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“AI Policy Labs: Regulation in Practice” is a simulation-driven, policy-maker-focused program designed to translate ethical principles and legal frameworks into enforceable AI regulation.
Participants explore and compare leading regulatory models—such as the EU AI Act, US Executive Orders, OECD AI Principles, UNESCO AI Ethics Recommendations, and national AI strategies—and apply them in lab environments. The program blends lectures, working groups, and live simulation labs to enable participants to design policies, conduct regulatory risk analysis, and advise governments or corporations on AI compliance, surveillance limits, and ethical oversight.
To develop practical policymaking and implementation skills for designing, analyzing, and enforcing AI governance and regulatory frameworks in real-world national, regional, and institutional settings.
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Professional Certification Program
Equip professionals with the tools to bridge theory and implementation in AI policy
Train participants to simulate, draft, and critique regulatory frameworks
Support creation of fair, democratic, and innovation-supportive AI ecosystems
Promote alignment across sectors and jurisdictions in regulating AI
Build institutional capacity to govern and monitor algorithmic systems
Chapter 1.1: Why Regulate AI? Risks, Public Interest, and Policy Gaps
Chapter 1.2: Core Concepts – Risk-Based Regulation, Accountability, Transparency
Chapter 1.3: Categories of AI Use Cases and Risk Levels
Chapter 1.4: Legal vs. Ethical Instruments in AI Governance
Chapter 2.1: The EU AI Act – Provisions, Risk Tiers, and Obligations
Chapter 2.2: U.S. AI Strategy – Executive Orders, NIST AI RMF, FTC Guidance
Chapter 2.3: Global Landscape – Canada’s AIDA, Brazil, Singapore, OECD, UNESCO
Chapter 2.4: Comparing Regulatory Approaches: Risk, Rights, and Enforcement Models
Chapter 3.1: AI System Classification and Use Case Mapping
Chapter 3.2: Compliance Requirements for High-Risk Systems (per EU AI Act)
Chapter 3.3: Roles and Accountability: DPOs, Risk Officers, and AI Governance Leads
Chapter 3.4: Documentation, Logging, and Risk Management Systems
Chapter 4.1: Impact Assessments (AI, Human Rights, Algorithmic, Environmental)
Chapter 4.2: Conformity Assessments and Post-Market Monitoring
Chapter 4.3: Supplier and Third-Party Due Diligence
Chapter 4.4: Interfacing with Regulators and Auditors
Chapter 5.1: Lab Setup – Regulatory Role Play (Company, Regulator, Public)
Chapter 5.2: Enforcing the EU AI Act – Mock Review and Assessment
Chapter 5.3: U.S. Risk Management Strategy Simulation
Chapter 5.4: Responding to Violations: Drafting Remediation Plans
Chapter 6.1: Sandbox Models and Experimental Regulation
Chapter 6.2: Public Engagement and Participatory Governance
Chapter 6.3: Building Regulatory Foresight into AI Strategy
Chapter 6.4: Capstone – Draft a Regulatory Compliance Plan or Policy Proposal
Video content aligned with weekly modules
Understanding the Global AI Regulatory Landscape
Introduction to AI Regulation: Why It Matters
Core Principles: Transparency, Accountability, and Risk-Based Design
Understanding Risk Categories in AI Systems
Legal vs. Ethical Governance in Practice
Deep Dive: EU AI Act – Scope, Risk Tiers, and Compliance Triggers
U.S. Federal Guidance: Executive Orders, NIST AI RMF, and FTC Policy Signals
International Perspectives: Brazil, Singapore, Canada, UNESCO, OECD
Comparative Case: Rights vs. Innovation-Centered Regulation
Operationalizing Regulation Inside Organizations
Classifying AI Systems by Use Case and Risk
High-Risk Obligations Under the EU AI Act
Documentation and Logging Requirements Explained
Roles and Accountability: Who Is Responsible?
Building Internal Risk Management Systems
Conducting AI Impact Assessments (AIA, HRIA, DPIA)
Conformity and Compliance Assessments: What They Look Like
Supplier Due Diligence and Procurement Compliance
Strategy, Simulation, and Future Policy Design
Regulatory Role-Play: Inside a Mock AI Audit
Drafting a Remediation Plan After a Compliance Violation
Simulating U.S. AI Risk Framework Implementation
Sandbox Governance and Experimental Regulation Models
Public Consultation, Civil Society Input, and Co-Governance
Trends in AI Law: What’s Coming in the Next 5 Years
Building Proactive AI Governance Into Innovation Strategy
Capstone Support Video: Policy Plan or Compliance Playbook
Final Recap: AI Regulation as a Strategic Capability
Interactive expert sessions aligned with weekly modules
Title: Navigating Global AI Laws: What Leaders Need to Know Now
Duration: 60 minutes
Focus: Unpacking key elements of the EU AI Act, U.S. regulatory direction, and international trends
Guest: AI Law & Policy Advisor (EU Commission / NIST / OECD-affiliated)
Interactive: Live map exercise: Identify how different risk tiers apply to common AI use cases across jurisdictions
Title: Inside the Compliance Engine: Building Operational Readiness
Duration: 75 minutes
Focus: How organizations prepare for AI regulation—system classification, documentation, impact assessments
Guest: Chief Compliance Officer / Legal Counsel from a tech or healthcare organization
Interactive: Walkthrough of a sample AI compliance checklist + audience critique and discussion
Title: AI Policy in Action: Regulation, Resistance, and Real-World Decisions
Duration: 90 minutes
Focus: Simulation debrief, participatory regulation, and future-focused governance strategies
Guest Panel: Regulator + Civil Society Advocate + Corporate Ethics Lead
Interactive: Capstone project feedback + group role-play: respond to an AI regulatory audit scenario in real time
Government officials and regulators
Policy researchers and legislative drafters
Legal scholars and AI ethics researchers
Multilateral organization professionals (UN, WHO, WEF, OECD, etc.)
Corporate legal and policy officers working on AI compliance
Understand the global landscape of AI regulation and its legal evolution
Draft practical and enforceable AI governance policies
Conduct policy simulations, risk classification, and stakeholder assessments
Advise on regulatory strategy for governments, companies, or civil societies
Receive a certificate in “AI Policy Implementation and Regulatory Practice”
Fee: INR 21499 USD 249
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of Currencies
AI Policy Consultant or Advisor
Government Tech Regulator
Regulatory Affairs Officer (AI/Tech Sector)
Ethics and Compliance Strategist
AI Governance Research Fellow
Government ministries and regulatory bodies
International policy organizations and think tanks
Law firms and tech consultancies
Corporate ESG and public affairs departments
Academia and AI ethics research centers
Take your research to the next level!
Achieve excellence and solidify your reputation among the elite!
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