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.
Algorithms in Scientific Work: A Qualitative Study of University Research Processes Between Engagement and Critical Reflection
Catone M. C.
2025
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


