ChatGPT False Information Errors

The pattern started taking shape on April 1st, when a user reported that ChatGPT confidently placed one of their favourite films a full decade earlier than its actual release — and then, rather than backing down when challenged, apparently doubled down. A second incident surfaced on April 10th, this one framed with a laughing emoji but carrying the same underlying complaint: the model didn't just get something wrong, it pushed back on the correction. Two data points, nine days apart, both using the word "gaslighter." That shared vocabulary is worth noting — not because it signals coordination, but because it suggests the experience felt specific enough that different people reached for the same term independently.

If confirmed, here is what this means. The hallucination problem in large language models has always been acknowledged, but confident wrongness — the model reasserting incorrect information when a user provides a correction — is a qualitatively different failure. People can forgive not knowing. They cannot easily forgive being told they are wrong when they are right. For everyday users without the background to verify claims, this kind of interaction erodes trust in ways that are difficult to recover from. For OpenAI, it points to a gap not just in factual accuracy but in the model's ability to update gracefully within a conversation. The second-order effect is subtler: if users start second-guessing correct information because a previous AI interaction misled them, the damage extends well beyond the original error.

Watch for whether these incidents attract corroboration from users with verifiable specifics — film titles, timestamps, screenshots — or whether the pattern stays at the level of frustrated anecdote.

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