Discussing politics with a chatbot: How political beliefs shape prompt formulation for generative AI
Victoria Vziatysheva, Reinhold Kliegl
Abstract
By generating comprehensive and highly personalized answers to user prompts, AI chatbots such as ChatGPT and Gemini can serve as alternatives to search engines and substantially transform online information seeking. However, little research has examined how users interact with these tools to find information, particularly about politics. In this experiment, we examine how Swiss citizens (N = 563) formulate prompts to search for migration-related issues using AI chatbots and whether this process is affected by selective exposure. We find evidence of attitude-consistent prompting, whereby participants who were more critical of migration were more likely to formulate prompts with an anti-migration stance. This effect was stronger for a broad topic (migration in general) than for a specific one (anti-migration popular initiative put to a vote in Switzerland). However, exposure to an attitude-consistent AI response did not further amplify selectivity in prompting. We also did not find evidence that either AI attitudes or thinking styles moderated selectivity in prompting. These findings contribute to the understanding of selective exposure via AI chatbots and the use of generative AI for political information-seeking.