In recent years, artificial intelligence (AI) has been introduced into the field of mental health interventions, which not only brings innovation and progress, but also causes a series of ethical problems. This paper systematically analyzes the triple ethical challenges of AI applying to mental health interventions. Firstly, the current ethical frameworks for AI-based mental health interventions primarily expand upon medical ethics principles, emphasizing benefit maximization, risk minimization, and patient autonomy. However, these frameworks face challenges such as insufficient standardization and difficulties in dynamically capturing and regulating ethical risks arising from rapid technological iteration. Secondly, ethical challenges related to data governance in AI-based mental health applications include data privacy issues and decision fairness concerns stemming from algorithmic bias. Finally, AI as a proxy resource risks eroding user autonomy and fostering interpersonal alienation, primarily through exerting influence beyond comprehension to undermine autonomous decision-making capabilities. Overreliance and blind trust in AI systems during usage may weaken social motivation, thereby threatening autonomy and psychological integrity.