Conventional accounts of epistemic opacity, particularly those that stem from the definitive work of Paul Humphreys, typically point to limitations on the part of epistemic agents to account for the distinct ways in which systems, such as computational methods and devices, are opaque. They point, for example, to the lack of technical skill on the part of an agent, the failure to meet standards of best practice, or even the nature of an agent as reasons why epistemically (...) relevant elements of a process may be inaccessible. In this paper I argue that there are certain instances of epistemic opacity— particularly in computational methods such a computer simulations and machine learning processes—that do not arise from, are not responsive to, and are therefore not explained by the epistemic limitations of an agent. I call these instances agent-neutral and agent-independent instances of epistemic opacity respectively. As a result, I also argue that conventional accounts of epistemic opacity offer a limited understanding of the full spectrum of kinds and sources of epistemic opacity, particularly of the kind found in computational methods. In particular, as I will show below, the limitations of these accounts are reflected in the way they fail to provide satisfactory explanations when faced with certain instances of opacity. (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)

This paper takes stock of all the various factors that cause the design-time opacity of autonomous systems behaviour. The factors include embodiment effects, design-time knowledge gap, human factors, emergent behaviour and tacit knowledge. This situation is contrasted with the usual representation of moral dilemmas that assume perfect information. Since perfect information is not achievable, the traditional moral dilemma representations are not valid and the whole problem of ethical autonomous systems design proves to be way more empirical than previously understood.

Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations :483–496, 2009; Morrison in Philos Stud 143:33–57, 2009), the nature of computer data Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of (...) computer simulations :277–292, 2008; Durán in Int Stud Philos Sci 31:27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of successful implementations, and the role of expert knowledge in simulations. (shrink)

The Fukushima nuclear accident from 2011 provided an occasion for the public display of radiation maps generated using decision-support systems for nuclear emergency management. Such systems rely on computer models for simulating the atmospheric dispersion of radioactive materials and estimating potential doses in the event of a radioactive release from a nuclear reactor. In Germany, as in Japan, such systems are part of the national emergency response apparatus and, in case of accidents, they can be used by emergency task forces (...) for planning radioprotection countermeasures. In this context, the paper addresses the epistemology of dose projections by critically analyzing some of the sources of epistemic opacity and non-knowledge affecting them, and the different methods and practices used by German radioprotection experts to improve their trustworthiness and reliability. It will be argued that dose projections are part of an entire radioprotection regime or assemblage built around the belief that the effects of nuclear accidents can be effectively mitigated thanks to the simulation technologies underlying different protocols and practices of nuclear preparedness. And, as the Fukushima experience showed, some of these expectations will not be met in real emergencies due to the inherent uncertainties entailed by the use of dose projections when planning protective countermeasures. (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)

In 2017 AlphaZero, a neural network-based chess engine shook the chess world by convincingly beating Stockfish, the highest-rated chess engine. In this paper, I describe the technical differences between the two chess engines and based on that, I discuss the impact of the modeling choices on the respective epistemic opacities. I argue that the success of AlphaZero’s approach with neural networks and reinforcement learning is counterbalanced by an increase in the epistemic opacity of the resulting model.

In Hawthorne and Magidor 2009, we presented an argument against Stalnaker’s meta-semantic framework. In this paper we address two critical responses to our paper: Stalnaker 2009, and Almotahari and Glick 2010. Sections 1–4 are devoted to addressing Stalnaker’s response and sections 5–8 to addressing Almotahari and Glick’s. We pay special attention (Sect. 2) to an interesting argument that Stalnaker offers to bolster the transparency of presupposition (an argument that, if successful, could also form the basis of a defence of the (...) KK principle). (shrink)

With regard to organ donation, Germany is an ‘opt-in’ country, which requires explicit consent from donors. The relatives are either asked to decide on behalf of the donors’ preferences, if these are unknown or if the potential donor has explicitly transferred the decision to them. At the core of this policy lies the sociocultural and moral premise of a rational, autonomous individual, whose rights require legal protection in order to guarantee a voluntary decision. In concrete transplantation practices, the family plays (...) an even more important role. Potential donors and their families decide while being embedded in relations, a point which does still not gain full recognition. This particular discrepancy between policy and practice creates conflicts, which remain taboos of academic inquiry and public discourse. Our analysis shows a plurality of the family’s role in the transplantation process, which reveals an inner tension of the organ donation system. This tension provokes epistemic opacity on the one hand and different collective strategies as responses to discursive exclusion on the other. In future deliberations about organ donation, it is important to create spaces for open discussion, but also practices of communicative engagement, which take care of the needs and emotions attached to taboos. (shrink)

Over the course of the twentieth century, hydraulic engineering has come to rely primarily on the use of computational models. Disco and van den Ende hint towards the reasons for widespread adoption of computational models by pointing out that such models fulfill a crucial role as management tools in Dutch water management, and meet a more general desire to quantify water-related phenomena. The successful application of computational models implies blackboxing : “[w]hen a machine runs efficiently … one need focus only (...) on its inputs and outputs and not on its internal complexity. Thus, paradoxically, the more science and technology succeed, the more opaque and obscure they become”.. (shrink)

ABSTRACT This paper offers an account of institutional testimonial justice and describes one way that it breaks down, which we call institutional opacity. An institution is opaque when it becomes resistant to epistemic evaluation and understanding by its agents and users. When one cannot understand the inner workings of an institution, it becomes difficult to know how to comport oneself testimonially. We offer an account of an institutional ethos to explain what it means for an institution to be (...) testimonially just; we then describe how an ethos of institutional testimonial justice can break down when the institution becomes opaque. An opaque institution is especially problematic for individuals and groups already rendered epistemically vulnerable during their interactions with that institution, which we call epistemically vulnerabilised individuals. We articulate the features of an encounter between an epistemically vulnerabilised individual and an opaque institution. We end by tracing ameliorative strategies that could help repair a deteriorated institutional ethos of testimonial justice. (shrink)

Referential opacity is the failure of substitutivity of identity (SI, for short) and in Quine’s view of existential generalization (EG, for short) as well. Quine thinks that its “solution” in epistemic and doxastic contexts, which relies on the notion of exportation, leads to undesirable results. But epistemic logicians such as Jaakko Hintikka and Wolfgang Lenzen provide another solution based on a different diagnosis: opacity is not, as in Quine’s view, due to the absence of reference, it (...) is rather due to the plurality of references; therefore, one must stabilize the reference to restore SI and EG. However, Hintikka’s semantics remains classical in its treatment of existence, which makes EG non-applicable to possible objects, while in Lenzen’s system, EG is applicable by means of a particular quantifier. But this requires adding the predicate of existence to account for real objects. In this paper, I will show the advantages and disadvantages of both solutions and will end by providing an alternative approach to the problem of non-existent objects, which stays into the frame of possible worlds semantics, but introduces some more restrictions, eliminates the problematic predicate of existence, and applies a neutral quantifier to possible non-existent objects. (shrink)

‘Statisticalists’ argue that the individual interactions of organisms taken together constitute natural selection. On this view, natural selection is an aggregated effect of interactions rather than some added cause acting on populations. The statisticalists’ view entails that natural selection and drift are indistinguishable aggregated effects of interactions, so that it becomes impossible to make a difference between them. The present paper attempts to make sense of the difference between selection and drift, given the main insights of statisticalism; basically, it will (...) disentangle the various kinds of indistinguishability between selection and drift that happen within biology, by examining the epistemological and metaphysical nature of the distinction between selection and drift. It will be based on a ‘difference-making account’ of selection. The first section will explicate the inscrutability of selection and drift, its various types in the statisticalist writings, and its implications. The second section specifies concepts of natural selection and drift in the difference making account of selection I am using, and shows that one can derive from this the statistical signatures of selection and drift. On this basis I focus on one sort of indistinguishability issue about selection and drift, which I call epistemic opacity, and explain why it mostly affects small populations. The last section explains why epistemic opacity does not raise an genuine epistemic problem for evolutionary biology. (shrink)

Wagenknecht a récemment introduit une distinction conceptuelle entre dépendance épistémique translucide et dépendance épistémique opaque, dans le but de mieux rendre compte de la diversité des relations de dépendance épistémique au sein des pratiques collaboratives de recherche. Dans la continuité de son travail, mon but est d’expliciter les différents types d’expertise requis lorsque sont employés instruments et ordinateurs dans la production de connaissance, et d’identifier des sources potentielles d’opacité. Mon analyse s’appuie sur un cas contemporain de création de connaissance scientifique, (...) à savoir le traitement de données astrophysiques. (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.

Philosophers have recently focused on critical, epistemological challenges that arise from the opacity of deep neural networks. One might conclude from this literature that doing good science with opaque models is exceptionally challenging, if not impossible. Yet, this is hard to square with the recent boom in optimism for AI in science alongside a flood of recent scientific breakthroughs driven by AI methods. In this paper, I argue that the disconnect between philosophical pessimism and scientific optimism is driven by (...) a failure to examine how AI is actually used in science. I show that, in order to understand the epistemic justification for AI-powered breakthroughs, philosophers must examine the role played by deep learning as part of a wider process of discovery. The philosophical distinction between the 'context of discovery' and the 'context of justification' is helpful in this regard. I demonstrate the importance of attending to this distinction with two cases drawn from the scientific literature, and show that epistemic opacity need not diminish AI's capacity to lead scientists to significant and justifiable breakthroughs. (shrink)

Computer simulations are often claimed to be opaque and thus to lack transparency. But what exactly is the opacity of simulations? This paper aims to answer that question by proposing an explication of opacity. Such an explication is needed, I argue, because the pioneering definition of opacity by P. Humphreys and a recent elaboration by Durán and Formanek are too narrow. While it is true that simulations are opaque in that they include too many computations and thus (...) cannot be checked by hand, this doesn’t exhaust what we might want to call the opacity of simulations. I thus make a fresh start with the natural idea that the opacity of a method is its disposition to resist knowledge and understanding. I draw on recent work on understanding and elaborate the idea by a systematic investigation into what type of knowledge and what type of understanding are required if opacity is to be avoided and why the required sort of understanding, in particular, is difficult to achieve. My proposal is that a method is opaque to the degree that it’s difficult for humans to know and to understand why its outcomes arise. This proposal allows for a comparison between different methods regarding opacity. It further refers to a kind of epistemic access that is important in scientific work with simulations. (shrink)

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

Key issues in epistemology for the most part have to do with epistemic values such as justification, truth, and knowledge—that is, values related to the epistemic status of our propositional attitudes, mental events, and states. However, another important issue that is worth examining is the extent to which a subject is in a position to evaluate the strength of her epistemic position. In this paper, I wish to emphasize two properties of our mental states that play a (...) decisive part in that respect: their opacity and transparency. In the following, I will assume that a mental state is opaque whenever it presents itself with no underlying reason, whereas states that are supported by apparent reasons are transparent. One main argument that I will defend is that even when the opacity and transparency of our mental states are not reliable cues, still they remain highly informative. Notably, I draw some implications relative to the externalist/internalist debate in epistemology. I examine the claim that only mental states that are justified are well grounded or justification conferring and the idea that often stands behind, that is, that only states whose reasons are accessible are justified—namely, the Accessibility Requirement. I also examine the source of a recent debate in epistemology: the epistemic status of our intuitive states, as these are perfect instances of opaque mental states. I conclude that intuitive states in some respect are less misleading than states that are supported by apparent reasons. (shrink)

I present the contours of an explanatory model of legitimacy that directs the focus away from normative questions and onto specific mechanisms of reality construction at play in constituting social orders. The key assumption informing the model is that stable orders rely fundamentally on their capacities to construct separate spheres of social reality, by which they exempt critical parts of reality from the burden of legitimation. I argue that an order's legitimacy ultimately depends on its ability to confine the question (...) of legitimacy by relegating authorship of reality to opaque sources that are separated epistemically from the institutional order. The effective reification of critical zones of reality is shown to be a functional precondition for institutional stability. I show that capitalist democracy, in particular, depends on this mode of constructing ‘passive legitimacy’, which constitutes a key obstacle for any attempt to transform it towards an ecologically and socially sustainable formation. (shrink)

This article defends a specific account of reasonableness as a virtue of liberal citizenship. I specify an account of reasonableness that I argue is more consistent with the phenomenology of intersubjective exchanges among citizens over political matters in contexts of deep disagreement. My reading requires reasonable citizens to undertake an attitude of epistemic modesty while deliberating public matters with agents who hold views different from theirs. In contrast with my view, I debate Martha Nussbaum’s and Steven Wall’s accounts of (...) reasonableness and specify why I believe that these proposals, although interesting, both require revisions. Distinguishing my account from theirs, I specify the normative relation between reasonableness and a general framework of political legitimacy that identifies citizens as ‘co-authors of democratic decisions’. Here, I argue that the liberal ideal of ascribing to each member of the constituency the status of putative epistemic authority can be properly fulfilled if coupled with a correct specification of the political ideal of mutual respect. I conclude claiming that opacity respect, a notion of respect according to which the recognition respect that is owed to individuals is expressed by the idea that we have to treat them as ‘opaque’, is the most adequate concept of political respect when dealing with interpersonal deliberations at political level in contexts of deep disagreement. (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)

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.

Scientificity is essentially methodology. The use of information technology as methodological instruments in science has been increasing for decades, this raises the question: Does this transform science? This question is the subject of the Special Issue in Minds and Machines “The epistemological significance of methods in computer simulation and machine learning”. We show that there is a technological change in this area that has three methodological and epistemic consequences: methodological opacity, reproducibility issues, and altered forms of justification.

Democratic legitimacy is often grounded in proceduralist terms, referring to the ideal of political equality that should be mirrored by fair procedures of decision-making. The paper argues (§1) that the normative commitments embedded in a non-minimalist account of procedural legitimacy are well expressed by the ideal of co-authorship. Against this background, the main goal of the paper is to argue that structural forms of epistemic injustice are detrimental to the overall legitimacy of democratic systems. In §2 I analyse Young’s (...) notion of political powerlessness and claim that in structurally unjust social contexts members of powerless groups often are not properly acknowledged as functioning members of the polity, hence being jeopardized in their ability to develop part of their personal identity. In §III, I define gerrymandering as an example of political disempowerment that involves an epistemic harm for oppressed citizens, namely, to be prejudicially excluded from the community of epistemic trust. My thesis is that being epistemically disempowered has a negative impact on the way in which citizens understand themselves as political actors, since they suffer a lack of social recognition that may impede a proper development of their reflexive agency. In §IV, I discuss the proposal of granting epistemic privilege to members of oppressed groups, given their specific experience of social injustices. I introduce two concerns about this proposal, one morally grounded and one pragmatically oriented. Finally, in §V, I briefly sketch some institutional remedies that can be employed in order to politically fight systemic forms of epistemic injustice. (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)

In this paper I argue that Artificial Intelligence and the many data science methods associated with it, such as machine learning and large language models, are first and foremost epistemic technologies. In order to establish this claim, I first argue that epistemic technologies can be conceptually and practically distinguished from other technologies in virtue of what they are designed for, what they do and how they do it. I then proceed to show that unlike other kinds of technology (...) (_including_ other epistemic technologies) AI can be uniquely positioned as an epistemic technology in that it is primarily designed, developed and deployed to be used in _epistemic contexts_ such as inquiry, it is specifically designed, developed and deployed to manipulate _epistemic content_ such as data, _and_ it is designed, developed and deployed to do so particularly through _epistemic operations_ such as prediction and analysis. As has been shown in recent work in the philosophy and ethics of AI (Alvarado, AI and Ethics, 2022a), understanding AI as an epistemic technology will also have significant implications for important debates regarding our relationship to AI technologies. This paper includes a brief overview of such implications, particularly those pertaining to explainability, opacity, trust and even epistemic harms related to AI technologies. (shrink)

Why decolonize knowledge and philosophy? Pascah Mungwini proposes that epistemic decolonization should be implemented to remain true to the spirit of philosophy and to the idea of humanity. Aaron Creller, Michael Monahan, and Esme Murdock focus on different aspects of Mungwini’s proposal in their individual responses. Creller suggests some “best practices” so that comparative epistemology can take into account the parochial embeddedness of universal reason. While Monahan underscores that world philosophy as a project must openly acknowledge its own incompleteness (...) and its instantiation in different world philosophies, Esme Murdock uses Glissant’s thoughts to make a case for the right to opacity as a strategy for subverting the dominating power of Euroamerican reason. In his reply, Mungwini underscores that philosophy will be able to increase the amount of justice, beauty, and truth in this world only when its practitioners begin to exhibit genuine pluralism in their work. (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)

The problem of epistemic opacity in Artificial Intelligence is often characterised as a problem of intransparent algorithms that give rise to intransparent models. However, the degrees of transparency of an AI model should not be taken as an absolute measure of the properties of its algorithms but of the model’s degree of intelligibility to human users. Its epistemically relevant elements are to be specified on various levels above and beyond the computational one. In order to elucidate this claim, (...) I first contrast computer models and their claims to algorithm-based universality with cybernetics-style analogue models and their claims to structural isomorphism between elements of model and target system. While analogue models aim at perceptually or conceptually accessible model-target relations, computer models give rise to a specific kind of underdetermination in these relations that needs to be addressed in specific ways. I then undertake a comparison between two contemporary AI approaches that, although related, distinctly align with the above modelling paradigms and represent distinct strategies towards model intelligibility: Deep Neural Networks and Predictive Processing. I conclude that their respective degrees of epistemic transparency primarily depend on the underlying purposes of modelling, not on their computational properties. (shrink)

In their article ‘Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI’, Durán and Jongsma discuss the epistemic and ethical challenges raised by black box algorithms in medical practice. The opacity of black box algorithms is an obstacle to the trustworthiness of their outcomes. Moreover, the use of opaque algorithms is not normatively justified in medical practice. The authors introduce a formalism, called computational reliabilism, which allows generating justified beliefs (...) on the algorithm reliability and trustworthy outcomes of artificial intelligence systems by means of epistemic warrants, called reliability indicators. However, they remark the need for reliability indicators specific to black box algorithms and that justified knowledge is not sufficient to justify normatively the actions of the physicians using medical AI systems. Therefore, Durán and Jongsma advocate for a more transparent design and implementation of black box algorithms, providing a series of recommendations to mitigate the epistemic and ethical challenges behind their use in medical practice. In this response, I argue that a peculiar form of black box algorithm transparency, called design publicity, may efficiently implement these recommendations. Design publicity encodes epistemic, that is, reliability indicators, and ethical recommendations for black box algorithms by means of four subtypes of transparency. These target the values and goals, their translation into design requirements, the performance and consistency of the algorithm altogether. I discuss design publicity applying it to a use case focused on the automated classification of skin lesions from medical images. (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 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)

This paper attempts to describe and address a specific puzzle related to compositionality in artificial networks such as Deep Neural Networks and machine learning in general. The puzzle identified here touches on a larger debate in Artificial Intelligence related to epistemic opacity but specifically focuses on computational applications of human level linguistic abilities or properties and a special difficulty with relation to these. Thus, the resulting issue is both general and unique. A partial solution is suggested.