通过评估GPT-3与不同社会群体在有争议的话题上的沟通来评估对话式人工智能和公平
Kaiping Chen1, Anqi Shao2, Jirayu Burapacheep3
1Department of Life Sciences Communication, University of Wisconsin-Madison, Madison, USA. kchen67@wisc.edu.
Scientific reports
|January 18, 2024
概括
这项研究发现,虽然像GPT-3这样的AI为少数群体提供了更糟糕的体验,但这些群体在与AI互动后,对支持气候变化和黑人生命的重要性倡议的态度转变更大.
科学领域:
- 人工智能的人工智能
- 计算社会科学 计算社会科学
- 人与计算机的交互
背景情况:
- 自主回归语言模型 (ALM) 越来越普遍,引发了人们对不同人群之间的公平性担忧.
- 现有的关于人工智能公平性的讨论缺乏评估对话系统的具体指标.
- 在了解ALM如何影响不同人口和意见群体的用户体验和态度转变方面存在差距.
研究的目的:
- 提出一个新的框架来评估人 - 人工智能沟通中的公平性,从审议民主和科学沟通中汲取.
- 使用该框架对算法性能和公平性进行审计,重点关注GPT-3的响应.
- 分析人工智能交互对用户对气候变化和黑人生命重要 (BLM) 运动的态度的影响.
主要方法:
- 开发了一个框架来评估人类-人工智能沟通中的公平性.
- 进行了一项算法审计研究,涉及20,000个对话与3,290名参与者.
- 分析了基于社会人口统计因素 (性别,种族,教育) 的参与者数据以及对气候变化和BLM的看法.
主要成果:
- 意见和教育少数群体报告说,用户体验明显更差.
- 这些少数群体在互动后表现出明显更大的态度变化,有利于BLM和气候变化努力.
- 在回应教育和意见少数群体的参与者时,GPT-3使用了更负面的语言.
结论:
- 人工智能系统可能会创造不公平的用户体验,特别是对于少数群体.
- 尽管有负面经验,但人工智能交互可以成为这些群体态度改变的强大催化剂.
- 调查结果突出了发展多样化,公平和包容性对话AI的关键社会技术影响.
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