Novel Predictions and Scientific Realism

Scientific results are often presented as ‘surprising’ as if that is a good thing. Is it? And if so, why? What is the value of surprise in science? Discussions of surprise in science have been limited, but surprise has been used as a way of defending the epistemic privilege of experiments over simulations. The argument is that while experiments can ‘confound’, simulations can merely surprise (Morgan, 2005). Our aim in this paper is to show that the discussion of surprise can (...) be usefully extended to thought experiments and theoretical derivations. We argue that in focusing on these features of scientific practice, we can see that the surprise-confoundment distinction does not fully capture surprise in science. We set out how thought experiments and theoretical derivations can bring about surprises that can be disruptive in a productive way, and we end by exploring how this links with their future fertility. (shrink)

The traditional No-Miracles Argument (TNMA) asserts that the novel predictive success of science would be a miracle, and thus too implausible to believe, if successful theories were not at least approximately true. The TNMA has come under fire in multiple ways, challenging each of its premises and its general argumentative structure. While the TNMA relies on explaining novel predictive success via the truth of the theories, we put forth a deductive version of the No-Miracles argument (DNMA) that avoids inference to (...) the best explanation entirely. Instead, a relatively simple empirical framework and a probabilistic analysis can accomplish the ambitious goals of the TNMA while entirely sidestepping its problems. This close-but-distinct argument has many independent strengths and comparatively few weaknesses. Indeed, objections tailored specifically to the DNMA reveal surprising insights into how exactly NMAs are neither circular nor question-begging, as has been widely speculated. (shrink)

Recent contributions to the philosophy of the social sciences have motivated ontological commitments using appeals to the social sciences (_naturalized_ social ontologies). These arguments rely on social scientific realism about the social sciences, the view that our social scientific theories are approximately true. I apply a distinction formulated in metaontology between ontologically loaded and unloaded meanings of existential quantification to argue that there is a pragmatic approach to naturalized social ontology that is minimally realist (it treats existence claims as true (...) or false) but that is ontologically austere. I argue that the extant arguments may be construed in terms of this pragmatic approach. The result is an approach to social ontology that is deflationist about naturalized social ontology. (shrink)

Deployment Realism resists Laudan’s and Lyons’ objections to the “No Miracle Argument” by arguing that a hypothesis is most probably true when it is deployed essentially in a novel prediction. However, Lyons criticized Psillos’ criterion of essentiality, maintaining that Deployment Realism should be committed to all the actually deployed assumptions. But since many actually deployed assumptions proved false, he concludes that the No Miracle Argument and Deployment Realism fail. I reply that the essentiality condition is required by Occam’s razor. In (...) fact, there is a simpler formulation of essentiality which escapes Lyons’ criticisms and rescues the No Miracle Argument and Deployment Realism from their purported historical counterexamples: a hypothesis is essential when it has no proper parts (in Yablo’s sense) sufficient to derive the same prediction. Although essentiality so conceived cannot be detected prospectively, this is just natural, and it is not a problem but an advantage for Deployment Realism. (shrink)

The notion of a hypothesis being deployed essentially in the derivation of a novel prediction plays a key role in the deployment realist reply to Laudan’s and Lyon’s attacks to the No Miracle Argument. However Lyons criticized Psillos’ criterion of essentiality, urging deployment realists to abandon this requirement altogether and accept as true all the assumptions actually deployed in novel predictions. But since many false assumptions were actually deployed in novel predictions, he concludes that the “no miracle argument” and deployment (...) realism fail. I reply that the essentiality condition is required by Occam’s razor, and a “no miracle argument” deprived of that condition is a straw man. While Lyons’ criticisms of Psillos’ formalization of essentiality may be well taken, I suggest that there is a simpler formulation which escapes those criticisms and is enough to deal with the supposed counterexamples to the No Miracle Argument and deployment realism: a hypothesis is essential when it does not have a proper part (in Yablo’s sense) from which the prediction could also be derived. I then show how this condition rescues deployment realism from Lyons’ purported historical counterexamples. Essentiality in this sense cannot be detected prospectively, but this is just what we should expect, and far from causing problems for deployment realists, this frees them from unreasonable obligations. (shrink)

This chapter examines the work in chemistry that led to the discovery of boron and explores the implications of this episode for the scientific realism debate. This episode begins with Lavoisier’s oxygen theory of acidity and his prediction that boracic acid contains oxygen and a hypothetical, combustible substance that he called the boracic radical. And it culminates in the work of Davy, Gay-Lussac, and Thénard, who used potassium to extract oxygen from boracic acid and thereby discovered boron. This episode constitutes (...) a novel predictive success of Lavoisier’s theory of acidity, which was not even approximately true. Selective realists attempt to accommodate such false-but-successful theories by showing that their success is due to the fact that they have approximately true parts. This episode poses a strong challenge to selective realism because the parts of Lavoisier’s theory that are responsible for its success are not even approximately true. (shrink)

Scientific realists claim we can justifiably believe that science is getting at the truth. But they have long faced historical challenges: various episodes across history appear to demonstrate that even strongly supported scientific theories can be overturned and left behind. In response, realists have developed new positions and arguments. As a result of specific challenges from the history of science, and realist responses, we find ourselves with an ever increasing data-set bearing on the (possible) relationship between science and truth. The (...) present volume introduces new historical cases impacting the debate, and advances the discussion of cases that have only very recently been introduced. At the same time, shifts in philosophical positions affect the very kind of case study that is relevant. Thus the historical work must proceed hand in hand with philosophical analysis of the different positions and arguments in play. It is with this in mind that the volume is divided into two sections, entitled “Historical cases for the debate,” and “Contemporary scientific realism”. All sides agree that historical cases are informative with regard to how, or whether, science connects with truth. Defying proclamations as early as the 1980s announcing the death knell of the scientific realism debate, here is that rare thing: a philosophical debate making steady and definite progress. Moreover, the progress it is making concerns one of humanity’s most profound and important questions: the relationship between science and truth, or, put more boldly, the epistemic relation between humankind and the reality in which we find ourselves. (shrink)

This is the first chapter of Modal Empiricism: Interpreting Science Without Scientific Realism. The debate on scientific realism results from a tension between the empiricist methodology, which is a defining feature of science, and claims to the effect that science can unveil the fundamental nature of reality. What distinguishes realist and anti-realist positions is not necessarily that the former take scientific knowledge “at face value” or take the side of scientists in general while the latter do not. Rather, realists and (...) anti-realists propose different ways of interpreting science as a whole, and in particular its aim, its possible achievements and its content. The aim of this book is to defend an interpretation that potentially applies to each of these three levels: modal empiricism. This position purports to be the articulation of a pragmatist stance towards science. This introductory chapter briefly presents the position, then outlines the structure of the book. (shrink)

In this paper I provide a novel argument for scientific realism. In contrast to most recent defenses of SR, my defense of SR does not rely on the no-miracles argument. Instead, I take a more unconventional approach: I focus on the different kinds of justification available to different individuals in relation to different kinds of propositions. I maintain that this alternative focus shows that most people are warranted in believing many propositions about unobservables. The paper is divided into three main (...) sections. In the first, I rehearse the main moves in the recent debate about SR. In the second, I argue that the discussion in section one enables us to see that most of the arguments in the recent debate about SR mistake their target: instead of being about SR, they are about meta-SR. I argue that what I call the JJ-principle should be rejected and, further, that if the JJ-principle is rejected, then meta-SR may be cleaved from SR. This enables me to advance to a position I call thin realism in the third and final section of the paper. (shrink)

Nickles (2016, 2017, forthcoming) raises many original objections against scientific realism. One of them holds that scientific realism originates from the end of history illusion. I reply that this objection is self-defeating and commits the genetic fallacy. Another objection is that it is unknowable whether our descendants will regard our current mature theories as true or false. I reply that this objection entails skepticism about induction, leading to skepticism about the world, which is inconsistent with the appeal to the end (...) of history illusion. Finally, I argue that we have an inductive rationale for thinking that our descendants will regard our current mature theories as true. (shrink)

What are the relevant values to the appraisal of research programs? This question remains hotly debated, as philosophers have recently proposed many lists of values potentially relevant to scientific appraisal. Surprisingly, despite being mentioned in many lists, little attention has been paid to fruitfulness. It is unclear how fruitfulness should be explicated, and whether it has any substantial role in scientific appraisal. In this paper, I argue we should explicate fruitfulness as the capacity to develop of research programs. Moreover, I (...) provide a novel strategy to assess and compare the fruitfulness of programs focused on their research questions and heuristics. To illustrate how this strategy would work, I will discuss a case study, namely the adaptationist program in evolutionary psychology. (shrink)

I critically examine Stewart’s suggestion that we should weigh the various predictions Mendeleev made differently. I argue that in his effort to justify discounting the weight of some of Mendeleev’s failures, Stewart invokes a principle that will, in turn, reduce the weight of some of the successful predictions Mendeleev made. So Stewart’s strategy will not necessarily lead to a net gain in Mendeleev’s favor.

In this book K. Brad Wray provides a comprehensive survey of the arguments against scientific realism. In addition to presenting logical considerations that undermine the realists' inferences to the likely truth or approximate truth of our theories, he provides a thorough assessment of the evidence from the history of science. He also examines grounds for a defence of anti-realism, including an anti-realist explanation for the success of our current theories, an account of why false theories can be empirically successful, and (...) an explanation for why we should expect radical changes of theory in the future. His arguments are supported and illustrated by cases from the history of science, including a sustained study of the Copernican Revolution, and a study of the revolution in early twentieth century chemistry, when chemists came to classify elements by their atomic number rather than by their atomic weight. (shrink)

This paper argues that scientific realism commits us to a metaphysical determination relation between the mathematical entities that are indispensible to scientific explanation and the modal structure of the empirical phenomena those entities explain. The argument presupposes that scientific realism commits us to the indispensability argument. The viewpresented here is that the indispensability of mathematics commits us not only to the existence of mathematical structures and entities but to a metaphysical determination relation between those entities and the modal structure of (...) the physical world. The no-miracles argument is the primary motivation for scientific realism. It is a presupposition of this argument that unobservable entities are explanatory only when they determine the empirical phenomena they explain. I argue that mathematical entities should also be seen as explanatory only when they determine the empirical facts they explain, namely, the modal structure of the physical world. Thus, scientific realism commits us to a metaphysical determination relation between mathematics and physical modality that has not been previously recognized. The requirement to account for the metaphysical dependence of modal physical structure on mathematics limits the class of acceptable solutions to the applicability problem that are available to the scientific realist. (shrink)

According to a defense of scientific realism known as the “divide et impera move”, mature scientific theories enjoying predictive success are partially true. This paper investigates a paradigmatic historical case: the prediction, based on Fresnel’s wave theory of light, that a bright spot should figure in the shadow of a disc. Two different derivations of this prediction have been given by both Poisson and Fresnel. I argue that the details of these derivations highlight two problems of indispensability arguments, which state (...) that only the indispensable constituents of this success are worthy of belief and retained through theory-change. The first problem is that, contrary to a common claim, Fresnel’s integrals are not needed to predict the bright spot phenomenon. The second problem is that the hypotheses shared by to these two derivations include problematic idealizations. I claim that this example leads us to be skeptical about which aspects of our current theories are worthy of belief. (shrink)

It has recently been suggested that realist responses to historical cases featured in pessimistic meta-inductions are not as successful as previously thought. In response, selective realists have updated the basic divide et impera strategy specifically to take such cases into account and to argue that more modern realist accounts are immune to the historical challenge. Using a case study—that of the nineteenth-century zymotic theory of disease—I argue that these updated proposals fail and that even the most sophisticated recent realist accounts (...) remain vulnerable to the challenge from history. (shrink)

review and discussion of: John Wright: Explaining science’s success: Understanding how scientific knowledge works. Durham: Acumen, 2012.

There is good reason to believe that scientific realism requires a commitment to the objective modal structure of the physical world. Causality, equilibrium, laws of nature, and probability all feature prominently in scientific theory and explanation, and each one is a modal notion. If we are committed to the content of our best scientific theories, we must accept the modal nature of the physical world. But what does the scientific realist’s commitment to physical modality require? We consider whether scientific realism (...) is compatible with Humeanism about the laws of nature, and we conclude that it is not. We specifically identify three major problems for the best-systems account of lawhood: its central concept of strength cannot be formulated non-circularly, it cannot offer a satisfactory account of the laws of the special sciences, and it can offer no explanation of the success of inductive inference. In addition, Humeanism fails to be naturalistically motivated. For these reasons, we conclude that the scientific realist must embrace natural necessity. (shrink)

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. (shrink)

Inferences from scientific success to the approximate truth of successful theories remain central to the most influential arguments for scientific realism. Challenges to such inferences, however, based on radical discontinuities within the history of science, have motivated a distinctive style of revision to the original argument. Conceding the historical claim, selective realists argue that accompanying even the most revolutionary change is the retention of significant parts of replaced theories, and that a realist attitude towards the systematically retained constituents of our (...) scientific theories can still be defended. Selective realists thereby hope to secure the argument from success against apparent historical counterexamples. Independently of that objective, historical considerations have inspired a further argument for selective realism, where evidence for the retention of parts of theories is itself offered as justification for adopting a realist attitude towards them. Given the nature of these arguments from success and from retention, a reasonable expectation is that they would complement and reinforce one another, but although several theses purport to provide such a synthesis the results are often unconvincing. In this paper I reconsider the realist’s favoured type of scientific success, novel success, offer a revised interpretation of the concept, and argue that a significant consequence of reconfiguring the realist’s argument from success accordingly is a greater potential for its unification with the argument from retention.Keywords: Scientific realism; Pessimistic meta-induction; Success; Progress; Aether; Novelty. (shrink)

An enduring question in the philosophy of science is the question of whether a scientific theory deserves more credit for its successful predictions than it does for accommodating data that was already known when the theory was developed. In The Paradox of Predictivism, Eric Barnes argues that the successful prediction of evidence testifies to the general credibility of the predictor in a way that evidence does not when the evidence is used in the process of endorsing the theory. He illustrates (...) his argument with an important episode from nineteenth-century chemistry, Mendeleev's Periodic Law and its successful predictions of the existence of various elements. The consequences of this account of predictivism for the realist/anti-realist debate are considerable, and strengthen the status of the 'no miracle' argument for scientific realism. Barnes's important and original contribution to the debate will interest a wide range of readers in philosophy of science. (shrink)

Harold Brown has written an ambitious work, which traces the formation of concepts in individuals and cultures, examines case studies of concepts in calculus, mathematics, biology and related fields, summarises important philosophical works on the theory of concepts, and seeks to reconcile scientific realism with conceptual change. Brown considers himself a scientific realist but concedes that this very label is one that depends on a long history of concepts that came before, and may indeed be superseded as conceptual change continues. (...) Yet, concepts are not strictly relative to their contexts. ‘‘The usual claim is that truth is relative – period; and this claim assumes a non-relativized truth-concept’’ (p. 309). Crucial to his goal of developing a theory of concepts is how Brown reconciles conceptual change with objectivity. (shrink)

It has been claimed that modern long-standing scientific theories are fertile, in the sense of having been progressively successfully modified to meet new experimental observations or theoretical developments in related areas, and that these modifications arise naturally from each preceding version of the theory. McMullin has advanced this form of fertility as a vindication of scientific realism, since if the theories did not approximate the real, the observation would be inexplicable. In response Nolan has denied the existence of fertility in (...) this sense as an independent virtue. The present paper argues that the rebuttal is flawed. Introduction McMullin's P-fertility Fertility Explained Away as Novel Prediction Conclusion CiteULike Connotea Del.icio.us What's this? (shrink)

Strong predictivism, the idea that novel predictions per se confirm theories more than accommodations, is based on a “no miracle” argument from novel predictions to the truth of theories (NMAT). Eric Barnes rejects both: he reconstructs the NMAT as seeking an explanation for the entailment relation between a theory and its novel consequences, and argues that it involves a fallacious application of Occam’s razor. However, he accepts a no miracle argument for the truth of background beliefs (NMABB): scientists endorsed a (...) successful theory because they were guided by largely true background beliefs. This in turn raises the probability that the theory is true; so Barnes embraces a form of weak predictivism, according to which predictions are only indirectly relevant to confirmation. To Barnes I reply that we should also explain how the successful theory was constructed, not just endorsed; background beliefs are not enough to explain success, scientific method must also be considered; Barnes can account for some measure of confirmation of our theories, but not for the practical certainty conferred to them by some astonishing predictions; true background beliefs and reliability by themselves cannot explain novel success, the truth of theories is also required. Hence, the NMAT is sound, and strong predictivism is right. In fact, Barnes misinterprets the NMAT, which does not involve Occam’s razor, takes as explanandum the building of a theory which turned out to predict surprising facts, and successfully concludes that the theory is true. This accounts for the practically certain confirmation of our most successful theories, in accordance with strong predictivism. (shrink)

Epistemologists have debated at length whether scientific discovery is a rational and logical process. If it is, according to the Artificial Intelligence hypothesis, it should be possible to write computer programs able to discover laws or theories; and if such programs were written, this would definitely prove the existence of a logic of discovery. Attempts in this direction, however, have been unsuccessful: the programs written by Simon's group, indeed, infer famous laws of physics and chemistry; but having found no new (...) law, they cannot properly be considered discovery machines. The programs written in the Turing tradition, instead, produced new and useful empirical generalization, but no theoretical discovery, thus failing to prove the logical character of the most significant kind of discoveries. A new cognitivist and connectionist approach by Holland, Holyoak, Nisbett and Thagard, looks more promising. Reflection on their proposals helps to understand the complex character of discovery processes, the abandonment of belief in the logic of discovery by logical positivists, and the necessity of a realist interpretation of scientific research. (shrink)

an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the (...) key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments. (shrink)

Scientific realists have claimed that the posit that our theories are (approximately) true provides the best or the only explanation for their success . In response, I revive two non-realists explanations. I show that realists, in discarding them, have either misconstrued the phenomena to be explained or mischaracterized the relationship between these explanations and their own. I contend nonetheless that these non-realist competitors, as well as their realist counterparts, should be rejected; for none of them succeed in explaining a significant (...) list of successes. I propose a related non-realist explanation of success that appears to be the most suitable among those considered. (shrink)

P. Kyle Stanford (2000) attempts to offer a truth-linked explanation of the success of science which, he thinks, can be welcome to antirealists. He proposes an explanation of the success of a theory T1 in terms of its predictive similarity to the true theory T of the relevant domain. After raising some qualms about the supposed antirealist credentials of Stanford's account, I examine his explanatory story in some detail and show that it fails to offer a satisfactory explanation of the (...) success of science. (shrink)

This paper analyzes Deborah Mayo's recent criticism of use-novelty requirement. She claims that her severity criterion captures actual scientific practice better than use-novelty, and that use-novelty is not a necessary condition for severity. Even though certain cases in which evidence used for the construction of the hypothesis can test the hypothesis severely, I do not think that her severity criterion fits better with our intuition about good tests than use-novelty. I argue for this by showing a parallelism in terms of (...) severity between the confidence interval case and what she calls 'gellerization'. To account for the difference between these cases, we need to take into account certain additional considerations like a systematic neglect of relevant alternatives. (shrink)

Leplin attempts to reinstate the common sense idea that theoretical knowledge is achievable, indeed that its achievement is part of the means to progress in empirical knowledge. He sketches the genesis of the skeptical position, then introduces his argument for Minimalist Scientific Realism -- the requirement that novel predicitons be explained, and the claim that only realism about scientific theories can explain the importance of novel prediction.