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AI Ethics

AI Governance: Building an Organizational Framework

Establish AI governance policies and procedures. Risk management, oversight, and compliance.

Rottawhite Team10 min readDecember 7, 2024
AI GovernanceRisk ManagementCompliance

AI Governance Fundamentals

AI governance establishes the policies, processes, and structures for responsible AI development and deployment.

Governance Components

Policies

  • AI ethics principles
  • Use case guidelines
  • Data governance
  • Risk tolerance

    • Processes

  • Review and approval
  • Risk assessment
  • Monitoring
  • Incident response

    • Structures

  • Oversight bodies
  • Clear roles
  • Escalation paths
  • Accountability

    • Key Elements

    Risk Management

  • Risk identification
  • Impact assessment
  • Mitigation strategies
  • Monitoring

    • Compliance

  • Regulatory requirements
  • Industry standards
  • Internal policies
  • Audit readiness

    • Accountability

  • Clear ownership
  • Decision authority
  • Documentation
  • Reporting

    • Implementation Steps

  • **Assessment**: Current state analysis
  • **Framework Design**: Policies and processes
  • **Structure Creation**: Committees and roles
  • **Rollout**: Communication and training
  • **Operation**: Ongoing governance
  • **Evolution**: Continuous improvement

    • Governance Bodies

    AI Ethics Committee

  • Strategic oversight
  • Policy decisions
  • Escalation handling

    • Technical Review Board

  • Technical standards
  • Model approval
  • Architecture decisions

    • Working Groups

  • Domain-specific guidance
  • Best practice development

    • Metrics and Reporting

  • Compliance rates
  • Incident tracking
  • Risk metrics
  • Audit findings

    • Conclusion

    Effective AI governance enables innovation while managing risks responsibly.

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