人工智能产生的内容的信誉和责任:个性化的影响在四个国家
Brian D Earp1,2, Sebastian Porsdam Mann2,3,4, Peng Liu5
1Uehiro Oxford Institute, University of Oxford, Oxford, UK.
Annals of the New York Academy of Sciences
|November 25, 2024
概括
人们对个性化的生成人工智能 (AI) 工具的用户给予更多的信誉,以获得良好的结果. 在大多数国家,对有害AI输出的责怪并没有受到AI类型的显著影响.
科学领域:
- 人工智能的伦理学 人工智能的伦理学
- 人与计算机的交互
- 社会心理学 社会心理学
背景情况:
- 生成型人工智能 (AI) 对人工智能产生的内容的问责制提出了新的伦理困境.
- 当人类使用人工智能工具,特别是个性化模型时,就有关于赋予信誉和责怪的问题出现了.
研究的目的:
- 调查非专业人士对使用标准,个性化或无人工智能辅助产生的有益或有害输出的信誉和责怪.
- 探索这些归因的跨文化差异.
主要方法:
- 在美国,英国,中国和新加坡进行了一项预先注册的代表性采样实验 (N=1802).
- 参与者评估了涉及人类用户使用标准大语言模型 (LLM),个性化的LLM或没有AI (控制) 产生输出的场景.
主要成果:
- 与会者普遍认为,与标准的LLM相比,个性化的LLM的用户对有益的输出有更多的信誉.
- 这种LLM类型并没有显著影响对有害输出的归咎,中国的部分例外.
- 英国参与者对使用任何LLM比没有AI更为责怪.
结论:
- 人工智能工具的个性化影响了对积极结果的认可.
- 对负面人工智能产生的内容的归咎对人工智能类型不那么敏感,但显示了一些跨文化差异.
- 这些发现对道德准则,法律责任和有关人工智能使用的政策制定有影响.
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