在LLM人群中出现的社会惯例和集体偏见
Ariel Flint Ashery1, Luca Maria Aiello2,3, Andrea Baronchelli1,4
1Department of Mathematics, City St George's, University of London, Northampton Square, London EC1V 0HB, UK.
Science advances
|May 14, 2025
概括
人工智能代理人自发地发展了社会惯例,展示了新兴的集体偏见. 少数群体甚至可以通过引入新的公约来推动社会变革.
科学领域:
- 人工智能的人工智能
- 社会心理学 社会心理学
- 计算社会科学 计算社会科学
背景情况:
- 社会惯例对于人类群体的协调和社会结构至关重要.
- 人工智能 (AI) 代理商在通信中的越来越多的使用需要了解它们在社会协调方面的潜力.
- 一个关键的问题是,人工智能代理人是否可以自主建立基本的社会规范.
研究的目的:
- 研究大型语言模型 (LLM) 代理人在分散的群体中自发出现的社会惯例.
- 分析会议形成期间集体偏见的发展.
- 检查对抗性少数群体对社会约定动态的影响.
主要方法:
- 实验设置与通过自然语言交流的LLM代理的去中心化群体.
- 观察各种病原体种群中公约的出现和采用情况.
- 分析个人代理人与集体行为的偏见形成.
- 模拟对抗性代理集团影响既定公约.
主要成果:
- 普遍采用的社会惯例在LLM代理人群中自发地出现.
- 强烈的集体偏见出现,即使个体代理人是公正的.
- 积极的少数群体的对抗性行为者成功地强加了替代性的社会公约.
结论:
- 人工智能系统,特别是LLM,可以在没有明确编程的情况下自主开发社会惯例.
- 人工智能的新兴惯例和偏见对人工智能与人类价值观的协调有影响.
- 了解AI的社会动态对于未来的AI系统设计和社会整合至关重要.
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