Artificial Intelligence, Patient Autonomy and Informed Consent

Dr. Christian Günther

doi:10.5771/9783748948919

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.

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Bibliographic data

Edition: 1/2024
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: Monograph

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

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