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Artificial Intelligence (AI) in healthcare requires transparency for quality and trust. Achieving this requires clarity on what information to share and how, especially for AI medical devices.

Keywords:
AI-based medical devicesSaMDartificial intelligenceexplainabilityhealthcare regulationlabels and instructionsmachine learningtransparency

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Area of Science:

  • Health Informatics
  • Artificial Intelligence
  • Medical Device Regulation

Background:

  • Artificial Intelligence (AI) is rapidly advancing in healthcare, raising concerns about transparency.
  • Transparency is crucial for ensuring the quality, safety, and trustworthiness of AI technologies in medical applications.
  • The meaning of AI transparency in healthcare is often ambiguous and requires clear definition.

Purpose of the Study:

  • To examine the concept of AI transparency in healthcare.
  • To differentiate AI transparency from related concepts like AI explainability.
  • To explore challenges in enhancing transparency for users of AI-based medical devices.

Main Methods:

  • Literature review of AI transparency in healthcare.
  • Analysis of policy documents to identify emerging consensus on AI transparency.
  • Stakeholder analysis of rationales for AI transparency.

Main Results:

  • AI transparency in healthcare is essential but lacks a universally agreed-upon definition.
  • Emerging consensus distinguishes AI transparency from AI explainability.
  • Key challenges exist in providing appropriate information to users of AI medical devices.

Conclusions:

  • While AI transparency in medical devices is recognized as vital, a significant hurdle is the lack of clarity.
  • Defining the appropriate level of information for different contexts and stakeholders is critical.
  • Effective methods for delivering information to achieve transparency goals are yet to be fully established.