A Conceptual Model of Trust, Perceived Risk, and Reliance on AI Decision Aids. Issue 2 (April 2022)

• Record Type: Journal Article
• Authors: Solberg, Elizabeth; Kaarstad, Magnhild; Eitrheim, Maren H. Rø; Bisio, Rossella; Reegård, Kine; Bloch, Marten
• Other Names: Rapp Tammy L. guest-editor.; Davis Walter D. guest-editor.; Gilson Lucy L. guest-editor.
• Is Part Of: Group & organization management. Volume 47:Issue 2(2022)
• Page Start: 187
• Page End: 222
• Publication Date: 2022-04
• Subjects: trust -- perceived risk -- reliance -- artificial intelligence -- AI decision aids; Group relations training -- Periodicals; 658.4
• DOI: 10.1177/10596011221081238
• Languages: English
• ISSNs: 1059-6011

Abstract

There is increasing interest in the use of artificial intelligence (AI) to improve organizational decision-making. However, research indicates that people's trust in and choice to rely on "AI decision aids" can be tenuous. In the present paper, we connect research on trust in AI with Mayer, Davis, and Schoorman's (1995) model of organizational trust to elaborate a conceptual model of trust, perceived risk, and reliance on AI decision aids at work. Drawing from the trust in technology, trust in automation, and decision support systems literatures, we redefine central concepts in Mayer et al.'s (1995) model, expand the model to include new, relevant constructs (like perceived control over an AI decision aid), and refine propositions about the relationships expected in this context. The conceptual model put forward presents a framework that can help researchers studying trust in and reliance on AI decision aids develop their research models, build systematically on each other's research, and contribute to a more cohesive understanding of the phenomenon. Our paper concludes with five next steps to take research on the topic forward.