- Spotting When Algorithms Are Wrong.Stefan Buijsman & Herman Veluwenkamp - 2023 - Minds and Machines 33 (4):541-562.details
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Theorem proving in artificial neural networks: new frontiers in mathematical AI.Markus Pantsar - 2024 - European Journal for Philosophy of Science 14 (1):1-22.details
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On the Opacity of Deep Neural Networks.Anders Søgaard - forthcoming - Canadian Journal of Philosophy:1-16.details
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AI and the need for justification (to the patient).Anantharaman Muralidharan, Julian Savulescu & G. Owen Schaefer - 2024 - Ethics and Information Technology 26 (1):1-12.details
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The Cost of Prediction.Johannes Lenhard, Simon Stephan & Hans Hasse - manuscriptdetails
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La deriva genética como fuerza evolutiva.Ariel Jonathan Roffé - 2015 - In J. Ahumada, N. Venturelli & S. Seno Chibeni (eds.), Selección de Trabajos del IX Encuentro AFHIC y las XXV Jornadas de Epistemología e Historia de la ciencia. pp. 615-626.details
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Models, Fictions and Artifacts.Tarja Knuuttila - 2021 - In Wenceslao J. Gonzalez (ed.), Language and Scientific Research. Springer Verlag. pp. 199-22.details
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Computational Modeling in Philosophy.Simon Scheller, Merdes Christoph & Stephan Hartmann (eds.) - 2022details
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From Models to Simulations.Franck Varenne - 2018 - London, UK: Routledge.details
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Homepage Eckhart Arnold.Eckhart Arnold (ed.) - 2001 - Munich: Preprint.details
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Scientific Exploration and Explainable Artificial Intelligence.Carlos Zednik & Hannes Boelsen - 2022 - Minds and Machines 32 (1):219-239.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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Two Exploratory Uses for General Circulation Models in Climate Science.Joseph Wilson - 2021 - Perspectives on Science 29 (4):493-509.details
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Models, Parameterization, and Software: Epistemic Opacity in Computational Chemistry.Frédéric Wieber & Alexandre Hocquet - 2020 - Perspectives on Science 28 (5):610-629.details
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Transparency and the Black Box Problem: Why We Do Not Trust AI.Warren J. von Eschenbach - 2021 - Philosophy and Technology 34 (4):1607-1622.details
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Markets, market algorithms, and algorithmic bias.Philippe van Basshuysen - 2022 - Journal of Economic Methodology 30 (4):310-321.details
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Can we trust Big Data? Applying philosophy of science to software.John Symons & Ramón Alvarado - 2016 - Big Data and Society 3 (2).details
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Epistemic Entitlements and the Practice of Computer Simulation.John Symons & Ramón Alvarado - 2019 - Minds and Machines 29 (1):37-60.details
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Epistemic injustice and data science technologies.John Symons & Ramón Alvarado - 2022 - Synthese 200 (2):1-26.details
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Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.details
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Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.details
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Creating Convincing Simulations in Astrophysics. [REVIEW]Mikaela Sundberg - 2012 - Science, Technology, and Human Values 37 (1):64-87.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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Peeking Inside the Black Box: A New Kind of Scientific Visualization.Michael T. Stuart & Nancy J. Nersessian - 2018 - Minds and Machines 29 (1):87-107.details
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Agnostic Science. Towards a Philosophy of Data Analysis.D. C. Struppa - 2011 - Foundations of Science 16 (1):1-20.details
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Protecting rainforest realism: James Ladyman, Don Ross: Everything must go: metaphysics naturalized, Oxford: Oxford University Press, 2007, pp. 368 £49.00 HB.P. Kyle Stanford, Paul Humphreys, Katherine Hawley, James Ladyman & Don Ross - 2010 - Metascience 19 (2):161-185.details
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The Automated Laplacean Demon: How ML Challenges Our Views on Prediction and Explanation.Sanja Srećković, Andrea Berber & Nenad Filipović - 2021 - Minds and Machines 32 (1):159-183.details
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Validating the Universe in a Box.Chris Smeenk & Sarah C. Gallagher - 2020 - Philosophy of Science 87 (5):1221-1233.details
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Metaphysics within Chemical Physics: The Case of Ab Initio Molecular Dynamics. [REVIEW]Carsten Seck - 2012 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 43 (2):361-375.details
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Dealing with Molecular Complexity. Atomistic Computer Simulations and Scientific Explanation.Julie Schweer & Marcus Elstner - 2023 - Perspectives on Science 31 (5):594-626.details
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Computational modeling in philosophy: introduction to a topical collection.Simon Scheller, Christoph Merdes & Stephan Hartmann - 2022 - Synthese 200 (2):1-10.details
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A practical philosophy of complex climate modelling.Gavin A. Schmidt & Steven Sherwood - 2015 - European Journal for Philosophy of Science 5 (2):149-169.details
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Model Organisms as Scientific Representations.Lorenzo Sartori - forthcoming - British Journal for the Philosophy of Science.details
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What is a Computer Simulation? A Review of a Passionate Debate.Nicole J. Saam - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (2):293-309.details
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Connecting ethics and epistemology of AI.Federica Russo, Eric Schliesser & Jean Wagemans - forthcoming - AI and Society:1-19.details
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The Epistemic Importance of Technology in Computer Simulation and Machine Learning.Michael Resch & Andreas Kaminski - 2019 - Minds and Machines 29 (1):1-9.details
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Mental evolution: a review of Daniel Dennett’s From Bacteria to Bach and Back. [REVIEW]Charles A. Rathkopf - 2017 - Biology and Philosophy 32 (6):1355-1368.details
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A Minimalist Epistemology for Agent-Based Simulations in the Artificial Sciences.Giuseppe Primiero - 2019 - Minds and Machines 29 (1):127-148.details
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Automated opioid risk scores: a case for machine learning-induced epistemic injustice in healthcare.Giorgia Pozzi - 2023 - Ethics and Information Technology 25 (1):1-12.details
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Humanistic interpretation and machine learning.Juho Pääkkönen & Petri Ylikoski - 2021 - Synthese 199:1461–1497.details
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Agent-based Models as Fictive Instantiations of Ecological Processes.Steven L. Peck - 2012 - Philosophy, Theory, and Practice in Biology 4 (20130604).details
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Introduction to Assessing climate models: knowledge, values and policy.Joel Katzav & Wendy S. Parker - 2015 - European Journal for Philosophy of Science 5 (2):141-148.details
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Are machines radically contextualist?Ryan M. Nefdt - 2023 - Mind and Language 38 (3):750-771.details
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A Puzzle concerning Compositionality in Machines.Ryan M. Nefdt - 2020 - Minds and Machines 30 (1):47-75.details
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The computational philosophy: simulation as a core philosophical method.Conor Mayo-Wilson & Kevin J. S. Zollman - 2021 - Synthese 199 (1-2):3647-3673.details
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Expert judgment in climate science: How it is used and how it can be justified.Mason Majszak & Julie Jebeile - 2023 - Studies in the History and Philosophy of Science 100 (C):32-38.details
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Mesoscopic modeling as a cognitive strategy for handling complex biological systems.Miles MacLeod & Nancy J. Nersessian - 2019 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 78:101201.details
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Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2018 - History and Philosophy of the Life Sciences 40 (1):17.details
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Traveling with TARDIS. Parameterization and transferability in molecular modeling and simulation.Johannes Lenhard & Hans Hasse - 2023 - Synthese 201 (4):1-18.details
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Holism, or the Erosion of Modularity: A Methodological Challenge for Validation.Johannes Lenhard - 2018 - Philosophy of Science 85 (5):832-844.details
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