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The reasons for generative AI’s problems are no mystery. Large language models like those that underlie ChatGPT work by predicting characters in a sequence, mapping statistical relationships between bits of text and the ideas they represent. Yet prediction, by definition, is not certainty. Chatbots are very good at producing writing that sounds convincing, but they do not make decisions according to what’s factually correct. Instead, they arrange patterns of words according to what “sounds” right. Meanwhile, these products’ internal algorithms are so large and complex that researchers cannot hope to fully understand their abilities and limitations. For all the additional protections tech companies have added to make AI more accurate, these bots can never guarantee accuracy. The embarrassing failures are a feature of AI products, and thus they are becoming features of the broader internet.