Towards value-awareness in administrative processes: an approach based on constraint answer set programming

Joaquín Arias, Mar Moreno-Rebato, José Antonio Rodríguez-García, Sascha Ossowski

Abstract: The proposed regulatory framework for Artificial Intelligence and the EU General Data Protection Regulation oblige automated reasoners to justify their conclusions in human-understandable terms. In addition, ethical and legal concerns must be provably addressed to ensure that the advice given by AI systems is aligned with human values. Value-aware systems tackle this challenge by explicitly representing and reasoning with norms and values applicable to a problem domain. For instance, in the context of a public administration such systems may provide support to decision-makers in the design and interpretation of administrative procedures and, ultimately, may enable the automation of (parts of) these administrative processes. However, this requires the capability to analyze as to how far a particular legal model is aligned with a certain value system.In this work, we take a step forward in this direction by analysing and formally representing two (political) strategies for school place allocation in educational institutions supported by public funds. The corresponding (legal) norms that specify this administrative process differently weigh human values such as equality, fairness, and non-segregation.We propose the use of s(LAW), a legal reasoner based on Answer Set Programming that has proven capable of adequately modelling administrative processes in the presence of vague concepts and/or discretion, to model both strategies. We illustrate how s(LAW) simultaneously models different scenarios, and how automated reasoning with these scenarios can answer questions related to the value-alignment of the resulting models.