bibliography
- Bacchus, Fahiem, et al. “Reasoning About Noisy Sensors and Effectors in the Situation Calculus.” Artificial Intelligence, vol. 111, nos. 1–2, 1999, pp. 171–208.
- Bansal, Hritik, et al. “How Well can Text-to-Image Generative Models Understand Ethical Natural Language Interventions?” arXiv preprint arXiv:2210.15230, 2022.
- Bender, Emily M., et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 2021.
- Borges, Jorge Luis. “Del rigor en la ciencia.” 1946. Museo de El Hacedor, 1960.
- Brown, Tom, et al. “Language Models are Few-Shot Learners.” Advances in Neural Information Processing Systems, vol. 33, 2020, pp. 1877–901.
- Clark, Andy, and David Chalmers. “The Extended Mind.” analysis, vol. 58, no. 1, 1998, pp. 7–19.
- Crawford, Kate. “Artificial Intelligence’s White Guy Problem.” New York Times, 25 June 2016.
- Curiel, Erik. “The Many Definitions of a Black Hole.” Nature Astronomy, vol. 3, no. 1, 2019, pp. 27–34.
- Davidson, Donald. “Truth and Meaning.” Philosophy, Language, and Artificial Intelligence. Springer, 1967, pp. 93–111.
- Davidson, D. “What Metaphors Mean.” Critical Inquiry, vol. 5, no. 1, 1978, pp. 31–47.
- Davis, Ernest. CS NYU WS Collection, 2011, cs.nyu.edu/faculty/davise/papers/WinogradSchemas/WSCollection. Accessed 12 Aug. 2022.
- De Jager, S. “Semantic Noise in the Winograd Schema Challenge of Pronoun Disambiguation.” Humanities and Social Sciences Communications, vol. 10, no. 1, 2023, pp. 1–10.
- Derrida, J. “White Mythology: Metaphor in the Text of Philosophy.” New Literary History, vol. 6, no. 1, 1974, pp. 5–74.
- Dreyfus, H. What Computers Can’t Do. Harper & Row, 1972.
- Elazar, Yanai, et al. “Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema.” arXiv preprint arXiv:2104.08161, 2021.
- Floridi, Luciano, and Massimo Chiriatti. “GPT-3: Its Nature, Scope, Limits, and Consequences.” Minds and Machines, vol. 30, no. 4, 2020, pp. 681–94.
- Friston, Karl, et al. “The Free Energy Principle Made Simpler But Not too Simple.” arXiv preprint arXiv:2201.06387, 2022.
- Gastaldi, Juan Luis. “Why Can Computers Understand Natural Language?” Philosophy and Technology, vol. 34, no. 1, 2021, pp. 149–214.
- Gebru, Timnit, et al. “Datasheets for Datasets.” Communications of the ACM, vol. 64, no. 12, 2021, pp. 86–92.
- Grice, H.P. Studies in the Way of Words. Harvard UP, 1989.
- Haraway, Donna. “A Cyborg Manifesto.” Socialist Review, 1985.
- Harris, Z. “Distributional Structure.” Papers in Structural and Transformational Linguistics. Springer, 1970, pp. 775–94.
- Hofstadter, Douglas R., and Emmanuel Sander. Surfaces and Essences: Analogy as the Fuel and Fire of Thinking. Basic Books, 2013.
- Kahneman, Daniel, et al. Noise: A Flaw in Human Judgment. HarperCollins, 2022.
- Kocijan, V., et al. “The Defeat of the Winograd Schema Challenge.” arXiv preprint arXiv:2201.02387, 2022.
- Lakoff, George, and Mark Johnson. Metaphors We Live By. U of Chicago P, 2008.
- Levesque, Hector. “The Winograd Schema Challenge.” American Association for Artificial Intelligence, 2011, www.aaai.org.
- Levesque, Hector, et al. “The Winograd Schema Challenge.” Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning, 2012.
- Luo, Xuewen, et al. “Semantic Communications: Overview, Open Issues, and Future Research Directions.” IEEE Wireless Communications, 2022.
- Malaspina, Cécile. An Epistemology of Noise. Bloomsbury, 2018.
- Marcuse, Herbert. One-Dimensional Man: Studies in the Ideology of Advanced Industrial Society. 1964. Routledge, 2007.
- McCarthy, John, et al. “On the Model Theory of Knowledge.” Stanford University, Department of Computer Science Publication, 1978.
- Mikolov, T., et al. “Efficient Estimation of Word Representations in Vector Space.” arXiv preprint, https://arxiv.org/abs/1301.3781, 2013.
- Miller, Tim, et al. “Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences.” arXiv preprint arXiv:1712.00547, 2017.
- Mitchell, Tom, et al. “Never-Ending Learning.” Communications of the ACM, vol. 61, no. 5, 2018, pp. 103–15.
- Morgenstern, Leora, et al. “Planning, Executing, and Evaluating the Winograd Schema Challenge.” AI Magazine, vol. 37, no. 1, 2016, pp. 50–54.
- Nietzsche, F. On Truth and Lie in an Extra-Moral Sense. 1873. Translated by Walter Kaufmann, The Portable Nietzsche, 1988.
- Prado Casanova, Miguel. Noise and Morphogenesis: Uncertainty, Randomness and Control. 2021. Faculty of Health and Applied Sciences, University of the West of England, Bristol, Ph.D. thesis.
- Rahman, Altaf, and Vincent Ng. “Resolving Complex Cases of Definite Pronouns: The Winograd Schema Challenge.” Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012.
- Rieder, Bernhard. Engines of Order: A Mechanology of Algorithmic Techniques. Amsterdam UP, 2020.
- Shanahan, Murray. “Talking About Large Language Models.” arXiv:2212.03551v2 [cs.CL], 11 Dec. 2022.
- Shannon, C.E., and W. Weaver. Mathematical Theory of Communication. 1949. U of Illinois P, 1964.
- Sharma, Arpit. “Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge.” Theory and Practice of Logic Programming, vol. 19, nos. 5–6, 2019, pp. 1021–37.
- Spärck Jones, K. “Language Modelling’s Generative Model: Is It Rational?” Technical Report. Computer Laboratory, University of Cambridge, 2004.
- Speer, Robyn, et al. “Conceptnet 5.5: An Open Multilingual Graph of General Knowledge.” Thirty-First AAAI Conference on Artificial Intelligence, 2017.
- Weaver, Warren. “Translation.” Memorandum, Rockefeller Foundation Archives, 1949.
- Winograd, Terry. Understanding Natural Language. Academic Press, 1972.
- Wolff, J. Gerard. “Interpreting Winograd Schemas Via the SP Theory of Intelligence and Its Realisation in the SP Computer Model.” arXiv preprint arXiv:1810.04554, 2018.
- Xie, Huiqiang, et al. “Deep Learning Based Semantic Communications: An Initial Investigation.” GLOBECOM 2020. 2020 IEEE Global Communications Conference, IEEE, 2020.