In a recent talk, @nilspooker very convincingly compared the way visual patterns are reproduced and amplified in AI #ImageGeneration to the practice of art forgery: forgers like van Meegeren or Beltracchi were highly successful at not only matching but even overfulfilling the stylistic expectations attached to an artist's name. What I like so much about this comparison is that it allows us to think about the media specificity of fakery. While paintings have been forged ever since there was an art market, photographs are rather manipulated than forged, and what is considered inauthentic fundamentally differs between painting and photography.
Forging a painting is about imitating a style and falsely attributing a unique artifact to an individual author who did not create it. Manipulating a photograph, however, is usually not about authorship, but about the relationship between a reproducible image and the reality it's meant to depict. Faking photographs, therefore, traditionally meant somehow interfering with the photographic process, be it by staging events that never happened, retouching the photographic surface, or combining elements from different photographs into one image.
AI image synthesis may seem to resemble the latter, but it's actually more like forging a painting: there's no actual photo to begin with, only a statistical process aimed at fulfilling the visual expectations associated with a particular label – whether that label is »Vermeer« or »documentary photo«. But the history of art forgery also shows us, as Nils has pointed out, that these expectations are historically conditioned: What looked like a Vermeer in the 1930s now appears to be a rather crude forgery – and what appears like a photo today might indeed reveal us the limits of our visual expectations of what a convincing photograph looks like.
#PlatformRealism