Images of Machine Learning
June 30 & July 1, 2021
Free registration and more information: https://imagesofml.ai/
Large image collections – from Sloan Sky Survey through to ImageNet – and their traversals through and by datasets, algorithmic functions and predictive models have become the operative ‘matter’ of contemporary AI. At the same time, machine learning assemblages have come to re-organise seeing itself as comprising processes of feature detection, convolutional accumulation of image/pixel building blocks and latent spaces. How have artists, cultural producers and critical AI scholars engaged with the ways in which images and machine learning have come to re-configure each other? What might redeployments of image-oriented machine-learning techniques tell us about the less than predictable sensibilities of AI’s visuality? This online symposium gathers artists and producers, media and STS thinkers together to think about and discuss such issues, collectively questioning how we might come to differently parse images of machine learning.
Organised by Anna Munster (University of New South Wales, Sydney, Australia) and Adrian MacKenzie (Australian National University, Canberra Australia) and supported by the Australian Research Council Discovery Project scheme.
Hosted by Media Futures Hub, UNSW.
Wednesday, June 30 2021, 3-6pm AEST
Keynote by Anna Ridler, artist and researcher
Automated Dreaming: Using AI in a Creative Practise
Panel 1: Images and Machine Learning Practices: critical interventions in art and curation
Thursday, July 1 2021, 3-6:30pm AEST
Keynote by Fabian Offert, Assistant Professor, History and Theory of Digital Humanities, UC Santa Barbara
Latent Deep Space: GANs between Art and Science
Panel 2: Images, machine learning and practices of knowledge-production