Notas sobre el tránsitoepistemológico de la inteligencia artificial (AIai)

Daniel Steven Moran Pizarro; Sandra Johana Dominguez Bonilla; Carolina Castaño Gutierrez

doi:10.22490/25394088.8480

Vol. 18 No. 3 (2024): Especial edition Expotech

Published 2024-10-10

license

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

When the Publicaciones e Investigaciones Journal receives an original study or article from its author(s), whether by email, postal service, or the platforms available for said purpose, know that it may be published in physical or electronic formats in national or international archives, databases, or SIRES. As such, Publications and Research authorizes the reproduction and citation of said material, provided that the description of information is carried out in conformity with bibliographic norms, and mention the corresponding names, authors, article, issue, and pages. Publications and Research, in advance, expresses that the information, concepts, and methods are the responsibility of the author(s). As such, the UNAD does not have any influence whatsoever over that expressed in the manuscript.

Review article

Notes on the epistemological transition of artificial intelligence (AIai)

DOI: https://doi.org/10.22490/25394088.8480

Daniel Steven Moran Pizarro Universidad Nacional Abierta y a Distancia

Sandra Johana Dominguez Bonilla Universidad Nacional Abierta y a Distancia

Carolina Castaño Gutierrez Universidad Nacional Abierta y a Distancia

PDF (Spanish)

XML (Spanish)

Abstract
References

Artificial intelligence (AI) has traversed through multiple paradigms that have drastically changed human understanding of these technologies. Originally based on symbolic rules, AI has migrated towards connectionist approaches, with a current surge in neural networks and deep learning. This paper analyzes this epistemological transition, examining contemporary ethical and conceptual debates surrounding machine capabilities. It is concluded that we are in a historical singularity, with challenges still open to understanding the foundations of the new AI.

keywords: Artificial Intelligence, Connectionism, Epistemological Perspectives, Knowledge Representation, Neural Networks

Alevizos, V., Georgousis, I., Simasiku, A., Messinis, A., Karypidou, S., & Malliarou, D. (2024). Evaluating the Inclusiveness of Artificial Intelligence Software in Enhancing Project Management Efficiency—A review and examples of quantitative measurement methods. International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024. Scopus. https://doi.org/10.1109/ACDSA59508.2024.10467463

Al-Hassan, M.-A. (2023). Revolutionizing Methods and Methodologies: Advancing Indigenous-Centered Research Methodologies in User Experience Research (UXR), Technical and Professional Communication Practice. 103-109. Scopus. https://doi.org/10.1145/3615335.3623018

Anderson, M. M. (2024). AI as Philosophical Ideology: A Critical look back at John McCarthy’s Program. Philosophy and Technology, 37(2). Scopus. https://doi.org/10.1007/s13347-024-00731-1

Berman, M. (1986). The cybernetic dream of the twenty-first century. Journal of Humanistic Psychology, 26(2), 24-51. Scopus. https://doi.org/10.1177/0022167886262003

Cáceres, E. (2011). Steps toward a Constructivist and Coherentist Theory of Judicial Reasoning in Civil Law Tradition. En Law and Neuroscience: Current Legal Issues (Vol. 13). Scopus. https://doi.org/10.1093/acprof:oso/9780199599844.003.0025

Cantarini, P. (2022). FOR AN ETHICS OF ARTIFICIAL INTELLIGENCE BASED ON POIETHICS. Revista Juridica, 4(71), 892-912. Scopus. https://doi.org/10.26668/revistajur.2316-753X.v4i71.6170

Cariani, P. (1993). To evolve an ear. Epistemological implications of gordon pask’s electrochemical devices. Systems Research, 10(3), 19-33. Scopus. https://doi.org/10.1002/sres.3850100305

Ceccon, L. (2023). Image Learning at the Crossroads Between Human and Artificial Intelligence: A Revived Centrality of Images in Cognition. 631 LNNS, 1038-1049. Scopus. https://doi.org/10.1007/978-3-031-25906-7_114

Christy, L. F. (2022). What is Intelligence? The Looming Philosophical Question behind Artificial Intelligence. Voprosy Filosofii, 2022(10), 208-212. Scopus. https://doi.org/10.21146/0042-8744-2022-10-208-212

Cristianini, N. (1995). Evolution and learning: An epistemological perspective—On some conceptual problems shared by artificial life and artificial intelligence. Axiomathes, 6(3), 429-437. Scopus. https://doi.org/10.1007/BF02228987

Cukurova, M. (2018). A Syllogism for Designing Collaborative Learning Technologies in the Age of AI and Multimodal Data. 11082 LNCS, 291-296. Scopus. https://doi.org/10.1007/978-3-319-98572-5_22

Dascal, M. (1989). Artificial intelligence and philosophy: The knowledge of representation. Systems Research, 6(1), 39-52. Scopus. https://doi.org/10.1002/sres.3850060106

Dias, P. (2019). Can practice based knowledge be formalized? En SpringerBriefs in Applied Sciences and Technology (pp. 103-116). Scopus. https://doi.org/10.1007/978-981-15-1271-1_8

Dixon-Román, E., & Parisi, L. (2020). Data capitalism and the counter futures of ethics in artificial intelligence. Communication and the Public, 5(3-4), 116-121. Scopus. https://doi.org/10.1177/2057047320972029

Duan, W. (2023). The Challenge of Artificial Intelligence Scientists to the Epistemology of Science. Journal of Library and Information Science in Agriculture, 35(11), 4-12. Scopus. https://doi.org/10.13998/j.cnki.issn1002-1248.23-0849

Eden, A. H. (2007). Three paradigms of computer science. Minds and Machines, 17(2), 135-167. Scopus. https://doi.org/10.1007/s11023-007-9060-8

Efimov, A. R., Ageeva, A. V., Krainov, A. G., Fedorov, A. K., Kardymon, O. L., & Starikov, P. P. (2024). Artificial Intelligence in Science: On the Threshold of a New Field of Knowledge? Voprosy Filosofii, 2024(4), 30-41. Scopus. https://doi.org/10.21146/0042-8744-2024-4-30-41

Fowler, T. B. (2021). The Limitations of Artificial Intelligence in Light of Zubiri’s Noology. Quaestio, 21, 233-258. Scopus. https://doi.org/10.1484/J.QUAESTIO.5.128394

Freyberg, S., & Hauser, H. (2023). The morphological paradigm in robotics. Studies in History and Philosophy of Science, 100, 1-11. Scopus. https://doi.org/10.1016/j.shpsa.2023.05.002

Garcia-Aguilar, G. (2024). The Strange and Promising Relationship Between EEG and AI Methods of Analysis. Cognitive Computation, 16(5), 2411-2419. Scopus. https://doi.org/10.1007/s12559-023-10142-7

Gauld, C., & Micoulaud-Franchi, J.-A. (2021). Network analysis by systemic text excavation of the concept of personalized psychiatry and precision. Encephale, 47(4), 341-347. Scopus. https://doi.org/10.1016/j.encep.2020.08.008

Goodfellow, I. G., Bengio, Y., & Courville, A. C. (2016). Deep learning. Massachusetts Institute of Technology. https://dialnet.unirioja.es/servlet/libro?codigo=740537

Hallsworth, J. E., Udaondo, Z., Pedrós-Alió, C., Höfer, J., Benison, K. C., Lloyd, K. G., Cordero, R. J. B., de Campos, C. B. L., Yakimov, M. M., & Amils, R. (2023). Scientific novelty beyond the experiment. Microbial Biotechnology, 16(6), 1131-1173. Scopus. https://doi.org/10.1111/1751-7915.14222

Heiden, B., Tonino-Heiden, B., & Alieksieiev, V. (2022). System Ordering Process Based on Uni-, Bi- and Multidirectionality – Theory and First Examples. 107, 594-604. Scopus. https://doi.org/10.1007/978-3-030-92632-8_55

Irwin, R., & White, T. H. (2019). Decolonising Technological Futures: A dialogical tryptich between Te Haumoana White, Ruth Irwin, and Tegmark’s Artificial Intelligence. Futures, 112. Scopus. https://doi.org/10.1016/j.futures.2019.06.003

Le Moigne, J.-L. (2002). On the exceptional epistomological manifesto: Symbols and Search. Revue d’Intelligence Artificielle, 16(1-2), 251-268. Scopus. https://doi.org/10.3166/ria.16.251-268

Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-Based Learning Applied to Document Recognition. Proceedings of the IEEE, 86, 2278-2324. https://doi.org/10.1109/5.726791

Lee, S. E., Ju, N., & Lee, K.-H. (2023). Service chatbot: Co-citation and big data analysis toward a review and research agenda. Technological Forecasting and Social Change, 194. Scopus. https://doi.org/10.1016/j.techfore.2023.122722

Luger, G. F. (2021). Knowing our world: An artificial intelligence perspective (p. 256). Scopus. https://doi.org/10.1007/978-3-030-71873-2

Magnani, L. (1995). Creative Processes in Scientific Discovery. European Journal of High Ability, 6(2), 160-169. Scopus. https://doi.org/10.1080/0937445940060260

Mariotti, S. (2021). Forging a new alliance between economics and engineering. Journal of Industrial and Business Economics, 48(4), 551-572. Scopus. https://doi.org/10.1007/s40812-021-00187-w

Mariotti, S. (2022). The economics–engineering nexus: Response to the commentaries. Journal of Industrial and Business Economics, 49(1). Scopus. https://doi.org/10.1007/s40812-021-00203-z

McGranaghan, R. M. (2024). Complexity Heliophysics: A Lived and Living History of Systems and Complexity Science in Heliophysics. Space Science Reviews, 220(5). Scopus. https://doi.org/10.1007/s11214-024-01081-2

Mikhaylovskiy, N. (2020). How do you test the strength of ai? 12177 LNAI, 257-266. Scopus. https://doi.org/10.1007/978-3-030-52152-3_27

Minsky, M. (1961). Steps toward Artificial Intelligence. Proceedings of the IRE, 49(1), 8-30. https://doi.org/10.1109/JRPROC.1961.287775

Minsky, M., & Papert, S. A. (2017). Perceptrons: An Introduction to Computational Geometry. The MIT Press. https://doi.org/10.7551/mitpress/11301.001.0001

Ovalle, A., Subramonian, A., Gautam, V., Gee, G., & Chang, K.-W. (2023). Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness. 496-511. Scopus. https://doi.org/10.1145/3600211.3604705

Raza, S. A. (2022). A paradigm shift to ethical decision-making—Incorporating systemic epistemology into complex socio-technical decision support systems research. Journal of Decision Systems, 32(1), 177-200. Scopus. https://doi.org/10.1080/12460125.2021.2015840

Reizinger, P. (2023). The Falsificationist View of Machine Learning. Informacios Tarsadalom, 23(2), 117-127. Scopus. https://doi.org/10.22503/INFTARS.XXIII.2023.2.7

Rhode, W., & Morik, K. (2022). Introduction. En Discovery in Physics (pp. 1-29). Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147942407&partnerID=40&md5=d7d8ab5fd57ac9bae987ad54855ad088

Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6), 386-408. https://doi.org/10.1037/h0042519

Rumelhart, E., D., Mcclelland, J., & L., J. (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Volume 1. Foundations.

Shedlock, K., & Hudson, P. (2022). Kaupapa Māori concept modelling for the creation of Māori IT Artefacts. Journal of the Royal Society of New Zealand, 52(S1), 18-32. Scopus. https://doi.org/10.1080/03036758.2022.2070223

Silano, J. A. (2024). Towards abundant intelligences: Considerations for Indigenous perspectives in adopting artificial intelligence technology. Healthcare Management Forum, 37(5), 329-333. Scopus. https://doi.org/10.1177/08404704241257144

Souza, M. (2020). Towards a Theory of Hyperintensional Belief Change. 12320 LNAI, 272-287. Scopus. https://doi.org/10.1007/978-3-030-61380-8_19

Sukkar, A. W., Fareed, M. W., Yahia, M. W., Mushtaha, E., & de Giosa, S. L. (2024). Artificial Intelligence Islamic Architecture (AIIA): What Is Islamic Architecture in the Age of Artificial Intelligence? Buildings, 14(3). Scopus. https://doi.org/10.3390/buildings14030781

TURING, A. M. (1950). I.—COMPUTING MACHINERY AND INTELLIGENCE. Mind, LIX(236), 433-460. https://doi.org/10.1093/mind/LIX.236.433

Van Gigch, J. P. (1990). Systems science, the discipline of epistemological domains, contributes to the design of the intelligent global web. Behavioral Science, 35(2), 122-137. Scopus. https://doi.org/10.1002/bs.3830350205

Van Gigch, J. P., & Le Moigne, J. L. (1989). A paradigmatic approach to the discipline of information systems. Behavioral Science, 34(2), 128-147. Scopus. https://doi.org/10.1002/bs.3830340203

Varkey, P., & Gmytrasiewicz, P. (2011). Resource bounded decision-theoretic bargaining with finite interactive epistemologies. 2, 219-225. Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960117569&partnerID=40&md5=779c2d4d5cc199a6862184e9a4245d41

Viniegra-Velázquez, L. (2020). Colonialism, science, and health. Boletin Medico del Hospital Infantil de Mexico, 77(4), 166-177. Scopus. https://doi.org/10.24875/BMHIM.20000069

license

How to Cite

Moran Pizarro, D. S., Dominguez Bonilla, S. J., & Castaño Gutierrez, C. (2024). Notes on the epistemological transition of artificial intelligence (AIai). Publicaciones E Investigación, 18(3). https://doi.org/10.22490/25394088.8480

Download Citation

Almétricas