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)

There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential (...) contexts , we can see that neither weak nor strong predictivism captures all of the reasons for valuing prediction available. A third path is presented, Pluralist Instrumental Predictivism; PIP for short. (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)

Are theories judged on the basis of empirical tests of their predictions, as proposed by Karl Popper and others, or are new theories adopted by younger scientists while old theories fade away when their advocates die, as Max Planck suggested? A famous historical episode, the rejection of steady state cosmology and the revival of the big bang cosmology following the 1965 discovery of the cosmic microwave background radiation, is examined to determine whether the scientific community followed Popper’s or Planck’s principle. (...) It is found that by 1975 almost all supporters of the steady state had either switched to the big bang or stopped publishing on cosmology. This case therefore seems to exemplify Popper’s principle, although it should be noted that two of the founders of steady state cosmology had strongly proclaimed their adherence to that principle. The case does not support the Popperian claim that successful novel predictions provide better evidence for a theory than deductions of known facts. (shrink)

I develop an account of predictive similarity that allows even Antirealists who accept a correspondence conception of truth to answer the Realist demand (recently given sophisticated reformulations by Musgrave and Leplin) to explain the success of particular scientific theories by appeal to some intrinsic feature of those theories (notwithstanding the failure of past efforts by van Fraassen, Fine, and Laudan). I conclude by arguing that we have no reason to find truth a better (i.e., more plausible) explanation of (...) a theory's success than predictive similarity, even of its success in making novel predictions. (shrink)

The extra value of novel confirmation over accommodation is explained based on an analysis of the underdetermination of scientific theory building. Novel confirmation can provide information on the number of possible scientific alternatives to a predictively successful theory. This information, in turn, can raise the probability that the given theory is true or will be empirically viable in the future.

In this paper I challenge and adjudicate between the two positions that have come to prominence in the scientific realism debate: deployment realism and structural realism. I discuss a set of cases from the history of celestial mechanics, including some of the most important successes in the history of science. To the surprise of the deployment realist, these are novel predictive successes toward which theoretical constituents that are now seen to be patently false were genuinely deployed. Exploring the (...) implications for structural realism, I show that the need to accommodate these cases forces our notion of “structure” toward a dramatic depletion of logical content, threatening to render it explanatorily vacuous: the better structuralism fares against these historical examples, in terms of retention, the worse it fares in content and explanatory strength. I conclude by considering recent restrictions that serve to make “structure” more specific. I show however that these refinements will not suffice: the better structuralism fares in specificity and explanatory strength, the worse it fares against history. In light of these case studies, both deployment realism and structural realism are significantly threatened by the very historical challenge they were introduced to answer. (shrink)

The thesis that scientists give greater weight to novel predictions than to explanations of known facts is tested against historical cases in physical science. Several theories were accepted after successful novel predictions but there is little evidence that extra credit was given for novelty. Other theories were rejected despite, or accepted without, making successful novel predictions. No examples were found of theories that were accepted primarily because of successful novel predictions and would not have been accepted (...) if those facts had been previously known. (shrink)

Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual (...) account of two features of structural representations: structural similarity and decoupling. We argue that structural similarity can be analysed in terms of two dimensions: number of preserved relations and state space granularity. Both dimensions can take on different values and hence render structural similarity gradual. We further argue that decoupling is gradual in two ways. First, we show that different brain areas are involved in decoupled cognitive processes to a greater or lesser degree depending on the cause (internal or external) of their activity. Second, and more importantly, we show that the degree of decoupling can be further regulated in some brain areas through precision weighting of prediction error. We lastly argue that gradation of decoupling (via precision weighting) and gradation of structural similarity (via state space granularity) are conducive to behavioural success. (shrink)

In the case of magnetic resonance imaging (MRI) imaging, image processing is crucial. In the medical industry, MRI images are commonly used to analyze and diagnose tumor growth in the body. A number of successful brain tumor identification and classification procedures have been developed by various experts. Existing approaches face a number of obstacles, including detection time, accuracy, and tumor size. Early detection of brain tumors improves options for treatment and patient survival rates. Manually segmenting brain tumors from a significant (...) number of MRI data for brain tumor diagnosis is a tough and time-consuming task. Automatic image segmentation of brain tumors is required. The objective of this study is to evaluate the degree of accuracy and simplify the medical picture segmentation procedure used to identify the type of brain tumor from MRI results. Additionally, this work suggests a novel method for identifying brain malignancies utilizing the Bagging Ensemble with K-Nearest Neighbor (BKNN) in order to raise the KNN’s accuracy and quality rate. For image segmentation, a U-Net architecture is utilized first, followed by a bagging-based k-NN prediction algorithm for classification. The goal of employing U-Net is to improve the accuracy and uniformity of parameter distribution in the layers. Each decision tree is fitted on a little different training dataset during classification, and the bagged decision trees are effective since each tree has minor differences and generates slightly different skilled predictions. The overall classification accuracy was up to 97.7 percent, confirming the efficiency of the suggested strategy for distinguishing normal and pathological tissues from brain MR images; this is greater than the methods that are already in use. (shrink)

“What did the President know and when did he know it?”Senator Howard Baker, Watergate hearings, 1973Why do scientists accept or reject theories? More specifically: why do they change from one theory to another? What is the role of empirical tests in the evaluation of theories?This paper focuses on a narrowly-defined question: in judging theories, do scientists give greater weight (other things being equal) to successfulnovel predictionsthan to successful deductions of previously-known facts? The affirmative answer is called the “predictivist thesis” (Maher (...) 1988).It is primarily philosophers who are interested in this question, and they have treated it mostly as a normative or logical problem. Can the writings of historians of science tell us how scientists have treated novel predictions in the past? Until recently historians have rarely addressed this point. (shrink)

This paper argues against a particular version of the inference from the success of a scientific theory to the claim that the theory must be approximately true to some extent. The kind of success at issue is comparative, where one theory is more empirically successful than its rival if that theory predicts phenomena that are inexplicable or anomalous according to its rival. A theory that exhibits this kind of comparative success can be seen as thereby achieving empirical (...) progress over its rival. David Harker has developed a form of selective scientific realism based on the idea that this kind of success is evidence for the approximate truth of the parts of theories responsible for such success. Counterexamples to Harker’s position are cases in which a theory is more successful than its rival in virtue of containing parts that are not even approximately true. In order to identify some counterexamples to Harker’s position, this paper considers four historical cases that Greg Frost-Arnold has recently used to motivate a novel historical challenge to realism called the Problem of Misleading Evidence. This paper argues that these four cases are counterexamples to Harker’s position, and that they provide a strong reason to doubt his position and the kind of success-to-truth inference that he defends. (shrink)

The Hurvich-Jameson (H-J) opponent-process network offers a familiar account of the empirical structure of the phenomenological color space for humans, an account with a number of predictive and explanatory virtues. Its successes form the bulk of the existing reasons for suggesting a strict identity between our various color sensations on the one hand, and our various coding vectors across the color-opponent neurons in our primary visual pathways on the other. But anti-reductionists standardly complain that the systematic parallels discovered by (...) the H-J network are just empirical correspondences, constructed post facto, with no predictive or explanatory purchase on the intrinsic characters of qualia proper. The present paper disputes that complaint, by illustrating that the H-J model yields some novel and unappreciated predictions, and some novel and unappreciated explanations, concerning the qualitative characters of a considerable variety of color sensations possible for human experience, color sensations that normal people have almost certainly never had before, color sensations whose accurate descriptions in ordinary language appear semantically ill-formed or even self-contradictory. Specifically, these "impossible" color sensations are activation-vectors (across our opponent-process neurons) that lie inside the space of neuronally possible activation-vectors, but outside the central 'color spindle' that confines the familiar range of sensations for possible objective colors. These extra-spindle chimerical-color sensations correspond to no reflective color that you will ever see objectively displayed on a physical object. But the H-J model both predicts their existence and explains their highly anomalous qualitative characters in some detail. It also suggests how to produce these rogue sensations by a simple procedure made available in the latter half of this paper. The relevant color plates will allow you to savor these sensations for yourself. (shrink)

Schurz (Synthese 164:201–234, 2008) proposed a justification of creative abduction on the basis of the Reichenbachian principle of the common cause. In this paper we take up the idea of combining creative abduction with causal principles and model instances of successful creative abduction within a Bayes net framework. We identify necessary conditions for such inferences and investigate their unificatory power. We also sketch several interesting applications of modeling creative abduction Bayesian style. In particular, we discuss use-novel predictions, confirmation, and (...) the problem of underdetermination in the context of abductive inferences. (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)

Battery energy storage is the pivotal project of renewable energy systems reform and an effective regulator of energy flow. Parallel battery packs can effectively increase the capacity of battery modules. However, the power loss caused by the uncertainty of parallel battery branch current poses severe challenge to the economy and safety of electric vehicles. Accuracy of battery branch current prediction is needed to improve the parallel connection. This paper proposes a radial basis function neural network model based on the pigeon-inspired (...) optimization method and successfully applies the algorithm to predict the parallel branch current of the battery pack. Numerical results demonstrate the high accuracy of the proposed pigeon-inspired optimized RBF model for parallel battery branch forecasting and provide a useful tool for the prediction of parallel branch currents of battery packs. (shrink)

Paul Feyeraband famously asked, what's so great about science? One answer is that it has been surprisingly successful in getting things right about the natural world, more successful than non-scientific or pre-scientific systems, religion or philosophy. Science has been able to formulate theories that have successfully predicted novel observations. It has produced theories about parts of reality that were not observable or accessible at the time those theories were first advanced, but the claims about those inaccessible areas have since (...) turned out to be true. And science has, on occasion, advanced on more or less a priori grounds theories that subsequently turned out to be highly empirically successful. In this book the philosopher of science, John Wright delves deep into science's methodology to offer an explanation for this remarkable success story. (shrink)

The currently most plausible version of scientific realism is probably “deployment” realism, based on various contributions in the recent literature, and worked out as a unitary account in Psillos. According to it we can believe in the at least partial truth of theories, because that is the best explanation of their predictive success, and discarded theories which had novel predictive success had nonetheless some true parts, those necessary to derive their novel predictions. According to (...) Doppelt this account cannot withstand the antirealist objections based on the “pessimistic meta-induction” and Laudan’s historical counterexamples. Moreover it is incomplete, as it purports to explain the predictive success of theories, but overlooks the necessity to explain also their explanatory success. Accordingly, he proposes a new version of realism, presented as the best explanation of both predictive and explanatory success, and committed only to the truth of best current theories, not of the discarded ones. Here I argue that Doppelt has not shown that deployment realism as it stands cannot solve the problems raised by the history of science, explaining explanatory success does not add much to explaining novel predictive success, and a realism confined to current theories is implausible, and actually the easiest prey to the pessimistic meta-induction argument. (shrink)

Gerald Doppelt claims that Deployment Realism cannot withstand the antirealist objections based on the “pessimistic meta-induction” and Laudan’s historical counterexamples. Moreover it is incomplete, as it purports to explain the predictive success of theories, but overlooks the necessity to explain also their explanatory success. Accordingly, he proposes a new version of realism, presented as the best explanation of both predictive and explanatory success, and committed only to the truth of best current theories, not of the (...) discarded ones. Elsewhere I criticized his new brand of realism. Here instead I argue that Doppelt has not shown that Deployment Realism cannot solve the problems raised by the history of science, explaining explanatory success does not add much to explaining novel predictive success, and Doppelt is right that truth is not a sufficient explanans, but for different reasons, and this does not refute Deployment Realism, but helps to detail it better. In a more explicit formulation, the realist IBE concludes not only to the truth of theories, but also to the reliability of scientists and scientific method, the order and simplicity of nature, and the approximate truth of background theories. (shrink)

This chapter explores the main argument for scientific realism, the No-Miracle Argument (NMA), and two antirealist arguments criticizing scientific realism, the Pessimistic Induction and the argument from Underdetermination. Scientific realists have articulated many different versions of their doctrine in response to the acknowledged shortcomings of the original NMA. While most rely on an inference to the best explanation, they propose stricter notions of novel predictive success, richer notion of success in general, and more discriminating ways of (...) identifying the parts of a theory responsible for that success. When one looks at the history of science, especially the scientific revolutions in physics, astronomy, and chemistry chronicled in T. S. Kuhn, the realist seems to be in a bind. For Kuhn, and later Larry Laudan, gave many examples of theories that were successful in their day and recognize as based on radically false assumptions about the world. (shrink)

According to a widely shared view, experience plays only a limited role in children's acquisition of the capacity to pass the false belief test: at most, it facilitates or attunes the development of mindreading abilities from infancy to early childhood. Against the facilitation—and also the maturation—hypothesis, I report empirical data attesting that children and even adults never come to understand false beliefs when deprived of proper social and linguistic interaction. In contrast to the attunement hypothesis, I argue that alleged mindreading (...) abilities in infancy differ significantly from those required to pass the false belief test at age four. I conclude that children's success in the false belief test reflects the acquisition of a novel psychological competence, and argue that social experience in the form of conversation about mental states teaches children to exploit belief reports to predict intelligent behaviour, and induces their acquisition of a capacity to recognize and track others' beliefs across contexts. (shrink)

Many scholars have conducted in-depth research on the evaluation and prediction of scholars’ scientific impact and meanwhile discovered various factors that affect the success of scholars. Among all these relevant factors, scholars’ ages have been universally acknowledged as one of the most important factors for it can shed light on many practical issues, e.g., finding supervisors, discovering rising stars, and research funding or award applications. However, due to the inaccessibility or the privacy issues of acquiring scholars’ personal data, there (...) is little research to explore the true ages of scholars currently. Alternatively, scholars’ publications’ information can be obtained through various digital libraries. Inspired by this fact, we propose a novel scholar’s age prediction method based on their articles’ information. Our method first classifies factors that affect scholars’ ages into intuitive and complex types according to their computational complexity and then apply machine learning algorithms to predict the ages of scholars based on these factors. The experimental results on the real dataset demonstrate that our method can effectively predict the true ages of scholars. Given that there is no completely accurate dataset because of the continuous publication of academic papers, we then apply our method on the incomplete dataset. Nevertheless, our method still has high prediction accuracy in such situations. (shrink)

The target paper (building on Ginsburg and Jablonka in JTB 381:55–60, 2015, The evolution of the sensitive soul: Learning and the origins of consciousness, MIT Press, USA, 2019) makes a significant and novel claim: that positive cases of non-human consciousness can be identified via the capacity of unlimited associative learning (UAL). In turn, this claim is generated by a novel methodology, which is that of identifying an evolutionary ‘transition marker’, which is claimed to have theoretical and empirical advantages (...) over other approaches. In this commentary I argue that UAL does not function as a successful transition marker (as defined by the authors), and has internal problems of its own. However, I conclude that it is still a very productive anchor for new research on the evolution of consciousness. (shrink)

A theory’s fertility is one of the standard theoretical virtues. But how is it to be construed? In current philosophical discourse, particularly in the realism debate, theoretical fertility is usually understood in terms of novel success: a theory is fertile if it manages to make successful novel predictions. Another, more permissible, notion of fertility can be found in the work of Ernan McMullin. This kind of fertility, McMullin claims, gives us just as strong grounds for realism. My (...) paper critically assesses McMullin’s notion of fertility and its realist rationale. It concludes that McMullin’s preferred example, namely the fertile development of the Bohr-Sommerfeld model of the atom, does not support McMullin’s argument for realism. Although the implications for the realism debate are as of yet unclear, the case study offers some important methodological lessons. (shrink)

Predictivism is the view that successful predictions of “novel” evidence carry more confirmational weight than accommodations of already known evidence. Novelty, in this context, has traditionally been conceived of as temporal novelty. However temporal predictivism has been criticized for lacking a rationale: why should the time order of theory and evidence matter? Instead, it has been proposed, novelty should be construed in terms of use-novelty, according to which evidence is novel if it was not used in the construction (...) of a theory. Only if evidence is use-novel can it fully support the theory entailing it. As I point out in this paper, the writings of the most influential proponent of use-novelty contain a weaker and a stronger version of use-novelty. However both versions, I argue, are problematic. With regard to the appraisal of Mendeleev’ periodic table, the most contentious historical case in the predictivism debate, I argue that temporal predictivism is indeed supported, although in ways not previously appreciated. On the basis of this case, I argue for a form of so-called symptomatic predictivism according to which temporally novel predictions carry more confirmational weight only insofar as they reveal the theory’s presumed coherence of facts as real. (shrink)

We develop a cultural evolutionary theory of the origins of prosocial religions and apply it to resolve two puzzles in human psychology and cultural history: (1) the rise of large-scale cooperation among strangers and, simultaneously, (2) the spread of prosocial religions in the last 10–12 millennia. We argue that these two developments were importantly linked and mutually energizing. We explain how a package of culturally evolved religious beliefs and practices characterized by increasingly potent, moralizing, supernatural agents, credible displays of faith, (...) and other psychologically active elements conducive to social solidarity promoted high fertility rates and large-scale cooperation with co-religionists, often contributing to success in intergroup competition and conflict. In turn, prosocial religious beliefs and practices spread and aggregated as these successful groups expanded, or were copied by less successful groups. This synthesis is grounded in the idea that although religious beliefs and practices originally arose as nonadaptive by-products of innate cognitive functions, particular cultural variants were then selected for their prosocial effects in a long-term, cultural evolutionary process. This framework (1) reconciles key aspects of the adaptationist and by-product approaches to the origins of religion, (2) explains a variety of empirical observations that have not received adequate attention, and (3) generates novel predictions. Converging lines of evidence drawn from diverse disciplines provide empirical support while at the same time encouraging new research directions and opening up new questions for exploration and debate. (shrink)

The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7–12 month-old-infants. In Piaget's classic “A-not-B error,” infants who have successfully uncovered a toy at location “A” continue to reach to that location even after they watch the toy hidden in a nearby location “B.” Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects (...) or other static mental structures. Instead, we demonstrate that the A-not-B error and its previously puzzling contextual variations can be understood by the coupled dynamics of the ordinary processes of goal-directed actions: looking, planning, reaching, and remembering. We offer a formal dynamic theory and model based on cognitive embodiment that both simulates the known A-not-B effects and offers novel predictions that match new experimental results. The demonstration supports an embodied view by casting the mental events involved in perception, planning, deciding, and remembering in the same analogic dynamic language as that used to describe bodily movement, so that they may be continuously meshed. We maintain that this mesh is a pre-eminently cognitive act of “knowing” not only in infancy but also in everyday activities throughout the life span. Key Words: cognitive development; dynamical systems theory; embodied cognition; infant development; motor control; motor planning; perception and action. (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)

Recent debates over adults' theory of mind use have been fueled by surprising failures of perspective-taking in communication, suggesting that perspective-taking may be relatively effortful. Yet adults routinely engage in effortful processes when needed. How, then, should speakers and listeners allocate their resources to achieve successful communication? We begin with the observation that the shared goal of communication induces a natural division of labor: The resources one agent chooses to allocate toward perspective-taking should depend on their expectations about the other's (...) allocation. We formalize this idea in a resource-rational model augmenting recent probabilistic weighting accounts with a mechanism for (costly) control over the degree of perspective-taking. In a series of simulations, we first derive an intermediate degree of perspective weighting as an optimal trade-off between expected costs and benefits of perspective-taking. We then present two behavioral experiments testing novel predictions of our model. In Experiment 1, we manipulated the presence or absence of occlusions in a director–matcher task. We found that speakers spontaneously modulated the informativeness of their descriptions to account for “known unknowns” in their partner's private view, reflecting a higher degree of speaker perspective-taking than previously acknowledged. In Experiment 2, we then compared the scripted utterances used by confederates in prior work with those produced in interactions with unscripted directors. We found that confederates were systematically less informative than listeners would initially expect given the presence of occlusions, but listeners used violations to adaptively make fewer errors over time. Taken together, our work suggests that people are not simply “mindblind”; they use contextually appropriate expectations to navigate the division of labor with their partner. We discuss how a resource-rational framework may provide a more deeply explanatory foundation for understanding flexible perspective-taking under processing constraints. (shrink)

I present a recent historical case from cosmology—the story of inflationary cosmology—and on its basis argue that solving explanatory problems is a reliable method for making progress in science. In particular, I claim that the success of inflationary theory at solving its predecessor’s explanatory problems justified the theory epistemically, even in advance of the development of novel predictions from the theory and the later confirmation of those predictions.

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of (...) the no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

I will first discuss a peculiarity of the realism-antirealism debate. Some authors defending antirealist positions in a philosophical discussion seem to be inconsistent with what they do when treating scientific subjects. In the latter situation, they behave as realists. This tension can be dissolved by distinguishing different discourses belonging to different levels of philosophical radicality. Depending on the respective level, certain presuppositions are either granted or questioned. I will then turn to a discussion of the miracle argument by discussing a (...) simple example of curve fitting. In the example, multiple use-novel predictions are possible without indicating the truth of the fitting curve. Because this situation has similarities with real scientific cases, it sheds serious doubt upon the miracle argument. Next, I discuss the strategy of selective realism, especially its additional crucial component, the continuity argument. The continuity of some X in a series of theories, with X being responsible for the theories’ use-novel predictions, is taken to be a reliable indicator for the reality of X. However, the continuity of X could as well be due to the similarity of the theories in the series with an empirically very successful theory embodying X, without X being real. Thus, the two main arguments for scientific realism show severe weaknesses. (shrink)

In this paper I comment on a recent paper by [Scerri, E., & Worrall, J. . Prediction and the periodic table. Studies in History and Philosophy of Science, 32, 407–452.] about the role temporally novel and use-novel predictions played in the acceptance of Mendeleev’s periodic table after the proposal of the latter in 1869. Scerri and Worrall allege that whereas temporally novel predictions—despite Brush’s earlier claim to the contrary—did not carry any special epistemic weight, use-novel predictions (...) did indeed contribute to the acceptance of the table. Although I agree with their first claim, I disagree with their second. In order to spell out my disagreement, I not only revisit Scerri and Worrall’s interpretation of crucial historical evidence they have cited in support of the ‘heuristic account’ of use-novel predictions, but I also criticise the latter on general grounds.Keywords: Periodic table; Dmitri Mendeleev; Noble gases; Use-novel predictions; Heuristic account; Ad hoc hypotheses. (shrink)

In Logik der Forschung (1934) and later works, Karl Popper proposed a set of methodological rules for scientists. Among these were requirements that theories should evolve in the direction of increasing content, and that new theories should only be accepted if some of their novel predictions are experimentally confirmed. There are currently two, viable theories of cosmology: the standard cosmological model, and a theory due to Mordehai Milgrom called MOND. Both theories can point to successes and failures, but only (...) MOND has repeatedly made novel predictions that were subsequently found to be correct. Standard-model cosmologists, by contrast, have almost always responded to new observations in a post-hoc manner, adjusting or augmenting their theory as needed to obtain correspondence with the facts. I argue that these methodological differences render a comparison of the two theories in terms of their ‘truthlikeness’ or ‘verisimilitude’ essentially impossible since the two groups of scientists achieve correspondence with the facts in fundamentally different ways, and I suggest that a better guide to the theories’ progress toward the truth might be the methodologies themselves. (shrink)

This is a comment on the paper by Barnes and the responses from Scerri and Worrall, debating the thesis that a fact successfully predicted by a theory is stronger evidence than a similar fact known before the prediction was made. Since Barnes and Scerri both use evidence presented in my paper on Mendeleev’s periodic law to support their views, I reiterate my own position on predictivism. I do not argue for or against predictivism in the normative sense that philosophers of (...) science employ, rather I describe how scientists themselves use facts and predictions to support their theories. I find wide variations, and no support for the assumption that scientists use a single ‘Scientific Method’ in deciding whether to accept a proposed new theory.Keywords: Predictivism; Novel predictions; Accommodation; Periodic law; Periodic table; Dmitri Mendeleev. (shrink)

Criticisms à la Laudan can block the “no miracles” argument for the (approximate) truth of whole theories. Realists have thus retrenched, arguing that at least the individual claims deployed in the derivation of novel predictions should be considered (approximately) true. But for Lyons (2002) there are historical counterexamples even to this weaker “deployment” realism: he lists a number of novel predictions supposedly derived from (radically) false claims. But if so, those successes would seem unexplainable, even by Lyons’ “modest (...) surrealism” or other surrogates to realism. In fact, I argue, some of those predictions were an easy guess, or independently probable in the light of available evidence; hence, they are no counterexamples to deployment realism, for the no miracles argument wouldn’t apply to them. In other instances, pace Lyon, the prediction was actually false, and could be reinterpreted as true only by interpreting as true also the claim from which it was derived; or again, a false claim was employed in the derivation of a true prediction, but inessentially, the essential role being played by a weaker true claim. But as soon as the paradoxical air of such historical cases is explained away in any of these manners, they cease to represent counterexamples to deployment realism. If, as I suggest, all of them can be dealt with by these strategies, a theoretical claim can still be assumed to be true if it is crucial in deriving an improbable novel prediction. (shrink)

While the existence of human cognitive and behavioral diversity is now widely recognized, it is not yet well established how to explain this diversity. In particular, it is still unclear how to determine whether any given instance of human cognitive and behavioral diversity is due to a common psychology that is merely “triggered” differently in different bio-cultural environments, or whether it is due to deeply and fundamentally different psychologies. This paper suggests that, to answer this question, we need to employ (...) subtle theoretical considerations of theory choice—especially the consideration of the complexity-weighted differential predictive successes of the two accounts. To make this clearer, the paper develops a novel analysis of the observed differences in human sharing dispositions. (shrink)

Virtually all philosophers of science have construed fundamental theories as descriptions of entities, properties, and/or structures. Call this the “descriptive-ontological” view. I argue that this view is incorrect, at least insofar as physical theories are concerned. I propose a novel construal of theories that I call the “prescriptive-dynamical” view. The central tenet of this view, roughly put, is that the _essential_ content of fundamental physical theories is a _prescription for interfacing with natural systems and translating local data into compact (...) theoretical language_. The descriptive-ontological aspects of theories, if any, are taken as _inessential_ content on this view: they do not contribute to the predictive success of the theory. Rather than describing _what is there_, the essence of a physical theory is to tell us _what to do_ when interfacing with a physical system. (shrink)

While the existence of human cognitive and behavioral diversity is now widely recognized, it is not yet well established how to explain this diversity. In particular, it is still unclear how to determine whether any given instance of human cognitive and behavioral diversity is due to a common psychology that is merely “triggered” differently in different bio-cultural environments, or whether it is due to deeply and fundamentally different psychologies. This paper suggests that, to answer this question, we need to employ (...) subtle theoretical considerations of theory choice—especially the consideration of the complexity-weighted differential predictive successes of the two accounts. To make this clearer, the paper develops a novel analysis of the observed differences in human sharing dispositions. (shrink)

Relativizing Newton" is a first step towards a simple and beautiful theory of everything. The theory, termed "Information Relativity" (IR) takes a novel approach to physics that overlooks all post-Newtonian physics. It stands on the shoulders of Newtonian dynamics, but modifies it by accounting for the time-travel of information from one reference-frame to another, a fact which somehow was ignored by Galileo Galilee and Isaac Newton, and which remained ill-treated by the all post-Newtonian theories, including Einstein's relativity and quantum (...) theories. Except for the aforementioned correction of classical physics, IR has no axiomatic presumptions, nor arbitrary free parameters. Astonishingly, accounting for the aforementioned delays in information results in a set of simple and beautiful transformations, which explain and predict a great deal of physical phenomena. Most importantly, IR's transformations reveal the mysteries of dark matter, dark energy, and gravity. They also provide a unifying platform for the physics of the too-big (astrophysics and cosmology), and the too-small (small particles dynamics and quantum mechanics). The phenomena explained and predicted successfully by IR include The Michelson-Morley's null-result, "time-dilation" of decaying muons, the neutrino velocities measured by OPERA and other collaborations, particle diffraction in the double-slit experiment, Sagnac Effects, the quantization of orbits in Bohr's hydrogen atom, entanglement, quantum criticality, confinement, asymptotic freedom, solar light bending, gravitational redshift, the Pioneer anomaly, dark matter in galaxies, and the Schwarzschild's black hole. (shrink)

Ever since the heyday of the Vienna Circle, scientific realists have worked hard to document and clarify the structure and growth of truth content in theoretical descriptions. Today, this trait is particularly intense among “selective realists” – realists focused on theory parts with high empirical corroboration rather than whole theories. From their perspective, theories with posits systematically deployed in corroborated novel predictions are, with high probability, descriptively true or contain a proper part that is. Unlike traditional realists, selectivists acknowledge (...) that (a) radical conceptual change is a recurring scientific phenomenon and (b) empirical theories have poor reliability records at the most profound ontological level. At the same time, they point to significant descriptive continuities at intermediate theoretical levels between successful theories and their successors – i.e., a false theory can (and often does) contain parts that succeed as correct descriptions. Selectivists seek to identify those parts. Their approaches limit ontological commitment exclusively to highly confirmed theoretical descriptions; unfortunately, the selection criteria they use seemingly support many regrettable choices. One source of trouble is that extant approaches leave unclear the ontology described by the selected parts. Historical cases and scientific practice gesture toward a functional resolution of this difficulty, but the clues could be more transparent and need elaboration. Otherwise, selectivism has improved in consistency over the last three decades. Current projects emphasize the continuity of well-established scientific content (relating to how entities and processes effectively behave within a specific regime or descriptive level) instead of just the continuity of “structure”. This paper provides some clarifications that arguably clear the road for realist commitment toward functional and effective theoretical content. The proposed functional/effective turn is checked against some plausible objections. (shrink)

Eric Barnes’ The Paradox of Predictivism is concerned primarily with two facts: predictivism (the fact that novel predictions play an important part in scientificconfirmation) and pluralism (the fact that scientific development is not just a matter of isolated individuals judging the truth, but at least partly a matter of trusting legitimate experts). In the middle part of the book, he peers through these two lenses at the tired realist scarecrow of the no-miracles argument. He attempts to reanimate this weatherworn (...) realist argument, contra suggestions by people like me that it should be abandoned. In this paper, I want to get clear on Barnes’ contribution to the debate. He focuses on what he calls the miraculous endorsement argument, which explains not the success of a specific theory but instead the history of successes for an entire research program. The history of successes is explained by reliable and improving methods, which are the flipside of approximately true background theories. Yet, as Barnes notes, the whole story must begin with methods that are at least minimally reliable. Barnes demands that the realist explain the origin of the minimally reliable take-off point, and he suggests a way that the realist might do so. I contend that his explanation still relies on contingent developments and so fails to completely explain the development of take-off theories. However, this line of argument digs into familiar details of the no-miracles argument and overlooks what’s new in Barnes’ approach. By calling attention to pluralism, he reminds us that we need an account of scientific expertise. This is important, I suggest, because expertise is not indefinite. We do not trust specific experts for everything, but only for things within the bounds of their expertise. Drawing these boundaries relies on our own background theories and is only likely to be reliable if our background theories are approximately true. I argue, then, that pluralism gives us reason to be realists (about some things). (shrink)

Intelligent Design (ID) argues for the existence of a designer, postulating it as a theoretical entity of a scientific theory aiming to explain specific characteristics in nature that seems to show design. It is commonly accepted within the Scientific Realism debate, however, that asserting that a scientific theory is successful is not enough for accepting the extramental existence of the entities it postulates. Instead, scientific theories must fulfill additional epistemic requirements, one of which is that they must show successful (...) class='Hi'>novel predictions. Evolutionists typically attack ID by offering cases of bad design, such as the inverted retina of vertebrates. ID defenders defend their position affirming that the inversion of the retina must be a detail of design for an as of yet unknown function. The recent discovery of such a function is celebrated by ID defenders as a triumph over evolutionists. The inverted retina case is a good candidate for a novel prediction in favor of ID. In this paper, I analyze whether this is the case. (shrink)

The accommodation of evidence has been argued to be associated with several methodological problems that should prompt evaluators to lower their confidence in the accommodative theory. Accommodators may overfit their model to data (Hitchcock and Sober, Br J Philos Sci 55(1):1–34, 2004. https://doi.org/10.1093/bjps/55.1.1), hunt for (spurious) associations between variables (Mayo, Error and the growth of experimental knowledge. University of Chicago Press, Chicago, 1996, pp 294–318), or ‘fudge’ their theory in the effort to accommodate a particular datum (Lipton, Inference to the (...) best explanation. Routledge, London, 2004, pp. 164–183). The converse of accommodation, novel prediction, has been offered as a solution. If theorists novelly predict empirical results rather than accommodate those results, the potential risks of accommodation are avoided, and the theory warrants greater confidence. This paper evaluates if the problems of accommodation justify a preference for novel prediction over accommodation for evaluators of a scientific theory. I argue that there is currently insufficient evidence to conclude that the problems of accommodation result in a predictivist advantage in theory confirmation. Taking into consideration the disadvantages of novel prediction and the advantages of accommodation, the impact of further evidential factors, and recent scientific evidence about the consequences of novel prediction and accommodation, novel prediction and accommodation appear roughly on a par, or accommodation is even superior in the current context. (shrink)

To consider metaphysical claims a priori and devoid of empirical content, is a rather commonplace received opinion. This paper attempts an exploration of a contemporary philosophical heresy: it is possible to test metaphysical claims if they play an indispensable role in producing empirical success, i.e. novel predictions. To do so one, firstly, needs to express the metaphysical claims employed in the logico-mathematical language of a scientific theory, i.e. to explicate them. Secondly, one should have an understanding of what (...) it is to test and to verify or to falsify a metaphysical claim. Finally, one also need to consider the philosophical practice of testing a metaphysical claim. These three aspects are introduced in this paper and they are illustrated by means of the metaphysical concept of common cause and the principle of the common cause. (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)

In “A Confutation of Convergent Realism,” Larry Laudan presents the realist with these fascinating challenges:What,then,of realism itself as a ‘scientific’ hypothesis?…If realism has made some novel predictions or been subjected to carefully controlled tests, one does not learn about it from the literature of contemporary realism. (1981, p. 46.)He then goes on to say:No proponent of realism has sought to show that realism satisfies those stringent empirical demands which the realist himself minimally insists on when appraising scientific theories. (1981, (...) p. 46)Not only do I fully endorse what Laudan says in these passages, I think it is time to take him up on these challenges.Laudan’s position has been that scientific progress can be explained without having to appeal to verisimilitude. Instead, we explain the success of a scientific theory in terms of its subjugation to the cannons of experimental controls: those theories that have been put through proper testing during the course of their formulation are the ones that are most likely to be reliable. (1984, pp. 96-101). (shrink)

The predictive inadequacy of the social sciences is well documented, and philosophers have sought to diagnose it. This paper examines Brian Epstein’s recent diagnosis. He argues that the social sciences treat the social world as entirely composed of individual people. Instead, social scientists should recognize that material, non-individualistic entities determine the social world, as well. First, I argue that Epstein’s argument both begs the question against his opponents and is not sufficiently charitable. Second, I present doubts that his proposal (...) will improve predictive success for the social sciences, which I support with Edith Penrose’s resource-based theory of the firm. (shrink)

Bayesian confirmation theory, as traditionally interpreted, treats the temporal relationship between the formulation of a hypothesis and the confirmation (or recognition) of evidence entailed by that hypothesis merely as a component of the psychology of discovery and acceptance of a hypothesis. The temporal order of these events is irrelevant to the logic of rational theory choice. A few years ago Richmond Campbell and Thomas Vinci offered a reinterpretation of Bayes' Theorem in defense of the view that the temporal relationship between (...) hypothesis and evidence really does matter. More specifically, they advocated the thesis that successful predictions implied by scientific hypothesis H will increase the degree of confirmation of H only if they are novel predictions in the following sense; Evidence E is heuristically novel with respect to hypothesis H if and only if H was not deliberately designed to explain E (if E has already been corroborated) or in anticipation of E (if E is regarded as likely to be corroborated at some future date). Campbell and Vinci argue that the traditional interpretation of Bayes' Theorem misconstrues the significance of predictive novelty by ignoring heuristic novelty. In this paper I review the formal component of their preferred interpretation and demonstrate that it fails to establish that heuristic novelty has any special effect on theory confirmation. That is, even on their revisionist interpretation, regardless of whether H was deliberately designed to explain known evidence E (or in anticipation of suspected E), or whether H was designed without any awareness of the entailment relationship between H and E, Bayes' Theorem will generate the same epistemic probability for hypothesis H. Cases where new evidence was not foreseen at the time a hypothesis first emerged do not carry any more epistemic weight than they would have if such evidence had been foreseen. * Research on this paper was supported by an NEH summer grant. My thanks also to Richmond Campbell and Thomas Vinci for their reply to my initial evaluation of their position (in private correspondence), which compelled me to reconsider their arguments more carefully. (shrink)