Citation

Argyle LP, Bail CA, Busby EC, Gubler JR, Howe T, Rytting C, Sorensen T, Wingate D. Proc. Natl. Acad. Sci. U. S. A. 2023; 120(41): e2311627120.

Copyright

(Copyright © 2023, National Academy of Sciences)

DOI

10.1073/pnas.2311627120

PMID

unavailable

Abstract

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.

Language: en