Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support
Privacy represents one of the most critical yet underaddressed barriers to AI adoption in mental healthcare -- particularly in high-sensitivity operational environments such as military, correctional, and remote healthcare settings, where the risk of patient data exposure can deter help-seeking behavior entirely. Existing AI-enabled psychiatric decision support systems predominantly rely on cloud-based inference pipelines, requiring sensitive patient data to leave the device and traverse externa
Record details
Published: 20 April 2026
Source: arXiv
Category: Research
Topics: Privacy · Healthcare · Military & security · Environment
Retrieved: 14 July 2026
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ethics.ai (20 April 2026), “Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support,” evidence record 5602, https://ethics.ai/record/5602 (originally published by arXiv).
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