Public defence in Photography, MA Sheung Yiu

We are creating more images than ever before. Photographs and their lookalikes saturate our fi eld of vision with information and stimuli. The sheer volume of images readily available online opens up new possibilities for image processing through large-scale computation—a fusion of sensor data visualizations, photography, computer simulations, and AI hallucinations. These photographic doppelgängers are not merely snapshots captured by a camera; they are technical artifacts produced by larger-than-human-scale computational processes. I call them Hyperimages.

The doctoral thesis presents a theory to understand the recent computational turn in photography through the concept of scale. Using photographic realism as a reference point, the thesis discusses how ‘large-scale’ displaces ‘indexicality’ as the epistemic virtue of image-making in hyperimage practices. The theory articulates the multiple ways scale is relevant to contemporary visual culture: Scale as the milieu in the age of overabundance of images, big data, and large vision models. Scale, as in large-scale deep learning models that extract statistical patterns from the mass of photography readily available online. Scale as an act of imaging, revealing aspects of the world by resolving a frame from the space-time continuum, or sampling patterns from training data. Finally, scalability as a philosophy driving the creation of hyperimages. Behind the apparent visual abundance, however, scalability appears to displace the humanistic pursuit of meaning, truth, and beauty in image-making. Examining hyperimage practices through the lens of scale, the thesis articulates the aesthetic politics behind the datafication of photographic seeing.

Title of the thesis: Hyperimage: Photography Beyond The Human Scale

Thesis defender: Sheung Yiu
Opponent: Prof. Seán Cubitt, Honorary Professorial Fellow, University of Melbourne, Australia
Custos: Prof. Harri Laakso, Aalto University School of Arts, Design and Architecture