Is AI Reasoning Right for the Wrong Reasons? | Hacker News

A Hacker News thread debated whether “reasoning” in large language models is real ability or just a useful illusion.

Some commenters framed it as mostly a semantic issue, while others argued that understanding internals could improve reliability, optimization, and safety.

A key concern was that models can give correct answers for the wrong reasons, with Clever Hans cited as a classic analogy.

Several replies noted that emitted reasoning traces may not match the true mechanism behind a model’s predictions.

The discussion has implications for LLM evaluation, prompt engineering, interpretability tools, and future AI policy or rights debates.