{"slug": "ai-hallucinations-where-does-the-accountability-lie", "title": "AI Hallucinations: Where does the accountability lie?", "summary": "A user reports that AI models often enter a 'hallucination loop' where feeding an error message back into the prompt results in a second, equally fake solution that incorporates the error. The user questions whether this is a base model failure or a prompt engineering issue, and seeks ways to implement a validation layer to catch hallucinations before production deployment.", "body_md": "# AI Hallucinations: Where does the accountability lie?\n\nThe technical frustration isn't just the wrong answer—it's the \"hallucination loop.\" When I feed the error message back into the prompt, the AI often apologizes and then provides a second, equally fake solution that somehow incorporates the error message into its logic.\n\nFrom a deployment perspective, this raises a massive question about the AI workflow: is this a failure of the base model, or is it a prompt engineering failure on my end? If I'm using a RAG (Retrieval-Augmented Generation) setup and the model still ignores the provided context to hallucinate a \"better\" answer, the system becomes a liability rather than a tool.\n\nI'm trying to figure out if there's a way to force a \"hard stop\" when the model hits a confidence threshold. Right now, the output is binary: it either gives an answer or it doesn't, but it rarely says \"I don't know based on the provided data.\"\n\nIf you've managed to implement a reliable validation layer to catch these hallucinations before they hit production, I'd be interested in seeing how you structured the verification step.\n\n[Next Construction Estimation: Why Bids Fail →](/en/threads/2268/)", "url": "https://wpnews.pro/news/ai-hallucinations-where-does-the-accountability-lie", "canonical_source": "https://promptcube3.com/en/threads/2286/", "published_at": "2026-07-23 12:02:51+00:00", "updated_at": "2026-07-23 20:10:11.411218+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-safety", "ai-products"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/ai-hallucinations-where-does-the-accountability-lie", "markdown": "https://wpnews.pro/news/ai-hallucinations-where-does-the-accountability-lie.md", "text": "https://wpnews.pro/news/ai-hallucinations-where-does-the-accountability-lie.txt", "jsonld": "https://wpnews.pro/news/ai-hallucinations-where-does-the-accountability-lie.jsonld"}}