1Chapter 1: Introduction to AI and Governance
16Chapter 16: Hard Law: Binding Regulations and Enforcement Mechanisms
2Chapter 2: A Historical Overview of Technology Policy
17Chapter 17: Sandboxing and Experimental AI Policy Frameworks
3Chapter 3: Defining Artificial Intelligence in Policy Contexts
18Chapter 18: AI Safety vs AI Security: Differentiating Risk Vectors
4Chapter 4: Ethical Frameworks in AI Regulation
19Chapter 19: Public Procurement as a Policy Lever for Ethical AI
5Chapter 5: Global Policy Approaches – US, EU, China, and Beyond
20Chapter 20: Decolonizing AI Policy
6Chapter 6: Data Governance and Sovereignty
21Chapter 21: The Role of Insurance and Liability Markets in AI Risk Management
7Chapter 7: Algorithmic Transparency and Explainability
22Chapter 22: AI Policy for Small Nations and Low-Resource States
8Chapter 8: AI and Human Rights: A Legal Perspective
23Chapter 23: Open-Source AI and Policy: Regulation Without Ownership
9Chapter 9: Bias, Fairness, and Discrimination in Machine Learning
24Chapter 24: Citizen Assemblies and Participatory AI Governance
10Chapter 10: Accountability Mechanisms and Auditing Systems
25Chapter 25: AI in Informal Economies and Non-Western Contexts
11Chapter 11: Workforce Impact and Economic Transition
26Chapter 26: Toward Global AI Treaties: Feasibility and Fractures
12Chapter 12: Surveillance, Privacy, and Civil Liberties
27Chapter 27: AI Policy Foresight: Scenarios for 2035 and Beyond
13Chapter 13: AI in Critical Infrastructure and National Security
28Chapter 28: Building Institutional Capacity for AI Governance
14Chapter 14: Environmental Impacts of Large-Scale AI Systems
29Chapter 29: Evaluating the Effectiveness of AI Regulations
15Chapter 15: Soft Law: Standards, Guidelines, and Voluntary Codes
30Chapter 30: Conclusion: Democratizing the Future of AI Policy
