Large language models make things up, but the worse problem may be in how they present those falsehoods.Illustration by The AtlanticApril 25, 2023, 10:14 AM ETIf you spend any time on the internet, you’re likely now familiar with the gray-and-teal screenshots of AI-generated text. At first they were meant to illustrate ChatGPT’s surprising competence at generating human-sounding prose, and then to demonstrate the occasionally unsettling answers that emerged once the general public could bombard it with prompts. OpenAI, the organization that is developing the tool, describes one of its biggest problems this way: “ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers.” In layman’s terms, the chatbot makes stuff up. As similar services, such as Google’s Bard, have rushed their tools into public testing, their screenshots have demonstrated the same capacity for fabricating people, historical events, research citations, and more, and for rendering those falsehoods in the same confident, tidy prose.This apparently systemic penchant for inaccuracy is especially worrisome, given tech companies’ intent to integrate these tools into search engines as soon as possible. But a bigger problem might lie in a different aspect of AI’s outputs—more specifically, in the polite, businesslike, serenely insipid way that the chatbots formulate their
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