Governance
AI Governance Framework
Establish robust governance structures, policies, and procedures for responsible AI development, deployment, and monitoring across your organization.
Governance Structure
Organizational roles and responsibilities for AI oversight
- • AI Ethics Board
- • Chief AI Officer
- • AI Review Committees
- • Stakeholder Engagement
Policies & Procedures
Documented guidelines for AI development and use
- • AI Use Policies
- • Development Standards
- • Review Processes
- • Incident Response
Monitoring & Control
Ongoing oversight and performance management
- • Performance Metrics
- • Audit Procedures
- • Compliance Tracking
- • Continuous Improvement
Governance Pillars
Accountability
Clear ownership and responsibility for AI systems
Establish clear lines of accountability for AI system development, deployment, and outcomes throughout the AI lifecycle.
Key Components
- • Designated AI system owners
- • Decision-making authority and escalation paths
- • Performance and outcome tracking
- • Incident response and remediation procedures
Transparency
Open communication about AI capabilities and limitations
Maintain transparency in AI system design, capabilities, limitations, and decision-making processes for all stakeholders.
Transparency Requirements
- • Model documentation and data provenance
- • Explainable AI techniques
- • User notification of AI interaction
- • Public reporting on AI use and impact
Fairness & Ethics
Ensuring equitable and ethical AI systems
Implement processes to identify and mitigate bias, ensure fairness, and uphold ethical principles in AI development and deployment.
Ethical Considerations
- • Bias detection and mitigation
- • Fairness metrics and testing
- • Ethical review processes
- • Stakeholder impact assessments
Related Resources
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