. 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.

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)

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.

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)

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)

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)

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)

Computer simulations of the formation and evolution of large-scale structure in the universe are integral to the enterprise of modern cosmology. Establishing the reliability of these simulations has been extremely challenging, primarily because of epistemic opacity. In this setting, robustness analysis defined by requiring converging outputs from a diverse ensemble of simulations is insufficient to determine simulation validity. We propose an alternative path of structured code validation that applies eliminative reasoning to isolate and reduce possible sources of error, (...) a potential path that is already being explored by some cosmologists. (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)

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)

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)

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)

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)

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)

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)

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)

On the dominant contemporary accounts of how practical considerations affect what we ought to believe, practical considerations either encroach on epistemic rationality by affecting whether a belief is epistemically justified, or constitute distinctively practical reasons for belief which can only affect what we ought to believe by conflicting with epistemic rationality. This paper argues that Søren Kierkegaard offers a promising alternative view on which practical considerations can affect what we ought to believe without either encroaching on or (necessarily) (...) conflicting with epistemic rationality by determining which among the epistemically permitted outright doxastic attitudes one should all‐things‐considered adopt. (shrink)

In a recent work, Walter Carnielli and Abilio Rodrigues present an epistemically motivated interpretation of paraconsistent logic. In their view, when there is conflicting evidence with regard to a proposition A (i.e. when there is both evidence in favor of A and evidence in favor of ￢A) both A and ￢A should be accepted without thereby accepting any proposition B whatsoever. Hence, reasoning within their system intends to mirror, and thus, should be constrained by, the way in which we reason (...) about evidence. In this article we will thoroughly discuss their position and suggest some ways in which this project can be further developed. The aim of the paper is twofold. On the one hand, we will present some philosophical critiques to the specific epistemic interpretation of paraconsistent logic proposed by Carnielli & Rodrigues. First, we will contend that Carnielli & Rodrigues’s interpretation implies a thesis about what evidence rationally justifies to accept or believe, called Extreme Permissivism, which is controversial among epistemologists. Second, we will argue that what agents should do, from an epistemic point of view, when faced with conflicting evidence, is to suspend judgment. On the other hand, despite these criticisms we do not believe that the epistemological motivation put forward by Carnielli & Rodrigues is entirely wrong. In the last section, we offer an alternative way in which one might account for the epistemic rationality of accepting contradictions and, thus, for an epistemic understanding of paraconsistency, which leads us to discuss the notion of diachronic epistemic rationality. (shrink)

Much of the plausibility of epistemic conservatism derives from its prospects of explaining our rationality in holding memory beliefs. In the first two parts of this paper, I argue for the inadequacy of the two standard approaches to the epistemology of memory beliefs, preservationism and evidentialism. In the third, I point out the advantages of the conservative approach and consider how well conservatism survives three of the strongest objections against it. Conservatism does survive, I claim, but only if qualified (...) in certain ways. Appropriately qualified, conservatism is no longer the powerful anti-skeptical tool some have hoped for, but a doctrine closely connected with memory. (shrink)

It is clear that lack of awareness of the consequences of an action can undermine moral responsibility and blame for these consequences. But when and how it does so is controversial. Sometimes an agent believing that the outcome might occur is excused because it seemed unlikely to her, and sometimes an agent having no idea that it would occur is nevertheless to blame. A low or zero degree of belief might seem to excuse unless the agent “should have known better”, (...) but it is unclear how to spell out this normative condition. -/- This chapter combines (a) an independently motivated account of responsibility, blame, and credit as grounded in a normal explanatory relation between agential qualities and objects of responsibility with (b) the familiar Strawsonian idea that moral blame and credit depend on the agent’s quality of will. The resulting explanatory quality of will condition on moral responsibility is then further motivated by being shown to account for the effects on moral blame and credit of justifications, as well as of excuses and undermined control in cases not involving ignorance. -/- The explanatory quality of will condition is finally applied to cases involving various degrees of lack of awareness. Though this condition itself involves no awareness requirement, it is shown how it accounts for the degrees to which lack of awareness can excuse. It is also explained how lack of awareness fails as an excuse exactly when the agent should have known better and can be blamed for not doing so. (shrink)

We argue that the interaction of biased media coverage and widespread employment of the recognition heuristic can produce epistemic injustices. First, we explain the recognition heuristic as studied by Gerd Gigerenzer and colleagues, highlighting how some of its components are largely external to, and outside the control of, the cognitive agent. We then connect the recognition heuristic with recent work on the hypotheses of embedded, extended, and scaffolded cognition, arguing that the recognition heuristic is best understood as an instance (...) of scaffolded cognition. In section three, we consider the double-edged sword of cognitive scaffolding. On the one hand, scaffolds can reduce the internal processing demands on cognitive agents while increasing their access to information. On the other hand, the use of scaffolding leaves cognitive agents increasingly vulnerable to forming false beliefs or failing to form beliefs at all about particular topics. With respect to the recognition heuristic, agents rely on third parties (such as the media) to report not just what’s true but also what’s important or valuable. This makes cognitive agents relying on these third parties vulnerable to two erroneous influences: 1) because they don’t recognize something, it isn’t important or valuable, and 2) because they do recognize something, it is important or valuable. Call the latter the Kardashian Inference and the former the Darfur Inference. In section four, we use Fricker’s (2007) concept of epistemic injustice to characterize the nature and harm of these false inferences, with special emphasis on the Darfur Inference. In section five, we use data-mining and an empirical study to show how Gigerenzer’s population estimation task is liable to produce Darfur Inferences. We conclude with some speculative remarks on more important Darfur Inferences, and how to avoid them by scaffolding better. One primary way to accomplish this it to shift the burden of embodying the virtue of epistemic justice from the hearer or consumer of media to the media themselves. (shrink)

A growing number of philosophers are concerned with the epistemic status of culturally nurtured beliefs, beliefs found especially in domains of morals, politics, philosophy, and religion. Plausibly, worries about the deep impact of cultural contingencies on beliefs in these domains of controversial views is a question about well-foundedness: Does it defeat well-foundedness if the agent is rationally convinced that she would take her own reasons for belief as insufficiently well-founded, or would take her own belief as biased, had she (...) been nurtured in a different psychographic community? This chapter will examine the proper scope and force of this epistemic location problem. It sketches an account of well and ill-founded nurtured belief based upon the many markers of doxastic strategies exhibiting low to high degrees of inductive risk: the moral and epistemic risk of ‘getting it wrong’ in an inductive context of inquiry. (shrink)

Many idealists have thought that realism raises epistemological problems. The worry is that, if it is possible for truths about ordinary objects to outstrip our experiences in the ways that realists typically suppose, we could never be justified in our beliefs about objects. Few contemporary theorists find this argument convincing; philosophers have offered a variety of responses to defend the epistemology of our object judgments under the assumption of realism. But in this paper, I offer a new type of (...) class='Hi'>epistemic argument against realism which is immune to the standard responses in the literature. In addition to raising a challenge for realism, the epistemology of our object judgments has implications for how the idealist should develop her own positive metaphysical view. So in the second half of this paper, I discuss how the idealist should understand the dependence between objects and our experiences if she is to secure epistemic advantages over the realist. (shrink)

In this paper, I characterize visual epistemic representations as concrete two- or three-dimensional tools for conveying information about aspects of their target systems or phenomena of interest. I outline two features of successful visual epistemic representation: that the vehicle of representation contain sufficiently accurate information about the phenomenon of interest for the user’s purpose, and that it convey this information to the user in a manner that makes it readily available to her. I argue that actual epistemic (...) representation may involve tradeoffs between these and is successful to the extent that they are present. (shrink)

When considering the question of possible transformation and disappearance of scientific objects, it is useful to distinguish between epistemic and technical objects. This paper presents preliminary observations and offers a typology of obsolescence. It is based on several case studies drawn from the history of life sciences. The paper proceeds as follows: first, the dynamics of epistemic objects is considered through the examples of Carl Correns’ study of “xenia”, Alfred Kühn’s work on physiological developmental genetics, and Paul Zamecnik’s (...) research on the protein biosynthesis. Second, the phasing out of technical objects is then separately discussed and illustrated by the example of radioactive tracing in biology – until recently, an established technique of visualization. (shrink)

The idea that our epistemic practices can be wrongful has been the core observation driving the growing literature on epistemic injustice, doxastic wronging, and moral encroachment. But, one element of our epistemic practice has been starkly absent from this discussion of epistemic morality: attention. The goal of this article is to show that attention is a worthwhile focus for epistemology, especially for the field of epistemic morality. After presenting a new dilemma for proponents of doxastic (...) wronging, I show how focusing on attention not only allows us to defuse that dilemma, but also helps to substantiate accounts of what goes wrong in cases of doxastic wronging. (shrink)

This article considers distinct ways of understanding the world, referred to in psychology as Functions of Consciousness or as Cognitive Modes, having as the scope of interest epistemology and natural sciences. Inspired by C.G. Jung's Simile of the Spectrum, we consider three basic cognitive modes associated to: (R) embodied instinct, experience, and action; (G) reality perception and learning; and (B) concept abstraction, rational thinking, and language. RGB stand for the primary colors: red, green, and blue. Accordingly, a conceptual map between (...) cognitive modes and primary and secondary colors is built based on the physics and physiology of color perception and epistemological characteristics of the aforementioned cognitive modes, leading to logical relations structured as an Hexagon of Opposition. Finally, this model of cognitive modes is applied to the analysis and interpretation of some important episodes in the historical development of physics and technology. (shrink)

What I call the Doxastic Puzzle, is the impression that while each of these claims seems true, at least one of them must be false: (a) Claims of the form ‘S ought to have doxastic attitude D towards p at t’ are sometimes true at t, (b) If Φ-ing at t is not within S’s effective control at t, then it is false, at t, that ‘S ought to Φ at t’, (c) For all S, p, and t, having doxastic (...) attitude D towards p at t is not within S’s effective control at t. All three natural replies to the puzzle have been pursued. Some have claimed that doxastic attitudes like believing that p are, in fact, within our effective control, or sufficiently so. Others have claimed that doxastic ought-claims, strictly speaking, are always false. And some have denied that effective control is required for the adequacy of doxastic ought-claims in general. I here pursue and examine a different strategy. In the first part of this paper, I argue that these claims are not only each true but actually not in tension with each other in the first place. Instead of attempting to dispel the puzzle, this solution proposes to evade it instead: to solve it by properly understanding, and by thereby accepting without contradiction, all of its constitutive claims. In the second part of the paper, I argue that the evasive strategy forces us to re-think our understanding of the place of normative reasons in epistemology. More exactly, it seems to come at the cost of one central way of thinking about our reasons for having doxastic attitudes, one where such reasons are good-standing exemplars of normative reasons in general. The evasive strategy, that is, threatens to lead us very quickly to a deflationary picture of epistemic normativity: it rescues normative talk, but sacrifices normative substance. I conclude by explaining why I think this is more consequential than some have made it out to be, and by suggesting that these consequences are welcome nonetheless. (shrink)

A number of authors have defended permissivism by appealing to rational supererogation, the thought that some doxastic states might be rationally permissible even though there are other, more rational beliefs available. If this is correct, then there are situations that allow for multiple rational doxastic responses, even if some of those responses are rationally suboptimal. In this paper, I will argue that this is the wrong approach to defending permissivism—there are no doxastic states that are rationally supererogatory. By the lights (...) of contemporary linguistics, ‘rational’ is an absolute gradable adjective, and as such, can only be applied to things that satisfy the top of the scale of rationality. For this reason, it is not possible to believe what is rational while also failing to believe what is rationally optimal. (shrink)

Epistemic Contextualism is the view that “knows that” is semantically context-sensitive and that properly accommodating this fact into our philosophical theory promises to solve various puzzles concerning knowledge. Yet Epistemic Contextualism faces a big—some would say fatal—problem: The Semantic Error Problem. In its prominent form, this runs thus: speakers just don’t seem to recognise that “knows that” is context-sensitive; so, if “knows that” really is context-sensitive then such speakers are systematically in error about what is said by, or (...) how to evaluate, ordinary uses of “S knows that p”; but since it's wildly implausible that ordinary speakers should exhibit such systematic error, the expression “knows that” isn't context-sensitive. We are interested in whether, and in what ways, there is such semantic error; if there is such error, how it arises and is made manifest; and, again, if there is such error to what extent it is a problem for Epistemic Contextualism. The upshot is that some forms of The Semantic Error Problem turn out to be largely unproblematic. Those that remain troublesome have analogue error problems for various competitor conceptions of knowledge. So, if error is any sort of problem, then there is a problem for every extant competitor view. (shrink)

If citizens are to make enlightened collective decisions, they need to rely on true factual beliefs, but misinformation impairs their ability to do so. Although some cases of misinformation are deliberate and amount to propaganda, cases of inadvertent misinformation are just as problematic in affecting the beliefs and behavior of democratic citizens. A review of empirical evidence suggests that this is a serious problem that cannot entirely be corrected by means of deliberation.

Stewart Cohen argues that much contemporary epistemological theorizing is hampered by the fact that ‘epistemic justification’ is a term of art and one that is never given any serious explication in a non-tendentious, theory-neutral way. He suggests that epistemologists are therefore better off theorizing in terms of rationality, rather than in terms of ‘epistemic justification’. Against this, I argue that even if the term ‘epistemic justification’ is not broadly known, the concept it picks out is quite familiar, (...) and partly because it’s a term of art, justification talk is a better vehicle for philosophical theorizing. ‘Rational’ is too unclear for our philosophical purposes, and the fact that ‘epistemic justification’ gets fleshed out by appeal to substantive, controversial theses is no obstacle to its playing the needed role in epistemological theorizing. (shrink)

Kyle Stanford’s reformulation of the problem of underdetermination has the potential to highlight the epistemic obligations of scientists. Stanford, however, presents the phenomenon of unconceived alternatives as a problem for realists, despite critics’ insistence that we have contextual explanations for scientists’ failure to conceive of their successors’ theories. I propose that responsibilist epistemology and the concept of “role oughts,” as discussed by Lorraine Code and Richard Feldman, can pacify Stanford’s critics and reveal broader relevance of the “new induction.” The (...) possibility of unconceived alternatives pushes us to question our contemporary expectation for scientists to reason outside of their historical moment. (shrink)

Consider two epistemic experts—for concreteness, let them be two weather forecasters. Suppose that you aren’t certain that they will issue identical forecasts, and you would like to proportion your degrees of belief to theirs in the following way: first, conditional on either’s forecast of rain being x, you’d like your own degree of belief in rain to be x. Secondly, conditional on them issuing different forecasts of rain, you’d like your own degree of belief in rain to be some (...) weighted average of the forecast of each. Finally, you’d like your degrees of belief to be given by an orthodox probability measure. Moderate ambitions, all. But you can’t always get what you want. (shrink)

It is not uncommon in time travel stories to find that the mechanism by which the time travel is achieved is not invented. A time traveller could journey to his/her own past and give the designs of the time travel machine to his/her earlier self as s/he was given the designs as a younger person. These designs never get thought up by anyone. Such a situation would conflict with the usual conception of the acquisition of knowledge. This situation is called (...) the Temporal Epistemic Anomaly and would arise if knowledge is gained at a time prior to the information in question being transmitted but is not discovered or invented at any time. This article examines the implications of information propagating around a causal chain that is closed in time (which is required to create the Anomaly) and whether this information need have a specific origin point. (shrink)

This paper seeks to intervene in environmental ethics and social epistemology. Within a predominant strand of environmental ethics, one witnesses accounts based on nonhumans’ ability to suffer, and consequently, the passivity of nonhumans. On the other hand, social epistemology is often not social enough insofar as it does not include nonhumans. Seminal accounts of epistemic injustice often conceal or exclude the possibility that nonhumans can be subjects of knowledge and victims of epistemic injustice because of an anthropocentric bias (...) that maintains propositional language is a necessary condition for knowledge. By presenting a non-anthropocentric, corporeal epistemology, this paper reveals a more affirmative account of nonhumans as epistemic agents with tacit, embodied knowledge. To prevent epistemic depreciation turning into ethical indifference or wrongdoing, this paper focuses on whether it is possible to commit epistemic injustices against nonhumans. In particular, this paper argues that humans can commit fourth-order epistemic exclusion, testimonial injustice, and testimonial smothering against nonhumans. (shrink)

Nietzsche believes that we do not know our own actions, nor their real motives. This belief, however, is but a consequence of his assuming a quite general skepticism about introspection. The main aim of this paper is to offer a reading of this last view, which I shall call the Inner Opacity (IO) view. In the first part of the paper I show that a strong motivation behind IO lies in Nietzsche’s claim that self-knowledge exploits the same set of (...) cognitive capacities as well as the same folk-psychological framework involved in outward-directed mind-reading. In the second part I turn to Nietzsche’s view of agency and argue that he sees a fundamental discrepancy between the conscious attitudes we have introspective access to, on the one hand, and the subpersonal processes and states occurring at the unconscious level of the drives, on the other hand. (shrink)