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Artificial intelligence (AI) transparency is crucial for healthcare trust. We developed an AI Facts Label, inspired by Drug Facts Labels, to clearly disclose AI use in products.

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Area of Science:

  • Healthcare Technology
  • Medical Informatics
  • Human-Computer Interaction

Background:

  • Artificial intelligence (AI) in healthcare raises transparency concerns, potentially eroding patient and clinician trust.
  • The invisible nature of AI in products can violate informed disclosure principles.
  • Existing transparency methods are insufficient for AI-assisted medical devices.

Purpose of the Study:

  • To develop a novel, patient-centric prototype AI transparency tool.
  • To address the ethical need for transparency in AI-assisted healthcare solutions.
  • To create a communication tool for understanding AI in medical devices.

Main Methods:

  • Designed an AI Facts Label prototype using the US Drug Facts Label as a model.
  • Populated the prototype with lay language for a hypothetical AI-assisted wearable device.
  • Utilized a defined, globally harmonizable graphic template for the label.

Main Results:

  • The AI Facts Label effectively communicates AI usage in lay language.
  • The prototype adheres to the ethical principle of transparency.
  • The tool is adaptable for various settings, including clinical and commercial.

Conclusions:

  • AI Facts Labels enhance understanding of AI in products for patients and healthcare workers.
  • This tool can foster trust and transparency in AI-assisted healthcare.
  • The concept has potential for global application in healthcare and consumer electronics.