Les algorithmes publics déterministes au prisme du cas italien de la mobilité des enseignants

Giorgio Mancosu

2019-01-01

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Abstract

Undeniably, it is machine learning algorithms (and the big data they processing) that spark the most interest on the international forum, for their capability of “improving” humans and even outperformed them. However, recent events shows that the national legislators, upstream, and the public administrations, downstream, are still struggling with the much more elementary algorithms, aimed simply to “accelerate” the humans: these are the deterministic algorithms. A focus on the litigation generated by the algorithm in charge of teacher mobility during the 2016-2017 school year will allow, first, to highlight some transversal issues of the automated decision-making and then to deepening the specificities of administrative decision-making. Finally, we will consider the impact of the 2017 and 2018 reforms, aimed to implementing the paradigms of Open Source and “total transparency” in the public sector