In early October, as the Nobel Foundation announced the recipients of this year’s Nobel prizes, a group of researchers, including a previous laureate, met in Stockholm to discuss how artificial intelligence (AI) might have an increasingly creative role in the scientific process. The workshop, led in part by Hiroaki Kitano, a biologist and chief executive of Sony AI in Tokyo, considered creating prizes for AIs and AI–human collaborations that produce world-class science. Two years earlier, Kitano proposed the Nobel Turing Challenge1: the creation of highly autonomous systems (‘AI scientists’) with the potential to make Nobel-worthy discoveries by 2050.
It’s easy to imagine that AI could perform some of the necessary steps in scientific discovery. Researchers already use it to search the literature, automate data collection, run statistical analyses and even draft parts of papers. Generating hypotheses — a task that typically requires a creative spark to ask interesting and important questions — poses a more complex challenge. For Sendhil Mullainathan, an economist at the University of Chicago Booth School of Business in Illinois, “it’s probably been the single most exhilarating kind of research I’ve ever done in my life”
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