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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallWhen a ChatGPT answer sounds too certain, ask: “What are you unsure about?” The question can prompt the model to identify ambiguity, missing context or parts of its answer that may need checking. I’ve found it a useful follow-up, but it is not a fact-check and it cannot guarantee a more accurate answer.
What this follow-up can—and cannot—do
The prompt gives ChatGPT an explicit opening to discuss uncertainty instead of simply continuing with its initial answer. That can help you spot a detail that depends on an unstated assumption, a question that needs more context, or a claim worth verifying.
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OpenAI’s GPT-5.2 prompting guidance says that model responses remain prompt-sensitive and steerable, and recommends making ambiguity handling explicit. That supports the general idea behind the question, but it does not test this exact wording or show that every ChatGPT model will respond equally well. The usefulness depends on the question, the context and whether the model surfaces a meaningful uncertainty.
Most importantly, a model’s account of what it is unsure about is still another model response. It may miss an error, sound confident about an unsupported claim, or offer a vague caveat. Treat it as a lead for follow-up—not independent evidence that the rest of the answer is correct.
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How to use it when an answer sounds too confident
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Read the answer and identify what is unclear: for example, a missing date, location, definition or source.
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Ask, “What are you unsure about?” You can make the request more specific by naming the claim or part of the answer you want examined.
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Use the reply to choose a next step: supply missing context, ask the model to state its assumptions, or check a factual claim against an appropriate source.
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For example, after a broad answer about a rule or recommendation, you might ask, “What are you unsure about in that answer, and what details would change it?” That asks the model to make uncertainty and relevant context more explicit; it does not establish that its response is complete.
When a different follow-up is more useful
“What are you unsure about?” is one option, not a universal best prompt. OpenAI’s prompting guidance and Model Spec describe other ways to handle ambiguity and insufficient confidence. Choose the follow-up that addresses the gap you actually see.
- Missing information: Ask, “What details do you need from me to answer this?” This invites clarification when the question lacks context.
- Hidden assumptions: Ask, “What assumptions are you making?” This is useful when an answer may depend on a particular interpretation or set of conditions.
- A claim that needs checking: Ask for sources or use an appropriate tool to verify it. A request to identify uncertainty does not itself supply corroboration.
These approaches serve different purposes; the cited guidance does not establish that one wording works better than another in every situation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why uncertainty matters—and why the prompt is not proof
OpenAI argues in “Why language models hallucinate” that accuracy-only evaluation can reward guessing. In an OpenAI-reported SimpleQA comparison, gpt-5-thinking-mini had a 52% abstention rate, 22% accuracy rate and 26% error rate; o4-mini had a 1% abstention rate, 24% accuracy rate and 75% error rate. Those figures apply to those two models in that specific evaluation. They are not measurements of the question “What are you unsure about?” or general rates for ChatGPT.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesOpenAI’s Model Spec says that when the assistant lacks sufficient confidence, it should use a tool to gather more information, hedge appropriately or explain that it cannot answer confidently. That principle is a reason to invite uncertainty into the conversation, not evidence that asking this particular question makes a response reliable.
For consequential claims, follow up with sources suited to the subject and check the relevant date, jurisdiction and context. If ChatGPT identifies a weak point, verify that point; if it does not, that silence is not confirmation.
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