AI in the Public Eye: Investigating Public AI Literacy Through AI Art

Drew Hemment · Morgan E. Currie · SJ Bennett · Jake Elwes · Anna Ridler · Caroline Sinders +2 more

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Art, Technology, and Culture Ethics and Social Impacts of AI Digital Media and Visual Art

Abstract

Recent advances in diffusion models and large language models have underpinned a new generation of powerful and accessible tools, and some of the most publicly visible applications are for artistic endeavour. Such tools, however, provide little scope for deeper understanding of AI systems, while the growing public interest in them can eclipse notice of the vibrant community of artists who have long worked with other forms of AI. We explore the potential for AI Art – particularly work in which AI is both tool and topic – to facilitate public AI literacies and consider how tactics developed before the current generative AI boom have continued relevance today. We look at the strategies of critical AI artists to scaffold public understanding of AI and enhance legibility for non-experts. This paper also investigates how collaborations between artists and AI researchers and designers can illuminate key technical and social issues relevant to the development of AI. The study entailed workshops between three professional artists who work with AI and a cross-disciplinary set of academic participants. This paper reports on these workshops and presents the intentions and strategies expressed by the artists, as well as insights of relevance to the research community on public AI literacies. We find that critical AI art can link underlying technical systems to structural issues of power and facilitate experiential learning that is situated and embodied, valuing interpretation over explanation. The findings also demonstrate the importance of transdisciplinary conversations around art, ethics and the political economy of AI technologies and how these dialogues may feed into AI design processes.

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References

1983Experiential Learning : Experience as the Source of Learning and Development 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor 2013Artificial hells: participatory art and the politics of spectatorship 2020Closing the AI accountability gap 2019From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices 2017Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age 2019Artificial Intelligence: American Attitudes and Trends 2019Algorithms of oppression: How search engines reinforce racism

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2024Rethinking open source generative AI: open washing and the EU AI Act 2024"I want it to talk like Darth Vader": Helping Children Construct Creative Self-Efficacy with Generative AI 2024Mediating Culture: Cultivating Socio-cultural Understanding of AI in Children through Participatory Design 2024Developing AI literacy in HRD: competencies, approaches, and implications 2024Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction

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