. Computational chemistry grew in a new era of “desktop modeling,” which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the epistemic opacity transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in order to assess in (...) detail the relationships between modeling methods, parameterization, software and the various forms of their enclosure or disclosure. Our claim is that parameterization issues are an important and often neglected source of epistemic opacity and that this opacity is entangled in methods and software alike. Models and software must be addressed together to understand the epistemological tensions at stake. (shrink)

The paper analyses in some depth the distinction by Paul Humphreys between "epistemic opacity" —which I refer to as "weak epistemic opacity" here— and "essential epistemic opacity", and defends the idea that epistemic opacity in general can be made sense as coming in degrees. The idea of degrees of epistemic opacity is then exploited to show, in the context of computer simulations, the tight relation between the concept of epistemic (...) opacity and actual scientific (modelling and simulation) practices. As a consequence, interesting questions arise in connection with the role of agents dealing with epistemically opaque processes such as computer simulations. (shrink)

This paper looks at the debates between internalism and externalism in mind and epistemology. In each realm, internalists face what we call 'The Connection Problem', while externalists face what we call 'The Problem of Opacity'. We offer an integrated account of thought content and epistemic warrant that overcomes the problems. We then apply the framework to debates between internalists and externalists in metaethics.

We motivate the idea that presupposition is a transparent attitude. We then explain why epistemic opacity is not a serious problem for Robert Stalnaker's theory of content and conversation. We conclude with critical remarks about John Hawthorne and Ofra Magidor's alternative theory.

Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One paradoxical implication of that proposal is that epistemic value may be obtained from mere ignorance. For the less we know, then the more is epistemically possible. This chapter examines a particular class of problematic epistemically possible how-possibly explanations, viz. *epistemically opaque* how-possibly explanations. Those are how-possibly explanations justified by an epistemically opaque process. How could epistemically opaque how-possibly explanations have (...) class='Hi'>epistemic value if they result from a process about which we lack knowledge or understanding? This chapter proposes three different strategies to salvage epistemic value from epistemic opacity, namely salvaging value from 1) functional transparency, 2) modal operator interpretation, and 3) pursuitworthiness. It illustrates using cases from deep neural network modeling. (shrink)

Many jurisdictions prohibit or severely restrict the use of evidence about a defendant’s character to prove legal culpability. Situationists, who argue that conduct is largely determined by situational features rather than by character, can easily defend this prohibition. According to situationism, character evidence is misleading or paltry. -/- Proscriptions on character evidence seem harder to justify, however, on virtue ethical accounts. It appears that excluding character evidence either denies the centrality of character for explaining conduct—the situationist position—or omits probative evidence. (...) Situationism is, after all, presented as antithetical to virtue ethics. -/- This essay provides a virtue ethical defense of character evidence exclusion rules. We show that existing virtue ethical rebuttals to situationism themselves support prohibitions on character evidence; even if behavior arises from stable character traits, character evidence should be prohibited. In building our case, we provide a taxonomy of kinds of character judgment and reconcile the ubiquity and reasonableness of character judgments in ordinary life with the epistemic legitimacy of character evidence prohibitions in law. (shrink)

In this chapter what I call the “backside” of habit is explored. I am interested in the philosophical implications of the physical and physiological processes that mediate, and which allow for what comes to appear as almost magic; namely the various sensorimotor associations and integrations that allows us to replay our past experiences, and to in a certain sense perceive potential futures, and to act and bring about anticipated outcomes – without quite knowing how. Thus, the term “backside” is meant (...) to refer both the actual mediation and the epistemic opacity of these backstage intermediaries that allow for the front stage magic. The question is if the epistemic complexities around sensorimotor mediation gives us valuable insights into the nature of human agency and further how it might begin to show us new ways to think of the mind as truly embodied yet not reducible to any finite body-as-object. (shrink)

Self-knowledge presents a challenge for naturalistic theories of mind. Peter Carruthers’s (2011) approach to this challenge is Rylean: He argues that we know our own propositional attitudes because we (unconsciously) interpret ourselves, just as we have to interpret others in order to know theirs’. An alternative approach, opposed by Carruthers, is to argue that we do have a special access to our own beliefs, but that this is a natural consequence of our reasoning capacity. This is the approach of transparency (...) theories of self-knowledge, neatly encapsulated in Byrne’s epistemic rule (BEL): If p, believe that you believe that p (Byrne 2005). In this paper, I examine an objection to Carruthers’s theory in order to see whether it opens up space for a transparency theory of self-knowledge: Is it not the case that in order to interpret someone I have to have some direct access to what I believe (cf. Friedman and Petrashek 2009)? (shrink)

Concerns over epistemic opacity abound in contemporary debates on Artificial Intelligence (AI). However, it is not always clear to what extent these concerns refer to the same set of problems. We can observe, first, that the terms 'transparency' and 'opacity' are used either in reference to the computational elements of an AI model or to the models to which they pertain. Second, opacity and transparency might either be understood to refer to the properties of AI systems (...) or to the epistemic situation of human agents with respect to these systems. While these diagnoses are independently discussed in the literature, juxtaposing them and exploring possible interrelations will help to get a view of the relevant distinctions between conceptions of opacity and their empirical bearing. In pursuit of this aim, two pertinent conditions affecting computer models in general and contemporary AI in particular are outlined and discussed: opacity as a problem of computational tractability and opacity as a problem of the universality of the computational method. (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)

Google Search is arguably one of the primary epistemic tools in use today, with the lion’s share of the search-engine market globally. Scholarship on countering the current scourge of misinformation often recommends “digital lit- eracy” where internet users, especially those who get their information from so- cial media, are encouraged to fact-check such information using reputable sources. Given our current internet-based epistemic landscape, and Google’s dominance of the internet, it is very likely that such acts of epistemic (...) hygiene will take place via Google Search. The question arises whether Google Search is fit for purpose, given the apparent misalignment the general epistemic goal of promoting true beliefs and the greater online commercial ecosystem in which it is embedded. I argue that Google Search is epistemically problematic as it stands, mainly due to the opacity related to the parameters it uses for personalising search results. I further argue that in as far as an ordinary internet user is legitimately ignorant of Google’s workings, uses it in an “ordinary manner”, and is generally unable to avoid using it in the current information environment, they are not ep- istemically blameworthy for any false beliefs that they acquire via it. I conclude that too much emphasis is currently placed on individual epistemic practices and not enough on our information environment and epistemic tools when it comes to countering misinformation. (shrink)

Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic (...) class='Hi'>opacity. The visualization is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

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)

It is generally assumed that if it is possible to believe that p without believing that q, then there is some difference between the object of the thought that p and the object of the thought that q. This assumption is challenged in the present paper, opening the way to an account of epistemic opacity that improves on existing accounts, not least because it casts doubt on various arguments that attempt to derive startling ontological conclusions from seemingly innocent (...) epistemic premises. (shrink)

The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that (...) a more fruitful exploration of this question will involve a different comparison class. We routinely treat judgments made by highly trained experts in specialized fields as fair or well-grounded even though—by the nature of expert/layperson division of epistemic labor—an expert will not be able to provide an explanation of the reasoning behind these judgments that makes sense to most other people. Regardless, laypeople are thought to be acting reasonably—and ethically—in deferring to the judgments of experts that concern their areas of specialization. I suggest that we reframe our question regarding the appropriate standards of transparency in AI as one that asks when, why, and to what degree it would be ethical to accept opacity in AI. I argue that our epistemic relation to certain opaque AI technology may be relevantly similar to the layperson’s epistemic relation to the expert in certain respects, such that the successful expert/layperson division of epistemic labor can serve as a blueprint for the ethical use of opaque AI. (shrink)

Psychedelic ingestion and meditative practice are both ancient methods for altering consciousness that became widely known in Western society in the second half of the 20th century. Do the similarities begin and end there, or do these methods – as many have claimed over the years – share some deeper common elements? In this chapter I take a neurophilosophical approach to this question and argue that there are, indeed, deeper commonalities. Recent empirical studies show that psychedelics and meditation modulate overlapping (...) brain networks involved in the sense of self, salience, and attention; moreover, psychedelics can occasion lasting increases in “mindfulness-related capacities” for taking a non-reactive stance on one’s inner experience (e.g. Sampedro et al. 2017). The self-binding theory of psychedelic ego dissolution (Letheby and Gerrans 2017) offers a plausible explanation of these findings: by disrupting self-related beliefs implemented in high-level cortical networks, both psychedelics and meditation can “unbind” mental contents from one’s self-model, moving these contents along the continuum from phenomenal transparency to opacity (cf. Metzinger 2003). In other words, both psychedelics and meditation can expose and weaken our foundational beliefs about our own identity, allowing us to disidentify with these beliefs and see them as “just thoughts”. There are connections between these ideas and recent arguments suggesting that psychedelic use may have epistemic benefits consistent with philosophical naturalism (Letheby 2015, 2016, 2019). I conclude with a proposal: these connections may help in thinking about the putative epistemic benefits of meditation practice from a naturalistic perspective. (shrink)

The relevance of any logical analysis lies in its ability to solve paradoxes and trace conceptual troubles back; with this respect, the task of epistemic logic is to handle paradoxes in connection with the concept of knowledge. Epistemic logic is currently introduced as the logical analysis of crucial concepts within epistemology, namely: knowledge, belief, truth, and justification. An alternative approach will be advanced here in order to enlighten such a discourse, as centred upon the word assertion and displayed (...) in terms of utterance. Insofar as epistemic modalities express some attitudes, the intentionality of discourse will be emphasized within an illocutionary modal logic. Two large views will range over the whole study: declarative and epistemic sentences have one and the same logic (assertion logic); the plurality of languages games doesn’t entail any logical pluralism. -/- La valeur d'une analyse logique réside dans sa capacité à résoudre des paradoxes et à comprendre l'origine de nos problèmes conceptuels ; à ce titre, le rôle d'une logique épistémique est de traiter des paradoxes liés au concept de connaissance. On présente généralement la logique épistémique comme une analyse logique de concepts centraux en épistémologie : connaissance, croyance, vérité, justification. Une autre approche sera proposée ici en vue de clarifier ce genre de discours, centrée sur la notion d'assertion et décrite en termes d'énonciation. Parce que les modalités épistémiques expriment des attitudes, c'est l'intentionnalité du discours qui sera mise en valeur dans le cadre d'une logique modale illocutoire. Deux thèses transversales parcourront l'ensemble du travail : les énoncés déclaratifs et épistémiques partagent la même logique (logique assertorique) ; la pluralité des jeux de langages n'implique pas un pluralisme logique. (shrink)

The opacity of some recent Machine Learning (ML) techniques have raised fundamental questions on their explainability, and created a whole domain dedicated to Explainable Artificial Intelligence (XAI). However, most of the literature has been dedicated to explainability as a scientific problem dealt with typical methods of computer science, from statistics to UX. In this paper, we focus on explainability as a pedagogical problem emerging from the interaction between lay users and complex technological systems. We defend an empirical methodology based (...) on field work, which should go beyond the in-vitro analysis of UX to examine in-vivo problems emerging in the field. Our methodology is also comparative, as it chooses to steer away from the almost exclusive focus on ML to compare its challenges with those faced by more vintage algorithms. Finally, it is also philosophical, as we defend the relevance of the philosophical literature to define the epistemic desiderata of a good explanation. This study was conducted in collaboration with Etalab, a Task Force of the French Prime Minister in charge of Open Data & Open Government Policies, dealing in particular with the enforcement of the right to an explanation. In order to illustrate and refine our methodology before going up to scale, we conduct a preliminary work of case studies on the main different types of algorithms used by the French administration: computation, matching algorithms and ML. We study the merits and drawbacks of a recent approach to explanation, which we baptize input-output black box reasoning or BBR for short. We begin by presenting a conceptual framework including the distinctions necessary to a study of pedagogical explainability. We proceed to algorithmic case studies, and draw model-specific and model-agnostic lessons and conjectures. (shrink)

It is widely held that counterfactuals, unlike attitude ascriptions, preserve the referential transparency of their constituents, i.e., that counterfactuals validate the substitution of identicals when their constituents do. The only putative counterexamples in the literature come from counterpossibles, i.e., counterfactuals with impossible antecedents. Advocates of counterpossibilism, i.e., the view that counterpossibles are not all vacuous, argue that counterpossibles can generate referential opacity. But in order to explain why most substitution inferences into counterfactuals seem valid, counterpossibilists also often maintain that (...) counterfactuals with possible antecedents are transparency‐preserving. I argue that if counterpossibles can generate opacity, then so can ordinary counterfactuals with possible antecedents. Utilizing an analogy between counterfactuals and attitude ascriptions, I provide a counterpossibilist‐friendly explanation for the apparent validity of substitution inferences into counterfactuals. I conclude by suggesting that the debate over counterpossibles is closely tied to questions concerning the extent to which counterfactuals are more like attitude ascriptions and epistemic operators than previously recognized. (shrink)

In the present paper I defend an interpretation of the Cartesian notion of material falsity that it would be adequate to describe as ‘epistemic’, as opposed to most other views in the literature, which could be described as ‘metaphysical’. Whereas metaphysical conceptions of material falsity consider an idea to be such because of some kind of failure in their representative properties, that is, in the relation between what they exhibit and their objects, an epistemic view considers that what (...) makes an idea materially false is some kind of opacity that precludes their representational properties to be known in the first place. In the paper the evidence for these two kinds of reading is assessed, and it is shown that epistemic views are clearly more adequate. (shrink)

I present an approach to our conceiving absolute impossibilities—things which obtain at no possible world—in terms of ceteris paribus intentional operators: variably restricted quantifiers on possible and impossible worlds based on world similarity. The explicit content of a representation plays a role similar in some respects to the one of a ceteris paribus conditional antecedent. I discuss how such operators invalidate logical closure for conceivability, and how similarity works when impossible worlds are around. Unlike what happens with ceteris paribus counterfactual (...) conditionals, the closest worlds are relevantly closest belief-worlds: closest to how things are believed to be, rather than to how they are. Also, closeness takes into account apriority and the opacity of intentional contexts. (shrink)

Definition of the problem The umbrella term “explicability” refers to the reduction of opacity of artificial intelligence (AI) systems. These efforts are challenging for medical AI applications because higher accuracy often comes at the cost of increased opacity. This entails ethical tensions because physicians and patients desire to trace how results are produced without compromising the performance of AI systems. The centrality of explicability within the informed consent process for medical AI systems compels an ethical reflection on the (...) trade-offs. Which levels of explicability are needed to obtain informed consent when utilizing medical AI? Arguments We proceed in five steps: First, we map the terms commonly associated with explicability as described in the ethics and computer science literature, i.e., disclosure, intelligibility, interpretability, and explainability. Second, we conduct a conceptual analysis of the ethical requirements for explicability when it comes to informed consent. Third, we distinguish hurdles for explicability in terms of epistemic and explanatory opacity. Fourth, this then allows to conclude the level of explicability physicians must reach and what patients can expect. In a final step, we show how the identified levels of explicability can technically be met from the perspective of computer science. Throughout our work, we take diagnostic AI systems in radiology as an example. Conclusion We determined four levels of explicability that need to be distinguished for ethically defensible informed consent processes and showed how developers of medical AI can technically meet these requirements. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. (...) For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

This chapter focuses on the connection between moral disagreement and moral relativism. Moral relativists, generally speaking, think both (i) that there is no unique objectively correct moral standard and (ii) that the rightness and wrongness of an action depends in some way on a moral standard accepted by some group or an individual. This chapter will first consider the metaphysical and epistemic arguments for moral relativism that begin from the premise that there is considerable amount of moral disagreement both (...) within individual societies and between them. The second half of the chapter, by contrast, focuses on the objection that moral relativism threatens to make us unable to have moral disagreements because it seems to make us speak past one another. This part of the chapter also evaluates relativist responses to this disagreement problem that rely on semantic opacity, disagreement in attitude, metalinguistic negotiations, and truth relativism. The chapter finally concludes by considering future directions of research in this area. (shrink)

Artificial intelligence (AI) and machine learning (ML) models have undoubtedly become useful tools in science. In general, scientists and ML developers are optimistic – perhaps rightfully so – about the potential that these models have in facilitating scientific progress. The philosophy of AI literature carries a different mood. The attention of philosophers remains on potential epistemological issues that stem from the so-called “black box” features of ML models. For instance, Eamon Duede (2023) argues that opacity in deep learning models (...) (DLMs) is epistemically problematic in the context of justification, though not in the context of discovery. -/- In this paper, I aim to show that a similar epistemological concern is echoed in the epistemology of imagination literature. It is traditionally held that, given its black box features, reliance on the imagination is epistemically problematic in the context of justification, though not in the context of discovery. The constraints-based approach to the imagination answers the epistemological concern by providing an account of how we can rely on the imagination in the context of justification by way of constraints. I argue by analogy that a similar approach can be applied to the opaque DLM case. Ultimately, my goal is to explore just how far this analogy extends, and whether a constraints-based approach to opaque DLMs can answer the epistemological concern surrounding their black box features in the context of justification. -/- (Note that this paper is IN PROGRESS and UNPUBLISHED). (shrink)

The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the experts (...) who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

Recent conversation has blurred two very different social epistemic phenomena: echo chambers and epistemic bubbles. Members of epistemic bubbles merely lack exposure to relevant information and arguments. Members of echo chambers, on the other hand, have been brought to systematically distrust all outside sources. In epistemic bubbles, other voices are not heard; in echo chambers, other voices are actively undermined. It is crucial to keep these phenomena distinct. First, echo chambers can explain the post-truth phenomena in (...) a way that epistemic bubbles cannot. Second, each type of structure requires a distinct intervention. Mere exposure to evidence can shatter an epistemic bubble, but may actually reinforce an echo chamber. Finally, echo chambers are much harder to escape. Once in their grip, an agent may act with epistemic virtue, but social context will pervert those actions. Escape from an echo chamber may require a radical rebooting of one's belief system. (shrink)

[Author note: There is a video explainer of this paper on youtube at the new work in philosophy channel (search for surname+deepfakes).] -/- It is widely thought that deepfake videos are a significant and unprecedented threat to our epistemic practices. In some writing about deepfakes, manipulated videos appear as the harbingers of an unprecedented _epistemic apocalypse_. In this paper I want to take a critical look at some of the more catastrophic predictions about deepfake videos. I will argue for (...) three claims: (1) that once we recognise the role of social norms in the epistemology of recordings, deepfakes are much less concerning, (2) that the history of photographic manipulation reveals some important precedents, correcting claims about the novelty of deepfakes, and (3) that proposed solutions to deepfakes have been overly focused on technological interventions. My overall goal is not so much to argue that deepfakes are not a problem, but to argue that behind concerns around deepfakes lie a more general class of social problems about the organisation of our epistemic practices. (shrink)

We present data and argument to show that in Tetris - a real-time interactive video game - certain cognitive and perceptual problems are more quickly, easily, and reliably solved by performing actions in the world rather than by performing computational actions in the head alone. We have found that some translations and rotations are best understood as using the world to improve cognition. These actions are not used to implement a plan, or to implement a reaction; they are used to (...) change the world in order to simplify the problem-solving task. Thus, we distinguish pragmatic actions ñ actions performed to bring one physically closer to a goal - from epistemic actions - actions performed to uncover information that is hidden or hard to compute mentally. To illustrate the need for epistemic actions, we first develop a standard information-processing model of Tetris-cognition, and show that it cannot explain performance data from human players of the game - even when we relax the assumption of fully sequential processing. Standard models disregard many actions taken by players because they appear unmotivated or superfluous. However, we describe many such actions that are actually taken by players that are far from superfluous, and that play valuable roles in improving human performance. We argue that traditional accounts are limited because they regard action as having a single function: to change the world. By recognizing a second function of action - an epistemic function - we can explain many of the actions that a traditional model cannot. Although, our argument is supported by numerous examples specifically from Tetris, we outline how the one category of epistemic action can be incorporated into theories of action more generally. (shrink)

We explore some possibilities for developing epistemic logic using truthmaker semantics. We identify three possible targets of analysis for the epistemic logician. We then list some candidate epistemic principles and review the arguments that render some controversial. We then present the classic Hintikkan approach to epistemic logic and note—as per the ‘problem of logical omniscience’—that it validates all of the aforementioned principles, controversial or otherwise. We then lay out a truthmaker framework in the style of Kit (...) Fine and present six different ways of extending this semantics with a conditional knowledge operator, drawing on notions of implication and content that are prominent in Fine’s work. We demonstrate that different logics are thereby generated, bearing on the aforementioned epistemic principles. Finally, we offer preliminary observations about the prospects for each logic. (shrink)

Within the United States, the most prominent justification for criminal punishment is retributivism. This retributivist justification for punishment maintains that punishment of a wrongdoer is justified for the reason that she deserves something bad to happen to her just because she has knowingly done wrong—this could include pain, deprivation, or death. For the retributivist, it is the basic desert attached to the criminal’s immoral action alone that provides the justification for punishment. This means that the retributivist position is not reducible (...) to consequentialist considerations nor in justifying punishment does it appeal to wider goods such as the safety of society or the moral improvement of those being punished. A number of sentencing guidelines in the U.S. have adopted desert as their distributive principle, and it is increasingly given deference in the “purposes” section of state criminal codes, where it can be the guiding principle in the interpretation and application of the code’s provisions. Indeed, the American Law Institute recently revised the Model Penal Code so as to set desert as the official dominate principle for sentencing. And courts have identified desert as the guiding principle in a variety of contexts, as with the Supreme Court’s enthroning retributivism as the “primary justification for the death penalty.” While retributivism provides one of the main sources of justification for punishment within the criminal justice system, there are good philosophical and practical reasons for rejecting it. One such reason is that it is unclear that agents truly deserve to suffer for the wrongs they have done in the sense required by retributivism. In the first section, I explore the retributivist justification of punishment and explain why it is inconsistent with free will skepticism. In the second section, I then argue that even if one is not convinced by the arguments for free will skepticism, there remains a strong epistemic argument against causing harm on retributivist grounds that undermines both libertarian and compatibilist attempts to justify it. I maintain that this argument provides sufficient reason for rejecting the retributive justification of criminal punishment. I conclude in the third section by briefly sketching my public health-quarantine model, a non-retributive alternative for addressing criminal behavior that draws on the public health framework and prioritizes prevention and social justice. I argue that the model is not only consistent with free will skepticism and the epistemic argument against retributivism, it also provides the most justified, humane, and effective way of dealing with criminal behavior. (shrink)

What if your peers tell you that you should disregard your perceptions? Worse, what if your peers tell you to disregard the testimony of your peers? How should we respond if we get evidence that seems to undermine our epistemic rules? Several philosophers have argued that some epistemic rules are indefeasible. I will argue that all epistemic rules are defeasible. The result is a kind of epistemic particularism, according to which there are no simple rules connecting (...) descriptive and normative facts. I will argue that this type of particularism is more plausible in epistemology than in ethics. The result is an unwieldy and possibly infinitely long epistemic rule — an Uber-rule. I will argue that the Uber-rule applies to all agents, but is still defeasible — one may get misleading evidence against it and rationally lower one’s credence in it. (shrink)

Examining previous discussions on how to construe the concepts of gender and race, we advocate what we call strategic conceptual engineering. This is the employment of a (possibly novel) concept for specific epistemic or social aims, concomitant with the openness to use a different concept (e.g., of race) for other purposes. We illustrate this approach by sketching three distinct concepts of gender and arguing that all of them are needed, as they answer to different social aims. The first concept (...) serves the aim of identifying and explaining gender-based discrimination. It is similar to Haslanger’s well-known account, except that rather than offering a definition of ‘woman’ we focus on ‘gender’ as one among several axes of discrimination. The second concept of gender is to assign legal rights and social recognitions, and thus is to be trans-inclusive. We argue that this cannot be achieved by previously suggested concepts that include substantial gender-related psychological features, such as awareness of social expectations. Instead, our concept counts someone as being of a certain gender solely based on the person’s self-identification with this gender. The third concept of gender serves the aim of personal empowerment by means of one’s gender identity. In this context, substantial psychological features and awareness of one’s social situation are involved. While previous accounts of concepts have focused on their role in determining extensions, we point to contexts where a concept’s role in explanation and moral reasoning can be more important. (shrink)

This paper outlines an empirically-grounded account of normative political legitimacy. The main idea is to give a normative edge to empirical measures of sociological legitimacy through a non-moralised form of ideology critique. A power structure’s responsiveness to the values of those subjected to its authority can be measured empirically and may be explanatory or predictive insofar as it tracks belief in legitimacy, but by itself it lacks normative purchase: it merely describes a preference alignment, and so tells us nothing about (...) whether the ruled have reason to support the rulers. I argue that we can close this gap by filtering the preferences of the ruled through a form of non-moralised epistemic ideology critique, itself grounded in an empirical account of how belief in legitimacy is formed. (shrink)

The epistemic closure principle says that knowledge is closed under known entailment. The closure principle is deeply implicated in numerous core debates in contemporary epistemology. Closure’s opponents claim that there are good theoretical reasons to abandon it. Closure’s proponents claim that it is a defining feature of ordinary thought and talk and, thus, abandoning it is radically revisionary. But evidence for these claims about ordinary practice has thus far been anecdotal. In this paper, I report five studies on the (...) status of epistemic closure in ordinary practice. Despite decades of widespread assumptions to the contrary in philosophy, ordinary practice is ambivalent about closure. Ordinary practice does not endorse an unqualified version of the epistemic closure principle, although it might endorse a source-relative version of the principle. In particular, whereas inferential knowledge is not viewed as closed under known entailment, perceptual knowledge might be. (shrink)

Are identity criteria grounding principles? A prima facie answer to this question is positive. Specifically, two-level identity criteria can be taken as principles related to issues of identity among objects of a given kind compared with objects of a more basic kind. Moreover, they are grounding metaphysical principles of some objects with regard to others. In the first part of the paper we criticise this prima facie natural reading of identity criteria. This result does not mean that identity criteria could (...) not be taken as grounding principles. In the second part, we propose some basic steps towards a conceptual reading of grounding. Such a way of understanding it goes along with an epistemic reading of identity criteria. (shrink)

In the last decade, structural realism has been presented as the most promising strategy for developing a defensible realist view of science. Nevertheless, controversy still continues in relation to the exact meaning of the proposed structuralism. The stronger version of structural realism, the so-called ontic structural realism, has been argued for on the basis of some ideas related to quantum mechanics. In this paper, I will first outline these arguments, mainly developed by Steven French and James Ladyman, then challenge them, (...) putting a particular emphasis on a metaphysical principle which, even though it is crucial for the whole argument, hasn't been, in my opinion, clearly stated and examined yet. My overall view will be that a weaker version of the form of realism we are considering is more plausible – namely, epistemic structural realism. (shrink)

According to Jago (2014a), logical omniscience is really part of a deeper paradox. Jago develops an epistemic logic with principles of indeterminate closure to solve this paradox, but his official semantics is difficult to navigate, it is motivated in part by substantive metaphysics, and the logic is not axiomatized. In this paper, I simplify this epistemic logic by adapting the hyperintensional semantic framework of Sedlár (2021). My first goal is metaphysical neutrality. The solution to the epistemic paradox (...) should not require appeal to a metaphysics of truth-makers, situations, or impossible worlds, by contrast with Jago’s official semantics. My second goal is to elaborate on the proof theory. I show how to axiomatize a family of logics with principles of indeterminate epistemic closure. (shrink)

Philosophers have observed that metaphysical necessity appears to be a true or real or genuine form of necessity while epistemic necessity does not. Similarly, natural necessity appears genuine while deontic necessity does not. But what is it for a form of necessity to be genuine? I defend an account of genuine necessity in explanatory terms. The genuine forms of necessity, I argue, are those that provide what I call necessitarianexplanation. I discuss the relationship of necessitarian explanation to ground.

Modal epistemologists parse modal conditions on knowledge in terms of metaphysical possibilities or ways the world might have been. This is problematic. Understanding modal conditions on knowledge this way has made modal epistemology, as currently worked out, unable to account for epistemic luck in the case of necessary truths, and unable to characterise widely discussed issues such as the problem of religious diversity and the perceived epistemological problem with knowledge of abstract objects. Moreover, there is reason to think that (...) this is a congenital defect of orthodox modal epistemology. This way of characterising modal epistemology is however optional. It is shown that one can non-circularly characterise modal conditions on knowledge in terms of epistemic possibilities, or ways the world might be for the target agent. Characterising the anti-luck condition in terms of epistemic possibilities removes the impediment to understanding epistemic luck in the case of necessary truths and opens the door to using these conditions to shed new light on some longstanding epistemological problems. (shrink)

Several philosophers have recently tried to define natural kinds in epistemic terms only. Given the persistent problems with finding a successful metaphysical theory, these philosophers argue that we would do better to describe natural kinds solely in terms of their epistemic usefulness, such as their role in supporting inductive inferences. In this paper, I argue against these epistemology-only theories of natural kinds and in favor of, at least partly, metaphysical theories. I do so in three steps. In the (...) first section of the paper, I propose two desiderata for a theory of natural kinds. In the second section, I discuss one example of a ‘general’ epistemology-only theory, proposed by Marc Ereshefsky and Thomas Reydon, and argue that theories like theirs fail to provide adequate criteria of natural kinds. In the third section, I focus on one example of a ‘specific’ epistemology-only theory, proposed by P. D. Magnus, and use it to show why such theories cannot justify the claim that the proposed epistemic criteria account for the naturalness of kinds. (shrink)

The Capgras delusion is a condition in which a person believes that an imposter has replaced some close friend or relative. Recent theorists have appealed to Bayesianism to help explain both why a subject with the Capgras delusion adopts this delusional belief and why it persists despite counter-evidence. The Bayesian approach is useful for addressing these questions; however, the main proposal of this essay is that Capgras subjects also have a delusional conception of epistemic possibility, more specifically, they think (...) more things are possible, given what is known, than non-delusional subjects do. I argue that this is a central way in which their thinking departs from ordinary cognition and that it cannot be characterized in Bayesian terms. Thus, in order to fully understand the cognitive processing involved in the Capgras delusion, we must move beyond Bayesianism. 1 The Simple Bayesian Model2 Anomalous Evidence and the Capgras Delusion3 Impaired Reasoning4 Setting Priors5 Epistemic Modality6 Delusions of Possibility7 Delusions of Possibility in Different Contexts8 How Many Factors? (shrink)

This paper explores the relationship between the questioning attitude of wondering and a class of attitudes I call 'epistemic desires'. Broadly, these are desires to improve one's epistemic position on some question. A common example is the attitude of wanting to know the answer to some question. I argue that one can have any kind of epistemic desire towards any question, Q, without necessarily wondering Q, but not conversely. That is, one cannot wonder Q without having at (...) least some epistemic desire directed towards Q. I defend this latter claim from apparent counterexamples due to Friedman (2013) and Drucker (2022), and finish with a proposal on which epistemic desires, particularly the desire for understanding, play an explanatory role in distinguishing wondering from other forms of question-directed thought. (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)

Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive (...) a systematic treatment in the literature: when such algorithms are used in life-changing decisions, they can obstruct us from effectively shaping our lives according to our goals and preferences, thus undermining our autonomy. I argue that this concern deserves closer attention as it furnishes the call for transparency in algorithmic decision-making with both new tools and new challenges. (shrink)

Reflection on the possibility of cases in which experience is cognitively penetrated has suggested to many that an experience's etiology can reduce its capacity to provide prima facie justification for believing its content below a baseline. This is epistemic downgrade due to etiology, and its possibility is incompatible with phenomenal conservatism. I develop a view that explains the epistemic deficiency in certain possible cases of cognitive penetration but on which there is no epistemic downgrading below a baseline (...) and on which etiology plays no explanatory role. This view is not phenomenal conservatism exactly, but it does capture what’s right about phenomenal conservatism. (shrink)

Is logic normative for belief? A standard approach to answering this question has been to investigate bridge principles relating claims of logical consequence to norms for belief. Although the question is naturally an epistemic one, bridge principles have typically been investigated in isolation from epistemic debates over the correct norms for belief. In this paper we tackle the question of whether logic is normative for belief by proposing a Kripkean model theory accounting for the interaction between logical, doxastic, (...) epistemic and deontic notions and using this model theory to show which bridge principles are implied by epistemic norms that we have independent reason to accept, for example, theknowledge normand thetruth norm. We propose a preliminary theory of the interaction between logical, doxastic, epistemic and deontic notions that has among its commitments bridge principles expressing how logic is normative for belief. We also show how our framework suggests that logic is exceptionally normative. (shrink)

In this peer commentary on L. Syd M. Johnson’s “Inference and Inductive Risk in Disorders of Consciousness,” I argue for the necessity of disability education as an integral component of decision-making processes concerning patients with DOC and, mutatis mutandis, all patients with disabilities. The sole qualification Johnson places on such decision-making is that stakeholders are educated about and “understand the uncertainties of diagnosis and prognosis.” Drawing upon research in philosophy of disability, social epistemology, and health psychology, I argue that this (...) educational qualification is insufficient to address systemic ableism and other forms of epistemic bias in quality of life judgments. (shrink)

This essay aims to vindicate the thesis that cognitive computational properties are abstract objects implemented in physical systems. I avail of Voevodsky's Univalence Axiom and function type equivalence in Homotopy Type Theory, in order to specify an abstraction principle for epistemic (hyper-)intensions. The homotopic abstraction principle for epistemic (hyper-)intensions provides an epistemic conduit for our knowledge of (hyper-)intensions as abstract objects. I examine, then, how intensional functions in Epistemic Modal Algebra are deployed as core models in (...) the philosophy of mind, Bayesian perceptual psychology, and the program of natural language semantics in linguistics, and I argue that this provides abductive support for the truth of homotopic abstraction. Epistemic modality can thus be shown to be both a compelling and a materially adequate candidate for the fundamental structure of mental representational states, comprising a fragment of the language of thought. (shrink)