Abstract

In this paper we argue that machine learning (ML) could contribute to develop regional policies by both improving the evaluation of the programs that are carried out and offering to the policy makers new tools to design them in a way that ensures higher effectiveness. We show two examples of the uses of such algorithms to tailor a couple of programs carried out in Italy. We also discuss some of the issues involved with the use of ML, showing that the methodological advances bring along some challenges concerning the interpretability of the algorithms, the transparency and the possibility that ML-based policies could lead to unwanted outcomes.