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Duran, Juan Manuel (2025) Beyond transparency: computational reliabilism as an externalist epistemology of algorithms. [Preprint] (Submitted)

Duran, Juan Manuel (2023) Machine learning, justification, and computational reliabilism. [Preprint]

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Greif, Hajo (2019) Exploring Minds. Modes of Modelling and Simulation in Artificial Intelligence. [Preprint]

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Pantsar, Markus and Fabry, Regina E. (2024) How Not to Talk about Chatbot Mistakes. [Preprint]

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Peters, Uwe and Carman, Mary (2024) Cultural Bias in Explainable AI Research: A Systematic Analysis. [Preprint]

Peters, Uwe and Ojea Quintana, Ignacio (2024) Are Generics and Negativity about Social Groups Common on Social Media? – A Comparative Analysis of Twitter (X) Data. [Preprint]

Pietsch, Wolfgang (2017) A Causal Approach to Analogy. [Preprint]

Pigozzi, Gabriella (2006) Belief Merging and the Discursive Dilemma: An Argument-Based Account to Paradoxes of Judgment Aggregation. [Preprint]

Pigozzi, Gabriella (2005) Two aggregation paradoxes in social decision making: the Ostrogorski paradox and the discursive dilemma. [Preprint]

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Steinert-Threlkeld, Shane (2019) Towards the Emergence of Non-trivial Compositionality. [Preprint]

Sterrett, S. G. (2014) Turing on the Integration of Human and Machine Intelligence. [Preprint]

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Conference or Workshop Item

Boccignone, Giuseppe and Cordeschi, Roberto (2007) Bayesian models and simulations in cognitive science. In: UNSPECIFIED.

Dawidowicz, Edward and Jackson, Vairzora and Bryant, Thomas E and Adams, Martin (2003) The Right Information… and Intelligent Nodes. In: UNSPECIFIED.

Duede, Eamon (2022) Deep Learning Opacity in Scientific Discovery. In: UNSPECIFIED.

Eberhardt, Frederick and Scheines, Richard (2006) Interventions and Causal Inference. In: UNSPECIFIED.

Grimsley, Christopher (2020) Causal and Non-Causal Explanations of Artificial Intelligence. In: UNSPECIFIED.

Khosrowi, Donal and Finn, Finola (2024) Can Generative AI Produce Novel Evidence? In: UNSPECIFIED.

Kieval, Phillip Hintikka and Westerblad, Oscar (2024) Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules. In: UNSPECIFIED.

Pietsch, Wolfgang (2014) Aspects of theory-ladenness in data-intensive science. In: UNSPECIFIED.

Pietsch, Wolfgang (2013) Big Data – The New Science of Complexity. In: UNSPECIFIED.

Pietsch, Wolfgang (2016) A difference-making account of causation. In: UNSPECIFIED.

Ratti, Emanuele and López-Rubio, Ezequiel (2018) Mechanistic Models and the Explanatory Limits of Machine Learning. In: UNSPECIFIED.

Rushing, Bruce and Gomez-Lavin, Javier (2024) Is the Scaling Hypothesis Falsifiable? In: UNSPECIFIED.

Wilson, Joseph (2024) The ghost in the machine: Metaphors of the ‘virtual’ and the ‘artificial’ in post-WW2 computer science. In: UNSPECIFIED.

Published Article or Volume

Bodanza, Gustavo Adrián (2015) Abstract Argumentation in Artificial Intelligence. Problems of Interpretation and Adequacy of Semantics for Decision Making. THEORIA. An International Journal for Theory, History and Foundations of Science, 30 (3). pp. 395-414. ISSN 2171-679X

Colaço, David (2024) When remediating one artifact results in another: control, confounders, and correction. History and Philosophy of the Life Sciences, 46 (5).

Friederich, Simon (2023) Symbiosis, not alignment, as the goal for liberal democracies in the transition to artificial general intelligence. AI and Ethics.

Friederich, Simon and Symons, Jonathan (2023) Norms for Academic Writing in the Era of Advanced Artificial Intelligence. Digital Society, 2.

Gao, Shan (2023) Does quantum cognition imply quantum minds? Journal of Consciousness Studies, 28 (3-4). pp. 100-111.

Gonçalves, Bernardo (2021) Machines will think: structure and interpretation of Alan Turing’s imitation game. The Digital Library of Theses and Dissertations of the University of São Paulo. pp. 1-291.

Graves, Mark and Ratti, Emanuele (2022) Who Is a Good Data Scientist? A Reply to Curzer and Epstein. Philosophy & Technology, 35.

Kasirzadeh, Atoosa (2022) Taxonomy of Risks posed by Language Models. FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. pp. 214-229.

Ling, Maurice HT (2012) Re-creating the Philosopher’s Mind: Artificial Life from Artificial Intelligence. Human-Level Intelligence, 3. p. 1. ISSN 2219-5173

List, Christian (2021) Group Agency and Artificial Intelligence. Philosophy & Technology, Online.

Miller, Ryan (2023) Holding Large Language Models to Account. Proceedings of the AISB Convention 2023. pp. 7-14.

Miłkowski, Marcin (2017) Situatedness and Embodiment of Computational Systems. Entropy, 19 (4). p. 162. ISSN 1099-4300

Otsuka, Jun (2021) Why does statistics matter to philosophy? Tetsugaku-Kenkyu (The Journal of Philosophical Studies), 606. pp. 1-24. ISSN 0386-9563

Plutniak, Sébastien (2017) Is an archaeological contribution to the theory of social science possible? Archaeological data and concepts in the dispute between Jean-Claude Gardin and Jean-Claude Passeron. Palethnologie, 9. pp. 7-21.

Ratti, Emanuele (2022) Integrating Artificial Intelligence in Scientific Practice: Explicable AI as an Interface. Philosophy & Technology, 35.

Reynolds, Jack (2024) Framing the Predictive Mind: Why we should think again about Dreyfus. Phenomenology and the cognitive sciences. ISSN 1572-8676

Sarma, Gopal P. and Faundez, Victor (2017) Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices. Cellular Logistics, 7 (4).

Sarma, Gopal P. and Hay, Nick J. (2017) Mammalian Value Systems. Informatica, 41 (4). pp. 441-449.

Sarma, Gopal P. and Hay, Nick J. (2017) Mammalian Value Systems. Informatica, 41 (4). pp. 441-449.

Sarma, Gopal P. and Hay, Nick J. (2017) Robust Computer Algebra, Theorem Proving, and Oracle AI. Informatica, 41 (4). pp. 451-461.

Sterkenburg, Tom F. (2018) Universal Prediction.

Tamir, Michael and Elay, Shech (2023) Machine Understanding and Deep Learning Representation. Synthese, 201 (51). ISSN 1573-0964

Votsis, Ioannis (2016) Ad Hoc Hypotheses and the Monsters within. Fundamental Issues of Artificial Intelligence. pp. 299-313.

Open Access Book

Leonelli, Sabina and Tempini, N (2020) Data Journeys in the Sciences. Springer.

Other

Vaas, Ruediger (2006) Dark Energy And Life's Ultimate Future. UNSPECIFIED.