Ravit Dotan

_Current Controversies in Philosophy of Science_ asks twelve philosophers to debate six questions that are driving contemporary work in this area of philosophy. But each question also leads readers back to more general issues and shows how these general issues play out in contemporary debates. The result is a book that’s perfect for the advanced student, building up her knowledge of the foundations of the field while also engaging with its cutting-edge questions. Preliminary descriptions of each chapter, annotated bibliographies for each controversy, study questions, and a supplemental guide to further controversies in philosophy of science help provide clearer and richer snapshots of active controversies for all readers.

I use a theorem from machine learning, called the “No Free Lunch” theorem to support the claim that non-epistemic values are essential to theory choice. I argue that NFL entails that predictive accuracy is insufficient to favor a given theory over others, and that NFL challenges our ability to give a purely epistemic justification for using other traditional epistemic virtues in theory choice. In addition, I argue that the natural way to overcome NFL’s challenge is to use non-epistemic values. If my argument holds, non-epistemic values are entangled in theory choice regardless of human limitations and regardless of the subject matter. Thereby, my argument overcomes objections to the main lines of argument revealing the role of values in theory choice. At the end of the paper, I argue that, contrary to common conception, the epistemic challenge arising from NFL is distinct from Hume’s problem of induction and other forms of underdetermination.