Two epistemological critiques of non-naturalism are not always carefully distinguished. According to the Causal Objection, the fact that moral properties cannot cause our moral beliefs implies that it would be a coincidence if many of them were true. According to the Evolutionary Objection, the fact that evolutionary pressures have influenced our moral beliefs implies a similar coincidence. After distinguishing these epistemological critiques, I provide an extensive defense of the Causal Objection that also strengthens the Evolutionary Objection. In particular, (...) I formulate a “Master Causal Objection” featuring the controversial premise that non-naturalism can provide no adequate explanation for moral knowledge. I defend this premise by first narrowing down the range of candidate explanations to conceptual, constitutive, and evolutionary explanations, and then considering and eliminating each of these in turn. My discussion of evolutionary explanations suggests that non-naturalists must refute the Causal Objection in order to refute the Evolutionary Objection. (shrink)

This paper formulates a general epistemological argument against what I call non-causal realism, generalizing domain specific arguments by Benacerraf, Field, and others. First I lay out the background to the argument, making a number of distinctions that are sometimes missed in discussions of epistemological arguments against realism. Then I define the target of the argument—non-causal realism—and argue that any non-causal realist theory, no matter the subject matter, cannot be given a reasonable epistemology and so should be (...) rejected. Finally I discuss and respond to several possible responses to the argument. In addition to clearing up and avoiding numerous misunderstandings of arguments of this kind that are quite common in the literature, this paper aims to present and endorse a rigorous and fully general epistemological argument against realism. (shrink)

Applied Evolutionary Epistemology is a scientific-philosophical theory that defines evolution as the set of phenomena whereby units evolve at levels of ontological hierarchies by mechanisms and processes. This theory also provides a methodology to study evolution, namely, studying evolution involves identifying the units that evolve, the levels at which they evolve, and the mechanisms and processes whereby they evolve. Identifying units and levels of evolution in turn requires the development of ontological hierarchy theories, and examining mechanisms and processes necessitates (...) theorizing about causality. Together, hierarchy and causality theories explain how biorealities form and diversify with time. This paper analyzes how Applied EE redefines both hierarchy and causality theories in the light of the recent explosion of network approaches to causal reasoning associated with studies on reticulate and macroevolution. Causality theories have often been framed from within a rigid, ladder-like hierarchy theory where the rungs of the ladder represent the different levels, and the elements on the rungs represent the evolving units. Causality then is either defined reductionistically as an upward movement along the strands of a singular hierarchy, or holistically as a downward movement along that same hierarchy. Upward causation theories thereby analyze causal processes in time, i.e. over the course of natural history or phylogenetically, as Darwin and the founders of the Modern Synthesis intended. Downward causation theories analyze causal processes in space, ontogenetically or ecologically, as the current eco-evo-devo schools are evidencing. This work demonstrates how macroevolution and reticulate evolution theories add to the complexity by examining reticulate causal processes in space–time, and the interactional hierarchies that such studies bring forth introduce a new form of causation that is here called reticulate causation. Reticulate causation occurs between units and levels belonging to different as well as to the same ontological hierarchies. This article concludes that beyond recognizing the existence of multiple units, levels, and mechanisms or processes of evolution, also the existence of multiple kinds of evolutionary causation as well as the existence of multiple evolutionary hierarchies needs to be acknowledged. This furthermore implies that evolution is a pluralistic process divisible into different kinds. (shrink)

Philosophical discussions on causal inference in medicine are stuck in dyadic camps, each defending one kind of evidence or method rather than another as best support for causal hypotheses. Whereas Evidence Based Medicine advocates the use of Randomised Controlled Trials and systematic reviews of RCTs as gold standard, philosophers of science emphasise the importance of mechanisms and their distinctive informational contribution to causal inference and assessment. Some have suggested the adoption of a pluralistic approach to causal (...) inference, and an inductive rather than hypothetico-deductive inferential paradigm. However, these proposals deliver no clear guidelines about how such plurality of evidence sources should jointly justify hypotheses of causal associations. We here develop such guidelines by first giving a philosophical analysis of the underpinnings of Hill’s viewpoints on causality. We then put forward an evidence-amalgamation framework adopting a Bayesian net approach to model causal inference in pharmacology for the assessment of harms. Our framework accommodates a number of intuitions already expressed in the literature concerning the EBM vs. pluralist debate on causal inference, evidence hierarchies, causal holism, relevance, and reliability. (shrink)

The term “historical epistemology” can be read in two different ways: (1) as referring to a program of ‘historicizing’ epistemology, in the sense of a critique of traditional epistemology’s tendency to gloss over historical context, or (2) as a manifesto of ‘epistemologizing’ history, i.e. as a critique of radical historicist and relativist approaches. In this paper I will defend a position in this second sense. I show that one can account for the historical development and diversity of (...) science without disavowing the relevance of a (normatively understood) epistemology and without denying the existence of human cognitive universals across historical and cultural differences. In support of my thesis, I draw on cognitive scientific research on causal and symbolic cognition, arguing that causal understanding constitutes a basic part of science, which, in the course of its development, becomes more and more superimposed by a culturally and historically variable symbolic superstructure. (shrink)

Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. (...) However, I argue that this is only part of the epistemology of causal selection. Recent work on portable causes has implicitly assumed them to be portable within the same causal system at a later time. As a result, it has appeared that the objective content of causal selection includes only facts about the causal structure of that single system. In contrast, I present a case study from systems biology in which scientists are searching for causal factors that are portable across rather than within causal systems. By paying careful attention to how these biologists find portable causes, I show that the objective content of causal selection can extend beyond the immediate systems of interest. In particular, knowledge of the evolutionary history of gene networks is necessary for correctly identifying causal patterns in these networks that explain cellular behavior in a portable way. (shrink)

This paper contributes to an increasing literature strengthening the connection between epistemic logic and epistemology (Van Benthem, Hendricks). I give a survey of the most important applications of epistemic logic in epistemology. I show how it is used in the history of philosophy (Steiner's reconstruction of Descartes' sceptical argument), in solutions to Moore's paradox (Hintikka), in discussions about the relation between knowledge and belief (Lenzen) and in an alleged refutation of verificationism (Fitch) and I examine an early argument (...) about the (im)possibility of epistemic logic (Hocutt). Subsequently, I deal with interpretive questions about epistemic logic that, although implicitly, already appeared in the first section. I contend that a conception of epistemic logic as a theory of knowledge assertions is incoherent, and I argue that it does not make sense to adopt a normative interpretation of epistemic logic. Finally, I show ways to extend epistemic logic with other branches of philosophical logic so as to make it useful for some epistemological questions. Conditional logics and logics of public announcement are used to understand causal theories of knowledge and versions of reliabilism. Temporal logic helps understand some dynamic aspects of knowledge as well as the verificationist thesis. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is (...) necessary for the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

The general goal is to encourage informal logicians and those interested in applied epistemology to look at epidemiology as a paradigmatic science crucially dependant on argumentation to justify its claims. Three specific goals are: 1. exemplify applied epistemology by looking critically at causal argumentation in epidemiology, 2. show that justification of causal claims in epidemiology is a form of “argument to the best explanation,” 3. show that there could be a symbiotic relationship between epidemiology and work (...) in various applied reasoning disciplines such as argumentation and “applied epistemology.”. (shrink)

In 1958 I set down some thoughts that arose from an attempt to consider epistemological problems on the assumptions that The biology of the human nervous system is relevant to epistemology and The human nervous system, like every other object of biological investigation, is a product of evolution by natural selection. These thoughts lay more or less neglected until they were brought stunningly to mind by Professor George Gaylord Simpson's [1] recent paper on “Biology and the Nature of Science”. (...) In that paper Professor Simpson writes: “Still another consideration seems to me the most interesting of all, and yet I have never seen it clearly expressed elsewhere. It is, in a sense a validation of the ‘animal faith’ given by Russell … as sole basis for assuming that we really can obtain knowledge of the outer world. The fact is that man originated by a slow process of evolution guided by natural selection. At every stage in this long progression our ancestors necessarily had adaptive reactions to the world around them. As behavior and sense organs became more complex, perception of sensations from those organs obviously maintained a realistic relationship to the environment. To put it crudely but graphically, the monkey who did not have a realistic perception of the tree branch he jumped for was soon a dead monkey-and therefore did not become one of our ancestors. Our perceptions do give true, even though not complete, representations of the outer world because that was and is a biological necessity.”. (shrink)

Virtue epistemologies about knowledge have traditionally been divided into two camps: virtue reliabilism and virtue responsibilism. Initially, what set them apart was that virtue responsibilism took intellectual character virtues and responsible agency to be necessary to knowledge acquisition, whereas virtue reliabilism took reliable cognitive faculties to be constitutive of it instead. Despite recent concessions between these camps, there are residual disagreements. Chapter 8 focuses primarily on Linda Zagzebski’s account of virtue responsibilism and John Greco’s and Ernest Sosa’s defenses of virtue (...) reliabilism. It argues that despite their misgivings about virtue responsibilism, Greco and Sosa are ultimately required to accept that intellectual character virtues involve a substantial truth-motivational component, and that knowledge requires a kind of epistemic responsibility that is far more substantive than a causal, naturalistic notion of attribution. (shrink)

Robust virtue epistemology holds that knowledge is true belief obtained through cognitive ability. In this essay I explain that robust virtue epistemology faces a dilemma, and the viability of the theory depends on an adequate understanding of the ‘through’ relation. Greco interprets this ‘through’ relation as one of causal explanation; the success is through the agent’s abilities iff the abilities play a sufficiently salient role in a causal explanation of why she possesses a true belief. In (...) this paper I argue that Greco’s account of the ‘through’ relation is inadequate. I describe kinds of counterexample and explain why salience is the wrong kind of property to track epistemically relevant conditions or to capture the nature of knowledge. Advocates of robust virtue epistemology should develop an alternative account of the ‘through’ relation. I also argue that virtue epistemology should employ an environment-relative interpretation of epistemic virtue. (shrink)

The manipulationist account of causation provides a conceptual analysis of cause-effect relationships in terms of hypothetical experiments. It also explains why and how experiments are used for the empirical testing of causal claims. This paper attempts to apply the manipulationist account of causation to a broader range of experiments—a range that extends beyond experiments explicitly designed for the testing of causal claims. I aim to show that the set of causal inferences afforded by an experiment is determined (...) solely on the basis of contrasting case structures that I call “experimental series”, and that the conditions that suffice for causal inference obtain quite commonly, even among “ordinary” experiments that are not explicitly designed for the testing of causal claims. (shrink)

Although Thomas Aquinas assumes that all knowledge begins in the senses, he maintains that substantial forms and the essences of material things are not apparent to the senses. Clearly, the noetic of abstraction per se cannot account for our knowledge of them. Thomas often says that they are “unknown in themselves” but “become known” through their accidents. The author argues that properties, or proper accidents — namely, accidents that are interconvertible with a subject — play a crucial role in this (...) obscure area of Thomas’s thought. Beginning with an examination of the property in logic , the author goes on to examine Thomas’s accounts of heat as a property of fire, and the powers of the soul as properties of its essence. Thomas maintains that such properties flow from the essence by a causal relation that he calls resultatio, but that their coexistence with the essence is absolutely necessary in a quasi-logical manner . Finally, the author suggests that in Thomas’s view, accidents really do make the hidden quiddities of their subjects known: knowing created things through their accidents is not at all like knowing God through creatures. (shrink)

The problem that will be dealt with in this paper is al-Ghazālī’saccount of causality in the observed phenomenal world where he denies thenecessity of that causation. This denial brought about Ibn Rushd’s accusationon the denial of knowledge, arguing that knowledge is based on causalityin the phenomenal words. However, detailed perusal of al-Ghazālī’s workssuggests that Ibn Rushd’s accusation is not the case. al-Ghazālī differentiatesbetween knowledge of the fact and knowledge of reasoned fact, or in otherwords he distinguished ontological causality from logical (...) causality. Inaddition, al-Ghazālī’s denial of causal necessity is supported by his ownlogic, where the knowledge attainment becomes possible when it is examinedfrom demonstrative sciences, especially from empirically tested premises. (shrink)

According to a common objection to epistemological naturalism, no empirical, scientific theory of knowledge can be normative in the way epistemological theories need to be. In response, such naturalists as W.V. Quine have claimed naturalized epistemology can be normative by emulating engineering disciplines and addressing the relations of causal efficacy between our cognitive means and ends. This paper evaluates that "engineering reply" and finds it a mixed success. Based on consideration of what it might mean to call a (...) theory "normative," seven versions of the normativity objection to epistemological naturalism are formulated. The engineering reply alone is sufficient to answer only the four least sophisticated versions. To answer the others, naturalists must draw on more resources than their engineering reply alone provides. (shrink)

Epistemologies and research methods are not free of metaphysics. This is to say that they are both, supported by (or presumed by), and support (or presume) fundamental ontologies. A discussion of the epistemological foundations of "multimethod" research in the social sciences—in as much as such research claims to unearth "causal" relations—therefore cannot avoid the ontological presuppositions or implications of such a discussion. But though there isn’t necessarily a perfect correspondence between ontology, epistemology, and methodology, they do constrain each (...) other. As such it is possible to make methodological choices that are at odds with one’s (implicit) ontology or argue from an ontology that is inconsistent one’s choice of methods.Yet lack of recognition of this fact has hampered methodological discussions in political science, especially with respect to the discussion on the merits of multimethod research. The ontology implicitly accepted in such discussions is "reductionist" and "regularist," that is, one that respectively defines causes in terms of noncausal relations and states of affair and affirms that such noncausal relations are regularities in nature. This article will argue that any attempt to fit "multimethod" research (where "multimethod" signifies some combination of inferential statistics and case studies) within this narrow ontology is destined to fail since such a metaphysics logically cannot accord case studies a necessary or sufficient role in the in the establishment of causal relations. However, there are metaphysical positions within the ambit of an empiricist philosophy of science that can accommodate multiple methods without contradiction. The article discusses two such ontologies and suggests ways in which they might allow the establishment of a coherent epistemological foundation for multimethod research, however, within a decidedly empiricist philosophy of science. (shrink)

The dominant conception of delusion in psychiatry (in textbooks, research papers, diagnostic manuals, etc.) is predominantly epistemic. Delusions are almost always characterized in terms of their epistemic defects, i.e., defects with respect to evidence, reasoning, judgment, etc. However, there is an individualistic bias in the epistemic conception; the alleged epistemic defects and abnormalities in delusions relate to individualistic epistemic processes rather than social epistemic processes. We endorse the social epistemological turn in recent philosophical epistemology, and claim that a corresponding (...) turn is needed in the study of delusions. It is a turn from the (purely) individualistic conception, which characterizes delusions only by individualistic epistemic defects and abnormalities, to the (partially) social epistemic conception, which characterizes delusions by individualistic as well as social epistemic defects and abnormalities. This paper is intended as an initial step toward such a social epistemological turn. In particular, we will develop a new model of the development of delusions according to which testimonial abnormalities, including testimonial isolation and testimonial discount, are a causal factor in the development of delusions. (shrink)

Some people -- including the present author -- have proposed and defended alternative restricted causal principles that block Robert Koons’s ’new’ cosmological argument without undermining the intuition that causation is very close to ubiquitous. In "Epistemological Foundations for the Cosmological Argument", Koons argues that any restricted causal principles that are insufficient for the purposes of his cosmological argument cause epistemological collapse into general scepticism. In this paper I argue, against Koons, that there is no reason to suppose that (...) my favourite restricted causal principle precipitates epistemological collapse into general scepticism. If we impose the ’same kinds’ of restrictions on causal epistemological principles and on principles of general causation, then we cannot be vulnerable to the kind of argument that Koons develops. (shrink)

David Hume's _Treatise on Human Nature_ and _Enquiry Concerning Human Understanding_ are amongst the most widely-studies texts on philosophy. _Hume's Epistemology and Metaphysics: An Introduction_ presents in a clear, concise and accessible manner the key themes of these texts. Georges Dicker clarifies Hume's views on meaning, knowledge, causality, and sense perception step by step and provides us with a sharp picture of how philosophical thinking has been influenced by Hume. Accessible to anyone coming to Hume for the first time, (...) _Hume's Epistemology and Metaphysics_ is an indispensible guide to Hume's philosophical thinking. (shrink)

Feminist epistemology aims to propose epistemic reasons for increasing the representation of women or socially subordinated people in science. This is typically done—albeit often only implicitly—by positing a causal mechanism through which the representation of sociodemographic minorities exerts a positive effect on scientific advancement. Two types of causal theories can be identified. The “epistemic diversity thesis” presents a causal path from sociodemographic diversity to scientific progress mediated by epistemic diversity. The “thesis of epistemic advantage” proposes a (...) causal path from social subjugation to capacity for inquiry. The latter theory is defined with substantial ambiguity in the existing literature, and I present an explicit causal reformulation that disambiguates it. The epistemic diversity thesis focuses on the effect of group composition on collective epistemic performance and is largely silent about what kind of characteristics lead to individual epistemic excellence. On the other hand, the thesis of epistemic advantage seeks to identify sociodemographic background conditions that make certain epistemic agents strictly better knowers or inquirers than others and pays little attention to the synergistic effects of diverse group composition. Such a difference in the causal structure reflects the diverging political characteristics of the two theories. (shrink)

Philosophers have recently highlighted substantial affinities between causation and grounding, which has inclined some to import the conceptual and formal resources of causal interventionism into the metaphysics of grounding. The prospect of grounding interventionism raises two important questions: exactly what are grounding interventions, and why should we think they enable knowledge of grounding? This paper will approach these questions by examining how causal interventionists have addressed (or might address) analogous questions and then comparing the available options for grounding (...) interventionism. I argue that grounding interventions must be understood in worldly terms, as adding something to or deleting something from the roster of entities, or making some fact obtain or fail to obtain. I consider three bases for counterfactual assessment: imagination, structural equation models, and background theory. I conclude that grounding interventionism requires firmer epistemological foundations, without which the interventionist's epistemology of grounding is incomplete and ineffectually rationalist. (shrink)

The 2021 Nobel Prize in Economics recognized an epistemology of causal inference based on the Rubin causal model (Rubin 1974), which merits broader attention in philosophy. This model, in fact, presupposes a logical principle of counterfactuals, Conditional Excluded Middle (CEM), the locus of a pivotal debate between Stalnaker (1968) and Lewis (1973) on the semantics of counterfactuals. Proponents of CEM should recognize that this connection points to a new argument for CEM---a Quine-Putnam indispensability argument grounded in the (...) Nobel-winning applications of the Rubin model in health and social sciences. To advance the dialectic, I challenge this argument with an updated Rubin causal model that retains its successes while dispensing with CEM. This novel approach combines the strengths of the Rubin causal model and a causal model familiar in philosophy, the causal Bayes net. The takeaway: deductive logic and inductive inference, often studied in isolation, are deeply interconnected. (shrink)

Many extant theories of placebo focus on their causal structure wherein placebo effects are those that originate from select features of the therapy (e.g., client expectations or “incidental” features like size and shape). Although such accounts can distinguish placebos from standard medical treatments, they cannot distinguish placebos from everyday occurrences, for example, when positive feedback improves our performance on a task. Providing a social-epistemological account of a treatment context can rule out such occurrences, and furthermore reveal a new way (...) to distinguish clinical placebos from standard medical treatments. (shrink)

Epistemological approaches to mental causation argue that the notorious problem of mental causation as captured in the question “How can irreducible, physically realized, and potentially relational mental properties be causally efficacious in the production of physical effects?” has a very simple solution: One merely has to abandon any metaphysical considerations in favor of epistemological considerations and accept that our explanatory practice is a much better guide to causal relevance than the metaphysical reasoning carried out from the philosophical armchair. I (...) argue that epistemological approaches to mental causation do not enjoy any genuine advantage over theories which treat the problem of mental causation as a genuinely metaphysical problem. (shrink)

This chapter argues that materialism is vulnerable to two kinds of epistemological objections: transcendental arguments, that show that materialism is incompatible with the very possibility of knowledge; and defeater arguments, that show that belief in materialism provides an effective defeaters to claims to knowledge. It constructs objections of these two kinds in three areas of epistemology: our knowledge of the laws of nature (and of scientific essences), our knowledge of the ontology of material objects, mathematical and logical knowledge. The (...) chapter argues that these epistemological weaknesses place the materialist in a dialectically weak position in respect of ontological identity claims, since the materialist cannot know the causal powers or persistence conditions of material objects. It also argues that the materialist can provide no non-circular account of epistemic normativity. Anti-realist accounts of normativity are unavailable because normativity is already implicated in all intentionality. Moreover, materialists face a fatal dilemma in attempting to carry out an etiological reduction of teleological norms, since neither Humean nor anti-Humean accounts of causation yield defensible results. (shrink)

ABSTRACT I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments. INTRODUCTION In contrast to the classic model of randomized-control trials, often with a large number of (...) subjects enrolled, precision medicine attempts to optimize therapeutic outcomes by focusing on the individual.[i] A recent publication highlights the strengths and weakness of both traditional evidence-based medicine and precision medicine.[ii] Plus, it outlines a tension in the shift from evidence-based medicine’s inductive reasoning style (the collection of data to postulate general theories) to precision medicine’s abductive reasoning style (the generation of an idea from the limited data available).[iii] The paper’s main example is the application of precision medicine for the treatment of cancer.[iv] I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. As the name suggests, brain-computer interfaces are a significant advancement in neurotechnology that directly connects someone’s brain to external or implanted devices.[v] Among the various kinds of brain-computer interfaces, adaptive deep brain stimulation devices require numerous personalized adjustments to their settings during the implantation and computation stages in order to provide adequate relief to patients with treatment-resistant disorders. What makes these devices unique is how adaptive deep brain stimulation integrates a sensory component to initiate the stimulation. While not commonly at the level of sophistication as self-supervising or generative large language models,[vi] they currently allow for a semi-autonomous form of neuromodulation. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments.[vii] ANALYSIS I. The State of Precision Medicine in Oncology and the Epistemological Shift While a thorough overview of precision medicine for the treatment of cancer is beyond the scope of this article, its practice can be roughly summarized as identifying clinically significant characteristics a patient possesses (e.g., genetic traits) to land on a specialized treatment option that, theoretically, should benefit the patient the most.[viii] However, in such a practice of stratification patients fall into smaller and smaller populations and the quality of evidence that can be applied to anyone outside these decreases in turn.[ix] As inductive logic helps to articulate, the greater the number of patients that respond to a particular therapy the higher the probability of its efficacy. By straying from this logical framework, precision medicine opens the treatment of cancer to more uncertainty about the validity of these approaches to the resulting disease subcategories.[x] Thus, while contemporary medical practices explicitly describe some treatments as “personalized”, they ought not be viewed as inherently better founded than other therapies.[xi] A relevant contemporary case of precision medicine out of Norway focuses on the care of a patient with cancer between the ventricles of the heart and esophagus, which had failed to respond to the standard regimen of therapies over four years.[xii] In a last-ditch effort, the patient elected to pay out-of-pocket for an experimental immunotherapy (nivolumab) at a private hospital. He experienced marked improvements and a reduction in the size of the tumor. Understandably, the patient tried to pursue further rounds of nivolumab at a public hospital. However, the hospital initially declined to pay for it given the “lack of evidence from randomised clinical trials for this drug relating to this [patient’s] condition.”[xiii] In rebuttal to this claim, the patient countered that he was actually similar to a subpopulation of patients who responded in “open‐label, single arm, phase 2 studies on another immune therapy drug” (pembrolizumab).[xiv] Given this interpretation of the prior studies and the patient’s response, further rounds of nivolumab were approved. Had the patient not had improvements in the tumor’s size following a round of nivolumab, then pembrolizumab’s prior empirical evidence in isolation would have been insufficient, inductively speaking, to justify his continued use of nivolumab.[xv] The case demonstrates a shift in reasoning from the traditional induction to abduction. The phenomenon of ‘cancer improvement’ is considered causally linked to nivolumab and its underlying physiological mechanisms.[xvi] However, “the weakness of abductions is that there may always be some other better, unknown explanation for an effect. The patient may for example belong to a special subgroup that spontaneously improves, or the change may be a placebo effect. This does not mean, however, that abductive inferences cannot be strong or reasonable, in the sense that they can make a conclusion probable.”[xvii] To demonstrate the limitations of relying on the abductive standard in isolation, commentators have pointed out that side effects in precision medicine are hard to rule out as being related to the initial intervention itself unless trends from a group of patients are taken into consideration.[xviii] As artificial intelligence (AI) assists the development of precision medicine for oncology, this uncertainty ought to be taken into consideration. The implementation of AI has been crucial to the development of precision medicine by providing a way to combine large patient datasets or a single patient with a large number of unique variables with machine learning to recommend matches based on statistics and probability of success upon which practitioners can base medical recommendations.[xix] The AI is usually not establishing a causal relationship[xx] – it is predicting. So, as AI bleeds into medical devices, like brain-computer interfaces, the same cautions about using abductive reasoning alone should be carried over. II. Responsive Neurostimulation, AI, and Personalized Medicine Like precision medicine in cancer treatment, computer-brain interface technology similarly focuses on the individual patient through personalized settings. In order to properly expose the intersection of AI, precision medicine, abductive reasoning, and implantable neurotechnologies, the descriptions of adaptive deep brain stimulation systems need to deepen.[xxi] As a broad summary of adaptive deep brain stimulation, to provide a patient with the therapeutic stimulation, a neural signal, typically referred to as a local field potential,[xxii] must first be detected and then interpreted by the device. The main adaptive deep brain stimulation device with premarket approval, the NeuroPace Responsive Neurostimulation system, is used to treat epilepsy by detecting and storing “programmer-defined phenomena.”[xxiii] Providers can optimize the detection settings of the device to align with the patient’s unique electrographic seizures as well as personalize the reacting stimulation’s parameters.[xxiv] The provider adjusts the technology based on trial and error. One day machine learning algorithms will be able to regularly aid this process in myriad ways, such as by identifying the specific stimulation settings a patient may respond to ahead of time based on their electrophysiological signatures.[xxv] Either way, with AI or programmers, adaptive neurostimulation technologies are individualized and therefore operate in line with precision medicine rather than standard treatments based on large clinical trials. Contemporary neurostimulation devices are not usually sophisticated enough to be prominent in AI discussions where the topics of neural networks, deep learning, generative models, and self-attention dominate the conversation. However, implantable high-density electrocorticography arrays (a much more sensitive version than adaptive deep brain stimulation systems use) have been used in combination with neural networks to help patients with neurologic deficits from a prior stroke “speak” through a virtual avatar.[xxvi] In some experimental situations, algorithms are optimizing stimulation parameters with increasing levels of independence.[xxvii] An example of neurostimulation that is analogous to the use of nivolumab in Norway surrounds a patient in the United States who was experiencing both treatment-resistant OCD and temporal lobe epilepsy.[xxviii]Given the refractory nature of her epilepsy, implantation of an adaptive deep brain stimulation system was indicated. As a form of experimental therapy, her treatment-resistant OCD was also indicated for the off-label use of an adaptive deep brain stimulation set-up. Another deep brain stimulation lead, other than the one implanted for epilepsy, was placed in the patient’s right nucleus accumbens and ventral pallidum region given the correlation these nuclei had with OCD symptoms in prior research. Following this, the patient underwent “1) ambulatory, patient-initiated magnet-swipe storage of data during moments of obsessive thoughts; (2) lab-based, naturalistic provocation of OCD-related distress (naturalistic provocation task); and (3) lab-based, VR [virtual reality] provocation of OCD-related distress (VR provocation task).”[xxix] Such signals were used to identify when to deliver the therapeutic stimulation in order to counter the OCD symptoms. Thankfully, following the procedure and calibration the patient exhibited marked improvements in their OCD symptoms and recently shared her results publicly.[xxx] In both cases, there is a similar level of abductive justification for the efficacy of the delivered therapy. In the case study in which the patient was treated with adaptive deep brain stimulation, they at least had their neural activity tested in various settings to determine the optimum parameters for treatment to avoid them being based on guesswork. Additionally, the adaptive deep brain stimulation lead was already placed before the calibration trials were conducted, meaning that the patient had already taken on the bulk of the procedural risk before the efficacy could be determined. Such an efficacy test could have been replicated in the first patient’s cancer treatment, had it been biopsied and tested against the remaining immunotherapies in vitro. Yet, in the case of cancer with few options, one previous dose of a drug that appeared to work on the patient may justify further doses. However, as the Norwegian case presents, corroboration with known responses to a similar drug (from a clinical trial) could be helpful to validate the treatment strategy. (It should be noted that both patients were resigned to these last resort options regardless of the efficacy of treatment.) There are some elements of inductive logic seen with adaptive deep brain stimulation research in general. For example, abductively the focus could be that patient X’s stimulation parameters are different from patient Y’s and patient Z’s. In contrast, when grouped as subjects who obtained personalized stimulation, patients X, Y, and Z demonstrate an inductive aspect to this approach’s safety and/or efficacy. The OCD case holds plenty of abductive characteristics in line with precision medicine’s approach to treating cancer and as more individuals try the method, there will be additional data. With the gradual integration of AI into brain-computer interfaces in the name of efficacy, this reliance on abduction will continue, if not grow, over time. Moving forward, if a responsive deep brain stimulation treatment is novel and individualized (like the dose of nivolumab) and there is some other suggestion of efficacy (like clinical similarities to other patients in the literature), then it may justify insurance coverage for the investigative intervention, absent other unrelated reasons to deny it. III. Ethical Implications and Next Steps While AI’s use in oncology and neurology is not yet as prominent as its use in other fields (e.g., radiology), it appears to be on the horizon for both.[xxxi] AI can be found in both the functioning of the neurotechnologies as well as the implementation of precision medicine. The increasing use of AI may serve to further individualize both oncologic and neurological therapies. Given these implications and the handful of publications cited in this article, it is important to have a nuanced evaluation of how these treatments, which heavily rely on abductive justification, ought to be managed. The just use an abductive approach may be difficult as AI infused precision medicine is further pursued. At baseline, such technology relies on a level of advanced technology literacy among the general public and could exclude populations who lack access to basic technological infrastructure or know-how from participation.[xxxii] Even among nations with adequate infrastructure, as more patients seek out implantable neurotechnologies, which require robust healthcare resources, the market will favor patient populations that can afford this complex care.[xxxiii] If patients already have the means to pay for an initial dose/use of a precision medicine product out of pocket, should insurance providers be required to cover subsequent treatments?[xxxiv] That is, if a first dose of a cancer drug or a deep brain stimulator over its initial battery life is successful, patients may feel justified in having the costs of further treatments covered. The Norwegian patient’s experience implies there is a precedent for the idea that some public insurance companies ought to cover successful cancer therapies, however, insurance companies may not all see themselves as obligated to cover neurotechnologies that rely on personalized settings or that are based on precision/abductive research more than on clinical trials. CONCLUSION The fact that the cases outlined above rely on abductive style of reasoning implies that there may not be as strong a justification for coverage by insurance, as they are both experimental and individualized, when compared to the more traditional large clinical trials in which groups have the same or a standardized protocol (settings/doses). If a study is examining the efficacy of a treatment with a large cohort of patients or with different experimental groups/phases, insurance companies may conclude that the resulting symptom improvements are more likely to be coming from the devices themselves. A preference for inductive justification may take priority when ruling in favor of funding someone’s continued use of an implantable neurostimulator. There are further nuances to this discussion surrounding the classifications of these interventions as research versus clinical care that warrant future exploration, since such a distinction is more of a scale[xxxv] than binary and could have significant impacts on the “right-to-try” approach to experimental therapies in the United States.[xxxvi] Namely, given the inherent limitations of conducting large cohort trials for deep brain stimulation interventions on patients with neuropsychiatric disorders, surgically innovative frameworks that blend abductive and inductive methodologies, like with sham stimulation phases, have traditionally been used.[xxxvii] Similarly, for adaptive brain-computer interface systems, if there are no large clinical trials and instead only publications that demonstrate that something similar worked for someone else, then, in addition to the evidence that the first treatment/dose worked for the patient in question, the balance of reasoning would be valid and arguably justify insurance coverage. As precision approaches to neurotechnology become more common, frameworks for evaluating efficacy will be crucial both for insurance coverage and for clinical decision making. ACKNOWLEDGEMENT This article was originally written as an assignment for Dr. Francis Shen’s “Bioethics & AI” course at Harvard’s Center for Bioethics. I would like to thank Dr. Shen for his comments as well as my colleagues in the Lázaro-Muñoz Lab for their feedback. - [i] Jonathan Kimmelman and Ian Tannock, “The Paradox of Precision Medicine,” Nature Reviews. Clinical Oncology 15, no. 6 (June 2018): 341–42, https://doi.org/10.1038/s41571-018-0016-0. [ii] Henrik Vogt and Bjørn Hofmann, “How Precision Medicine Changes Medical Epistemology: A Formative Case from Norway,” Journal of Evaluation in Clinical Practice 28, no. 6 (December 2022): 1205–12, https://doi.org/10.1111/jep.13649. [iii] David Barrett and Ahtisham Younas, “Induction, Deduction and Abduction,” Evidence-Based Nursing 27, no. 1 (January 1, 2024): 6–7, https://doi.org/10.1136/ebnurs-2023-103873. [iv] Vogt and Hofmann, “How Precision Medicine Changes Medical Epistemology,” 1208. [v] Wireko Andrew Awuah et al., “Bridging Minds and Machines: The Recent Advances of Brain-Computer Interfaces in Neurological and Neurosurgical Applications,” World Neurosurgery, May 22, 2024, S1878-8750(24)00867-2, https://doi.org/10.1016/j.wneu.2024.05.104. [vi] Mark Riedl, “A Very Gentle Introduction to Large Language Models without the Hype,” Medium (blog), May 25, 2023, https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5 f67941fa59e. [vii] David E. Burdette and Barbara E. Swartz, “Chapter 4 - Responsive Neurostimulation,” in Neurostimulation for Epilepsy, ed. Vikram R. Rao (Academic Press, 2023), 97–132, https://doi.org/10.1016/B978-0-323-91702-5.00002-5. [viii] Kimmelman and Tannock, 2018. [ix] Kimmelman and Tannock, 2018. [x] Simon Lohse, “Mapping Uncertainty in Precision Medicine: A Systematic Scoping Review,” Journal of Evaluation in Clinical Practice 29, no. 3 (April 2023): 554–64, https://doi.org/10.1111/jep.13789. [xi] Kimmelman and Tannock, “The Paradox of Precision Medicine.” [xii] Vogt and Hofmann, 1206. [xiii] Vogt and Hofmann, 1206. [xiv] Vogt and Hofmann, 1206. [xv] Vogt and Hofmann, 1207. [xvi] Vogt and Hofmann, 1207. [xvii] Vogt and Hofmann, 1207. [xviii] Vogt and Hofmann, 1210. [xix] Mehar Sahu et al., “Chapter Three - Artificial Intelligence and Machine Learning in Precision Medicine: A Paradigm Shift in Big Data Analysis,” in Progress in Molecular Biology and Translational Science, ed. David B. Teplow, vol. 190, 1 vols., Precision Medicine (Academic Press, 2022), 57–100, https://doi.org/10.1016/bs.pmbts.2022.03.002. [xx] Stefan Feuerriegel et al., “Causal Machine Learning for Predicting Treatment Outcomes,” Nature Medicine 30, no. 4 (April 2024): 958–68, https://doi.org/10.1038/s41591-024-02902-1. [xxi] Sunderland Baker et al., “Ethical Considerations in Closed Loop Deep Brain Stimulation,” Deep Brain Stimulation 3 (October 1, 2023): 8–15, https://doi.org/10.1016/j.jdbs.2023.11.001. [xxii] David Haslacher et al., “AI for Brain-Computer Interfaces,” 2024, 7, https://doi.org/10.1016/bs.dnb.2024.02.003. [xxiii] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 103–4; “Premarket Approval (PMA),” https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P100026. [xxiv] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 104. [xxv] Burdette and Swartz, 126. [xxvi] Sean L. Metzger et al., “A High-Performance Neuroprosthesis for Speech Decoding and Avatar Control,” Nature 620, no. 7976 (August 2023): 1037–46, https://doi.org/10.1038/s41586-023-06443-4. [xxvii] Hao Fang and Yuxiao Yang, “Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder Using a Brain-Computer Interface System: A Simulation Study,” Frontiers in Computational Neuroscience 17 (March 6, 2023), https://doi.org/10.3389/fncom.2023.1119685; Mahsa Malekmohammadi et al., “Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson’s Disease,” Movement Disorders 31, no. 3 (2016): 426–28, https://doi.org/10.1002/mds.26482. [xxviii] Young-Hoon Nho et al., “Responsive Deep Brain Stimulation Guided by Ventral Striatal Electrophysiology of Obsession Durably Ameliorates Compulsion,” Neuron 0, no. 0 (October 20, 2023), https://doi.org/10.1016/j.neuron.2023.09.034. [xxix] Nho et al. [xxx] Nho et al.; Erik Robinson, “Brain Implant at OHSU Successfully Controls Both Seizures and OCD,” OHSU News, accessed March 3, 2024, https://news.ohsu.edu/2023/10/25/brain-implant-at-ohsu-successfully-controls-both-seizures-and-ocd. [xxxi] Awuah et al., “Bridging Minds and Machines”; Haslacher et al., “AI for Brain-Computer Interfaces.” [xxxii] Awuah et al., “Bridging Minds and Machines.” [xxxiii] Sara Green, Barbara Prainsack, and Maya Sabatello, “The Roots of (in)Equity in Precision Medicine: Gaps in the Discourse,” Personalized Medicine 21, no. 1 (January 2024): 5–9, https://doi.org/10.2217/pme-2023-0097. [xxxiv] Green, Prainsack, and Sabatello, 7. [xxxv] Robyn Bluhm and Kirstin Borgerson, “An Epistemic Argument for Research-Practice Integration in Medicine,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 43, no. 4 (July 9, 2018): 469–84, https://doi.org/10.1093/jmp/jhy009. [xxxvi] Vijay Mahant, “‘Right-to-Try’ Experimental Drugs: An Overview,” Journal of Translational Medicine 18 (June 23, 2020): 253, https://doi.org/10.1186/s12967-020-02427-4. [xxxvii] Michael S. Okun et al., “Deep Brain Stimulation in the Internal Capsule and Nucleus Accumbens Region: Responses Observed during Active and Sham Programming,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 3 (March 1, 2007): 310–14, https://doi.org/10.1136/jnnp.2006.095315. (shrink)

With his book The Nature of Mathematical Knowledge (1983), Ph. Kitcher, that had been doing extensive research in the history of the subject and in the contemporary debates on epistemology, saw clearly the need for a change in philosophy of mathematics. His goal was to replace the dominant, apriorist philosophy of mathematics with an empiricist philosophy. The current philosophies of mathematics all appeared, according to his analysis, not to fit well with how mathematicians actually do mathematics. A shift in (...) orientation should invoke the more general reflection that causal, genetic factors are as significant for epistemology as logical structure. As I am to a large extent sympathetic with Kitcher's proposal, my aims here will be simple: first I start presenting Kitcher's argument, and then I try to raise some doubts about his contribution. These doubts come probably from my unskilfulness to follow the torrential flow of Kitcher's ideas. (shrink)

The aim of the present paper is to offer a critical examination of the episte- mological foundations of rational emotive behavior therapy (REBT). Taking the tension between the basic presupposition between REBT and the ABC cognitive model constituting its core as its cue, the paper focuses on the causal relation between cognition and emotion and tries to argue that, at closer inspection, neither the theoretical, nor the experimental reasons ad- duced in favor of the idea of a determining role (...) of cognition in the appear- ance of mental disturbance actually hold. (shrink)

Intuitions are widely assumed to play an important evidential role in ethical inquiry. In this paper I critically discuss a recently influential claim that the epistemological credentials of ethical intuitions are undermined by their causal pedigree and functional role. I argue that this claim is exaggerated. In the course of doing so I argue that the challenge to ethical intuitions embodied in this claim should be understood not only as a narrowly epistemological challenge, but also as a substantially ethical (...) one. I argue that this fact illuminates the epistemology of ethical intuitions. (shrink)

Any experimental field consists of preparing special conditions for examining interesting objects for research. So naturally, the particular ways in which scientists prepare their objects determine the kind and the content of knowledge produced. This book provides a framework for the analysis of experimental practices - the Social Epistemology of Experiment - that incorporates both the ‘material’ and the ‘social’ dimensions of knowledge production. The Social Epistemology of Experiment is applied to experimental economics and in so doing, it (...) introduces the epistemic role of the participation of human subjects in experiments and the causal efficacy of institutions in constraining and enabling human behaviour. It also develops the role of the social and socially established practices in overcoming the methodological difficulties associated with experimenting with humans subjects in the social sciences as well as the effect of scientists’ interventions in the laboratory worlds. This book provides an historical and contextualized account of the emergence of experimental economics, the methodological discussions that have informed and constituted it, its main research programmes, and stylized facts. The analysis of its three main research programmes – market experiments, game theory experiments and individual decision-making experiments – shows how economics experiments are particularly tailored to produce knowledge about market institutions and individual behaviour in contexts where there might be conflicts of individual and social goals, and also about the processes of individual decision-making. (shrink)

Frederick F. Schmitt offers a new account of Hume's epistemology in A Treatise of Human Nature, which alternately manifests scepticism, empiricism, and naturalism. Critics have emphasised one of these positions over the others, but Schmitt argues that they can be reconciled by tracing them to an underlying epistemology of knowledge and probability.

Epistemologists have begun paying attention to the phenomenon of _core cognition_ from developmental psychology. Core cognition posits innate automatic cognitive modules that enable children to quickly grasp and learn certain concepts. A key element of core cognition is sometimes named _core knowledge_ because it encodes the constraints, parameters, and concepts that are required for core cognition modules to function. Until now, no successful epistemological account of it has been presented, and it is difficult to integrate into standard accounts of (...) class='Hi'>epistemology given that it is only implicitly believed, not accessible to explicit cognitive processing, and innate. In this paper I propose an account of the epistemology of core cognition, focussing on the epistemic status of this core knowledge. I argue that, rather than being knowledge, or some ordinary justified belief, it consists of Wittgensteinian _hinge certainties_. These are the implicit presupposition that we need for our epistemology to function. I illustrate the argument with the core cognition of causality. Finally, I propose that even though core knowledge consists of unjustified hinges, we are epistemically entitled to trust them to be accurate. (shrink)

Epistemological realism was postulated as a prolegomenon to clinical research. Observation of single cases must precede any effort for generalization. Observation of men by men is always a field process. In clinical research the experimenter exercises a great amount of power over the subject, thus a naive empirical approach and operationism may be misleading. Clinical theory must be coated in a language different from empirical data and enable the formation of causal chains of events.

Experimental studies show that some corvids, apes, and rodents possess a common long-term memory system that allows them to take goal-directed actions on the basis of absent spatiotemporal contexts. In other words, evidence supports the hypothesis that Episodic Memory —far from being uniquely human— has evolved as a cross-species meaning making system. However, within this zoosemiotic breakthrough, neurocognitive studies now struggle characterizing the relations between teleological factors and phenomenological factors that would account for the episodic behavior displayed by these living (...) beings. Within such field, this paper identifies four epistemological gaps —the ‘Nagelian’, ‘de Waalian’, ‘Chomskyan’, and ‘semiotic’ gaps—, making a case for the need of a future biosemiotic model of Alloanimal Episodic Memory to come into the equation. As a whole, I conclude that experimental developments in AEM research, and philosophical advancements in biosemiotics could converge through the concept of semiosis. Introducing the latter would account for animal episodic agency as a causal influence and continuity between the above relations, outclassing the reductionist and Cartesian separation between ‘external’ bodily behavior and ‘internal’ computational operations. (shrink)

Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper (...) is to demonstrate that one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. If by causal reasoning is meant the entirety of the process through which we discover causal relationships and make use of this knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals, then one relies besides on tacit knowledge, as might be constituted by or derived from the epistemic faculty virtues and abilities of the causal reasoner, the value systems and character traits of the causal reasoner, the implicit knowledge base available to the causal reasoner, and the habits that sustain our causal reasoning practices. While certain aspects of causal reasoning may be axiomatized and formalized and algorithms may be implemented to approximate causal reasoning, one has to remain skeptical about whether causal reasoning may be fully automated. This demonstration will involve an engagement with Meno’s Paradox. (shrink)

Discussions of technoscience are bringing to light that scientific journals feature very different knowledge claims. At one end of the spectrum, there is the scientific claim that a hypothesis needs to be reevaluated in light of new evidence. At the other end of the spectrum, there is the technoscientific claim that some new measure of control has been achieved in a laboratory. The latter claim has not received sufficient attention as of yet. In what sense is the achievement of control (...) genuine knowledge in its own right; how is this knowledge acquired; and publicly validated? Notions of tacit or embodied knowledge, of knowledge by acquaintance, of engineering or thing knowledge, and reconstructions of ability or skill take us only part of the way towards answering such questions. The epistemology of technoscience needs to account for the acquisition and demonstration of a public knowledge of control that does not consist in the holding of propositions, even though it is usually communicated in writing: Technoscientific knowledge is, firstly, objective and public insofar as it is exhibited and documented. Secondly, it presupposes a specific context of technology and expertise. Thirdly, it is communicable, even where the achieved capability itself is not. Knowledge of control entails, fourthly, a knowledge of causal relationships, and it sediments itself, fifthly, as a habit of action in the sense proposed by Charles Sanders Peirce. (shrink)

Disasters in sociotechnical systems are caused by many factors. For example, the tragic chemical disaster in Bhopal, India, was caused by a leaky valve and a maintenance error. Safety scientists and investigators call these proximate factors. But the tragedy was also caused by what experts call systemic factors, which include the facility’s design, the organization of its workforce, and the safety culture of the plant and surrounding community. Other disasters share a similarly complex causality, depending on a multitude of proximate (...) and systemic factors. Investigators and scientists distinguish between these different types of factors because they think each has distinctive causal features and also because they often think some factors are more significant causes of disasters than others. In this dissertation, I analyze these distinctions and the reasoning experts use when selecting important causes of disasters in cases like the Bhopal gas tragedy and the Challenger shuttle loss. Using James Woodward’s interventionist theory of causation, I explicate three causal concepts that can be used to distinguish among causal factors: amplifying/damping, causal inertia, and causal delay. I employ these concepts to elaborate and clarify the causal features safety scientists identify to draw distinctions among different types of causal factors, and their reasons for thinking some causes are more important than others for understanding disasters. My dissertation takes a pragmatic approach to causal selection. Although philosophers have emphasized John Stuart Mill’s remark that selecting individual causal factors is “capricious,” I base my approach on Mill’s deeper thinking about the logic of causal selection and the philosophical challenge it poses. I show that selections of causal factors in investigations of disasters and the surrounding discussions of safety are motivated primarily by the dual aim of preventing future disasters and making systems safer. Considering these purposes is essential to understand why investigators single out causes with certain features. Analyzing causal selection in terms of why certain types of causes with certain kinds of features are more useful than others for particular purposes clarifies vital reasoning about the important causes of disasters and enriches our understanding of causal knowledge. (shrink)

Complex environmental problems require well-researched policies that integrate knowledge from both the natural and social sciences. Epistemic differences can impede interdisciplinary collaboration, as shown by debates between conservation biologists and anthropologists who are working to preserve biological diversity and support economic development in central Africa. Disciplinary differences with regard to 1) facts, 2) rigor, 3) causal explanation, and 4) research goals reinforce each other, such that early decisions about how to define concepts or which methods to adopt may tilt (...) research design and data interpretation toward one discipline’s epistemological framework. If one of the contributing fields imposes a solution to an epistemic problem, this sets the stage for what I call disciplinary capture. Avoiding disciplinary capture requires clear communication between collaborators, but beyond this it also requires that collaborators craft research questions and innovate research designs which are different from the inherited epistemological frameworks of contributing disciplines. (shrink)

According to Hartry Field, the mathematical Platonist is hostage of a dilemma. Faced with the request of explaining the mathematicians’ reliability, one option could be to maintain that the mathematicians are reliably responsive to a realm populated with mathematical entities; alternatively, one might try to contend that the mathematical realm conceptually depends on, and for this reason is reliably reflected by, the mathematicians’ (best) opinions; however, both alternatives are actually unavailable to the Platonist: the first one because it is in (...) tension with the idea that mathematical entities are causally ineffective, the second one because it is in tension with the suggestion that mathematical entities are mind-independent. John Divers and Alexander Miller have tried to reject the conclusion of this argument—according to which Platonism is inconsistent with a satisfactory epistemology for arithmetic—by redescribing the second horn of the dilemma in light of Crispin Wright’s notion of judgment-dependent truth; in particular they have contended that once arithmetical truth is conceived in this way the Platonist can have a substantial epistemology which does not conflict with the idea that the mathematical entities exist mind-independently. In this paper I analyze Wright’s notion of judgment-dependent truth, and reject Divers and Miller’s argument for the conclusion that arithmetical truth can be so characterized. In the final part, I address the worry that my argument generalizes very quickly to the conclusion that no area of discourse could be characterized as judgment-dependent. As against this conclusion, I indicate under what conditions—notably not satisfied in Divers and Miller’s case, but possibly satisfied in others—a discourse’s judgment-dependency can be successfully vindicated. (shrink)

How should we understand the relationship between the contents of our color, causal, modal, and evaluative beliefs, on the one hand, and color, causal, modal, and evaluative properties, on the other? According to Barry Stroud (2011), because of the nature of the contents of those types of beliefs, we should also think that what he calls a “negative metaphysical verdict” on the latter is not one that we could consistently maintain. The metaphysical project aims to arrive at an (...) improved conception of ourselves and our relation the world, no matter if that conception is positive or negative. But if Stroud is right that we cannot consistently arrive at the view that all of our causal, modal, and evaluative beliefs are systematically false, we will see that we cannot consistently reach the negative verdict. But failure to reach the negative verdict doesn’t mean that we have reached the positive verdict. Stroud calls this philosophical failure “metaphysical dissatisfaction”. In this paper, I argue that we can appropriate a metaepistemological response to the problem of the external world which shares its core features with Stroud’s (2000, 2011) arguments, but which nevertheless leaves us with a distinctive kind of epistemological dissatisfaction. (shrink)

Biomedical research and study design have recently been examined in detail by philosophers of science, who, like biomedical researchers, are concerned with the ability to accurately represent causal relationships through scientific study and apply these relationships to improve the health of individuals and populations. Epistemology—defined by the OED as "the theory of knowledge, especially with regard to its methods, validity, and scope, and the distinction between justified belief and opinion"—is fundamental to these concerns. In particular, philosophers of science (...) and biomedical researchers have discussed the epistemological value of randomized-controlled trials in regards to their individual components.... (shrink)

This paper concerns an epistemological objection against mathematical platonism, due to Hartry Field.The argument poses an explanatory challenge – the challenge to explain the reliability of our mathematical beliefs – which the platonist, it’s argued, cannot meet. Is the objection compelling? Philosophers disagree, but they also disagree on (and are sometimes very unclear about) how the objection should be understood. Here I distinguish some options, and highlight some gaps that need to be filled in on the potentially most compelling version (...) of the argument. (shrink)

Evolutionary epistemology has experienced a continuous rise over the last decades. Important new theoretical considerations and novel empirical findings have been integrated into the existing framework. In this paper, I would like to suggest three lines of research that I believe will significantly contribute to further advance EE: ontogenetic considerations, key ideas from cognitive biology, and the framework of the Extended Evolutionary Synthesis. EE, in particular the program of the evolution of epistemological mechanisms, seeks to provide a phylogenetic account (...) of the generation of cognitive processes underlying knowledge creation. Traditionally, EE and EEM have been oriented towards an account of evolutionary theory that mainly drew from the tenets of the Modern Synthesis. The Modern Synthesis largely dismisses ontogenetic processes and considers them irrelevant for evolutionary explanations. If anything, the role of development in evolution is believed to be that of a constraint. There is, however, ample evidence for a tight intertwinement of developmental and evolutionary processes. Organisms employ their cognitive apparatus to interact with the environment in order to achieve a fully functioning perceptual and cognitive nervous system. Also, ontogeny provides generative potentials to enable variations that natural selection can act upon. EEM’s agenda may, therefore, strongly benefit from bringing together ontogenetic and phylogenetic approaches. To grapple with this challenge, an alternative vision of the evolutionary theory termed Extended Evolutionary Synthesis could be used. This extended evolutionary theory explores relationships between the processes of individual development and phenotypic change during evolution and can provide a more suitable framework for EEM to draw from. In recent years, cognitive biology has gained momentum as an independent research field. Cognitive biology builds on the concepts of EEM and understands knowledge as a biogenic phenomenon. Its main objective is also the formulation of substantiated interrelations between cognition and evolution but it focuses on cognitive functionality at all levels of biological organization. It thus employs a “vertical” approach that encompasses nested hierarchies which span from single molecules, cells, and tissues to the organismal level, communities, and societies. In contrast to cognitive biology, EEM is here understood to adopt a “horizontal” approach that focuses on phylogenetic explanations of cognition and knowledge acquisition. Linking EEM with the key ideas of cognitive biology could make EEM’s research program stronger as it can more easily accommodate phylogenetic and ontogenetic questions within a hierarchical, multilevel perspective. This is of particular importance for a more comprehensive account of cognition since living systems are subject to context-dependent causal influences from different organizational levels. In addition to EEM, there is a second program of EE. This program has been labeled evolutionary epistemology of theories and understands the increase in human knowledge, such as scientific theories, as naturalistic accounts of evolution. Both, EEM and EET initially drew from the core concepts of the Modern Synthesis. Several scholars have severely criticized the analogies made between EET and the Neo-Darwinian key processes of evolution. In particular processes of random mutation, the rate of variation, natural selection as the unique driving force, and the adaptationist agenda are believed to reveal disanalogies. In contrast to the Modern Synthesis, the Extended Evolutionary Synthesis not only recognizes developmental processes but also ecological interactions and systems dynamics as well as social and cultural evolutionary reciprocity as important evolutionary processes. Concepts of the Extended Evolutionary Synthesis are therefore expected to be more fruitful for re-conceptualizing parallels between scientific theorizing and biological evolution. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:FROM EPISTEMOLOGY TO METAPHYSICS WHAT I HOPE to do in what follows is to sketch how one might go about constructing a rational, ritical, and in a sense 'scientific' metaphysics. It goes without saying that a great many current conceptions of ' metaphysics ' are abusive. On one account, ' metaphysics ' is whatever isn't science or common sense, where science and common sense are assumed to be (...) good things. On another, 'metaphysics' consists of an abuse of language which is brought about by a wrenching of it out of its normal context. Again, ' metaphysics ' is supposed to substitute a bloodless dance of categories for the spontaneous outflow of religious feeling, or idolatrous human constructions for the Word of God. However, it seems in general much clearer that metaphysics is to be contemptuously repudiated than exactly what it is. A traditional definition of metaphysics is ' the study of being qua being'. It is perhaps understandable that many should complain, when confronted by such a sententious formula, that such an inquiry is a waste of time, and one had much better get on with the more fruitful business of pursuing one of the particular sciences. (Ezra Pound once remarked that, since the Renaissance, a philosopher had been someone who was too damned lazy to work in a laboratory; and the same may be felt to apply a fortiori to the metaphysician.) And yet there are problems which do not seem to go away, however often it is confidently asserted that they have done so or are about to do so, problems which might be said to be concerned with ' being ' or ' reality ' at a very high level of generality. Those who brush the problems aside may perhaps sometimes be suspected of arbitrarily taking sides on them. For example, the psychological doctrine known as behaviorism is ~05 206 HUGO MEYNELL based on the assumption that all talk about thoughts, feelings, and emotions is in the final analysis reducible to talk about the behavior of organisms. But it is one thing to allow such an assumption to dominate one's work, another to set it clearly, another still to examine and to justify it. If any examination of the account of the relation of mind to matter implied by behaviorism has to be of such generality as to enter the realm of the 'metaphysical ', it would seem to be still worth carrying out, unless indeed we are to accept behaviorism quite uncritically as a dogma. Just the same applies to writing which assumes the existence of non-existence of a Deity. The fact is that every passage of speech or writing which exists, and makes claims as to matters of fact, involves certain assumptions about the ultimate constituents of things, and about the nature and interrelations of appearance, reality, mind, matter, experience, causality, things, properties, events, space, time, God, and so on. Let us call each such set of basic assumptions (including the ones mentioned earlier, that talk about minds is reducible to talk about the behavior of organisms, that there is or is not a God) a 'metaphysic'. Let us say that 'metaphysics ' is an attempt to discuss, and to come to well-founded conclusions on, the question as to whether any such ' metaphysic ' is to be preferred, as more closely approximating to the truth about how things are in the world, to any other. Empiricism, idealism, materialism, critical realism, and naive realism, will at this rate each be a 'metaphysic'; that is to say, each consists of theses about the existence, nature and interrelations of actual or alleged basic constituents of reality like those listed above. Any attempt to discuss the rival merits of any of them, or.to defend any one as more appropriate than the others, will count as ' metaphysics '. The arguments by which Plato, Leibniz, or Hegel established their conclusions about the ultimate nature of things evidently count as ' metaphysics ' according to our conception; and this does seem in conformity with ordinary usage. Perhaps it is obvious that one such 'metaphysic' (say, materialism) is to be preferred to the rest; FROM EPISTEMOLOGY TO METAPHYSICS 207 or at least that another such (say, idealism) should be repudiated ; but it would be as... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Epistemology in Pracīna and Navya NyāyaJonardon GaneriEpistemology in Pracīna and Navya Nyāya. By Sukharanjan Saha. Kolkata: Jadavpur University, 2003. Pp. 166.Epistemology in Pracīna and Navya Nyāya, by Sukharanjan Saha, usefully collates ten previously published essays on Indian epistemology: two longer essays first published in 1986 and a series of more recent shorter pieces. The leading thesis of the book is that the epistemology of (...) the older writers in the tradition of Nyāya-Vaiṣesika is, in important respects, better than the "new epistemology" originating with Gaṅgeśa. Sustained attention is given to the epistemology of the Vaiśeṣika thinker Praśastapāda (ca. A.D. 660), and the first six essays all "seek to show that Praśastapāda's views are more acceptable than those of Gaṅgeśa considered from the point of view of contemporary epistemology" (p. 4). The remaining essays argue in support of a similar conclusion with regard to certain ideas found in the older Nyāya of Gautama and Vātsyāyana. The titles of the essays collected here are: (1) "Epistemology in Pracīna and Navya Nyāya"; (2) "Kindred Points in an Old Epistemology" (1986); (3) "Gaṅgeśa's Reactions to Some Gettier-like Problems" (1986); (4) "The Unestab-lished Reason in Nyāya"; (5) "The Savyabhicāra Hetvābhāsa in Nyāya and Vaiśeṣika Schools"; (6) "The Thesis of Nirvikalpaka in Nyāya and Vaiśeṣika"; (7) "Truth as Avyabhicāritatva"; (8) "A Note on the Definition of Pramā; (9) "Nyāya Theory of Predication"; (10) "The Present and Its Knowledge"; and (11) "Types of Inference in Gautama and Vātsyāyana."Whether or not one finds oneself in agreement with Saha's specific arguments, the general conception of the book seems to me to be laudable. The astonishing [End Page 120] continuity of the Indian philosophical tradition makes it all too easy to survey the history of Indian philosophy and assume that historical development runs in tandem with philosophical progression. It is tempting to think, for example, that Gaṅśa, reviewing the epistemology of the older tradition, and considering the various objections that had been brought against it by external critics like Śrīharṣa and the later Buddhists, produced a new theory that was both an improvement on and a systematization of earlier Nyāya epistemology. To succumb to this temptation would be a mistake, however, for at least two reasons. First, it might be that the discussion of the earlier thinkers was, though less sophisticated, "closer to the ground," so to speak, than that of their successors. The comparative absence of theoretical baggage may have enabled those earlier writers to remain true to the facts, even when they could not easily be explained or systematized. This does indeed seem to be the case with the sūtra texts, and it is also very noticeably the case with Praśastapāda, who exhibited, for instance in his discussion of motion, an openness to the facts rather than closure born of theoretical over-commitment.Second and relatedly, it might be that the earlier thinkers had not yet closed down the range of topics and approaches deemed worthy of philosophical discussion or exploration. Thus, again in the sūtras, we find the beginnings of discussions on an enormous array of issues and hypotheses, not all of which were subsequently picked up or extended in later theory. Saha, for example, argues that Gaṅgeśa committed the later tradition to a rigid causal theory of knowledge, and suggests further that because of this he "failed to appreciate the richness of the philosophical insight of the founders of the system of philosophy to which he owes his allegiance" (p. 69). If this is right, then a return to the earlier strata of the tradition might well lead to an enrichment of our understanding of the range of philosophical possibility. Saha's approach, then, helps to guard the modern student of Indian philosophy from mistakenly thinking that "newer is always better," just as we have learned to be on guard against the older and contrary... (shrink)