Inference to the Best Explanation by P. Lipton [Book Review]

2005

The first edition of Peter Lipton's Inference to the Best Explanation, which appeared in 1991, is a modern classic in the philosophy of science. Yet in the second edition of the book, Lipton proves that even a classic can be improved. Not only does Lipton elaborate and expand on the themes covered in the first edition, but he also adds a new chapter on Bayesianism. In particular, he attempts a reconciliation between the Bayesian approach and that offered by Inference to the Best Explanation (IBE).

Synthese, 1994

This paper discusses the nature and the status of inference to the best explanation (IBE). We (1) outline the foundational role given IBE by its defenders and the arguments of critics who deny it any place at all; (2) argue that, on the two main conceptions of explanation, IBE cannot be a foundational inference rule; (3) sketch an account of IBE that makes it contextual and dependent on substantive empirical assumptions, much as simplicity seems to be; (4) show how that account avoids the critics' complaints and leaves IBE an important role; and (5) sketch how our account can clarify debates over IBE in arguments for scientific realism.

How do we reconcile the claim of Bayesianism to be a correct normative theory of scientific reasoning with the explanationists' claim that Inference to the Best Explanation provides a correct description of our inferential practices? I first develop Peter Lipton's approach to compatibilism and then argue that three challenges remain, focusing in particular on the idea that IBE can lead to knowledge. Answering those challenges requires renouncing standard Bayesianism's commitment to personalism, while also going beyond objective Bayesianism regarding the constraints on good priors. The result is a non-standard, super-objective Bayesianism that identifies probabilities with evaluations of plausibil-ity in the light of the evidence, conforming to Williamson's account of evidential probability.

Philosophical Books, 1995

INFERENCE, EXPLANATION, AND OTHER FRUSTRATIONS ESSAYS IN THE PHILOSOPHY OF SCIENCE Edited by John Earman These provocative essays by leading philosophers of science exemplify and illuminate the contemporary uncertainty—and the renewed excitement ...

Existence and Explanation, 1991

Theoria, 2008

Bayesianism and Inference to the best explanation (IBE) are two different models of inference. Recently there has been some debate about the possibility of "bayesianizing" IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes's Theorem. Then I distinguish two different interpretations of prior probabilities: "IBE-Bayesianism" (IBE-Bay) and "frequentist-Bayesianism" (Freq-Bay). After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i) endorses a role for explanatory value in the assessment of scientific hypotheses; (ii) avoids a purely subjectivist reading of prior probabilities; and (iii) fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.

Analysis, 2013

In the world of philosophy of science, the dominant theory of confirmation is Bayesian. In the wider philosophical world, the idea of inference to the best explanation exerts a considerable influence. Here we place the two worlds in collision, using Bayesian confirmation theory to argue that explanatoriness is evidentially irrelevant.

Social Science Research Network, 2002

I shall endeavor to show that every physical theory since Newton explains without drawing attention to causes-that, in other words, physical theories as physical theories aspire to explain under an ideal quite distinct from that of causal explanation. If I am right, then even if sometimes the explanations achieved by a physical theory are not in violation of the standard of causal explanation, this is purely an accident. For physical theories, as I will show, do not, as such, aim at accommodating the goals or aspirations of causal explanation. This will serve as the founding insight for a new theory of explanation, which will itself serve as the cornerstone of a new theory of scientific method.

Topoi, 1990

Causation and explanation are obviously connected. A sterling task for a philosopher of science is to lay bare the connection. The dominating tradition has been that an explanation is a form of inferential relation between the sentences included in the explanans and the explanandum. This tradition can be traced back to Aristotle:

We argue that there is no general theory of explanation that spans the sciences, mathematics, and ethics, etc. More specifically, there is no good reason to believe that substantive and domain-invariant constraints on explanatory information exist. Using Nickel (Noûs 44(2):305–328, 2010) as an exemplar of the contrary, generalist position, we first show that Nickel’s arguments rest on several ambiguities, and then show that even when these ambiguities are charitably corrected, Nickel’s defense of general theories of explanation is inadequate along several different dimensions. Specifically, we argue that Nickel’s argument has three fatal flaws. First, he has not provided any compelling illustrations of domain-invariant constraints on explanation. Second, in order to fend off the most vehement skeptics of domain-invariant theories of explanation, Nickel must beg all of the important questions. Third, Nickel’s examples of explanations from different domains with common explanatory structure rely on incorrect formulations of the explanations under consideration, circular justifications, and/or a mischaracterization of the position Nickel intends to critique. Given that the best and most elaborate defense of the generalist position fails in so many ways, we conclude that the standard practice in philosophy (and in philosophy of science in particular), which is to develop theories of explanation that are tailored to specific domains, still is justified. For those who want to buy into a more ambitious project:beware of the costs!