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Advancements in artificial intelligence (AI) over the last decade demonstratethat machines can exhibit communicative behavior and influence how humansthink, feel, and behave. In fact, the recent development of ChatGPT has shownthat large language models (LLMs) can be leveraged to generate high-qualitycommunication content at scale and across domains, suggesting that they will beincreasingly used in practice. However, many questions remain about how knowingthe source of the messages influences recipients' evaluation of and preferencefor AI-generated messages compared to human-generated messages. This paperinvestigated this topic in the context of vaping prevention messaging. In Study1, which was pre-registered, we examined the influence of source disclosure onpeople's evaluation of AI-generated health prevention messages compared tohuman-generated messages. We found that source disclosure (i.e., labeling thesource of a message as AI vs. human) significantly impacted the evaluation ofthe messages but did not significantly alter message rankings. In a follow-upstudy (Study 2), we examined how the influence of source disclosure may vary bythe participants' negative attitudes towards AI. We found a significantmoderating effect of negative attitudes towards AI on message evaluation, butnot for message selection. However, for those with moderate levels of negativeattitudes towards AI, source disclosure decreased the preference forAI-generated messages. Overall, the results of this series of studies showed aslight bias against AI-generated messages once the source was disclosed, addingto the emerging area of study that lies at the intersection of AI andcommunication.

The effect of source disclosure on evaluation of AI-generated messages: A two-part study