On Nov. 27, 2024, a study led by the University College London reported that large language models, a type of AI that analyses text, can predict the results of proposed neuroscience studies more accurately than human experts, finds a new study led by UCL researchers.

The findings, published in Nature Human Behaviour, demonstrated that large language models (LLMs) trained on vast datasets of text can distil patterns from scientific literature, enabling them to forecast scientific outcomes with superhuman accuracy. All of the LLMs outperformed the neuroscientists, with the LLMs averaging 81% accuracy and the humans averaging 63% accuracy. Even when the study team restricted the human responses to only those with the highest degree of expertise for a given domain of neuroscience (based on self-reported expertise), the accuracy of the neuroscientists still fell short of the LLMs, at 66%.

The researchers say this highlights their potential as powerful tools for accelerating research, going far beyond just knowledge retrieval.