research-article

The role of experts in the public perception of risk of artificial intelligence

Authors:

Fabio CozmanAuthors Info & Claims

AI & SOCIETY, Volume 35, Issue 3

Pages 663 - 673

https://doi.org/10.1007/s00146-019-00924-9

Published: 01 September 2020 Publication History

Abstract

The goal of this paper is to describe the mechanism of the public perception of risk of artificial intelligence. For that we apply the social amplification of risk framework to the public perception of artificial intelligence using data collected from Twitter from 2007 to 2018. We analyzed when and how there appeared a significant representation of the association between risk and artificial intelligence in the public awareness of artificial intelligence. A significant finding is that the image of the risk of AI is mostly associated with existential risks that became popular after the fourth quarter of 2014. The source of that was the public positioning of experts who happen to be the real movers of the risk perception of AI so far instead of actual disasters. We analyze here how this kind of risk was amplified, its secondary effects, what are the varieties of risk unrelated to existential risk, and what is the dynamics of the experts in addressing their concerns to the audience of lay people.

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Cited By

Altmeyer PDemetriou ABartlett ALiem CSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)PositionProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692121(1222-1242)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692121
Recki LLawo DKrauß VPins DBoden A(2024)"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCIProceedings of the ACM on Human-Computer Interaction10.1145/36869968:CSCW2(1-25)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686996
Shah CWhite RThomas PMitra BSarkar SBelkin N(2023)Taking Search to TaskProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578288(1-13)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578288
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cover image AI & Society

AI & Society Volume 35, Issue 3

Sep 2020

256 pages

ISSN:0951-5666

Issue’s Table of Contents

© Springer-Verlag London Ltd., part of Springer Nature 2019.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 September 2020

Accepted: 31 October 2019

Received: 22 May 2019

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Cited By

Altmeyer PDemetriou ABartlett ALiem CSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)PositionProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692121(1222-1242)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692121
Recki LLawo DKrauß VPins DBoden A(2024)"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCIProceedings of the ACM on Human-Computer Interaction10.1145/36869968:CSCW2(1-25)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686996
Shah CWhite RThomas PMitra BSarkar SBelkin N(2023)Taking Search to TaskProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578288(1-13)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578288
Lehtiö AHartikainen MAla-Luopa SOlsson TVäänänen K(2022)Understanding citizen perceptions of AI in the smart cityAI & Society10.1007/s00146-022-01589-738:3(1123-1134)Online publication date: 24-Nov-2022
https://dl.acm.org/doi/10.1007/s00146-022-01589-7
Sartori LBocca G(2022)Minding the gap(s): public perceptions of AI and socio-technical imaginariesAI & Society10.1007/s00146-022-01422-138:2(443-458)Online publication date: 26-Mar-2022
https://dl.acm.org/doi/10.1007/s00146-022-01422-1

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