AI Policy Labs Regulation in Practice

Module 1: Foundations of AI Regulation

• Explore the risks and public interest in AI regulation
• Understand core concepts – risk-based regulation, accountability, transparency
• Categorize AI use cases and risk levels

Module 2: Major Regulatory Frameworks

• Analyze the EU AI Act – provisions, risk tiers, and obligations
• Examine the U.S. AI Strategy – Executive Orders, NIST AI RMF, FTC Guidance
• Compare global regulatory approaches: risk, rights, and enforcement models

Module 3: Compliance and Internal Governance

• Classify AI systems and map use cases
• Implement compliance requirements for high-risk systems
• Assign roles and accountability: DPOs, risk officers, and AI governance leads

Module 4: Tools for Policy Implementation

• Conduct impact assessments (AI, human rights, algorithmic, environmental)
• Perform conformity assessments and post-market monitoring
• Develop supplier and third-party due diligence

Module 5: AI Policy Simulation Labs

• Set up regulatory role-play (company, regulator, public)
• Enforce the EU AI Act – mock review and assessment
• Simulate U.S. risk management strategy

Module 6: Innovation, Influence, and Next-Gen Governance

• Explore sandbox models and experimental regulation
• Engage in public participation and governance
• Build regulatory foresight into AI strategy