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Reducing political polarization through conversations with artificial intelligence
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DOI：10.1093/jcmc/zmag003.png)
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Abstract
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Political polarization is threatening the welfare of individuals and societies. Connecting insights gained from interpersonal communication to human–machine communication, we hypothesized that positive interactions with artificial intelligence (AI) could reduce polarization between humans. To evaluate this proposition, two experiments were conducted, in which human participants (N = 1,035) communicated with AI chatbots in real time. The bots engaged in different communication styles while opposing the participants’ most polarized political views. Across both experiments, engaging with a counterarguing AI chatbot led to significant issue depolarization. AI chatbots exhibiting high (vs. low) conversational receptiveness and active listening during the AI conversation resulted in stronger affective depolarization toward humans, higher participant intellectual humility, and a greater willingness to engage in future conversations with holders of opposing opinions—AI and humans alike. Our experiments show that large language models are powerful tools for individual depolarization and the promotion of beneficial cognitive processing skills.
Keywords:
political polarization
artificial intelligence
conversational receptiveness
intellectual humility
depolarization
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