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

Walker, Johanna; Thuermer, Gefion; Vicens, Julian; Simperl, Elena

doi:10.1145/3600211.3604715

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Other1

Article1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction

Shelby,

Rismani,

Rostamzadeh

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction

Shelby,

Rismani,

Rostamzadeh

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

Critical Climate Machine: A Visual and Musical Exploration of Climate Misinformation through Machine Learning

Robillard,

Nika

2024

Proc. ACM Comput. Graph. Interact. Tech.

View full text Add to dashboard Cite

Critical Climate Machine is a cutting-edge media art installation that critically exposes and quantifies mechanisms of climate change misinformation. Utilizing computational aesthetics across data, imagery, and sound, this work processes real-time data from X (Twitter) through a natural language processing learning model derived from cognitive sciences. It not only renders the statistical aspects of this data visually but also manifests its thermal effects. A unique audio dimension is introduced through dialogues between climate skeptics and climate advocates, processed by the generative machine learning (ML) algorithm Dicy2. These elements collectively shape the installation, each unveiling its distinctive algorithmic aesthetics and technical underpinnings. This paper concentrates on the dual application of ML algorithms: one for dissecting extensive online misinformation streams, and the other for creating climate-related dialogues. This dual approach opens a discussion on the mediation of climate, at the convergence of computational and physical realms. Our aim is to critically examine the role of ML technologies in crafting aesthetic experiences that resonate within scientific discourse and public debate on climate issues.

show abstract

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

Cited by 2 publications

References 45 publications

Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction

Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction

Critical Climate Machine: A Visual and Musical Exploration of Climate Misinformation through Machine Learning

Contact Info

Product

Resources

About