PhilSci Archive

Items where Subject is "Specific Sciences > Artificial Intelligence"

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Number of items at this level: 120.

A

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

Arsiwalla, Xerxes and Elshatlawy, Hatem and Rickles, Dean (2023) Pregeometry, Formal Language and Constructivist Foundations of Physics. [Preprint]

B

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]

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

Bochman, Alexander (2023) Causal reasoning from almost first principles. [Preprint]

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

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

Buckner, Cameron (2023) From Deep Learning to 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]

Buijsman, Stefan (2023) Causal scientific explanations from Machine Learning. [Preprint]

C

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

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

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

D

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]

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

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) Deep Learning Opacity in Scientific Discovery. In: UNSPECIFIED.

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

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

Durt, Christoph and Froese, Tom and Fuchs, Thomas (2023) Large Language Models and the Patterns of Human Language Use: An Alternative View of the Relation of AI to Understanding and Sentience. [Preprint]

E

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

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]

F

Facchin, Marco and Zanotti, Giacomo (2024) Affective artificial agents as sui generis affective artifacts. [Preprint]

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

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.

G

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

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

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

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.

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]

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

Grujicic, Bojana and Illari, Phyllis (2023) Using deep neural networks and similarity metrics to predict and control brain responses. [Preprint]

H

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]

K

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

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

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

Koskinen, Inkeri (2023) We have no satisfactory social epistemology of AI-based science. [Preprint]

Kästner, Lena and Crook, Barnaby (2023) Don't Fear the Bogeyman: On Why There is No Prediction-Understanding Trade-Off for Deep Learning in Neuroscience. [Preprint]

L

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

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

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

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

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

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]

M

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]

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

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]

N

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

O

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

Ovidiu Cristinel, Stoica (2023) Does a computer think if no one is around to see it? [Preprint]

P

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

Pedro, Leonardo (2023) Non-informative priors vs. Fermi Paradox and Artificial General Intelligence. [Preprint]

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.

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]

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.

R

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

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

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

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]

S

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]

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.

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

Scorzato, Luigi (2024) Reliability and Interpretability in Science and Deep Learning. [Preprint]

Shkliarevsky, Gennady (2023) THE EMPEROR WITH NO CLOTHES: Chomsky Against ChatGPT. [Preprint]

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

Sterkenburg, Tom F. (2018) Universal Prediction.

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]

Sullivan, Emily (2023) Do ML models represent their targets? [Preprint]

T

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]

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

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]

V

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

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

Vernazzani, Alfredo and Coelho Mollo, Dimitri (2023) The Formats of Cognitive Representation: A Computational Account. [Preprint]

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

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

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

W

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]

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

Y

Yee, Adrian K. (2023) Machine Learning, Misinformation, and Citizen Science. [Preprint]

This list was generated on Wed May 22 15:59:45 2024 EDT.