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Personalized Persuasion Through Conversational AI: Can DeepSeek Change Perceptions of Genetically Modified Foods in China?

Year: 2026

Type: article

Abstract: Conversational AI has become an influential intermediary in public communication. Emerging research on conversational AI highlights its potential to correct misconceptions and influence attitudes across domains. This study investigates the persuasive effects of personalized conversational AI, focusing on genetically modified foods in China. Employing a between-subjects factorial design, 813 participants engaged in dialogues with a DeepSeek-based chatbot. Participants were randomly assigned to one of four conditions, ranging from a non-personalized generic control to increasingly tailored approaches based on demographic information, risk perceptions, or a combination of both. Results indicate that while AI interactions significantly improve attitudes and willingness to consume genetically modified foods across all conditions, the additional persuasive effect of personalization was conditional. Only a personalization strategy combining demographics and risk perception yielded greater persuasive effects than the control, primarily among participants with positive risk perceptions. Furthermore, moderation analyses revealed a divergence in individual differences: Among participants with negative risk perceptions, while greater prior experience with AI and higher trust in science decreased the persuasive effects, higher AI knowledge facilitated greater attitude gains.

Source: Media and Communication

DOI: 10.17645/mac.11451

Authors: Qi Xi, Jing Zeng, Zhanghao Li, Mike S. Schäfer

Institutions: Beijing Normal University, University of Zurich, Guangzhou University

Language: English

Topic: Genetically Modified Organisms Research

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,132