This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Artificial intelligence can develop solutions that humans would be unlikely to discover on their own. But what happens when machines do more than solve individual problems and actually discover entirely new solution strategies?
And can such discoveries become part of human knowledge? A team from the Center for Humans and Machines at the Max Planck Institute for Human Development, together with researchers from the Toulouse School of Economics and Humboldt University of Berlin, investigated this question experimentally for the first time. The results, published in Nature Communications, show that under certain conditions humans can not only adopt strategies discovered by machines but also pass them on and preserve them across multiple generations.
The study was motivated by the observation that modern AI systems are increasingly developing strategies that surprise human experts. This phenomenon became well known through AI systems' performance in board games such as Go and chess, where they discovered unusual yet highly successful ways of playing. Until now, however, it was unclear which conditions are required for such machine discoveries to have a lasting influence on human thinking and behavior.
The researchers argue that three conditions must be met: The strategy must initially be difficult for humans to discover, it must remain learnable and its advantage must be clearly recognizable. Only then can it spread within a community and be maintained over time. "Human cultural evolution depends on knowledge being transmitted across many individuals and generations," says lead author Levin Brinkmann, a research scientist at the Center for Humans and Machines at the Max Planck Institute for Human Development.
"If machines are now discovering novel strategies, the question is whether these can also become part of the knowledge humans pass on. That is exactly what we investigated." To test their hypothesis, the researchers conducted a behavioral experiment involving 1,155 participants. Participants were asked to earn as many points as possible in specially designed reward-based tasks.
The task was structured so that the optimal strategy initially required participants to accept small early losses to achieve much larger gains later. This ran counter to a common human tendency: avoiding short-term losses whenever possible. The participants were organized into groups that learned from one another across multiple generations.
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