Dissent is thought to play a valuable role in science, so that scientific communities ought to create opportunities for receiving critical feedback and take dissenting views seriously. There is concern, however, that some dissent does more harm than good. Dissent on climate change and evolutionary theory, for example, has confused the public, created doubt about existing consensus, derailed public policy, and forced scientists to devote resources to respond. Are there limits to the extent to which scientific communities have obligations to (...) seek and engage dissenting views? We consider the two main criteria that have been offered for what constitutes “normatively appropriate dissent” or the sort of dissent that ought to have the opportunity to be heard and taken seriously. Many have argued that dissenters must (1) engage in uptake of criticism against their own views and (2) share some standards for theory appraisal. We argue these criteria ultimately are unsuccessful. (shrink)

The idea that “simplicity is a sign of truth”, and the related “Occam’s razor” principle, stating that, all other things being equal, simpler models should be preferred to more complex ones, have been long discussed in philosophy and science. We explore these ideas in the context of supervised machine learning, namely the branch of artificial intelligence that studies algorithms which balance simplicity and accuracy in order to effectively learn about the features of the underlying domain. Focusing on statistical learning theory, (...) we show that situations exist for which a preference for simpler models provably slows down, instead of favoring, the supervised learning process. Our results shed new light on the relations between simplicity and truth approximation, which are briefly discussed in the context of both machine learning and the philosophy of science. (shrink)

This article argues that a successful answer to Hume's problem of induction can be developed from a sub-genre of philosophy of science known as formal learning theory. One of the central concepts of formal learning theory is logical reliability: roughly, a method is logically reliable when it is assured of eventually settling on the truth for every sequence of data that is possible given what we know. I show that the principle of induction (PI) is necessary and sufficient for logical (...) reliability in what I call simple enumerative induction. This answer to Hume's problem rests on interpreting PI as a normative claim justified by a non-empirical epistemic means-ends argument. In such an argument, a rule of inference is shown by mathematical or logical proof to promote a specified epistemic end. Since the proof concerning PI and logical reliability is not based on inductive reasoning, this argument avoids the circularity that Hume argued was inherent in any attempt to justify PI. (shrink)