The Global Politics of Artificial Intelligence

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgements
Editor
List of Contributors
Chapter 1 Threading Innovation, Regulation, and the Mitigation of AI Harm: Examining Ethics in National AI Strategies
	1.1 Introduction
	1.2 Artificial Intelligence: The Eternal Dream
		1.2.1 Harmful AI
	1.3 National AI Strategies
		1.3.1 Defining National AI Strategies
		1.3.2 No Strategy, No AI?
	1.4 To Regulate, Or Not To Regulate?
		1.4.1 AI Tensions: Between Innovation and Regulation
		1.4.2 Risk Mitigation
		1.4.3 Design and Deployment Concerns
	1.5 Governance Approaches
	1.6 The Limits and Potentials of Ethics in National AI Strategies
		1.6.1 AI Ethics Limits: Five Issues
		1.6.2 AI Ethics Potentials: Ten Cues
	1.7 Conclusion
	Notes
	References
Chapter 2 Governance of Artificial Intelligence: Emerging International Trends and Policy Frames
	2.1 Introduction: Why Focus on AI Policy and Governance?
	2.2 Emerging Sciences and Technologies and Their Governance: Hype, Expectations, and Uncertainties
	2.3 Literature Review of AI Governance: Ethics, Responsibility and Policy
	2.4 Fast-Developing Policy For AI: International Trends and Drivers
	2.5 Emerging AI Policy Frames: Revolution, Global Race, and Balancing Benefits, Risks, and Responsibilities
	2.6 Conclusions: Key Insights and Future Research Questions
	Acknowledgements
	Notes
Chapter 3 Multilateralism and Artificial Intelligence: What Role for the United Nations?
	3.1 Introduction
	3.2 The International Governance of AI: A Fragmented Landscape
	3.3 What the United Nations Has Been Doing, Could It Do More?
	3.4 The High-Level Panel on Digital Cooperation and the Way Ahead
	3.5 Conclusion
	Acknowledgements
	Notes
Chapter 4 Governing the Use of Autonomous Weapon Systems
	4.1 Principles of International Humanitarian Law
		4.1.1 The Principle of Distinction
		4.1.2 The Principles of Proportionality and Precautions in Attack
	4.2 A New Legal Framework
		4.2.1 A Ban Treaty
			4.2.1.1 Clarity
			4.2.1.2 Feasibility
			4.2.1.3 Applicability
		4.2.2 Regulatory Framework on the Use of AWS
			4.2.2.1 Regulations on Targeting
			4.2.2.2 Regulations on Residual Human Control
			4.2.2.3 Clarity
			4.2.2.4 Feasibility
			4.2.2.5 Applicability
		4.2.3 A Framework Convention
			4.2.3.1 Clarity
			4.2.3.2 Feasibility
			4.2.3.3 Applicability
	Conclusion
	Notes
Chapter 5 Lessons for Artificial Intelligence from Other Global Risks
	5.1 Introduction
	5.2 Definitions
	5.3 Biotechnology
	5.4 Nuclear Weapons
	5.5 Global Warming
	5.6 Asteroid Collision
	5.7 Lessons Learned
	5.8 Conclusion
	Acknowledgements
	Notes
Chapter 6 Vulnerability, AI, and Power in a Global Context: From Being-at-Risk to Biopolitics in the COVID-19 Pandemic
	6.1 Introduction
	6.2 Existential-Epistemological Issues
	6.3 Political-Epistemological Issues
	6.4 Conclusion
	Notes
Chapter 7 Using Decision Theory and Value Alignment to Integrate Analogue and Digital AI
	7.1 Introduction
	7.2 Value Alignment: When One AI Agent Represents Multiple Human Principals
		7.2.1 Baum’s Taxonomy
		7.2.2 Paradox of the Democratic Imposition Problem
		7.2.3 Four-Stage Sequence Heuristic
		7.2.4 Procedural Legitimacy
		7.2.5 Risk Aversion Principle
		7.2.6 Mechanism Design
		7.2.7 Non-Deterministic Voting and Voting as a Game
		7.2.8 Condorcet, Social Choice, and Institutional Design
		7.2.9 Sociopathy and Sen’s Paradox
	7.3 The 2016 Republican Presidential Nomination Process: Case Study 1
		7.3.1 What’s the Matter with Plurality Voting?
		7.3.2 Condorcet’s Paradox
		7.3.3 The Paradox of Unanimous Consent and Majority Preference
		7.3.4 Approval Voting
	7.4 Two Global Politics Mini-Cases in Need of Future Work
		7.4.1 AI Safety: Case Study 2a
		7.4.2 Critch’s Theorem: Case Study 2b
	7.5 Conclusion
	Acknowledgements
	Notes
Chapter 8 Nomadic Artificial Intelligence and Royal Research Councils: Curiosity-Driven Research Against Imperatives Implying Imperialism
	8.1 Introductory Remarks on Scope, Method, and Theory: Why an Examination of Artificial Intelligence Research as an Arena of Nomads against the Royals
		8.1.1 A Note on Method: Theoretical and Empirical Tools
			8.1.1.1 First Lessons from Interviews with AI Specialists in the UK
			8.1.1.2 Nomadic and Royal Science: From Cybernetics to AI
	8.2 Nomads Surviving AI Winters: DARPA and the War Machines
		8.2.1 How to Become a Nomad by Applying for State Grants
		8.2.2 Using War to Make AI, Not War
	8.3 2013–2016: Research Councils Imperatives as Royal Science Imperialism
		8.3.1 The Imperialism of Eight Great Technologies: Upon Examining How Royal Science Integrates Nomads and How Nomads Are Willing to Partake in the Game
		8.3.2 Extending Royal Science to a Constellation of Mainstream Media and State Academics
		8.3.3 Lucasian Men of the State: Airy, Lighthill, Hawking
	8.4 Conclusion: Stationary Voyages and a Modest Proposal to Make Room for Curiosity-Driven Research
	Acknowledgements
	Notes
Chapter 9 Artificial Intelligence and Post-Capitalism: The Prospect and Challenges of AI-Automated Labour
	9.1 Introduction
	9.2 The Genealogy of AI: Between Angst and Failed Promises
		9.2.1 Fear of the Robot?
		9.2.2 A Future That Never Arrived?
		9.2.3 Imminent Human Labour Replacement?
	9.3 Value and Profit, AI and Capitalism
		9.3.1 Value and Labour
		9.3.2 Labour and Profit
	9.4 Technology, Labour, and the Falling Rate of Profit
	9.5 Value without Human Labour? AI and the Captivation of Human Abilities
	9.6 Conclusion: Paths towards Post-Capitalism
	Notes
Chapter 10 Artificial General Intelligence’s Beneficial Use within Capitalist Democracy: A Realistic Vision
	10.1 Introduction
	10.2 How Capital Reshapes Democracies into Plutocracies
	10.3 Capitalism vs Democracy
	10.4 Capital Cannot Abide Obstacles
	10.5 Safe AGI Might Not Be Enough to Avoid a Dystopian Future
	10.6 Conclusion
	Notes
Index