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  1. Do ML models represent their targets?Emily Sullivan - forthcoming - Philosophy of Science.
    I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.
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  • Understanding with epistemic possibilities: The epistemic aim and value of metaphysics.Ylwa Sjölin Wirling - forthcoming - Argumenta.
    According to a recent proposal, the epistemic aim of metaphysics as a discipline is to chart the different viable theories of metaphysical objects of inquiry (e.g. causation, persistence). This paper elaborates on and seeks to improve on that proposal in two related ways. First, drawing on an analogy with how-possibly explanation in science, I argue that we can usefully understand this aim of metaphysics as the charting of epistemically possible answers to metaphysical questions. Second, I argue that in order to (...)
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  • The puzzle of model-based explanation.N. Emrah Aydinonat - 2024 - In Tarja Knuuttila, Natalia Carrillo & Rami Koskinen (eds.), The Routledge Handbook of Philosophy of Scientific Modeling. New York, NY: Routledge.
    Among the many functions of models, explanation is central to the functioning and aims of science. However, the discussions surrounding modeling and explanation in philosophy have largely remained separate from each other. This chapter seeks to bridge the gap by focusing on the puzzle of model-based explanation, asking how different philosophical accounts answer the following question: if idealizations and fictions introduce falsehoods into models, how can idealized and fictional models provide true explanations? The chapter provides a selective and critical overview (...)
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  • Nested modalities in astrophysical modeling.Elena Castellani & Giulia Schettino - 2023 - European Journal for Philosophy of Science 13 (1):1-20.
    In the context of astrophysical modeling at the solar system scale, we investigate the modalities implied by taking into account different levels of detail at which phenomena can be considered. In particular, by framing the analysis in terms of the how-possibly/how-actually distinction, we address the debated question as to whether the degree of plausibility is tightly linked to the degree of detail. On the grounds of concrete examples, we argue that, also in the astrophysical context examined, this is not necessarily (...)
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  • The Importance of Understanding Deep Learning.Tim Räz & Claus Beisbart - 2024 - Erkenntnis 89 (5).
    Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, _contra_ Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with (...)
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  • The epistemology of modal modeling.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2021 - Philosophy Compass 16 (10):e12775.
    Philosophers of science have recently taken care to highlight different modeling practices where scientific models primarily contribute modal information, in the form of for example possibility claims, how-possibly explanations, or counterfactual conditionals. While examples abound, comparatively little attention is being paid to the question of under what conditions, and in virtue of what, models can perform this epistemic function. In this paper, we firstly delineate modal modeling from other modeling practices, and secondly reviewattempts to spell out and explain the epistemic (...)
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  • Is credibility a guide to possibility? A challenge for toy models in science.Ylwa Sjölin Wirling - 2021 - Analysis 81 (3):470-478.
    Several philosophers of science claim that scientific toy models afford knowledge of possibility, but answers to the question of why toy models can be expected to competently play this role are scarce. The main line of reply is that toy models support possibility claims insofar as they are credible. I raise a challenge for this credibility-thesis, drawing on a familiar problem for imagination-based modal epistemologies, and argue that it remains unanswered in the current literature. The credibility-thesis has a long way (...)
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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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  • Understanding does not depend on (causal) explanation.Philippe Verreault-Julien - 2019 - European Journal for Philosophy of Science 9 (2):18.
    One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding. While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it on the (...)
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  • Toy models, dispositions, and the power to explain.Philippe Verreault-Julien - 2023 - Synthese 201 (5):1-17.
    Two recent contributions have discussed, and disagreed, over whether so-called toy models that attempt to represent dispositions have the power to explain. In this paper, I argue that neither of these positions is completely correct. Toy models may accurately represent, satisfy the veridicality condition, yet fail to provide how-actually explanations. This is because some dispositions remain unmanifested. Instead, the models provide how-possibly explanations; they _possibly_ explain.
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  • The Modal Basis of Scientific Modelling.Tuomas E. Tahko - 2023 - Synthese 201 (75):1-16.
    The practice of scientific modelling often resorts to hypothetical, false, idealised, targetless, partial, generalised, and other types of modelling that appear to have at least partially non-actual targets. In this paper, I will argue that we can avoid a commitment to non-actual targets by sketching a framework where models are understood as having networks of possibilities as their targets. This raises a further question: what are the truthmakers for the modal claims that we can derive from models? I propose that (...)
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  • What Kind of Explanations Do We Get from Agent-Based Models of Scientific Inquiry?Dunja Šešelja - 2022 - In Tomas Marvan, Hanne Andersen, Hasok Chang, Benedikt Löwe & Ivo Pezlar (eds.), Proceedings of the 16th International Congress of Logic, Methodology and Philosophy of Science and Technology. London: College Publications.
    Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide (...)
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  • Agent‐based models of scientific interaction.Dunja Šešelja - 2022 - Philosophy Compass 17 (7):e12855.
    Philosophy Compass, Volume 17, Issue 7, July 2022.
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  • Modal inferences in science: a tale of two epistemologies.Ilmari Hirvonen, Rami Koskinen & Ilkka Pättiniemi - 2021 - Synthese 199 (5-6):13823-13843.
    Recent epistemology of modality has seen a growing trend towards metaphysics-first approaches. Contrastingly, this paper offers a more philosophically modest account of justifying modal claims, focusing on the practices of scientific modal inferences. Two ways of making such inferences are identified and analyzed: actualist-manipulationist modality and relative modality. In AM, what is observed to be or not to be the case in actuality or under manipulations, allows us to make modal inferences. AM-based inferences are fallible, but the same holds for (...)
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  • Model Pluralism.Walter Veit - 2019 - Philosophy of the Social Sciences 50 (2):91-114.
    This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...)
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  • Some lessons from simulations of scientific disagreements.Dunja Šešelja - 2019 - Synthese 198 (Suppl 25):6143-6158.
    This paper examines lessons obtained by means of simulations in the form of agent-based models about the norms that are to guide disagreeing scientists. I focus on two types of epistemic and methodological norms: norms that guide one’s attitude towards one’s own theory, and norms that guide one’s attitude towards the opponent’s theory. Concerning I look into ABMs that have been designed to examine the context of peer disagreement. Here I challenge the conclusion that the given ABMs provide a support (...)
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  • Exploring Scientific Inquiry via Agent-Based Modelling.Dunja Šešelja - 2021 - Perspectives on Science 29 (4):537-557.
    In this paper I examine the epistemic function of agent-based models of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni’s classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the last category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of science, but by (...)
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  • Introduction to the Synthese Topical Collection 'Modal Modeling in Science: Modal Epistemology meets Philosophy of Science’.Ylwa Sjölin Wirling & Till Grüne-Yanoff - 2023 - Synthese 201 (6):1-13.
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  • (1 other version)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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  • Resolving empirical controversies with mechanistic evidence.Mariusz Maziarz - 2021 - Synthese 199 (3-4):9957-9978.
    The results of econometric modeling are fragile in the sense that minor changes in estimation techniques or sample can lead to statistical models that support inconsistent causal hypotheses. The fragility of econometric results undermines making conclusive inferences from the empirical literature. I argue that the program of evidential pluralism, which originated in the context of medicine and encapsulates to the normative reading of the Russo-Williamson Thesis that causal claims need the support of both difference-making and mechanistic evidence, offers a ground (...)
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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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  • Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare.Juan M. Durán - 2021 - Artificial Intelligence 297 (C):103498.
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  • Possibility of Scientific Explanation from Models Based on Artificial Neural Networks.Alejandro E. Rodríguez-Sánchez - 2024 - Revista Colombiana de Filosofía de la Ciencia 24 (48).
    In Artificial Intelligence, Artificial Neural Networks are very accurate models in tasks such as classification and regression in the study of natural phenomena, but they are considered “black boxes” because they do not allow direct explanation of what they address. This paper reviews the possibility of scientific explanation from these models and concludes that other efforts are required to understand their inner workings. This poses challenges to access scientific explanation through their use, since the nature of Artificial Neural Networks makes (...)
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  • Kinds of modalities and modeling practices.Rami Koskinen - 2023 - Synthese 201 (6):1-15.
    Several recent accounts of modeling have focused on the modal dimension of scientific inquiry. More precisely, it has been suggested that there are specific models and modeling practices that are best understood as being geared towards possibilities, a view recently dubbed modal modeling. But modalities encompass much more than mere possibility claims. Besides possibilities, modal modeling can also be used to investigate contingencies, necessities or impossibilities. Although these modal concepts are logically connected to the notion of possibility, not all models (...)
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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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  • Contextualist model evaluation: models in financial economics and index funds.Melissa Vergara-Fernández, Conrad Heilmann & Marta Szymanowska - 2023 - European Journal for Philosophy of Science 13 (1):1-23.
    Philosophers of science typically focus on the epistemic performance of scientific models when evaluating them. Analysing the effects that models may have on the world has typically been the purview of sociologists of science. We argue that the reactive (or “performative”) effects of models should also figure in model evaluations by philosophers of science. We provide a detailed analysis of how models in financial economics created the impetus for the growing importance of the phenomenon of “passive investing” in financial markets. (...)
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  • Puzzled by Idealizations and Understanding Their Functions.Uskali Mäki - 2020 - Philosophy of the Social Sciences 50 (3):215-237.
    Idealization is ubiquitous in human cognition, and so is the inclination to be puzzled by it: what to make of ideal gas, infinitely large populations, homo economicus, perfectly just society, known to violate matters of fact? This is apparent in social science theorizing, recent philosophy of science analyzing scientific modeling, and the debate over ideal and non-ideal theory in political philosophy. I will offer a set of concepts and principles to improve transparency about the precise contents of idealizations and their (...)
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  • Hamilton's rule: A non-causal explanation?Vaios Koliofotis & Philippe Verreault-Julien - 2022 - Studies in History and Philosophy of Science Part A 92 (C):109-118.
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  • Exploratory modeling and indeterminacy in the search for life.Franklin R. Jacoby - 2022 - European Journal for Philosophy of Science 12 (2):1-20.
    The aim of this article is to use a model from the origin of life studies to provide some depth and detail to our understanding of exploratory models by suggesting that some of these models should be understood as indeterminate. Models that are indeterminate are a type of exploratory model and therefore have extensive potential and can prompt new lines of research. They are distinctive in that, given the current state of scientific understanding, we cannot specify how and where the (...)
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  • (1 other version)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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