Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities

Roman Lukyanenko (), Wolfgang Maass () and Veda C. Storey ()
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Roman Lukyanenko: University of Virginia
Wolfgang Maass: Saarland University and German Research Center for Artificial Intelligence (DFKI)
Veda C. Storey: Georgia State University

Electronic Markets, 2022, vol. 32, issue 4, No 11, 1993-2020

Abstract: Abstract With the rise of artificial intelligence (AI), the issue of trust in AI emerges as a paramount societal concern. Despite increased attention of researchers, the topic remains fragmented without a common conceptual and theoretical foundation. To facilitate systematic research on this topic, we develop a Foundational Trust Framework to provide a conceptual, theoretical, and methodological foundation for trust research in general. The framework positions trust in general and trust in AI specifically as a problem of interaction among systems and applies systems thinking and general systems theory to trust and trust in AI. The Foundational Trust Framework is then used to gain a deeper understanding of the nature of trust in AI. From doing so, a research agenda emerges that proposes significant questions to facilitate further advances in empirical, theoretical, and design research on trust in AI.

Keywords: Artificial intelligence (AI); Trust; Foundational Trust Framework; Trust in AI; Explainable AI; Transparency; Systems (search for similar items in EconPapers)
JEL-codes: C71 C72 C73 C80 D11 J00 L63 L64 L86 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12525-022-00605-4

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