Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale

被引:28
|
作者
Argyle, Lisa P. [1 ]
Bail, Christopher A. [2 ]
Busby, Ethan C. [1 ]
Gubler, Joshua R. [1 ]
Howe, Thomas [3 ]
Rytting, Christopher [3 ]
Sorensen, Taylor [4 ]
Wingate, David [3 ]
机构
[1] Brigham Young Univ, Dept Polit Sci, Provo, UT 84602 USA
[2] Duke Univ, Dept Sociol Polit Sci & Publ Policy, Durham, NC 27708 USA
[3] Brigham Young Univ, Dept Comp Sci, Provo, UT 84602 USA
[4] Univ Washington, Dept Comp Sci, Seattle, WA 98195 USA
关键词
democratic deliberation; computational social science; generative AI; political science; SOCIAL MEDIA; PARTISAN; CONFLICT; HEALTH;
D O I
10.1073/pnas.2311627120
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Political discourse is the soul of democracy, but misunderstanding and conflict can fester in divisive conversations. The widespread shift to online discourse exacerbates many of these problems and corrodes the capacity of diverse societies to cooperate in solving social problems. Scholars and civil society groups promote interventions that make conversations less divisive or more productive, but scaling these efforts to online discourse is challenging. We conduct a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with AI tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood. These interventions improve reported conversation quality, promote democratic reciprocity, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes.
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页数:8
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