- A Knower Without a Voice: Co-Reasoning with Machine Learning.Eleanor Gilmore-Szott & Ryan Dougherty - 2024 - American Journal of Bioethics 24 (9):103-105.details
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Percentages and reasons: AI explainability and ultimate human responsibility within the medical field.Eva Winkler, Andreas Wabro & Markus Herrmann - 2024 - Ethics and Information Technology 26 (2):1-10.details
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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.details
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Axe the X in XAI: A Plea for Understandable AI.Andrés Páez - forthcoming - In Juan Manuel Durán & Giorgia Pozzi (eds.), Philosophy of science for machine learning: Core issues and new perspectives. Springer.details
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Algorithms Don’t Have A Future: On the Relation of Judgement and Calculation.Daniel Stader - 2024 - Philosophy and Technology 37 (1):1-29.details
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The Explanatory Role of Machine Learning in Molecular Biology.Fridolin Gross - forthcoming - Erkenntnis:1-21.details
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KI:Text: Diskurse über KI-Textgeneratoren.Gerhard Schreiber & Lukas Ohly (eds.) - 2024 - De Gruyter.details
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Linguistic Competence and New Empiricism in Philosophy and Science.Vanja Subotić - 2023 - Dissertation, University of Belgradedetails
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Allure of Simplicity.Thomas Grote - 2023 - Philosophy of Medicine 4 (1).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 virtues of interpretable medical AI.Joshua Hatherley, Robert Sparrow & Mark Howard - forthcoming - Cambridge Quarterly of Healthcare Ethics.details
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Understanding, Idealization, and Explainable AI.Will Fleisher - 2022 - Episteme 19 (4):534-560.details
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The virtues of interpretable medical artificial intelligence.Joshua Hatherley, Robert Sparrow & Mark Howard - forthcoming - Cambridge Quarterly of Healthcare Ethics.details
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Defining the undefinable: the black box problem in healthcare artificial intelligence.Jordan Joseph Wadden - 2022 - Journal of Medical Ethics 48 (10):764-768.details
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The Importance of Understanding Deep Learning.Tim Räz & Claus Beisbart - 2024 - Erkenntnis 89 (5).details
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The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems.Kathleen Creel & Deborah Hellman - 2022 - Canadian Journal of Philosophy 52 (1):26-43.details
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Conceptual challenges for interpretable machine learning.David S. Watson - 2022 - Synthese 200 (2):1-33.details
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Explanations in AI as Claims of Tacit Knowledge.Nardi Lam - 2022 - Minds and Machines 32 (1):135-158.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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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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What is Interpretability?Adrian Erasmus, Tyler D. P. Brunet & Eyal Fisher - 2021 - Philosophy and Technology 34:833–862.details
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The State Space of Artificial Intelligence.Holger Lyre - 2020 - Minds and Machines 30 (3):325-347.details
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Prediction versus understanding in computationally enhanced neuroscience.Mazviita Chirimuuta - 2020 - Synthese 199 (1-2):767-790.details
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Artificial intelligence, transparency, and public decision-making.Karl de Fine Licht & Jenny de Fine Licht - 2020 - AI and Society 35 (4):917-926.details
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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).details
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Imagine This: Opaque DLMs are Reliable in the Context of Justification.Logan Carter - manuscriptdetails
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Understanding via exemplification in XAI: how explaining image classification benefits from exemplars.Sara Mann - forthcoming - AI and Society:1-16.details
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ML interpretability: Simple isn't easy.Tim Räz - 2024 - Studies in History and Philosophy of Science Part A 103 (C):159-167.details
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Uncertainty, Evidence, and the Integration of Machine Learning into Medical Practice.Thomas Grote & Philipp Berens - 2023 - Journal of Medicine and Philosophy 48 (1):84-97.details
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(1 other version)The epistemological foundations of data science: a critical review.Luciano Floridi, Mariarosaria Taddeo, Vincent Wang, David Watson & Jules Desai - 2022 - Synthese 200 (6):1-27.details
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How to Make AlphaGo’s Children Explainable.Woosuk Park - 2022 - Philosophies 7 (3):55.details
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The Deception of Certainty: how Non-Interpretable Machine Learning Outcomes Challenge the Epistemic Authority of Physicians. A deliberative-relational Approach.Florian Funer - 2022 - Medicine, Health Care and Philosophy 25 (2):167-178.details
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Putting explainable AI in context: institutional explanations for medical AI.Jacob Browning & Mark Theunissen - 2022 - Ethics and Information Technology 24 (2).details
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Philosophy of science at sea: Clarifying the interpretability of machine learning.Claus Beisbart & Tim Räz - 2022 - Philosophy Compass 17 (6):e12830.details
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Beyond English: Considering Language and Culture in Psychological Text Analysis.Dalibor Kučera & Matthias R. Mehl - 2022 - Frontiers in Psychology 13.details
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Justificatory explanations in machine learning: for increased transparency through documenting how key concepts drive and underpin design and engineering decisions.David Casacuberta, Ariel Guersenzvaig & Cristian Moyano-Fernández - 2024 - AI and Society 39 (1):279-293.details
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Analogue Models and Universal Machines. Paradigms of Epistemic Transparency in Artificial Intelligence.Hajo Greif - 2022 - Minds and Machines 32 (1):111-133.details
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Explanatory pragmatism: a context-sensitive framework for explainable medical AI.Diana Robinson & Rune Nyrup - 2022 - Ethics and Information Technology 24 (1).details
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Empiricism in the foundations of cognition.Timothy Childers, Juraj Hvorecký & Ondrej Majer - 2023 - AI and Society 38 (1):67-87.details
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Black Boxes or Unflattering Mirrors? Comparative Bias in the Science of Machine Behaviour.Cameron Buckner - 2023 - British Journal for the Philosophy of Science 74 (3):681-712.details
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Morality First?Nathaniel Sharadin - forthcoming - AI and Society:1-13.details
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Epistemic Value of Digital Simulacra for Patients.Eleanor Gilmore-Szott - 2023 - American Journal of Bioethics 23 (9):63-66.details
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The black box problem revisited. Real and imaginary challenges for automated legal decision making.Bartosz Brożek, Michał Furman, Marek Jakubiec & Bartłomiej Kucharzyk - 2024 - Artificial Intelligence and Law 32 (2):427-440.details
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Assembled Bias: Beyond Transparent Algorithmic Bias.Robyn Repko Waller & Russell L. Waller - 2022 - Minds and Machines 32 (3):533-562.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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Accuracy and Interpretability: Struggling with the Epistemic Foundations of Machine Learning-Generated Medical Information and Their Practical Implications for the Doctor-Patient Relationship.Florian Funer - 2022 - Philosophy and Technology 35 (1):1-20.details
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Values and inductive risk in machine learning modelling: the case of binary classification models.Koray Karaca - 2021 - European Journal for Philosophy of Science 11 (4):1-27.details
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What Kind of Artificial Intelligence Should We Want for Use in Healthcare Decision-Making Applications?Jordan Joseph Wadden - 2021 - Canadian Journal of Bioethics / Revue canadienne de bioéthique 4 (1).details
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Explainability, Public Reason, and Medical Artificial Intelligence.Michael Da Silva - 2023 - Ethical Theory and Moral Practice 26 (5):743-762.details
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Justice and the Normative Standards of Explainability in Healthcare.Saskia K. Nagel, Nils Freyer & Hendrik Kempt - 2022 - Philosophy and Technology 35 (4):1-19.details
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