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Responsibility Gaps and Black Box Healthcare AI: Shared Responsibilization as a Solution.

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Artificial intelligence (AI) in healthcare creates "responsibility gaps" when errors occur. Stakeholders must voluntarily assume moral responsibility to permit AI use in patient care.

Keywords:
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Area of Science:

  • Medical Ethics
  • Artificial Intelligence
  • Healthcare Administration

Background:

  • Increasing integration of sophisticated artificial intelligence (AI) into healthcare raises questions about accountability for AI actions.
  • Responsibility gaps emerge when AI errors occur in automated tasks, leaving a void in moral blame attribution.

Purpose of the Study:

  • To examine the generation of responsibility gaps by "black box" AI in healthcare.
  • To address the moral implications of unaddressed responsibility gaps.
  • To propose a solution for the ethical integration of AI in healthcare.

Main Methods:

  • Philosophical analysis of AI-induced responsibility gaps.
  • Ethical examination of accountability in healthcare AI.
  • Proposal of stakeholder "responsibilization" as a solution.

Main Results:

  • "Black box" healthcare AI demonstrably generates responsibility gaps.
  • Unaddressed gaps pose significant moral challenges in healthcare.
  • Voluntary assumption of responsibility by stakeholders is a viable solution.

Conclusions:

  • Stakeholders can "responsibilize" AI gaps, assuming moral responsibility.
  • This approach permits the use of "black box" healthcare AI.
  • Ethical frameworks must adapt to AI integration in critical sectors like healthcare.