AI Policy Principles, Practice, and the Path Forward
By Anand Vemula
Length5h 54m
About this audiobook
This comprehensive volume on AI policy provides an in-depth, forward-looking exploration of how artificial intelligence intersects with governance, ethics, law, economy, and society. Structured across four parts and thirty chapters, the book examines both foundational principles and emerging challenges in global AI policymaking.
The first part lays the groundwork, tracing historical technology policies, defining AI within regulatory contexts, and analyzing ethical frameworks and geopolitical approaches. Part II explores core policy themes such as data governance, algorithmic transparency, human rights, bias, accountability, economic disruption, surveillance, national security, and environmental impact. These chapters unpack the tensions between innovation and regulation, and between individual rights and collective risks.
Part III shifts to the tools of governance, distinguishing between soft law (standards, guidelines) and hard law (binding regulations), and addressing mechanisms like policy sandboxes, public procurement levers, and risk differentiation between safety and security. The final part uniquely delves into underexplored topics, including AI in informal economies, the Global South, participatory governance, open-source regulation, and liability insurance.
The concluding chapters anticipate future challenges—global treaty feasibility, long-term foresight, institutional capacity-building, and evaluating policy effectiveness. A strong emphasis is placed on democratizing AI policy, arguing that equitable, inclusive, transparent, and accountable governance must be central to any sustainable AI future.
By offering a holistic yet detailed view, the book equips policymakers, researchers, and civil society actors with the tools to navigate and shape AI governance in a way that serves the public good, respects diversity, and guards against harm across all societies.
Audiobook details
GenreEducation and Learning, Self-Help
Length5 hrs 54 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateJun 1, 2025
LanguageEnglish
Table of contents
1Chapter 1: Introduction to AI and Governance
2Chapter 2: A Historical Overview of Technology Policy
3Chapter 3: Defining Artificial Intelligence in Policy Contexts
4Chapter 4: Ethical Frameworks in AI Regulation
5Chapter 5: Global Policy Approaches – US, EU, China, and Beyond
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6Chapter 6: Data Governance and Sovereignty
7Chapter 7: Algorithmic Transparency and Explainability
8Chapter 8: AI and Human Rights: A Legal Perspective
9Chapter 9: Bias, Fairness, and Discrimination in Machine Learning
10Chapter 10: Accountability Mechanisms and Auditing Systems
11Chapter 11: Workforce Impact and Economic Transition
12Chapter 12: Surveillance, Privacy, and Civil Liberties
13Chapter 13: AI in Critical Infrastructure and National Security
14Chapter 14: Environmental Impacts of Large-Scale AI Systems
15Chapter 15: Soft Law: Standards, Guidelines, and Voluntary Codes
16Chapter 16: Hard Law: Binding Regulations and Enforcement Mechanisms
17Chapter 17: Sandboxing and Experimental AI Policy Frameworks
18Chapter 18: AI Safety vs AI Security: Differentiating Risk Vectors
19Chapter 19: Public Procurement as a Policy Lever for Ethical AI
20Chapter 20: Decolonizing AI Policy
21Chapter 21: The Role of Insurance and Liability Markets in AI Risk Management
22Chapter 22: AI Policy for Small Nations and Low-Resource States
23Chapter 23: Open-Source AI and Policy: Regulation Without Ownership
24Chapter 24: Citizen Assemblies and Participatory AI Governance
25Chapter 25: AI in Informal Economies and Non-Western Contexts
26Chapter 26: Toward Global AI Treaties: Feasibility and Fractures
27Chapter 27: AI Policy Foresight: Scenarios for 2035 and Beyond
28Chapter 28: Building Institutional Capacity for AI Governance
29Chapter 29: Evaluating the Effectiveness of AI Regulations
30Chapter 30: Conclusion: Democratizing the Future of AI Policy
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