Review of David Faust, The Limits of Scientific Reasoning.

Psychoanalytic reasoning is an instance of inference to the best explanation and provides an extension of commonsense psychology that is potentially cogent, cumulative, and radical.

Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are adequately interpreted as an agent's actual subjective degrees of belief, measured by her betting behaviour. Confirmation is one important aspect of scientific reasoning. The thesis of this paper is the following: if scientific reasoning is at all probabilistic, the subjective interpretation has to be given up in order to get right confirmation—and thus scientific reasoning in general. The Bayesian approach (...) to scientific reasoning Bayesian confirmation theory The example The less reliable the source of information, the higher the degree of Bayesian confirmation Measure sensitivity A more general version of the problem of old evidence Conditioning on the entailment relation The counterfactual strategy Generalizing the counterfactual strategy The desired result, and a necessary and sufficient condition for it Actual degrees of belief The common knock-down feature, or ‘anything goes’ The problem of prior probabilities. (shrink)

Scientists regularly invoke broadly aesthetic properties like elegance and simplicity when evaluating theories, but why should we expect aesthetic pleasure to signal an epistemic good? I argue that aesthetic judgements in science are best understood as a special case of affective cognition, and that the feelings on which these judgements are based are the upshots of metacognitive monitoring of the quality of our engagement with theory and evidence. Finding a theory beautiful fallibly signals that it fits well with our background (...) knowledge and that it’s neither artificially adjusted to accommodate otherwise disconfirming evidence nor fitted to noise in the data, which makes aesthetic pleasure a good heuristic for theory evaluation. (shrink)

The paper investigates measures of explanatory power and how to define the inference schema “Inference to the Best Explanation”. It argues that these measures can also be used to quantify the systematic power of a hypothesis and the inference schema “Inference to the Best Systematization” is defined. It demonstrates that systematic power is a fruitful criterion for theory choice and IBS is truth-conducive. It also shows that even radical Bayesians must admit that systemic power is an integral component of Bayesian (...) reasoning. Finally, the paper puts the achieved results in perspective with van Fraassen’s famous criticism of IBE. (shrink)

Just before the Scientific Revolution, there was a "Mathematical Revolution", heavily based on geometrical and machine diagrams. The "faculty of imagination" (now called scientific visualization) was developed to allow 3D understanding of planetary motion, human anatomy and the workings of machines. 1543 saw the publication of the heavily geometrical work of Copernicus and Vesalius, as well as the first Italian translation of Euclid.

Many philosophers have wrongly assumed that there is an asymmetry between the problem of induction and the logocentric predicament (the justification of deductive inferences). This paper will show that the demand for justification, for the very inferences that are required for justification, is deeply problematic. Using a Wittgensteinian approach, I will argue that justification has an internal relation with deductive and inductive inferences. For Wittgenstein, two concepts are internally related if my understanding of one is predicated on my understanding of (...) the other. Separating the two concepts so that one can be applied to the other is then a misunderstanding of role that these concepts play. (shrink)

There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. (...) With the help of an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Selling Points Helps students develop scientific literacy—an essential aspect of _any_ undergraduate education in the 21 st century, including a broad understanding of scientific reasoning, methods, and concepts Written for all beginning college students: preparing science majors for more focused work in particular science; introducing the humanities’ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, _as well as_ strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated ‘For Further Reading’ sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a Companion Website, with: For Students: direct links to many of the primary sources discussed in the text, student self-check assessments, a bank of exam questions, and ideas for extended out-of-class projects For Instructors: a password-protected Teacher’s Manual, which provides student exam questions with answers, extensive lecture notes, classroom-ready Power Point presentations, and sample syllabi Extensive Curricular Development materials, helping any instructor who needs to create a Scientific Reasoning Course, ex nihilo. (shrink)

The extended mind thesis maintains that while minds may be centrally located in one’s brain-and-body, they are sometimes partly constituted by tools in our environment. Critics argue that we have no reason to move from the claim that cognition is embedded in the environment to the stronger claim that cognition can be constituted by the environment. I will argue that there are normative reasons, both scientific and ethical, for preferring the extended account of the mind to the rival embedded (...) account. (shrink)

The purpose of this article is to present an evidence-supported curriculum covering the fundamentals of logic, reasoning, and argumentation skills to address the emphasized basic knowledge, skills, and abilities required to be scientifically literate, which will prepare the public to understand and engage with science meaningfully. An analytic-synthetic approach toward understanding the notion of public is taken using a theoretical biomimetics framework that identifies naturally occurring objects or phenomena that descriptively captures the essence of a construct to facilitate creative (...) problem-solving. In the present case, the problem being solved is how to reconcile what is meant by public, how it ought to be interpreted, determining the diverse levels of confidence in science that exist, and various understandings of science all with one another. The results demonstrate there is an inherent denotative-connotative inconsistency in the traditional notion of public that can be explicated through the concept of a fractal allowing for comprehension of the relationship between public confidence in, and understanding of, science. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical (...) confirmation has not yet been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

Without doubt, there is a great diversity of scientific images both with regard to their appearances and their functions. Diagrams, photographs, drawings, etc. serve as evidence in publications, as eye-catchers in presentations, as surrogates for the research object in scientific reasoning. This fact has been highlighted by Stephen M. Downes who takes this diversity as a reason to argue against a unifying representation-based account of how visualisations play their epistemic role in science. In the following paper, I (...) will suggest an alternative explanation of the diversity of scientific images. This account refers to processes which are caused by the social setting of science. What exactly is meant by this, I will spell out with the aid of Ludwik Fleck’s theory of the social mechanisms of scientific communication. (shrink)

"Understanding Scientific Progress constitutes a potentially enormous and revolutionary advancement in philosophy of science. It deserves to be read and studied by everyone with any interest in or connection with physics or the theory of science. Maxwell cites the work of Hume, Kant, J.S. Mill, Ludwig Bolzmann, Pierre Duhem, Einstein, Henri Poincaré, C.S. Peirce, Whitehead, Russell, Carnap, A.J. Ayer, Karl Popper, Thomas Kuhn, Imre Lakatos, Paul Feyerabend, Nelson Goodman, Bas van Fraassen, and numerous others. He lauds Popper for advancing (...) beyond verificationism and Hume’s problem of induction, but faults both Kuhn and Popper for being unable to show that and how their work could lead nearer to the truth." —Dr. LLOYD EBY teaches philosophy at The George Washington University and The Catholic University of America, in Washington, DC "Maxwell's aim-oriented empiricism is in my opinion a very significant contribution to the philosophy of science. I hope that it will be widely discussed and debated." – ALAN SOKAL, Professor of Physics, New York University "Maxwell takes up the philosophical challenge of how natural science makes progress and provides a superb treatment of the problem in terms of the contrast between traditional conceptions and his own scientifically-informed theory—aim-oriented empiricism. This clear and rigorously-argued work deserves the attention of scientists and philosophers alike, especially those who believe that it is the accumulation of knowledge and technology that answers the question."—LEEMON McHENRY, California State University, Northridge "Maxwell has distilled the finest essence of the scientific enterprise. Science is about making the world a better place. Sometimes science loses its way. The future depends on scientists doing the right things for the right reasons. Maxwell's Aim-Oriented Empiricism is a map to put science back on the right track."—TIMOTHY McGETTIGAN, Professor of Sociology, Colorado State University - Pueblo "Maxwell has a great deal to offer with these important ideas, and deserves to be much more widely recognised than he is. Readers with a background in philosophy of science will appreciate the rigour and thoroughness of his argument, while more general readers will find his aim-oriented rationality a promising way forward in terms of a future sustainable and wise social order."—David Lorimer, Paradigm Explorer, 2017/2 "This is a book about the very core problems of the philosophy of science. The idea of replacing Standard Empiricism with Aim-Oriented Empiricism is understood by Maxwell as the key to the solution of these central problems. Maxwell handles his main tool masterfully, producing a fascinating and important reading to his colleagues in the field. However, Nicholas Maxwell is much more than just a philosopher of science. In the closing part of the book he lets the reader know about his deep concern and possible solutions of the biggest problems humanity is facing."—Professor PEETER MŰŰREPP, Tallinn University of Technology, Estonia “For many years, Maxwell has been arguing that fundamental philosophical problems about scientific progress, especially the problem of induction, cannot be solved granted standard empiricism (SE), a doctrine which, he thinks, most scientists and philosophers of science take for granted. A key tenet of SE is that no permanent thesis about the world can be accepted as a part of scientific knowledge independent of evidence. For a number of reasons, Maxwell argues, we need to adopt a rather different conception of science which he calls aim-oriented empiricism (AOE). This holds that we need to construe physics as accepting, as a part of theoretical scientific knowledge, a hierarchy of metaphysical theses about the comprehensibility and knowability of the universe, which become increasingly insubstantial as we go up the hierarchy. In his book “Understanding Scientific Progress: Aim-Oriented Empiricism”, Maxwell gives a concise and excellent illustration of this view and the arguments supporting it… Maxwell’s book is a potentially important contribution to our understanding of scientific progress and philosophy of science more generally. Maybe it is the time for scientists and philosophers to acknowledge that science has to make metaphysical assumptions concerning the knowability and comprehensibility of the universe. Fundamental philosophical problems about scientific progress, which cannot be solved granted SE, may be solved granted AOE.” Professor SHAN GAO, Shanxi University, China . (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination (...) in problem-solving. But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

In my book Understanding Scientific Progress, I argue that fundamental philosophical problems about scientific progress, above all the problem of induction, cannot be solved granted standard empiricism (SE), a doctrine which most scientists and philosophers of science take for granted. A key tenet of SE is that no permanent thesis about the world can be accepted as a part of scientific knowledge independent of evidence. For a number of reasons, we need to adopt a rather different conception (...) of science which I call aim-oriented empiricism (AOE). This holds that we need to construe physics as accepting, as a part of theoretical scientific knowledge, a hierarchy of metaphysical theses about the comprehensibility and knowability of the universe, these theses becoming increasingly insubstantial as we go up the hierarchy. Fundamental philosophical problems about scientific progress, including the problems of induction, theory unity, verisimilitude and scientific discovery, which cannot be solved granted SE, can be solved granted AOE. In his review of Understanding Scientific Progress, Moti Mizrahi makes a number of criticisms, almost all of which are invalid in quite elementary ways. (shrink)

Eliminative reasoning is a method that has been employed in many significant episodes in the history of science. It has also been advocated by some philosophers as an important means for justifying well-established scientific theories. Arguments for how eliminative reasoning is able to do so, however, have generally relied on a too narrow conception of evidence, and have therefore tended to lapse into merely heuristic or pragmatic justifications for their conclusions. This paper shows how a broader conception (...) of evidence not only can supply the needed justification but also illuminates the methodological significance of eliminative reasoning in a variety of contexts. (shrink)

A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically (...) distinct from currently accepted theories in the relevant respects. In other words, it may seem that realists should recommend that scientists be relatively conservative in their theoretical endeavors. This paper aims to show that this argument is mistaken. While realists should indeed be less optimistic of finding radically distinct alternatives to replace current theories, realists also have greater reasons to value the outcomes of such searches. Interestingly, this holds both for successful and failed attempts to identify and develop such alternatives. (shrink)

Can reasoning improve moral judgments and lead to moral progress? Pessimistic answers to this question are often based on caricatures of reasoning, weak scientific evidence, and flawed interpretations of solid evidence. In support of optimism, we discuss three forms of moral reasoning (principle reasoning, consistency reasoning, and social proof) that can spur progressive changes in attitudes and behavior on a variety of issues, such as charitable giving, gay rights, and meat consumption. We conclude that (...) moral reasoning, particularly when embedded in social networks with mutual trust and respect, is integral to moral progress. (shrink)

La recherche empirique et philosophique récente remet en question l’idée selon laquelle raison et émotion sont nécessairement en conflit l’une avec l’autre. Pourtant, les philosophes des sciences ont été lents à réagir à cette recherche. Je soutiens qu’ils continuent à exclure l’émotion de leurs modèles du raisonnement scientifique, parce qu’ils considèrent qu’elle appartient typiquement au contexte de découverte plutôt qu’au contexte de justification. Je suggère toutefois, en prenant pour exemple le fiabilisme, que des travaux récents en épistémologie remettent en cause (...) l’autorité généralement accordée à la distinction entre ces contextes. On peut considérer que l’émotion joue un rôle fiable dans la formation des croyances scientifiques, ce qui pour le fiabiliste signifie également leur justification. (shrink)

In reading Barbara Koslowski's "Theory and Evidence: The Development of Scientific Reasoning", one may be convinced that the ancient debate between classical rationalists and empiricists is alive. And like most people who carefully investigate the ability of either rationalism or empiricism truly to account for all of our ability to know, Koslowski arrives at the position of saying that knowledge (in this case scientific knowledge) is a product of both: "neither theory nor data alone is sufficient to (...) achieve scientific success; each must be evaluated in the context of, and constrained by, the other". The problem, according to Koslowski, for those who insist upon empiricism as being the only type of understanding which counts as science, is that we then exclude much of the productive thought in children empiricism champions itself as being theory-independent. The theory-independent notion of science uses covariation as its exclusive criterion for scientific reasoning. "In short, the empiricist aim of rationally reconstructing scientific inquiry in terms of theory-independent principles went along with an (all but exclusive) emphasis on the role of Humean indices. And this, in turn, brought with it a corresponding emphasis on hypothesis testing rather than hypothesis discovery and revision". Consequently, according to Koslowski, if we are willing to expand our notion of scientific reasoning to go beyond testing for covariation, then we will find that many more children and adults can be seen to reason in a manner which would be called "scientific". (shrink)

Scientific hedges are communicative devices used to qualify and weaken scientific claims. Gregor Betz has argued—unconvincingly, we think—that hedging can rescue the value-free ideal for science. Nevertheless, Betz is onto something when he suggests there are political principles that recommend scientists hedge public-facing claims. In this article, we recast this suggestion using the notion of public justification. We formulate and reject a Rawlsian argument that locates the justification for hedging in its ability to forge consensus. On our alternative (...) proposal, hedging is often justified because it renders scientific claims as publicly accessible reasons. (shrink)

What are the reasons of the second scientific revolution that happened at the beginning of the XX century? Why did the new physics supersede the old one? The author tries to answer the subtle questions with a help of the epistemological model of scientific revolutions that takes into account some recent advances in philosophy, sociology and history of science. According to the model, Einstein’s Revolution took place due to resolution of deep contradictions between the basic classical research traditions: (...) Newtonian mechanics, maxwellian electrodynamics, thermodynamics and statistical mechanics. As a result, two new research programmes – relativistic and quantum- had been constructed. It was the interaction between them that formed the interdisciplinary context of Einstein’s Revolution. (shrink)

Discussions over whether these natural kinds exist, what is the nature of their existence, and whether natural kinds are themselves natural kinds aim to not only characterize the kinds of things that exist in the world, but also what can knowledge of these categories provide. Although philosophically critical, much of the past discussions of natural kinds have often answered these questions in a way that is unresponsive to, or has actively avoided, discussions of the empirical use of natural kinds and (...) what I dub “activities of natural kinding” and “natural kinding practices”. The natural kinds of a particular discipline are those entities, events, mechanisms, processes, relationships, and concepts that delimit investigation within it—but we might reasonably ask: How are these natural kinds discovered?, How are they made?, Are they revisable?, and Where do they come from? A turn to natural kinding practices reveals a new set of questions open for investigation: How do natural kinds explain through practice?, What are natural kinding practices and classifications and why should we care?, What is the nature of natural kinds viewed as a set of activities?, and How do practice approaches to natural kinds shape and reconfigure scientific disciplines? Natural kinds have traditionally been discussed in terms of how they classify the contents of the world. The metaphysical project has been one which identifies essences, laws, sameness relations, fundamental properties, and clusters of family resemblances and how these map out the ontological space of the world. But actually how this is done has been less important in the discussion than the resultant categories that are produced. I aim to rectify these omissions and suggest a new metaphysical project investigating kinds in practice. (shrink)

Scientific theories are used for a variety of purposes. For example, physical theories such as classical mechanics and electrodynamics have important applications in engineering and technology, and we trust that this results in useful machines, stable bridges, and the like. Similarly, theories such as quantum mechanics and relativity theory have many applications as well. Beyond that, these theories provide us with an understanding of the world and address fundamental questions about space, time, and matter. Here we trust that the (...) answers scientific theories give are reliable and that we have good reason to believe that the features of the world are similar to what the theories say about them. But why do we trust scientific theories, and what counts as evidence in favor of them? (shrink)

Public reason liberalism is defined by the idea that laws and policies should be justifiable to each person who is subject to them. But what does it mean for reasons to be public or, in other words, suitable for this process of justification? In response to this question, Kevin Vallier has recently developed the traditional distinction between consensus and convergence public reason into a classification distinguishing three main approaches: shareability, accessibility and intelligibility. The goal of this paper is to defend (...) the accessibility approach by demonstrating its ability to strike an appealing middle course in terms of inclusivity between shareability and intelligibility. We first argue against Vallier that accessibility can exclude religious reasons from public justification. Second, we use scientific reasons as a case study to show that accessibility excludes considerably fewer reasons than shareability. Throughout the paper, we connect our discussion of accessibility to John Rawls’s model of public reason, so as to give substance to the accessibility approach and to further our understanding of Rawls’s influential model. (shrink)

Abstract. In Dynamics of Reason Michael Friedman proposes a kind of synthesis between the neokantianism of Ernst Cassirer, the logical empiricism of Rudolf Carnap, and the historicism of Thomas Kuhn. Cassirer and Carnap are to take care of the Kantian legacy of modern philosophy of science, encapsulated in the concept of a relativized a priori and the globally rational or continuous evolution of scientific knowledge,while Kuhn´s role is to ensure that the historicist character of scientific knowledge is taken (...) seriously. More precisely, Carnapian linguistic frameworks, guarantee that the evolution of science procedes in a rational manner locally,while Cassirer’s concept of an internally defined conceptual convergence of empirical theories provides the means to maintain the global continuity of scientific reason. In this paper it is argued that Friedman’s neokantian account of scientific reason based on the concept of the relativized a priori underestimates the pragmatic aspects of the dynamics of scientific reason. To overcome this short-coming, I propose to reconsider C.I. Lewis’s account of a pragmatic the priori, recently modernized and elaborated by Hasok Chang. This may be<br><br><br><br><br><br><br><br><br><br&g t;<br><br><br><br><br><br>Keywords: Dynamics of reason, Paradigms, Logical Empiricism,Neokantianism, Pragmatism, Mathematics, Communicative Rationality. (shrink)

This chapter discusses contemporary scientific research on the role of reason and emotion in moral judgment. The literature suggests that moral judgment is influenced by both reasoning and emotion separately, but there is also emerging evidence of the interaction between the two. While there are clear implications for the rationalism-sentimentalism debate, we conclude that important questions remain open about how central emotion is to moral judgment. We also suggest ways in which moral philosophy is not only guided by (...) empirical research but continues to guide it. (shrink)

In Kant, Science, and Human Nature, Robert Hanna argues against a version of scientific realism founded on the Kripke/Putnam theory of reference, and defends a Kant-inspired manifest realism in its place. I reject Kriple/Putnam for different reasons than Hanna does, and argue that what should replace it is not manifest realism, but Kant‘s own scientific realism, which rests on a radically different theory of reference. Kant holds that we picture manifest objects by uniting manifolds of sensation using concepts-qua-inferential-rules. (...) When these rules are demonstrated to be invalid, we replace the picture of the macroscopic world with a picture of the microscopic entities of theoretical science that unites the very same manifolds using different rules of inference. Thus, we refer to "unobservable" theoretical entities in the same way that we do manifest ones: by specifying both their determinate location in space and time and the concepts by which they are understood. (shrink)

Moral philosophers are, among other things, in the business of constructing moral theories. And moral theories are, among other things, supposed to explain moral phenomena. Consequently, one’s views about the nature of moral explanation will influence the kinds of moral theories one is willing to countenance. Many moral philosophers are (explicitly or implicitly) committed to a deductive model of explanation. As I see it, this commitment lies at the heart of the current debate between moral particularists and moral generalists. In (...) this paper I argue that we have good reasons to give up this commitment. In fact, I show that an examination of the literature on scientific explanation reveals that we are used to, and comfortable with, non-deductive explanations in almost all areas of inquiry. As a result, I argue that we have reason to believe that moral explanations need not be grounded in exceptionless moral principles. (shrink)

Normative explanations, which specify why things have the normative features they do, are ubiquitous in normative theory and ordinary thought. But there is much less work on normative explanation than on scientific or metaphysical explanation. Skow (2016) argues that a complete answer to the question why some fact Q occurs consists in all of the reasons why Q occurs. This paper explores this theory as a case study of a general theory that promises to offer us a grip on (...) normative explanation which is independent of particular normative theories. I first argue that the theory doesn’t give an adequate account of certain enablers of reasons which are important in normative explanation. I then formulate and reject three responses on behalf of the theory. But I suggest that since theories of this general sort have the right kind of resources to illuminate how normative explanation might be similar to and different from explanations in other domains, they nonetheless merit further exploration by normative theorists. (shrink)

John Searle offers what he thinks to be a reasonable scientific approach to the understanding of consciousness. I argue that Searle is demanding nothing less than a Kuhnian-type revolution with respect to how scientists should study consciousness given his rejection of the subject-object distinction and affirmation of mental causation. As part of my analysis, I reveal that Searle embraces a version of emergentism that is in tension, not only with his own account, but also with some of the theoretical (...) tenets of science. I conclude that Searle has offered little to motivate scientists to adopt his proposal. (shrink)

The UK has been ‘following the science’ in response to the COVID-19 pandemic in line with the national framework for the use of scientific advice in assessment of risk. We argue that the way in which it does so is unsatisfactory in two important respects. Firstly, pandemic policy making is not based on a comprehensive assessment of policy impacts. And secondly, the focus on reasonable worst-case scenarios as a way of managing uncertainty results in a loss of decision-relevant information (...) and does not provide a coherent basis for policy making. (shrink)

In 1984 the author published From Knowledge to Wisdom, a book that argued that a revolution in academia is urgently needed, so that problems of living, including global problems, are put at the heart of the enterprise, and the basic aim becomes to seek and promote wisdom, and not just acquire knowledge. Every discipline and aspect of academia needs to change, and the whole way in which academia is related to the rest of the social world. Universities devoted to the (...) pursuit of knowledge and technological know-how betray reason and, as a result, betray humanity. As a result of becoming more intellectually rigorous, academic inquiry becomes of far greater benefit to humanity. If the revolution argued for all those years ago had been taken up and put into academic practice, we might now live in a much more hopeful world than the one that confronts us. Humanity might have begun to learn how to solve global problems; the Amazon rain forests might not face destruction; we might not be faced with mass extinction of species; Brexit might not have been voted for in the UK in 2016, and Trump might not have been elected President in the USA. An account is given of work published by the author during the years 1972 to 2021 that expounds and develops the argument. The conclusion is that we urgently need to create a high-profile campaign devoted to transforming universities in the way required so that humanity may learn how to make social progress towards a better, wiser, more civilized, enlightened world. (shrink)

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation model (...) and the results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well. (shrink)

1. EXPLICATING THE CONCEPT OF REFLECTION (under review) -/- To understand how ‘reflection’ is used, I consider ordinary, philosophical, and scientific discourse. I find that ‘reflection’ seems to refer to reasoning that is deliberate and conscious, but not necessarily self-conscious. Then I offer an empirical explication of reflection’s conscious and deliberate features. These explications not only help explain how reflection can be detected; they also distinguish reflection from nearby concepts such as ruminative and reformative reasoning. After this, (...) I find that reflection is not obviously limited to only practical or only theoretical reasoning. The chapter ends with reasons to prefer ‘unreflective’ and ‘reflective’ to dual process theorists’ labels about systems or types. -/- 2. BOUNDED REFLECTIVISM & EPISTEMIC IDENTITY (in Metaphilosophy) -/- Reflection features centrally in philosophy (e.g., Korsgaard, 1996; Rawls, 1971; Sosa, 1991) and psychology (e.g., Pennycook, 2018). Bounded reflectivism is an empirically adequate model of reflection that explains reflection’s capacity to either help or hinder reasoning—e.g., reflective equilibrium vs. reflective polarization (e.g., Kahan et al., 2017). One innovation of the model is epistemic identity: an identity that involves particular beliefs—e.g., religious and political identities. When we feel that our epistemic identity is threatened, we can reflectively defend its beliefs rather than update our beliefs according to the best arguments and evidence. The solution, I argue, is not to suppress epistemic identity but embrace it by appealing to shared, superordinate epistemic identities. -/- 3. ALL MEASURES ARE NOT CREATED EQUAL (under review) -/- A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? “10 cents” comes to most people’s minds immediately. However, upon reflection, we can realize that “5 cents” is the correct answer. There are many reflection tests. Each has its limitations. Some reflection tests are mathematical—like the bat-and-ball problem (e.g., Frederick, 2005) and others are logical (e.g., Janis & Frick, 1943). So there are concerns that reflection tests track logical and mathematical competence rather than reflection per se. Also, some psychologists assume a priori that correct answers are reflective and lured answers are unreflective. New evidence raises additional concerns about the plausibility of these assumptions. I argue that think aloud protocols (Ericsson & Simon, 1998) and process dissociation (Jacoby, 1991) can assuage some of these concerns. -/- 4. GREAT MINDS DO NOT THINK ALIKE (in Review of Philosophy and Psychology) -/- Two large studies (N = 1299), one pre-registered, found that many correlations between reflection and philosophical beliefs among non-philosophers replicated among philosophers. For example, less reflective philosophers preferred theism to atheism and utilitarian rather than deontological responses to the trolley problem (Hannikainen & Cova, in prep.; Pennycook et al., 2016; Reynolds, Byrd, & Conway, forthcoming). However, philosophical judgments were sometimes better predicted by factors like education, gender, and personality than by reflection test performance. So although some relationships between reflection and philosophy were robust, there is more to the link between reflection and philosophy. Normative implications are also discussed—e.g., how we can infer the quality of philosophical views from their correlations with reflective or unreflective reasoning. -/- 5. WHAT WE CAN (AND CAN’T) INFER ABOUT IMPLICIT BIAS (in Synthese) -/- Contrary to some philosophers and psychologists, I argue that implicit bias is probably associative. However, I also argue that debiasing is not thereby entirely unconscious and involuntary. Indeed, strong evidence suggests that reflection can change implicitly biased behavior—e.g., conscious and deliberate counterconditioning. This has implications for the science and morality of implicit bias—e.g., evidence suggests that we can reform biases; so. intuitively, we can be responsible for biases. (shrink)

This paper argues that the proponents of epistemological scientism must take some stand on scientific methodology. The supporters of scientism cannot simply defer to the social organisation of science because the social processes themselves must meet some methodological criteria. Among such criteria is epistemic evaluability, which demands intersubjective access to reasons. We derive twelve theses outlining some implications of epistemic evaluability. Evaluability can support weak and broad variants of epistemological scientism, which state that sciences, broadly construed, are the best (...) sources of knowledge or some other epistemic goods. Since humanities and social sciences produce epistemically evaluable results, narrow types of scientism that take only natural sciences as sources of knowledge require additional argumentation in their support. Strong scientism, which takes sciences as the only source of knowledge, also needs to appeal to some further principles since evaluability is not an all-or-nothing affair. (shrink)

In “Normative Reasons from a Naturalistic Point of View”, Marko Jurjako explores the foundational concept of normative reasons through the lens of methodological naturalism. Departing from traditional analytic or purely conceptual approaches, this philosophical inquiry navigates the terrain of reasons, rationality, and normativity—concepts with a long philosophical pedigree—within a framework rooted in our understanding of the natural and social world. By aligning the exploration with scientifically based theorizing, the book seeks a synoptic view that bridges the gap between relatively isolated (...) philosophical discussions of the nature of normative reasons and their grounding in human intrapersonal and interpersonal interactions that can be understood and explained by an array of scientifically inspired models. (shrink)

If successful scientific inquiry is to be possible, there must be a world that is independent of how we believe it to be, and in which there are kinds and laws; and we must have the sensory apparatus to perceive particular things and events, and the capacity to represent them, to form generalized explanatory conjectures, and check how these conjectures stand up to further experience. Whether these preconditions are met is not a question the sciences can answer; it is (...) specifically philosophical. This is why the myriad forms of scientistic philosophy in vogue today (neurophilosophy, experimental philosophy, naturalized metaphysics, evangelical-atheist reductionism, etc), are all hollow at the core. Does this mean we must return to the old, a priori analytic model? No! What is needed instead is scientific philosophy in the sense Peirce articulated more than a century ago: philosophy motivated by a genuine desire to discover the truth, and relying not solely on reason but also on experience—only not the special, recherché experience required by the sciences, but close attention to aspects of everyday experience so familiar we hardly notice them. (shrink)

The science of mind wandering has rapidly expanded over the past 20 years. During this boom, mind wandering researchers have relied on self-report methods, where participants rate whether their minds were wandering. This is not an historical quirk. Rather, we argue that self-report is indispensable for researchers who study passive phenomena like mind wandering. We consider purportedly “objective” methods that measure mind wandering with eye tracking and machine learning. These measures are validated in terms of how well they predict self-reports, (...) which means that purportedly objective measures of mind wandering retain a subjective core. Mind wandering science cannot break from the cycle of self-report. Skeptics about self-report might conclude that mind wandering science has methodological foundations of sand. We take a rather more optimistic view. We present empirical and philosophical reasons to be confident in self-reports about mind wandering. Empirically, these self-reports are remarkably consistent in their contents and behavioral and neural correlates. Philosophically, self-reports are consistent with our best theories about the function of mind wandering. We argue that this triangulation gives us reason to trust both theory and method. (shrink)

Considerations of scientific evidence are often thought to provide externalism with the dialectical upper hand in the internalism–externalism debate. How so? A couple of reasons are forthcoming in the literature. (1) Williamson (2000) argues that the E = K thesis (in contrast to internalism) provides the best explanation for the fact that scientists appear to argue from premises about true propositions (or facts) that are common knowledge among the members of the scientific community. (2) Kelly (Philosophy Compass, 3 (...) (5), 933–955, 2008; 2016) argues that only externalism is suited to account for the public character of scientific evidence. In this article, I respond to Williamson and Kelly’s arguments. First, I show that the E = K thesis isn’t supported by the way in which we talk about scientific evidence, and that it is unable to account for facts about what has been regarded as scientific evidence and as justified scientific belief in the history of science. Second, I argue that there are internalist views that can account for the publicity of scientific evidence, and that those views indeed do better in that regard than the (externalist) view proposed by Kelly. The upshot is that considerations of scientific evidence do not favor externalism over internalism. (shrink)

This paper analyzes the historical context and systematic importance of Kant's hypothetical use of reason. It does so by investigating the role of hypotheses in Kant's philosophy of science. We first situate Kant’s account of hypotheses in the context of eighteenth-century German philosophy of science, focusing on the works of Wolff, Meier, and Crusius. We contrast different conceptions of hypotheses of these authors and elucidate the different theories of probability informing them. We then adopt a more systematic perspective to discuss (...) Kant's idea that scientific hypotheses must articulate real possibilities. We argue that Kant's views on the intelligibility of scientific hypotheses constitute a valuable perspective on scientific understanding and the constraints it imposes on scientific rationality. (shrink)

The question of our place in nature has long been with us. One answer lies in comparing humans with other animals , thereby highlighting the uniquely human. To this end, I examine the distinction between humans and brutes as delineated by Descartes, Kant, and the Chicago pragmatist George Mead. This selection not merely assures a wide-spectrum of opinion still alive today, it marks a general historical shift from the metaphysical dualism of Descartes' mechanical world and spiritual self, to the epistemic (...) dualism of Kant and his double sense of self, finally to Mead's naturalistic monism, in which consciousness emerges naturally from the non-conscious. Apart from illuminating issues current in the animal-rights literature, examining this single topic casts a new light on these figures, especially Kant and Mead . Descartes' dualism is understandable simply given his scientific commitments, and the chasm he found in the human/brute gap was as much a result of this scientific motivation as any religious or moral one. For Kant, brutes lack the power to judge, understand, or reason. But more importantly, they lack autonomy and are therefore without moral worth. The unbridgeable chasm, metaphysical for Descartes, became for Kant primarily moral. Brutes do have representations and desires, however, and, by virtue of being alive, an immaterial principle; Kant consequently rejected Descartes' animal-machine hypothesis. Darwin's account of the human/brute gap and Mead's Darwinistic psychology are discussed. Selfhood and consciousness are unique to humans, although brutes are conscious in another sense. Mead's different uses of 'consciousness' are separated in order to clarify this difference as well as the role of language in the emergence of mind. Mead argued that humans perceive social objects prior to physical objects while brutes perceive none of these, lacking the capacities of universalization and object-manipulation. Like Descartes and Kant, Mead minimized brute experience, thereby maintaining a wide gulf between humans and brutes despite his Darwinian naturalism. (shrink)

Studies on difficulties in understanding scientific terms have shown that the problem is more serious among non-Western learners. The main reasons for this are the learners' pre-existing knowledge of scientific terms, their native language incommensurability with Western languages, and the polysemy of the words used to denote scientific concepts. The current study is an analysis of the conceptualisation of scientific concepts in two culturally different languages, i.e. Arabic and French, which represent a non-Western language and a (...) Western language respectively. Physics concepts which are considered as some of the most challenging concepts for non-Western languages (Loo 2005; Aranador 2005) were selected for analysis. To this end, the terms that refer to two physics concepts, "weight" and "mass" in Arabic وَزْن (wazn) and كُتْلَة (kutla) and in French poids and masse were semantically analysed. The analysis of the concepts in both languages is informed by the prototype theory by Rosch (1973; 1975), idealised cognitive models (ICMs) by Lakoff (1987), and conceptual metaphor and conceptual metonymy by Lakoff and Johnson (2003). The data for analysis were retrieved from two comparable Arabic and French corpora, namely the ArabiCorpus and the Concordancier-Corpus Français. The results suggest that there are both similarities and differences between the Arabic and French concepts in terms of meanings, prototypes, and metaphorical as well as metonymic semantic extensions. These findings support the argument that the human conceptual system is related to our environmental and cultural experiences and also importantly, validate previous claims on the need for educators to be cognizant of the culturally relevant meanings of scientific words found in everyday language that may impede learners' understanding of scientific concepts. (shrink)

This paper outlines the methodological and empirical limitations of analysing the potential relationship between complex social phenomena such as democracy and inequality. It shows that the means to assess how they may be related is much more limited than recognised in the existing literature that is laden with contradictory hypotheses and findings. Better understanding our scientific limitations in studying this potential relationship is important for research and policy because many leading economists and other social scientists such as Acemoglu and (...) Robinson mistakenly claim to identify causal linkages between inequality and democracy but at times still inform policy. In contrast to the existing literature, the paper argues that ‘structural’ or ‘causal’ mechanisms that may potentially link the distribution of economic wealth and different political regimes will remain unknown given reasons such as their highly complex and idiosyncratic characteristics, fundamental econometric constraints and analysis at the macro-level. Neither new data sources, different analysed time periods nor new data analysis techniques can resolve this question and provide robust, general conclusions about this potential relationship across countries. Researchers are thus restricted to exploring rough correlations over specific time periods and geographic contexts with imperfect data that are very limited for cross-country comparisons. (shrink)

In this paper I argue for a kind of intellectual inquiry which has, as its basic aim, to help all of us to resolve rationally the most important problems that we encounter in our lives, problems that arise as we seek to discover and achieve that which is of value in life. Rational problem-solving involves articulating our problems, proposing and criticizing possible solutions. It also involves breaking problems up into subordinate problems, creating a tradition of specialized problem-solving - specialized (...) class='Hi'>scientific, academic inquiry, in other words. It is vital, however, that specialized academic problem-solving be subordinated to discussion of our more fundamental problems of living. At present specialized academic inquiry is dissociated from problems of living - the sin of specialism, which I criticize. (shrink)

If we consider modeling not as a heap of contingent structures, but (where possible) as evolving coordinated systems of models, then we can reasonably explain as "direct representations" even some very complicated model-based cognitive situations. Scientific modeling is not as indirect as it may seem. "Direct theorizing" comes later, as the result of a successful model evolution.

In this three-part paper, my concern is to expound and defend a conception of science, close to Einstein's, which I call aim-oriented empiricism. I argue that aim-oriented empiricsim has the following virtues. (i) It solve the problem of induction; (ii) it provides decisive reasons for rejecting van Fraassen's brilliantly defended but intuitively implausible constructive empiricism; (iii) it solves the problem of verisimilitude, the problem of explicating what it can mean to speak of scientific progress given that science advances from (...) one false theory to another; (iv) it enables us to hold that appropriate scientific theories, even though false, can nevertheless legitimately be interpreted realistically, as providing us with genuine , even if only approximate, knowledge of unobservable physical entities; (v) it provies science with a rational, even though fallible and non-mechanical, method for the discovery of fundamental new theories in physics. In the third part of the paper I show that Einstein made essential use of aim-oriented empiricism in scientific practice in developing special and general relativity. I conclude by considering to what extent Einstein came explicitly to advocate aim-oriented empiricism in his later years. (shrink)