When Sam Rodriques was a neurobiology graduate student, he was struck by a fundamental limitation of science. Even if researchers had already produced all the information needed to understand a human cell or a brain, "I’m not sure we would know it", he says, "because no human has the ability to understand or read all the literature and get a comprehensive view."
Five years later, Rodriques says he is closer to solving that problem using artificial intelligence (AI). In September, he and his team at the US start-up FutureHouse announced that an AI-based system they had built could, within minutes, produce syntheses of scientific knowledge that were more accurate than Wikipedia pages.
Some of the newer AI-powered science search engines can already help people to produce narrative literature reviews – a written tour of studies – by finding, sorting and summarizing publications. But they can’t yet produce a high-quality review by themselves. Researchers fear that AI tools could lead to more sloppy, inaccurate or misleading reviews polluting the literature. "The worry is that all the decades of research on how to do good evidence synthesis starts to be undermined," says James Thomas, who studies evidence synthesis at University College London.
