You Don't Need a Mechanistic Model to Predict Interventional Outcomes
BlancheMinerva · x · 2026-08-13
In a discussion about how AI agents conduct scientific discovery, a developer proposed a counterintuitive view: predicting the outcome of interventions or building good theories does not require a mechanistic model.
To substantiate this, he provided historical examples: vaccines predate germ theory, the second law of thermodynamics was identified by someone with the wrong model of heat, and Quantum Mechanics doesn’t even have a standard mechanistic model today. This challenges the traditional assumption that establishing a mechanistic model through costly experimentation is the only way to answer interventional "what if?" questions, offering a strong defense for data-driven, AI-assisted scientific discovery.
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