Liabilities and Modern Artificial Intelligence - Wallingford, Estelle

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Résumé :
This book addresses how private law liability should be assigned in contexts where modern forms of AI are deployed. This book explores legal approaches to AI, how AI should be legally characterised, and proposes an overarching theoretical liability framework termed the Tri-Phase AI Liability Model....

Sommaire:

List of Figures
List of Tables
Table of Cases
Table of Legislation
Table of Statutory Instruments
Acknowledgements

Introduction
1. Artificial Intelligence: A Legal Problem
2. What Is Modern AI?
3. Regulation versus Liability
4. Overview of Chapters
5. A Need for Flexibility

Part I
Chapter 1-Understanding the AI Legal Landscape
1. Evaluating Legal Approaches to Artificial Intelligence
2. Regulatory Responses to Artificial Intelligence
3. Evaluation of Proposed Legal Responses to a Deployed AI
4. The Need for an Overarching Liability Framework

Part II
Chapter 2-Reevaluating Legal Personality for AI
1. AI as a Legal Person?
2. Legal Personhood Approaches to AI
3. Socio-Legal Background of Legal Personhood
4. Elements of Legal Personhood: Legal Rights and Duties
5. Elements of Legal Personhood: Capacity
6. Viewing Legal Personality Hierarchically
7. Legal Personhood: An Adaptable Concept
Chapter 3-AI as a Legal Agent
1. The AI Legal Agent
2. Theories of Agency and Their Applicability to AI
3. Key Elements of a Principal-Agent Relationship
4. Problems with Modern AI as a Legal Agent
5. Agency and Situational Utility
Chapter 4-AI as Property
1. Proprietary Nature of AI
2. Can AI Be Construed as Non-IP Property?
3. AI as Intellectual Property
4. Other Important Considerations
5. Characterising AI as Property: Sufficient?
6. Artificial Intelligence: More than Merely Property
Chapter 5-A New Legal Characterisation
1. Artificial Intelligence: What Should It Be Legally?
2. The Unique Characteristics of AI
3. A Hierarchical Model of Legal Personhood
4. Incorporating Agency and Property into the Hierarchical Legal Personality Model
5. Resolving Characterising AI and Its Importance for Liability

Part III
Chapter 6-Adapting Causation Principles for AI
1. Causation: A Threshold Issue
2. Legal Causation and AI: Theoretical Approaches
3. Evaluating Proposed Causation Solutions in an AI Context
4. Additional Problems with Causation Approaches in an AI Context
5. Alternative Solution: Need for a Situational Approach to Causation
6. The Need for a Situational Approach to Causation for AI
Chapter 7-Narrowing Liability
1. Other Threshold Issues
2. Context in which AI Is Deployed, Scope of Actions and Multiple AI Systems
3. Question of Who Could Be Liable
4. Considering AI in Context: Viewing AI Situationally Rather than through a Fixed Approach
Chapter 8-The Tri-Phase AI Liability Model
1. A Liability Response for AI
2. A New Proposal: Alternative Liability Framework
3. Phase 1: Identification of Maximum Potential Legal Personhood Status
4. Phase 2: Liability Threshold Issues
5. Phase 3: Drawing Together Phases 1 and 2 - Situational Approach to Deciding Liability for AI Systems Operating at Different Levels of Ability
6. Evaluation of the Tri-Phase AI Liability Model
7. Reconceiving Liability as a Flexible Paradigm

Part IV
Chapter 9-Model in Application
1. Theory Informing Practice
2. The Tri-Phase AI Liability Model Relative to Regulatory Responses
3. Considerations for Stakeholders
4. Beyond Fixed Approaches: The Need for a Situational Response to AI

Conclusion
Bibliography