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We study a class of {\em aggregation rules} that could be applied to ethicalAI decision-making. These rules yield the decisions to be made by automatedsystems based on the information of profiles of preferences over possiblechoices. We consider two different but very intuitive notions of preferences ofan alternative over another one, namely {\it pairwise majority} and {\itposition} dominance. Preferences are represented by permutation processes overalternatives and aggregation rules are applied to obtain results that aresocially considered to be ethically correct. In this setting, we find manyaggregation rules that satisfy desirable properties for an autonomous system.We also address the problem of the stability of the aggregation process, whichis important when the information is variable. These results are a contributionfor an AI designer that wants to justify the decisions made by an autonomoussystem.\\ \textit{Keywords:} Aggregation Operators; Permutation Process;Decision Analysis.

Classes of Aggregation Rules for Ethical Decision Making in Automated Systems