recommendations. Hallucination In generative AI, “hallucination” refers to the phenomenon in which the system produces fictional, misleading, or unintended content and presents it as if it were factual. Examples include a text model making claims that are unrelated to actual facts, or an image model adding objects that were not mentioned in the input description. This occurs because generative AI systems produce responses through statistical predictions that are based on data patterns, a process that is inherently disconnected from evaluating whether something is true. In this sense, one could argue that all generative AI outputs are a kind of hallucination, as they are not grounded in factual verification. However, in everyday usage, the term “AI hallucination” likely refers to outputs that are factually inaccurate or false. Some also view the term “hallucination” as inappropriate, because it anthropomorphizes AI systems—as if they were having sensory experiences. Alternatives such as “dis/misinformation,” or even “bullshit” are sometimes considered more suitable. RAG Retrieval-Augmented Generation (RAG) is a technique designed to improve the accuracy of generative AI systems by addressing one of 20 21