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  1. SIDEs: Separating Idealization from Deceptive ‘Explanations’ in xAI.Emily Sullivan - forthcoming - Proceedings of the 2024 Acm Conference on Fairness, Accountability, and Transparency.
    Explainable AI (xAI) methods are important for establishing trust in using black-box models. However, recent criticism has mounted against current xAI methods that they disagree, are necessarily false, and can be manipulated, which has started to undermine the deployment of black-box models. Rudin (2019) goes so far as to say that we should stop using black-box models altogether in high-stakes cases because xAI explanations ‘must be wrong’. However, strict fidelity to the truth is historically not a desideratum in science. Idealizations (...)
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  • Explanation Hacking: The perils of algorithmic recourse.E. Sullivan & Atoosa Kasirzadeh - forthcoming - In Juan Manuel Durán & Giorgia Pozzi (eds.), Philosophy of science for machine learning: Core issues and new perspectives. Springer.
    We argue that the trend toward providing users with feasible and actionable explanations of AI decisions—known as recourse explanations—comes with ethical downsides. Specifically, we argue that recourse explanations face several conceptual pitfalls and can lead to problematic explanation hacking, which undermines their ethical status. As an alternative, we advocate that explanations of AI decisions should aim at understanding.
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  • Describing model relations: The case of the capital asset pricing model (CAPM) family in financial economics.Melissa Vergara-Fernández, Conrad Heilmann & Marta Szymanowska - 2023 - Studies in History and Philosophy of Science Part A 97 (C):91-100.
    The description of how individual models in families of models are related to each other is crucial for the general philosophical understanding of model-based scientific practice. We focus on the Capital Asset Pricing Models (CAPM) family, a cornerstone in financial economics, to provide a descriptive analysis of model relations within a family. We introduce the concepts of theoretical and empirical complementarity to characterise model relations. Our complementarity analysis of model relations has two types of payoff. Specifically regarding the CAPM, our (...)
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  • Understanding metaphorical understanding (literally).Michael T. Stuart & Daniel Wilkenfeld - 2022 - European Journal for Philosophy of Science 12 (3):1-20.
    Metaphors are found all throughout science: in published papers, working hypotheses, policy documents, lecture slides, grant proposals, and press releases. They serve different functions, but perhaps most striking is the way they enable understanding, of a theory, phenomenon, or idea. In this paper, we leverage recent advances on the nature of metaphor and the nature of understanding to explore how they accomplish this feat. We attempt to shift the focus away from the epistemic value of the content of metaphors, to (...)
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  • The Truth About Better Understanding?Lewis Ross - 2021 - Erkenntnis 88 (2):747-770.
    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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  • (1 other version)An Artifactual Perspective on Idealization: Constant Capacitance and the Hodgkin and Huxley Model.Natalia Carrillo & Tarja Knuuttila - 2021 - In Alejandro Cassini & Juan Redmond (eds.), Models and Idealizations in Science: Fictional and Artefactual Approaches. Cham: Springer.
    There are two traditions of thinking about idealization offering almost opposite views on their functioning and epistemic status. While one tradition views idealizations as epistemic deficiencies, the other one highlights the epistemic benefits of idealization. Both of these, however, identify idealization with misrepresentation. In this article, we instead approach idealization from the artifactual perspective, comparing it to the distortion-to-reality accounts of idealization, and exemplifying it through the case of the Hodgkin and Huxley model of nerve impulse. From the artifactual perspective, (...)
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  • Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models.Christopher Grimsley, Elijah Mayfield & Julia Bursten - 2020 - Proceedings of the 12th Conference on Language Resources and Evaluation.
    As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert the (...)
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  • Model Explanation Versus Model-Induced Explanation.Insa Lawler & Emily Sullivan - 2021 - Foundations of Science 26 (4):1049-1074.
    Scientists appeal to models when explaining phenomena. Such explanations are often dubbed model explanations or model-based explanations. But what are the precise conditions for ME? Are ME special explanations? In our paper, we first rebut two definitions of ME and specify a more promising one. Based on this analysis, we single out a related conception that is concerned with explanations that are induced from working with a model. We call them ‘model-induced explanations’. Second, we study three paradigmatic cases of alleged (...)
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  • Deidealization: No Easy Reversals.Tarja Knuuttila & Mary S. Morgan - 2019 - Philosophy of Science 86 (4):641-661.
    Deidealization as a topic in its own right has attracted remarkably little philosophical interest despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, deidealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal (...)
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  • Revisiting abstraction and idealization: how not to criticize mechanistic explanation in molecular biology.Martin Zach - 2022 - European Journal for Philosophy of Science 12 (1):1-20.
    Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...)
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  • Holistic Idealization: An Artifactual Standpoint.Tarja Knuuttila & Natalia Carrillo - 2022 - Studies in History and Philosophy of Science Part A 91 (C):49-59.
    Idealization is commonly understood as distortion: representing things differently than how they actually are. In this paper, we outline an alternative artifactual approach that does not make misrepresentation central for the analysis of idealization. We examine the contrast between the Hodgkin-Huxley (1952a, b, c) and the Heimburg-Jackson (2005, 2006) models of the nerve impulse from the artifactual perspective, and argue that, since the two models draw upon different epistemic resources and research programs, it is often difficult to tell which features (...)
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  • Factive inferentialism and the puzzle of model-based explanation.Philippe Verreault-Julien - 2021 - Synthese 199 (3-4):10039-10057.
    Highly idealized models may serve various epistemic functions, notably explanation, in virtue of representing the world. Inferentialism provides a prima facie compelling characterization of what constitutes the representation relation. In this paper, I argue that what I call factive inferentialism does not provide a satisfactory solution to the puzzle of model-based—factive—explanation. In particular, I show that making explanatory counterfactual inferences is not a sufficient guide for accurate representation, factivity, or realism. I conclude by calling for a more explicit specification of (...)
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  • Extending Similarity-based Epistemology of Modality with Models.Ylwa Sjölin Wirling - 2022 - Ergo: An Open Access Journal of Philosophy 8 (45).
    Empiricist modal epistemologies can be attractive, but are often limited in the range of modal knowledge they manage to secure. In this paper, I argue that one such account – similarity-based modal empiricism – can be extended to also cover justification of many scientifically interesting possibility claims. Drawing on recent work on modelling in the philosophy of science, I suggest that scientific modelling is usefully seen as the creation and investigation of relevantly similar epistemic counterparts of real target systems. On (...)
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  • A Defense of Truth as a Necessary Condition on Scientific Explanation.Christopher Pincock - 2021 - Erkenntnis 88 (2):621-640.
    How can a reflective scientist put forward an explanation using a model when they are aware that many of the assumptions used to specify that model are false? This paper addresses this challenge by making two substantial assumptions about explanatory practice. First, many of the propositions deployed in the course of explaining have a non-representational function. In particular, a proposition that a scientist uses and also believes to be false, i.e. an “idealization”, typically has some non-representational function in the practice, (...)
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  • Cognitive dynamical models as minimal models.Travis Holmes - 2021 - Synthese 199 (1):2353-2373.
    The debate over the explanatory nature of cognitive models has been waged mostly between two factions: the mechanists and the dynamical systems theorists. The former hold that cognitive models are explanatory only if they satisfy a set of mapping criteria, particularly the 3M/3m* requirement. The latter have argued, pace the mechanists, that some cognitive models are both dynamical and constitute covering-law explanations. In this paper, I provide a minimal model interpretation of dynamical cognitive models, arguing that this both provides needed (...)
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  • Model Evaluation: An Adequacy-for-Purpose View.Wendy S. Parker - 2020 - Philosophy of Science 87 (3):457-477.
    According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers...
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  • Scaling procedures in climate science: Using temporal scaling to identify a paleoclimate analogue.Aja Watkins - 2023 - Studies in History and Philosophy of Science Part A 102 (C):31-44.
    Using past episodes of climate change as a source of evidence to inform our projections about contemporary climate change requires establishing the extent to which episodes in the deep past are analogous to the current crisis. However, many scientists claim that contemporary rates of climate change (e.g., rates of carbon emissions or temperature change) are unprecedented, including compared to episodes in the deep past. If so, this would limit the utility of paleoclimate analogues. In this paper, I show how a (...)
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  • Empirical techniques and the accuracy of scientific representations.Dana Matthiessen - 2022 - Studies in History and Philosophy of Science Part A 94 (C):143-157.
    This paper proposes an account of accurate scientific representation in terms of techniques that produce data from a target phenomenon. I consider an approach to accurate representation that abstracts from such epistemic factors, justified by a thesis I call Ontic Priority. This holds that criteria for representational accuracy depend on a pre-established account of the nature of the relation between a model and its target phenomenon. I challenge Ontic Priority, drawing on the observation that many working scientists do not have (...)
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  • Understanding realism.Collin Rice - 2019 - Synthese 198 (5):4097-4121.
    Catherine Elgin has recently argued that a nonfactive conception of understanding is required to accommodate the epistemic successes of science that make essential use of idealizations and models. In this paper, I argue that the fact that our best scientific models and theories are pervasively inaccurate representations can be made compatible with a more nuanced form of scientific realism that I call Understanding Realism. According to this view, science aims at (and often achieves) factive scientific understanding of natural phenomena. I (...)
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  • Concrete Scale Models, Essential Idealization, and Causal Explanation.Christopher Pincock - 2022 - British Journal for the Philosophy of Science 73 (2):299-323.
    This paper defends three claims about concrete or physical models: these models remain important in science and engineering, they are often essentially idealized, in a sense to be made precise, and despite these essential idealizations, some of these models may be reliably used for the purpose of causal explanation. This discussion of concrete models is pursued using a detailed case study of some recent models of landslide generated impulse waves. Practitioners show a clear awareness of the idealized character of these (...)
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  • How to Reconcile a Unified Account of Explanation with Explanatory Diversity.Collin Rice & Yasha Rohwer - 2020 - Foundations of Science 26 (4):1025-1047.
    The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). Either there is nothing that (...)
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  • Scientific understanding and felicitous legitimate falsehoods.Insa Lawler - 2021 - Synthese 198 (7):6859-6887.
    Science is replete with falsehoods that epistemically facilitate understanding by virtue of being the very falsehoods they are. In view of this puzzling fact, some have relaxed the truth requirement on understanding. I offer a factive view of understanding that fully accommodates the puzzling fact in four steps: (i) I argue that the question how these falsehoods are related to the phenomenon to be understood and the question how they figure into the content of understanding it are independent. (ii) I (...)
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  • Reckoning with Continuum Idealizations: Some Lessons from Soil Hydrology.Travis Holmes - 2022 - Philosophy of Science 89 (2):319-336.
    In scientific modeling, continuum idealizations bridge scales but at the cost of fundamentally misrepresenting the microstructure of the system. This engenders a mystery. If continuum idealizations are dispensable in principle, this de-problematizes their representational inaccuracy, since continuum properties reduce to lower-scale properties, but the mystery of how this reduction could be carried out endures. Alternatively, if continuum idealizations are indispensable in principle, this is consistent with their explanatory and predictive success but renders their representational inaccuracy mysterious. I argue for a (...)
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  • (1 other version)Defending De-idealization in Economic Modeling: A Case Study.Edoardo Peruzzi & Gustavo Cevolani - 2021 - Sage Publications Inc: Philosophy of the Social Sciences 52 (1-2):25-52.
    This paper defends the viability of de-idealization strategies in economic modeling against recent criticism. De-idealization occurs when an idealized assumption of a theoretical model is replaced with a more realistic one. Recently, some scholars have raised objections against the possibility or fruitfulness of de-idealizing economic models, suggesting that economists do not employ this kind of strategy. We present a detailed case study from the theory of industrial organization, discussing three different models, two of which can be construed as de-idealized versions (...)
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  • Micro-level model explanation and counterfactual constraint.Samuel Schindler - 2022 - European Journal for Philosophy of Science 12 (2):1-27.
    Relationships of counterfactual dependence have played a major role in recent debates of explanation and understanding in the philosophy of science. Usually, counterfactual dependencies have been viewed as the explanantia of explanation, i.e., the things providing explanation and understanding. Sometimes, however, counterfactual dependencies are themselves the targets of explanations in science. These kinds of explanations are the focus of this paper. I argue that “micro-level model explanations” explain the particular form of the empirical regularity underlying a counterfactual dependency by representing (...)
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  • Generative Models.Sim-Hui Tee - 2020 - Erkenntnis 88 (1):23-41.
    Generative models have been proposed as a new type of non-representational scientific models recently. A generative model is characterized with the capacity of producing new models on the basis of the existing one. The current accounts do not explain sufficiently the mechanism of the generative capacity of a generative model. I attempt to accomplish this task in this paper. I outline two antecedent accounts of generative models. I point out that both types of generative models function to generate new homogenous (...)
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  • Modeling multiscale patterns: active matter, minimal models, and explanatory autonomy.Collin Rice - 2022 - Synthese 200 (6):1-35.
    Both ecologists and statistical physicists use a variety of highly idealized models to study active matter and self-organizing critical phenomena. In this paper, I show how universality classes play a crucial role in justifying the application of highly idealized ‘minimal’ models to explain and understand the critical behaviors of active matter systems across a wide range of scales and scientific fields. Appealing to universality enables us to see why the same minimal models can be used to explain and understand behaviors (...)
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  • On Leszek Nowak’s Conception of the Unity of Science.Mateusz Wajzer - 2024 - Foundations of Science 29 (2):307-324.
    The purpose of this essay is to present and analyse the basic assumptions of Leszek Nowak’s conception of the unity of science. According to Nowak, the unity of science is manifested in the common application of the method of idealisation in scientific research. In accordance with his conception, regardless of the discipline they represent, researchers go through the same stages in building a theory. Two key ones among them are: introducing idealising assumptions into the representation and then their concretisation. In (...)
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  • Economic Methodology in the Twenty-First Century (So Far): Some Post-Reflection Reflections.Douglas Wade Hands - 2020 - Revue de Philosophie Économique 20 (2):221-252.
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  • (1 other version)Design principles as minimal models.Wei Fang - 2024 - Studies in History and Philosophy of Science Part A 105 (C):50-58.
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  • (1 other version)Defending De-idealization in Economic Modeling: A Case Study.Edoardo Peruzzi & Gustavo Cevolani - 2022 - Philosophy of the Social Sciences 52 (1-2):25-52.
    This paper defends the viability of de-idealization strategies in economic modeling against recent criticism. De-idealization occurs when an idealized assumption of a theoretical model is replaced with a more realistic one. Recently, some scholars have raised objections against the possibility or fruitfulness of de-idealizing economic models, suggesting that economists do not employ this kind of strategy. We present a detailed case study from the theory of industrial organization, discussing three different models, two of which can be construed as de-idealized versions (...)
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