Recently, a woman slowed down a line at the post office, waving her phone at the clerk. ChatGPT told her there’s a “price match promise” on the USPS website. No such promise exists. But she trusted what the AI “knows” more than the postal worker—as if she’d consulted an oracle rather than a statistical text generator accommodating her wishes.
This scene reveals a fundamental misunderstanding about AI chatbots. There is nothing inherently special, authoritative, or accurate about AI-generated outputs. Given a reasonably trained AI model, the accuracy of any large language model (LLM) response depends on how you guide the conversation. They are prediction machines that will produce whatever pattern best fits your question, regardless of whether that output corresponds to reality.
Despite these issues, millions of daily users engage with AI chatbots as if they were talking to a consistent person—confiding secrets, seeking advice, and attributing fixed beliefs to what is actually a fluid idea-connection machine with no persistent self. This personhood illusion isn’t just philosophically troublesome—it can actively harm vulnerable individuals while obscuring a sense of accountability when a company’s chatbot “goes off the rails.”
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