eprintid: 50334 rev_number: 8 eprint_status: archive userid: 1482 importid: 105 dir: disk0/00/05/03/34 datestamp: 2025-02-05 15:26:15 lastmod: 2025-02-05 15:30:15 status_changed: 2025-02-05 15:26:15 type: article metadata_visibility: show creators_name: Köbis, Nils creators_name: von Schenk, Alicia creators_name: Klockmann, Victor creators_name: Bonnefon, Jean-François creators_name: Rahwan, Iyad creators_idrefppn: 076374645 creators_idrefppn: 154839345 creators_halaffid: 326884 creators_halaffid: 353294 creators_halaffid: 309384 creators_halaffid: 1002422;441569 creators_halaffid: 353294 title: Lie detection algorithms disrupt the social dynamics of accusation behavior ispublished: pub subjects: subjects_ECO abstract: Humans, aware of the social costs associated with false accusations, are generally hesitant to accuse others of lying. Our study shows how lie detection algorithms disrupt this social dynamic. We develop a supervised machine-learning classifier that surpasses human accuracy and conduct a large-scale incentivized experiment manipulating the availability of this lie-detection algorithm. In the absence of algorithmic support, people are reluctant to accuse others of lying, but when the algorithm becomes available, a minority actively seeks its prediction and consistently relies on it for accusations. Although those who request machine predictions are not inherently more prone to accuse, they more willingly follow predictions that suggest accusation than those who receive such predictions without actively seeking them. date: 2024-06 date_type: published publisher: Elsevier id_number: 10.1016/j.isci.2024.110201 official_url: http://tse-fr.eu/pub/130255 faculty: tse divisions: tse language: en has_fulltext: FALSE doi: 10.1016/j.isci.2024.110201 view_date_year: 2024 full_text_status: none publication: iScience volume: vol.27 number: n°7 place_of_pub: Cambridge refereed: TRUE issn: 2589-0042 oai_identifier: oai:tse-fr.eu:130255 harvester_local_overwrite: number harvester_local_overwrite: volume harvester_local_overwrite: issn harvester_local_overwrite: pending harvester_local_overwrite: creators_idrefppn harvester_local_overwrite: creators_halaffid harvester_local_overwrite: publisher harvester_local_overwrite: place_of_pub oai_lastmod: 2025-02-04T10:21:17Z oai_set: tse site: ut1 citation: Köbis, Nils, von Schenk, Alicia, Klockmann, Victor, Bonnefon, Jean-François and Rahwan, Iyad (2024) Lie detection algorithms disrupt the social dynamics of accusation behavior. iScience, vol.27 (n°7).