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The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
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Mapping Ethical Guidelines for AI in Healthcare: A Global Perspective.

Ful Belin Korukoglu1, Razik Mohammed Rishan2, Zineb Elhamer3

  • 1Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.

Studies in Health Technology and Informatics
|May 17, 2025
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Summary
This summary is machine-generated.

Global AI ethics guidelines in healthcare are evolving, with regional variations in principles like fairness and privacy. Harmonizing these frameworks is crucial for responsible AI integration in medicine.

Keywords:
Artificial IntelligenceEthicsHealth Policy

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Area of Science:

  • Healthcare Ethics
  • Artificial Intelligence
  • Public Policy

Background:

  • Ethical concerns surrounding artificial intelligence (AI) in healthcare, including bias, privacy, and accountability, are prominent.
  • Global efforts to create AI ethical guidelines exist, but healthcare-specific frameworks are still developing and not widely implemented.
  • Existing guidelines show emerging common principles but lack consistent adoption in practice.

Purpose of the Study:

  • To systematically review and map global AI ethics guidelines specifically for the healthcare sector.
  • To identify and analyze regional variations in key ethical principles within healthcare AI.
  • To provide insights for harmonizing AI ethics in healthcare policy and practice.

Main Methods:

  • Systematic review of over 3,800 English-language policy documents related to AI ethics.
  • Selection of 140 documents based on explicit AI reference, normative ethical language, and institutional origin.
  • Visualization of findings on an interactive world map to illustrate regional differences.

Main Results:

  • Significant regional disparities were identified in the ethical principles advocated for AI in healthcare.
  • Commonly emerging principles include fairness, transparency, and patient privacy, though their emphasis varies geographically.
  • The study mapped the global landscape of AI ethics guidelines in healthcare.

Conclusions:

  • There is a pressing need to harmonize AI ethics guidelines within the global healthcare landscape.
  • The identified regional variations highlight challenges in establishing universally accepted AI ethical standards in medicine.
  • Actionable insights are provided for policymakers, researchers, and stakeholders to foster responsible AI adoption in healthcare.