Oxford Researchers Develop Method to Detect AI 'Hallucinations'

New technique improves reliability of generative models by identifying semantic inconsistencies.

The method distinguishes between factual uncertainty and phrasing uncertainty in AI responses.
It calculates 'semantic entropy' to measure the consistency of generated answers.
The technique outperforms previous methods in detecting AI errors across various datasets.
Although computationally intensive, it enhances AI reliability in high-stakes applications.
Experts caution that while promising, the method doesn't address all types of AI errors.