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

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.