Why LLM Confidence Scores Are Unreliable and Misleading

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A blog post published on July 27, 2026, by Justin Flick argues against using large language models to self-report confidence scores on their outputs. The piece contends that LLMs are not designed to accurately assess their own certainty, making such scores potentially misleading. The post gained traction on Hacker News, accumulating 39 points and sparking discussion. The core concern is that developers and users may place undue trust in AI outputs when accompanied by a numerical confidence figure. The author cautions that relying on these scores could lead to poor decision-making in applications where accuracy is critical.

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ProgrammingDEV Community ·

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