Art and AI

Maja Bak Herrie (Aarhus University)

From Image to Model and Back: Three Forms of Visual Ignorance

Abstract
As AI-generated content increasingly shapes how we encounter and interpret the world, the boundaries between knowledge and ignorance are becoming a key area of contention. But how is ignorance produced, and what role does aesthetics play in this process? Drawing on agnotology – the study of the deliberate production of ignorance – this lecture examines how images, and the institutions and systems through which they are produced, organised and interpreted, shape what can be known. It explores these questions through three contemporary artistic projects.

In *Ancestral Seeds* (2020), Nouf Aljowaysir engages with colonial photographic archives; in *ماه طلعت* (*Moon-faced*) (2022), Morehshin Allahyari reimagines Qajar portraiture; and in The Post-Truth Museum (2021–23), Nora Al-Badri uses deepfakes to address cultural heritage and institutional authority. Through these projects, I propose ‘visual ignorance’ as a concept for examining how ignorance is produced, negotiated and given visual form, particularly in relation to historical erasure and the authority to interpret cultural images.

Moving from image to model and back, the lecture considers how visual ignorance takes shape across different contexts, from the datasets that inform machine learning and image generation to the institutions that preserve and interpret cultural heritage. It asks how ignorance can be understood not simply as an absence of knowledge, but as something actively produced and expressed through aesthetic forms.

Bio
Maja Bak Herrie is an Assistant Professor in the Department of Art History, Aesthetics and Culture and Museology at Aarhus University. She works at the intersection of aesthetics, media theory and theories of knowledge, exploring computational imaging, technologies of vision, photography and artistic research. Her work investigates how images, data and technologies shape perception, as explored in her monograph *Thinking Through Data: How Outliers, Aggregates, and Patterns Shape Perception* (Stanford University Press, 2025). She is co-founder of AIIM: Centre for Aesthetics of AI Images, and co-editor of *The Nordic Journal of Aesthetics*.

Memo Files (University of California, San Diego) / Katie Peyton Hofstadter (Superradiance Centre for Entangled Intelligence and Planetary Consciousness)

Cosmosapience: Embodying our Planetary Mind

Francis Hunger (Academy of Fine Arts, Munich)

The Materiality of Data and its Aesthetic Consequences

Abstract
Databases have become central to the organisation of data and the processes of everyday human life. They lie at the heart of all software, and an examination of database practices enables media theory to realign its conceptual understanding of computing from ‘algorithms’ or ‘machines’ towards ‘data practices’. Databases are “media of cooperation” (Schüttpelz) and, as such, central to the data materialities of primary data, transactional data and analytical data. These three materialities are organised around a structuralist paradigm of world-making that arranges data into a formation to become in-formation (Krajewski). In contrast to these structured data materialities stands the probabilistic, synthetic approach of so-called ‘neural’ networks in so-called Artificial Intelligence, which produces a different data materiality: derivative data. The lecture explores these materialities and suggests their aesthetic implications.

Marie-France Rafael (Zurich University of the Arts)

Stitching the Code. Feminism and the Politics of Datasets

Angela Krewani (Philipps University of Marburg)

Making AI visible: Art and the material conditions of artificial intelligence

Constant Dullaart (Nuremberg Academy of Fine Arts)

Art in the Age of Synthetic – Speaker