Alucinaciones de la inteligencia artificial: impacto en tecnología, política y sociedad

Buchanan, B. G. (2005). A (very) brief history of artificial intelligence. Ai Magazine, 26(4), 53-53.

Chen, Y., Fu, Q., Yuan, Y., Wen, Z., Fan, G., Liu, D., ... & Xiao, Y. (2023, October). Hallucination detection: Robustly discerning reliable answers in large language models. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (pp. 245-255).

Cipolla, C. M., & Altan. (2015). Le leggi fondamentali della stupidità umana. Il mulino.

Dechter, R. (1986). Learning while searching in constraint-satisfaction problems. https://n9.cl/f8jd2

Dziri, N., Milton, S., Yu, M., Zaiane, O., & Reddy, S. (2022). On the origin of hallucinations in conversational models: Is it the datasets or the models? arXiv preprint arXiv:2204.07931

Floridi, L. (2020). AI and its new winter: From myths to realities. Philosophy & Technology, 33, 1-3.

Fradkov, A. L. (2020). Early history of machine learning. IFAC-PapersOnLine, 53(2), 1385-1390.

Gugerty, L. (2006). Newell and Simon's logic theorist: Historical background and impact on cognitive modeling. In Proceedings of the human factors and ergonomics society annual meeting 50(9), 880-884). Sage CA. SAGE Publications.

Hatem, R., Simmons, B., & Thornton, J. E. (2023). A Call to Address AI “Hallucinations” and How Healthcare Professionals Can Mitigate Their Risks. Cureus, 15(9).

Haugeland, J. (1989). Artificial intelligence: The very idea. MIT press.

IBM. (2024, April 11). What are ai hallucinations? https://n9.cl/3tvd4

Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., ... & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), 1-38.

Lee, K., Firat, O., Agarwal, A., Fannjiang, C., & Sussillo, D. (2018). Hallucinations in neural machine translation. https://n9.cl/0s0vb

Li, Z. (2023). The dark side of ChatGPT: legal and ethical challenges from stochastic parrots and hallucination. arXiv preprint arXiv:2304.14347

Luo, J., Li, T., Wu, D., Jenkin, M., Liu, S., & Dudek, G. (2024). Hallucination Detection and Hallucination Mitigation: An Investigation. arXiv preprint arXiv:2401.08358

Merriam-Webster. (s. f.). Hallucination. In Merriam-Webster.com dictionary. Retrieved May 3, 2024, from https://n9.cl/ay325n

Muthukrishnan, N., Maleki, F., Ovens, K., Reinhold, C., Forghani, B., & Forghani, R. (2020). Brief history of artificial intelligence. Neuroimaging Clinics of North America, 30(4), 393-399.

Newell, A., & Shaw, J. C. (1959). A variety of intelligent learning in a general problem solver. RAND Report, p. 1742. https://n9.cl/wy401

Olivetti, E. (s. f.). Online Latin dictionary - Latin - English. Latin Dictionary. Olivetti Media Communication. https://n9.cl/pb4ft

Rawte, V., Sheth, A., & Das, A. (2023). A survey of hallucination in large foundation models. arXiv preprint arXiv:2309.05922

Sah, S. (2020). Machine learning: a review of learning types. https://doi.org/10.20944/preprints202007.0230.v1

Schmidhuber, J. (2022). Annotated history of modern ai and deep learning. arXiv preprint arXiv:2212.11279.

Siegel, R. K. (1977) Hallucinations. Scientific American, 237(4), 132-141.

Su, W., Wang, C., Ai, Q., Hu, Y., Wu, Z., Zhou, Y., & Liu, Y. (2024). Unsupervised real-time hallucination detection based on the internal states of large language models. arXiv preprint arXiv:2403.06448

Venkit, P. N., Chakravorti, T., Gupta, V., Biggs, H., Srinath, M., Goswami, K., ... & Wilson, S. (2024). “Confidently Nonsensical?”: A Critical Survey on the Perspectives and Challenges of ‘Hallucinations' in NLP. arXiv preprint arXiv:2404.07461

West, D. M., & Allen, J. R. (2018). How artificial intelligence is transforming the world. https://n9.cl/ju4u5

Xiao, W., Huang, Z., Gan, L., He, W., Li, H., Yu, Z., ... & Zhu, L. (2024). Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback. arXiv preprint arXiv:2404.14233