LLM-Based Bot Broadens the Range of Arguments in Online Discussions, Even When Transparently Disclosed as AI
This addresses the issue of political polarization and narrow discourse in online platforms for democratic engagement, representing a novel application but with incremental technical innovation.
The study tackled the problem of limited perspectives in online political discussions by using an LLM-based bot to introduce missing arguments, resulting in a significant expansion of the range of arguments as measured by objective and subjective metrics, with disclosure of the bot as AI not altering these effects.
A wide range of participation is essential for democracy, as it helps prevent the dominance of extreme views, erosion of legitimacy, and political polarization. However, engagement in online political discussions often features a limited spectrum of views due to high levels of self-selection and the tendency of online platforms to facilitate exchanges primarily among like-minded individuals. This study examines whether an LLM-based bot can widen the scope of perspectives expressed by participants in online discussions through two pre-registered randomized experiments conducted in a chatroom. We evaluate the impact of a bot that actively monitors discussions, identifies missing arguments, and introduces them into the conversation. The results indicate that our bot significantly expands the range of arguments, as measured by both objective and subjective metrics. Furthermore, disclosure of the bot as AI does not significantly alter these effects. These findings suggest that LLM-based moderation tools can positively influence online political discourse.