人工智能可以帮助人类在民主审议中找到共同点
Michael Henry Tessler1, Michiel A Bakker1, Daniel Jarrett1
1Google DeepMind, London, UK.
概括
一个人工智能 (AI) 调解员受过培训,以促进小组讨论,产生了与会者认为比人类撰写的更具信息性和公正的陈述. 这种人工智能方法有助于团队找到共同点,并更有效地聚焦共同的观点.
科学领域:
- 计算社会科学
- 人工智能应用
- 人与计算机的交互
背景情况:
- 集体审议对于民主社会至关重要,但在可扩展性,效率和公平参与方面面临挑战.
- 传统的调解方法可能很慢,
- 开发人工智能工具以加强群体沟通和共识构建是一个新兴的研究领域.
研究的目的:
- 训练人工智能系统作为人类群体讨论中的调解者.
- 评估人工智能调解的审议在产生共同基础声明中的有效性.
- 与人工智能产生的陈述相比,评估参与者的偏好和感知质量.
主要方法:
- 训练人工智能以代方式生成和完善表达基于参与者的意见和批评的共同点的陈述.
- 收集了5734名参与者参与人工智能调解的社会或政治问题的数据.
- 分析了参与者对人工智能生成的陈述的评分,以确定其信息性,清晰性和偏见性.
- 使用文本嵌入来分析成功的群组语句的语言特性.
主要成果:
- 参与者 (N = 5734) 显著更喜欢人工智能生成的陈述,与人为介导的陈述相比,他们认为它们更具信息性,清晰和公正.
- 通过人工智能调解的讨论使得讨论参与者更新了他们的观点,并汇聚了共同的观点.
- 嵌入文本表明有效的群体声明在承认多数观点的同时整合了不同意见.
- 结果在一个虚拟的公民集会中成功复制,
结论:
- 人工智能可以有效调解人类的讨论,增强在复杂问题上寻找共同点的过程.
- 人工智能产生的陈述被参与者认为质量优越 (信息丰富,清晰,公正).
- 人工智能调解显示出改善大规模公共话语和达成共识的潜力,正如代表性公民大会所示.
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