Abstract
The use of AI in digital mental healthcare promises to make treatments more effective, accessible, and scalable than ever before. At the same time, the use of AI opens a myriad of ethical concerns, including the lack of transparency, the risk of bias leading to increasing social inequalities, and the risk of responsibility gaps. This raises a crucial question: Can we rely on these systems to deliver care that is both ethical and effective? In attempts to regulate and ensure the safe usage of AI-powered tools, calls to trustworthy AI systems have become central. However, the use of terms such as "trust" and "trustworthiness" risks increasing anthropomorphization of AI systems, attaching human moral activities, such as trust, to artificial systems. In this article, we propose that terms such as "trustworthiness" be used with caution regarding AI and that when used, they should reflect an AI system's ability to consistently demonstrate measurable adherence to ethical principles, such as respect for human autonomy, nonmaleficence, fairness, and transparency. On this approach, trustworthy and ethical AI has the possibility of becoming a tangible goal rather than wishful thinking.