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.

人工智能在我们的日常生活中越来越广泛地使用，尤其在各种应用、服务和产品中。因此，从用户角度来看，对人工智能的信任或不信任变得非常重要。这篇论文通过系统文献综述，探讨了当前人工智能领域的信任概念，并研究了不同类型的人机交互中的信任以及其对不同领域的技术接受度的影响。此外，还提出了技术和非技术的可信度指标以及一些可信度衡量标准，并分析了一些人工智能中的主要破坏因素和信任建立因素，并为实现可信度从而实现人工智能的可靠过渡提出了一些未来的方向和可能的解决方案。