Perceived Factors of Trustworthiness in Generative Artificial Intelligence (GenAI): Towards an Understanding of how to Assess and Build Trustworthiness

Abstract

Given the benefits and risks associated with GenAI adoption in organizations, many academics and practitioners have stressed the importance of understanding how humans come to trust these technologies and the information and knowledge (e.g., solutions/decisions) they produce. The objective of this paper is to further examine human trust in AI technologies through the lens of a widely accepted organizational trust theory and model developed by Mayer, Davis, and Schoorman. More specifically, this paper focuses on developing a better understanding of perceived factors of GenAI trustworthiness since assessing trustworthiness is a critical determinant of trust. Building on the existing theory and model, it is proposed that an individual's perception of one or more of the following dimensions of trustworthiness - ability, integrity, and benevolence - will determine how trustworthy they find GenAI to be. Ability (or competence) refers to the trustee’s specific skills, knowledge, and expertise required in a specific domain. Integrity reflects the trustee’s sound values or principles (e.g., fairness, consistency, justice). Benevolence is an altruistic loyalty that reflects the trustee’s concern for the welfare, needs, desires, and interests of the individual over organizational or profit motives. Many researchers have proposed assessments related to GenAI ability, but integrity and benevolence are more difficult to assess, as technologies do not intrinsically embody human values or altruistic behaviors. Consequently, other parties within the organizations, such as AI designers and developers, strategic decision-makers, or the organization may be conflated into perceptions of these dimensions. The paper continues by briefly discussing how emotions and organizational culture may influence individuals' perceptions of trustworthiness and concludes by suggesting potential directions and strategies for building and representing each dimension of perceived trustworthiness in the context of GenAI.