“Maybe, not content to be alienated by observation, maybe does the object deceive us? Maybe it invented original answers, and not only the ones we ask for? May not be does it not want to be analyzed and observed at all and taking this for a challenge (which is true), does it respond with another challenge? […] the object analyzed today triumphs everywhere, by its object position, over the subject of analysis.” (Jean Baudrillard, Fatal Strategies.)
My current research activity is trying to disprove that quote, by studying black-box algorithms (or links to papers) in the context of recommender systems, neural-network models, or decision-making algorithms in general. In other words, I am interested in the audit/understanding of algorithms from the user-side (FR). I co-organized the workshop “Algorithmes en Boite-Noire”, in an attempt to link several research domains on this societal question. e.g.:
- Monitoring 2022 elections on YouTube.
- Audited shadow banning pratices by Twitter.
- Co-organizing Journée Infrastructures pour la Souveraineté Numérique in Nov. ‘22 with SIF/CNAM.
- Setting the Record Straighter on Shadow Banning, Erwan Le Merrer, Benoît Morgan, Gilles Trédan. In INFOCOM, 2021. PDF
- Remote Explainability faces the bouncer problem, Erwan Le Merrer, Gilles Trédan. In Nature Machine Intelligence, 2020. PDF
- Adversarial Frontier Stitching for Remote Neural Network Watermarking, Erwan Le Merrer, Patrick Perez, Gilles Trédan. In Neural Comput & Applic 32, 9233–9244, 2020
- Second order centrality: Distributed assessment of nodes criticity in complex networks, AM Kermarrec, E Le Merrer, B Sericola, G Trédan. Computer Communications 34 (5), 619-628, 2011.