Preventing Constructive Assumption Error in AI-Assisted Clinical Documentation
AI-assisted documentation tools are increasingly used in clinical, social work, and human services settings to reduce administrative burden and improve efficiency. While these systems demonstrate high fluency and structural competence, they introduce a subtle but under-examined ethical risk: the generation of clinically plausible content that exceeds what was explicitly documented by the professional. This paper identifies and names a specific failure mode that emerges under documentation expansion pressure: constructive assumption error.
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This paper supports ethical reflection and governance design. It does not replace professional licensure requirements, organizational policy, or legal counsel.