Responsible AI Framework for Mental‑Health Monitoring Systems: Governance, Safety, and Ethical Architecture
DOI:
https://doi.org/10.30750/ijarst.110196Keywords:
Responsible AI; Mental-Health Monitoring; AI Governance; AI Ethics; Privacy; Algorithmic Fairness; Explainable AI; Human Oversight; Risk Management; Healthcare AIAbstract
The use of Artificial Intelligence (AI) in mental-health monitoring systems is an increasing trend to identify potential indicators of emotional distress, stress, burnout and behavioral changes. These technologies offer opportunities for early intervention and appropriate support, but there are concerns with the use of these technologies in sensitive mental health contexts, such as privacy, informed consent, algorithmic bias, transparency, safety, and inappropriate automation. In this paper, we propose a Responsible AI Framework for Mental-Health Monitoring Systems, which is composed of governance, safety, ethical considerations and technical architecture. This framework consists of the following components: Risk classification, data handling with privacy protection, fairness assessment, explainability, human oversight, boundaries of ethical use, continuous monitoring, and accountability mechanisms. It provides a multi-layered architecture encompassing data, model, governance and human oversight and user experience layers, to aid in the responsible implementation of the AI lifecycle. The framework also includes protection against the misinterpretation of the results, overreliance on automated predictions, unauthorized second use of the prediction, and even harmful interventions. This proposed framework includes a structured approach for developing mental-health monitoring systems that are both trustworthy and ethical, combining technical, organizational, and ethical considerations. It emphasizes the role of AI in supporting rather than replacing human knowledge and skills, and it underscores the necessity of transparency and accountability in utilizing AI-driven data and the need for individuals to have clear control over their personal and sensitive information.
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