Online research in philosophy

As Laudan and Fine show, and Boyd concedes, the attempt to infer the truth of scientific realism from the fact that it putatively provides the best explanation of the instrumental success of science is circular, since what is to be shown is precisely the legitimacy of such abductive inferences. Hacking's "experimental argument for scientific realism about entities" is one of the few arguments for scientific realism that purports to avoid this circularity. We argue that Hacking's argument is as dependent on inference to the best explanation (IBE), and therefore as weak, as the other realist arguments.

How do we go about weighing evidence, testing hypotheses, and making inferences? The model of "inference to the best explanation" (IBE) -- that we infer the hypothesis that would, if correct, provide the best explanation of the available evidence--offers a compelling account of inferences both in science and in ordinary life. Widely cited by epistemologists and philosophers of science, IBE has nonetheless remained little more than a slogan. Now this influential work has been thoroughly revised and updated, and features a new introduction and two new chapters. Inference to the Best Explanation is an unrivaled exposition of a theory of particular interest in the fields both of epistemology and the philosophy of science.

The second edition of Peter Lipton’s classic text contains new and important material on the causal model of explanation, the relation of inference to the best explanation to the Bayesian account of scientific reasoning, how exactly explanation guides inference, and why we ought to think that explanatory virtues are truth-tropic. Lipton is a wonderfully clear writer and a thorough and subtle philosopher, and his book is both a student-friendly introduction to the issues addressed, and essential reading for expert epistemologists and philosophers of science. Appeal to the notion of inference to the best explanation is ubiquitous in defences of scientific realism, but also elsewhere in philosophy where the explanatory virtues of theories are often the only purported grounds for accepting or rejecting them. Despite this, most authors are far from explicit about the details of inference to the best explanation, and Lipton’s book is the most sustained investigation of the relationship between explanation and inference currently available. Furthermore, Lipton is exemplary in his engagement with the problems his arguments face, and judiciously modest in his claims, though not so modest as to court triviality. Hence, the book is replete with interesting and careful arguments. Everyone interested in epistemology or philosophy of science ought to read this book. That said, in my discussion below I will concentrate on what I regard as problems with some of Lipton’s arguments. The model of explanation which he develops is contrastive and causal. Lipton is clear that he does not think all explanations are causal, but he does think that many are, especially in science, and.

Second, there is a form of ampliative inference that has come to be called ‘inference to the best explanation,’ or more briefly ‘explanatory inference.’ Roughly: From the fact that a certain hypothesis would explain the data at hand better than any other available hypothesis, we infer with some degree of confidence that that leading hypothesis is correct. There is no question but that this inference is often performed. Arguably, every human being performs it many times in a day, perhaps without letup.

In this paper, I argue that the ultimate argument for Scientific Realism, also known as the No-Miracles Argument (NMA), ultimately fails as an abductive defence of Epistemic Scientific Realism (ESR), where (ESR) is the thesis that successful theories of mature sciences are approximately true. The NMA is supposed to be an Inference to the Best Explanation (IBE) that purports to explain the success of science. However, the explanation offered as the best explanation for success, namely (ESR), fails to yield independently testable predictions that alternative explanations for success do not yield. If this is correct, then there seems to be no good reason to prefer (ESR) over alternative explanations for success.

This paper offers an account of the relationship between inference and explanation in functional morphology which combines Robert Brandon's theory of adaptation explanation with standard accounts of inference to the best explanation. Inferences of function from structure, it is argued, are inferences to the best adaptation explanation. There are, however, three different approaches to the problem of determining which adaptation explanation is the best. The theory of inference to the best adaptation explanation is then applied to a case study from the history of functional morphology: the case of the crested duckbilled dinosaurs.

Many scientific realists think that the best reasons for scientific theories are abductive, i.e., must appeal to what is also called inference to the best explanation (IBE), while some anti-realists have argued that the use of abduction in defending realism is question-begging, circular, or incoherent. This paper studies the idea that abductive inference can be reformulated by taking its conclusion to concern the truthlikeness of a hypothetical theory on the basis of its success in explanation and prediction. The strength of such arguments is measured by the estimated verisimilitude of its conclusion given the premises. It is argued that this formulation helps to make precise and justifies the "ultimate argument for scientific realism": the empirical success of scientific theories would be a miracle unless they are truthlike.

Hacking (1983) introduces an attempt to defend scientific realism on the basis of the reality of theoretical entities. This position, which is called entity realism, is based on disconnecting the reality of theoretical entities from the truth and explanatory power of theories that account for them. In this way, two problems can be avoided. First if theories about theoretical entities are rejected, the entities themselves do not have to go with them, and the realist thesis that we can have knowledge of what exists in the world can be sustained. Second, theoretical entities, which will replace theories as the grounds for the realist position, would be protected from attacks on the validity of the inference to the best explanation which underlies classical or "theory" realism. In other words, theoretical entities would be able to survive the collapse of the inference to the best explanation. The subject of this paper is a critique of this line of defending realism.

This paper develops a stronger version of ‘inference‐to‐the‐best explanation’ scientific realism. I argue against three standard assumptions of current realists: (1) realism is confirmed if it provides the best explanation of theories’ predictive success; (2) the realist claim that successful theories are always approximately true provides the best explanation of their success; and (3) realists are committed to giving the same sort of truth‐based explanation of superseded theories’ success that they give to explain our best current theories’ success. On the positive side, I argue that (1) the confirmation of realism requires explaining theories’ explanatory success, not just their predictive success; (2) in turn this task requires a richer realist model of explanation that brings into the explanans both (a) successful theories’ epistemic virtues (e.g., unification and simplicity) and (b) the standards governing these virtues, as well as truth; (3) this richer realist model is further confirmed because it can better explain the success of theories in gaining wide acceptance among scientists; and (4) the model is further supported because it is superior to ‘preservative realism’ in providing a plausible rebuttal of the pessimistic meta‐induction from the many past successful‐but‐false theories to the likelihood that our best current theories are likewise false.

Inference to the Best Explanation has become the subject of a livelydebate in the philosophy of science. Scientific realists maintain, while scientificantirealists deny, that it is a compelling rule of inference. It seems that anyattempt to settle this debate empirically must beg the question against theantirealist. The present paper argues that this impression is misleading. A methodis described that, by combining Glymour''s theory of bootstrapping and Hacking''sarguments from microscopy, allows us to test IBE without begging any antirealistissues.