AI and Mental Health – White Paper
AI and Mental Health – Policy and regulatory analysis
For Mental Health AI Systems
1. Purpose
The purpose of this Charter is to establish a governance framework for the safe, ethical, compliant, and effective use of Artificial Intelligence systems in mental health service delivery.
This framework ensures:
• Patient safety
• Regulatory compliance
• Privacy protection
• Clinical integrity
• Risk mitigation
• Ethical deployment
• Ongoing oversight
2. Scope
This Charter applies to all AI systems used within:
• Clinical documentation
• Risk prediction and triage
• Digital therapeutics
• Monitoring tools
• Decision support systems
• Vendor-provided AI solutions
• Internally developed models
3. Governance Structure
3.1 AI Clinical Oversight Committee (AICOC)
Composition:
• Chief Medical Officer (Chair)
• Chief Information Officer
• Chief Privacy Officer
• Chief Risk Officer
• Director of Mental Health Services
• Data Science Lead
• Legal Counsel
Mandate:
• Approve new AI use cases
• Review regulatory classification
• Monitor safety and bias
• Oversee vendor compliance
• Review adverse events
• Approve material model updates
Meeting Frequency:
• Monthly during implementation
• Quarterly post-stabilization
4. AI System Classification
All AI systems must be classified into one of three categories:
Category 1 — Administrative Augmentation
Category 2 — Clinical Decision Support
Category 3 — Regulated Medical Device / Therapeutic
Each classification determines:
• Required validation level
• Regulatory pathway
• Monitoring intensity
• Board reporting requirements
5. Risk Management Framework
For each AI system, the following must be documented:
• Intended use
• Clinical validation evidence
• Data sources
• Bias risk analysis
• Privacy impact assessment
• Regulatory status
• Escalation protocols
• Human-in-the-loop controls
• Monitoring metrics
6. Model Update Governance
All model updates must include:
• Version tracking
• Change documentation
• Impact assessment
• Validation review
• Committee approval for material changes
No automated deployment of major model revisions without oversight.
7. Privacy & Data Governance
AI deployments must comply with:
Canada:
• PHIPA / provincial health privacy laws
• PIPEDA (where applicable)
• Cross-border data disclosure obligations
US:
• HIPAA
• State privacy statutes
• Business Associate Agreements
Explicit restrictions:
• No secondary data use without approval
• No vendor retraining on patient data without consent
• Encryption at rest and in transit
8. Monitoring & Reporting
Quarterly AI Governance Report must include:
• Active AI systems
• Risk classification
• Performance metrics
• False positive/negative rates
• Bias assessment results
• Privacy incidents
• Regulatory developments
Annual:
• Independent bias audit
• Regulatory compliance review
• Board-level safety summary
9. Incident Response
Trigger events requiring immediate escalation:
• Patient harm linked to AI output
• Significant bias detection
• Privacy breach
• Regulatory investigation
• Model drift exceeding thresholds
10. Review Cycle
Charter reviewed annually or upon:
• Regulatory change
• Major AI expansion
• Significant safety event