IA generativa y asistentes inteligentes

Andrés Desantes de Mergelina
Resumen

El artículo analiza el desarrollo histórico de las interfaces humano-máquina, desglosa los elementos fundamentales de una interfaz conversacional (administrador, orquestador, integración de IA, entre otros), y evalúa su transición hacia la autonomía a través de la Agentic AI. Se incluyen ejemplos prácticos y consideraciones regulatorias. Las interfaces conversacionales han pasado de ser sistemas rígidos basados en reglas a herramientas avanzadas potenciadas por IA generativa. Aunque enfrentan desafíos como costes, seguridad y regulación, la integración de grandes modelos de lenguaje (LLM) y el enfoque hacia la autonomía (Agentic AI) posicionan a estos sistemas como el futuro de la interacción humano-máquina, transformando cómo nos comunicamos y trabajamos.

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Palabras clave:
asistente, interfaz conversacional, interacción humano-máquina (HMI), inteligencia artificial generativa (GenAI), grandes modelos del lenguaje (LLM), procesamiento del lenguaje natural (NLP)
Citas

Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A Survey. Computer Networks, 54(15), 2787-2805. https://doi.org/10.1016/j.comnet.2010.05.010

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610-623). https://doi.org/10.1145/3442188.3445922

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., Brynjolfsson, E., Buch, S., Card, D., Castellon, R., Chatterji, N., Chen, A., Creel, K., Davis, J. Q., Demszky, D., … Liang, P. (2021). On the opportunities and risks of foundation models. arXiv preprint, arXiv:2108.07258. https://arxiv.org/abs/2108.07258

Botpress. (2024, 21 de agosto). Estadísticas clave de Chatbot para 2025: percepciones, crecimiento del mercado y tendencias. Botpress blog. https://botpress.com/es/blog/key-chatbot-statistics

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., … Amodei, D. (2020). Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan & H. Lin (Eds.), Advances in Neural Information Processing Systems 33 (pp. 1877-1901). Neural Information Processing Systems (NeurIPS). https://papers.nips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html

Clarke, C., Peper, J., Krishnamurthy, K., Talamonti, W., Leach, K., Lasecki, W., Kang, Y., Tang, L., & Mars, J. (2022). One agent to rule them all: towards multi-agent conversational AI. In S. Muresan, P. Nakov & A. Villavicencio (Eds.), Findings of the Association for Computational Linguistics: ACL 2022 (pp. 3258-3267). Association for Computational Linguistics. https://aclanthology.org/2022.findings-acl.257/

Cook, J. (2024). OpenAI's 5 levels of 'super AI' (AGI to outperform human capability). Forbes. https://www.forbes.com/sites/jodiecook/2024/07/16/openais-5-levels-of-super-ai-agi-to-outperform-human-capability/

Dale, R. (2016). The return of the chatbots. Natural Language Engineering, 22(5), 811-817. https://doi.org/10.1017/S1351324916000243

Demarco, G., Fanelli, N., Vessio, G., & Castellano, G. (2024). Converso: improving LLM chatbot interfaces and task execution via conversational form. In R. Sousa-Silva, H. Lopes Cardoso, M. Koponen, A. Pareja Lora & M. Seresi (Eds.), Proceedings of the First LUHME Workshop (pp. 5-11). CLUP, Centro de Linguística da Universidade do Porto FLUP - Faculdade de Letras da Universidade do Porto. https://aclanthology.org/2024.luhme-1.1/

Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681-694. https://doi.org/10.1007/s11023-020-09548-1

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. In Z. Grahramani, M. Welling, C. Cortes, N. Lawrence & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 27 (pp. 2672-2680). Neural Information Processing Systems (NeurIPS). https://proceedings.neurips.cc/paper_files/paper/2014/hash/f033ed80deb0234979a61f95710dbe25-Abstract.html

Grupo 1Millionbot. (2024). La inteligencia artificial en las universidades: retos y oportunidades. Informe anual sobre IA y educación superior. Enero. https://www.1millionbot.com/informe-ia-en-universidades-retos-y-oportunidades

Hochberg, L. R., Serruya, M. D., Friesh, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006). Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature, 442(7099), 164-171. https://doi.org/10.1038/nature04970

IBM Archives. (1961). IBM Shoebox. https://mediacenter.ibm.com/media/%281961%29%2BShoebox%2B-%2BIBM%2BArchives%2B%2878-013%29/0_4m2ynnkk

Juniper Research. (2019). Bank Cost Savings via Chatbots to Reach $7.3 Billion by 2023, as Automated Customer Experience Evolves. Representing a Growth in Operational Savings of 3,400% from 2019. Juniper Research. https://www.juniperresearch.com/press/bank-cost-savings-viachatbots-reach-7-3bn-2023/

Jurafsky, D., & Martin, J. H. (2020). Speech and language processing. Third draft edition. Stanford University.

Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-T., Rocktäschel, T., Riedel, S., & Kiela, D. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan & H. Lin (Eds.), Advances in Neural Information Processing Systems 33 (pp. 9459-9474). Neural Information Processing Systems (NeurIPS). https://proceedings.neurips.cc/paper/2020/hash/6b493230205f780e1bc26945df7481e5-Abstract.html

Lipton, Z. C. (2018). The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery. Queue, 16(3), 31-57. https://doi.org/10.1145/3236386.3241340

Martino, C. (2020). A History of Chatbots and Voice Assistants. Timeline of the evolution of Conversational Interfaces. Women in Voice. https://medium.com/women-in-voice/a-history-of-chatbots-and-voice-assistants-e39ec598a92

McTear, M., Callejas, Z., & Griol, D. (2016). The conversational interface: Talking to smart devices. Springer.

Mordor Intelligence. (2024). Global chatbot market. https://www.mordorintelligence.com/es/industry-reports/global-chatbot-market

Pinola, M. (2011). Speech recognition through the decades: How we ended up with Siri. PCWorld. https://www.pcworld.com/article/477914/speech_recognition_through_the_decades_how_we_ended_up_with_siri.html

Preece, J., Sharp, H., Rogers, Y. (2015). Interaction design: Beyond human-computer interaction. Fourth edition. Wiley.

Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre-training. OpenAI. https://openai.com/blog/language-unsupervised/

Rasa. (2021). Rasa Open Source: Conversational AI framework. https://rasa.com/

Red Hat. (2024). What is agentic AI? https://www.redhat.com/en/topics/ai/what-is-agentic-ai

Reuters. (2024). Elon Musk´s Neuralink receives Canadian approval for brain chip trial. Reuters. https://www.reuters.com/science/elon-musks-neuralink-receives-canadian-approval-brain-chip-trial-2024-11-21

Sánchez, C. (s.f.). This is the business of virtual assistants: figures and use cases. Opinno. https://opinno.com/es/insight/this-is-the-business-of-virtual-assistants-figures

Shneiderman, B., Plaisant, C., Cohen, M., Jacobs, S., Elmqvist, N., & Diakopoulos, N. (2016). Designing the user interface: Strategies for effective human-computer interaction. Sixth edition. Pearson.

Statista. (2023). Frecuencia de uso de asistentes virtuales de voz en España en 2023. https://es.statista.com/estadisticas/1018541/uso-de-asistentes-virtuales-de-voz-en-espana/

Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. In A. Korhonen, D. Traum & L. Màrquez (Eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 3645-3650). https://doi.org/10.18653/v1/P19-1355

The Royal Society. (2019). iHuman: Blurring the lines between mind and machine. https://royalsociety.org/-/media/policy/projects/ihuman/reportneural-interfaces.pdf

Vance, A. (2016). Elon Musk: Tesla, SpaceX, and the quest for a fantastic future. Harper Collins.

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, Ll., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is All you Need. In I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan & R. Garnett (Eds.), Advances in Neural Information Processing Systems. 31st Annual Conference on Neural Information Processing Systems 30 (pp. 5998-6008). Neural Information Processing Systems (NeurIPS). https://papers.nips.cc/paper_files/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html

Wang, K. (2023). From ELIZA to ChatGPT: A brief history of chatbots and their evolution. Applied and Computational Engineering, 39(1), 57-62. https://www.researchgate.net/publication/378316730_From_ELIZA_to_ChatGPT_A_brief_history_of_chatbots_and_their_evolutio

Weizenbaum, J. (1966). ELIZA-a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45. https://doi.org/10.1145/365153.365168

Wikipedia contributors. (s.f.). Prompt injection. Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/wiki/Prompt_injection

Young, S., Gasic, M., Thomson, B., & Williams, J. D. (2013). POMDP-based statistical spoken dialog systems: A review. Proceedings of the IEEE, 101(5), 1160-1179. http://dx.doi.org/10.1109/JPROC.2012.2225812

Zhang, Y., Sun, S., Galley, M., Chen, Y.-C., Brockett, C., Gao, X., Gao, J., Liu, J., & Dolan, B. (2020). DIALOGPT: Large-scale generative pre-training for conversational response generation. In D. Jurafsky, J. Chai, N. Schluter & J. Tetreault (Eds.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 270-278). https://doi.org/10.18653/v1/2020.acl-demos.30

Millionbot. (2023a, 1 de agosto). 1MillionBot asume el liderazgo en IA generativa y reinventa el futuro con soluciones innovadoras. https://1millionbot.com/1millionbot-asume-el-liderazgo-en-ia-generativa/

Millionbot. (2023b, 12 de agosto). ¿Qué tendencias emergentes están formando el futuro de los chatbots y la inteligencia artificial? https://1millionbot.com/tendencias-emergentes-chatbots-inteligencia-artificial/