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Computer knows best? The need for value-flexibility in medical AI
Journal of Medical Ethics
|November 24, 2018
Summary
Artificial intelligence (AI) in medicine offers opportunities and risks for shared decision-making. Value-flexible AI can support patient autonomy and clinician collaboration in treatment planning.
Area of Science:
- Bioethics
- Medical Informatics
- Artificial Intelligence in Healthcare
Background:
- Artificial intelligence (AI) is increasingly integrated into medical diagnosis and treatment decision-making.
- The ethical implications of AI in medical treatment, particularly concerning shared decision-making, require in-depth bioethical exploration.
- Existing AI systems may pose risks to patient autonomy if value judgments are embedded covertly.
Purpose of the Study:
- To analyze the relationship between AI treatment recommendation systems and the ethical ideal of shared decision-making.
- To examine the risks and opportunities presented by AI, using IBM's Watson for Oncology as a case study.
- To advocate for the development of value-flexible AI that supports patient-centered care.
Main Methods:
- Ethical analysis of AI systems in medical treatment decision-making.
- Case study examination of IBM's Watson for Oncology.
- Conceptual exploration of value judgments within AI algorithms.
Main Results:
- AI systems for treatment recommendations present both significant risks and opportunities for shared decision-making.
- Covert or fixed value judgments in AI risk a return to paternalistic medical care.
- Ethically designed AI can enhance shared decision-making by incorporating explicit value reflection and promoting patient autonomy.
Conclusions:
- Value-flexible AI is crucial for modern medical treatment, capable of responding to individual patient values and goals.
- AI can be a powerful tool to support clinicians in engaging in effective shared decision-making.
- Ethical design and implementation are paramount to leveraging AI for patient-centered care and autonomy.
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