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Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health.

Leon Rozenblit1, Amy Price2, Anthony Solomonides3

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Developing tailored governance for consumer health AI is crucial. A multi-stakeholder approach, centered on patient needs and transparency, ensures AI is safe, effective, and trustworthy.

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • AI Governance

Background:

  • Rapid advancement of AI in healthcare presents both opportunities and risks.
  • Current AI governance lacks domain-specific recommendations for consumer health.
  • Generic guidelines may lead to unintended consequences in diverse healthcare contexts.

Purpose of the Study:

  • To explore pragmatic, multi-stakeholder governance approaches for consumer-facing health AI.
  • To establish a tailored governance framework for consumer health AI.
  • To identify key constraints and desirable characteristics for health AI governance models.

Main Methods:

  • A 4-month multidisciplinary expert consensus process involving nearly 200 participants.
  • Synthesis of insights to guide the development of proposed governance models.
  • Focus on collaborative deliberation to inform practical solutions.

Main Results:

  • A consensus emphasizes limiting scope and incorporating multi-stakeholder, patient-centered perspectives.
  • Desirable governance characteristics include adaptability, patient empowerment, and transparency.
  • A recommended pathway involves forming a Health AI Consumer Consortium (HAIC2) to align incentives.

Conclusions:

  • Core themes of consumer voice, transparency, and balanced oversight are globally relevant.
  • Proposed principles for multi-stakeholder alignment and patient empowerment can ensure AI is safe, effective, equitable, and trustworthy (SEET).
  • This framework offers a productive approach for governing AI in consumer health worldwide.