SHAPE: A Framework for Evaluating the Ethicality of Influence

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Agents often exert influence when interacting with humans and non-human agents. However, the ethical status of such influence is often unclear. In this paper, we present the SHAPE framework, which lists reasons why influence may be unethical. We draw on literature from descriptive and moral philosophy and connect it to machine learning to help guide ethical considerations when developing algorithms with potential influence. Lastly, we explore mechanisms for governing influential algorithmic systems, inspired by regulation in journalism, human subject research, and advertising.
Original languageEnglish
Title of host publicationMulti-Agent Systems - 20th European Conference, EUMAS 2023, Proceedings
EditorsVadim Malvone, Aniello Murano
Number of pages19
Publication statusPublished - 14 Sept 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14282 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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