The potential of generative AI for personalized persuasion at scale

Matching the language or content of a message to the psychological profile of its recipient (known as “personalized persuasion”) is widely considered to be one of the most effective messaging strategies. We demonstrate that the rapid advances in large language models (LLMs), like ChatGPT, could acce...

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Bibliographic Details
Published in:Scientific reports 2024-02, Vol.14 (1), p.4692-16, Article 4692
Main Authors: Matz, S. C., Teeny, J. D., Vaid, S. S., Peters, H., Harari, G. M., Cerf, M.
Format: Article
Language:English
Subjects:
631/477
631/477/2811
Chatbots
Climate
Climate action
Consumer products
Generative artificial intelligence
Humanities and Social Sciences
Language
Marketing
Morals
multidisciplinary
Persuasive Communication
Science
Science (multidisciplinary)
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Summary:Matching the language or content of a message to the psychological profile of its recipient (known as “personalized persuasion”) is widely considered to be one of the most effective messaging strategies. We demonstrate that the rapid advances in large language models (LLMs), like ChatGPT, could accelerate this influence by making personalized persuasion scalable. Across four studies (consisting of seven sub-studies; total N  = 1788), we show that personalized messages crafted by ChatGPT exhibit significantly more influence than non-personalized messages. This was true across different domains of persuasion (e.g., marketing of consumer products, political appeals for climate action), psychological profiles (e.g., personality traits, political ideology, moral foundations), and when only providing the LLM with a single, short prompt naming or describing the targeted psychological dimension. Thus, our findings are among the first to demonstrate the potential for LLMs to automate, and thereby scale, the use of personalized persuasion in ways that enhance its effectiveness and efficiency. We discuss the implications for researchers, practitioners, and the general public.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-53755-0