AI Governance

1. Purpose and Scope

These policies establish governance requirements for the design, development, deployment, and monitoring of Artificial Intelligence (AI) systems within Cordata Healthcare Innovations Inc. The goal is to ensure that AI systems are safe, secure, explainable, fair, and trustworthy, while complying with HIPAA, NIST guidance, and other applicable regulations.

These policies apply to all employees, contractors, vendors, and partners engaged in AI-related activities.

2. Governance Principles

• Validity & Reliability: AI systems must be accurate, robust, and clinically relevant.
• Safety & Security: AI must not introduce risks to patient safety, system integrity, or data confidentiality.
• Accountability & Transparency: Roles, responsibilities, and decision-making authority must be clear and auditable.
• Explainability & Interpretability: AI outputs should be explainable to clinicians, patients, and regulators.
• Privacy & Fairness: AI systems must safeguard Protected Health Information (PHI) and prevent discrimination.
• Continuous Improvement: AI systems must undergo ongoing monitoring, testing, and refinement.

3. Policy Requirements

3.1 Governance & Accountability

• Establish an AI Governance Committee to oversee compliance, risk assessments, and ethical use.
• Define roles and responsibilities for developers and compliance officers.
• Require documented approvals before any AI system is deployed in production.

3.2 Risk Management

• Conduct AI Risk Assessments using the NIST AI RMF across the lifecycle (design → deployment → monitoring).
• Evaluate risks for bias, accuracy, interpretability, and security vulnerabilities.
• Maintain a risk register for all AI systems and mitigation strategies.

3.3 Data Management & Quality

• Use only HIPAA-compliant data sources with documented lineage.
• Apply de-identification or anonymization techniques where possible.
• Require data quality checks for completeness, consistency, and bias.
• Maintain data use agreements with third-party providers.

3.4 Development Standards

• Document AI design decisions, assumptions, and limitations.
• Require model explainability techniques for decision support systems.
• Ensure AI systems meet software validation standards (e.g., FDA SaMD guidance, ISO/IEC standards).

3.5 Security & Privacy

• Apply NIST Cybersecurity Framework (CSF) controls to AI pipelines.
• Encrypt PHI at rest and in transit.
• Require access controls and audit logging for AI models and datasets.
• Perform adversarial robustness testing to detect model manipulation.

3.6 Deployment & Monitoring

• Require pilot testing with clinicians before full-scale deployment.
• Continuously monitor AI for accuracy drift, bias, and unintended consequences.
• Implement human-in-the-loop safeguards for high-stakes clinical decisions.
• Establish a model update and retraining policy with version control.

3.7 Transparency & Documentation

• Maintain a Model Card or equivalent documentation for each AI system.
• Provide patient-facing disclosures when AI is used in clinical decision-making.
• Maintain explainability reports for regulators, auditors, and customers.

3.8 Compliance & Auditing

• Conduct annual AI audits aligned with HIPAA, NIST AI RMF, and FDA guidance.
• Require vendor compliance attestations for AI components from third parties.
• Ensure incident reporting mechanisms exist for AI failures, bias, or security breaches.

4. Training & Awareness

• Provide mandatory AI governance training for technical and clinical staff.
• Educate employees on bias, fairness, and responsible AI practices.
• Maintain ongoing compliance refreshers aligned with evolving regulations.

5. Enforcement

Non-compliance with these policies may result in disciplinary action, contract termination, or regulatory reporting. The AI Governance Committee is responsible for enforcement, exception handling, and policy updates.

6. Review & Updates

This policy will be reviewed annually or when new laws, regulations, or standards are published. Updates will be approved by the AI Governance Committee and communicated to all employees.