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Algorithm exploitation: Humans are keen to exploit benevolent AI

We cooperate with other people despite the risk of being exploited or hurt. If future artificial intelligence (AI) systems are benevolent and cooperative toward us, what will we do in return? Here we show that our cooperative dispositions are weaker when we interact with AI. In nine experiments, hum...

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Detalles Bibliográficos
Autores principales: Karpus, Jurgis, Krüger, Adrian, Verba, Julia Tovar, Bahrami, Bahador, Deroy, Ophelia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219775/
https://www.ncbi.nlm.nih.gov/pubmed/34189440
http://dx.doi.org/10.1016/j.isci.2021.102679
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author Karpus, Jurgis
Krüger, Adrian
Verba, Julia Tovar
Bahrami, Bahador
Deroy, Ophelia
author_facet Karpus, Jurgis
Krüger, Adrian
Verba, Julia Tovar
Bahrami, Bahador
Deroy, Ophelia
author_sort Karpus, Jurgis
collection PubMed
description We cooperate with other people despite the risk of being exploited or hurt. If future artificial intelligence (AI) systems are benevolent and cooperative toward us, what will we do in return? Here we show that our cooperative dispositions are weaker when we interact with AI. In nine experiments, humans interacted with either another human or an AI agent in four classic social dilemma economic games and a newly designed game of Reciprocity that we introduce here. Contrary to the hypothesis that people mistrust algorithms, participants trusted their AI partners to be as cooperative as humans. However, they did not return AI's benevolence as much and exploited the AI more than humans. These findings warn that future self-driving cars or co-working robots, whose success depends on humans' returning their cooperativeness, run the risk of being exploited. This vulnerability calls not just for smarter machines but also better human-centered policies.
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spelling pubmed-82197752021-06-28 Algorithm exploitation: Humans are keen to exploit benevolent AI Karpus, Jurgis Krüger, Adrian Verba, Julia Tovar Bahrami, Bahador Deroy, Ophelia iScience Article We cooperate with other people despite the risk of being exploited or hurt. If future artificial intelligence (AI) systems are benevolent and cooperative toward us, what will we do in return? Here we show that our cooperative dispositions are weaker when we interact with AI. In nine experiments, humans interacted with either another human or an AI agent in four classic social dilemma economic games and a newly designed game of Reciprocity that we introduce here. Contrary to the hypothesis that people mistrust algorithms, participants trusted their AI partners to be as cooperative as humans. However, they did not return AI's benevolence as much and exploited the AI more than humans. These findings warn that future self-driving cars or co-working robots, whose success depends on humans' returning their cooperativeness, run the risk of being exploited. This vulnerability calls not just for smarter machines but also better human-centered policies. Elsevier 2021-06-01 /pmc/articles/PMC8219775/ /pubmed/34189440 http://dx.doi.org/10.1016/j.isci.2021.102679 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Karpus, Jurgis
Krüger, Adrian
Verba, Julia Tovar
Bahrami, Bahador
Deroy, Ophelia
Algorithm exploitation: Humans are keen to exploit benevolent AI
title Algorithm exploitation: Humans are keen to exploit benevolent AI
title_full Algorithm exploitation: Humans are keen to exploit benevolent AI
title_fullStr Algorithm exploitation: Humans are keen to exploit benevolent AI
title_full_unstemmed Algorithm exploitation: Humans are keen to exploit benevolent AI
title_short Algorithm exploitation: Humans are keen to exploit benevolent AI
title_sort algorithm exploitation: humans are keen to exploit benevolent ai
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219775/
https://www.ncbi.nlm.nih.gov/pubmed/34189440
http://dx.doi.org/10.1016/j.isci.2021.102679
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