About this topic
Summary Understanding considered as an epistemic accomplishment.  Some of the relevant questions include: How does understanding differ (if at all) from other epistemic accomplishments such as knowledge or wisdom?  And what does it take to understand events in the world, as opposed to people, or languages, or works of art?
Key works Influential recent works include Zagzebski 2001, Kvanvig 2003, and Grimm 2006.
Introductions Grimm 2011 offers an overview of the literature.
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426 found
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1 — 50 / 426
  1. ‘Let me understand!’: Protection of students’ epistemic rights.Samet Merzifonluoglu & Ercenk Hamarat - manuscript
    We all know unequivocally that we hold certain rights entitled to every human being, that are enshrined in and guaranteed by the constitution, that would have been there, even if we were not yet stepped into the world. These rights comprise a broad range from our right to food, to our right to education, our right to freedom, and the like. However, in her recent book, Watson points out an unnoticed rights framework regarding epistemic goods to which are all entitled. (...)
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  2. Resilient Understanding: The Value of Seeing for Oneself.Matthew Slater & Jason Leddington - manuscript
    The primary aim of this paper is to argue that the value of understanding derives in part from a kind of subjective stability of belief that we call epistemic resilience. We think that this feature of understanding has been overlooked by recent work, and we think it’s especially important to the value of understanding for social cognitive agents such as us. We approach the concept of epistemic resilience via the idea of the experience of epistemic ownership and argue that the (...)
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  3. Understanding, seeming and believing.Douglas Patterson - manuscript
    A short discussion of whether or not an error theorist of understanding should construe understanding in terms of belief. This is a comment on a discussion between Dean Pettit and Steven Gross.
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  4. Epistemic Value, Duty, and Virtue.Guy Axtell - forthcoming - In Brian C. Barnett (ed.), Introduction to Philosophy: Epistemology. Rebus Community.
    This chapter introduces some central issues in Epistemology, and, like others in the open textbook series Introduction to Philosophy, is set up for rewarding college classroom use, with discussion/reflection questions matched to clearly-stated learning objectives,, a brief glossary of the introduced/bolded terms/concepts, links to further open source readings as a next step, and a readily-accessible outline of the classic between William Clifford and William James over the "ethics of belief." The chapter introduces questions of epistemic value through Plato's famous example (...)
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  5. Grasping in Understanding.Miloud Belkoniene - forthcoming - British Journal for the Philosophy of Science.
    There is, among philosophers involved in the debate concerning the nature and epistemology of understanding, a general recognition that this state has a grasping component that accounts for some of its distinctive features. This paper defends the view that this component of understanding consists of a knowledge of how to use a particular explanation to account for a given phenomenon. The way in which a subject acquires this knowledge is examined and the result of this examination is shown to highlight (...)
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  6. Reassessing Lucky Understanding.Miloud Belkoniene - forthcoming - Episteme:1-15.
    Knowledge is widely regarded as being incompatible with epistemic luck, but according to several philosophers, the same does not hold for understanding. This paper examines to what extent understanding is vulnerable to epistemic luck. After discussing the weaknesses of some of the cases that have been offered to support the conclusion that understanding tolerates environmental epistemic luck, I turn to a more recent one offered in favour of the opposite conclusion. I argue that this case does not manage to establish (...)
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  7. Elgin on Science, Art and Understanding.Jochen Briesen - forthcoming - Erkenntnis.
    Is art epistemically valuable? Catherine Z. Elgin answers this question in the affirmative. She argues for the epistemic value of art on the basis of her innovative epistemological theory, in which the focus is shifted from knowledge and truth to a non-factive account of understanding. After an exposition and critique of her view, as she develops it in her most recent book “True Enough”, I will build on some of her ideas in order to strengthen her account.
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  8. On Pritchard, Objectual Understanding and the Value Problem.J. Adam Carter & Emma C. Gordon - forthcoming - American Philosophical Quarterly.
    Duncan Pritchard (2008, 2009, 2010, forthcoming) has argued for an elegant solution to what have been called the value problems for knowledge at the forefront of recent literature on epistemic value. As Pritchard sees it, these problems dissolve once it is recognized that that it is understanding-why, not knowledge, that bears the distinctive epistemic value often (mistakenly) attributed to knowledge. A key element of Pritchard’s revisionist argument is the claim that understanding-why always involves what he calls strong cognitive achievement—viz., cognitive (...)
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  9. Scientific Progress without Problems: A Reply to McCoy.Finnur Dellsén - forthcoming - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. Routledge.
    In the course of developing an account of scientific progress, C. D. McCoy (2022) appeals centrally to understanding as well as to problem-solving. On the face of it, McCoy’s account could thus be described as a kind of hybrid of the understanding-based account that I favor (Dellsén 2016, 2021) and the functional (a.k.a. problem-solving) account developed most prominently by Laudan (1977; see also Kuhn 1970; Shan 2019). In this commentary, I offer two possible interpretations of McCoy’s account and explain why (...)
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  10. Helping Others to Understand: A Normative Account of the Speech Act of Explanation.Grzegorz Gaszczyk - forthcoming - Topoi:1-12.
    This paper offers a normative account of the speech act of explanation with understanding as its norm. The previous accounts of the speech act of explanation rely on the factive notion of understanding and maintain that proper explanations require knowledge. I argue, however, that such accounts are too demanding and do not reflect the everyday practice of explanation and the attribution of understanding. Instead, I argue that the non-factive, objectual attitude of understanding is sufficient for a proper explanation. On the (...)
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  11. Understanding Philosophy.Michael Hannon & James Nguyen - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    What is the primary intellectual aim of philosophy? The standard view is that philosophy aims to provide true answers to philosophical questions. But if our aim is to settle controversy by answering such questions, our discipline is an embarrassing failure. Moreover, taking philosophy to aim at providing true answers to these questions leads to a variety of puzzles: How do we account for philosophical expertise? How is philosophical progress possible? Why do job search committees not care about the truth or (...)
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  12. Testimony, Understanding, and Art Criticism.Allan Hazlett - forthcoming - In Christy Mag Uidhir (ed.), Philosophy and Art: New Essays at the Intersection. Oxford University Press.
    I present a puzzle – the “puzzle of aesthetic testimony” – along with a solution to it that appeals to the impossibility of testimonial understanding. I'll criticize this solution by defending the possibility of testimonial understanding, including testimonial aesthetic understanding.
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  13. Understanding and Testimony.Allan Hazlett - forthcoming - In Jennifer Lackey & Aidan McGlynn (eds.), The Oxford Handbook of Social Epistemology. Oxford.
    Can understanding be transmitted by testimony, in the same sense that propositional knowledge can be transmitted by testimony? Some contemporary philosophers – call them testimonial understanding pessimists – say No, and others – call them testimonial understanding optimists – say Yes. In this chapter I will articulate testimonial understanding pessimism (§1) and consider some arguments for it (§2).
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  14. Hot-Cold Empathy Gaps and the Grounds of Authenticity.Grace Helton & Christopher Register - forthcoming - Synthese.
    Hot-cold empathy gaps are a pervasive phenomena wherein one’s predictions about others tend to skew ‘in the direction’ of one’s own current visceral states. For instance, when one predicts how hungry someone else is, one’s prediction will tend to reflect one’s own current hunger state. These gaps also obtain intrapersonally, when one attempts to predict what one oneself would do at a different time. In this paper, we do three things: We draw on empirical evidence to argue that so-called hot-cold (...)
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  15. The Epistemic Value of Understanding-why.Xingming Hu - forthcoming - Episteme:1-17.
    Some philosophers recently have objected that veritism cannot explain the epistemic value of understanding-why. And they have proposed two anti-veritist accounts. In this paper, I first introduce their objection and argue that it fails. Next, I consider a strengthened version of their objection and argue that it also fails. After that, I suggest a new veritist account: Understanding-why entails believing the truth that what is grasped is accurate, and it is this true belief, along with many other true beliefs understanding-why (...)
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  16. Epistemic Welfare Bads and Other Failures of Reason.Antti Kauppinen - forthcoming - Midwest Studies in Philosophy.
    Very plausibly, there is something important missing in our lives if we are thoroughly ignorant or misled about reality – even if, as in a kind of Truman Show scenario, intervention or fantastic luck prevents unhappiness and practical failure. But why? I argue that perfectionism about well-being offers the most promising explanation. My version says, roughly, that we flourish when we exercise our self-defining capacities successfully according to their constitutive standards. One of these self-defining capacities, or capacities whose exercise reveals (...)
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  17. Imagination, Modal Knowledge, and Modal Understanding.Uriah Kriegel - forthcoming - In Íngrid Vendrell Ferran & Christiana Werner (eds.), Imagination and Experience: Philosophical Explorations. London: Routledge.
    Recent work on the imagination has stressed the epistemic role of imaginative experiences, notably in justifying modal beliefs. An immediate problem with this is that modal beliefs appear to admit of justification through the mere exercise of rational capacities. For instance, mastery of the concepts of pig, flying, and possibility should suffice to form a justified belief that flying pigs are possible, regardless of whether one imagines a flying pig. In this paper, I consider three ways to defend the epistemic (...)
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  18. Understanding the Progress of Science.C. D. McCoy - forthcoming - In Kareem Khalifa, Insa Lawler & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. Routledge.
    A problem-solving-based account of scientific progress that takes understanding as the principal epistemic aim of science is developed and defended against knowledge reductionism.
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  19. Common knowledge. The development of understanding in the classroom.N. Mercer & D. Edwards - forthcoming - Common Knowledge: The Development of Understanding in the Classroom.
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  20. Understanding Misunderstanding.Gilad Nir - forthcoming - In Carla Carmona, David Perez-Chico & Chon Tejedor (eds.), Intercultural Understanding: Wittgensteinian Approaches.
    Wittgenstein seeks to throw light on our concept of understanding by looking at how misunderstandings arise and what kinds of failure they involve. He discerns a peculiar sort of misunderstanding in the writings of the social anthropologist James Frazer. In Frazer’s hands, the anthropological project of enabling us to understand human behavior seems to yield the result that there are certain forms of human behavior that simply cannot be understood. The source of Frazer’s misunderstanding, according to Wittgenstein, is that he (...)
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  21. The truth about better understanding?Lewis Ross - forthcoming - Erkenntnis:1-24.
    The notion of understanding occupies an increasingly prominent place in contemporary epistemology, philosophy of science, and moral theory. A central and ongoing debate about the nature of understanding is how it relates to the truth. In a series of influential contributions, Catherine Elgin has used a variety of familiar motivations for antirealism in philosophy of science to defend a non- factive theory of understanding. Key to her position are: (i) the fact that false theories can contribute to the upwards trajectory (...)
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  22. Kant on Reason as the Capacity for Comprehension.Karl Schafer - forthcoming - Australasian Journal of Philosophy:1-19.
    This essay develops an interpretation of Kant’s conception of the faculty of reason as the capacity for what he calls "comprehension" (Begreifen). In doing so, it first discusses Kant's characterizations of reason in relation to what he describes as the two highest grades of cognition—insight and comprehension. Then it discusses how the resulting conception of reason relates to more familiar characterizations as the faculty for inference and the faculty of principles. In doing so, it focuses on how the idea of (...)
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  23. Grounding, Understanding, and Explanation.Wes Siscoe - forthcoming - Pacific Philosophical Quarterly.
    Starting with the slogan that understanding is a 'knowledge of causes,' Stephen Grimm and John Greco have argued that understanding comes from a knowledge of dependence relations. Grounding is the trendiest dependence relation on the market, and if Grimm and Greco are correct, then instances of grounding should also give rise to understanding. In this paper, I will show that this prediction is correct-grounding does indeed generate understanding in just the way that Grimm and Greco anticipate. However, grounding examples of (...)
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  24. Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - forthcoming - Philosophy of Science:1-13.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this paper, I argue that non-epistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
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  25. Empathy and the Value of Humane Understanding.Olivia Bailey - 2022 - Philosophy and Phenomenological Research 104 (1):50-65.
    Philosophy and Phenomenological Research, EarlyView.
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  26. The rational dimension of understanding.Miloud Belkoniene - 2022 - Synthese 200 (5):1-16.
    It is natural to regard understanding as having a rational dimension, in the sense that understanding seems to require having justification for holding certain beliefs about the world. Some philosophers however argue that justification is not required to gain understanding of phenomena. In the present paper, my intention is to provide a critical examination of the arguments that have been offered against the view that understanding requires justification in order to show that, contrary to what they purport to establish, justification (...)
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  27. Two Dimensions of Opacity and the Deep Learning Predicament.Florian J. Boge - 2022 - Minds and Machines 32 (1):43-75.
    Deep neural networks have become increasingly successful in applications from biology to cosmology to social science. Trained DNNs, moreover, correspond to models that ideally allow the prediction of new phenomena. Building in part on the literature on ‘eXplainable AI’, I here argue that these models are instrumental in a sense that makes them non-explanatory, and that their automated generation is opaque in a unique way. This combination implies the possibility of an unprecedented gap between discovery and explanation: When unsupervised models (...)
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  28. Unrealistic Models in Mathematics.William D'Alessandro - 2022 - Philosophers’ Imprint.
    Models are indispensable tools of scientific inquiry, and one of their main uses is to improve our understanding of the phenomena they represent. How do models accomplish this? And what does this tell us about the nature of understanding? While much recent work has aimed at answering these questions, philosophers' focus has been squarely on models in empirical science. I aim to show that pure mathematics also deserves a seat at the table. I begin by presenting two cases: Cramér’s random (...)
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  29. The Noetic Approach: Scientific Progress as Enabling Understanding.Finnur Dellsén - 2022 - In Yafeng Shan (ed.), New Philosophical Perspectives on Scientific Progress. Routledge. pp. 62-81.
    Roughly, the noetic account characterizes scientific progress in terms of increased understanding. This chapter outlines a version of the noetic account according to which scientific progress on some phenomenon consists in making scientific information publicly available so as to enable relevant members of society to increase their understanding of that phenomenon. This version of the noetic account is briefly compared with four rival accounts of scientific progress, viz. the truthlikeness account, the problem-solving account, the new functional account, and the epistemic (...)
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  30. Understanding and scientific progress: lessons from epistemology.Nicholas Emmerson - 2022 - Synthese 200 (1):1-18.
    Contemporary debate surrounding the nature of scientific progress has focused upon the precise role played by justification, with two realist accounts having dominated proceedings. Recently, however, a third realist account has been put forward, one which offers no role for justification at all. According to Finnur Dellsén’s (Stud Hist Philos Sci Part A 56:72–83, 2016) noetic account, science progresses when understanding increases, that is, when scientists grasp how to correctly explain or predict more aspects of the world that they could (...)
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  31. Understanding, Idealization, and Explainable AI.Will Fleisher - 2022 - Episteme 19 (4):534-560.
    Many AI systems that make important decisions are black boxes: how they function is opaque even to their developers. This is due to their high complexity and to the fact that they are trained rather than programmed. Efforts to alleviate the opacity of black box systems are typically discussed in terms of transparency, interpretability, and explainability. However, there is little agreement about what these key concepts mean, which makes it difficult to adjudicate the success or promise of opacity alleviation methods. (...)
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  32. Analogue Quantum Simulation: A New Instrument for Scientific Understanding.Dominik Hangleiter, Jacques Carolan & Karim Thebault - 2022 - Cham: Springer.
    This book presents fresh insights into analogue quantum simulation. It argues that these simulations are a new instrument of science. They require a bespoke philosophical analysis, sensitive to both the similarities to and the differences with conventional scientific practices such as analogical argument, experimentation, and classical simulation. -/- The analysis situates the various forms of analogue quantum simulation on the methodological map of modern science. In doing so, it clarifies the functions that analogue quantum simulation serves in scientific practice. To (...)
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  33. Towards Ideal Understanding.Mario Hubert & Federica Malfatti - 2022 - Ergo:1-34.
    What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...)
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  34. Integrating Philosophy of Understanding with the Cognitive Sciences.Kareem Khalifa, Farhan Islam, J. P. Gamboa, Daniel Wilkenfeld & Daniel Kostić - 2022 - Frontiers in Systems Neuroscience 16.
    We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.
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  35. Introduction to the edited volume “Scientific Understanding and Representation: Modeling in the Physical Sciences”.Kareem Khalifa, Insa Lawler & Elay Shech - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation: Modeling in the Physical Sciences. Routledge.
    This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.
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  36. Phenomenal Grounds of Epistemic Value.Uriah Kriegel - 2022 - Philosophy Compass 17 (12):e12888.
    Imagine a zombie world that looks “from the outside” just like ours, but where there is no phenomenal consciousness. Creatures that look like us move about just as we do and make the same noises we do, but nobody experiences or feels anything. How much of the epistemic value that’s exemplified in our world survives in that one? The short answer is: any kind of epistemic value that requires the occurrence of consciousness for its exemplification cannot exist in that world, (...)
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  37. Scientific Understanding and Representation: Modeling in the Physical Sciences.Insa Lawler, Kareem Khalifa & Elay Shech (eds.) - 2022 - New York, NY: Routledge.
    This volume brings together leading scholars working on understanding and representation in philosophy of science. It features a critical conversation format between contributors that advances debates concerning scientific understanding, scientific representation, and their delicate interplay.
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  38. Understanding, Psychology, and the Human Sciences: Dilthey and Völkerpsychologie.Lydia Patton - 2022 - In Adam Tamas Tuboly (ed.), The History of Understanding in Analytic Philosophy. London: Bloomsbury. pp. 39-62.
    The framework of the modern Western analysis of culture, in terms of the socio-historical situation of the subject and the reciprocal influence of one on the other, has its roots in nineteenth century discussions. This paper will examine two traditions: the hermeneutic approach of Wilhelm Dilthey, and the Völkerpsychologie of Moses Lazarus and Chajim Steinthal. The account will focus on two elements. First, Lazarus and Steinthal attempted to motivate an account based on collective structures, or forms, of rationality made manifest (...)
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  39. Link Uncertainty, Implementation, and ML Opacity: A Reply to Tamir and Shech.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 341-345.
    This chapter responds to Michael Tamir and Elay Shech’s chapter “Understanding from Deep Learning Models in Context.”.
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  40. How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 306-322.
    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) (...)
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  41. Can We Have Physical Understanding of Mathematical Facts?Gabriel Tȃrziu - 2022 - Acta Analytica 37 (2):135-158.
    A lot of philosophical energy has been devoted recently in trying to determine if mathematics can contribute to our understanding of physical phenomena. Not many philosophers are interested, though, if the converse makes sense, i.e., if our cognitive interaction (scientific or otherwise) with the physical world can be helpful (in an explanatory or non-explanatory way) in our efforts to make sense of mathematical facts. My aim in this paper is to try to fill this important lacuna in the recent literature. (...)
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  42. Disagreement, Testimony, and Religious Understanding.Laura Frances Callahan - 2021 - In Matthew A. Benton & Jonathan L. Kvanvig (eds.), Religious Disagreement and Pluralism. Oxford: Oxford University Press. pp. 41--64.
  43. Understanding Attributions: Problems, Options, and a Proposal.Felipe Morales Carbonell - 2021 - Theoria 88 (3):558-583.
    In this paper, I give an overview of different models of understanding attribution and advance a contextualist account of understanding attribution. Whereas other contextualist accounts make the degree in which the epistemic states of the relevant agents satisfy certain invariant conditions context-sensitive, the proposed account makes the conditions themselves context-sensitive.
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  44. We Owe It to Others to Think for Ourselves.Finnur Dellsén - 2021 - In Jonathan Matheson & Kirk Lougheed (eds.), Epistemic Autonomy. Routledge.
    We are often urged to figure things out for ourselves rather than to rely on other people’s say-so, and thus be ‘epistemically autonomous’ in one sense of the term. But why? For almost any important question, there will be someone around you who is at least as well placed to answer it correctly. So why bother making up your own mind at all? I consider, and then reject, two ‘egoistic’ answers to this question according to which thinking for oneself is (...)
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  45. Understanding scientific progress: the noetic account.Finnur Dellsén - 2021 - Synthese 199 (3-4):11249-11278.
    What is scientific progress? This paper advances an interpretation of this question, and an account that serves to answer it. Roughly, the question is here understood to concern what type of cognitive change with respect to a topic X constitutes a scientific improvement with respect to X. The answer explored in the paper is that the requisite type of cognitive change occurs when scientific results are made publicly available so as to make it possible for anyone to increase their understanding (...)
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  46. Why understanding-why is contrastive.Miguel Egler - 2021 - Synthese 199 (3-4):6061-6083.
    Contrastivism about interrogative understanding is the view that ‘S understands why p’ posits a three-place epistemic relation between a subject S, a fact p, and an alternative to p, q. This thesis stands in stark opposition to the natural idea that a subject S can be said to understand why psimpliciter. I argue that contrastivism offers the best explanation for the fact that evaluations of the form ‘S understands why p’ vary depending on the alternatives to p under consideration. I (...)
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  47. Recent Work in the Epistemology of Understanding.Michael Hannon - 2021 - American Philosophical Quarterly 58 (3):269-290.
    The philosophical interest in the nature, value, and varieties of human understanding has swelled in recent years. This article will provide an overview of new research in the epistemology of understanding, with a particular focus on the following questions: What is understanding and why should we care about it? Is understanding reducible to knowledge? Does it require truth, belief, or justification? Can there be lucky understanding? Does it require ‘grasping’ or some kind of ‘know-how’? This cluster of questions has largely (...)
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  48. Hempel on Scientific Understanding.Xingming Hu - 2021 - Studies in History and Philosophy of Science Part A 88 (8):164-171.
    Hempel seems to hold the following three views: (H1) Understanding is pragmatic/relativistic: Whether one understands why X happened in terms of Explanation E depends on one's beliefs and cognitive abilities; (H2) Whether a scientific explanation is good, just like whether a mathematical proof is good, is a nonpragmatic and objective issue independent of the beliefs or cognitive abilities of individuals; (H3) The goal of scientific explanation is understanding: A good scientific explanation is the one that provides understanding. Apparently, H1, H2, (...)
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  49. Understanding Physics: ‘What?’, ‘Why?’, and ‘How?’.Mario Hubert - 2021 - European Journal for Philosophy of Science 11 (3):1-36.
    I want to combine two hitherto largely independent research projects, scientific understanding and mechanistic explanations. Understanding is not only achieved by answering why-questions, that is, by providing scientific explanations, but also by answering what-questions, that is, by providing what I call scientific descriptions. Based on this distinction, I develop three forms of understanding: understanding-what, understanding-why, and understanding-how. I argue that understanding-how is a particularly deep form of understanding, because it is based on mechanistic explanations, which answer why something happens in (...)
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  50. What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research.Markus Langer, Daniel Oster, Timo Speith, Lena Kästner, Kevin Baum, Holger Hermanns, Eva Schmidt & Andreas Sesing - 2021 - Artificial Intelligence 296 (C):103473.
    Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, and demands regarding artificial systems (we call these “stakeholders' desiderata”) in a variety of contexts. However, the literature on XAI is vast, spreads out across multiple largely disconnected disciplines, and it often remains unclear how explainability approaches are supposed to achieve the goal of satisfying stakeholders' desiderata. This paper discusses the main classes of stakeholders calling for explainability (...)
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