Inteligencia Artificial Generativa: Entre la Potenciación y la Externalización Cognitiva
DOI:
https://doi.org/10.12800/ccd.v20i66.2698Resumen
La historia de la tecnología puede entenderse como la historia de la externalización de las capacidades humanas. En este sentido, la irrupción de la Inteligencia Artificial Generativa (IAG) marca un punto de inflexión al delegar, por primera vez, funciones ejecutivas y de razonamiento. Surge así un dilema fundamental: ¿es la IAG un amplificador que democratiza el desempeño o un mecanismo de dependencia que conduce a la atrofia cognitiva? A partir de la literatura reciente, se examinan sus implicaciones educativas, culturales y sociales, destacando la necesidad de comprenderla tanto como herramienta técnica como fenómeno que transforma la relación entre la mente y el conocimiento. En un futuro donde lo humano y lo artificial se entrelazan, la cuestión final es si esta simbiosis abrirá un nuevo capítulo en la evolución intelectual o, por el contrario, derivará en una involución que amenace la soberanía de la mente sobre sus propios procesos.
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Acemoglu, D., & Restrepo, P. (2018). Low-skill and high-skill automation. Journal of human capital, 12(2), 204–232. https://doi.org/10.1086/697242
Anthropic (2025). Claude [Large language model]. Anthropic. https://claude.ai/
Bjork, R. A., & Bjork, E. L. (2020). Desirable difficulties in theory and practice. Journal of Applied Research in Memory and Cognition, 9(4), 475–479. https://doi.org/10.1016/j.jarmac.2020.09.003
Blasco, A., & Charisi, V. (2024). AI Chatbots in K-12 Education: An Experimental Study of Socratic vs. Non-Socratic Approaches and the Role of Step-by-Step Reasoning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5040921
Boyle, R. W., & Farreras, I. G. (2015). The effect of calculator use on college students’ mathematical performance. International journal of research in education and science, 1(2), 95.
Brette, R. (2022). Brains as computers: Metaphor, analogy, theory or fact? Frontiers in ecology and evolution, 10(878729). https://doi.org/10.3389/fevo.2022.878729
Chiu, T. K. F. (2025). AI literacy and competency: definitions, frameworks, development and future research directions. Interactive Learning Environments, 33(5), 3225–3229. https://doi.org/10.1080/10494820.2025.2514372
Chong, T. T.J., Apps, M., Giehl, K., Sillence, A., Grima, L. L., & Husain, M. (2017). Neurocomputational mechanisms underlying subjective valuation of effort costs. PLoS Biology, 15(2), e1002598. https://doi.org/10.1371/journal.pbio.1002598
Clark, A. (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford University Press.
Crowston, K., & Bolici, F. (2025). Deskilling and upskilling with AI systems. Information research, 30, 1009–1023. https://doi.org/10.47989/ir30iconf47143
Daware, N. (2025). The De-Skilling Dilemma: A Critical Analysis of AI´s Impact on Human Potential. Vidyabharati International Interdisciplinary Research Journal.
Delevich, K., Thomas, A. W., & Wilbrecht, L. (2018). Adolescence and “late blooming” synapses of the prefrontal cortex. Cold Spring Harbor Symposia on Quantitative Biology, 83, 37–43. https://doi.org/10.1101/sqb.2018.83.037507
Dell’Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4573321
Donald, M. (2002). A mind so rare: The evolution of human consciousness. WW Norton.
Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. https://doi.org/10.1126/sciadv.adn5290
Duncan, K., & Shohamy, D. (2024). Dopamine and learning. En The Oxford Handbook of Human Memory, Two Volume Pack (pp. 689–710). Oxford University Press.
Ferdman, A. (2025). AI deskilling is a structural problem. AI & Society. https://doi.org/10.1007/s00146-025-02686-z
Fernandes, D., Villa, S., Nicholls, S., Haavisto, O., Buschek, D., Schmidt, A., Kosch, T., Shen, C., & Welsch, R. (2025). AI makes you smarter but none the wiser: The disconnect between performance and metacognition. Computers in Human Behavior, 175(108779), 108779. https://doi.org/10.1016/j.chb.2025.108779
Fields, R. D. (2005). Myelination: an overlooked mechanism of synaptic plasticity? The Neuroscientist: A Review Journal Bringing Neurobiology, Neurology and Psychiatry, 11(6), 528–531. https://doi.org/10.1177/1073858405282304
Fleming, L. L., & McDermott, T. J. (2024). Cognitive control and neural activity during human development: Evidence for synaptic pruning. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 44(26), e0373242024. https://doi.org/10.1523/JNEUROSCI.0373-24.2024
Flower, G., Vorthmann, S., Fulton, D., & Hamilton, N. B. (2025). Plasticity of myelination. Advances in Neurobiology, 43, 181–204. https://doi.org/10.1007/978-3-031-87919-7_8
Fragiadakis, G., Diou, C., Kousiouris, G., & Nikolaidou, M. (2024). Evaluating Human-AI Collaboration: A review and methodological framework. En arXiv. https://doi.org/10.48550/ARXIV.2407.19098
Gavira-Durón, N., Jiménez Preciado, A. L., Alonso-Rivera, A., & Ramírez-Culebro, C. M. (2025). The role of generative AI in transforming educational practices. Education and New Developments. https://doi.org/10.36315/2025v2end027
Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies (Basel, Switzerland), 15(1), 6. https://doi.org/10.3390/soc15010006
Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez-Leo, D., Järvelä, S., Mavrikis, M., & Rienties, B. (2024). The promise and challenges of generative AI in education. Behaviour & Information Technology, 1–27. https://doi.org/10.1080/0144929x.2024.2394886
Gill, M. L. (2020). Socrates’ critique of writing in Plato’s phaedrus. En Wisdom, Love, and Friendship in Ancient Greek Philosophy (pp. 159–174). De Gruyter.
Google DeepMind (2025). Gemini [Large language model]. Google. https://deepmind.google/
Han, Y. (2024). Commentary: Generative artificial intelligence empowers educational reform: current status, issues, and prospects. Frontiers in education, 9. https://doi.org/10.3389/feduc.2024.1445169
Harris, K. M., Kuwajima, M., Flores, J. C., & Zito, K. (2024). Synapse-specific structural plasticity that protects and refines local circuits during LTP and LTD. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 379(1906), 20230224. https://doi.org/10.1098/rstb.2023.0224
Hebb, D. O. (1949). The Organization of Behavior. Wiley.
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I.I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
Jose, B., Cherian, J., Verghis, A. M., Varghise, S. M., S, M., & Joseph, S. (2025). The cognitive paradox of AI in education: between enhancement and erosion. Frontiers in Psychology, 16, 1550621. https://doi.org/10.3389/fpsyg.2025.1550621
Jwair, A. A. B. (2025). Generative artificial intelligence in higher education: Students’ journey through opportunities, challenges, and the horizons of academic transformation. Cogent Education, 12(1). https://doi.org/10.1080/2331186x.2025.2589495
Kirschner, P., & Hendrick, C. (2024). How Learning Happens. Seminal Works in Educational Psychology and What They Mean in Practice. Routledge.
Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. En arXiv. http://arxiv.org/abs/2506.08872
Labedzki, R. (2025). Human-AI collaboration in Hybrid Multi-Agent Systems. International Journal of Electronics and Telecommunications, 1–9. https://doi.org/10.24425/ijet.2025.155474
Lee, H.P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 1–22.
MacCallum, K., Parsons, D., & Mohaghegh, M. (2024). The Scaffolded AI Literacy (SAIL) Framework for Education: Preparing learners at all levels to engage constructively with Artificial Intelligence. He Rourou, 23. https://doi.org/10.54474/herourou.v1i1.10835
Malafouris, L. (2016). How things shape the mind: A theory of material engagement. MIT Press.
Marzola, P., Melzer, T., Pavesi, E., Gil-Mohapel, J., & Brocardo, P. S. (2023). Exploring the role of neuroplasticity in development, aging, and neurodegeneration. Brain Sciences, 13(12), 1610. https://doi.org/10.3390/brainsci13121610
Matueny, D. R. M., & Nyamai, D. J. J. (2025). Illusion of competence and skill degradation in artificial intelligence dependency among users. International Journal of Research and Scientific Innovation, 12(5), 1725–1738.
Michely, J., Viswanathan, S., Hauser, T. U., Delker, L., Dolan, R. J., & Grefkes, C. (2020). The role of dopamine in dynamic effort-reward integration. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 45(9), 1448–1453. https://doi.org/10.1038/s41386-020-0669-0
Morris, R. G. (1999). D.O. Hebb: The organization of behavior, Wiley: New York; 1949. Brain Research Bulletin, 50(5–6), 437. https://doi.org/10.1016/s0361-9230(99)00182-3
Mount, C. W., & Monje, M. (2017). Wrapped to adapt: Experience-dependent myelination. Neuron, 95(4), 743–756. https://doi.org/10.1016/j.neuron.2017.07.009
Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., & Mian, A. (2023). A comprehensive overview of large Language Models. En arXiv. https://doi.org/10.48550/ARXIV.2307.06435
Nicoll, R. A. (2017). A brief history of long-term potentiation. Neuron, 93(2), 281–290. https://doi.org/10.1016/j.neuron.2016.12.015
Nilsson, C. (2025). The artificial intelligence (AI) competence paradox: how AI reshapes clinical expertise. Transforming Government People Process and Policy. https://doi.org/10.1108/tg-02-2025-0048
OpenAI (2025). ChatGPT [Large language model]. OpenAI. https://chat.openai.com/
Ostroff, L. (2023). Ltp and structural plasticity. IBRO Neuroscience Reports, 15, S37–S38. https://doi.org/10.1016/j.ibneur.2023.08.2125
Pallant, J. L., Blijlevens, J., Campbell, A., & Jopp, R. (2025). Mastering knowledge: the impact of generative AI on student learning outcomes. Studies in Higher Education, 1–22. https://doi.org/10.1080/03075079.2025.2487570
Palmquist, A., Sigurdardottir, H. D. I., & Myhre, H. (2025). Exploring interfaces and implications for integrating social-emotional competencies into AI literacy for education: a narrative review. Journal of Computers in Education. https://doi.org/10.1007/s40692-025-00354-1
Pan, W., Lu, J., Wu, L., Kou, J., & Lei, Y. (2023). Expending effort may share neural responses with reward and evokes high subjective satisfaction. Biological Psychology, 177(108480), 108480. https://doi.org/10.1016/j.biopsycho.2022.108480
Passerini, A., Gema, A., Minervini, P., Sayin, B., & Tentori, K. (2024). Fostering effective hybrid human-LLM reasoning and decision making. Frontiers in Artificial Intelligence, 7, 1464690. https://doi.org/10.3389/frai.2024.1464690
Peláez-Sánchez, I. C., Velarde-Camaqui, D., & Glasserman-Morales, L. D. (2024). The impact of large language models on higher education: exploring the connection between AI and Education 4.0. Frontiers in education, 9. https://doi.org/10.3389/feduc.2024.1392091
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688. https://doi.org/10.1016/j.tics.2016.07.002
Roochnik, D. (2024). Socrates’ critique of writing. Society, 61(6), 700–705. https://doi.org/10.1007/s12115-024-00968-8
Sadegh-Zadeh, S.A., Bahrami, M., Soleimani, O., & Ahmadi, S. (2024). Neural reshaping: the plasticity of human brain and artificial intelligence in the learning process. American Journal of Neurodegenerative Disease, 13(5), 34–48. https://doi.org/10.62347/NHKD7661
Saleh, Y., Abu Talib, M., Nasir, Q., & Dakalbab, F. (2025). Evaluating large language models: a systematic review of efficiency, applications, and future directions. Frontiers in Computer Science, 7(1523699). https://doi.org/10.3389/fcomp.2025.1523699
Schultz, W. (2016). Dopamine reward prediction error coding. Dialogues in Clinical Neuroscience, 18(1), 23–32. https://doi.org/10.31887/dcns.2016.18.1/wschultz
Selemon, L. D. (2013). A role for synaptic plasticity in the adolescent development of executive function. Translational Psychiatry, 3(3), e238. https://doi.org/10.1038/tp.2013.7
Shahzad, T., Mazhar, T., Tariq, M. U., Ahmad, W., Ouahada, K., & Hamam, H. (2025). A comprehensive review of large language models: issues and solutions in learning environments. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-00815-8
Shukla, P., Bui, P., Levy, S. S., Kowalski, M., Baigelenov, A., & Parsons, P. (2025). De-skilling, cognitive offloading, and misplaced responsibilities: Potential ironies of AI-assisted design. En arXiv. https://doi.org/10.48550/ARXIV.2503.03924
Soto-Sanfiel, M. T., Angulo-Brunet, A., & Lutz, C. (2025). The scale of artificial intelligence literacy for all (SAIL4ALL): assessing knowledge of artificial intelligence in all adult populations. Humanities & Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-05978-3
Tian, J., & Zhang, R. (2025). Learners’ AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy. Acta Psychologica, 260(105725), 105725. https://doi.org/10.1016/j.actpsy.2025.105725
Topolnyk, Y., Gurevych, R., Debenko, I., Klochok, O., Cherniakova, Z., Yarova, A., & Maksymchuk, B. (2025). The impact of digital technologies and AI on adult learning: From digital literacy to neuroplasticity. Brain: broad research in artificial intelligence and neuroscience, 16(2), 148–155. https://doi.org/10.70594/brain/16.2/11
Tyson, L. D., & Zysman, J. (2022). Automation, AI & work. Daedalus, 151(2), 256–271. https://doi.org/10.1162/daed_a_01914
UNESCO (2024a). AI competency framework for students. https://doi.org/10.54675/jkjb9835
UNESCO (2024b). AI competency framework for teachers. https://doi.org/10.54675/zjte2084
Wang, A. R., Groome, A., Taniguchi, L., Eshel, N., & Bentzley, B. S. (2020). The role of dopamine in reward-related behavior: shining new light on an old debate. Journal of Neurophysiology, 124(2), 309–311. https://doi.org/10.1152/jn.00323.2020
Wang, H., Xu, X., Yang, Z., & Zhang, T. (2025). Alterations of synaptic plasticity and brain oscillation are associated with autophagy induced synaptic pruning during adolescence. Cognitive Neurodynamics, 19(1), 2. https://doi.org/10.1007/s11571-024-10185-y
Weinstein, A. M. (2023). Reward, motivation and brain imaging in human healthy participants - A narrative review. Frontiers in Behavioral Neuroscience, 17, 1123733. https://doi.org/10.3389/fnbeh.2023.1123733
Willingham, D. T. (2009). Why Don’t Students Like School? Jossey-Bass.
Willingham, D. T. (2021). Why don’t students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom (2a ed.). Jossey-Bass.
World Economic Forum (2025). The Future of Jobs Report 2025.
X Corp. (2025). Grok [Large language model]. X. https://x.ai/
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