Long-form thinking on artificial intelligence, scientific inquiry, and what it means to know.
AI can generate research possibilities faster than scientists can test them. If the bottleneck moves to validation, what should we optimize—and what should we count as progress?
Automating a research workflow is not the same as a scientific revolution. What would have to change for AI-mediated discovery to become a new paradigm?
Suppose an AI discovers a model that predicts and guides interventions but resists human explanation. What, exactly, has science gained?
When hypotheses and explanations become dramatically cheaper to produce, are we discovering more knowledge—or simply producing more of what looks like discovery?
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