research-article

Working With AI to Persuade: Examining a Large Language Model's Ability to Generate Pro-Vaccination Messages

Authors:

Elise Karinshak,

Joon Sung Park,

Jeffrey T. HancockAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 7, Issue CSCW1

Article No.: 116, Pages 1 - 29

https://doi.org/10.1145/3579592

Published: 16 April 2023 Publication History

Abstract

Artificial Intelligence (AI) is a transformative force in communication and messaging strategy, with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI, are capable of generating high-quality, humanlike text. We investigate the persuasive quality of AI-generated messages to understand how AI could impact public health messaging. Specifically, through a series of studies designed to characterize and evaluate generative AI in developing public health messages, we analyze COVID-19 pro-vaccination messages generated by GPT-3, a state-of-the-art instantiation of a large language model. Study 1 is a systematic evaluation of GPT-3's ability to generate pro-vaccination messages. Study 2 then observed peoples' perceptions of curated GPT-3-generated messages compared to human-authored messages released by the CDC (Centers for Disease Control and Prevention), finding that GPT-3 messages were perceived as more effective, stronger arguments, and evoked more positive attitudes than CDC messages. Finally, Study 3 assessed the role of source labels on perceived quality, finding that while participants preferred AI-generated messages, they expressed dispreference for messages that were labeled as AI-generated. The results suggest that, with human supervision, AI can be used to create effective public health messages, but that individuals prefer their public health messages to come from human institutions rather than AI sources. We propose best practices for assessing generative outputs of large language models in future social science research and ways health professionals can use AI systems to augment public health messaging.

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https://dl.acm.org/doi/10.1016/j.ijhcs.2024.103380
Gawlik-Kobylińska M(2024)Harnessing Artificial Intelligence for Enhanced Scientific Collaboration: Insights from Students and Educational ImplicationsEducation Sciences10.3390/educsci1410113214:10(1132)Online publication date: 18-Oct-2024
https://doi.org/10.3390/educsci14101132
Wiśniewska JMatysik S(2024)The application of OpenAI Technology in Marketing Activities - A Systematic Literature ReviewJournal of Modern Science10.13166/jms/19701660:6(392-410)Online publication date: 29-Dec-2024
https://doi.org/10.13166/jms/197016
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Index Terms

Working With AI to Persuade: Examining a Large Language Model's Ability to Generate Pro-Vaccination Messages
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 7, Issue CSCW1

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April 2023

3836 pages

EISSN:2573-0142

DOI:10.1145/3593053

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