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Artificial Intelligence, Patient Autonomy and Informed Consent

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Publisher:
 2024

Summary

Artificial intelligence (AI) is rapidly being implemented in the healthcare sphere, threatening the ability of patients to make judgments tailored to their personal circumstances and beliefs. This book is concerned with the ability of two legal systems, those of the UK and the U.S., to meet the resulting challenges posed to patient autonomy. It deploys a forward-looking analysis to identify the unique problems raised by clinical AI and to anticipate the responses that are offered by the common law’s doctrine of informed consent. This assessment culminates in a concrete proposal for the regulation of medical AI and an affirmation of the law’s fundamental role in societies’ adaptation to innovative technologies.

Keywords

Bibliographic data

Copyright year
2024
ISBN-Print
978-3-7560-2239-7
ISBN-Online
978-3-7489-4891-9
Publisher
Nomos, Baden-Baden
Series
Studien aus dem Max-Planck-Institut für Sozialrecht und Sozialpolitik
Volume
81
Language
English
Pages
433
Product type
Book Titles

Table of contents

ChapterPages
  1. Titelei/Inhaltsverzeichnis 1 - 24 Download chapter (PDF)
  2. Download chapter (PDF)
    1. I. Problem statement
      1. A. Comparative method
      2. B. Scope of inquiry
        1. 1. Instrumentality of law
        2. 2. Technological dynamism and legal inertia
        3. 3. Desirability of non-legal regulation
        4. 4. Summation
      4. D. Research question
    3. III. State of the art
    4. IV. Outlook and structure
  3. Download chapter (PDF)
        1. A. Definition
        2. B. Machine learning: the underlying technology
          1. 1. Sub-symbolic functioning
          2. 2. The training process
          3. 3. Data and performance evaluation
          4. 4. Summary
        1. A. Devices complementing human expertise
        2. B. Devices (partially) replacing pre-existing cognitive capabilities
        3. C. Devices determining dimensions of clinical decision-making
        1. A. Prevalent types of opacity
          1. 1. Explainability
          2. 2. Interpretability
          3. 3. Evaluation
        1. A. Choices in the use of ML devices
        2. B. User knowledge of ML devices
        3. C. ML influence
      5. V. Conclusion
        1. A. Decisional autonomy
        2. B. Practical autonomy
        3. C. Summation
        1. A. The need to form true beliefs about AI’s goal-directed action
        2. B. Theoretical rationality and changes in human-AI expertise
          1. 1. General risk characteristics of AI
            1. i. AI nudging
            2. ii. Impermissible manipulation
      3. III. Conclusion
  4. Download chapter (PDF)
      1. I. Scope
      2. II. Function
        1. A. Rationality
        2. B. Individual reflection
        3. C. Positive and negative freedom
      4. IV. Limitations
      5. V. Conclusion
        1. A. Jurisdictional scope
        2. B. Conceptual scope
      2. II. Function
        1. A. Rationality
        2. B. Individual reflection
        3. C. Positive and negative freedom
      4. IV. Limitations
      5. V. Conclusion
  5. Download chapter (PDF)
        1. A. Limitations flowing from the battery doctrine
          1. 1. Nature of the procedure
          2. 2. Identity of the professional
          3. 3. Non-therapeutic motivations
        3. C. Summation
          1. 1. Personal injury
            1. i. The nature of the award
            2. ii. The autonomy interest
          3. 3. Summation
          1. 1. Medical professionals
          2. 2. Healthcare institutions
          3. 3. Summation
            1. i. The meaning of reasonable disclosure
            2. ii. The operationalisation of reasonable disclosure
            3. iii. Summation
            1. i. Specific risks
            2. ii. Risk-relevant status
          3. 3. Alterations of expertise
            1. i. Understanding choices
            2. ii. AI’s lesser influence on the pursuit of objectives
          5. 5. Summation
        4. D. Causation
        5. E. Awarding damages
      3. III. The UK General Data Protection Regulation
      4. IV. Conclusion
          1. 1. Contact
          2. 2. Unlawful nature
          3. 3. Intention
          4. 4. Summation
            1. i. Physical nature of the procedure
            2. ii. Identity of the professional
            3. iii. Non-therapeutic motivations
          2. 2. Conditional consent
        3. C. Summation
          1. 1. Personal injury
          2. 2. Autonomy interest
          3. 3. Emotional distress
          4. 4. Summation
          1. 1. Medical professionals
          2. 2. Healthcare institutions
          3. 3. Summation
            1. i. The meaning of reasonable disclosure
            2. ii. The operationalisation of reasonable disclosure
            3. iii. Summation
            1. i. Specific risks
            2. ii. Risk-relevant status
          3. 3. Alterations to expertise
            1. i. Understanding choices
            2. ii. AI’s lesser influence on the pursuit of objectives
          5. 5. Summation
        4. D. Causation
        5. E. Awarding damages
      3. III. Conclusion
            1. i. Risk-relevant characteristics
            2. ii. Goal-directed action by AI
            3. iii. Human-AI expertise
            4. iv. Informational manipulation
          2. 2. Non-informational requirements
          1. 1. Informational requirements for valid consent
          2. 2. Non-informational requirements
        3. C. Conclusion
          1. 1. United Kingdom
          2. 2. California
          3. 3. Rationale
        2. B. An informed consent statute for AI
        1. A. Understated challenges of non-legal regulation
        2. B. The significance of law’s resistance to instrumentalisation
        3. C. Law’s nuanced normative dynamism
      4. IV. Conclusion
  6. Download chapter (PDF)
    1. I. Literature
    2. II. Material

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