人工智能可以在预测个性项目之间的相关性方面胜过人类
Philipp Schoenegger1, Spencer Greenberg2, Alexander Grishin2
1London School of Economics and Political Science, London, UK. P.Schoenegger@lse.ac.uk.
Communications psychology
|February 12, 2025
概括
人工智能模型擅长预测人格相关性,表现优于个人. 像PersonalityMap这样的专门AI与专家组的表现相匹配,突出显示AI.
科学领域:
- 人工智能的人工智能
- 心理学 心理学 心理学
- 计算社会科学 计算社会科学
背景情况:
- 评估人类个性对于各种领域至关重要.
- 传统方法依赖于自我报告问卷和专家解释.
- 人工智能的出现,包括大型语言模型 (LLM),为人格分析提供了新的途径.
研究的目的:
- 评估专门的AI (PersonalityMap) 和一般的LLM (GPT-4o,Claude 3 Opus) 在预测人格调查问卷项之间的相关性方面的表现.
- 为了比较人工智能性能与非专业人士和学术专家.
- 通过比较群体中位数预测来研究"群众智慧"效应.
主要方法:
- 人工智能模型预测了人格调查问卷项之间的相关性.
- 绩效与普通人和学术专家的中位数预测进行了比较.
- 该研究分析了个人AI预测和汇总的"群众智慧"估计.
主要成果:
- 所有的人工智能模型在个人预测中显著超过了大多数普通人和学术专家.
- 综合的"群众智慧"估计提高了预测准确度.
- 专业的人工智能 (PersonalityMap) 和学术专家介质超过了一般的LLM和平民介质.
结论:
- 高级LLM在人格研究中表现出优越的预测能力,超过大多数个体.
- 专门的AI模型可以在特定领域的任务中实现专家组级别的性能.
- 人工智能的进步和人类的专业知识对未来的人格研究至关重要.
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