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Properties of Aggregation Operators Relevant for Ethical Decision Making in Artificial Intelligence

Author

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  • Federico Fioravanti

    (Universidad Nacional del Sur/CONICET)

  • Iyad Rahwan

    (Max Planck Institute for Human Development)

  • Fernando Tohmé

    (Universidad Nacional del Sur/CONICET)

Abstract

We present an axiomatic study of aggregation operators that could be applied to ethical AI decision making. The information is given here by different preferences over the decisions to be made by automated systems. We consider two different but very intuitive notions of preference of an alternative over another one, namely pairwise majority and position dominance. Preferences are represented by permutation processes over alternatives and aggregation rules are applied to obtain results that are socially considered to be ethically correct. We address the problem of the stability of the aggregation process, which is important when the information is variable. In this setting we find many aggregation rules that satisfy desirable properties for an autonomous system.

Suggested Citation

  • Federico Fioravanti & Iyad Rahwan & Fernando Tohmé, 2022. "Properties of Aggregation Operators Relevant for Ethical Decision Making in Artificial Intelligence," Working Papers 177, Red Nacional de Investigadores en Economía (RedNIE).
    • Handle: RePEc:aoz:wpaper:177
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    File URL: https://rednie.eco.unc.edu.ar/files/DT/177.pdf
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    References listed on IDEAS

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    Keywords

    Aggregation Operators; Permutation Process; Decision Analysis;
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