Exploring the AI Trust Paradox: Evidence from a Survey Experiment in the US

• In Event: Studying the Impact of Information Technology on Citizens

Abstract

Advances in Artificial Intelligence (AI) are poised to transform society, national defense,
and the economy by increasing efficiency, precision, and safety. Yet, widespread adoption within
society depends on public trust and willingness to use AI-enabled technologies. In this study we
propose the possibility of an AI “trust paradox,” in which individuals’ willingness to use AI-enabled
technologies exceeds their level of trust in these capabilities. We conduct a two-part study to explore
the trust paradox. First, we conduct a conjoint analysis, varying different attributes of AI-enabled
technologies in different domains—including armed drones, general surgery, police surveillance, self-
driving cars, and social media content moderation—to evaluate whether and under what conditions a
trust paradox may exist. Second, we use causal mediation analysis in the context of a second survey
experiment to help explain why individuals use AI-enabled technologies that they do and do not trust.
We find strong support for the trust paradox, particularly in the area of AI-enabled police surveillance,
where the levels of support for its use are both higher than other domains but also significantly exceed
trust. We unpack these findings to show that several underlying beliefs help account for public
attitudes of support, including the fear of missing out, optimism that future versions of the technology
will be more trustworthy, a belief that the benefits of AI-enabled technologies outweigh the risks, and
calculation that AI-enabled technologies yield efficiency gains. Our findings have important
implications for the integration of AI-enabled technologies in multiple settings.

Authors

• Sarah E. Kreps

• Julie George, Cornell University

• Paul Lushenko, The George Washington University

• Adi Rao, Cornell University