Challenges and Trends in User Trust Discourse in AI
It addresses the problem of trust gaps and misinterpretations in AI adoption for users and developers, but is incremental as it focuses on clarifying existing discourse rather than introducing new solutions.
This work tackles the problem of misconceptions and lack of clarity in user trust within AI discourse, aiming to prevent vulnerable interactions and trust breaches, with findings highlighting unclear understanding and measurement of user trust characteristics.
The Internet revolution in 1990, followed by the data-driven and information revolution, has transformed the world as we know it. Nowadays, what seam to be 10 to 20 years ago, a science fiction idea (i.e., machines dominating the world) is seen as possible. This revolution also brought a need for new regulatory practices where user trust and artificial Intelligence (AI) discourse has a central role. This work aims to clarify some misconceptions about user trust in AI discourse and fight the tendency to design vulnerable interactions that lead to further breaches of trust, both real and perceived. Findings illustrate the lack of clarity in understanding user trust and its effects on computer science, especially in measuring user trust characteristics. It argues for clarifying those notions to avoid possible trust gaps and misinterpretations in AI adoption and appropriation.