The ICB laboratory, ICMUB, and LIB, in partnership with CNRS Physics and the AI ​​cluster at the University of Burgundy Europe, co-organized a day dedicated to gender bias in artificial intelligence systems. Hosted at the Economics and Management Center (IAE), this event brought together researchers, faculty, staff, and students to discuss a topic at the intersection of science, technology, and societal challenges.

The morning session focused on the mechanisms underlying bias in artificial intelligence systems. Magalie Ochs (Aix-Marseille University) presented her work on algorithmic bias, while Dominique Ginhac (University of Burgundy Europe) demonstrated how choices made during the design of an AI system—such as the data used, annotation methods, and evaluation criteria—can influence the results produced.

Raphaël Scherrer then offered a reflection on the links between artificial intelligence and employment, specifically examining the representation of professions in digital tools and the potential consequences for recruitment processes.

The afternoon continued with a presentation by Isabelle Collet, a sociologist and professor at the University of Geneva, whose work has focused for many years on gender issues in the digital sector. Fanny Jourdan then presented various initiatives developed to identify and reduce bias in artificial intelligence projects.

Throughout the discussions, the presentations highlighted that the biases observed in AI systems are not solely technical. They often originate in the data, social representations, or methodological choices that accompany the design of digital tools. These observations underscore the importance of a multidisciplinary approach to developing more inclusive technologies better suited to the diversity of uses.

The day concluded with a discussion led by Fabrice Mériaudeau and Luca Nobile, opening up perspectives on actions to be pursued in the areas of research, training and awareness-raising.