Underdetermination: Can Inference to the Best Explanation provide a way out?

Abstract

This thesis evaluates a specific argument within the debate between scientific realism and anti-realism. Specifically concerning a problem for scientific realism known as underdetermination, as put forward by Bas van Fraassen in The Scientific Image: the idea that empirical equivalence leads to inherent underdetermination of scientific theories, which therefore cannot be considered to be true. It is the aim of this thesis to defend the project of scientific realism against Van Fraassen’s argument by taking a dive into various conceptions of the idea of Inference to the Best Explanation, which is a type of inference that claims that from the best explanation of a phenomenon the truth can be inferred. Three versions of IBE as put forward by Gilbert Harman, Richard Boyd and Peter Lipton are considered. Harman believes the best explanation can be found using Bayesian probability theory. Boyd argues for the validity of Inference to the Best Explanation on a much more empirical basis. Finally, Lipton details an incredibly concise account of Inference to the Best Explanation, defining it as Inference to the ‘Loveliest’ Explanation and detailing the various criteria that go with it. This final conception of Inference to the Best Explanation along with its criteria shows that the problem of Underdetermination need not be a problem at all, since empirical equivalency of contradicting theories does not necessarily entail underdetermination.