Preface

Section 1. Why This Book Matters

• The rise of AI and robotic systems in healthcare
• The urgency of legal adaptation
• Who should read this book

Section 2. How to Use This Book

• Structure and organization
• Key features: case studies, checklists, templates
• Online resources and updates

Chapter 1. The Collapse of Traditional Malpractice

Section 1. Evolution from Individual Negligence to Systemic Failure

• Shift from single-actor fault to distributed liability
• Complexity of AI-driven decision chains
• Strain on negligence doctrines

Section 2. Duty of Care in Human–AI Collaboration

• Human-in-the-loop (supervisor liability)
• Human-on-the-loop (monitor liability)
• Human-out-of-the-loop (systems liability)

Section 3. Standard of Care Evolution

• When AI becomes the baseline standard
• Professional guidelines and automation
• Conflicts in defining reasonable care

Section 4. Foreseeability Paradox in Machine Learning

• Predictability vs algorithmic opacity
• Failure modes beyond human foresight
• Legal consequences of unforeseeable harm

Section 5. Case Study: Diagnostic AI False Negative

• Melanoma misdiagnosis in darker skin tones
• Delay in treatment and litigation outcomes
• Lessons for liability allocation

Chapter 2. Product Liability Meets Healthcare

Section 1. Algorithmic and Design Defects

• Model architecture flaws
• Training data bias and incompleteness
• Inadequate safety testing

Section 2. Deployment and Integration Defects

• Software bugs at hospital deployment
• Sensor and interoperability failures
• System validation gaps

Section 3. Failure-to-Warn and Risk Communication

• Evolution from package inserts to live warnings
• Dynamic risks and ongoing disclosure duties
• Patient vs clinician risk communication

Section 4. The Learned Intermediary Doctrine under Pressure

• Traditional shielding of manufacturers
• Breakdown with autonomous AI
• Calls for reform

Section 5. Data as a Product

• Treating datasets as defective products
• Liability for corrupted or biased data
• Case law analogues

Section 6. Case Study: Surgical Robot Malfunction

• Unexpected movement during cardiac procedure
• Allocation of blame between hospital and vendor
• Implications for design controls

Chapter 3. Evidence, Causation, and the Black Box Problem

Section 1. Admissibility of AI Evidence

• Daubert and Frye standards
• Proprietary code and discovery disputes
• Admissibility of statistical outputs

Section 2. Explainability vs Technical Limits

• Black-box opacity
• Legal requirements for interpretability
• Technical impossibility defense

Section 3. Statistical vs Traditional Causation

• Probabilistic harm attribution
• Causation in multi-patient datasets
• Courts grappling with probabilities

Section 4. Chain of Causation in Multi-Agent Systems

• Shared fault between humans and machines
• Proximate cause analysis
• Joint and several liability issues

Section 5. Audit Trails and Documentation

• Model cards and logs
• Evidence preservation for litigation
• Designing litigation-ready systems

Section 6. Case Study: Dosing Algorithm Error

• Software update introduces error
• Multiple contributing factors
• Settlement and accountability

Chapter 4. Risk Allocation Through Contract and Insurance

Section 1. Hospital–Vendor Agreements

• Liability caps and disclaimers
• Indemnification structures
• Negotiation leverage in high-tech procurement

Section 2. Insurance Coverage Gaps

• Malpractice vs product liability
• Cyber policies and AI incidents
• Emerging insurance products

Section 3. Warranty Disclaimers vs Non-Disclaimable Duties

• Attempts to contract away liability
• Statutory safety duties
• Court treatment of disclaimers

Section 4. Clinical Trial Agreements

• AI pilots and shared risk
• Data ownership and obligations
• FDA investigational frameworks

Section 5. Case Study: Hospital–Vendor Dispute

• Robotic surgery incident
• Contractual loopholes
• Precedent for future agreements

Chapter 5. United States Framework

Section 1. Federal Preemption and FDA Oversight

• Device approval vs continuous software updates
• SaMD regulation
• Post-market surveillance

Section 2. State Tort Law Variations

• Emerging AI-specific statutes
• Divergent state precedents
• Common law evolution

Section 3. Hospital Corporate Negligence

• Credentialing of AI tools
• Oversight and monitoring duties
• Institutional liability trends

Section 4. Privacy and Security Intersections

• HIPAA implications for AI
• State breach laws
• Data misuse in AI contexts

Section 5. Professional Licensing and Scope of Practice

• Physician liability with AI tools
• Expansion of scope-of-practice disputes
• Disciplinary trends

Section 6. State Spotlight: California

• Early AI liability initiatives
• Legislative experiments
• Lessons for other jurisdictions

Chapter 6. European Union Approach

Section 1. AI Act and Medical Device Regulation

• High-risk categorization
• Integration with MDR
• Provider obligations

Section 2. Responsibility Matrix

• Provider, deployer, manufacturer roles
• Shared responsibility models
• EU case law trends

Section 3. High-Risk AI System Obligations

• Documentation requirements
• Risk management processes
• Transparency mandates

Section 4. GDPR Implications

• AI training data restrictions
• Patient data rights
• Enforcement examples

Section 5. Country Spotlight: Germany

• Hospital liability for AI
• National court perspectives
• Comparative insights

Chapter 7. United Kingdom and Commonwealth

Section 1. UK Risk-Based Regulatory Approach

• MHRA frameworks
• AI safety standards
• Post-Brexit divergence

Section 2. Professional Standards Evolution

• GMC and NMC guidance
• Clinician duties with AI
• Liability for guideline breaches

Section 3. Clinical Governance Requirements

• Hospital oversight frameworks
• Audit and compliance duties
• NHS experience with AI

Section 4. New Zealand: No-Fault ACC System

• Unique compensation structure
• Litigation strategy implications
• Regulatory focus instead of torts

Section 5. Country Spotlight: Australia

• TGA AI pathway
• Hospital obligations
• Insurance perspectives

Chapter 8. Emerging Global Trends

Section 1. Convergence and Divergence

• Aligning vs diverging approaches
• Global compliance challenges
• Risk of fragmentation

Section 2. Cross-Border Telemedicine

• Jurisdiction shopping
• Conflict of laws
• Enforcement difficulties

Section 3. International Standards

• ISO and IEC developments
• Soft law influence
• Adoption by regulators

Section 4. Export Controls and Technology Transfer

• AI export restrictions
• Healthcare technology transfer
• Liability in multinational contexts