Sabina Leonelli (TUM)
19 February 2026
Room 420, Via Festa del Perdono 3
20122 Milano
This lecture turns to the use of AI for scientific discovery. I examine examples of using AI methods for convenience and speed of inquiry, and dissect the very idea of convenience when applied to research. I demonstrate that apparently convenient uses of AI may turn out to be treacherous; and that resilient and responsible methods may involve highly domain- or phenomenon-specific systems, and/or the use of AI to avoid data sharing altogether, focusing instead on data analysis (as in the emerging literature on data visitations).
References
Leonelli, S. and Mussgnug, A. M. (2025) Convenience AI. Preprint. PhilSci Archive.
Hajek K, Trauttmansdorf P, Leonelli S, Guttinger S, Milano S (2025) How to Foster Responsible and Resilient Data: The Ethical Data Initiative. Computer 58(4): 95-99
Leonelli, S. (2025) What to Do about Data Distance? Responsible Alternatives to Data Sharing. Harvard Data Science Review 7(2)
Beaulieu, A. and Leonelli, S. (2021) Data and Society: A Critical Introduction. London, UK: SAGE.
