Why AI can’t be trusted to write scientific reviews
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Bluesky
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Artificial-intelligence tools are being touted as a means to conduct rapid reviews of scientific literature. At the London-based publisher the Cochrane Collaboration, where I became editor-in-chief in March, we specialize in health-related systematic reviews: the highest-quality syntheses of all the available research. We are testing ways to use AI to increase our reviews’ efficiency and scale. But, in our experience, the current tools are far from ready for mainstream adoption, and the assumption that machines can replace humans on all methodological tasks is flawed.
The stakes are high. Systematic reviews and other types of evidence synthesis inform clinical practice, public-health guidance and policy decisions that affect entire populations. Errors could give false hope to patients or lead health systems to waste money on ineffective or unsafe interventions.
Will AI speed up literature reviews or derail them entirely?