Research

Overview

Primarily, my research focuses on questions that fall within general philosophy of science, with overlap into both formal and traditional epistemology. I’ve long been interested in the precise nature of explanatory reasoning, e.g. Inference to the Best Explanation, and its relationship to formal, probabilistic accounts of scientific method, e.g. Bayesianism. Additionally, I’ve worked on issues that fall within philosophy of biology. In particular, I’ve long been interested in phylogenetic inference and the nature of cultural evolution, and especially in the recent application of computational methods from biology within historical linguistics. Much of my more recent work, however, has consisted of applications of my research in general philosophy of science to issues raised by new and emerging technologies. This includes both epistemological and ethical issues, and especially ones at the intersection of the two. More information about my primary research can be found here.

Publications

Fritts, M. & Cabrera, F. (forthcoming). "Fake News and Epistemic Vice: Combating a Uniquely Noxious Market." Journal of the American Philosophical Association, 1-25.

Abstract: The topic of fake news has received increased attention from philosophers since the term became a favorite of politicians (Habgood-Coote 2016; Dentith 2016). Notably missing from the conversation, however, is a discussion of fake news and conspiracy theory media as a market. This paper will take as its starting point the account of noxious markets put forward by Debra Satz (2010), and will argue that there is a pro tanto moral reason to restrict the market for fake news. Specifically, we begin with Satz’s argument that restricting a market may be required when i) that market inhibits citizens from being able to stand in an equal relationship with one another, and ii) this problem cannot be solved without such direct restrictions. Our own argument then proceeds in three parts: first, we argue that the market for fake news fits Satz’s description of a noxious market; second, we argue against explanations of the proliferation of fake news that are couched in terms of “epistemic vice”, and likewise argue against prescribing critical thinking education as a solution to the problem; finally, we conclude that, in the absence of other solutions to mitigate the noxious effects of the fake news market, we have a pro tanto moral reason to impose restrictions on this market. At the end of the paper, we consider one proposal to regulate the fake news market, which involves making social media outlets potentially liable in civil court for damages caused by the fake news hosted on their websites.

Fritts, M. & Cabrera, F. (forthcoming). "Online Misinformation and ‘Phantom Patterns’: Epistemic Exploitation in the Era of Big Data", Southern Journal of Philosophy, 1-29.

In this paper, we examine how the availability of massive quantities of data i.e., the “Big Data” phenomenon, contributes to the creation, spread, and harms of online misinformation. Specifically, we argue that a factor in the problem of online misinformation is the evolved human instinct to recognize patterns. While the pattern-recognition instinct is a crucial evolutionary adaptation, we argue that in the age of Big Data, these capacities have, unfortunately, rendered us vulnerable. Given the ways in which online media outlets profit from the spread of misinformation by preying on this pattern-finding instinct, we conceptualize the problem that we identify as a morally objectionable form of “epistemic exploitation.” As we argue, the consumer of digital misinformation is often exploited by having her pattern-recognition instinct used against her. This exploitation is morally objectionable because it deprives her of an epistemic good to which she has a right. This epistemic good is the integrity of the pattern-recognition instinct itself which, we argue, is a capacity that allows us to participate in uniquely human goods. While our primary goal is to bring attention to this form of epistemic exploitation, we conclude by briefly evaluating some general solutions to the growing problem of online misinformation.

Fritts, M. & Cabrera, F. (2021). "AI Recruitment Algorithms and the Dehumanization Problem." Ethics and Information Technology, 1-11, doi: 10.1007/s10676-021-09615-w

According to a recent survey by the HR Research Institute, as the presence of artificial intelligence (AI) becomes increasingly common in the workplace, HR professionals are worried that the use of recruitment algorithms will lead to a “dehumanization” of the hiring process. Our main goals in this paper are threefold: i) to bring attention to this neglected issue, ii) to clarify what exactly this concern about dehumanization might amount to, and iii) to sketch an argument for why dehumanizing the hiring process is ethically suspect. After distinguishing the use of the term “dehumanization” in this context (i.e., removing the human presence) from its more common meaning in the interdisciplinary field of dehumanization studies (i.e., conceiving of other humans as subhuman), we argue that the use of hiring algorithms may negatively impact the employee-employer relationship. We argue that there are good independent reasons to accept a substantive employee-employer relationship, as well as an applicant-employer relationship, both of which are consistent with a stakeholder theory of corporate obligations. We further argue that dehumanizing the hiring process may negatively impact these relationships because of the difference between the values of human recruiters and the values embedded in recruitment algorithms. Drawing on Nguyen’s (2021) critique of how Twitter “gamifies communication”, we argue that replacing human recruiters with algorithms imports artificial values into the hiring process. We close by briefly considering some ways to potentially mitigate the problems posed by recruitment algorithms, along with the possibility that some difficult trade-offs will need to be made.

Cabrera, F. (2021). “Second Philosophy and Testimonial Reliability: Philosophy of Science for STEM Students,” European Journal for Philosophy of Science, 11(67): 1-13.

In this paper, I describe some strategies for teaching an introductory philosophy of science course to Science, Technology, Engineering, and Mathematics (STEM) students, with reference to my own experience teaching a philosophy of science course in the Fall of 2020. The most important strategy that I advocate is what I call the “Second Philosophy” approach, according to which instructors ought to emphasize that the problems that concern philosophers of science are not manufactured and imposed by philosophers from the outside, but rather are ones that arise internally, during the practice of science itself. To justify this approach, I appeal to considerations from both educational research and the epistemology of testimony. In addition, I defend some distinctive learning goals that philosophy of science instructors ought to adopt when teaching STEM students, which include rectifying empirically well-documented shortcomings in students’ conceptions of the “scientific method” and the “nature of science.” Although my primary focus will be on teaching philosophy of science to STEM students, much of what I propose can be applied to non-philosophy majors generally. Ultimately, as I argue, a successful philosophy of science course for non-philosophy majors must be one that advances a student’s science education. The strategies that I describe and defend here are aimed at precisely that end.

Cabrera, F. (2021). “Is Epistemic Anxiety an Intellectual Virtue?” Synthese, 1–25. doi:10.1007/s11229-021-03383-2

In this paper, I discuss the ways in which epistemic anxiety promotes well-being, specifically by examining the positive contributions that feelings of epistemic anxiety make toward intellectually virtuous inquiry. While the prospects for connecting the concept of epistemic anxiety to the two most prominent accounts of intellectual virtue, i.e., “virtue-reliabilism” and “virtue-responsibilism”, are promising, I primarily focus on whether the capacity for epistemic anxiety counts as an intellectual virtue in the reliabilist sense. As I argue, there is a close yet unexplored connection between feelings of epistemic anxiety and the form of inference commonly known as “Inference to the Best Explanation” (IBE). Specifically, I argue that both the recognition that some fact requires an explanation—a necessary first step in applying IBE—and the subsequent motivation to employ IBE are typically facilitated by feelings of epistemic anxiety. So, provided IBE is truth-conducive the capacity for epistemic anxiety should count as an intellectual virtue in the reliabilist sense. After outlining my main argument, I address the challenge that the capacity for epistemic anxiety has the potential to be misleading. To respond to this challenge, I discuss how our recognition that a fact requires an explanation must in part be a species of practical knowledge, rather than theoretical knowledge. For the agent to skillfully distinguish between facts that require an explanation and facts that do not, she must develop the virtuous disposition to feel the appropriate amount of epistemic anxiety. Despite the many negative aspects associated with anxiety, as I conclude, being disposed to feel the appropriate amount of epistemic anxiety is ultimately good for us.

Cabrera, F. (2021). "String Theory, Non-Empirical Theory Assessment, and the Context of Pursuit", Synthese (198): 3671–3699.

Abstract: In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to non-empirical methods of theory assessment given the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I suggest, much of the controversy stems from a failure to properly distinguish the "context of justification" from the "context of pursuit". Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit.

Cabrera, F. (2020). “The Fate of Explanatory Reasoning in the Age of Big Data.” Philosophy & Technology, 1–21 doi:10.1007/s13347-020-00420-9

Abstract: In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In section 3, I argue that these methodological claims are in tension with a prominent account of scientific method, often called “Inference to the Best Explanation” (IBE). Later on, in section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely the argument due to Roche and Sober (2013) that “explanatoriness is evidentially irrelevant”. This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In section 4, I consider some extant responses to this argument, especially that of Climenhaga (2017). In section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, (CCR), which states roughly that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations”, chance correlations which we should not rely upon for predictive inference. In section 7, I offer some concluding remarks

Cabrera, F. (2020). "Evidence and Explanation in Cicero's On Divination", Studies in History and Philosophy of Science Part A. 82: 34–43.

Abstract: In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault on superstition that it is sometimes portrayed to be. Then, I offer an extended analysis of the second of the main arguments against divination given by Marcus. Inspired by Marcus’ second main argument, I formulate, explicate, and defend a substantive principle of scientific methodology that I call the “Ciceronian Causal-Nomological Requirement” (CCR). Roughly, this principle states that causal knowledge is essential for relying on correlations in predictive inference. Although I go on to argue that Marcus’ application of the CCR in his debate with Quintus is dialectically inadequate, I conclude that De Divinatione deserves its place in Cicero’s philosophical corpus, and that ultimately, its significance for the history and philosophy of science ought to be recognized.

Cabrera, F. (2020). “Does IBE Require a ‘Model’ of Explanation?”, The British Journal for the Philosophy of Science. 71(2): 727–750.

Abstract: Here, I consider an important challenge to the popular theory of scientific inference commonly known as “Inference to the Best Explanation” (IBE), one which has received scant attention. The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival models of explanation. However, I argue that i) how ranking explanations on this pluralistic account of IBE remains obscure and ii) pluralism leads to contradictory results. In light of these objections, I attempt to dissolve the problem by showing why IBE does not require a “model” of explanation and by giving an account of what explanation consists in within the context of IBE.

Cabrera, F. (2020). "Critical Notice: Kevin McCain and Ted Poston's Best Explanations", International Journal for the Study of Skepticism, 10(2): 157–166.

Abstract: In this critical notice, I focus my attention on the essays that deal with the explanationist response to skepticism. I critically engage with several of the essays in the volume.

Cabrera, F. (2017). “Can there be a Bayesian explanationism? On the prospects of a productive partnership”, Synthese, 194(4):1245–1272

Abstract: In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends.

Cabrera, F. (2017). “Cladistic Parsimony, Historical Linguistics, and Cultural Phylogenetics”, Mind & Language, 32(1):65-100

Abstract: Here, I consider the recent application of phylogenetic methods from systematic biology in historical linguistics. After a preliminary survey of one such method, i.e. cladistic parsimony, I respond to two common criticisms of cultural phylogenies: (1) that cultural artifacts cannot be modeled as tree-like because of borrowing across lineages, and (2) that the mechanism of cultural change differs radically from that of biological evolution. I argue that while perhaps (2) remains true for certain cultural artifacts, the nature of language may be such as to side-step this objection. Moreover, I explore the possibility that cladistic parsimony can be justified even if (2) is true by thinking of applications of cladistic parsimony as one particular instance of IBE.

Book Reviews

Cabrera, F. (2021). "Correlation Isn't Good Enough: Causal Explanation and Big Data." Metascience, 1-4.

Abstract: A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020.

Dissertation

"Inference to the Best Explanation, Bayesianism, and the Context of Pursuit"

Works In Progress

“Modeling Action: Recasting the Causal Theory” (with Megan Fritts),

“Scientific Modeling and the Mathematization of Nature”