Researchers in the EU-OperA project have published the paper "The Legal and Ethical Framework for Artificial Intelligence in Gastrointestinal Endoscopy: A World Endoscopy Organization International Consensus Statement" in Annals of Internal Medicine. The World Endoscopy Organization–backed Delphi study led by the OperA project members convened 14 international experts to identify legal and ethical priorities for artificial intelligence (AI) in gastrointestinal (GI) endoscopy. The consensus produced 10 key statements across three domains — data governance, medicolegal implications, and equity/bias — aimed at smoothing the path from validation to safe, equitable clinical use.
First author is dr. Omer F. Ahmad at the University College London. Ahmad is leading the ethical and legal concerns work package of the OperA project. Professors Yuichi Mori and Michael Bretthauer at the Clinical Effectiveness Research Group, at the University of Oslo, co-authored the paper in collaboration with researchers from Europe, Asia, and the USA.
A short summary of the paper
- Purpose: International Delphi consensus identifying legal and ethical priorities for AI in gastrointestinal (GI) endoscopy, produced as part of the OperA project to support safe clinical integration.
- Leadership and authorship: Led by members of the OperA project with an international steering committee and 14 Delphi panel experts listed in the paper.
- Method: Two‑round Delphi process—round 1 generated candidate issues and round 2 rated and refined them to reach consensus.
- Main outcome: Consensus on 10 prioritized statements organized into three domains: data governance; medicolegal implications (liability, standards of care); and equity/bias.
- Key data‑governance recommendations: Require informed consent where applicable, strict adherence to data protection rules, clear policies on data ownership, and transparent logging/reporting of algorithm changes and performance.
- Medicolegal focus: Emphasizes clinician responsibility to use AI within reasonable medical practice and per manufacturer guidance, and highlights emerging liability risks for device makers and clinicians.
- Equity and bias: Calls for attention to algorithmic fairness, dataset quality, and measures to avoid widening disparities in care.
- Practical value: Provides a concise, clinician‑focused roadmap to guide developers, hospitals, regulators, and clinicians toward trustworthy, transparent, and equitable AI adoption in endoscopy.