Bas van Fraassen’s Darwinian explanation for the success of science has sparked four decades of discussion, with scientific realists and antirealists alike using biologically inspired reasoning to support their points of view. Based on critical engagement with van Fraassen’s proposal itself and later contributions by Stathis Psillos and K. Brad Wray, we claim that central arguments on both sides of this controversy suffer from an insufficient understanding of Darwinism and its underlying biological concepts. Adding the necessary biological background turns out (...) to subvert the argumentative force of viewing the success of scientific theories as analogous to the behaviour of biotic entities. In conclusion, we sketch more productive ways of viewing the relationship between biology and scientific realism. (shrink)

It has become apparent that the debate between scientific realists and constructive empiricists has come to a stalemate. Neither view can reasonably claim to be the most rational philosophy of science, exclusively capable of making sense of all scientific activities. On one prominent analysis of the situation, whether we accept a realist or an anti-realist account of science actually seems to depend on which values we antecedently accept, rather than our commitment to “rationality” per se. Accordingly, several philosophers have attempted (...) to argue in favour of scientific realism or constructive empiricism by showing that one set of values is exclusively best, for anyone and everyone, and that the downstream choice of the philosophy of science which best serves those values is therefore best, for anyone and everyone. These efforts, however, seem to have failed. In response, I suggest that philosophers of science should suspend the effort to determine which philosophy of science is best for everyone, and instead begin investigating which philosophy of science is best for specific people, with specific values, in specific contexts. I illustrate how this might be done by briefly sketching a single case study from the history of science, which seems to show that different philosophies of science are better at motivating different forms of scientific practice. (shrink)

The pessimistic induction over scientific theories holds that present theories will be overthrown as were past theories. The pessimistic induction over scientists holds that present scientists cannot conceive of future theories just as past scientists could not conceive of present theories. The pessimistic induction over realists :4321–4330, 2013) holds that present realists are wrong about present theories just as past realists were wrong about past theories. The pessimistic induction over antirealist theories :3–21, 2014) holds that the latest antirealist explanation of (...) the success of science :891–901, 2003) has hidden problems just as its eight predecessors did. In this paper, I criticize the pessimistic inductions over scientific theories, scientists, and realists, introduce a pessimistic induction over antirealist theories, and then construct two new pessimistic inductions. One is a pessimistic induction over antirealists according to which the author of the latest antirealist proposal cannot see hidden problems with his proposal just as his antirealist predecessors could not see hidden problems with their proposals. The other is the pessimistic induction over pessimists according to which since past pessimists have been wrong about their present scientific theories from the early twentieth century to the early twenty-first century, future pessimists will also be wrong about their present scientific theories from the early twenty-first century to the early twenty-second century. (shrink)

A scientific theory is successful, according to Stanford (2000), because it is suficiently observationally similar to its corresponding true theory. The Ptolemaic theory, for example, is successful because it is sufficiently similar to the Copernican theory at the observational level. The suggestion meets the scientific realists' request to explain the success of science without committing to the (approximate) truth of successful scientific theories. I argue that Stanford's proposal has a conceptual flaw. A conceptually sound explanation, I claim, respects the ontological (...) order between properties. A dependent property is to be explained in terms of its underlying property, not the other way around. The applicability of this point goes well beyond the realm of the debate between scientific realists and antirealists. Any philosophers should keep the point in mind when they attempt to give an explanation of a property in their field whatever it may be. (shrink)

Structural realism is considered by many realists and antirealists alike as the most defensible form of scientific realism. There are now many forms of structural realism and an extensive literature about them. There are interesting connections with debates in metaphysics, philosophy of physics and philosophy of mathematics. This entry is intended to be a comprehensive survey of the field.

Charles S. Peirce argued that, besides deduction and induction, there is a third mode of inference which he called " hypothesis " or " abduction." He characterized abduction as reasoning " from effect to cause," and as " the operation of adopting an explanatory hypothesis." Peirce ' s ideas about abduction, which are related also to historically earlier accounts of heuristic reasoning, have been seen as providing a logic of scientific discovery. Alternatively, abduction is interpreted as giving reasons for pursuing (...) a hypothesis. Inference to the best explanation has also been regarded as an important mode of justification, both in everyday life, detective stories, and science. In particular, scientific realism has been defended by an abductive nomiracle argument, while the critics of realism have attempted to show that this appeal to abduction is question - begging, circular, or incoherent. This paper approaches these issues by distinguishing weaker and stronger forms of abduction, and by showing how these types of inferences can be given Peircean and Bayesian probabilistic reconstructions. (shrink)

Proponents of the no-miracles argument contend that scientific realism is “the only philosophy that doesn’t make the success of science a miracle.” Bas van Fraassen argued, however, that the success of our best theories can be explained in Darwinian terms—by the fact they are survivors of a winnowing process in which unsuccessful theories are rejected. Critics of this selectionist explanation complain that while it may account for the fact we have chosen successful theories, it does not explain why any particular (...) one of those theories succeeds. Against this I defend the claim that if selectionists manage to account for the former, they have no burden to account for the latter; the success of any particular one of our best theories might as well be an extraordinary coincidence. I refer to this enhanced selectionist reply as “coincidentalism” and argue that it is a serious but underappreciated response to the no-miracles argument. More generally, I argue the considerations raised in favor of this response show that versions of the no-miracles argument focusing on the success of particular theories are misguided. (shrink)

There are nine antirealist explanations of the success of science in the literature. I raise difficulties against all of them except the latest one, and then construct a pessimistic induction that the latest one will turn out to be problematic because its eight forerunners turned out to be problematic. This pessimistic induction is on a par with the traditional pessimistic induction that successful present scientific theories will be revealed to be false because successful past scientific theories were revealed to be (...) false. (shrink)

Antirealist explanations for the success of science have been widely discussed up to today and have received several formulations. This makes it rather complex to assess them all. The objective of this paper is to help understand and assess the proposal of an anti-realist explanation for science’s success. I show the core assumptions contained in the several anti-realist explanations, how they relate to each other, and which background assumptions are required in order to warrant each position. I argue that, since (...) the many anti-realist explanations are only plausible when maintained conjointly, there is essentially only one anti-realist account to science’s success: scientists find successful (and even fertile) theories because they use methods of theory-selection and theory-construction that preserve only successful theories; the fact that these theories prove themselves successful will not be mysterious if it is conjointly assumed that false theories are often empirically successful. This explanation relies on a semantic and a methodological view concerning the probabilistic relation between success and truth, and also on an epistemic stance regarding the limits of explanatory reasoning. The crucial divergence between realist and antirealist accounts of science's success lies in how probable they assess the possibility of a theory to be false and empirically successful. Since the stale-mate between realist and antirealist explanations results from a prior disagreement about the probabilistic connection between success and truth (or the underdetermination thesis), the challenge raised by the antirealist explanation to realism becomes equivalent to the traditional charge that the no-miracles argument is circular. (shrink)

Van Fraassen believes our current best theories enable us to make accurate predictions because they have been subjected to a selection process similar to natural selection. His explanation for the predictive success of our best theories has been subjected to extensive criticism from realists. I aim to clarify the nature of van Fraassen’s selectionist explanation for the success of science. Contrary to what the critics claim, the selectionist can explain why it is that we have successful theories, as well as (...) why it is reasonable to expect past successful theories to be successful in the future. I also argue that the plausibility of the realists’ explanation rests on an inaccurate understanding of the nature of predictive success . The predictive success of our best theories is a relative success. (shrink)

The aim or goal of science has long been discussed by both philosophers of science and scientists themselves. In The Scientific Image (van Fraassen 1980), the aim of science is famously employed to characterize scientific realism and a version of anti-realism, called constructive empiricism. Since the publication of The Scientific Image, however, various changes have occurred in scientific practice. The increasing use of machine learning technology, especially deep learning (DL), is probably one of the major changes in the last decade. (...) This paper aims to explore the implications of DL-aided research for the aim of science debate. I argue that, while the emerging DL-aided research is unlikely to change the state of classic opposition between constructive empiricism and scientific realism, it could offer interesting cases regarding the opposition between those who espouse truth as the aim of science and those oriented to understanding (of the kind that sacrifices truth). (shrink)