The uses of generative artificial intelligence in social research north and south: Comparing empirical evidence from surveys in Denmark and Mexico

The rapid development of generative artificial intelligence (gen-AI) confronts the social sciences in the Global North and South with uncertainties along a spectrum between hopes for previously unimagined, leapfrogging potentials and fears of unprecedented risks that deepen divides. Lack of empirical data made it difficult to comprehend the situation and how to respond to it. To remedy this predicament, it is necessary to obtain empirical data to understand the extent and the ways in which these innovations are being used in research, teaching, and learning. This article compares evidence from pioneering surveys in Denmark and Mexico, of how gen-AI is used and perceived by faculty and students at institutions within these two strongly contrasting countries. The comparison reveals distinct patterns of usage by country, academic status, and gender. Normative assessments among respondents vary across different research phases and tasks in which gen-AI is deployed. Open survey items suggest uncertainty about gen-AI’s ethical and methodological suitability and a contrast between faculty emphasis on regulation and student prioritization of training. The comparison of the two data sets aims to provide a foundation for reflection and discussion about normative frameworks, facilitative initiatives, and collective interventions at this historical juncture of enormous methodological innovation.

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Publication Details

Journal
Methodological Innovations
Published
2026-06-24
DOI
https://doi.org/10.1177/20597991261454555
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

The uses of generative artificial intelligence in social research north and south: Comparing empirical evidence from surveys in Denmark and Mexico

Danay Quintana Nedelcu, Mauricio I. Dussauge Laguna, Markus S. Schulz, J W Andersen et al.
Methodological Innovations
Computational and Text Analysis Methods
article

The uses of generative artificial intelligence in social research north and south: Comparing empirical evidence from surveys in Denmark and Mexico

Danay Quintana Nedelcu, Mauricio I. Dussauge Laguna, Markus S. Schulz, J W Andersen, Oscar Fontanelli, Ligia Tavera Fenollosa, Jackeline Alba Udave
article en

Abstract

The rapid development of generative artificial intelligence (gen-AI) confronts the social sciences in the Global North and South with uncertainties along a spectrum between hopes for previously unimagined, leapfrogging potentials and fears of unprecedented risks that deepen divides. Lack of empirical data made it difficult to comprehend the situation and how to respond to it. To remedy this predicament, it is necessary to obtain empirical data to understand the extent and the ways in which these innovations are being used in research, teaching, and learning. This article compares evidence from pioneering surveys in Denmark and Mexico, of how gen-AI is used and perceived by faculty and students at institutions within these two strongly contrasting countries. The comparison reveals distinct patterns of usage by country, academic status, and gender. Normative assessments among respondents vary across different research phases and tasks in which gen-AI is deployed. Open survey items suggest uncertainty about gen-AI’s ethical and methodological suitability and a contrast between faculty emphasis on regulation and student prioritization of training. The comparison of the two data sets aims to provide a foundation for reflection and discussion about normative frameworks, facilitative initiatives, and collective interventions at this historical juncture of enormous methodological innovation.

Methodological Innovations
Aarhus University (DK), Facultad Latinoamericana de Ciencias Ecuador (EC), Facultad Latinoamericana de Ciencias Sociales Sede Académica México (MX)
Openalex Percentile: Top 3%
Computational and Text Analysis Methods
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