Search for "Atlas of Anomalous AI" filetype:pdf or check academic repositories like arXiv and the Partnership on AI. You will find editions ranging from 2018 (the "classic era" of weird ImageNet classifications) to 2024 (the "generative hallucination" era).
A perfect factual answer is a database lookup. But a confident, beautiful, wrong answer? That requires creativity. When the AI tells you that "elevators are a type of bird," it is not just wrong. It is poetically wrong. atlas of anomalous ai pdf
A neural network views a red stop sign. 99.9% confidence. Then, someone places a few specific stickers on the sign—imperceptible chaos to a human eye. Suddenly, the AI sees a speed limit sign. The Atlas shows you the exact pixel modifications. It is terrifying because it proves AI doesn't "see" like we do; it sees statistical patterns. Search for "Atlas of Anomalous AI" filetype:pdf or
The Atlas features contributions from notable thinkers like , Catherine Malabou , and Suzanne Treister . These authors argue that instead of viewing AI as a "black box" of pure logic, we should see it as an extension of deep-seated human myths and biological processes. This shift in perspective is crucial for developing ethical and sustainable AI futures that are not purely extractive. Critical Reception But a confident, beautiful, wrong answer
While every version of the Atlas differs (it is a living document across several research groups), here are three classic anomalies you will likely find:
