Research/Practice: Trevor Paglen: Adversarially Evolved Hallucination (Sternberg Press, 2024) (ISBN: 9783956795831)

Editor: Anthony Downey

How machine learning and computer vision generate images.

Although often considered to be a fault or a glitch in the system, the event of hallucination is central to the models of image production generated by artificial intelligence (AI). Through mining the latent space of computer vision, Trevor Paglen’s series Adversarially Evolved Hallucination (2017–ongoing) reveals this phantasmal and hallucinatory domain. In the conversation included in this volume, he discusses how we can think from within these opaque structures and, in turn, question the frequently inflated claims made on behalf of automated image production systems. In an accompanying essay, Anthony Downey explores the uncanny realm of algorithmically induced images and proposes that AI, through its generative modelling of the world, invariably estranges us from the present and the future.

Edited by Anthony Downey, the Research/Practice series focuses on artistic research and how it contributes to the formation of experimental knowledge systems. Drawing on primary materials such as technical specifications, preliminary content, datasets, digital and social media, informal communications, and project drafts, the series examines the inter and multidisciplinary research methods that artists employ in their practices. Each volume endeavors to ask: In their often speculative and yet purposeful approach to generating research, what forms of critical knowledge do artists produce?

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