I Accept - A quantitative study exploring possible determinants for consumer trust in AI

Abstract

In this study, we examine factors which determine consumer trust in AI and explore challenges and opportunities in relation to these. Through investigating previous findings regarding online trust and trust in AI, we hypothesized that data transparency and anthropomorphism would have a direct effect on trust in AI, and that privacy concern and personal relevance would moderate these relationships. A 2x2- between-subject experiment was conducted, where anthropomorphism and data transparency were manipulated in fictitious shopping scenarios. The results concluded that anthropomorphism was not a predictor, while data transparency had a significant direct negative impact on trust in AI. Privacy concern and personal relevance were not shown to moderate any of the proposed relationships. Instead, privacy concern had a direct, negative impact, and personal relevance had a direct positive relationship with trust in AI. Altogether, we conclude data transparency and privacy concern negatively affects trust, whereas personal relevance is a strong positive predictor of trust in AI. Making content personally relevant through the use of AI, was identified as one of the main opportunities for marketers, while privacy concern and data transparency may pose a challenge for companies.