  We present an overview of the literature on trust in AI and AI
trustworthiness and argue for the need to distinguish these concepts more
clearly and to gather more empirically evidence on what contributes to people s
trusting behaviours. We discuss that trust in AI involves not only reliance on
the system itself, but also trust in the developers of the AI system. AI ethics
principles such as explainability and transparency are often assumed to promote
user trust, but empirical evidence of how such features actually affect how
users perceive the system s trustworthiness is not as abundance or not that
clear. AI systems should be recognised as socio-technical systems, where the
people involved in designing, developing, deploying, and using the system are
as important as the system for determining whether it is trustworthy. Without
recognising these nuances, trust in AI and trustworthy AI risk becoming
nebulous terms for any desirable feature for AI systems.
