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  1. Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...)
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  • Defending Nonreductionism About Understanding.Michele Palmira - 2019 - Thought: A Journal of Philosophy 8 (3):222-231.
    In this note I defend nonreductionism about understanding by arguing that knowledge is neither necessary nor sufficient for understanding. To do so, I examine Paulina Sliwa’s recent (Sliwa 2015, 2017) defence of knowledge-based Reductionism (Reductionism for short). Sliwa claims that one understands why p if and only if one has a sufficient amount of knowledge why p. Sliwa also contends that Reductionism is supported by intuitive verdicts about our uses of ‘understanding why’ and ‘knowing why’. In reply, I first argue (...)
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  • Can Non-Causal Explanations Answer the Leibniz Question?Jens Lemanski - 2022 - Metaphysica 23 (2):427-443.
    Leibniz is often cited as an authority when it comes to the formulation and answer strategy of the question “Why is there something rather than nothing?” Yet much current research assumes that Leibniz advocates an unambiguous question and strategy for the answer. In this respect, one repeatedly finds the argument in the literature that alternative explanatory approaches to this question violate Leibniz’s intention, since he derives the question from the principle of sufficient reason and also demands a causal explanation to (...)
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  • Kinds of knowledge and epistemic reduction.А. А Шевченко - 2023 - Siberian Journal of Philosophy 21 (1):43-50.
    The article provides a brief analysis of the current debate on the two types of knowledge – knowledge-how and knowledge-that and discusses the possibility of reduction of the former to the latter. Two promising anti-reductionist strategies are highlighted. The first strategy uses the notion of “epistemic luck” to demonstrate that the epistemic characteristics of these two kinds of knowledge differ. The second strategy can be based on M. Dewitt’s treatment of linguistic knowledge, which, if accepted, at least deprives the proponents (...)
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  • Using Figurate Numbers in Elementary Number Theory – Discussing a ‘Useful’ Heuristic From the Perspectives of Semiotics and Cognitive Psychology.Leander Kempen & Rolf Biehler - 2020 - Frontiers in Psychology 11.
    The use of figurate numbers (e. g. in the context of elementary number theory) can be considered a heuristic in the field of problem solving or proving. In this paper, we want to discuss this heuristic from the perspectives of the semiotic theory of Peirce (“diagrammatic reasoning” and “collateral knowledge”) and cognitive psychology (“schema theory” and “Gestalt psychology”). We will make use of several results taken from our research to illustrate first-year students’ problems when dealing with figurate numbers in the (...)
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  • Sentimentalism about Moral Understanding.Nathan Robert Howard - 2018 - Ethical Theory and Moral Practice 21 (5):1065-1078.
    Some have attempted to explain why it appears that action based on deferential moral belief lacks moral worth by appealing to claims about an attitude that is difficult to acquire through testimony, which theorists have called “moral understanding”. I argue that this state is at least partly non-cognitive. I begin by employing case-driven judgments to undermine the assumption that I argue is responsible for the strangeness of deferential moral belief: the assumption that if an agent knows that some fact gives (...)
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  • Understanding by Testimony: A Reply to Malfatti.Eric Gilbertson - 2020 - Theoria 86 (4):528-534.
    Federica Malfatti criticizes recent arguments against the possibility of understanding transmission. While she offers no positive argument for the claim that understanding can be transmitted, she does defend a liberal conception of transmission that allows for the possibility of understanding transmission. In this article, I have three aims. First, I will show that there is a stronger version of one of the arguments against understanding transmission that Malfatti considers, which avoids her objection. This argument also fails, however, and the reason (...)
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  • Explainable AI and Causal Understanding: Counterfactual Approaches Considered.Sam Baron - 2023 - Minds and Machines 33 (2):347-377.
    The counterfactual approach to explainable AI (XAI) seeks to provide understanding of AI systems through the provision of counterfactual explanations. In a recent systematic review, Chou et al. (Inform Fus 81:59–83, 2022) argue that the counterfactual approach does not clearly provide causal understanding. They diagnose the problem in terms of the underlying framework within which the counterfactual approach has been developed. To date, the counterfactual approach has not been developed in concert with the approach for specifying causes developed by Pearl (...)
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  • Appreciation as an Epistemic Emotion.Dong An - 2022 - Ethical Theory and Moral Practice 25 (2):249-264.
    In this paper, I develop an account of appreciation. I argue that appreciation is an epistemic emotion in which the subject grasps the object in an affective way. The “grasping” and “feeling” components implies that in appreciation, we make sense of the object by having cognitive control over it, are motivated to maintain the valuable epistemic state of understanding, and experience the “aha” or “eureka” moment. This account offers a unified account of the many types of appreciation, including the aesthetic, (...)
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