The intersection of philosophy of language and artificial intelligence: Challenges in replicating human language understanding
Sooraj Kumar Maurya
Resumen
This work explores the intersection between the philosophy of language and artificial intelligence (AI), focusing on how machines process human language. Analyzes theories of meaning, reference, and communication in AI systems and evaluates their ability to address linguistic nuances such as context, ambiguity, and the social use of language. It is noteworthy that although AI can simulate some facets of human language, it lacks the
deep, contextual understanding that characterizes humans. The research concluded that, as AI has advanced significantly, there is a fundamental
gap between the human and artificial ability to understand and use languages in a natural and meaningful way.
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Citas
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Davidson, D. (1967). Truth and Meaning. Synthese, 17(1), 304-323.
Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.
Dreyfus, H. L. (1972). What Computers Can't Do: A Critique of Artificial Reason. Harper & Row.
Ekman, P. (1992). An Argument for Basic Emotions. Cognition & Emotion, 6(3-4), 169-200.
Austin, J. L. (1962). How to Do Things with Words. Oxford University Press.
Barsalou, L. W. (2008). Grounded Cognition. Annual Review of Psychology, 59, 617-645.
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623.
Brewster, S., McGookin, D., & Miller, C. (2003). Olfactory Interfaces. Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, 1(1), 654-661.
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., & Amodei, D. (2020). Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165.
Clark, H. H. (1996). Using Language. Cambridge University Press.
Clark, H. H., & Brennan, S. E. (1991). Grounding in Communication. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on Socially Shared Cognition (pp. 127-149). American Psychological Association.
Crawford, K., & Calo, R. (2016). There is a Blind Spot in AI Research. Nature, 538(7625), 311-313.
Davidson, D. (1967). Truth and Meaning. Synthese, 17(1), 304-323.
Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.
Dreyfus, H. L. (1972). What Computers Can't Do: A Critique of Artificial Reason. Harper & Row.
Ekman, P. (1992). An Argument for Basic Emotions. Cognition & Emotion, 6(3-4), 169-200.
Publicado
2024-11-19
Cómo citar
Kumar Maurya, S. (2024). The intersection of philosophy of language and artificial intelligence: Challenges in replicating human language understanding: Sooraj Kumar Maurya. Quórum Académico, 21(2), 12-41. Recuperado a partir de https://produccioncientificaluz.org/index.php/quorum/article/view/42934
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