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Governing AI-Driven Health Research: Are IRBs Up to the Task?
Phoebe Friesen1, Rachel Douglas-Jones2, Mason Marks3
1Assistant professor in the Biomedical Ethics Unit and the Department of Social Studies of Medicine at McGill University.
Ethics & Human Research
|March 8, 2021
Summary
Institutional Review Boards (IRBs) are being considered for oversight of health research using artificial intelligence (AI). This study examines IRB challenges and proposes adaptations for effective AI ethics governance in health research.
Area of Science:
- Health research ethics
- Artificial intelligence in healthcare
- Governance of AI
Background:
- Growing demand for oversight mechanisms in AI-driven health research.
- Institutional Review Boards (IRBs) are a traditional governance model.
- Existing IRB structures face challenges with AI integration.
Purpose of the Study:
- To examine the suitability of the IRB model for AI health research oversight.
- To analyze current challenges IRBs encounter with AI research.
- To propose recommendations for adapting IRBs for AI ethics governance.
Main Methods:
- Review of IRB model origins and functions.
- Analysis of challenges in academic and industry settings.
- Development of recommendations for IRB adaptation.
Main Results:
- IRBs face significant challenges in overseeing AI health research.
- Adaptations are necessary to address the unique aspects of AI.
- Current models may not be fully equipped for AI governance.
Conclusions:
- IRBs can be adapted to provide effective oversight for AI health research.
- Specific recommendations are needed to enhance IRB capacity for AI.
- Proactive adaptation is crucial for responsible AI innovation in health.
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