Moti Mizrahi

Timothy Lyons’s Scientific Realism (2025) is a book in the Cambridge Elements in the Philosophy of Science series. Like all books in this series, its purported aim is to provide an extensive overview of a topic or debate in philosophy of science. In the case of Lyons, the debate is the scientific realism/antirealism debate in philosophy of science, which is philosophically rich with various positions and arguments (Chakravartty 2017). Unfortunately, I think the book fails to provide an extensive overview of the scientific realism/antirealism debate. Instead of an extensive overview, the book serves readers a rather thin slice of the debate. As a result, the book paints a rather impoverished picture of the debate. The book also advances arguments with known problems that have been discussed in the literature on scientific realism, but fails to address them adequately.

In this paper, I argue that appeals to intuition in Analytic Philosophy are not compelling arguments because intuitions are not the sort of thing that has the power to rationally persuade other professional analytic philosophers. This conclusion follows from reasonable premises about the goal of Analytic Philosophy, which is rational persuasion by means of arguments, and the requirement that evidence for and/or against philosophical theses used by professional analytic philosophers be public (or transparent) in order to have the power to rationally persuade other professional analytic philosophers. Since intuitions are not public (or transparent) evidence, it follows that appeals to intuition are not compelling arguments for and/or against philosophical theses because they lack the power to rationally persuade other professional analytic philosophers.

In this paper, I respond to Sterpetti’s (Axiomathes, 2018. 10.1007/s10516-018-9392-4) attempt to defend Kyle P. Stanford’s Problem of Unconceived Alternatives and his New Induction over the History of Science (NIS) from my reductio argument outlined in Mizrahi (J Gen Philos Sci 47(1):59–68, 2016a). I discuss what I take to be the ways in which Sterpetti has misconstrued my argument against Stanford’s NIS, in particular, that it is a reductio, not a dilemma, as Sterpetti erroneously thinks. I argue that antirealists who endorse Stanford’s NIS still face an absurd consequence of this argument, namely, that they should not believe their own brand of scientific antirealism.

In this paper, I sketch an answer to the question “Why be an intellectually humble philosopher?” I argue that, as far as philosophical argumentation is concerned, the historical record of Western Philosophy provides a straightforward answer to this question. That is, the historical record of philosophical argumentation, which is a track record that is marked by an abundance of alternative theories and serious problems for those theories, can teach us important lessons about the limits of philosophical argumentation. These lessons, in turn, show why philosophers should argue with humility.

Some philosophers are optimistic about progress in philosophy (e.g., Stoljar 2017), whereas other philosophers have more pessimistic views about philosophical progress in comparison to scientific progress (e.g., Chalmers 2015). As far as scientific progress is concerned, there is no question among philosophers of science that science does make progress. Instead, the question philosophers of science are primarily concerned with is this: what is the basic unit of scientific progress? Does science make progress by approximating truth, accumulating knowledge, increasing understanding, or solving problems? Mizrahi (2021; 2022) attempts to approach this question about scientific progress empirically. Using computational, corpus-based methods, Mizrahi (2021; 2022) analyzes a large corpus of scientific publications to find out whether practicing scientists talk about the aim(s) or goal(s) of scientific research in terms of truth, knowledge, understanding, or solutions in their academic publications. In this chapter, we attempt to do the same with respect to philosophical progress. That is, using computational, quantitative, and corpus-based methods, we address the following question empirically. When they talk about the aim(s) or goal(s) of academic philosophy in their academic publications, which of the following terms do academic philosophers use more frequently: ‘truth’, ‘knowledge’, ‘understanding’, or ‘solution’? Overall, the results of this quantitative, corpus-based study suggest that there is significantly more truth talk than knowledge talk, more knowledge talk than understanding talk, and more understanding talk than solution talk around progress terms in academic articles published in philosophy journals.

It is difficult to engage in a constructive dialogue with philosophers who dismiss their fellow philosophers’ work as “philosophically irrelevant.” In Mizrahi (2025a), I conducted a mixed-method study of Thomas Kuhn’s The Structure of Scientific Revolutions (1962/1996). The qualitative and quantitative evidence detailed in Mizrahi (2025a) suggest that Kuhn (1962/1996) perpetuates “Great Man” of science historiography. “Great Man” of science historiography paints a picture of the history of science as the biography of “great men.” For Politi (2025, 8), however, quantitative evidence is not “philosophically relevant.” He sees no value in a mixed-methods approach to philosophical questions (13). Given this methodological chasm between our approaches to philosophical research, I wonder why Politi even bothered to write a reply to Mizrahi (2025a) in the first place. Be that as it may, in this paper, I respond to Politi’s (2025) substantive criticisms as I understand them. I show that they are misguided and miss their intended target.

More than 50 years after the publication of Thomas Kuhn’s seminal book, The Structure of Scientific Revolutions, this volume assesses the adequacy of the Kuhnian model in explaining certain aspects of science, particularly the social and epistemic aspects of science. One argument put forward is that there are no good reasons to accept Kunh’s incommensurability thesis, according to which scientific revolutions involve the replacement of theories with conceptually incompatible ones. Perhaps, therefore, it is time for another “decisive transformation in the image of science by which we are now possessed.” Only this time, the image of science that needs to be transformed is the Kuhnian one. Does the Kuhnian image of science provide an adequate model of scientific practice? If we abandon the Kuhnian picture of revolutionary change and incommensurability, what consequences would follow from that vis-à-vis our understanding of scientific knowledge as a social endeavour? The essays in this collection continue this debate, offering a critical examination of the arguments for and against the Kuhnian image of science as well as their implications for our understanding of science as a social and epistemic enterprise.

The excitement about Large Language Models (LLMs) has led some to consider the possibility that they could be artificial epistemic authorities. For instance, after considering arguments for and against granting LLMs the status of epistemic authorities, Hauswald (2025) argues that the standard view of epistemic authorities should be revised to accommodate LLMs as epistemic authorities. This paper aims to contribute to the literature on LLM or chatbot epistemology by sketching two arguments against granting LLMs the status of epistemic authorities. According to the first argument, if LLMs are bullshit machines, then they should not be granted the status of epistemic authorities that are worthy of our epistemic respect. According to the second argument, if LLMs cannot take responsibility and be held accountable for their outputs, then they should not be granted the status of epistemic authorities that are worthy of our epistemic respect.

In his comprehensive survey of the contemporary debate over scientific progress in philosophy of science, Rowbottom observes that philosophers of science have mostly relied on interpretations of historical cases from the history of science and intuitions elicited by hypothetical cases as evidence for or against philosophical accounts of scientific progress. Only a few have tried to introduce empirical evidence into this debate, whereas most others have resisted the introduction of empirical evidence by claiming that doing so would reduce the debate to empirical studies of science. In this paper, I set out to show how empirical evidence can be introduced into the scientific progress debate. I conduct a corpus-based, quantitative study whose results suggest that there is a positive linear relationship between _knowledge that_ talk and _knowledge how_ talk in scientific articles. These results are contrary to Niiniluoto’s view according to which there is a clear distinction between scientific progress and technological progress such that _knowledge that_ belongs to the former, whereas _knowledge how_ belongs to the latter.

More than 50 years after the publication of Thomas Kuhn’s seminal book, The Structure of Scientific Revolutions, this volume assesses the adequacy of the Kuhnian model in explaining certain aspects of science, particularly the social and epistemic aspects of science. One argument put forward is that there are no good reasons to accept Kuhn’s incommensurability thesis, according to which scientific revolutions involve the replacement of theories with conceptually incompatible ones. Perhaps, therefore, it is time for another “decisive transformation in the image of science by which we are now possessed.” Only this time, the image of science that needs to be transformed is the Kuhnian one. Does the Kuhnian image of science provide an adequate model of scientific practice? If we abandon the Kuhnian picture of revolutionary change and incommensurability, what consequences would follow from that vis-à-vis our understanding of scientific knowledge as a social endeavour? The essays in this collection continue this debate, offering a critical examination of the arguments for and against the Kuhnian image of science as well as their implications for our understanding of science as a social and epistemic enterprise.

The term scientism is used in several ways. It is used to denote an epistemological thesis according to which science is the source of our knowledge about the world and ourselves. Relatedly, it is used to denote a methodological thesis according to which the methods of science are superior to the methods of non-scientific fields or areas of inquiry, or even used to put forward a metaphysical thesis that what exists is what science says exists. In recent decades, the term scientism has acquired a derogatory meaning when it is used in defense of non-scientific ways of knowing. In particular, some philosophers level the charge of “scientism” against those (mostly scientists) who are dismissive of philosophy. Other philosophers, however, embrace scientism, or some variant thereof, and object to the pejorative use of the term scientism. This book critically examines the arguments for and against scientism of various kinds to answer the central question: does scientism pose an existential threat to philosophy, or should philosophy become more scientific?

Public debates over the morality of new or emerging technologies tend to devolve into false dichotomies of optimism versus pessimism. Playing God with Emerging Technologies: How to Avoid the Traps of Techno-Optimism and Techno-Pessimism provides a conceptual apparatus for engaging in such debates in a critical manner through the constructive lens of “playing God” arguments. Moti Mizrahi sketches a conceptual framework consisting of an argumentation scheme for “playing God” arguments along with Critical Questions. This framework can be used to analyze and evaluate “playing God” arguments as they are made in debates over the ethical development and deployment of new and emerging technologies, such as solar geoengineering, Artificial Intelligence (AI), autonomous vehicles, autonomous weapons, and more. Mizrahi argues that “playing God” arguments allow us to assume an intermediate, critical attitude between the extremes of hype and panic as well as to approach the governance of new or emerging technologies in ways that might help to increase our control over, improve our understanding of, and prevent our misuse or abuse of such technologies.

I argue that forays into history of science in Kuhn’s The Structure of Scientific Revolutions (1962/1996) are by and large instances of “Great Man” history of science. “Great Man” history is the idea that history is the biography of great men. The “Great Man” of science model not only excludes women and people of color from science but also suggests that only special, exceptional people can succeed in science. If this is correct, then Kuhn (1962/1996) fails to usher in a “historiographic revolution in the study of science” or a “new historiography” (Kuhn 1962/1996, 3), as the book purports to do. Instead, it merely perpetuates the defunct historiography of the “Great Man” of science.

“AI4Science” refers to the use of Artificial Intelligence (AI) in scientific research. As AI systems become more widely used in science, we need guidelines for when such uses are acceptable and when they are unacceptable. To that end, I propose that the distinction between the context of discovery and the context of justification, which comes from philosophy of science, may provide a preliminary but still useful guideline for acceptable uses of AI in science. Given that AI systems used in scientific research are black boxes, for the most part, we should use such systems in the context of discovery but not in the context of justification. The former refers to processes of idea generation, which may be unproblematically opaque whether they occur in human brains or artificial neural networks, whereas the latter refers to scientific methods by which scientific ideas are tested, confirmed, verified, and justified, which should be transparent.

I would like to thank Renia Gasparatou, Philip Goff, and Andreas Vrahimis for contributing to the book symposium on For and Against Scientism: Science, Methodology, and the Future of Philosophy (London: Rowman & Littlefield, 2022). I am grateful to James Collier for hosting this book symposium on the Social Epistemology Review and Reply Collective. In what follows, I will reply to Gasparatou and Vrahimis’s contributions to this book symposium.1 Before I do so, I will summarize what I take to be their main arguments against my conception of scientism. Briefly, my conception of scientism runs along the weak and broad lines of epistemological scientism (Mizrahi 2022a, 12). More specifically, Weak Scientism is the view that scientific knowledge is the best knowledge (or some other epistemic good, such as justified belief) we have. Weak Scientism is a weaker version of epistemological scientism than Strong Scientism, which is the view that scientific knowledge is the only knowledge we have. According to Weak Scientism, while non-scientific disciplines do produce knowledge, scientific disciplines produce knowledge that is superior—both quantitatively (in terms of research output and research impact) and qualitatively (in terms of explanatory, predictive, and instrumental success)—to non-scientific knowledge (Mizrahi 2017, 354; 2022a, 6–7; 2023, 41).

Mizrahi (2017a) advances an argument in support of Weak Scientism, which is the view that scientific knowledge is the best (but not the only) knowledge we have, according to which Weak Scientism follows from the premises that scientific knowledge is quantitatively and qualitatively better than non-scientific knowledge. In this paper, I develop a different argument for Weak Scientism. This latter argument for Weak Scientism proceeds from the premise that academic disciplines that make progress are superior to academic disciplines that do not make progress. In other words, other things being equal, it is generally better for an academic discipline to make progress than to make little or no progress, given that an academic discipline that is making little or no progress is an academic discipline that is failing to achieve its epistemic goals. Now, if there is no question among academic philosophers that science makes progress, and significantly so, but there is an open question among academic philosophers as to whether academic philosophy makes progress (and if so, how much), then academic philosophers would have to agree that science is superior to academic philosophy in terms of making progress. I develop this argument in this paper and provide empirical evidence suggesting that the premises would be acceptable to academic philosophers.

Drawing on the epistemology of logic literature on anti-exceptionalism about logic, we set out to investigate the following metaphilosophical questions empirically: Is philosophy special? Are its methods (dis)continuous with science? More specifically, we test the following metaphilosophical hypotheses empirically: philosophical deductivism, philosophical inductivism, and philosophical abductivism. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we searched through a large corpus of philosophical texts mined from the JSTOR database (N = 435,703) to find patterns of argumentation. The results of our quantitative, corpus-based study suggest that deductive arguments are significantly more common than abductive arguments and inductive arguments in philosophical texts overall, but they are gradually and steadily giving way to non-deductive (i.e. inductive and abductive) arguments in academic philosophy.

In this paper, we set out to investigate the following question: if science relies heavily on induction, does philosophy of science rely heavily on induction as well? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database (n = 14,199) in order to answer this question empirically. If philosophy of science relies heavily on induction, just as science supposedly does, then we would expect to find significantly more inductive arguments than deductive arguments and abductive arguments in the published works of philosophers of science. Using indicator words to classify arguments by type (namely, deductive, inductive, and abductive arguments), we search through our corpus to find patterns of argumentation. Overall, the results of our study suggest that philosophers of science do rely on inductive inference. But induction may not be as foundational to philosophy of science as it is thought to be for science, given that philosophers of science make significantly more deductive arguments than inductive arguments. Interestingly, our results also suggest that philosophers of science do not rely on abductive arguments all that much, even though philosophers of science consider abduction to be a cornerstone of scientific methodology.

While the empirical evidence pointing to a gender gap in professional, academic philosophy in the English-speaking world is widely accepted, explanations of this gap are less so. In this paper, we aim to make a modest contribution to the literature on the gender gap in academic philosophy by taking a quantitative, corpus-based empirical approach. Since some philosophers have suggested that it may be the argumentative, “logic-chopping,” and “paradox-mongering” nature of academic philosophy that explains the underrepresentation of women in the discipline, our research questions are the following: Do men and women philosophers make different types of arguments in their published works? If so, which ones and with what frequency? Using data mining and text analysis methods, we study a large corpus of philosophical texts mined from the JSTOR database in order to answer these questions empirically. Using indicator words to classify arguments by type, we search through our corpus to find patterns of argumentation. Overall, the results of our empirical study suggest that women philosophers make deductive, inductive, and abductive arguments in their published works just as much as male philosophers do, with no statistically significant differences in the proportions of those arguments relative to each philosopher’s body of work.

In a reply to Mizrahi (2019), Bryant (2020) raises several methodological concerns regarding my attempt to test hypotheses about the observation that academic philosophers tend to find “scientism” threatening empirically using quantitative, corpus based methods. Chief among her methodological concerns is that numbers of philosophical publications that mention “scientism” are a “poor proxy for scholarly sentiment” (Bryant 2020, 31). In reply, I conduct a sentiment analysis that is designed to find out whether academic philosophers have negative, positive, or neutral sentiments toward “scientism.” The results of this analysis suggest that, for the most part, articles on “scientism” written by academic philosophers tend to contain mostly negative rather than positive (or neutral) sentiments about “scientism.”

Philosophy is often divided into two traditions: analytic and continental philosophy. Characterizing the analytic-continental divide, however, is no easy task. Some philosophers explain the divide in terms of the place of argument in these traditions. This raises the following questions: Is analytic philosophy rife with arguments while continental philosophy is devoid of arguments? Or can different types of arguments be found in analytic and continental philosophy? This paper presents the results of an empirical study of a large corpus of philosophical texts mined from the JSTOR database (n = 53,260) designed to find patterns of argumentation by type. Overall, the results suggest that there are no significant differences between the types of arguments advanced in analytic and continental philosophy journal articles. The findings, therefore, provide no empirical support to the hypothesis that the divide between analytic and continental philosophy has to do with the place of argument in these traditions.

This paper presents the results of an empirical study following up on Mizrahi (2021). Using the same methods of text mining and corpus analysis used by Mizrahi (2021), we test empirically a philosophical account of scientific progress that Mizrahi (2021) left out of his empirical study, namely, the so-called functional-internalist account of scientific progress according to which the aim or goal or scientific research is to solve problems. In general, our results do not lend much empirical evidence in support of the problem-solving model of scientific progress over the other philosophical accounts of scientific progress (namely, the epistemic, noetic, and semantic accounts of scientific progress) tested in Mizrahi (2021) and in this follow-up study. Of all the subjects in the JSTOR database we have tested in this study, however, Mathematics is an interesting exception as far as the problem-solving model of scientific progress is concerned. For, in Mathematics alone, we have found that there is significantly more talk of the aims and/or goals of research in terms of solutions than in terms of truth, knowledge, or understanding.

In this paper, I reply to Seungbae Park’s (2021) reply to my (Mizrahi 2021) reply to his (Park 2020) critique of the view I defend in Chapter 6 of The Relativity of Theory: Key Positions and Arguments in the Contemporary Scientific Realism/Antirealism Debate (Cham: Springer, 2020), namely, Relative Realism. Relative Realism is the view that, of a set of competing scientific theories, the more successful theory is comparatively true. Comparative truth is a relation between competing theories. So, to say that T1 is comparatively true is to say that T1 is closer to the truth than its competitors, T2, T3, …, Tn. In his latest reply, Park (2021) clarifies his notions of “T-space” and “F-space,” which he now labels “T-space” and “O-space,” and further develops what he calls the “Argument from Double Spaces,” which is supposed to show that, contrary to what the relative realist argues, relative judgments about the comparative truth of competing theories are not rationally justified. I argue that Park’s revised version of the “Argument from Double Spaces” still fails as an argument against Relative Realism.

In this paper, I argue that appeals to intuition in Analytic Philosophy are not compelling arguments because intuitions are not the sort of thing that has the power to rationally persuade other professional analytic philosophers. This conclusion follows from reasonable premises about the goal of Analytic Philosophy, which is rational persuasion by means of arguments, and the requirement that evidence for and/or against philosophical theses used by professional analytic philosophers be public (or transparent) in order to have the power to rationally persuade other professional analytic philosophers. Since intuitions are not public (or transparent) evidence, it follows that appeals to intuition are not compelling arguments for and/or against philosophical theses because they lack the power to rationally persuade other professional analytic philosophers.

In this paper, I reply to Seungbae Park’s (2020) critique of the view I defend in Chapter 6 of The Relativity of Theory: Key Positions and Arguments in the Contemporary Scientific Realism/Antirealism Debate (Cham: Springer, 2020), namely, Relative Realism. Relative Realism is the view that, of a set of competing scientific theories, the more predictively successful theory is comparatively true. Comparative truth is a relation between competing theories. So, to say that T1 is comparatively true is to say that T1 is closer to the truth than its competitors, T2, T3, ..., Tn. Park offers two arguments against Relative Realism. The first is an argument by analogy to NBA players, which is supposed to show that, contrary to what the relative realist argues, absolute judgments about the (approximate) truth and (predictive) success of competing theories are rationally justified. The second is what Park calls “The Argument from Double Spaces,” which is supposed to show that, contrary to what the relative realist argues, relative judgments about the (comparative) truth of competing theories are not rationally justified. I argue that Park’s arguments fail to do what he wants them to do.

The aim of this paper is to contribute to the debate over the nature of scientific progress in philosophy of science by taking a quantitative, corpus-based approach. By employing the methods of data science and corpus linguistics, the following philosophical accounts of scientific progress are tested empirically: the semantic account of scientific progress, the epistemic account of scientific progress, and the noetic account of scientific progress. Overall, the results of this quantitative, corpus-based study lend some empirical support to the epistemic and the noetic accounts over the semantic account of scientific progress, for they suggest that practicing scientists use the terms ‘knowledge’ and ‘understanding’ significantly more often than the term ‘truth’ when they talk about the aims or goals of scientific research in their published works. But the results do not favor the epistemic account over the noetic account, or vice versa, for they reveal no significant differences between the frequency with which practicing scientists use the terms ‘knowledge’ and ‘understanding’ when they talk about the aims or goals of scientific research in their published works.