Reframing Ethical Governance of Artificial Intelligence in Mental Health Care: Toward a Human-Centered, Explainable, and Clinically Responsible Psychotherapeutic Paradigm

Abstract

The rapid integration of Artificial Intelligence (AI) into Mental Health care represents a transformative shift in the diagnosis, monitoring, and treatment of psychological disorders. While AI-driven tools—including digital phenotyping systems, natural language processing models, and conversational agents—offer significant potential to enhance diagnostic precision, accessibility, and personalized interventions, they simultaneously introduce complex ethical, clinical, and epistemological challenges. This study provides a comprehensive and critical synthesis of contemporary literature (2019–2025) to examine the ethical implications of AI deployment in psychotherapeutic contexts. Moving beyond descriptive review, the paper develops a conceptual ethical governance framework grounded in the principles of autonomy, beneficence, non-maleficence, and justice, as well as the emerging “ethics of care” paradigm. It identifies key risk domains, including algorithmic bias, opacity of decision-making processes, data privacy vulnerabilities, erosion of therapeutic alliance, and the reconfiguration of professional accountability. Furthermore, the study proposes a human-centered, explainable, and clinically supervised AI integration model, emphasizing transparency, continuous ethical auditing, stakeholder inclusion, and hybrid human–AI decision-making structures. The findings highlight that while AI can significantly improve efficiency and expand access to mental healthcare—particularly in resource-constrained settings—its unregulated or poorly designed application may exacerbate inequalities, compromise patient autonomy, and undermine trust in clinical practice. The paper contributes to the interdisciplinary discourse by offering a structured ethical framework that bridges technological innovation with clinical responsibility and humanistic values. It concludes that sustainable and ethically aligned AI integration in mental health requires robust regulatory architectures, cross-disciplinary collaboration, and the preservation of the fundamentally human dimensions of psychotherapy.

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