A machine learning approach to design a DPSIR model: A real case implementation of evidence-based policy creation using AI

Abstract

In this paper a method to learn a similarity metric from expert assessments via questionnaires is presented. The approach employed provides a solution to the modelling of a DPSIR sustainability approach where budgetary resources are limited and thus there is a need to select the most informative variables from the identified possibilities. This paper also shows the proposed approach already implemented by the local council of Las Palmas of Gran Canaria as part of the work to create a sustainability system to better control the impact of human pressure in the local region. The metric is learned using a weakly supervised approach and the expert assessments are modelled through variable triplets. The employment of machine learning approaches in the creation of sustainability models is fairly recent and rare but presents a great opportunity to contribute to one of the main challenges that human societies have to face nowadays.