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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Celia Cintas, Curtis P Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A González, Folkert W Asselbergs, Fred Prior, Gabriel P Krestin, Gary Collins, Geletaw S Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Horst Joachim Mayer, Hugo JWL Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Isabell Tributsch, Islem Rekik, James Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W Gichoya, Julia A Schnabel, Kaisar Kushibar, Katrine Riklund, Kensaku Mori, Kostas Marias, Lameck M Amugongo, Lauren A Fromont, Lena Maier-Hein, Leonor Cerdá Alberich, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Luis Martí-Bonmatí, M Jorge Cardoso, Maciej Bobowicz, Mahsa Shabani, Manolis Tsiknakis, Maria A Zuluaga, Maria Bielikova, Marie-Christine Fritzsche, Marina Camacho, Marius George Linguraru, Markus Wenzel, Marleen De Bruijne, Martin G Tolsgaard, Marzyeh Ghassemi, Md Ashrafuzzaman, Melanie Goisauf, Mohammad Yaqub, Mónica Cano Abadía, Mukhtar M E Mahmoud, Mustafa Elattar, Nicola Rieke, Nikolaos Papanikolaou, Noussair Lazrak, Oliver Díaz, Olivier Salvado, Oriol Pujol, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Richard Osuala, Rose Nakasi, S Kevin Zhou, Sandy Napel, Sara Colantonio, Shadi Albarqouni, Smriti Joshi, Stacy Carter, Stefan Klein, Steffen E Petersen, Susanna Aussó, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe E M Mutsvangwa, Wendy A Rogers, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino, Zohaib Salahuddin, Martijn P A Starmans
August 11, 2023
British medical journal
827 citations
44 influential
Key Takeaways
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International consensus matters: The FUTURE-AI framework represents agreement among 118 experts from 51 countries across multiple disciplines (AI scientists, clinicians, ethicists, and social scientists), suggesting these recommendations reflect broad global perspectives on responsible AI in healthcare rather than narrow technical viewpoints.
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Trust is the barrier to real-world use: Despite AI advances in medicine, actual clinical adoption remains limited. The guideline identifies that patients, clinicians, hospitals, and regulators need to trust and accept AI tools before they're deployed—meaning technical performance alone isn't enough for healthcare AI to succeed.
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Six core principles guide trustworthy AI: The framework establishes Fairness, Universality, Traceability, Usability, Robustness, and Explainability as foundational requirements. This means responsible medical AI should work fairly across different populations, be traceable in its decisions, be usable by clinicians, and be able to explain its reasoning—not just be accurate.
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28 practical best practices cover the full lifecycle: Rather than abstract principles, the guideline provides 28 specific recommendations addressing technical, clinical, legal, and ethical dimensions across the entire AI development and deployment process—from initial design through real-world implementation.
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Multiple dimensions of risk require attention: The framework acknowledges that medical AI involves technical risks (accuracy, robustness), clinical risks (patient safety), ethical risks (fairness, bias), and legal risks—requiring coordinated oversight beyond just computer scientists.