Collective intelligence in clinical medicine: what works, what fails, and how collaboration with AI really helps - 05/06/26
, Bahador Bahrami 2, 5Abstract |
As clinical information multiplies and patient cases become more intricate, even the most experienced doctors face the limits of solitary expertise. Collective intelligence—the idea that groups of people, and increasingly people together with AI, can make better decisions than individuals—offers a promising way to meet this challenge.
We define collective intelligence in medicine and explain why healthcare is a uniquely important domain for its study, given the combination of high complexity and high stakes. We then distinguish different dimensions of collective medical decision-making, and review evidence for the benefits and limits of simple aggregation of judgments (“the wisdom of crowds”) and interactive decision-making through deliberation. Finally, we highlight open questions and emerging directions, with particular focus on the expanding role of human–AI collaboration. We argue that the future of collective intelligence in medicine lies not only in classic hybrid intelligence—where individual human judgement can be augmented by algorithmic decisions—but in truly collaborative intelligence, where deliberation across multiple hybrid teams remain central to managing uncertainty.
Le texte complet de cet article est disponible en PDF.Keyword s : Collective intelligence, Health, AI, Hybrid Intelligence, Joint decision, Medical decisions
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| Funding: OD is funded by the Volkswagen Foundation (Co-Sense), and by the European Union under Grant Agreement 101070918 (EMERGE) BB is also funded by EMERGE and an ENS Lyon Fellowship |
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| CRediT Author Statement |
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| Ophelia Deroy (OD): Conceptualization; Methodology; Writing – original draft; Writing – review & editing; Supervision; Project administration. |
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| Bahador Bahrami (BB): Conceptualization; Methodology; Writing – review & editing; Visualization. |
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| Competing interests |
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| The author declares that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article. |
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