Potential cognitive risks of generative transformer-based AI chatbots on higher order executive functions.
Abstract
BACKGROUND: Chat generative retrained transformer (ChatGPT) represents a groundbreaking advancement in Artificial Intelligence (AI-chatbot) technology, utilizing transformer algorithms to enhance natural language processing and facilitating their use for addressing specific tasks. These AI chatbots can respond to questions by generating verbal instructions similar to those a person would provide during the problem-solving process. AIM: ChatGPT has become the fastest growing software in terms of user adoption in history, leading to an anticipated widespread use of this technology in the general population. Current literature is predominantly focused on the functional aspects of these technologies, but the field has not yet explored hypotheses on how these AI chatbots could impact the evolutionary aspects of human cognitive development. Thesis: The "neuronal recycling hypothesis" posits that the brain undergoes structural transformation by incorporating new cultural tools into "neural niches," consequently altering individual cognition. In the case of technological tools, it has been established that they reduce the cognitive demand needed to solve tasks through a process called "cognitive offloading." In this theoretical article, three hypotheses were proposed via forward inference about how algorithms such as ChatGPT and similar models may influence the cognitive processes and structures of upcoming generations. CONCLUSIONS: By forecasting the neurocognitive effects of these technologies, educational and political communities can anticipate future scenarios and formulate strategic plans to either mitigate or enhance the cognitive influence that these factors may have on the general population. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Self-directed engagement with GenAI presents risks related to privacy, safety, and ethical considerations and may influence children's cognitive and social development in complex ways.
“it also presents risks related to privacy, safety, and ethical considerations and may influence children's cognitive and social development in complex ways [8,34,38,41].”
From Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations (2025) · cites this paper as [34]
Cites
Still being checked.
Cited by
Sorted by citations
Klarin, J., Hoff, E. V., Larsson, A., & Daukantaité, D. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1415782 · Cited by 74 · see citing works
Cognitive offloading or cognitive overload? How AI alters the mental architecture of coping
Chirayath, G., Premamalini, K., & Joseph, J. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1699320 · Cited by 58 · see citing works
Copiloting the future: How generative AI transforms Software Engineering
Banh, L., Holldack, F., & Strobel, G. (2025) · Information and Software Technology · doi:10.1016/j.infsof.2025.107751 · Cited by 66 · see citing works
Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization
Skulmowski, A. (2024) · Educational Psychology Review · doi:10.1007/s10648-024-09894-x · Cited by 50 · see citing works
Wong, L. P. W. (2024) · Merits · doi:10.3390/merits4040027 · Cited by 45 · see citing works
Xia, Q., Zhang, P., Huang, W., & Chiu, T. K. F. (2025) · Asia Pacific Journal of Education · doi:10.1080/02188791.2025.2530503 · Cited by 31 · see citing works
Development and validation of the conversational AI dependence scale for Chinese college students
Chen, Y., Wang, M., Yuan, S., & Zhao, Y. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1621540 · Cited by 29 · see citing works
Dubey, S., Ghosh, R., Chatterjee, S., Dubey, M. J., Das, S., & Benito‐León, J. (2024) · Medical Research Archives · doi:10.18103/mra.v12i6.5383 · Cited by 27 · see citing works
Cai, Z., Han, A., Zhou, X., Gazulla, E. D., & Peppler, K. (2025) · Proceedings of the 24th Interaction Design and Children · doi:10.1145/3713043.3731506 · Cited by 17 · see citing works
Costa, C., & Murphy, M. G. (2025) · Technology Pedagogy and Education · doi:10.1080/1475939x.2025.2547728 · Cited by 16 · see citing works
Caffaratti, L. B., Longobardi, C., Badenes‐Ribera, L., & Marengo, D. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1614993 · Cited by 21 · see citing works
Existence hacked: meaning, freedom, death, and intimacy in the age of AI
Andreescu, F. C. (2024) · AI & Society · doi:10.1007/s00146-024-02052-5 · Cited by 12 · see citing works
AI-overdependence and human cognitive decline: Hazards, evidence, and mitigation strategies
Noorbehbahani, F., & Oyibo, K. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101102 · Cited by 12 · see citing works
Seung, Y., & Basham, J. D. (2026) · Learning Disability Quarterly · doi:10.1177/07319487261439132 · Cited by 12 · see citing works
The impact of artificial intelligence: from cognitive costs to global inequality
Paić, G., & Serkin, L. (2025) · The European Physical Journal Special Topics · doi:10.1140/epjs/s11734-025-01561-8 · Cited by 12 · see citing works
Stoyanova, D., Stoyanova-Petrova, S. V., Shotarova, S., Lyubomirov, S. Y., & Mileva, N. S. (2025) · Education Sciences · doi:10.3390/educsci16010019 · Cited by 12 · see citing works
Recalibrating academic expertise in the age of generative AI
Lin, Z., & Sohail, A. (2026) · Patterns · doi:10.1016/j.patter.2025.101473 · Cited by 14 · see citing works
The Impact of Chatbots on Adolescent Mental Health Development: A Comprehensive Literature Review
Wu, Y., Wu, T., Zhu, K., Liu, X., Liu, J., Wang, Y., Shi, R., Xiong, J., Xing, X., Lv, Y., et al. (2026) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s579872 · Cited by 8 · see citing works
Seung, Y., Basham, J. D., Kim, T., & Lohoefener, J. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70144 · Cited by 7 · see citing works
Heliades, G. P., Gkintoni, E., Panas, G., Halkiopoulos, C., & Boutsinas, B. (2025) · Springer proceedings in business and economics · doi:10.1007/978-3-031-78471-2_38 · Cited by 7 · see citing works
Critical Alliance of AI in Education: A Pedagogical Framework for Safeguarding Cognitive Skills
Ramos-Benítez, M. J., García-Osorio, M. E., & Delgado, Y. (2026) · International Medical Education · doi:10.3390/ime5010022 · Cited by 8 · see citing works
León-Domínguez, U. (2025) · Ergonomics · doi:10.1080/00140139.2025.2560581 · Cited by 5 · see citing works
Self-citationLi, Y., Gu, T., Yang, C., Li, M., Wang, C., Yao, L., Gu, W., & Sun, D. (2025) · Journal of Medical Internet Research · doi:10.2196/66161 · Cited by 5 · see citing works
To fear or not to fear: generative artificial intelligence in drama education
Clark-Fookes, T. (2024) · Research in Drama Education The Journal of Applied Theatre and Performance · doi:10.1080/13569783.2024.2401335 · Cited by 5 · see citing works
Chatto, M. J., & Logronio, F. V. (2025) · Journal of Education and Learning Reviews · doi:10.60027/jelr.2025.2061 · Cited by 11 · see citing works
Factors of AI Adoption in Educational Contexts: A Meta-Analytic Synthesis Through the UTAUT
Zhuang, Y., Li, R., & Duan, S. (2025) · International Conference on Distance Education and Learning (ICDEL) · doi:10.1109/icdel65868.2025.11193611 · Cited by 5 · see citing works
The design framework for pedagogical agents supporting constructivist learning with generative AI
Liu, C., Tsai, C., Yilmaz, R., Wu, J., Ranieri, M., Zou, D., Archambault, L., van Braak, J., & Biswas, G. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105744 · Cited by 4 · see citing works
Problematic ChatGPT use: Manifestations, etiologies, and evaluation
Liao, H.-Y., Ko, C., & Yen, C. (2026) · Biomedical Journal · doi:10.1016/j.bj.2026.100998 · Cited by 4 · see citing works
Fodor, G. H., Tolnai, J., Rárosi, F., Nagy, A., & Peták, F. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08146-y · Cited by 3 · see citing works
Informed Consent in Educational AI Research Needs to Be Transparent, Flexible, and Dynamic
Skulmowski, A. (2025) · Mind Brain and Education · doi:10.1111/mbe.12435 · Cited by 4 · see citing works
Deskilling: The Atrophy of Cognitive and Social Aptitudes
Thiele, L. P. (2025) · Springer eBooks · doi:10.1007/978-3-031-82086-1_4 · Cited by 2 · see citing works
Colombari, R., Marimón, F., & Mas‐Machuca, M. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101016 · Cited by 3 · see citing works
A Process Model of Managerial Phronesis in the Age of Generative AI
Lindebaum, D., Balasubramanian, N., Ashraf, M., & Haack, P. (2026) · Academy of Management Review · doi:10.5465/amr.2024.0582 · Cited by 2 · see citing works
Initial Validation of the IMPACT Model: Technological Appropriation of ChatGPT by University Faculty
Pereira, L. M., Basantes-Andrade, A., Naranjo-Toro, M., & Guia-Pereira, M. (2025) · Education Sciences · doi:10.3390/educsci15111520 · Cited by 3 · see citing works
Revolutionizing Neurodegenerative Disease Management: The Synergy of AI and Pharmacy
Manubolu, K., & Peeriga, R. (2025) · Current Aging Science · doi:10.2174/0118746098375978250820220024 · Cited by 1 · see citing works
Behavioural preference for Google and ChatGPT in an online search task
Healy, K., & Radell, M. L. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2560549 · Cited by 1 · see citing works
Communication Transformed by Generative Artificial Intelligence
Shafik, W. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2502-6.ch006 · Cited by 1 · see citing works
Cognitive Externalization and Generative AI in Higher Education
Сидорчук, Р. (2026) · Высшее образование в России · doi:10.31992/0869-3617-2026-35-7-53-75 · Cited by 1 · see citing works
Liu, C., Guo, J., Gao, R., Chen, X., Zhu, Q., & Chang, P. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1910545 · Cited by 1 · see citing works
Mahajan, P. T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5386814 · Cited by 1 · see citing works
Damola, F. M., Dayo, U. O., Sheriff, A., Edem, M. E., Daniel, C. S., Ebite, C., & Paul, M. E. (2025) · Global Journal of Educational Research · doi:10.4314/gjedr.v24i2.6
de la Garza, L. M. G. (2025) · Revista Derecho y Economía de la Integración · doi:10.69592/2530-5093-n14-junio-2025-art-4
Janowski, J. M., & Mazurek, A. (2025) · Studia z Teorii Wychowania · doi:10.5604/01.3001.0055.5082
Razvi, A. F., & Bashir, E. (2025) · IEEE International Smart Cities Conference (ISC2) · doi:10.1109/isc266238.2025.11293322
Retrieval Augmented Generation Chatbot for Enhancing One Stop Service in Universitas Sebelas Maret
Setyawan, H. H., Khadija, M. A., Budianto, A., & Nurmala, M. L. T. (2025) · International Conference on Computer, Control, Informatics and its Applications · doi:10.1109/ic3ina68387.2025.11325382
On the Dangers of Large‐Language Model Mediated Learning for Human Capital
Lindebaum, D., Nolan, E., & Swart, J. (2026) · Human Resource Management Journal · doi:10.1111/1748-8583.70036
黎政諺, & Chen, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30860-3_29
Yang, J., Li, M. Y., Wang, S., Shi, Z., Fang, J., Zheng, P., & Wu, Z. (2026) · BMC Oral Health · doi:10.1186/s12903-026-09345-9
de Souza, B. C., Neto, A. S. D. A., & Roazzi, A. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7158756
Isfaeni, H., Ma’arif, N., Rusdi, R., Komala, R., Utami, A. W. A., Sari, A. N., & Nafisah, W. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2702744
Mittal, P., Kaur, A., Malhotra, S., Kaur, B., & Kaur, A. (2026) · Mental Illness · doi:10.1155/mij/8325823
Neuroplastic Consequences of Artificial Intelligence Dependency
Britel, I., Moummou, H., Aghdou, Z., Bouzidi, H. E., & El‐Mansoury, B. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9484-8.ch011
Wang, K., Qin, S., Shen, Y., Guo, J., Ruan, Q., & Jia, T. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70079 · Cited by 1 · see citing works
Digital Twins for Sustainable Development: Silver Bullet or Silicon Cage?
Thiele, L. P., & Billesbach, G. (2026) · Sustainability · doi:10.3390/su18168101
Hoque, M. O., Chowdhury, H. J., & Islam, M. S. (2026) · Applied Cognitive Psychology · doi:10.1002/acp.70269
AI Over-Reliance and Cognitive Decline: Evidence from Higher Education Students
Noorbehbahani, F., & Oyibo, K. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-33957-7_33
The Emergence of Critical AI Literacy
Duarte, T., Conrad, K., & Garcia, I. K. (2026) · Springer eBooks · doi:10.1007/978-3-032-12201-8_1
AI Sabbatical: A conceptual framework for cognitive sustainability in AI-augmented knowledge work
Anthuvan, T., & Prabhuram, S. (2026) · Human Systems Management · doi:10.1177/01672533261484224
Generative AI as the second wave of cognitive externalization
Сидорчук, Р. (2026) · MIR (Modernization Innovation Research) · doi:10.18184/2079-4665.2026.17.3.396-416
A Critical Review of Critical Thinking in HCI Research About AI
Inie, N., Kristensen, A. M., Misfeldt, M., & Dalsgaard, P. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2722522
A scoping review of the negative effects of digital technology on cognition
Žnidarič, U., Štrumbelj, E., & Machidon, O. M. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.101326 · Cited by 5 · see citing works
Generative Artificial Intelligence Use and Adolescent Mental Health
Nagata, J. M., Hur, J. O., Diep, T., Alsamman, H., Lee, E. D., Heuer, A., Huynh, H., Nayak, S., McBain, R. K., Cantor, J. H., et al. (2026) · Current Pediatrics Reports · doi:10.1007/s40124-026-00388-8
Perceptions of AI-assisted learning and learner development among Moroccan secondary school students
Kandirou, R., Youssfi, S. E., Atlassi, M. E., Dahman, A., & Hammoumi, M. M. E. (2026) · Discover Education · doi:10.1007/s44217-026-02109-1
Children’s AI use: Developmental risks and opportunities in early and middle childhood
Flynn, R. M., Blumberg, F. C., Kleinknecht, E., & Mann, R. B. (2026) · Journal of Children and Media · doi:10.1080/17482798.2026.2744461
Guo, Y., & Dong, P. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1998976
- Authors
- León-Domínguez, U.
- Affiliations
- University of Monterrey (MX)
- Corresponding author
- León-Domínguez, Umberto
- Venue
- Neuropsychology
- Published
- 2024-05
- Volume
- 38
- Issue
- 4
- Pages
- 293-308
- ISSN
- 0894-4105 (ISSN-L)
- 1931-1559
- OpenAlex
- W4391433987
- Cited by
- 65
- References
- 0
- Citations by year
- 2026: 31 · 2025: 28 · 2024: 6
- FWCI
- 24.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuropsychology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Digital Media and Philosophy
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Keywords
- AI chatbots, ChatGPT, generative AI, executive function, cognitive offloading, cognitive development, future generations, human-AI interaction
- MeSH terms
- Algorithms, Artificial Intelligence, Cognition, Humans, Natural Language Processing, Problem Solving, Executive Function
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review