Preprint

Aaronson, Scott (2011) Why Philosophers Should Care About Computational Complexity. [Preprint]

Barrett, Jeffrey A. (2015) On the Evolution of Truth. [Preprint]

Barrett, Jeffrey A. and Skyrms, Brian (2015) Self-Assembling Games. [Preprint]

Barrett, Jeffrey A. and Skyrms, Brian and Cochran, Calvin (2018) Hierarchical Models for the Evolution of Compositional Language. [Preprint]

Bartlett, Steven James (2015) THE SPECIES PROBLEM AND ITS LOGIC: Inescapable Ambiguity and Framework-relativity. [Preprint]

Briegel, Hans and Müller, Thomas (2014) A chance for attributable agency. [Preprint]

Browning, Heather and Veit, Walter (2022) Longtermism and Animals. [Preprint]

Buckner, Cameron (2019) The Comparative Psychology of Artificial Intelligences. [Preprint]

Buckner, Cameron (2023) Deeply Rational Machines -- What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence -- Sample Chapter 1 -- "Moderate Empiricism and Machine Learning". [Preprint]

Buckner, Cameron (2018) Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks. [Preprint]

Coelho Mollo, Dimitri (2022) Intelligent Behaviour. [Preprint]

Colombo, Matteo (2015) Why Build a Virtual Brain? Large-scale Neural Simulations as Test-bed for Artificial Computing Systems. [Preprint]

Datteri, Edoardo and Laudisa, Federico (2016) Large-scale simulations of brain mechanisms: beyond the synthetic method. [Preprint]

Datteri, Edoardo (2020) Interactive Biorobotics. [Preprint]

Datteri, Edoardo (2016) The epistemic value of brain-machine systems for the study of the brain. [Preprint]

De Pretis, Francesco and Landes, Juergen and Peden, William and Osimani, Barbara (2021) Pharmacovigilance as Personalized Medicine. In: Chiara Beneduce and Marta Bertolaso (eds.) Personalized Medicine: A Multidisciplinary Approach to Complexity, Springer Nature. [Preprint]

Dotan, Ravit (2020) Theory Choice, Non-epistemic Values, and Machine Learning. [Preprint]

Duede, Eamon (2022) Instruments, Agents, and Artificial Intelligence: Novel Epistemic Categories of Reliability. [Preprint]

Ellman, Roger (1997) Mental Processes -- How the Mind Arises from the Brain. [Preprint]

Eva, Benjamin and Shear, Ted and Fitelson, Branden (2020) Four Approaches to Supposition. [Preprint]

Floridi, Luciano (2005) Consciousness, Agents and the Knowledge Game. [Preprint]

Gao, Shan (2001) A possible quantum basis of panpsychism. [Preprint]

Gonçalves, Bernardo (2021) Can machines think? The controversy that led to the Turing test. [Preprint]

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

Greif, Hajo (2020) Invention, Intension and the Limits of Computation. [Preprint]

Helman, Daniel (2022) Finding or Creating a Living Organism? Past and Future Thought Experiments in Astrobiology Applied to Artificial Intelligence. [Preprint]

Holster, Andrew (2003) An Introduction to Pavel Tichy and Transparent Intensional Logic. [Preprint]

Kasirzadeh, Atoosa (2022) In conversation with Artificial Intelligence: aligning language models with human values. [Preprint]

Knight, Andrew (2020) Relativistic Implications for Physical Copies of Conscious States. [Preprint]

LaCroix, Travis (2022) The Linguistic Blind Spot of Value-Aligned Agency, Natural and Artificial. [Preprint]

LaCroix, Travis (2022) Moral Dilemmas for Moral Machines. [Preprint]

List, Christian (2015) What is it like to be a group agent? [Preprint]

Livengood, Jonathan and Sytsma, Justin (2017) Empirical Investigations: Reflecting on Turing and Wittgenstein on Thinking Machines. [Preprint]

López-Rubio, Ezequiel (2020) The Big Data razor. [Preprint]

López-Rubio, Ezequiel and Ratti, Emanuele (2019) Data science and molecular biology: prediction and mechanistic explanation. [Preprint]

Mann, Stephen Francis and Gregory, Daniel (2023) Might text-davinci-003 have inner speech? [Preprint]

Miller, Ryan (2021) Does Artificial Intelligence Use Private Language? [Preprint]

Moruzzi, Caterina (2020) Measuring Creativity: An Account of Natural and Artificial Creativity. [Preprint]

Mussgnug, Alexander (2022) The Predictive Reframing of Machine Learning Applications: Good Predictions and Bad Measurements. [Preprint]

Müller, Thomas and Briegel, Hans (2016) Stochastic libertarianism: How to maintain integrity in action without determinism. [Preprint]

Neth, Sven (2022) A Dilemma for Solomonoff Prediction. [Preprint]

Patil, Kaustubh R. and Heinrichs, Bert (2022) Verifiability as a Complement to AI Explainability: A Conceptual Proposal. [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]

Ramstead, Maxwell J. D. and Kirchhoff, Michael D. and Friston, Karl J. (2019) A tale of two densities: Active inference is enactive inference. [Preprint]

Ratti, Emanuele (2020) What Kind of Novelties Can Machine Learning Possibly Generate? The Case of Genomics. [Preprint]

Rochefort-Maranda, Guillaume and Liu, Mo (2019) Finding True Clusters: On the Importance of Simplicity in Science. [Preprint]

Räz, Tim (2016) The Necessity of Learning for Agency. [Preprint]

Saba, Walid (2019) On the Winograd Schema: Situating Language Understanding in the Data-Information-Knowledge Continuum. [Preprint]

Saint-Mont, Uwe (2016) Roads to Consciousness: Crucial steps in mental development. [Preprint]

Schubbach, Arno (2019) Judging Machines. Philosophical Aspects of Deep Learning. [Preprint]

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]

Sterrett, Susan G. (1999) Turing's Two Tests for Intelligence. [Preprint]

Stoica, Cristi (2008) Turing test, easy to pass; human mind, hard to understand. [Preprint]

Stoica, Ovidiu Cristinel (2008) Convergence and free-will. [Preprint]

Taddeo, Mariarosaria and Floridi, Luciano (2008) A Praxical Solution of the Symbol Grounding Problem. [Preprint]

Taddeo, Mariarosaria and Floridi, Luciano (2005) Solving the Symbol Grounding Problem: a Critical Review of Fifteen Years of Research. [Preprint]

Thagard, Paul (2021) Energy Requirements Undermine Substrate Independence and Mind-Body Functionalism. [Preprint]

Thompson, Jessica A. F. (2018) Towards a common theory of explanation for artificial and biological intelligence. [Preprint]

Twardy, Charles R. and Korb, Kevin B. and Oppy, Graham and Handfield, Toby (2005) Token causation by probabilistic active paths. [Preprint]

Veit, Walter and Browning, Heather (2023) Defending Sentientism. [Preprint]

Vorobyev, Oleg Yu (2016) Postulating the theory of experience and chance as a theory of co~events (co~beings). [Preprint]

Wallace, Rodrick (2008) Lurching Toward Chernobyl: Dysfunctions of Real-Time Computation. [Preprint]

Wallace, Rodrick (2006) New mathematical foundations for AI and Alife: Are the necessary conditions for animal consciousness sufficient for the design of intelligent machines? [Preprint]

Weinberger, Naftali (2022) Path-Specific Discrimination. [Preprint]

Wheeler, Gregory (2016) Machine Epistemology and Big Data. [Preprint]

Williamson, Jon (2020) A Bayesian account of establishing. [Preprint]

vincenzo, fano and pierluigi, graziani (2011) On the necessary philosophical premises of the Goedelian arguments. [Preprint]

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.

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.

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

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.

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

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.

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.