- A Genealogical Approach to Algorithmic Bias.Marta Ziosi, David Watson & Luciano Floridi - 2024 - Minds and Machines 34 (2):1-17.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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A qualified defense of top-down approaches in machine ethics.Tyler Cook - forthcoming - AI and Society:1-15.details
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On the Philosophy of Unsupervised Learning.David S. Watson - 2023 - Philosophy and Technology 36 (2):1-26.details
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Levels of explicability for medical artificial intelligence: What do we normatively need and what can we technically reach?Frank Ursin, Felix Lindner, Timo Ropinski, Sabine Salloch & Cristian Timmermann - 2023 - Ethik in der Medizin 35 (2):173-199.details
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Self-fulfilling Prophecy in Practical and Automated Prediction.Owen C. King & Mayli Mertens - 2023 - Ethical Theory and Moral Practice 26 (1):127-152.details
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Logic Explained Networks.Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini & Stefano Melacci - 2023 - Artificial Intelligence 314 (C):103822.details
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Artificial agents’ explainability to support trust: considerations on timing and context.Guglielmo Papagni, Jesse de Pagter, Setareh Zafari, Michael Filzmoser & Sabine T. Koeszegi - 2023 - AI and Society 38 (2):947-960.details
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Applying AI for social good: Aligning academic journal ratings with the United Nations Sustainable Development Goals (SDGs).David Steingard, Marcello Balduccini & Akanksha Sinha - 2023 - AI and Society 38 (2):613-629.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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Explaining Machine Learning Decisions.John Zerilli - 2022 - Philosophy of Science 89 (1):1-19.details
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Fairness, explainability and in-between: understanding the impact of different explanation methods on non-expert users’ perceptions of fairness toward an algorithmic system.Doron Kliger, Tsvi Kuflik & Avital Shulner-Tal - 2022 - Ethics and Information Technology 24 (1).details
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Embedded ethics: a proposal for integrating ethics into the development of medical AI.Alena Buyx, Sami Haddadin, Ruth Müller, Daniel Tigard, Amelia Fiske & Stuart McLennan - 2022 - BMC Medical Ethics 23 (1):1-10.details
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Doing versus saying: responsible AI among large firms.Jacques Bughin - forthcoming - AI and Society:1-13.details
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Beyond explainability: justifiability and contestability of algorithmic decision systems.Clément Henin & Daniel Le Métayer - 2022 - AI and Society 37 (4):1397-1410.details
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Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI.Juan Manuel Durán & Karin Rolanda Jongsma - 2021 - Journal of Medical Ethics 47 (5):medethics - 2020-106820.details
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What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research.Markus Langer, Daniel Oster, Timo Speith, Lena Kästner, Kevin Baum, Holger Hermanns, Eva Schmidt & Andreas Sesing - 2021 - Artificial Intelligence 296 (C):103473.details
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Evaluating XAI: A comparison of rule-based and example-based explanations.Jasper van der Waa, Elisabeth Nieuwburg, Anita Cremers & Mark Neerincx - 2021 - Artificial Intelligence 291 (C):103404.details
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Artificial intelligence in medicine and the disclosure of risks.Maximilian Kiener - 2021 - AI and Society 36 (3):705-713.details
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Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability.Mark Coeckelbergh - 2020 - Science and Engineering Ethics 26 (4):2051-2068.details
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The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David Watson - 2019 - Minds and Machines 29 (3):417-440.details
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Responding to uncertainty in emotion recognition.Björn Schuller - 2019 - Journal of Information, Communication and Ethics in Society 17 (3):299-303.details
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No such thing as one-size-fits-all in AI ethics frameworks: a comparative case study.Vivian Qiang, Jimin Rhim & AJung Moon - forthcoming - AI and Society:1-20.details
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Argumentative explanations for pattern-based text classifiers.Piyawat Lertvittayakumjorn & Francesca Toni - 2023 - Argument and Computation 14 (2):163-234.details
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AI Documentation: A path to accountability.Florian Königstorfer & Stefan Thalmann - 2022 - Journal of Responsible Technology 11 (C):100043.details
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Influencing laughter with AI-mediated communication.Gregory Mills, Eleni Gregoromichelaki, Chris Howes & Vladislav Maraev - 2021 - Interaction Studies 22 (3):416-463.details
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Artificial Intelligence Regulation: a framework for governance.Patricia Gomes Rêgo de Almeida, Carlos Denner dos Santos & Josivania Silva Farias - 2021 - Ethics and Information Technology 23 (3):505-525.details
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Towards Transparency by Design for Artificial Intelligence.Heike Felzmann, Eduard Fosch-Villaronga, Christoph Lutz & Aurelia Tamò-Larrieux - 2020 - Science and Engineering Ethics 26 (6):3333-3361.details
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A Teleological Approach to Information Systems Design.Mattia Fumagalli, Roberta Ferrario & Giancarlo Guizzardi - 2024 - Minds and Machines 34 (3):1-35.details
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Expropriated Minds: On Some Practical Problems of Generative AI, Beyond Our Cognitive Illusions.Fabio Paglieri - 2024 - Philosophy and Technology 37 (2):1-30.details
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Explainable AI in the military domain.Nathan Gabriel Wood - 2024 - Ethics and Information Technology 26 (2):1-13.details
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Information-seeking dialogue for explainable artificial intelligence: Modelling and analytics.Ilia Stepin, Katarzyna Budzynska, Alejandro Catala, Martín Pereira-Fariña & Jose M. Alonso-Moral - 2024 - Argument and Computation 15 (1):49-107.details
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On the robustness of sparse counterfactual explanations to adverse perturbations.Marco Virgolin & Saverio Fracaros - 2023 - Artificial Intelligence 316 (C):103840.details
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Explanation and Agency: exploring the normative-epistemic landscape of the “Right to Explanation”.Esther Keymolen & Fleur Jongepier - 2022 - Ethics and Information Technology 24 (4):1-11.details
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Cognitive architectures for artificial intelligence ethics.Steve J. Bickley & Benno Torgler - 2023 - AI and Society 38 (2):501-519.details
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ICAIL Doctoral Consortium, Montreal 2019.Michał Araszkiewicz, Ilaria Angela Amantea, Saurabh Chakravarty, Robert van Doesburg, Maria Dymitruk, Marie Garin, Leilani Gilpin, Daphne Odekerken & Seyedeh Sajedeh Salehi - 2020 - Artificial Intelligence and Law 28 (2):267-280.details
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A top-level model of case-based argumentation for explanation: Formalisation and experiments.Henry Prakken & Rosa Ratsma - 2022 - Argument and Computation 13 (2):159-194.details
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Searching for Features with Artificial Neural Networks in Science: The Problem of Non-Uniqueness.Siyu Yao & Amit Hagar - 2024 - International Studies in the Philosophy of Science 37 (1):51-67.details
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“Please understand we cannot provide further information”: evaluating content and transparency of GDPR-mandated AI disclosures.Alexander J. Wulf & Ognyan Seizov - 2024 - AI and Society 39 (1):235-256.details
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Subjectivity of Explainable Artificial Intelligence.Александр Николаевич Райков - 2022 - Russian Journal of Philosophical Sciences 65 (1):72-90.details
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Ethical challenges in argumentation and dialogue in a healthcare context.Mark Snaith, Rasmus Øjvind Nielsen, Sita Ramchandra Kotnis & Alison Pease - forthcoming - Argument and Computation:1-16.details
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Explainability for experts: A design framework for making algorithms supporting expert decisions more explainable.Auste Simkute, Ewa Luger, Bronwyn Jones, Michael Evans & Rhianne Jones - 2021 - Journal of Responsible Technology 7-8 (C):100017.details
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GLocalX - From Local to Global Explanations of Black Box AI Models.Mattia Setzu, Riccardo Guidotti, Anna Monreale, Franco Turini, Dino Pedreschi & Fosca Giannotti - 2021 - Artificial Intelligence 294 (C):103457.details
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Going beyond the “common suspects”: to be presumed innocent in the era of algorithms, big data and artificial intelligence.Athina Sachoulidou - forthcoming - Artificial Intelligence and Law:1-54.details
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“That's (not) the output I expected!” On the role of end user expectations in creating explanations of AI systems.Maria Riveiro & Serge Thill - 2021 - Artificial Intelligence 298:103507.details
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Defining Explanation and Explanatory Depth in XAI.Stefan Buijsman - 2022 - Minds and Machines 32 (3):563-584.details
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Karl Jaspers and artificial neural nets: on the relation of explaining and understanding artificial intelligence in medicine.Christopher Poppe & Georg Starke - 2022 - Ethics and Information Technology 24 (3):1-10.details
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Sources of Understanding in Supervised Machine Learning Models.Paulo Pirozelli - 2022 - Philosophy and Technology 35 (2):1-19.details
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How to Make AlphaGo’s Children Explainable.Woosuk Park - 2022 - Philosophies 7 (3):55.details
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Predicting inmates misconduct using the SHAP approach.Fábio M. Oliveira, Marcelo S. Balbino, Luis E. Zarate, Fawn Ngo, Ramakrishna Govindu, Anurag Agarwal & Cristiane N. Nobre - 2024 - Artificial Intelligence and Law 32 (2):369-395.details
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