Poor lie detection related to an under-reliance on statistical cues and overreliance on own behaviour

Author:

Zheng Sarah YingORCID,Rozenkrantz Liron,Sharot Tali

Abstract

AbstractThe surge of online scams is taking a considerable financial and emotional toll. This is partially because humans are poor at detecting lies. In a series of three online experiments (Nexp1 = 102, Nexp2 = 108, Nexp3 = 100) where participants are given the opportunity to lie as well as to assess the potential lies of others, we show that poor lie detection is related to the suboptimal computations people engage in when assessing lies. Participants used their own lying behaviour to predict whether other people lied, despite this cue being uninformative, while under-using more predictive statistical cues. This was observed by comparing the weights participants assigned to different cues, to those of a model trained on the ground truth. Moreover, across individuals, reliance on statistical cues was associated with better discernment, while reliance on one’s own behaviour was not. These findings suggest scam detection may be improved by using tools that augment relevant statistical cues.

Funder

Wellcome Trust

Publisher

Springer Science and Business Media LLC

Reference66 articles.

1. Brook, C. Fraud cost Americans $5.8 billion in 2021. Retrieved 21 September 2022, from https://digitalguardian.com/blog/fraud-costamericans-58-billion-2021 (2022).

2. Bond, C. F., Levine, T. & Hartwig, M. New findings in physical lie detection. https://doi.org/10.1002/9781118510001.ch2 (2014).

3. Bond, C. F. & DePaulo, B. M. Accuracy of deception judgments. Personal. Soc. Psychol. Rev. 10, 214–234 (2006).

4. Feeley, T. H. & Young, M. J. Humans as lie detectors: Some more second thoughts. Commun. Q. 46, 109–126 (1998).

5. Jones, R. More than £2.3bn lost in a year as scams surge during pandemic. The Guardian. https://www.theguardian.com/money/2021/jul/15/more-than-23bn-lost-in-a-year-as-scams-surge-during-pandemi (2021).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3