AI Art and Misinformation - Approaches and Strategies for Media Literacy and Fact Checking

TY - CHAP

T1 - AI Art and Misinformation - Approaches and Strategies for Media Literacy and Fact Checking

AU - Walker, Johanna

AU - Thuermer, Gefion

AU - Vicens, Julian

AU - Simperl, Elena Paslaru Bontas

N1 - Funding Information: MediaFutures is part of the European S+T+Arts programme. It offers grant funding and support for startups and artists, via open calls held in 2020, 2021 and 2022. In MediaFutures, artists are asked to use data as an art material to create works that question the impact of misinformation on individuals and society. The 1st cohort graduated in September 2021, the 2nd cohort graduated in April 2022 and a 3rd cohort started in November 2022 and will graduate in June 2023. Publisher Copyright: © 2023 Owner/Author.

PY - 2023/8/8

Y1 - 2023/8/8

N2 - Misinformation in its many forms is a substantial and growing problem for society today. Whether financially or ideologically motivated, purveyors of misinformation do not abide by legal, technical or moral rules. Therefore new, ludic, narrative, gamified and artistic approaches are needed. In this paper we analyse the approaches taken in countering misinformation by 18 AI and machine learning works of art, developed in the MediaFutures project. We examine how these align with existing AI approaches to countering misinformation, and how they address some of the key challenges. We show that AI artists engage with existing debunking and inoculating strategies, including highly technical aspects such as deepfakes, while also utilizing focused strategies of data literacy and collective intelligence. We also find that they are able to integrate hard-to-refute strategies such as narrative and emotion. These findings suggest that data as an art material and AI techniques as art tools are worth of further investigation as to their effectiveness for countering misinformation within society.

AB - Misinformation in its many forms is a substantial and growing problem for society today. Whether financially or ideologically motivated, purveyors of misinformation do not abide by legal, technical or moral rules. Therefore new, ludic, narrative, gamified and artistic approaches are needed. In this paper we analyse the approaches taken in countering misinformation by 18 AI and machine learning works of art, developed in the MediaFutures project. We examine how these align with existing AI approaches to countering misinformation, and how they address some of the key challenges. We show that AI artists engage with existing debunking and inoculating strategies, including highly technical aspects such as deepfakes, while also utilizing focused strategies of data literacy and collective intelligence. We also find that they are able to integrate hard-to-refute strategies such as narrative and emotion. These findings suggest that data as an art material and AI techniques as art tools are worth of further investigation as to their effectiveness for countering misinformation within society.

UR - http://www.scopus.com/inward/record.url?scp=85173605089&partnerID=8YFLogxK

U2 - 10.1145/3600211.3604715

DO - 10.1145/3600211.3604715

M3 - Conference paper

T3 - AIES 2023 - Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

SP - 26

EP - 37

BT - AIES 2023 - Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

PB - ACM

T2 - 6th ACM/AAAI AI Ethics and Society

Y2 - 8 August 2023 through 10 August 2023

ER -