Trust in AI: Progress, Challenges, and Future Directions
arxiv(2024)
摘要
The increasing use of artificial intelligence (AI) systems in our daily life
through various applications, services, and products explains the significance
of trust/distrust in AI from a user perspective. AI-driven systems (as opposed
to other technologies) have ubiquitously diffused in our life not only as some
beneficial tools to be used by human agents but also are going to be
substitutive agents on our behalf, or manipulative minds that would influence
human thought, decision, and agency. Trust/distrust in AI plays the role of a
regulator and could significantly control the level of this diffusion, as trust
can increase, and distrust may reduce the rate of adoption of AI. Recently,
varieties of studies have paid attention to the variant dimension of
trust/distrust in AI, and its relevant considerations. In this systematic
literature review, after conceptualization of trust in the current AI
literature review, we will investigate trust in different types of
human-Machine interaction, and its impact on technology acceptance in different
domains. In addition to that, we propose a taxonomy of technical (i.e., safety,
accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and
mixed) trustworthiness metrics, and some trustworthy measurements. Moreover, we
examine some major trust-breakers in AI (e.g., autonomy and dignity threat),
and trust makers; and propose some future directions and probable solutions for
the transition to a trustworthy AI.
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