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Artificial superintelligence alignment in healthcare.

Daiju Ueda1,2, Shannon L Walston3, Ryo Kurokawa4

  • 1Department of Artificial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan. ai.labo.ocu@gmail.com.

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|November 14, 2025
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Summary
This summary is machine-generated.

Artificial Superintelligence (ASI) in healthcare offers great promise but poses risks if not aligned with human values. Ensuring ASI alignment is crucial for patient safety and the future of medicine.

Keywords:
AlignmentArtificial intelligenceArtificial superintelligenceDeep learningHealthcarePatient safety

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence Ethics
  • Health Policy

Background:

  • Artificial Superintelligence (ASI) presents transformative potential in healthcare, including diagnostics, treatment, and population health.
  • However, misaligned ASI systems risk patient harm and systemic failures by optimizing for incorrect objectives.
  • Real-world examples in radiology and clinical decision-making highlight issues like bias and inappropriate proxy measures.

Purpose of the Study:

  • To examine the theoretical foundations of ASI and the alignment problem within healthcare.
  • To analyze key challenges in achieving ASI alignment in medical contexts.
  • To discuss technical and normative strategies for ensuring safe and effective ASI integration in healthcare.

Main Methods:

  • Review of theoretical ASI foundations and alignment problem.
  • Analysis of real-world AI challenges in healthcare (radiology, clinical decision-making).
  • Discussion of technical alignment strategies (e.g., RLHF, interpretability) and normative solutions (e.g., ethical frameworks, governance).

Main Results:

  • Misaligned AI systems can lead to patient harm through biases, generalization failures, and optimization for wrong objectives.
  • Key challenges include objective complexity, data bias, ethical integration (compassion, autonomy), and policy/regulatory hurdles.
  • Both technical AI research and fundamental medical ethics are essential for successful ASI alignment.

Conclusions:

  • Successful ASI alignment in healthcare demands a synergy between advanced AI research and core medical ethics.
  • Proper alignment can unlock unprecedented health improvements and medical breakthroughs.
  • Misalignment poses significant risks, potentially undermining medicine's core purpose and public trust, with high ethical and technological stakes.