Algorithmic Citizenship in Formation: Artificial Intelligence, Regulation, and Technological Dependence in Mexican Public Universities
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Keywords

algorithmic citizenship
generative artificial intelligence
Mexico
public higher education
university governance

How to Cite

Luque Brazán, J. C., Pérez Tagle, J. A., Anaya Marino, K. R., & Ibarez Luna, E. N. (2026). Algorithmic Citizenship in Formation: Artificial Intelligence, Regulation, and Technological Dependence in Mexican Public Universities . Entretextos, 20(40), 85–103. https://doi.org/10.5281/zenodo.19786675

ARK

https://n2t.net/ark:/47886/19786675

Abstract

This article analyzes the adoption, uses, and perceptions of generative artificial intelligence (AI) among undergraduate students at three Mexican public universities: the Universidad Autónoma de la Ciudad de México, the Universidad Autónoma Metropolitana-Iztapalapa, and the Universidad Autónoma de Guerrero (n = 240). Based on a comparative quantitative design, it identifies usage patterns, modalities of appropriation, perceptions of academic integrity, and institutional governance frameworks. The results show a widespread adoption (75.4%) driven primarily by individual initiative, within an environment characterized by the absence of formal guidelines and a low offering of structured training. The chi-square test confirms institutional homogeneity regarding training (χ²(2) = 0.007, p = .997), suggesting a systemic rather than organizational regulatory vacuum. The study proposes the category of algorithmic citizenship to understand the intersection between practical use, technological dependence, and critical formation in public higher education. It concludes that the incorporation of AI is advancing faster than its pedagogical institutionalization, raising responsibilities regarding governance and algorithmic literacy.

https://doi.org/10.5281/zenodo.19786675
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References

Acevedo Tarazona, Á., y Quiroz Prada, M. (2022). Karl Marx en clave de actualidad. Resignificaciones, descentramientos y resistencias desde el Sur Global. Ánfora, 29(53), 19-41. https://doi.org/10.30854/anf.v29.n53.2022.844

Agamben, G. (2005). Estado de excepción. Buenos Aires: Adriana Hidalgo editora. Filosofía e historia, 1-176. ISBN 987-1156-15-4.

Arendt, H. (2006). Los orígenes del totalitarismo. Alianza Editorial, 2006.

Benjamín, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Polity Press.

Couldry, N., & Mejias, U. A. (2019). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford University Press. https://doi.org/10.1515/9781503609754

Crawford, K. (2021). Atlas of IA: Power, politics, and the planetary costs of artificial intelligence. Yale University Press. https://doi.org/10.12987/9780300252392

Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.

Floridi, L. (2014). The fourth revolution: How the infosphere is reshaping human reality. Oxford University Press.

Gillespie, T. (2018). Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media. Yale University Press. https://doi.org/10.12987/9780300235029

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Hofkirchner, W. (2010). How to design the infosphere: The fourth revolution, the management of the life cycle of information, and information ethics as a macroethics. Knowledge, Technology & Policy, 23(1–2), 177–192. https://doi.org/10.1007/s12130-010-9108-6

Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. SAGE. https://doi.org/10.4135/9781473909472

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for IA in education. Pearson.

Moulier-Boutang, Y. (2011). Cognitive capitalism. Polity Press.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.

Organisation for Economic Co-operation and Development. (2019). OECD principles on artificial intelligence. OECD Publishing. https://www.oecd.org/going-digital/ai/principles/

Quijano, A. (2000). Colonialidad del poder, eurocentrismo y América Latina. En E. Lander (Ed.), La colonialidad del saber: Eurocentrismo y ciencias sociales. Perspectivas latinoamericanas (pp. 201–246). CLACSO.

Santos, B. de S. (2007). Para além do pensamento abissal: Das linhas globais a uma ecologia de saberes. Revista Crítica de Ciências Sociais, 78, 3–46. https://doi.org/10.4000/rccs.753

Selwyn, N. (2019). Should robots replace teachers? IA and the future of education. Polity Press.

Srnicek, N. (2017). Platform capitalism. Polity Press. (En español: 2018, Caja Negra).

UNESCO. (2021). Recommendation on the ethics of artificial intelligence. UNESCO. https://unesdoc.unesco.org/

Van Dijck, J., Poell, T., & de Waal, M. (2018). The platform society: Public values in a connective world. Oxford University Press. https://doi.org/10.1093/oso/9780190889760.001.0001

Williamson, B. (2017). Big data in education: The digital future of learning, policy and practice. SAGE. https://doi.org/10.4135/9781529714920

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

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