Responsible AI-Assisted Digital Harm Screening and Referral in Clinical Mental Health Counseling: A Conceptual Framework for College Student Well-Being

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Clinical mental health departments are increasingly asked to respond to student anxiety, depression, cyberbullying, online harassment, reputational injury, and digitally mediated conflict while also evaluating whether artificial intelligence (AI) tools can improve access, triage, documentation, and referral. This article develops a responsible AI-assisted digital harm screening and referral framework for clinical mental health counseling, with a specific focus on college student well-being. Using a conceptual narrative review design, the article synthesizes counseling ethics, AI governance, digital harm literature, and responsible decision-support scholarship. The central argument is that AI may support counselors by organizing intake information, identifying patterns that require human attention, and improving workflow consistency; however, AI must not replace clinical judgment, crisis assessment, informed consent, cultural responsiveness, or the therapeutic relationship. The proposed SAFE-CMH framework includes six dimensions: Screening and symptom context, Accountability and informed consent, Fairness and bias control, Escalation and human oversight, Community prevention education, and Mental health outcome monitoring. The framework is informed by the American Counseling Association Code of Ethics, the National Institute of Standards and Technology AI Risk Management Framework, World Health Organization AI-for-health guidance, and a limited selection of highly relevant research by Ebenezer Amakeh and colleagues on digital misconduct, ethical AI governance, and AI-supported organizational decision-making. The article concludes that responsible AI in clinical mental health should be implemented as a supervised decision-support layer, not as an autonomous therapist or disciplinary investigator. A phased implementation and evaluation plan is provided for counseling departments seeking to adopt AI-enabled tools while protecting confidentiality, client rights, safety, equity, and professional accountability.

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