Business EconomyPosted at: Sep 7 2025 11:07PM


Hallucinations persist partly because current evaluation methods set the wrong incentives: OpenAI on AI hallucination

New Delhi, Sep 7 (UNI) GPT-5 has significantly fewer hallucinations, especially when reasoning, but they still occur, said OpenAI in its research paper themed ‘Why language models hallucinate.’
‘Hallucination’ in relation to AI tools refer to the situation when an AI model produces outputs that are inaccurate, misleading, or entirely fabricated, despite often presenting them with high confidence.
Sharing insights on hallucination, the OpenAI research paper said “Hallucinations persist partly because current evaluation methods set the wrong incentives. While evaluations themselves do not directly cause hallucinations, most evaluations measure model performance in a way that encourages guessing rather than honesty about uncertainty.”
“Think about it like a multiple-choice test. If you do not know the answer but take a wild guess, you might get lucky and be right. Leaving it blank guarantees a zero. In the same way, when models are graded only on accuracy, the percentage of questions they get exactly right, they are encouraged to guess rather than say, “I don’t know.”
The research paper also noted that the older OpenAI o4-mini model performs slightly better. However, its error rate (rate of hallucination) is significantly higher.
The ‘OpenAI o4-mini’ is a compact, cost-efficient and high-throughout reasoning model from OpenAI’s ‘o-series.’ This model is specifically designed for applications requiring fast and budget-friendly AI performance including high-volume tasks.
“When averaging results across dozens of evaluations, most benchmarks pluck out the accuracy metric, but this entails a false dichotomy between right and wrong. On simplistic evals like SimpleQA, some models achieve near 100% accuracy and thereby eliminate hallucinations. However, on more challenging evaluations and in real use, accuracy is capped below 100% because there are some questions whose answers can’t be determined for a variety of reasons, such as unavailable information, limited thinking abilities of small models, or ambiguities that need to be clarified.” OpenAI said.
Pointing towards a solution, OpenAI said there is “no straightforward fix” for this problem. The research paper noted the key finding that “ Accuracy will never reach 100% because, regardless of the model size, search and reasoning capabilities, some real-world questions are inherently unanswerable.”
OpenAI, a US-based AI research and deployment company that creates and promotes artificial intelligence (AI).

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