CONCEPT
Typographical Hallucinations
Gitelman's lecture-series diagnostic: the mangled letterforms image-generating AI systems produce in otherwise plausible visual contexts, read as evidence of what the system does and does not know about human culture.
Between 2024 and 2025, Gitelman delivered lectures at the University of Pennsylvania and the University of Virginia analyzing the specific failure mode of image-generating AI: systems like DALL-E produce images whose typographic elements are garbled even when the surrounding visual context is coherent. The lectures refused to treat these failures as mere errors to be fixed. Instead, Gitelman approached them as documents that reveal the specific kind of knowledge that statistical pattern-matching produces. Her characteristic question — is there something that DALL-E 3 knows about typography, in short, that we don't? — treated the machine's output not as a success or failure relative to human standards but as evidence of the medium's distinctive operations. The typographical hallucination is a small-scale instance of a large-scale phenomenon: AI systems produce outputs plausible within their own statistical framework but failing when measured against the culturally embedded knowledge human practitioners bring to the same domain.
In The You On AI Field Guide
A typographer knows that letterforms obey