What Can Artificial Intelligence Learn from Medicine? Generative Analogies and Reliable Machine Learning Systems

The paper examines how machine learning (ML) in medicine parallels clinical translation, framing this relationship as a generative analogy. It identifies epistemic and methodological warrants from clinical translation that are often invoked in ML discussions and analyzes how these warrants apply analogically to ML. The authors propose a new form of ML reliabilism, interpreting clinical translation warrants in reliabilist terms and showing how this perspective can inform ML systems distinct from existing reliabilist accounts in philosophy of AI.

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