Writing / Conference paper
Critical Averaging and the Politics of Statistical Representation
Abstract
Critical Averaging examines decisions made before a system's fairness can be assessed: task formulation, selection, weighting and representation. A generative artwork exposes these operations by constructing weighted averages of national flags across several representational spaces. The France, Uruguay and Palestine case demonstrates how a choice of weights or representation can erase smaller populations or change what an apparently simple average depicts.
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Citation
Laurenzo, Tomas. Critical Averaging and the Politics of Statistical Representation. In Proceedings of the 19th Ibero-American Conference on Artificial Intelligence (IBERAMIA 2026), Asunción, Paraguay, 18–20 November 2026. Lecture Notes in Artificial Intelligence (LNCS/LNAI), Springer, Cham. Forthcoming.