谎言检测算法破坏了指责行为的社会动态
Alicia von Schenk1,2, Victor Klockmann1,2, Jean-François Bonnefon3,4
1Julius-Maximilians-Universität Würzburg, Department of Economics, Sanderring 2, 97070 Würzburg, Germany.
iScience
|August 7, 2024
概括
谎言检测算法改变了社会动态,使人们更愿意指责他人不诚实. 即使具有卓越的机器精度,当算法可用时,人类对指责的犹也会减少.
科学领域:
- 行为经济学是一种行为经济学.
- 人工智能的人工智能
- 社会心理学 社会心理学
背景情况:
- 人类表现出社会犹在指责由于社会成本.
- 算法谎言检测对人类社会动态的影响尚不清楚.
研究的目的:
- 调查谎言检测算法的可用性如何影响人类的指责行为.
- 将基于机器学习的谎言检测分类器的准确度与人类准确度进行比较.
主要方法:
- 开发用于谎言检测的监督机器学习分类器.
- 进行大规模的激励实验,观察有或没有算法支持的指控行为.
主要成果:
- 开发的谎言检测算法超过了人类的准确性.
- 算法可用性显著减少了人类不愿意指责的情况.
- 少数人积极使用该算法,依靠其预测进行指控.
结论:
- 谎言检测算法可以破坏有关指控的既定社会规范.
- 与被动可用性相比,对算法预测的积极搜索导致对指控的依赖性更大.
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