Images of Machine Learning

Online Symposium

June 30 & July 1 2021 

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.

An online symposium, chaired by Anna Munster (University of New South Wales, Sydney, Australia) and Adrian MacKenzie (Australian National University, Canberra, Australia).

Wednesday, June 30 2021, 3-6pm AEST

Keynote by Anna Ridler, artist and researcher

Automated Dreaming: Using AI in a Creative Practice

Anna Ridler is an artist and researcher who works with systems of knowledge and how technologies are created in order to better understand the world. She is particularly interested in ideas around measurement and quantification and how this relates to the natural world. Her process often involves working with collections of information or data, particularly datasets, to create new and unusual narratives. Her work has been exhibited at cultural institutions worldwide including the Victoria and Albert Museum, Tate Modern, the Barbican Centre, Centre Pompidou, HeK Basel, the ZKM Karlsruhe, Ars Electronica, Sheffield Documentary Festival and the Leverhulme Centre for Future Intelligence. She was a European Union EMAP fellow and the winner of the 2018-2019 DARE Art Prize.

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

Fabian Offert is tenure track Assistant Professor in the History and Theory of Digital Humanities at the University of California, Santa Barbara. His research investigates machine learning as a critical technical practice in the digital humanities, with a special interest in the epistemology of machine vision. At UCSB, he is affiliated with the Center for Responsible Machine Learning and principal investigator of the UCHRI multi campus research group “Critical Machine Learning Studies”. Previously, Fabian was Postdoctoral Researcher in the DFG priority program “The Digital Image” (SPP 2172) and Affiliated Researcher in the Artificial Intelligence and Media Philosophy Research Group (KIM) at Karlsruhe University of Arts and Design. He has also worked for a number of German cultural institutions, including ZKM | Center for Art and Media Karlsruhe, Goethe-Institut New York, and Ruhrtriennale Festival of the Arts. Website: 

zentralwerkstatt.org
Panel 2: Images, machine learning and practices of knowledge-production