Training on AI Governance and Regulatory Frameworks

Module 1: Key AI Concepts and Their Governance Implications

• Understanding the core concepts of AI and machine learning
• Exploring the governance implications of AI technologies
• Identifying the stakeholders and actors in AI governance
• Understanding the policy and regulatory landscape for AI
• Developing a governance framework for AI
• Case Study: Mapping the governance implications of an AI technology

Module 2: Ethics and Cybersecurity in AI Governance

• Understanding the ethical dimensions of AI governance
• Addressing bias, fairness, and accountability in AI systems
• Exploring cybersecurity risks and challenges in AI
• Developing strategies for secure and trustworthy AI
• Integrating ethics and cybersecurity into AI governance
• Case Study: Analyzing ethics and cybersecurity in an AI application

Module 3: Global Legal Frameworks for AI Regulation

• Understanding international AI regulations and standards
• Exploring national and regional AI strategies and policies
• Examining the role of international organizations in AI regulation
• Understanding compliance requirements and best practices
• Developing strategies for regulatory alignment and cooperation
• Case Study: Analyzing a global legal framework for AI

Module 4: AI System Lifecycles and Governance Gaps

• Understanding the lifecycle of AI systems from design to deployment
• Identifying governance gaps at each stage of the AI lifecycle
• Assessing risks and challenges in AI system governance
• Developing strategies for closing governance gaps
• Building governance structures for AI systems
• Case Study: Identifying governance gaps in an AI system lifecycle

Module 5: Design Thinking Labs for Governance Solutions

• Applying design thinking to AI governance challenges
• Developing innovative governance solutions through labs
• Prototyping governance frameworks and tools
• Testing and refining governance solutions
• Building stakeholder engagement and collaboration
• Case Study: Developing a governance solution through design thinking

Module 6: Journey Mapping and Prototyping for AI Governance

• Understanding journey mapping as a governance tool
• Mapping the AI governance journey for stakeholders
• Prototyping governance processes and workflows
• Testing and refining governance prototypes
• Building user-centered governance frameworks
• Case Study: Journey mapping and prototyping for AI governance

Module 7: Testing Oversight Tools for AI Systems

• Understanding the need for oversight in AI systems
• Developing oversight tools and mechanisms for AI
• Testing oversight tools for effectiveness and efficiency
• Evaluating oversight tools for different AI applications
• Building a comprehensive oversight framework for AI
• Case Study: Testing an oversight tool for an AI system

Module 8: Sector-Specific Challenges and Risk Mapping

• Understanding sector-specific challenges in AI governance
• Mapping risks and opportunities in different sectors
• Developing sector-specific governance strategies
• Addressing cross-sectoral issues and interdependencies
• Building sectoral governance frameworks for AI
• Case Study: Developing a sector-specific governance strategy

Module 9: Cross-Border Regulatory Negotiations

• Understanding the challenges and opportunities of cross-border AI governance
• Developing strategies for regulatory cooperation and harmonization
• Engaging in cross-border regulatory negotiations
• Building consensus and trust among regulatory actors
• Developing mechanisms for cross-border enforcement and compliance
• Case Study: Conducting a cross-border regulatory negotiation

Module 10: Co-Developing a Five-Year AI Governance Roadmap

• Developing a shared vision for AI governance
• Setting strategic objectives and priorities for governance
• Creating a five-year roadmap for AI governance implementation
• Identifying resources, partners, and stakeholders for implementation
• Monitoring and evaluating progress on the roadmap
• Case Study: Co-developing a five-year AI governance roadmap