Salvi, F., Ribeiro, M. H., Gallotti, R., & West, R. (2025).
Nature Human Behaviour.
Abstract
Early work has found that large language models (LLMs) can generate persuasive content. However, evidence on whether they can also personalize arguments to individual attributes remains limited, despite being crucial for assessing misuse. This preregistered study examines AI-driven persuasion in a controlled setting, where participants engaged in short multiround debates. Participants were randomly assigned to 1 of 12 conditions in a 2 × 2 × 3 design: (1) human or GPT-4 debate opponent; (2) opponent with or without access to sociodemographic participant data; (3) debate topic of low, medium or high opinion strength. In debate pairs where AI and humans were not equally persuasive, GPT-4 with personalization was more persuasive 64.4% of the time (81.2% relative increase in odds of higher post-debate agreement; 95% confidence interval [+26.0%, +160.7%], P < 0.01; N = 900). Our findings highlight the power of LLM-based persuasion and have implications for the governance and design of online platforms.
Here are some thoughts:
This study is highly relevant to psychologists because it raises pressing ethical concerns and offers important implications for clinical and applied settings. Ethically, the research demonstrates that GPT-4 can use even minimal demographic data—such as age, gender, or political affiliation—to personalize persuasive arguments more effectively than human counterparts. This ability to microtarget individuals poses serious risks of manipulation, particularly when users may not be aware of how their personal information is being used.
For psychologists concerned with informed consent, autonomy, and the responsible use of technology, these findings underscore the need for robust ethical guidelines governing AI-driven communication.
Importantly, the study has significant relevance for clinical, counseling, and health psychologists. As AI becomes more integrated into mental health apps, health messaging, and therapeutic tools, understanding how machines influence human attitudes and behavior becomes essential. This research suggests that AI could potentially support therapeutic goals—but also has the capacity to undermine trust, reinforce bias, or sway vulnerable individuals in unintended ways.
