Algorithms in Scientific Work: A Qualitative Study of University Research Processes Between Engagement and Critical Reflection

This study examines the role of algorithms—particularly artificial intelligence—in scientific research processes and how automation intersects with expert knowledge and the autonomy of the researcher. Drawing on 25 qualitative interviews with Italian university scholars in the social sciences and humanities, the research explores how academics either incorporate or resist AI at various stages in their scientific work, the strategies they employ to manage the relationship between professional expertise and algorithmic systems and the forms of trust, caution or scepticism that characterise these interactions. The findings reveal diverse patterns of use, non-use and critical engagement, ranging from instrumental and efficiency-oriented adoption to dialogical experimentation and from identity-based resistance to systemic reflexivity regarding the institutional implications of AI. The study also highlights the need to thoroughly examine the characteristics of disciplinary scientific cultures, while highlighting the importance of promoting algorithmic awareness to support scientific rigour in the digital age.

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Publication Details

Journal
Societies
Published
2025-12-12
DOI
https://doi.org/10.3390/soc15120349
Primary Topic
Digital Education and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

Algorithms in Scientific Work: A Qualitative Study of University Research Processes Between Engagement and Critical Reflection

Maria Carmela Catone
Societies
Digital Education and Society
article

Algorithms in Scientific Work: A Qualitative Study of University Research Processes Between Engagement and Critical Reflection

Maria Carmela Catone
article en

Abstract

This study examines the role of algorithms—particularly artificial intelligence—in scientific research processes and how automation intersects with expert knowledge and the autonomy of the researcher. Drawing on 25 qualitative interviews with Italian university scholars in the social sciences and humanities, the research explores how academics either incorporate or resist AI at various stages in their scientific work, the strategies they employ to manage the relationship between professional expertise and algorithmic systems and the forms of trust, caution or scepticism that characterise these interactions. The findings reveal diverse patterns of use, non-use and critical engagement, ranging from instrumental and efficiency-oriented adoption to dialogical experimentation and from identity-based resistance to systemic reflexivity regarding the institutional implications of AI. The study also highlights the need to thoroughly examine the characteristics of disciplinary scientific cultures, while highlighting the importance of promoting algorithmic awareness to support scientific rigour in the digital age.

SocietiesVol. 15(12)
University of Salerno (IT)
Openalex Percentile: Top 48%
Digital Education and Society
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