A new study explores how artificial intelligence can not only better predict new scientific discoveries but can also usefully expand them. The researchers, who published their work in Nature Human Behaviour, built models that could predict human inferences and the scientists who will make them.

The authors also built models that avoided human inference to generate scientifically promising “alien” hypotheses that would not likely be considered until the distant future, if at all. They argue that the two demonstrations—the first allowing for the acceleration of human discovery, while the second identifies and passes over its blind spots—means that a human-aware AI would allow for movement beyond the contemporary scientific frontier.

“If you build in awareness to what people are doing, you can improve prediction and leapfrog them to accelerate science,” says co-author James A. Evans, the Max Palevsky Professor in the Department of Sociology and director of the Knowledge Lab. “But you can also figure out what people can’t currently do, or won’t be able to do for decades or more into the future. You can augment them by providing them that kind of complementary intelligence.”