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.
CITATION STYLE
Lukyanenko, R., Maass, W., & Storey, V. C. (2022, December 1). Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities. Electronic Markets. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s12525-022-00605-4
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