Protocol for Studies from Generative AI in Social Sciences

Authors

DOI:

https://doi.org/10.35362/issn.1850-0013-1053

Keywords:

artificial intelligence, protocol, social sciences, research

Abstract

Generative artificial intelligence (AI) is breaking into higher education with the potential to revolutionize teaching, learning, and research. However, its integration into social science research, especially in digital ethnography, raises questions about its limitations and ethical implications. This article proposes a protocol for exploratory studies using generative AI in social sciences. Firstly, it considers the potential of AI to analyze large volumes of data, identify patterns, and generate hypotheses. Secondly, it highlights “exploration” as a key tool in digital ethnography. The protocol includes identifying the way of knowing, selecting AI tools, collecting and analyzing data, and generating conclusions. Its implementation is reflected upon as a valuable resource for systematic and rigorous research. Finally, the article concludes that generative AI, together with the proposed protocol, can transform social research.

Downloads

Download data is not yet available.

Author Biography

Lucrecia Agustina Sotelo, National University of Southern Patagonia (UNPA)

Postdoctoral researcher in multidisciplinary studies, Center for Advanced Studies, National University of Córdoba, Argentina. Research professor at the National University of Southern Patagonia (UNPA). Coordinator of the Network for Studies on the Beginnings of University Life.

References

Amozurrutia, J. A. (2011). Complejidad y Ciencias Sociales. Un modelo adaptativo para la investigación interdisciplinaria. México: UNAM.

Feenberg, A. (2012). Transformar la tecnología. Una nueva visita a la teoría crítica. Bernal: Universidad de Quilmes.

Garcia Peñalvo, F. J. (2024). Inteligencia Artificial Generativa: un análisis desde múltiples perspectivas. Education in the Knowledge Society, 25. DOI: https://doi.org/10.14201/eks.31942.

González Alcaide, G. (s/f). Inteligencia artificial generativa: Un contexto disruptivo en el acceso a la información. Infonomy, 2(1), e24013. DOI: https://doi.org/10.3145/infonomy.24.013.

Goyanes, M. & Lopezosa, C. (2024). ChatGPT en educación: Usos, retos y oportunidades de la Inteligencia Artificial Generativa en Educación. Buenos Aires: GEDISA.

Guersenzvaig, A., Sánchez-Monedero, J., Picassó i Piquer, M. & Gopegui, B. (s/f). Inteligencia artificial generativa en la educación universitaria: la urgencia de una perspectiva crítica. Daimon. Revista Internacional de Filosofía, en prensa. DOI: http://dx.doi.org/10.6018/daimon.636721.

Mata, M. M. (2023). Indisciplinada. Buenos Aires: Fundación Friedrich Ebert.

Pichardo, J. I., Borrás-Gené, O., Santoro Domingo, P., Martínez Álvaro, L. & Carabantes-Alarcó, D. (2024). Inteligencia artificial generativa como recurso en los procesos de enseñanza y aprendizaje en educación superior. En J. L. Ayala Rodrigo (Coord.), III Jornada «Aprendizaje Eficaz con TIC en la UCM» (33-46). DOI: https://dx.doi.org/10.5209/act.001.

Rosa, H. (2016). Alienación y aceleración. Hacia una teoría crítica de la temporalidad en la modernidad tardía. Buenos Aires: Katz.

Rosa, H. (2020). Resonancia. Una sociología de la relación con el mundo. Buenos Aires: Katz.

Sotelo, L. (2018). Estudiar en los confines. Río Gallegos: UNPAEdita.

Sotelo, L (2025) Desigualdad digital y virtualización forzada: el ingreso a la universidad pública argentina en pandemia. Revista IRICE, (48), e2030. Recuperado de: https://ojs.rosario-conicet.gov.ar/index.php/revistairice/article/view/2030.

Downloads

Published

2026-09-14

How to Cite

Sotelo, L. A. (2026). Protocol for Studies from Generative AI in Social Sciences. Revista Iberoamericana De Ciencia, Tecnología Y Sociedad - CTS (Ibero-American Science, Technology and Society Journal), 21, 267–290. https://doi.org/10.35362/issn.1850-0013-1053

Issue

Ethical Commitments Regarding Artificial Intelligence

Section

Selected articles

License

Copyright (c) 2025 CC Attribution 4.0

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All CTS's issues and academic articles are under a CC-BY license.

Since 2007, CTS has provided open and free access to all its contents, including the complete archive of its quarterly edition and the different products presented in its electronic platform. This decision is based on the belief that offering free access to published materials helps to build a greater and better exchange of knowledge.

In turn, for the quarterly edition, CTS allows institutional and thematic repositories, as well as personal web pages, to self-archive articles in their post-print or editorial version, immediately after  the publication of the final version of each issue and under the condition that a link to the original source will be incorporated into the self-archive.