This essay examines how data-based practices contribute to new perspectives on the empirical value of images. Recent methods employing machine learning enable visualisations to be produced based on the large-scale analysis of data but that are detached from direct sensorial observation, subverting the forms of visual objectivity traditionally associated with technical and scientific methods of image-making. This research aims to develop insights into the forms of visual knowledge that these methods may give rise to, as well as facilitating critical discourse on the grounding of visual practices in relation to technical and scientific methods.
Powerful machine learning (ML) image generators have recently become widely accessible to non-experts including artists, designers, and the general public, which has contributed to contentious discussions on the new aesthetics and creative practices that have emerged as a result. ML enables believable simulations to be produced based on statistical models trained on datasets of multitudes of other images. Generative ML systems have received a great deal of visibility for the affordances they offer, allowing realistic photographic images to be generated based on text inputs without significant technical knowledge. While images may be treated as the product of or interchangeable with data, the theoretical implications of this perspective are connected to longer tendencies in the history of photography and digital graphics, whereby technical modes of imaging have often been framed as observational rather than interpretive. Such perspectives on visual media are in need of critical reassessment as new methods expose a rift between speculative aspects entailed in imaging and the capacity for images to present visual knowledge (Drucker 2020). “Synthetic Images: Data-based Aesthetics” examines interdisciplinary practices working with data-intensive forms of visualisation in relation to existing theories on the epistemic qualities of visual technologies.
Synthetic Images: Data-based Aesthetics
Published in Live Interfaces Journal
liveinterfacesjournal.ulusofona.pt/synthetic-images-data-based-aesthetics/
Live Interfaces is an open access, peer-reviewed and media-rich journal that aims to reflect on how specific understandings of ‘liveness’, ‘immediacy’, ‘timing’ and ‘flow’ manifest in performance with creative media, be they physical, electronic, digital or hybrid. It seeks to expose and discuss how different technologies and creative processes might convey original approaches to and/ or alienation from the physical body and the natural environment.