Call for Papers: Photography Network Annual CAA Sponsored Session
Photography in the Age of Artificial Intelligence
Whither “photography” in the age of Artificial Intelligence? The medium has experienced many identity crises since the 1830s, but the current one may be its most urgent. Increasingly, AI can produce images that convincingly mimic the look of photographs and trade on photographic credibility—inducing fears of deepfake deceptions, challenging what constitutes photographic labor and artistry, provoking accusations of copyright and privacy violation in the training sets used for machine learning, and opening both exciting and troubling frontiers in human-technology collaboration.
But most existentially, AI throws open the question: what is (now) a photograph?
This session invites scholars and artists to contemplate the status and identity of photography as we enter the era of ubiquitous artificial intelligence.
Questions may include:
How should we understand AI-generated images that look like, and are received as, camera-made photographs?
Ought we to police a boundary between photography and AI, or revise photography’s ontology to encompass AI?
Which methodological tools or case studies from the history of photography can aid us in navigating this new landscape?
What concepts might we draw from contemporary art, media studies, and other fields to theorize the desires, possibilities, and dangers attending photographic AI?
How do AI algorithms reinscribe/subvert cultural biases already established by, or in, photographs?
What forms might a critical artistic/photographic practice take now, vis-a-vis AI’s social, ethical, and artistic implications?
Interested in presenting? Email the following to session chair Sarah Miller, sarahmiller3737@me.com:
Abstract (250 words)
CV
CAA member ID
Address & phone
Adam Chin, Woman #1, 2021, from the series SAGAN. Selenium toned gelatin silver print, copyright Adam Chin 2023, courtesy of the artist.
SAGAN is a series of portraits generated by the Machine Learning algorithm Self-Attention Generative Adversarial Networks. For each portrait, 800 photographs are taken of the subject. The photographs are fed into a neural network, and the network is tasked with producing a new “photograph” that is indistinguishable from any of the original 800. To accomplish this task, the neural network employs an iterative process where the image evolves over the course of approximately 80,000 training cycles. In the course of this training, the neural network generates 8,000 attempts at a photograph. Of those 8,000 attempts, 16 are selected by the artist to form the final portrait.