将聊天机器人与招聘中的心理测试进行比较:减少了社会可取性偏见,但预测有效性较低
Danilo Dukanovic1, Dario Krpan1
1Department of Psychological and Behavioural Science, The London School of Economics and Political Science, London, United Kingdom.
Frontiers in psychology
|May 12, 2025
概括
人工智能聊天机器人在评估性格特征 (如外向和良心) 中表现有前途,比传统测试更少偏见. 然而,它们对现实世界工作结果的预测有效性需要进一步的研究.
科学领域:
- 心理测量 心理测量 心理测量
- 人工智能的人工智能
- 人力资源 人力资源 人力资源
背景情况:
- 人工智能工具在招聘中越来越多地使用,需要验证它们的有效性.
- 了解AI在人格评估中的可靠性和有效性对于专业的招聘至关重要.
研究的目的:
- 与传统的心理测试相比,评估人工智能聊天机器人在推断人格特征方面的有效性.
- 评估基于人工智能的人格评估的有效性 (结构性,实质性,收性,外部性,预测性).
- 调查AI推断得分对社会可取性偏见的易感性.
主要方法:
- 准实验性设计与倾向性得分匹配.
- 用传统的心理测试和人工智能聊天机器人评估 (五大个性模型) 来分析159名候选人的数据.
- 对于精细的人工智能评估而言,一种新的"每面一个问题"方法.
主要成果:
- 人工智能聊天机器人在外向和良心方面表现出良好的有效性,但在神经主义,乐观或开放方面没有.
- 人工智能推断的得分比传统测试显示的社会可取性偏差要小.
- 人工智能评估没有显著预测现实世界的结果,这表明外部/预测有效性有限.
结论:
- 由人工智能驱动的聊天机器人显示出对人格评估和减少偏见的潜力.
- 人工智能预测现实世界工作表现的能力存在局限性.
- 需要进一步开发,以完善人工智能评估属性,用于专业选择.
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