According to realists, theories are successful because they are true, but according to selectionists, theories are successful because they have gone through a rigorous selection process. Wray claims that the realist and selectionist explanations are rivals to each other. Lee objects that they are instead complementary to each other. In my view, Lee’s objection presupposes that the realist explanation is true, and thus it begs the question against selectionists. By contrast, the selectionist explanation invokes a scientific (...) theory, and thus it is not clear whether it is a realist explanation or an antirealist explanation. Finally, the six new arguments for scientific realism in the literature truly complement the no-miracles argument. (shrink)

I identify two versions of the scientific anti-realist’s selectionist explanation for the success of science: Bas van Fraassen’s original and K. Brad Wray’s newer interpretation. In Wray’s version, psycho-social factors internal to the scientific community – viz. scientists’ interests, goals, and preferences – explain the theory-selection practices that explain theory-success. I argue that, if Wray’s version were correct, then science should resemble art. In art, the artwork-selection practices that explain artwork-success appear faddish. They (...) are prone to radical change over time. Theory-selection practices that explain theory-success in science are however not faddish. They are mostly stable; that is, long-lived and consistent over time. This is because scientists (explicitly or implicitly) subscribe to what I will call the testability norm: scientific theories must make falsifiable claims about the external physical world. The testability norm and not psycho-sociology explains the theory-selection practices that explain theory-success in science. Contra Wray, scientific anti-realists can then maintain that the external physical world (as expressed in the testability norm) explains theory-success. (shrink)

Book Review K. Brad Wray: Resisting Scientific Realism. Cambridge University Press: Cambridge 2018, xii + 224 pp, £ 75.00 (Hardcover), ISBN: 9781108231633. By Ragnar van der Merwe. In The Journal for the General Philosophy of Science.

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)

David Hull accounts for the success of science in terms of an invisible hand mechanism, arguing that it is difficult to reconcile scientists' self-interestedness or their desire for recognition with traditional philosophical explanations for the success of science. I argue that we have less reason to invoke an invisible hand mechanism to explain the success of science than Hull implies, and that many of the practices and institutions constitutive of science are intentionally designed (...) by scientists with an eye to realizing the very goals that Hull believes need to be explained by reference to an invisible hand mechanism. Thus, I reduce the scope of Hull's invisible hand explanation and supplement it by appealing to a hidden hand explanation. (shrink)

Arguments for the effectiveness, and even the indispensability, of mathematics in scientific explanation rely on the claim that mathematics is an effective or even a necessary component in successful scientific predictions and explanations. Well-known accounts of successful mathematical explanation in physical science appeals to scientists’ ability to solve equations directly in key domains. But there are spectacular physical theories, including general relativity and fluid dynamics, in which the equations of the theory cannot be solved directly in target (...) domains, and yet scientists and mathematicians do effective work there (McLarty 2023, Elder 2023). Building on extant accounts of structural scientific explanation (Bokulich 2011, Leng 2021), I argue that philosophical accounts of the role of equations in scientific explanation need not rely on scientists’ ability to solve equations independently of their understanding of the empirical or experimental context. For instance, the process of formulating solutions to equations can involve significant appeal to information about experimental contexts (Curiel 2010) or of physically similar systems (Sterrett 2023). Working from a close analysis of work in fluid mechanics by Martin Bazant and Keith Moffatt (2005), I propose an account of heuristic structural explanation in mathematics (Einstein 1921, Pincock 2021), which explains how physical explanations can be constructed even in domains where basic equations cannot be solved directly. (shrink)

Several metaphysical naturalists argue that the success of science, together with the claim that scientists adhere to methodological naturalism, amounts to strong evidence for metaphysical naturalism. I call this the scientific-success argument. It is argued that the scientific-success argument is similar to the no-miracles argument for realism in philosophy of science. On the no-miracles argument, the success of science is taken as strong evidence that scientific theories are true. Based (...) on this similarity, some considerations relevant to one argument may also be relevant to the other. One particular consideration is explored. The selectionist response to the no-miracles argument states that on an evolutionary model of science, in which scientific theories are accepted only after surviving a rigorous selection process, the no-miracles argument fails. The selectionist response also applies to the scientific-success argument. If scientific theories are selected for success, we do not need to explain the success of science by appealing to metaphysical naturalism. (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)

This is a forthcoming section for the book "Theism and Atheism: Opposing Arguments in Philosophy", edited by Graham Oppy, Gregory Dawes, Evan Fales, Joseph Koterski, Mashhad Al-Allaf, Robert Fastiggi, and David Shatz. I was asked to write a brief essay on whether naturalism or theism can successfully explain the distribution of suffering in our world. Wheras another section covers the possibility that suffering is evidence against theism, my essay is concerned only with the ability for either naturalism or theism to (...) explain suffering. I argue that, for naturalists, suffering is not to be explained by either philosophers of religion or theologians. Instead, naturalists believe that suffering should be explained by the cognitive and social sciences, perhaps in conjunction with political philosophy and philosophy of mind. Moreover, naturalists may take suffering to be an important reason for action. In a world without a transcendent, supernatural being to watch over us, we can only depend upon each other to ameliorate existing conditions, to the extent that they can be ameliorated. On the other hand, theistic explanations of the distibution of suffering slip very easily into problematic theologies when they try to offer explicit explanations for suffering. For example, the world's most vulnerable people are often those who suffer the most, whereas oppressors are often able to prosper. That is, theistic explanations of our world's suffering easily slip into, e.g., the just world fallacy, racist ideology (i.e., that God favors some race(s) of people over others), or patriarchal ideology. Instead of offering an explicit explanation, theists should instead be skeptical theists -- i.e., they should argue that an explanation for our world's suffering is beyond our ken. While skeptical theism avoids the aforementioned problematic implications, if skeptical theism is true, then our world's suffering cannot be fully explained. (shrink)

According to the Nomological Argument, observed regularities in nature are best explained by an appeal to a supernatural being. A successful explanation must avoid two perils. Some explanations provide too little structure, predicting a universe without regularities. Others provide too much structure, thereby precluding an explanation of certain types of lawlike regularities featured in modern scientific theories. We argue that an explanation based in the creative, intentional action of a supernatural being avoids these two perils whereas (...) leading competitors do not. Although our argument falls short of a full defense, it does suggest that the Nomological Argument is worthy of philosophical attention. (shrink)

As formulated by atheist Jeffery Jay Lowder, the Evidential Argument from the History of Science, or AHS, is premised on the observation that over the course of modern history, naturalistic explanations have progressively overtaken supernaturalistic explanations. That history, says Lowder, constitutes evidence that metaphysical naturalism is true (hence that theism is false). But it’s possible that the historical pattern as described is not actually the result of any genuine explanatory virtues of naturalistic over supernaturalistic explanations. If there are (...) good reasons to suspect that naturalistic explanations fail to accurately or adequately explain the world around us, then we would not have sufficient grounds to follow Lowder’s argument to its conclusion. Here I will present three reasons to suspect that naturalistic explanations fail to accurately or adequately explain the world around us: (1) an alternative reading of the history of science according to pessimistic induction; (2) the arbitrary epistemic requirements of methodological naturalism; and (3) the ongoing resistance of certain phenomena (the origins of the universe and of life on earth) to any naturalistic explanations that are coherent and relatively simple. (shrink)

I examine some of the key scientific pre-commitments of modern psychology, and argue that their adoption has the unintended consequence of rendering a purely psychological analysis of mind indistinguishable from a purely biological treatment. And, since these pre-commitments sanction an “authority of the biological”, explanation of phenomena traditionally considered the purview of psychological analysis is fully subsumed under the biological. I next evaluate the epistemic warrant of these pre-commitments and suggest there are good reasons to question their applicability to (...) psychological science. I conclude that experiential aspects of reality give us reason to remain open to the need for psychological explanation in the treatment of mind. (shrink)

I argue that a certain type of naturalist should not accept a prominent version of the no-miracles argument (NMA). First, scientists (usually) do not accept explanations whose explanans-statements neither generate novel predictions nor unify apparently disparate established claims. Second, scientific realism (as it appears in the NMA) is an explanans that makes no new predictions and fails to unify disparate established claims. Third, many proponents of the NMA explicitly adopt a naturalism that forbids philosophy of science from using (...) any methods not employed by science itself. Therefore, such naturalistic philosophers of science should not accept the version of scientific realism that appears in the NMA. (shrink)

A background assumption of this paper is that the repertoire of inference schemes available to humanity is not fixed, but subject to change as new schemes are invented or refined and as old ones are obsolesced or abandoned. This is particularly visible in areas like health and environmental sciences, where enormous societal investment has been made in finding ways to reach more dependable conclusions. Computational modeling of argumentation, at least for the discourse in expert fields, will require the possibility of (...) modeling change in a stock of schemes that may be applied to generate conclusions from data. We examine Randomized Clinical Trial, an inference scheme established within medical science in the mid-20th Century, and show that its successful defense by means of practical reasoning allowed for its black-boxing as an inference scheme that generates (and warrants belief in) conclusions about the effects of medical treatments. Modeling the use of a scheme is well-understood; here we focus on modeling how the scheme comes to be established so that it is available for use. (shrink)

In this paper, I argue that the “positive argument” for Constructive Empiricism (CE), according to which CE “makes better sense of science, and of scientific activity, than realism does” (van Fraassen 1980, 73), is an Inference to the Best Explanation (IBE). But constructive empiricists are critical of IBE, and thus they have to be critical of their own “positive argument” for CE. If my argument is sound, then constructive empiricists are in the awkward position of (...) having to reject their own “positive argument” for CE by their own lights. (shrink)

The idea that science is objective, or able to achieve objectivity, is in large part responsible for the role that science plays within society. But what is objectivity? The idea of objectivity is ambiguous. This paper distinguishes between three basic forms of objectivity. The first form of objectivity is ontological objectivity: the world as it is in itself does not depend upon what we think about it; it is independent of human thought, language, conceptual activity or experience. The (...) second form of objectivity is the objectivity of truth: truth does not depend upon what we believe or justifiably believe; truth depends upon the way reality itself is. The third form of objectivity is epistemic objectivity: this form of objectivity resides in the scientific method which ensures that subjective factors are excluded, and only epistemically relevant factors play a role in scientific inquiry. The paper considers two problems that arise for the notion of epistemic objectivity: the theory-dependence of observation and the variability of the methods of science. It is argued that the use of shared standard procedures ensures the objectivity of observation despite theory-dependence. It is argued that the variability of methods need not lead to epistemic relativism about science. The paper concludes with the realist suggestion that the best explanation of the success of the sciences is that the methods employed in the sciences are highly reliable truth-conducive tools of inquiry. The objectivity of the methods of the sciences leads to the objective truth about the objective world. (shrink)

Our aim in this paper is to bring the woefully neglected literature on predictive modeling to bear on some central questions in the philosophy of science. The lesson of this literature is straightforward: For a very wide range of prediction problems, statistical prediction rules (SPRs), often rules that are very easy to implement, make predictions than are as reliable as, and typically more reliable than, human experts. We will argue that the success of SPRs forces us to reconsider (...) our views about what is involved in understanding, explanation, good reasoning, and about how we ought to do philosophy of science. (shrink)

I explore the process of changes in the observability of entities and objects in science and how such changes impact two key issues in the scientific realism debate: the claim that predictively successful elements of past science are retained in current scientific theories, and the inductive defense of a specific version of inference to the best explanation with respect to unobservables. I provide a case-study of the discovery of radium by Marie Curie in order to show that (...) the observability of some entities can change and that such changes are relevant for arguments seeking to establish the reliability of success-to-truth inferences with respect to unobservables. (shrink)

Alex Rosenberg’s latest book purports to establish that narrative history cannot have any epistemic value. Rosenberg argues not for the replacement of narrative history by something more science-like, but rather the end of histories understood as an account of human doings under a certain description. This review critiques three of his main arguments: 1) narrative history must root its explanations in folk psychology, 2) there are no beliefs nor desires guiding human action, and 3) historical narratives are morally and (...) ethically pernicious. Rosenberg’s book reprises themes about action explanation he first rehearsed 40 years ago, albeit with neuroscience rather than sociobiology now “preempting” explanations that trade on folk psychological notions. Although Rosenberg’s argument strategy has not altered, the review develops a number of reasons as to why his approach now lacks any plausibility as a strategy for explaining histories, much less a successful one. (shrink)

This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...) It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr’s theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop. (shrink)

_ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as (...) a case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call _tendential prediction_. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of (...) explanation cannot explain such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

How confident does the history of science allow us to be about our current well-tested scientific theories, and why? The scientific realist thinks we are well within our rights to believe our best-tested theories, or some aspects of them, are approximately true.2 Ambitious arguments have been made to this effect, such as that over historical time our scientific theories are converging to the truth, that the retention of concepts and claims is evidence for this, and that there can be (...) no other serious explanation of the success of science than that its theories are approximately true. There is appeal in each of these ideas, but making such strong claims has tended to be hazardous, leaving us open to charges that many typical episodes in the history of science just do not fit the model. (See, e.g., Laudan 1981.) Arguing for a realist attitude via general claims – properties ascribed to sets of theories, trends we see in progressions of theories, and claimed links between general properties like success and truth that apply or fail to apply to any theory regardless of its content – is like arguing for or via a theory of science, which brings with it the obligation to defend that theory. I think a realist attitude toward particular scientific theories for which we have evidence can be maintained rationally without such a theory, even in the face of the pessimistic induction over the history of science. The starting point at which questions arise as to what we have a right to believe about our theories is one where we have theories and evidence for them, and we are involved in the activity of apportioning our belief in each particular theory or hypothesis in accord with the strength of the particular evidence.3 The devil’s advocate sees our innocence and tries his best to sow seeds of doubt. If our starting point is as I say, though, the innocent believer in particular theories does not have to play offense and propose sweeping views about science in general, but only to respond to the skeptic’s challenges; the burden of initial argument is on the skeptic.. (shrink)

In this dissertation I achieve the following: (1) I present motivating criteria for a general comprehensive theory of scientific explanation. I review historical approaches to modeling explanation in light of these criteria. (2) I present New Mechanist Explanation ("NME") as the leading candidate for a contemporary, complete theory of scientific explanation. (3) I present constraints on the applicability of New Mechanism in modeling biology, chemistry, and physics. I argue for the unsuitability of NME as a candidate (...) for a general theory of explanation due to its significant omissions of explanatory content and subsequent incompleteness. (4) I present arguments for the indispensable explanatory power of mathematics in science, noting that much of NME's failures are owed to its poor integration of mathematical explanation as applied to science. (5) I propose a Rational-Relational theory of explanation(“RRE”). I present RRE in detail and demonstrate it as a true working general theory of explanation which best meets the motivating criteria presented in (1). I disambiguate RRE from structural explanation ("SE"). I show that historical models of explanation, including the deductive nomological (DNE) model, statistical relevance ("SRE") model, structural model (SE) and unification model ("UE") may be successfully treated as sub-classes of explanation within the scope of RRE. I provide a rubric for selecting amongst sub-theories of explanation under RRE in the purpose of highlighting particular features of relational explanations. (6) In conclusion, I argue that philosophers of science should move forward using RRE as a general model of scientific explanation as a working alternative to the incomplete model of NME. (shrink)

The scientific realism debate has now reached an entirely new level of sophistication. Faced with increasingly focused challenges, epistemic scientific realists have appropriately revised their basic meta-hypothesis that successful scientific theories are approximately true: they have emphasized criteria that render realism far more selective and, so, plausible. As a framework for discussion, I use what I take to be the most influential current variant of selective epistemic realism, deployment realism. Toward the identification of new case studies that challenge this form (...) of realism, I break away from the standard list and look to the history of celestial mechanics, with an emphasis on twentieth century advances. I then articulate two purely deductive arguments that, I argue, properly capture the historical threat to realism. I contend that both the content and form of these novel challenges seriously threaten selective epistemic realism. I conclude on a positive note, however, arguing for selective realism at a higher level. Even in the face of threats to its epistemic tenet, scientific realism need not be rejected outright: concern with belief can be bracketed while nonetheless advocating core realist tenets. I show that, in contrast with epistemic deployment realism, a purely axiological scientific realism can account for key scientific practices made salient in my twentieth century case studies. And embracing the realists favored account of inference, inference to the best explanation, while pointing to a set of the most promising alternative selective realist meta-hypothesis, I show how testing the latter can be immensely valuable to our understanding of science. (shrink)

Philosophy of science is showing an increasing interest in the social aspects and the social organisation of science—the ways social values and social interactions and structures play a role in the creation of knowledge and the ways this role should be taken into account in the organisation of science and science policy. My thesis explores a number of issues related to this theme. I argue that a prominent approach to the social organisation of science—Philip Kitcher’s (...) well-ordered science—runs into a number of problems. They undermine its philosophical plausibility and practical usefulness. I agree with Kitcher that arguments about the social organisation of science should recognise profound societal consequences of science. Kitcher argues that the appropriate organisation of science should therefore take into account laypersons’ values and needs when making decisions concerning research planning, evaluation and application. My criticisms show that this is not enough. Drawing on Helen Longino ideas, I argue that laypersons’ perspectives and knowledge may also be relevant when doing research. In order to show how more inclusive research practices may be possible, I discuss connections between philosophy of science and some developments in science policy, which has also recently shown considerable interest in democratic participation. I demonstrate how public participation experiments in science policy may sometimes be close enough to what the philosopher would recommend. Their analysis can thus be helpful for understanding how societal developments may provide opportunities for the involvement of laypersons in science and what factors may endanger its success. I conclude that a way to pursue a more socially relevant philosophy of science is to focus on the points of contact and possibilities of cooperation between philosophical proposals and these public participation initiatives. (shrink)

Van Fraassen explains rejections and asymmetries in science in terms of his contextual theory of explanation in the same way that scientists explain observable phenomena in the world in terms of scientific theories. I object that van Fraassen’s skeptical view regarding inference to the best explanation together with the English view of rationality jointly imply that the contextual theory is not rationally compelling, so van Fraassen and his epistemic colleagues can rationally disbelieve it. Prasetya replies that the (...) truth of the contextual theory coincides with its empirical adequacy, so the contextual theory is compelling. He also replies that the contextual theory is compelling, provided that van Fraassen’s argument for it instantiates a compelling subset of IBE. I argue that Prasetya’s replies either fail or help scientific realism. (shrink)

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular (...) system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal; and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps to unify essential concepts of biological networks. (shrink)

Broadly speaking, the contemporary scientific realist is concerned to justify belief in what we might call theoretical truth, which includes truth based on ampliative inference and truth about unobservables. Many, if not most, contemporary realists say scientific realism should be treated as ‘an overarching scientific hypothesis’ (Putnam 1978, p. 18). In its most basic form, the realist hypothesis states that theories enjoying general predictive success are true. This hypothesis becomes a hypothesis to be tested. To justify our belief in (...) the realist hypothesis, realists commonly put forward an argument known as the ‘no-miracles argument’. With respect to the basic hypothesis this argument can be stated as follows: it would be a miracle were our theories as successful as they are, were they not true; the only possible explanation for the general predictive success of our scientific theories is that they are true. (shrink)

This paper argues for several related theses. First, the epistemological position that knowledge requires safe belief can be motivated by views in the philosophy of science, according to which good explanations show that their explananda are robust. This motivation goes via the idea—recently defended on both conceptual and empirical grounds—that knowledge attributions play a crucial role in explaining successful action. Second, motivating the safety requirement in this way creates a choice point—depending on how we understand robustness, we'll end up (...) with different conceptions of safety in epistemology. Lastly, and most controversially, there's an attractive choice at this point that will not vindicate some of the most influential applications of the safety-theoretic framework in epistemology, e.g., Williamson's arguments against the KK principle, and luminosity. (shrink)

Recently, several philosophers have defended an explanatory argument that supposedly provides novel empirical grounds for accepting the type identity theory of phenomenal consciousness. They claim that we are justified in believing that the type identity thesis is true because it provides the best explanation for the correlations between physical properties and phenomenal properties. In this paper, I examine the actual role identities play in science and point out crucial shortcomings in the explanatory argument. I show that (...) the supporters of the argument have failed to show that the identity thesis provides a satisfactory explanation for the correlations between physical and phenomenal properties. Hence, the explanatory argument, as it stands, does not provide new grounds for accepting the type identity theory. (shrink)

In a recent paper, Erasmus et al. (2021) defend the idea that the ambiguity of the term “explanation” in explainable AI (XAI) can be solved by adopting any of four different extant accounts of explanation in the philosophy of science: the Deductive Nomological, Inductive Statistical, Causal Mechanical, and New Mechanist models. In this chapter, I show that the authors’ claim that these accounts can be applied to deep neural networks as they would to any natural phenomenon is (...) mistaken. I also provide a more general argument as to why the notion of explainability as it is currently used in the XAI literature bears little resemblance to the traditional concept of scientific explanation. It would be more fruitful to use the label “understandable AI” to avoid the confusion that surrounds the goal and purposes of XAI. In the second half of the chapter, I argue for a pragmatic conception of understanding that is better suited to play the central role attributed to explanation in XAI. Following De Regt (2017) and Kuorikoski and Ylikoski (2015), the conditions of satisfaction for understanding an ML system are fleshed out in terms of an agent’s success in using the system. (shrink)

Introduction Reza Davari Ardakni, the Iranian contemporary philosopher, distinguishes development from Western modernity; in that it considers modernity as natural and organic changes that Europe has gone through, but sees development as a planned design for implementing modernity in other countries. As a result, the closedness of development concerns only the developing countries, not Western modern ones. Davari emphasizes that the Western modernity has a universality that pertains to a unique reason and a unified world. The only way of thinking (...) in this world is a philosophical thought based on human self-centered reason, and given the pervasiveness of Western civilization. Therefore, Davari does not consider Westernization as mere imitation of Western customs and methods, but rather as a way of existence in the world. Westernization is a subjective view of the world and beings. Westernization is not optional, enabling non-Western people to avoid it. According to the Westernization scenario, the world today is entirely Westernized, and Davari considers Westernization as the inevitable fate of the people of this era, seeing two alternatives for them, both of which ultimately lead to the same destination, which is to embrace development; either they seize the power of science and technology and join the process of global modernization and participate in it, or they become subdued by this process and accept it without participation. Davari regards the first type of Westernization as active and the second type as passive. Problematique Therefore, underdevelopment is not a concept of the ancient world, nor even of a world between the ancient and the modern, or on the threshold of modernization. Underdevelopment is a condition of suspension and timelessness and being exposed to modernization. To escape the paradox of underdevelopment, which is the inevitable historical fate of non-modernized societies, Davari sees no way out other than embracing development. In other words, Westernized societies, which have become confused due to modernization, have no escape route other than turning to development. Therefore, some critics of Davari accuse the theory of Westernization of being a theoretical rupture. M. T. Tabatabaei, by rejecting the theoretical rupture in the theory of Westernization, believes that in the argument of Davari, we are only faced with a shift from a philosophical to an intellectual level. Tabatabaei, by avoiding providing a philosophical response to the critics of the theoretical rupture, believes that the introduction of active Westernization and collaboration in science and technology as a solution to escape from underdevelopment conditions, is only a shift from a philosophical level to an intellectual level and does not involve a rupture. Therefore, it seems that the philosophical issue of how or the possibility of escaping from underdevelopment conditions is still an open non answered problem. In this study, seeking a philosophical answer to this problem, an attempt has been made to summarize Davari's definitions of development, underdevelopment, participation in the world of science, and the role of humanities and social sciences in development, using his writings and speeches. It is proposed that a way to escape from the clesedness of development based on Davari's views, is to make use of analytical method with emphasizing on concepts and theories of the philosophy and metaphysics of science. Argument According to Davari, the social and human sciences that are responsible for development planning in underdeveloped societies must consider the characteristics of underdevelopment in order to facilitate the transition to more favorable conditions. Davari identifies the following conditions for successful development: 1) replacing tradition with science as the organizing and coordinating principle in society, 2) recognizing the universality of philosophy and science of the Western modernity and the impossibility of blindly imitation and adopting it, 3) inevitability of actively engaging and interacting with development, 4) recognizing the internal dynamics of scientific progress and avoiding authoritarian control, and 5) promoting free participation in the scientific paradigms. Therefore, Davari suggests the following steps towards development: 1) recognizing and understanding the problems of society and the local ecosystem, 2) understanding the philosophical and cultural foundations of Western civilization, 3) understanding the historical context and paradigms of science, 4) understanding the philosophical and metaphysical foundations of science, 5) recognizing the intellectual and philosophical capacities of our own community, and 6) reflecting our own philosophical and metaphysical assumptions in the scientific world in a way that is compatible with scientific methods. Given the motivations for change in science at both the global and national levels, including the emergence of heterodox or indigenous sciences, and the inevitable nature of development, Davari points to the possibility of a path between absolute rejecting or accepting the mainstream social and human sciences. However, this path is challenging and contingent upon the aforementioned conditions and steps of transition. Conclusion It is necessary to seek this path within the realm of the philosophy and metaphysics of science, particularly in the origins and foundations of the social and human sciences. Research in the metaphysics and philosophy of the social sciences provides the opportunity for active scientific engagement in the scientific paradigms and a reconsideration of the foundations of science, allowing for different philosophical foundations while are compatible with scientific methods. Successfully finding a path between absolute rejecting or accepting the existing social sciences will lead to an internal transformation within the field of science and, in fact, will advance the boundaries of knowledge. Therefore, it is possible, while adhering to the conditions of transition and actively participating in the world of science and technology, and accepting the unity of modernity and avoiding selectivity and imitation, to search for a way to overcome the closedness of development through a reconsideration of the philosophical and metaphysical foundations of science, while recognizing our own intellectual heritage and critically assessing Western science and technology. (shrink)

Kyle Stanford has recently claimed to offer a new challenge to scientific realism. Taking his inspiration from the familiar Pessimistic Induction (PI), Stanford proposes a New Induction (NI). Contra Anjan Chakravartty’s suggestion that the NI is a ‘red herring’, I argue that it reveals something deep and important about science. The Problem of Unconceived Alternatives, which lies at the heart of the NI, yields a richer anti-realism than the PI. It explains why science falls short when it falls (...) short, and so it might figure in the most coherent account of scientific practice. However, this best account will be antirealist in some respects and about some theories. It will not be a sweeping antirealism about all or most of science. (shrink)

The ‘psychologist’s green thumb’ refers to the argument that an experimenter needs an indeterminate set of skills to successfully replicate an effect. This argument is sometimes invoked by psychological researchers to explain away failures of independent replication attempts of their work. In this paper, I assess the psychologist’s green thumb as a candidate explanation for individual replication failure and argue that it is potentially costly for psychology as a field. I also present other, more likely reasons for (...) these replication failures. I conclude that appealing to a psychologist’s green thumb is not a convincing explanation for replication failure. (shrink)

The appeal to mechanisms in scientific explanation is commonplace in contemporary philosophy of science. In short, mechanists argue that an explanation of a phenomenon consists of citing the mechanism that brings the phenomenon about. In this paper, we present an argument that challenges the universality of mechanistic explanation: in explanations of the contemporary features of the eukaryotic cell, biologists appeal to its symbiogenetic origin and therefore the notion of symbiogenesis plays the main explanatory role. We (...) defend the notion that symbiogenesis is non-mechanistic in nature and that any attempt to explain some of the contemporary features of the eukaryotic cell mechanistically turns out to be at least insufficient and sometimes fails to address the question that is asked. Finally, we suggest that symbiogenesis is better understood as a pragmatic scientific law and present an alternative non-mechanistic model of scientific explanation. In the model we present, the use of scientific laws is supposed to be a minimal requirement of all scientific explanations, since the purpose of a scientific explanation is to make phenomena expectable. Therefore, this model would help to understand biologists’ appeal to the notion of symbiosis and thus is shown to be better, for the case under examination, than the mechanistic alternative. (shrink)

Moti Mizrahi has argued that Thomas Kuhn does not have a good argument for the incommensurability of successive scientific paradigms. With Rouse, Andersen, and others, I defend a view on which Kuhn primarily was trying to explain scientific practice in Structure. Kuhn, like Hilary Putnam, incorporated sociological and psychological methods into his history of science. On Kuhn’s account, the education and initiation of scientists into a research tradition is a key element in scientific training and in his (...) class='Hi'>explanation of incommensurability between research paradigms. The first part of this paper will explain and defend my reading of Kuhn. The second part will probe the extent to which Kuhn’s account can be supported, and the extent to which it rests on shaky premises. That investigation will center on Moti Mizrahi’s project, which aims to transform the Kuhnian account of science and of its history. While I do defend a modified kind of incommensurability, I agree that the strongest version of Kuhn’s account is steadfastly local and focused on the practice of science. (shrink)

The basic task of the essay is to exhibit science as a rational enterprise. I argue that in order to do this we need to change quite fundamentally our whole conception of science. Today it is rather generally taken for granted that a precondition for science to be rational is that in science we do not make substantial assumptions about the world, or about the phenomena we are investigating, which are held permanently immune from empirical appraisal. (...) According to this standard view, science is rational precisely because science does not make a priori metaphysical presuppositions about the world forever preserved from possible empirical refutation. It is of course accepted that an individual scientist, developing a new theory, may well be influenced by his own metaphysical presuppositions. In addition, it is acknowledged that a successful scientific theory, within the context of a particular research program, may be protected for a while from refutation, thus acquiring a kind of temporary metaphysical status, as long as the program continues to be empirically progressive. All such views unite, however, in maintaining that science cannot make permanent metaphysical presuppositions, held permanently immune from objective empirical evaluation. According to this standard view, the rationality of science arises, not from the way in which new theories are discovered, but rather from the way in which already formulated theories are appraised in the light of empirical considerations. And the fundamental problem of the rationality of science--the Humean problem of induction--concerns precisely the crucial issue of the rationality of accepting theories in the light of evidence. In this essay I argue that this widely accepted standard conception of science must be completely rejected if we are to see science as a rational enterprise. In order to assess the rationality of accepting a theory in the light of evidence it is essential to consider the ultimate aims of science. This is because adopting different aims for science will lead us, quite rationally, to accept different theories in the light of evidence. I argue that a basic aim of science is to explain. At the outset science simply presupposes, in a completely a priori fashion, that explanations can be found, that the world is ultimately intelligible or simple. In other words, science simply presupposes in an a priori way the metaphysical thesis that the world is intelligible, and then seeks to convert this presupposed metaphysical theory into a testable scientific theory. Scientific theories are only accepted insofar as they promise to help us realize this fundamental aim. At once a crucial problem arises. If scientific theories are only accepted insofar as they promise to lead us towards articulating a presupposed metaphysical theory, it is clearly essential that we can choose rationally, in an a priori way, between all the very different possible metaphysical theories that can be thought up, all the very different ways in which the universe might ultimately be intelligible. For holding different aims, accepting different metaphysical theories conceived of as blueprints for future scientific theories will, quite rationally, lead us to accept different scientific theories. Thus it is only if we can choose rationally between conflicting metaphysical blueprints for future scientific theories that we will be in a position to appraise rationally the acceptability of our present day scientific theories. We thus face the crucial problem: How can we choose rationally between conflicting possible aims for science, conflicting metaphysical blueprints for future scientific theories? It is only if we can solve this fundamental problem concerning the aims of science that we can be in a position to appraise rationally the acceptability of existing scientific theories. There is a further point here. If we could choose rationally between rival aims, rival metaphysical blueprints for future scientific theories, then we would in effect have a rational method for the discovery of new scientific theories! Thus we reach the result: there is only a rational method for the appraisal of existing scientific theories if there is a rational method of discovery. I shall argue that the aim-oriented theory of scientific inquiry to be advocated here succeeds in exhibiting science as a rational enterprise in that it succeeds in providing a rational procedure for choosing between rival metaphysical blueprints: it thus provides a rational, if fallible, method of discovery, and a rational method for the appraisal of existing scientific theories--thus resolving the Humean problem. In Part I of the essay I argue that the orthodox conception of science fails to exhibit science as a rational enterprise because it fails to solve the Humean problem of induction. The presuppositional view advocated here does however succeed in resolving the Humean problem. In Part II of the essay I spell out the new aim-oriented theory of scientific method that becomes inevitable once we accept the basic presuppositional viewpoint. I argue that this new aim oriented conception of scientific method is essentially a rational method of scientific discovery, and that the theory has important implications for scientific practice. (shrink)

The Successive Addition Argument (SAA) is one of the key arguments espoused by William Lane Craig for the thesis that the universe began to exist. Recently, Malpass, Mind, 131(523), 786–804 (2021) has developed a challenge to the SAA by way of constructing a counterexample that originates in the work of Fred Dretske. In this paper, I show that the Malpass-Dretske counterexample is in fact no counterexample to the argument. Utilizing a distinction between properties of members and properties of (...) collections, I argue that Malpass’ counterexample has no bearing on the soundness of the SAA. I also develop a novel parity argument against Malpass’ argument that I demonstrate can only be resolved by way of the aforementioned analysis. (shrink)

The dominant view today on evolutionary progress is that it has been thoroughly debunked. Even value-neutral progress concepts are seen to lack important theoretical underpinnings: natural selection provides no rationale for progress, and natural selection need not even be invoked to explain large-scale evolutionary trends. In this paper I challenge this view by analysing how natural selection acts in heterogeneous environments. This not only undermines key debunking arguments, but also provides a selectionist rationale for a pattern of “evolutionary unfolding”, (...) where life radiates across an increased range of exploitation of environmental heterogeneity. (shrink)

When natural selection theory was presented, much active philosophical debate, in which Darwin himself participated, centered on its hypothetical nature, its explanatory power, and Darwin's methodology. Upon first examination, Darwin's support of his theory seems to consist of a set of claims pertaining to various aspects of explanatory success. I analyze the support of his method and theory given in the Origin of Species and private correspondence, and conclude that an interpretation focusing on the explanatory strengths of natural selection (...) theory accurately reflects neither Darwin's own self-consciously held views, nor the nature of his support. Darwin's methodological and philosophical arguments were at once consistently empiricist and more sophisticated than such interpretations credit to him. (shrink)

Despite their success in describing and predicting cognitive behavior, the plausibility of so-called ‘rational explanations’ is often contested on the grounds of computational intractability. Several cognitive scientists have argued that such intractability is an orthogonal pseudoproblem, however, since rational explanations account for the ‘why’ of cognition but are agnostic about the ‘how’. Their central premise is that humans do not actually perform the rational calculations posited by their models, but only act as if they do. Whether or not the (...) problem of intractability is solved by recourse to ‘as if’ explanations critically depends, inter alia, on the semantics of the ‘as if’ connective. We examine the five most sensible explications in the literature, and conclude that none of them circumvents the problem. As a result, rational ‘as if’ explanations must obey the minimal computational constraint of tractability. (shrink)

The distinction between dimensions and units in physics is commonplace. But are dimensions a feature of reality? The most widely-held view is that they are no more than a tool for keeping track of the values of quantities under a change of units. This anti-realist position is supported by an argument from underdetermination: one can assign dimensions to quantities in many different ways, all of which are empirically equivalent. In contrast, I defend a form of dimensional realism, on which (...) some assignments of dimensions to quantities better describe reality than others. The argument I provide is a form of inference to the best explanation. In particular, the technique of dimensional analysis is explanatory, but it is only successful for certain systems of dimensions. Since these dimensional systems support scientific explanations, we have reason to believe that they are real. (shrink)

In this paper, I am clarifying and defending my argument in favor of the claim that cumulative selection can explain adaptation provided that the environmental resources are limited. Further, elaborate on what this limitation of environmental resources means and why it is relevant for the explanatory power of natural selection.

Scientific antirealists run the argument from underconsideration against scientific realism. I argue that the argument from underconsideration backfires on antirealists’ positive philosophical theories, such as the contextual theory of explanation (van Fraassen, 1980), the English model of rationality (van Fraassen, 1989), the evolutionary explanation of the success of science (Wray, 2008; 2012), and explanatory idealism (Khalifa, 2013). Antirealists strengthen the argument from underconsideration with the pessimistic induction against current scientific theories. In response, I (...) construct a pessimistic induction against antirealists that since antirealists generated problematic philosophical theories in the past, they must be generating problematic philosophical theories now. (shrink)

I begin by retracing an argument from Aristotle for final causes in science. Then, I advance this ancient thought, and defend an argument for a stronger conclusion: that no scientific explanation can succeed, if Naturalism is true. The argument goes like this: (1) Any scientific explanation can be successful only if it crucially involves a natural regularity. Next, I argue that (2) any explanation can be successful only if it crucially involves no element (...) that calls out for explanation but lacks one. From (1) and (2) it follows that (3) a scientific explanation can be successful only if it crucially involves a natural regularity, and this regularity does not call out for explanation while lacking one. I then argue that (4) if Naturalism is true, then all natural regularities call out for explanation but lack them. From (3) and (4) it follows that (5) if Naturalism is true, then no scientific explanation can be successful. If you believe that scientific explanation can be (indeed, often has been) successful, as I do, then this is a reason to reject Naturalism. (shrink)

The practice of science appears to involve “model-talk”. Scientists, one thinks, are in the business of giving accounts of reality. Scientists, in the process of furnishing such accounts, talk about what they call “models”. Philosophers of science have inspected what this talk of models suggests about how scientific theories manage to represent reality. There are, it seems, at least three distinct philosophical views on the role of scientific models in science’s portrayal of reality: the abstractionist view, the (...) indirect fictionalist view, and the direct fictionalist view. In this essay, I try to articulate a question about what makes a scientific model more or less appropriate for a specific domain of reality. More precisely, I ask, “What accounts for the fact that given a determinate target domain, some scientific models, but not others, are thought to be “appropriate” for that domain?” I then consider whether and the degree to which each of the mentioned views on scientific models institutes a satisfactory response to this question. I conclude that, amongst those views, the direct fictionalist view seems to have the most promising response. I then utilize this argument to develop a more precise account of the problem of differential importability, and ultimately offer a more general and less presumptive argument that the problem seems to be optimally solved by justifying comparative evaluation of model-importabilities solely in terms of comparative evaluations of what I characterize as models’ “holistic” predictive success. (shrink)

Within the context of the Quine–Putnam indispensability argument, one discussion about the status of mathematics is concerned with the ‘Enhanced Indispensability Argument’, which makes explicit in what way mathematics is supposed to be indispensable in science, namely explanatory. If there are genuine mathematical explanations of empirical phenomena, an argument for mathematical platonism could be extracted by using inference to the best explanation. The best explanation of the primeness of the life cycles of Periodical Cicadas (...) is genuinely mathematical, according to Baker :223–238, 2005; Br J Philos Sci 60:611–633, 2009). Furthermore, the result is then also used to strengthen the platonist position :779–793, 2017a). We pick up the circularity problem brought up by Leng Mathematical reasoning, heuristics and the development of mathematics, King’s College Publications, London, pp 167–189, 2005) and Bangu :13–20, 2008). We will argue that Baker’s attempt to solve this problem fails, if Hume’s Principle is analytic. We will also provide the opponent of the Enhanced Indispensability Argument with the so-called ‘interpretability strategy’, which can be used to come up with alternative explanations in case Hume’s Principle is non-analytic. (shrink)

Numbers without Science opposes the Quine-Putnam indispensability argument, seeking to undermine the argument and reduce its profound influence. Philosophers rely on indispensability to justify mathematical knowledge using only empiricist epistemology. I argue that we need an independent account of our knowledge of mathematics. The indispensability argument, in broad form, consists of two premises. The major premise alleges that we are committed to mathematical objects if science requires them. The minor premise alleges that science in (...) fact requires mathematical objects. The most common rejection of the argument denies its minor premise by introducing scientific theories which do not refer to mathematical objects. Hartry Field has shown how we can reformulate some physical theories without mathematical commitments. I argue that Field’s preference for intrinsic explanation, which underlies his reformulation, is ill-motivated, and that his resultant fictionalism suffers unacceptable consequences. I attack the major premise instead. I argue that Quine provides a mistaken criterion for ontic commitment. Our uses of mathematics in scientific theory are instrumental and do not commit us to mathematical objects. Furthermore, even if we accept Quine’s criterion for ontic commitment, the indispensability argument justifies only an anemic version of mathematics, and does not yield traditional mathematical objects. The first two chapters of the dissertation develop these results for Quine’s indispensability argument. In the third chapter, I apply my findings to other contemporary indispensabilists, specifically the structuralists Michael Resnik and Stewart Shapiro. In the fourth chapter, I show that indispensability arguments which do not rely on Quine’s holism, like that of Putnam, are even less successful. Also in Chapter 4, I show how Putnam’s work in the philosophy of mathematics is unified around the indispensability argument. In the last chapter of the dissertation, I conclude that we need an account of mathematical knowledge which does not appeal to empirical science and which does not succumb to mysticism and speculation. Briefly, my strategy is to argue that any defensible solution to the demarcation problem of separating good scientific theories from bad ones will find mathematics to be good, if not empirical, science. (shrink)

There is a need to bring about a revolution in the philosophy of science, interpreted to be both the academic discipline, and the official view of the aims and methods of science upheld by the scientific community. At present both are dominated by the view that in science theories are chosen on the basis of empirical considerations alone, nothing being permanently accepted as a part of scientific knowledge independently of evidence. Biasing choice of theory in the direction (...) of simplicity, unity or explanatory power does not permanently commit science to the thesis that nature is simple or unified. This current ‘paradigm’ is, I argue, untenable. We need a new paradigm, which acknowledges that science makes a hierarchy of metaphysical assumptions concerning the comprehensibility and knowability of the universe, theories being chosen partly on the basis of compatibility with these assumptions. Eleven arguments are given for favouring this new ‘paradigm’ over the current one. (shrink)