Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/217724
Title: Encoding Ethics to Compute Value‑Aligned Norm
Author: Serramia, Marc
Rodriguez Soto, Manel
López Sánchez, Maite
Rodriguez Aguilar, Juan A.
Bistaffa, Filippo
Boddington, Paula
Wooldridge, Michael
Ansótegui Gil, Carlos José
Keywords: Intel·ligència artificial
Ètica
Optimització matemàtica
Artificial intelligence
Ethics
Mathematical optimization
Issue Date: 22-Nov-2023
Publisher: Springer Verlag
Abstract: Norms have been widely enacted in human and agent societies to regulate individuals’ actions. However, although legislators may have ethics in mind when establishing norms, moral values are only sometimes explicitly considered. This paper advances the state of the art by providing a method for selecting the norms to enact within a society that best aligns with the moral values of such a society. Our approach to aligning norms and values is grounded in the ethics literature. Specifically, from the literature’s study of the relations between norms, actions, and values, we formally define how actions and values relate through the so-called value judgment function and how norms and values relate through the so-called norm promotion function. We show that both functions provide the means to compute value alignment for a set of norms. Moreover, we detail how to cast our decision-making problem as an optimisation problem: finding the norms that maximise value alignment. We also show how to solve our problem using off-the-shelf optimisation tools. Finally, we illustrate our approach with a specific case study on the European Value Study.
Note: Reproducció del document publicat a: https://doi.org/10.1007/s11023-023-09649-7
It is part of: Minds and Machines, 2023, vol. 33, p. 761-790
URI: https://hdl.handle.net/2445/217724
Related resource: https://doi.org/10.1007/s11023-023-09649-7
ISSN: 0924-6495
Appears in Collections:Articles publicats en revistes (Matemàtiques i Informàtica)

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