使用人工智能测试政治说服理论
Lisa P Argyle1, Ethan C Busby1, Joshua R Gubler1
1Department of Political Science, Brigham Young University, Provo, UT 84602.
概括
生成型人工智能 (AI) 可以帮助政治说服研究. 人工智能生成的信息改变了人们的态度,但定制和交互对通用内容提供了最小的优势.
科学领域:
- 政治科学 政治科学是指政治学.
- 心理学 心理学 心理学
- 人工智能的人工智能
背景情况:
- 政治说服研究面临的数据局限性阻碍了对社会和心理过程的理解.
- 生成型大语言模型 (LLG) 提供了新的解决方案,以克服说服研究中的数据约束.
研究的目的:
- 调查生成AI在政治说服研究中的有效性.
- 评估人工智能产生的说服力策略,包括信息定制和阐述,对态度变化和投票支持.
主要方法:
- 进行了两个预先注册的在线调查实验.
- 测试了四种类型的AI生成的反态度的说服性信息.
- 检查了消息定制 (基于个人特征) 和阐述 (通过交互).
主要成果:
- 与对照组相比,所有人工智能生成的说服力策略都显著改变了态度和投票支持.
- 消息定制和人工智能交互没有比通用消息产生更大的说服力.
- 有说服力的信息调节了态度,但对民主互惠和情感两极分化的影响有限.
结论:
- 生成性人工智能是研究政治说服力的可行工具,为心理和沟通过程提供了洞察力.
- 人工智能驱动的说服力的有效性并没有通过信息定制或交互式阐述显著提高.
- 态度适度并不自动转化为增加民主宽容或减少情感两极分化.
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