Questions about the transparency of evidence are central to debates between factive and non-factive versions of mentalism about evidence. If all evidence is transparent, then factive mentalism is false, since no factive mental states are transparent. However, Timothy Williamson has argued that transparency is a myth and that no conditions are transparent except trivial ones. This paper responds by drawing a distinction between doxastic and epistemic notions of transparency. Williamson's argument may show that no conditions are (...) doxastically transparent, but it fails to show that no conditions are epistemically transparent. Moreover, this reinstates the argument from the transparency of evidence against factive mentalism. (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.

In recent work, Stephen John (2018, 2019) has deepened the social epistemological perspective on expert testimony by arguing that science communication often operates at the institutional level, and that at that level sincerity, transparency, and honesty are not necessarily epistemic virtues. In this paper I consider his arguments in the context of science journalism, a key constituent of the science communication ecosystem. I argue that this context reveals both the weakness of his arguments and a need for further (...) analysis of how non-experts learn from experts. (shrink)

Can AI developers be held epistemically responsible for the processing of their AI systems when these systems are epistemically opaque? And can explainable AI (XAI) provide public justificatory reasons for opaque AI systems’ outputs? Koskinen (2024) gives negative answers to both questions. Here, I respond to her and argue for affirmative answers. More generally, I suggest that when considering people’s uncertainty about the factors causally determining an opaque AI’s output, it might be worth keeping in mind that a degree of (...) uncertainty about conclusions is inevitable even in entirely human-based empirical science because in induction there’s always a risk of getting it wrong. Keeping this in mind may help appreciate that requiring full transparency from AI systems before epistemically trusting their outputs might be unusually (and potentially overly) demanding. (shrink)

In her BBC Reith Lectures on Trust, Onora O’Neill offers a short, but biting, criticism of transparency. People think that trust and transparency go together but in reality, says O'Neill, they are deeply opposed. Transparency forces people to conceal their actual reasons for action and invent different ones for public consumption. Transparency forces deception. I work out the details of her argument and worsen her conclusion. I focus on public transparency – that is, transparency (...) to the public over expert domains. I offer two versions of the criticism. First, the epistemic intrusion argument: The drive to transparency forces experts to explain their reasoning to non-experts. But expert reasons are, by their nature, often inaccessible to non-experts. So the demand for transparency can pressure experts to act only in those ways for which they can offer public justification. Second, the intimate reasons argument: In many cases of practical deliberation, the relevant reasons are intimate to a community and not easily explicable to those who lack a particular shared background. The demand for transparency, then, pressures community members to abandon the special understanding and sensitivity that arises from their particular experiences. Transparency, it turns out, is a form of surveillance. By forcing reasoning into the explicit and public sphere, transparency roots out corruption — but it also inhibits the full application of expert skill, sensitivity, and subtle shared understandings. The difficulty here arises from the basic fact that human knowledge vastly outstrips any individual’s capacities. We all depend on experts, which makes us vulnerable to their biases and corruption. But if we try to wholly secure our trust — if we leash groups of experts to pursuing only the goals and taking only the actions that can be justified to the non-expert public — then we will undermine their expertise. We need both trust and transparency, but they are in essential tension. This is a deep practical dilemma; it admits of no neat resolution, but only painful compromise. (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 (...) class='Hi'>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)

Anti-individualists hold that having a thought with a certain intentional content is a relational rather than an intrinsic property of the subject. Some anti-individualists also hold that thought-content serves to explain the subject’s cognitive perspective. Since there seems to be a tension between these two views, much discussed in the philosophical literature, attempts have been made to resolve it. In an attempt to reconcile these views, and in relation to perception-based demonstrative thoughts, Stalnaker (Our knowledge of the internal world, Oxford (...) University Press, Oxford, 2008) argues that an anti-individualist account of the facts that determine thought-content can be reconciled with a suitably qualified version of a principle of epistemic transparency. Acknowledging this, and in agreement with the view that thought-content should serve to explain the subject’s cognitive perspective, I argue that, his intentions notwithstanding, this view of transparency of thought-contents does not serve to explain the subject’s cognitive perspective on Stalnaker’s own terms and that the intricacies involved in his argumentation for saving his anti-individualist project are indirectly supportive of an individualist account of the subject’s cognitive perspective. In so doing, I leave intact some of his key claims that are plausible in their own right. (shrink)

Abstract This chapter is interested in the epistemology of algorithms. As I intend to approach the topic, this is an issue about epistemic justification. Current approaches to justification emphasize the transparency of algorithms, which entails elucidating their internal mechanisms –such as functions and variables– and demonstrating how (or that) these produce outputs. Thus, the mode of justification through transparency is contingent on what can be shown about the algorithm and, in this sense, is internal to the algorithm. (...) In contrast, I advocate for an externalist epistemology of algorithms that I term computational reliabilism (CR). While I have previously introduced and examined CR in the field of computer simulations ([42, 53, 4]), this chapter extends this reliabilist epistemology to encompass a broader spectrum of algorithms utilized in various scientific disciplines, with a particular emphasis on machine learning applications. At its core, CR posits that an algorithm’s output is justified if it is produced by a reliable algorithm. A reliable algorithm is one that has been specified, coded, used, and maintained utilizing reliability indicators. These reliability indicators stem from formal methods, algorithmic metrics, expert competencies, cultures of research, and other scientific endeavors. The primary aim of this chapter is to delineate the foundations of CR, explicate its operational mechanisms, and outline its potential as an externalist epistemology of algorithms. (shrink)

This paper controverts the ability of intentionalism about perception to account for unique epistemic significance of phenomenal consciousness. More specifically, the intentionalist cannot explain the latter without denying two well-founded claims: the transparency of experience, and the possibility of unconscious perception. If they are true, intentionality of perception entails that phenomenal consciousness has no special epistemic role to play. Although some intentionalists are ready to bite this bullet, by doing so they effectively undermine one of the standard (...) motivations of their view, i.e. the claim that perceptual experiences justify beliefs. Consequently, whatever reason might there be to think that phenomenal consciousness has unique epistemic import, it is also a reason to reject intentionalism. I recommend replacing the latter with an unorthodox formulation of relationalism about perception. (shrink)

Belief has a special connection to truth, a connection not shared by mental states like imagination. One way of capturing this connection is by the claim that belief aims at truth. Normativists argue that we should understand this claim as a normative claim about belief – beliefs ought to be true. A second important connection between belief and truth is revealed by the transparency of belief, i.e. the fact that, when I deliberate about what to believe, I can settle (...) this deliberation only by appeal to considerations I take to show p to be true. It is natural to think that there is a connection between these two features of belief, that the fact that believing for non-evidential considerations would be irrational can help to explain why it is impossible, and Shah and Velleman make exactly this argument. However, as I shall argue, we cannot explain transparency on the basis of a normative requirement on belief. For this explanation to work non-evidential considerations would have to fail to be reasons for belief, and we would have to be able to explain why we are unable to form beliefs on the basis of non-evidential considerations by appealing to the fact that they fail to be reasons for belief. However, while it is plausible that non-evidential considerations are not in fact reasons for belief, the explanatory picture is the other way around. Such considerations only fail to be reasons for belief because we are unable to form beliefs on their basis. (shrink)

I explore the extent to which the epistemic state of understanding is transparent to the one who understands. Against several contemporary epistemologists, I argue that it is not transparent in the way that many have claimed, drawing on results from developmental psychology, animal cognition, and other fields.

Some physicians, in their care of patients at risk of misusing opioids, use machine learning (ML)-based prediction drug monitoring programmes (PDMPs) to guide their decision making in the prescription of opioids. This can cause a conflict: a PDMP Score can indicate a patient is at a high risk of opioid abuse while a patient expressly reports oppositely. The prescriber is then left to balance the credibility and trust of the patient with the PDMP Score. Pozzi1 argues that a prescriber who (...) downgrades the credibility of a patient’s testimony based on a low PDMP Score is epistemically and morally unjustified and contributes to a form of testimonial injustice. This results in patients being silenced, excluded from decision-making processes and subjected to structural injustices. Additionally, the use of ML systems in medical practices raises concerns about perpetuating existing inequalities, overestimating their capabilities and displacing human authority. However, almost the very same critiques apply to human-based systems. Formalisation, ML systems included, should instead be viewed positively,2 and precisely as a powerful means to begin eroding these and other problems in ethically sensitive domains. In this case, the epistemic virtues of formalisation include promoting transparency, consistency and replicability in decision making. Rigorous ML systems can also help ensure that models …. (shrink)

When are you in a position to rely on p in practical reasoning? Existing accounts say that you must know that p, or be in a position to know that p, or be justified in believing that p, or be in a position to justifiably believe it, and so on. This paper argues that all of these proposals face important problems, which I call the Problems of Negative Bootstrapping and of Level Confusions. I offer a diagnosis of these problems, and (...) I argue that an adequate epistemic norm must be transparent in the following sense: According to the correct epistemic norm, a consideration counts in favor of (or against) relying on p in practical reasoning iff, and to the extent that, this consideration also counts in favor of (or against) p being true. I introduce a candidate epistemic norm that satisfies this condition. According to this norm, one should rely on p in practical reasoning only if it must be that p. If we adopt a non-factualist account of “must”, this amounts to a novel and attractive proposal, a proposal that satisfies the transparency condition. (shrink)

This paper critically evaluates Amie Thomasson’s (2003; 2005; 2006) view of the conscious mind and the interpretation of Husserl’s phenomenological reduction that it adopts. In Thomasson’s view, the phenomenological method is not an introspectionist method, but rather a “transparent” or “extrospectionist” method for acquiring epistemically privileged self-knowledge. I argue that Thomasson’s reading of Husserl’s phenomenological reduction is correct. But the view of consciousness that she pairs with it—a view of consciousness as “transparent” in the sense that first-order, world-oriented experience is (...) in no way given to itself—is not compatible with it. Rather, Thomasson’s view is, from a Husserlian vantage point, self-undermining in the same way that any genuinely skeptical view is self-undermining: it undermines the conditions of its own possibility. This is one of the motives Husserl has for developing a same-order view of self-consciousness as the complement to his transparent method for self-knowledge acquisition. (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)

In this paper, I will examine the notion of an epistemic dilemma, its characterizations in the literature, and the different intuitions prompted by it. I will illustrate that the notion of an epistemic dilemma is expected to capture various phenomena that are not easily unified with one concept: while some aspects of these phenomena are more about the agent in a certain situation, other aspects seem to be more about the situation as such. As a consequence, incompatible intuitions (...) emerge concerning the transparency of epistemic dilemmas as well as regarding the role that doxastic suspension plays in resolving cases of epistemic dilemma. I suggest to distinguish between the mental state of agents who find themselves in an epistemic dilemma and the normative situation that gives rise to a dilemma. I will refer to the agent’s mental state as epistemic conflict and will reserve the term epistemic dilemma for evidential situations in which epistemic principles either recommend incompatible doxastic responses or render all options impermissible. The concept of epistemic conflict not only captures the mental state of agents who find themselves in a genuine epistemic dilemma but also applies to agents who face difficult epistemic choices that they cannot resolve without substantial cognitive (and often pragmatic) effort, for example, via doxastic suspension. (shrink)

My interest lies in offering a phenomenological perspective on how noise is experienced, with particular attention to what may be common to different sorts of noise phenomena. As a counterpoint to the notion that noise is an empty or constructed notion, I argue for two desiderata of a phenomenological account of noise; accommodating a plurality of noise experiences, on the one hand, and clarifying their specific phenomenal character, on the other. I then pursue these desiderata by turning to an examination (...) of some contemporary views of perception that have implications for how the phenomenal character of perceptual noise in particular is to be understood; an epistemic misfire view and a sensory misfire view. After clarifying each and its appeal, I convey concerns about the one and the other. I propose a third alternative for further exploration - a perceptual disjoint view - and point to how it ought to explored. On the premise that there is something like a unity of consciousness or experience, I lay out the idea that there may then be many forms of 'disunities' of experience. From an analysis of the latter, I suggest, one may account for many different types of experiences of noise, though with a common ‘phenomenal’ thread running through them. (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)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked (...) in accounts of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (shrink)

. 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)

Perceptions guide our actions and provide us with evidence of the world around us. Illusions and hallucinations can mislead us: they may prompt as to act in ways that do not mesh with the world around us and they may lead us to form false beliefs about that world. The capacity view provides an account of evidence that does justice to these two facts. It shows in virtue of what illusions and hallucinations mislead us and prompt us to act. Moreover, (...) it shows in virtue of what we are in a better epistemic position when we perceive than when we hallucination. In this paper, I develop the capacity view, that is, the view that perceptual experience has epistemic force in virtue of the epistemic and metaphysical primacy of the perceptual capacities employed in perception. By grounding the epistemic force of experience in facts about the metaphysical structure of experience, the capacity view is not only an externalist view, but moreover a naturalistic view of the epistemology of perceptual experience. So it is an externalist and naturalistic alternative to reliabilism. I discuss the repercussions of this view for the justification of beliefs and the epistemic transparency of mental states, as well as, familiar problem cases. (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)

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)

ABSTRACT In Consciousness and Fundamental Reality, Philip Goff argues that the case against physicalist views of consciousness turns on ‘Phenomenal Transparency’, roughly the thesis that phenomenal concepts reveal the essential nature of phenomenal properties. This paper considers the argument that Goff offers for Phenomenal Transparency. The key premise is that our introspective judgments about current conscious experience are ‘Super Justified’, in that these judgments enjoy an epistemic status comparable to that of simple mathematical judgments, and a better (...) epistemic status than run of the mill perceptual judgments. After presenting the key ideas in the ‘Super Justification Argument’, I distinguish two Super Justification theses, which vary according to the kind of introspective judgments that they take to be Super Justified. I argue that Goff’s case requires ‘Strong Super Justification’, according to which a wide range of introspective judgments about conscious experience are Super Justified. Unfortunately, it turns out that Strong Super Justification is implausible and not well-supported by examples. In contrast, a weaker Super Justification thesis does not require anything like Phenomenal Transparency and, indeed, can be explained by physicalistic accounts of phenomenal concepts. (shrink)

We might worry that our seamless reliance on AI systems makes us prone to adopting the strange errors that these systems commit. One proposed solution is to design AI systems so that they are not phenomenally transparent to their users. This stops cognitive extension and the automatic uptake of errors. Although we acknowledge that some aspects of AI extension are concerning, we can address these concerns without discouraging transparent employment altogether. First, we believe that the potential danger should be put (...) into perspective – many unreliable technologies are unlikely to be used transparently precisely because they are unreliable. Second, an agent who transparently employs a resource may also reflect (opaquely) on its reliability. Finally, agents can rely on a process transparently and be yanked out of their transparent use when it turns unreliable. When an agent is responsive to the reliability of their process in this way, they have epistemically integrated it, and the beliefs they form with it are formed responsibly. This prevents the agent from automatically incorporating problematic beliefs. Responsible (and transparent) use of AI resources – and consequently responsible AI extension – is hence possible. We end the paper with several design and policy recommendations that encourage epistemic integration of AI-involving belief-forming processes. (shrink)

Abstract In a context of human demographic, technological and economic pressure on natural systems, we face some demanding challenges. We must decide 1) whether to “preserve” nature for its own sake or to “conserve” nature because nature is essentially a reservoir of goods that are functional to humanity’s wellbeing; 2) to choose ways of life that respect the biodiversity and evolutionary potential of the planet; and, to allow all this to come to fruition, 3) to clearly define the role of (...) scientific expertise in a democratic society, recognizing the importance of biospheric equilibrium. In fact, in socio-scientific controversies, which are characterized by complex linkages between some life and environmental sciences objects and economic, political and ethical issues, a posture of transparent, impartial commitment is appearing, more and more, as a deontological necessity. (shrink)

Some moral value is transparent just in case an agent with average mental capacities can feasibly come to know whether some entity does, or does not, possess that value. In this paper, I consider whether legitimacy—that is, the property of exercises of political power to be permissible—is transparent. Implicit in much theorising about legitimacy is the idea that it is. I will offer two counter-arguments. First, injustice can defeat legitimacy, and injustice can be intransparent. Second, legitimacy can play a critical (...) function in our practical thought, which sometimes requires intransparency. (shrink)

The sentences ‘p but I don’t believe p’ (omissive form) and ‘p but I believe that not-p’ (comissive form) are typical examples of Moore’s paradox. When an agent (sincerely) asserts such sentences under normal circumstances, we consider his statements absurd. The Simple Solution (Moore, Heal, Wolgast, Kriegel, et al.) finds the source of absurdity for such statements in a certain formal contradiction (some kind of like ‘p & not-p’), the presence of which is lexically disguised. This solution is facing criticism (...) since it is obvious that the denial of the contradiction allegedly hidden in Moore’s paradox will not become an expression of tautology for us. Hintikka offers another solution to Moore’s paradox. In his view, the source of absurdity is the practical inconceivability of the situation, in which the agent would be able to hold mutually incompatible (inconsistent) beliefs. The sentences ‘p but I don’t believe that p’ and ‘p but I believe that not-p’ sound absurd because they express high-ordered beliefs that no rational agent can hold. A belief expressed in the sentence ‘he believes that p’, in order to be available to the agent, must be compatible with the truth of everything the agent believes. The problem with Hintikka’s solution is that it relies on an epistemic principle that does not correspond to our general intuitions about the notion of belief. According to this principle, there must be a close connection between the sentence ‘p but I don’t believe that p’ and the sentence ‘I believe that is the case is that p but I don’t believe that p’. However, it is not difficult to imagine the context for situations when the agent asserts the sentence ‘p but I don’t believe that p’ when s/he believes that p, but in parallel does not hold any high-ordered belief about his/her belief in p. For example, the agent does not recognize oneself in a photograph after a hard plastic surgery, and when one asks him ‘who is this?’ it would not be absurd for him/her to accept the following description of his/her beliefs ‘I believe that {I am me} but I don’t believe that I believe that {I am me}’. Wittgenstein provides an alternative solution based on a descriptive analysis of the grammar of verbs we use to express, attribute, and understand each other’s psychological states. In his view, the everyday practice of using the verb ‘believe’ demonstrates a characteristic asymmetry in the semantic and logical properties of the usage of this verb in the first person. The expression ‘I believe falsely’ has no real meaning since no one can meaningfully say the sentence ‘Now I believe falsely that p’ on their own behalf. Therefore, the genuine source of absurdity is associated with situations of self-attribution of false belief by the agent. Despite its originality, Wittgenstein’s solution faces objections. For example, in a certain context, it would not be absurd to assert the sentence ‘There are no beliefs, but I don’t believe in it’, unlike the sentence ‘There are no beliefs and I believe that it is so’. The solution proposed by Wittgenstein does not allow us to correct the situation since one could assert quite reasonably and without any absurdity a sentence like ‘In fact, there are no beliefs and now I falsely believe that it is so’. Based on Evans’ principle of epistemic transparency, some researchers (Atlas, Chan, Kwon, et al.) offer another strategy for solving Moore’s paradox, in which peculiar attention is paid to the dependence of understanding and evaluating the meaning of the sentences ‘p but I do not believe that p’ and ‘p but I believe that not-p’ from the immediate context of their usage. The source of absurdity should be looked for in the established practice of the self-referential use of the pronoun ‘I’. In the researchers’ view, Moore’s paradox arises only in the context of situations where the agent asserting such sentences is conscious speaking about oneself. Therefore, there is an obvious structural analogy between the sentences of the Liar family (‘This very sentence is false’, ‘Now I am lying’, etc.) and Moore’s paradox (‘p but I don’t believe that p’, ‘p but I believe that not-p’) – self-reference is constitutive for both families of paradoxical statements. (shrink)

What is it for two people to think of an object, natural kind or other entity under the same mode of presentation (MOP)? This has seemed a particularly difficult question for advocates of the Mental Files approach, the Language of Thought, or other ‘atomistic’ theories. In this paper I propose a simple answer. I first argue that, by parallel with the synchronic intrapersonal case, the sharing of a MOP should involve a certain kind of epistemic transparency between the (...) token thoughts of the two thinkers. I then explain how shared words help bring about this transparency. Finally, I show how this account can be extended for thoughts expressed using demonstratives or indexicals. (shrink)

There is much to be said for a diachronic or interpersonal individuation of singular modes of presentation (MOPs) in terms of a criterion of epistemic transparency between thought tokens. This way of individuating MOPs has been discussed recently within the mental files framework, though the issues discussed here arise for all theories that individuate MOPs in terms of relations among tokens. All such theories face objections concerning apparent failures of the transitivity of the ‘same MOP’ relation. For mental (...) files, these transitivity failures most obviously occur because mental files can merge or undergo fission. In this paper I argue that this problem is easily resolved once mental files are properly construed as continuants, whose metaphysics is analogous to that of persons or physical objects. All continuants can undergo fission or fusion, leading to similar transitivity problems, but there are well-established theories of persistence that accommodate this. I suggest that, in particular, the stage theory best suits the purposes of a continuant theory of MOPs. (shrink)

Traditional descriptivism and Kripkean causalism are standardly interpreted as rival theories on a single topic. I argue that there is no such shared topic, i.e. that there is no question that they can be interpreted as giving rival answers to. The only way to make sense of the commitment to epistemic transparency that characterizes traditional descriptivism is to interpret Russell and Frege as proposing rival accounts of how to characterize a subject’s beliefs about what names refer to. My (...) argument relies on a development of the distinction between speaker’s reference and semantic reference. (shrink)

While the idea of philosophy as conceptual analysis has attracted many adherents and undergone a number of variations, in general it suffers from an authority problem with two dimensions. First, it is unclear why the analysis of a concept should have objective authority: why explicating what we mean should express how things are. Second, conceptual analysis seems to lack intersubjective authority: why philosophical analysis should apply to more than a parochial group of individuals. I argue that Hegel’s conception of social (...) ontology, focused on his concept of “ethical life” (Sittlichkeit), helps to explain how concepts (and their explication) have both objective and intersubjective authority in the social domain. Hegel claims that modern institutions are the product of self-conscious purposes, so that they are conceptually constituted. Concepts do not just represent these objects and so depend on a contingent relation to them. As many contemporary social ontologists agree, this means that our concepts of these institutions are uniquely epistemically “transparent.” They have objective authority. Concepts have intersubjective authority in the modern world as well, according to Hegel. However, I show that this feature of Hegel’s account does not rely on the solution to a philosophical problem. Rather, since the concepts of modern ethical life are “essentially contested,” their content depends on the practical and political agreement of modern subjects. This means that concepts can only have objective authority if some prior intersubjective agreement has been reached. The role of philosophy as conceptual analysis is thus importantly dependent on political developments. (shrink)

Roughly, empirical AI alignment research (AIA) is an area of AI research which investigates empirically how to design AI systems in line with human goals. This paper examines the role of non-epistemic values in AIA. It argues that: (1) Sciences differ in the degree to which values influence them. (2) AIA is strongly value-laden. (3) This influence of values is managed inappropriately and thus threatens AIA’s epistemic integrity and ethical beneficence. (4) AIA should strive to achieve value (...) class='Hi'>transparency, critical scrutiny from inside and outside the discipline – involving the public –, and to empower actors without strong commercial interests. (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)

Contemporary phenomenal externalists are motivated to a large extent by the transparency of experience and by the related doctrine of representationalism. On their own, however, transparency and representationalism do not suffice to establish externalism. Hence we should hesitate to dismiss phenomenal internalism, a view shared by many generations of competent philosophers. Rather, we should keep both our options open, internalism and externalism. It is hard, however, to see how to keep open the internalist option, for although transparency (...) and representationalism have not yet definitively established externalism, they have indeed made it quite intuitive. Internalism, by comparison, comes across at first sight as antiquated and ridden with difficulties. This is why I propose the Stained Glass model of consciousness. I do so with the following two aims: first, to make internalism intuitive in the age of transparency, and second, to show how to resist the many recent anti-internalist arguments. In particular, I argue that phenomenal internalism need not be epistemically worrisome, that it is compatible at once with transparency, representationalism, and content externalism, and that although it requires an error theory, this error theory is a harmless one. (shrink)

You can come to know that you believe that p partly by reflecting on whether p and then judging that p. Call this procedure “the transparency method for belief.” How exactly does the transparency method generate known self-attributions of belief? To answer that question, we cannot interpret the transparency method as involving a transition between the contents p and I believe that p. It is hard to see how some such transition could be warranted. Instead, in this (...) context, one mental action is both a judgment that p and a self-attribution of a belief that p. The notion of embedded mental action is introduced here to explain how this can be so and to provide a full epistemic explanation of the transparency method. That explanation makes sense of first-person authority and immediacy in transparent self-knowledge. In generalized form, it gives sufficient conditions on an attitude’s being known transparently. (shrink)

There is a growing consensus among philosophers of science that core parts of the scientific process involve non-epistemic values. This undermines the traditional foundation for public trust in science. In this article I consider two proposals for justifying public trust in value-laden science. According to the first, scientists can promote trust by being transparent about their value choices. On the second, trust requires that the values of a scientist align with the values of an individual member of the public. (...) I argue that neither of these proposals work and suggest an alternative that does better. When scientists must appeal to values in the course of their research, they should appeal to democratic values: the values of the public or its representatives. (shrink)

The aim of this article is to provide an account of introspective knowledge concerning visual experiences that is in accordance with the idea of transparent introspection. According to transparent introspection, a person gains knowledge of her own current mental state M solely by paying attention to those aspects of the external world which M is about. In my view, transparent introspection is a promising alternative to inner sense theories. However, it raises the fundamental question why a person who pays attention (...) to something extra-mental should be epistemically justified in holding a belief about something intra-mental. In his Naturalizing the Mind, Fred Dretske solves this problem by conceiving of introspection concerning visual experiences as an inference based on a connecting belief. Although Dretske's account proves defective upon closer inspection, its essence can be salvaged by looking upon introspection as being a game of make-believe. (shrink)

Human-centered explainable AI (HCXAI) advocates for the integration of social aspects into AI explanations. Central to the HCXAI discourse is the Social Transparency (ST) framework, which aims to make the socio-organizational context of AI systems accessible to their users. In this work, we suggest extending the ST framework to address the risks of social misattributions in Large Language Models (LLMs), particularly in sensitive areas like mental health. In fact LLMs, which are remarkably capable of simulating roles and personas, may (...) lead to mismatches between designers' intentions and users' perceptions of social attributes, risking to promote emotional manipulation and dangerous behaviors, cases of epistemic injustice, and unwarranted trust. To address these issues, we propose enhancing the ST framework with a fifth 'W-question' to clarify the specific social attributions assigned to LLMs by its designers and users. This addition aims to bridge the gap between LLM capabilities and user perceptions, promoting the ethically responsible development and use of LLM-based technology. (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)

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 paper presents a new philosophical theory of blurred vision according to which visual experiences have two types of content: exteroceptive content, characterizing external entities, and interoceptive content, characterizing the state of the visual system. In particular, it is claimed that blurriness-related phenomenology interoceptively presents acuity of vision in relation to eye focus. The proposed theory is consistent with the representationalist thesis that phenomenal character supervenes on representational content and with the strong transparency thesis formulated in terms of mind-independentness. (...) Furthermore, the interoceptive approach is free from controversial assumptions adopted by other philosophical theories of blurred experiences and is able to account for the epistemic and motivational role of visual blur, i.e. that blurred experiences provide a prima facie justification for beliefs regarding our vision and motivate actions directed toward our eyes. (shrink)

I am aware of the tree and its leaves, but am I aware of my awareness of these things? When I try to introspect my awareness, I just find myself attending to objects and their properties. This observation is known as the ‘transparency of experience’. On the other hand, I seem to directly know that I am aware. Given the first observation, it is not clear how I know that I am aware. Fred Dretske thought that the problem was (...) so acute that he issued the challenge of answering ‘How do you know that you are not a zombie?’ I propose that a view found in the Advaita Vedanta, that awareness is self luminous, reconciles these two observations. I understand self-luminosity as the thesis that: (1) I am implicitly aware of my awareness and (2) I am phenomenally aware of a distinct phenomenal character of my awareness. In support of the first claim, that I apparently only attend to objects in the world when introspecting perceptual experience, suggests that I do not know my awareness explicitly, but rather that I must know it implicitly. In support of the second claim, I argue that the mere fact that I am perceptually conscious is not sufficient to allow me to know that I am perceptually conscious. In particular, the qualities I am perceptually aware of do not tell me that I aware of them, rather they just seem to be properties of objects. I also assess whether strategies for responding to Cartesian sceptical scenarios can be employed against Dretske’s consciousness scepticism. I argue that these strategies either fail to distinguish me from a zombie or they do not adequately describe my epistemic situation. By contrast to other accounts, if awareness has its own distinct phenomenal character, then it cannot be considered to be a prima facie property of the world, hence the self-luminosity of awareness provides a plausible account of how I know that I’m not a zombie. (shrink)

Marine ecosystems are under increasing pressure from human activity, yet successful management relies on knowledge. The evidence-based policy (EBP) approach has been promoted on the grounds that it provides greater transparency and consistency by relying on ‘high quality’ information. However, EBP also creates epistemic responsibilities. Decision-making where limited or no empirical evidence exists, such as is often the case in marine systems, creates epistemic obligations for new information acquisition. We argue that philosophical approaches can inform the science-policy (...) interface. Using marine biosecurity examples, we specifically examine the epistemic challenges in the acquisition and acceptance of evidence to inform policy, discussing epistemic due care and biases in consideration of evidence. (shrink)

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds (...) in philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision-making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub-kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making. (shrink)

We introduce an expected-value theory of linguistic modality that makes reference to expected utility and a likelihood-based confirmation measure for deontics and epistemics, respectively. The account is a probabilistic semantics for deontics and epistemics, yet it proposes that deontics and epistemics share a common core modal semantics, as in traditional possible-worlds analysis of modality. We argue that this account is not only theoretically advantageous, but also has far-reaching empirical consequences. In particular, we predict modal versions of reasoning fallacies from the (...) heuristics and biases literature. Additionally, we derive the modal semantics in an entirely transparent manner, as it is based on the compositional semantics of Korean modal expressions that are morphosyntactically decomposed into a conditional and an evaluative predicate. (shrink)

What we traditionally call ‘conscious thought’ actually is a subpersonal process, and only rarely a form of mental action. The paradigmatic, standard form of conscious thought is non-agentive, because it lacks veto-control and involves an unnoticed loss of epistemic agency and goal-directed causal self-determination at the level of mental content. Conceptually, it must be described as an unintentional form of inner behaviour. Empirical research shows that we are not mentally autonomous subjects for about two thirds of our conscious lifetime, (...) because while conscious cognition is unfolding, it often cannot be inhibited, suspended, or terminated. The instantiation of a stable first- person perspective as well as of certain necessary conditions of personhood turn out to be rare, graded, and dynamically variable properties of human beings. I argue that individual representational events only become part of a personal-level process by being functionally integrated into a specific form of transparent conscious self-representation, the ‘epistemic agent model’. The EAM may be the true origin of our consciously experienced firstperson perspective. (shrink)

Everyday (mis)uses of deepfakes define prevailing conceptualizations of what they are and the moral stakes in their deployment. But one complication in understanding deepfakes is that they are not photographic yet nonetheless manipulate lens-based recordings with the intent of mimicking photographs. The harmfulness of deepfakes, moreover, significantly depends on their potential to be mistaken for photographs and on the belief that photographs capture actual events, a tenet known as the transparency thesis, which scholars have somewhat ironically attacked by citing (...) digital imaging techniques as counterexamples. Combining these positions, this paper sets out two core points: (1) that conceptions about the nature of photography introduce imperatives about its uses; and (2) that popular cultural understandings of photography imply normative ideas that infuse our encounters with deepfakes. Within this, I further raise the question of what moral ground deepfakes occupy that allows them to have such a potentially devastating effect. I show that answering this question involves reinstating the notion that photographs are popularly conceived of as transparent. The rejoinder to this argument, however, is that to take the sting out of deepfakes we must, once again, become skeptical of the veracity of all images, including photoreal ones. This kind of critical mindedness was warranted before the invention of photography for both pictorial imprints and written accounts from various media sources. Given this, along with the fact that photographic trickery is nothing new, deepfakes need not push us into a post-truth epistemic abyss, for they imply a decidedly old turn. (shrink)

The main aim of this paper is to clarify the relation between epistemic feel- ings, mental action, and self-ascription. Acting mentally and/or thinking about one’s mental states are two possible outcomes of epistemic or metacognitive feelings. Our men- tal actions are often guided by our E-feelings, such as when we check what we just saw based on a feeling of visual uncertainty; but thought about our own perceptual states and capacities can also be triggered by the same E-feelings. (...) The first section of the pa- per presents Dokic’s argument for the insufficiency of the “ascent routine” to account for non-transparent cases of self-ascription, as well as his account of E-feelings. The second section then presents a two-level model of metacognition that builds on Dokic’s account and my own view of the issue. The two-level model links E-feelings to a min- dreading capacity in order to account for non-transparent self-ascriptions. Finally, the third section develops a deeper characterization of the relation among E-feelings, mental action, and self-ascription of mental states based on epistemic rules. In the context of self-knowledge, these remarks suggest the existence of means of forming self-ascriptions other than the ascent routine. (shrink)

This paper calls for a re-appraisal of McGee's analysis of the semantics, logic and probabilities of indicative conditionals presented in his 1989 paper Conditional probabilities and compounds of conditionals. The probabilistic measures introduced by McGee are given a new axiomatisation built on the principle that the antecedent of a conditional is probabilistically independent of the conditional and a more transparent method of constructing such measures is provided. McGee's Dutch book argument is restructured to more clearly reveal that it introduces a (...) novel contribution to the epistemology of semantic indeterminacy, and shows that its more controversial implications are unavoidable if we want to maintain the Ramsey Test along with the standard laws of probability. Importantly, it is shown that the counterexamples that have been levelled at McGee's analysis|generating a rather wide consensus that it yields `unintuitive' or `wrong' probabilities for compounds |fail to strike at their intended target; for to honour the intuitions of the counterexamples one must either give up the Ramsey Test or the standard laws of probability. It will be argued that we need to give up neither if we take the counterexamples as further evidence that the indicative conditional sometimes allows for a non-epistemic `causal' interpretation alongside its usual epistemic interpretation. (shrink)