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From Tool to Agent: A Semi-Systematic Review of Human-AI Alignment and a Proposed Tiered Healing Ecosystem for Mental
Anran Ma1, Jingying Chen1, Zhiyi Yang1
1National Engineering Research Center for E-Learning, Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China.
Abstract:
Background: This study aims to systematically analyze the structural transition of AI in mental health, differentiating between passive tools and autonomous agents, and to propose a governance framework to facilitate responsible integration or mitigate integration risks. Methods: Employing a semi-systematic approach, we screened records from IEEE Xplore, PubMed, and ACM DL, ultimately analyzing 61 included studies. We track the transition from the first paradigm, AI-as-Tool (AI-T) to the second paradigm, AI-as-Agent (AI-A). Results: Early empirical evidence suggests that AI-A systems may assist in fostering preliminary working alliances and demonstrate potential for symptom reduction in controlled settings; however, their efficacy cannot currently be equated with, nor serve as a replacement for, standard low-intensity clinical care. Conclusions: To mitigate these risks, we propose the Tiered Human-AI Healing Ecosystem (THHE) for mental health. This framework utilizes dynamic autonomy modulation-automatically restricting AI agency based on real-time risk markers-to manage transitions between AI-led support and human-led care, promoting clinical safety.
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