Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...) this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

Social epistemologists should be well-equipped to explain and evaluate the growing vulnerabilities associated with filter bubbles, echo chambers, and group polarization in social media. However, almost all social epistemology has been built for social contexts that involve merely a speaker-hearer dyad. Filter bubbles, echo chambers, and group polarization all presuppose much larger and more complex network structures. In this paper, we lay the groundwork for a properly social epistemology that gives the role and structure of networks their due. In particular, (...) we formally define epistemic constructs that quantify the structural epistemic position of each node within an interconnected network. We argue for the epistemic value of a structure that we call the (m,k)-observer. We then present empirical evidence that (m,k)-observers are rare in social media discussions of controversial topics, which suggests that people suffer from serious problems of epistemic vulnerability. We conclude by arguing that social epistemologists and computer scientists should work together to develop minimal interventions that improve the structure of epistemic networks. (shrink)

Henry More est le plus connu des Platoniciens de Cambridge et l’Enchiridion Metaphysicum, son dernier ouvrage, représente l’accomplissement de sa pensée. Il s’agit d’une enquête métaphysique dont le principal objectif est d’établir l’existence d’une substance immatérielle, d’une âme du monde, sorte d’intermédiaire entre Dieu et le monde par laquelle les choses agissent. More nous invite ainsi à découvrir la vraie métaphysique qui consiste en la découverte de la nature véritable de l’étendue des êtres spirituels comme Dieu, les anges et les (...) démons, l’espace, les âmes individuelles des hommes ou des bêtes. Ce manuel de métaphysique prend appui sur le mécanisme cartésien pour mieux le contredire et démontre que l’extension spirituelle est la principale qualité des esprits. Cette doctrine conduira More à re-diviniser l’espace pour l’instituer à l’instar des kabbalistes de l’école de Safed, comme lieu de la possibilité de l’existence du monde. More montre ainsi les limites des mécanismes d’Hobbes et de Descartes tout en essayant de composer avec d’autres savants mécanistes tels que Robert Boyle et Robert Hooke. Quelques années plus tard, à Cambridge, Newton, sur les pas d’Henry More, pensera la nature de son espace physique comme un espace de nature divine, comme un Sensorium Dei. ---------------------------------------------------------------------------------------------------- ------------- Biographie de l'auteur: Françoise Monnoyeur est Docent en philosophie (Associate Professor). Elle enseigne la philosophie et l’histoire des sciences en France, aux États-Unis et en Suède. Elle est chercheur associée au centre Jean Pépin, Paris, France. Ses principaux ouvrages portent sur Descartes, l’infini, la matière, la vie. (shrink)

The development of personal technologies has recently shifted from devices that seek to capture user attention to those that aim to improve user well-being. Digital wellness technologies use the same attractive qualities of other persuasive apps to motivate users towards behaviors that are personally and socially valuable, such as exercise, wealth-management, and meaningful communication. While these aims are certainly an improvement over the market-driven motivations of earlier technologies, they retain their predecessors’ focus on influencing user behavior as a primary metric (...) of success. Digital wellness technologies are still persuasive technologies, and they do not evade concerns over whether their influence on users is ethically justified. In this paper, we describe several ethical frameworks with which to assess the justification of digital wellness technologies’ influence on users. We propose that while some technologies help users to complete tasks and satisfy immediate preferences, other technologies encourage users to reflect on the values underlying their habits and teach them to evaluate their lives’ competing demands. While the former approach to digital wellness technology is not unethical, we propose that the latter approach is more likely to lead to skillful user engagement with technology. (shrink)

Explainable AI (xAI) methods are important for establishing trust in using black-box models. However, recent criticism has mounted against current xAI methods that they disagree, are necessarily false, and can be manipulated, which has started to undermine the deployment of black-box models. Rudin (2019) goes so far as to say that we should stop using black-box models altogether in high-stakes cases because xAI explanations ‘must be wrong’. However, strict fidelity to the truth is historically not a desideratum in science. Idealizations (...) – the intentional distortions introduced to scientific theories and models – are commonplace in the natural sciences and are seen as a successful scientific tool. Thus, it is not falsehood qua falsehood that is the issue. In this paper, I outline the need for xAI research to engage in idealization evaluation. Drawing on the use of idealizations in the natural sciences and philosophy of science, I introduce a novel framework for evaluating whether xAI methods engage in successful idealizations or deceptive explanations (SIDEs). SIDEs evaluates whether the limitations of xAI methods, and the distortions that they introduce, can be part of a successful idealization or are indeed deceptive distortions as critics suggest. I discuss the role that existing research can play in idealization evaluation and where innovation is necessary. Through a qualitative analysis we find that leading feature importance methods and counterfactual explanations are subject to idealization failure and suggest remedies for ameliorating idealization failure. (shrink)

We argue that the trend toward providing users with feasible and actionable explanations of AI decisions—known as recourse explanations—comes with ethical downsides. Specifically, we argue that recourse explanations face several conceptual pitfalls and can lead to problematic explanation hacking, which undermines their ethical status. As an alternative, we advocate that explanations of AI decisions should aim at understanding.

Trust is a core feature of the physician-patient relationship, and risk is central to trust. Patients take risks when they trust their providers to care for them effectively and appropriately. Not all patients take these risks: some medical relationships are marked by mistrust and suspicion. Empirical evidence suggests that some patients and families of color in the United States may be more likely to mistrust their providers and to be suspicious of specific medical practices and institutions. Given both historical and (...) ongoing oppression and injustice in American medical institutions, such mistrust can be apt. Yet it can also frustrate patient care, leading to family and provider distress. In this paper, I propose one way that providers might work to reestablish trust by taking risks in signaling their own trustworthiness. This interpersonal step is not meant to replace efforts to remedy systemic injustice, but is an immediate measure for addressing mistrust in occurrent cases. (shrink)

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models (...) are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Recently, many have argued that there are certain kinds of abstract mathematical explanations that are noncausal. In particular, the irrelevancy approach suggests that abstracting away irrelevant causal details can leave us with a noncausal explanation. In this paper, I argue that the common example of Renormalization Group explanations of universality used to motivate the irrelevancy approach deserves more critical attention. I argue that the reasons given by those who hold up RG as noncausal do not stand up to critical scrutiny. (...) As a result, the irrelevancy approach and the line between casual and noncausal explanation deserves more scrutiny. (shrink)

This paper offers a critique of an account of explanatory integration that claims that explanations of cognitive capacities by functional analyses and mechanistic explanations can be seamlessly integrated. It is shown that achieving such explanatory integration requires that the terms designating cognitive capacities in the two forms of explanation are stable but that experimental practice in the mind-brain sciences currently is not directed at achieving such stability. A positive proposal for changing experimental practice so as to promote such stability is (...) put forward and its implications for explanatory integration are briefly considered. (shrink)

In 2007, ten world-renowned neuroscientists proposed “A Decade of the Mind Initiative.” The contention was that, despite the successes of the Decade of the Brain, “a fundamental understanding of how the brain gives rise to the mind [was] still lacking” (2007, 1321). The primary aims of the decade of the mind were “to build on the progress of the recent Decade of the Brain (1990-99)” by focusing on “four broad but intertwined areas” of research, including: healing and protecting, understanding, enriching, (...) and modeling the mind. These four aims were to be the result of “transdisciplinary and multiagency” research spanning “across disparate fields, such as cognitive science, medicine, neuroscience, psychology, mathematics, engineering, and computer science.” The proposal for a decade of the mind prompted many questions (See Spitzer 2008). In this chapter, I address three of them: (1) How do proponents of this new decade conceive of the mind? (2) Why should a decade be devoted to understanding it? (3) What should this decade look like? (shrink)

Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...) neuroscience with a particular focus on two research areas: cognitive neuroscience and cognitive neurobiology. (shrink)

The past decade has witnessed a growing awareness of conceptual and methodological hurdles within psychology and neuroscience that must be addressed for taxonomic and explanatory progress in understanding psychological functions to be possible. In this paper, I evaluate several recent knowledge-building initiatives aimed at overcoming these obstacles. I argue that while each initiative offers important insights about how to facilitate taxonomic and explanatory progress in psychology and neuroscience, only a “coordinated pluralism” that incorporates positive aspects of each initiative will have (...) the potential for success. (shrink)

In this paper, we explain and showcase the promising methodology of testimonial network analysis and visualization for experimental epistemology, arguing that it can be used to gain insights and answer philosophical questions in social epistemology. Our use case is the epistemic community that discusses vaccine safety primarily in English on Twitter. In two studies, we show, using both statistical analysis and exploratory data visualization, that there is almost no neutral or ambivalent discussion of vaccine safety on Twitter. Roughly half the (...) accounts engaging with this topic are pro-vaccine, while the other half are con-vaccine. We also show that these two camps rarely engage with one another, and that the con-vaccine camp has greater epistemic reach and receptivity than the pro-vaccine camp. In light of these findings, we question whether testimonial networks as they are currently constituted on popular fora such as Twitter are living up to their promise of delivering the wisdom of crowds. We conclude by pointing to directions for further research in digital social epistemology. (shrink)

Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation. I suggest that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds as philosophers of science have traditionally conceived them.

Ethical analyses of the effects of neural interventions commonly focus on changes to personality and behavior, interpreting these changes in terms of authenticity and identity. These phenomena have led to debate among ethicists about the meaning of these terms for ethical analysis of such interventions. While these theoretical approaches have different criteria for ethical significance, they agree that patients’ reports are concerning because a sense of self is valuable. In this paper, I question this assumption. I propose that the Buddhist (...) theory of no‐self offers a novel approach to making ethical sense of patients’ claims following deep brain stimulation. This alternative approach is based on the value of insight into patterns of cause and effect among mental states and actions. (shrink)

The Morris water maze has been put forward in the philosophy of neuroscience as an example of an experimental arrangement that may be used to delineate the cognitive faculty of spatial memory (e.g., Craver and Darden, Theory and method in the neurosciences, University of Pittsburgh Press, Pittsburgh, 2001; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford, 2007). However, in the experimental and review literature on the water maze throughout the history of its use, (...) we encounter numerous responses to the question of “what” phenomenon it circumscribes ranging from cognitive functions (e.g., “spatial learning”, “spatial navigation”), to representational changes (e.g., “cognitive map formation”) to terms that appear to refer exclusively to observable changes in behavior (e.g., “water maze performance”). To date philosophical analyses of the water maze have not been directed at sorting out what phenomenon the device delineates nor the sources of the different answers to the question of what. I undertake both of these tasks in this paper. I begin with an analysis of Morris’s first published research study using the water maze and demonstrate that he emerged from it with an experimental learning paradigm that at best circumscribed a discrete set of observable changes in behavior. However, it delineated neither a discrete set of representational changes nor a discrete cognitive function. I cite this in combination with a reductionist-oriented research agenda in cellular and molecular neurobiology dating back to the 1980s as two sources of the lack of consistency across the history of the experimental and review literature as to what is under study in the water maze. (shrink)

Epistemologists have addressed a variety of modal epistemic standings, such as sensitivity, safety, risk, and epistemic virtue. These concepts mark out the ways that beliefs can fail to track the truth, articulate the conditions needed for knowledge, and indicate ways to become a better epistemic agent. However, it is our contention that current ways of carving up epistemic modality ignore the complexities that emerge when individuals are embedded within a community and listening to a variety of sources, some of whom (...) are intentionally engaged in deception or bullshit. In this context we want our beliefs to be secure. In this paper we translate the epistemic modal standing of safety into a framework appropriate for social epistemology and argue for the importance of epistemic network-security and belief-security to be added to this framework. We discuss the virtues that are salient for promoting network-security and the vices that undermine it. In particular, we highlight monitoring, adjusting, and restructuring virtues and vices. Importantly, each of these vices can be other-regarding or self-regarding. For example, one tempting way of dealing with insecurity within a network is to completely cut oneself off from biased sources. However, we argue that this is a self-regarding restructuring vice because it closes oneself off from opportunities for epistemic growth. By contrast, an other-regarding restructuring vice would be to cut off others from hearing from sources of information that would make their network more secure. (shrink)

It is widely thought that functionalism and the qualia theory are better positioned to accommodate the ‘affective’ aspect of pain phenomenology than representationalism. In this paper, we attempt to overturn this opinion by raising problems for both functionalism and the qualia theory on this score. With regard to functionalism, we argue that it gets the order of explanation wrong: pain experience gives rise to the effects it does because it hurts, and not the other way around. With regard to the (...) qualia theory, we argue that it fails to capture the sense in which pain 's affective phenomenology rationalises various bodily-directed beliefs, desires, and behaviours. Representationalism, in contrast, escapes both of these problems: it gets the order of explanation right and it explains how pain 's affective phenomenology can rationalise bodily-directed beliefs, desires, and behaviours. For this reason, we argue that representationalism has a significant advantage in the debates about pain 's affective phenomenology. We end the paper by examining objections, including the question of what representationalists should say about so-called ‘disassociation cases’, such as pain asymbolia. (shrink)

Crime is a serious social problem, but its causes are not exclusively social. There is growing consensus that explaining and preventing it requires interdisciplinary research efforts. Indeed, the landscape of contemporary criminology includes a variety of theoretical models that incorporate psychological, biological and sociological factors. These multi-disciplinary approaches, however, have yet to radically advance scientific understandings of crime and shed light on how to manage it. In this paper, using conceptual tools on offer in the philosophy of science in combination (...) with theoretical work represented in this special volume of Psychology, Crime and Law, I provide some perspective on why explanatory progress in criminology has remained elusive and evaluate some positive proposals for attaining it. -/- . (shrink)

In book: Infini des mathématiciens, infini des philosophes, Edition: 1992, 1995, 1999, 2002, 2008, 2011 ebook, Chapter: Introduction, Publisher: Belin, Paris, Editors: F. Monnoyeur, pp.9-16.

People have always shared information through chains and networks of testimony. It’s arguably part of what makes us human and enables us to live in cooperative communities with populations greater than the Dunbar number. The invention of the Internet and the rise of social media have turbo-charged our ability to share information. In this chapter, we develop a normative framework for sharing information online. This framework takes into account both ethical and epistemic considerations that are intertwined in typical cases of (...) online testimony. We argue that, while the current state of affairs is not entirely novel, recent technological developments call for a rethinking of the norms of testimony, as well as the articulation of a set of virtuous dispositions that people would do well to cultivate in the capacity as conduits (not just sources or receivers) of information. (shrink)

In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such mechanistic understanding (...) is achieved, cognitive capacities purportedly will be relegated into natural kind categories that correspond to real divisions in the causal structure of the world. I provide reasons here, however, in support of the claim that the neurosciences of cognition currently are not on a trajectory for discovering natural kinds. As I explain, this has to do with how mechanistic explanations of cognitive capacities are developed. Mechanistic explanations and the kinds they explain are abstract representational byproducts of the conceptual, experimental and integrative practices of neuroscientists. If these practices are not coordinated towards developing mechanistic explanations that mirror the causal structure of the world, then natural kinds of cognitive capacities will not be discovered. I provide reasons to think that such coordination is currently lacking in the neurosciences of cognition and indicate where changes in these practices appropriate to the natural kinds ideal would be required if achieving this ideal is indeed the goal. However, I suggest that an evaluation of current practices in these research areas is suggestive that discovering natural kinds of cognitive capacities is not the goal. (shrink)

In their book on Descartes’s Changing Mind, Peter Machamer and J. E. McGuire argue that Descartes discarded dualism to embrace a kind of monism. Descartes famously proposed that there are two separate substances, mind and body, with distinct attributes of thought and extension. According to Machamer and McGuire, because of the limitations of our intellect, we cannot have insight into the nature of either substance. After reviewing their argument in some detail, I will argue that Descartes did not relinquish his (...) favorite doctrine but may have actually fooled himself about the nature of his dualism. It is my contention that the problem with Cartesian dualism stems from the definition of mind and body as substances and the role of their respective attributes—thought and extension—in the definition of substances. (shrink)

Sullivan surveys the philosophical problem-areas surrounding multiculturalism as an ideology of group-identity. While endorsing the claims of underrepresented minorities for recognition, the article sides with traditionalists in prioritizing the autonomy of the self-fashioning individual over ethnic or cultural affiliations. The multicultural challenge to Western logocentrism, its assertion of the implicit power structures embedded in truth claims, and the excesses of postmodern relativism are all subjected to measured criticism. Finally, the essay examines Habermas' role in postwar Germany's embrace of multiculturalism (...) as a national platform of reinvention, and as a means to negate the trauma of the monocultural chauvinism of the Nazi era. However, Sullivan argues, it has taken cosmopolitanism too far. While post-national strategies such as Habermas' Verfassungspatriotismus are well-intentioned, they are ultimately too sterile, universalist and abstract, to satisfy a deep human need for belonging, rooted in a common cultural heritage. -/- All rights reserved. For permission to reprint please contact Rowman & Littlefield. (shrink)

This paper argues that the concept of paternalism is currently overextended to include a variety of actions that, while resembling paternalistic actions, are importantly different. I use the example of Japanese physicians’ non-disclosures of cancer diagnoses directly to patients, arguing that the concept of maternalism better captures these actions. To act paternalistically is to substitute one's own judgement for that of another person and decide in place of that person for his/her best interest. By contrast, to act maternalistically is to (...) decide for another person based on a reasonable understanding of that person's own preferences. The concept of maternalism allows for a more thorough assessment of the moral justification of these types of actions. I conclude that it is possible, at least in principle, to justify Japanese physicians’ non-disclosures, and that this justification must be based on an understanding of these actions as maternalistic. (shrink)

In this volume, leading philosophers of psychiatry examine psychiatric classification systems, including the Diagnostic and Statistical Manual of Mental Disorders, asking whether current systems are sufficient for effective diagnosis, treatment, and research. Doing so, they take up the question of whether mental disorders are natural kinds, grounded in something in the outside world. Psychiatric categories based on natural kinds should group phenomena in such a way that they are subject to the same type of causal explanations and respond similarly to (...) the same type of causal interventions. When these categories do not evince such groupings, there is reason to revise existing classifications. The contributors all question current psychiatric classifications systems and the assumptions on which they are based. They differ, however, as to why and to what extent the categories are inadequate and how to address the problem. Topics discussed include taxometric methods for identifying natural kinds, the error and bias inherent in DSM categories, and the complexities involved in classifying such specific mental disorders as "oppositional defiance disorder" and pathological gambling. -/- Contributors George Graham, Nick Haslam, Allan Horwitz, Harold Kincaid, Dominic Murphy, Jeffrey Poland, Nancy Nyquist Potter, Don Ross, Dan Stein, Jacqueline Sullivan, Serife Tekin, Peter Zachar. (shrink)

One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...) explanation, and (iii) attributions of understanding. At each of these stages, non-epistemic values can, in part, determine how much machine learning model opacity poses a problem. (shrink)

In the quest to discover the neural bases of cognition, rigorous behavioral tools are equally as important as sophisticated tools for neural intervention. This paper evaluates several episodes in the development of a novel behavioral tool for rodent cognitive testing, the rodent touchscreen operant chamber. Using conceptual tools on offer in the philosophical literature on exploratory experimentation and control, I illuminate how optimization of this behavioral tool and an understanding of the causal knowledge it may be used to generate historically (...) has involved dynamic interplay between community-driven exploratory practices operating in parallel with causal hypothesis-driven research. (shrink)

People are increasingly subject to algorithmic decisions, and it is generally agreed that end-users should be provided an explanation or rationale for these decisions. There are different purposes that explanations can have, such as increasing user trust in the system or allowing users to contest the decision. One specific purpose that is gaining more traction is algorithmic recourse. We first pro- pose that recourse should be viewed as a recommendation problem, not an explanation problem. Then, we argue that the capability (...) approach provides plausible and fruitful ethical standards for re- course. We illustrate by considering the case of diversity constraints on algorithmic recourse. Finally, we discuss the significance and implications of adopting the capability approach for algorithmic recourse research. (shrink)

I characterize Nishida Kitarō’s metaethical perspective throughout his work but focus especially on his later papers, most notably his writings on kōiteki chokkan, or active intuition. These include Kōiteki Chokkan no Tachiba (published in 1935), Kōiteki Chokkan (published in 1937), as well as Nothingness and the Religious Worldview (Bashoteki Ronri to Shūkyōteki Sekaikan, published in 1945, and widely available in translation). I explore affinities between Nishida’s approach to ethics and metaethical intuitionism and sensibility theory. I then use this analysis to (...) identify a lesson that Nishida offers to contemporary metaethicists. (shrink)

Ian Hacking instigated a revolution in 20th century philosophy of science by putting experiments (“interventions”) at the top of a philosophical agenda that historically had focused nearly exclusively on representations (“theories”). In this paper, I focus on a set of conceptual tools Hacking (1992) put forward to understand how laboratory sciences become stable and to explain what such stability meant for the prospects of unity of science and kind discovery in experimental science. I first use Hacking’s tools to understand sources (...) of instability and disunity in rodent behavioral neuroscience. I then use them to understand recent grass-roots collaborative open science initiatives aimed at establishing stability in this research area and tease out some implications for unity of science and kind creation and discovery in cognitive neuroscience. -/- . (shrink)

Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation (LTP). I argue that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds.

The creation of guidelines has long been a popular means of conveying normative requirements in scientific and medical research. The recent case of He Jiankui, whose research flouted both widely accepted ethical standards and a set of field-specific guidelines he co-authored, raises the question of whether guidelines are an effective means of preventing misconduct. This paper advances the theory that guidelines can facilitate moral rationalization, a form of motivated reasoning. Moral rationalization in research occurs when individuals justify their actions with (...) plausible reasons that cohere with their moral standards. This allows them to act as they want while believing in their own goodness. If guidelines facilitate moral rationalization, this has implications for research ethics training and for the work of applied ethicists. Research ethics training ought to incorporate reflection on conative features of reasoning, including incentives to commit misconduct, and applied ethicists ought to be circumspect about their use of ethics guidelines. Otherwise, they are feeding the fire of rationalization with the cognitive material practitioners need to accomplish their desired ends. (shrink)

Clinical psychology is characterized by persistent disagreement about fundamental aspects of the discipline ranging from what mental disorders are to what constitutes effective treatment. Attempts to address the problem of epistemic disagreement have been frequently based on establishing the correct answer by fiat without identifying and addressing the sources of the disagreement. We argue that this strategy has not worked very well and the result is frequently ongoing and intractable disagreement, with each side in an argument convinced they are correct. (...) In this paper, we outline an epistemic disagreement procedural model intended to assist researchers and clinicians in the field of clinical psychology to identify, explore, and develop inquiry strategies that capitalize on situations where competing knowledge claims are made. The result is a flexible conceptual framework committed to a defensible epistemic pluralism, fallibilism, and contextualism, across the various research tasks constituting the field of clinical psychology. (shrink)

This article investigates several consequences of a recent trend in philosophy of mind to shift the relata of realization from mental state–physical state to function‐mechanism. It is shown, by applying both frameworks to the neuroscientific case study of memory consolidation, that, although this shift can be used to avoid the immediate antireductionist consequences of the traditional argument from multiple realizability, what is gained is a far more modest form of reductionism than recent philosophical accounts have intimated and neuroscientists themselves have (...) claimed. (shrink)

Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...) problem, where greater inductive risk demands a higher level of transparency regarding the inferences the model makes. (shrink)

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [BOU 99]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in [AMB 07], make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information (for a first outline [CHA 76, SCH 01]). The first section 1 introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two 2 discusses the intermediary but central notion of models. Section three 3, more exploratory, introduces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in chapter 4, make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information. The first section introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two discusses the intermediary but central notion of models. Section three, more exploratory, intro-duces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.

Issues of reliability are claiming center-stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning – as far as they are concerned with reliability.