The University of Oxford researchers have come up with a new method to detect and prevent artificial intelligence “hallucinations” that are false answers given by AI. Their study, published in the journal Nature, introduced a statistical model that can identify when a question posed to a large language model (LLM) running an AI chatbot is likely to produce an incorrect answer.
As AI technology becomes more advanced and capable of conversing with users, the issue of “hallucinations” has become increasingly concerning. This is especially true in fields such as medicine and law, where accurate information is critical.
The researchers found a way to distinguish between an AI’s confidence in its answer and when it was providing inaccurate information. Dr. Sebastian Farquhar, one of the study authors, explained that previous approaches struggled to differentiate between a lack of knowledge and a failure to communicate that knowledge effectively.
The team’s new method aims to address this limitation and improve the accuracy of AI responses. While the new method shows promise in identifying “hallucinations,” Dr. Farquhar emphasized that further research is needed to refine AI models and minimize errors they may produce.
The ongoing work is crucial for ensuring that AI technology can be used effectively and responsibly across various applications. As experts continue to call for measures to curb these misleading responses, this study marks an important step towards improving the reliability and accuracy of artificial intelligence systems.
