A Voting-Based System for Ethical Decision Making

Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal prefere...

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Váldodahkkit: Noothigattu, Ritesh, Gaikwad, Snehalkumar "Neil" S., Awad, Edmond, Dsouza, Sohan, Rahwan, Iyad, Ravikumar, Pradeep, Procaccia, Ariel D.
Eará dahkkit: Massachusetts Institute of Technology. Media Laboratory
Materiálatiipa: Artihkal
Giella:English
Almmustuhtton: 2021
Liŋkkat:https://hdl.handle.net/1721.1/137819
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author Noothigattu, Ritesh
Gaikwad, Snehalkumar "Neil" S.
Awad, Edmond
Dsouza, Sohan
Rahwan, Iyad
Ravikumar, Pradeep
Procaccia, Ariel D.
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Noothigattu, Ritesh
Gaikwad, Snehalkumar "Neil" S.
Awad, Edmond
Dsouza, Sohan
Rahwan, Iyad
Ravikumar, Pradeep
Procaccia, Ariel D.
author_sort Noothigattu, Ritesh
collection MIT
description Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal preferences, and, when faced with a specific ethical dilemma at runtime, efficiently aggregate those preferences to identify a desirable choice. We provide a concrete algorithm that instantiates our approach; some of its crucial steps are informed by a new theory of swap-dominance efficient voting rules. Finally, we implement and evaluate a system for ethical decision making in the autonomous vehicle domain, using preference data collected from 1.3 million people through the Moral Machine website.
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spelling mit-1721.1/1378192022-09-26T15:00:37Z A Voting-Based System for Ethical Decision Making Noothigattu, Ritesh Gaikwad, Snehalkumar "Neil" S. Awad, Edmond Dsouza, Sohan Rahwan, Iyad Ravikumar, Pradeep Procaccia, Ariel D. Massachusetts Institute of Technology. Media Laboratory Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal preferences, and, when faced with a specific ethical dilemma at runtime, efficiently aggregate those preferences to identify a desirable choice. We provide a concrete algorithm that instantiates our approach; some of its crucial steps are informed by a new theory of swap-dominance efficient voting rules. Finally, we implement and evaluate a system for ethical decision making in the autonomous vehicle domain, using preference data collected from 1.3 million people through the Moral Machine website. 2021-11-08T20:30:09Z 2021-11-08T20:30:09Z 2018 2019-07-25T15:18:06Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137819 Noothigattu, Ritesh, Gaikwad, Snehalkumar "Neil" S., Awad, Edmond, Dsouza, Sohan, Rahwan, Iyad et al. 2018. "A Voting-Based System for Ethical Decision Making." en https://aaai.org/Library/AAAI/aaai18contents.php Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf arXiv
spellingShingle Noothigattu, Ritesh
Gaikwad, Snehalkumar "Neil" S.
Awad, Edmond
Dsouza, Sohan
Rahwan, Iyad
Ravikumar, Pradeep
Procaccia, Ariel D.
A Voting-Based System for Ethical Decision Making
title A Voting-Based System for Ethical Decision Making
title_full A Voting-Based System for Ethical Decision Making
title_fullStr A Voting-Based System for Ethical Decision Making
title_full_unstemmed A Voting-Based System for Ethical Decision Making
title_short A Voting-Based System for Ethical Decision Making
title_sort voting based system for ethical decision making
url https://hdl.handle.net/1721.1/137819
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