大型语言模型可以在社会情境判断方面表现优于人类
Justin M Mittelstädt1, Julia Maier2, Panja Goerke2
1Department of Aviation and Space Psychology, German Aerospace Center, Institute of Aerospace Medicine, 22335, Hamburg, Germany. justin.mittelstaedt@dlr.de.
Scientific reports
|November 10, 2024
概括
大型语言模型 (LLM) 显示出熟练的社会判断,在情境判断测试中表现优于人类. 这表明他们有潜力发挥社会作用,尽管存在相关风险.
科学领域:
- 人工智能的人工智能
- 人与计算机的交互
- 社会心理学 社会心理学
背景情况:
- 由于大型语言模型 (LLM) 的推动,公众对人工智能 (AI) 的兴趣正在激增.
- 士在基于知识的任务中表现出色,但他们的社会智力仍然不确定.
- 评估社会情况和适当的行为是人工智能发展的一个关键挑战.
研究的目的:
- 评估领先的大型语言模型 (LLM) 的社会判断能力.
- 将AI在社会场景中的表现与人类参与者进行比较.
- 为了确定LLMs作为虚拟社会助理的适用性.
主要方法:
- 对五种不同的聊天机器人进行了既定的情境判断测试 (SJT).
- 聊天机器人响应与276名人类参与者的响应进行了比较.
- 人工智能建议行为的有效性评级与专家评估进行了基准对比.
主要成果:
- 与人类参与者相比,Claude,Copilot和you.com的助理表现出了卓越的表现.
- 在社交场合,人工智能生成的行为建议显著更有效.
- 对不同行为的人工智能有效性评级与专家评估非常相匹配.
结论:
- 大型语言模型对熟练的社会判断表现出了显著的能力.
- 这些发现支持LLM作为虚拟社会助理的潜在实用性.
- 法律法规的广泛社会应用需要仔细考虑相关的挑战和风险.
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