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AI Generative Art as Algorithmic Remediation
Bolter, Jay David (2023) , S. 195-207
As the essays in this collection demonstrate, AI generative imagery raises compelling theoretical and historical questions for media studies. One fruitful approach is to regard these AI systems as a medium rooted in the principle of remediation, because the AI models depend on vast numbers of samples of other media (painting, drawing, photography, and textual captions) scraped from the web. This algorithmic remediation is related to, but distinct from earlier forms of remix, such as hip-hop. To generate new images from the AI models, the user types in a textual prompt. The resulting text-image pairs constitute a kind of metapicture, as defined by William J.T. Mitchell in Picture Theory (1994).