Insights on AI, medical research, and the future of scientific discovery.
Grant reviewers read hundreds of applications. The ones that land are not the most ambitious ones. They are the ones that answer the right question in the right way.
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The replication crisis is not really a crisis of fraud. It is a crisis of incomplete evidence at the design stage, and that is a problem we can actually fix.
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We have had the same conversation more times than we can count. A researcher tried a tool, stopped using it within weeks, and can explain exactly why. The explanations are remarkably consistent.
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Accuracy is necessary. It is not sufficient. The most dangerous AI systems in medicine are not the ones that are wrong, they are the ones that are wrong with confidence.
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The distance between a stack of relevant papers and a finished protocol is longer than it looks. This is about what happens in that space.
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The AI drug discovery revolution arrived later than expected and works differently than advertised. The tools that are actually delivering value are less dramatic and more useful.
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PICO gets taught early and used constantly. It also gets misunderstood in ways that produce well-formatted questions that are nearly impossible to answer.
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Ten hours a week is a number we arrived at honestly, not by working backwards from a marketing claim. Here is where the time actually goes
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PubMed is extraordinary. It is also a retrieval tool, not a thinking tool. The difference matters more than it used to.
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AI is not automating systematic reviews. It is handling the parts that slow researchers down and the difference matters.
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We interviewed dozens of researchers before building NousLab. Almost all of them described the same problem, and the same quiet resignation about it.
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The hard part is not understanding what a hypothesis is. It is knowing whether the one you have is any good, and that depends almost entirely on the evidence you have not yet found.
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