use-the-best heuristic facilitates deception detection

Author

Listed:
  • Bruno Verschuere

    (University of Amsterdam)

  • Chu-Chien Lin

    (University of Amsterdam)

  • Sara Huismann

    (University of Amsterdam)

  • Bennett Kleinberg

    (Tilburg University
    University College London)

  • Marleen Willemse

    (University of Amsterdam)

  • Emily Chong Jia Mei

    (University of Amsterdam)

  • Thierry Goor

    (University of Amsterdam)

  • Leonie H. S. Löwy

    (University of Amsterdam)

  • Obed Kwame Appiah

    (University of Amsterdam)

  • Ewout Meijer

    (Maastricht University)

Abstract

Decades of research have shown that people are poor at detecting deception. Understandably, people struggle with integrating the many putative cues to deception into an accurate veracity judgement. Heuristics simplify difficult decisions by ignoring most of the information and relying instead only on the most diagnostic cues. Here we conducted nine studies in which people evaluated honest and deceptive handwritten statements, video transcripts, videotaped interviews or live interviews. Participants performed at the chance level when they made intuitive judgements, free to use any possible cue. But when instructed to rely only on the best available cue (detailedness), they were consistently able to discriminate lies from truths. Our findings challenge the notion that people lack the potential to detect deception. The simplicity and accuracy of the use-the-best heuristic provides a promising new avenue for deception research.

Suggested Citation

  • Bruno Verschuere & Chu-Chien Lin & Sara Huismann & Bennett Kleinberg & Marleen Willemse & Emily Chong Jia Mei & Thierry Goor & Leonie H. S. Löwy & Obed Kwame Appiah & Ewout Meijer, 2023. "The use-the-best heuristic facilitates deception detection," Nature Human Behaviour, Nature, vol. 7(5), pages 718-728, May.
  • Handle: RePEc:nat:nathum:v:7:y:2023:i:5:d:10.1038_s41562-023-01556-2
    DOI: 10.1038/s41562-023-01556-2
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    Cited by:

    1. von Schenk, Alicia & Klockmann, Victor & Bonnefon, Jean-François & Rahwan, Iyad & Köbis, Nils, 2023. "Lie-detection algorithms attract few users but vastly increase accusation rates," IAST Working Papers 23-155, Institute for Advanced Study in Toulouse (IAST).

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