AI Awareness and Tobacco Policy Messaging Among US Adults: Electronic Experimental Study

TL;DR

This study explores how US adults perceive AI-generated health messages about tobacco control and finds that awareness of AI use affects speaker ratings but not overall message effectiveness.

Contribution

The study introduces a novel experimental approach to assess public perception of AI-generated health messaging in the context of tobacco policy.

Findings

Perceived video effectiveness and credibility did not differ significantly across AI awareness conditions.

Participants rated the speaker higher when told the narrator was human compared to other conditions.

Positive attitudes toward AI were highest among those not informed about the narrator, though not statistically significant.

Abstract

Despite public health efforts, tobacco use remains the leading cause of preventable death in the United States and continues to disproportionately affect underrepresented populations. Public policies are needed to improve health equity in tobacco-related health outcomes. One strategy for promoting public support for these policies is through health messaging. Improvements in artificial intelligence (AI) technology offer new opportunities to create tailored policy messages quickly; however, there is limited research on how the public might perceive the use of AI for public health messages.

This study aimed to examine how knowledge of AI use impacts perceptions of a tobacco control policy video.

A national sample of US adults (N=500) was shown the same AI-generated video that focused on a tobacco control policy. Participants were then randomly assigned to 1 of 4 conditions where they were (1) told the narrator of the video was AI, (2) told the narrator of the video was human, (3) told it was unknown whether the narrator was AI or human, or (4) not provided any information about the narrator.

Perceived video rating, effectiveness, and credibility did not significantly differ among the conditions. However, the mean speaker rating was significantly higher (P=.001) when participants were told the narrator of the health message was human (mean 3.65, SD 0.91) compared to the other conditions. Notably, positive attitudes toward AI were highest among those not provided information about the narrator; however, this difference was not statistically significant (mean 3.04, SD 0.90).

Results suggest that AI may impact perceptions of the speaker of a video; however, more research is needed to understand if these impacts would occur over time and after multiple exposures to content. Further qualitative research may help explain why potential differences may have occurred in speaker ratings. Public health professionals and researchers should further consider the ethics and cost-effectiveness of using AI for health messaging.

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