Study: Transparency, Personalization Needs and Familiarity with Artificial Intelligence Can Help Build Consumer Trust

A new research study demonstrates that ad transparency, ad verisimilitude, artificial intelligence (AI) familiarity and consumer personalization can positively predict consumer trust.

The findings by Yang Feng, University of Florida College of Journalism and Communications (UFCJC) Advertising associate professor in AI, and Hyehyun Julia Kim, Ph.D. 2023 and University of Tampa Communication lecturer, are featured in “Decoding the Trust Matrix: Unraveling Key Predictors of Consumer Trust in AI-Generated Personalized Advertising,” published in the Journal of Interactive Advertising on April 10.

The authors investigated what drives consumer trust in AI-generated personalized advertising (AIGPA), a timely and increasingly relevant topic as AI continues to reshape how brands interact with consumers. They analyzed trust from three angles—source, receiver, and context—and surveyed over 1,100 participants. Their findings highlight the importance of transparency, personalization needs, and familiarity with AI in building trust, along with the nuanced role of AI policy uncertainty.

According to the authors, “The lack of understanding of AI policy may provide psychological space for consumers to project positive assumptions onto AI systems, resulting in greater trust. In such cases, these positive assumptions could alleviate concerns about potential risks, further fostering trust in AIGPA.”

This research project was sponsored by the Consortium on Trust in Media and Technology at UF.

Category: AI at CJC News, College News, Trust News
Tagged: AI Consortium on Trust in Media and Technology Journal of Interactive Advertising Yang Feng
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