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ML is useful for many things, but not for predicting scientific replicability

normaltech.ai · 1,068 words · saved by 1 readers

How the veneer of AI is used to legitimize awful ideas

Science rests on replicability and reproducibility. Without it, we can’t separate useful insights about the world from artifacts arising due to chance, and even fraud and malpractice by researchers. There are other costs too: one study estimated the cost of irreproducible research at $28 billion every single year, in the field of preclinical research alone. Earlier this year, a paper in the widely read PNAS journal raised the possibility of detecting non-replicable findings using machine learning (ML). The authors claimed ML could be used to predict which studies would replicate, and…

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