- How to Do Science with Models: A Philosophical Primer.Axel Gelfert - 2016 - Cham: Springer.details
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(1 other version)Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.details
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The philosophical novelty of computer simulation methods.Paul Humphreys - 2009 - Synthese 169 (3):615 - 626.details
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Entering new fields: Exploratory uses of experimentation.Friedrich Steinle - 1997 - Philosophy of Science 64 (4):74.details
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Why we view the brain as a computer.Oron Shagrir - 2006 - Synthese 153 (3):393-416.details
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Opacity thought through: on the intransparency of computer simulations.Claus Beisbart - 2021 - Synthese 199 (3-4):11643-11666.details
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How the machine ‘thinks’: Understanding opacity in machine learning algorithms.Jenna Burrell - 2016 - Big Data and Society 3 (1):205395171562251.details
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What is Interpretability?Adrian Erasmus, Tyler D. P. Brunet & Eyal Fisher - 2021 - Philosophy and Technology 34:833–862.details
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Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?John Zerilli, Alistair Knott, James Maclaurin & Colin Gavaghan - 2018 - Philosophy and Technology 32 (4):661-683.details
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Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence.Carlos Zednik - 2019 - Philosophy and Technology 34 (2):265-288.details
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Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.details
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Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience.J. Brendan Ritchie, David Michael Kaplan & Colin Klein - 2019 - British Journal for the Philosophy of Science 70 (2):581-607.details
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Two Kinds of Exploratory Models.Michela Massimi - 2019 - Philosophy of Science 86 (5):869-881.details
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Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience.J. Brendan Ritchie, David Michael Kaplan & Colin Klein - 2016 - British Journal for the Philosophy of Science:axx023.details
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Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.details
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(1 other version)Four Decades of Scientific Explanation.Wesley C. Salmon & Anne Fagot-Largeault - 1989 - History and Philosophy of the Life Sciences 16 (2):355.details
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In search of mechanisms: discoveries across the life sciences.Carl F. Craver - 2013 - London: University of Chicago Press. Edited by Lindley Darden.details
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Big Data Biology: Between Eliminative Inferences and Exploratory Experiments.Emanuele Ratti - 2015 - Philosophy of Science 82 (2):198-218.details
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Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism.Juan M. Durán & Nico Formanek - 2018 - Minds and Machines 28 (4):645-666.details
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Unmasking Clever Hans Predictors and Assessing What Machines Really Learn.Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek & Klaus-Robert Müller - 2019 - Nature Communications 10 (1):1--8.details
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Aspects of Theory-Ladenness in Data-Intensive Science.Wolfgang Pietsch - 2015 - Philosophy of Science 82 (5):905-916.details
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Cynthia Rudin - 2019 - Nature Machine Intelligence 1.details
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