In 1996, a young graduate student called Richard Watson sat down to read a paper on evolution. The article was provocative. It tackled a long-running problem in evolutionary biology: we do not fully understand how organisms can adapt so successfully to their environments.

Creatures do not seem to be merely at the mercy of random changes, or mutations, in their genes over time. Instead, they actually seem to “improve” their ability to adapt. It seemed this ability was not explained solely by the process of natural selection, in which the best traits are passed on by the most successful organisms.

So the paper’s authors, Gunter Wagner at Yale University and Lee Altenberg at the Hawaii Institute of Geophysics and Planetology in Honolulu, decided to look for answers in a surprising place: computer science.

Watson, a computer scientist, was hooked. In the 20 years since he read that paper, he has been developing a theory based on the ideas it contained. His ideas could help explain why animals are so good at evolving: a trait called their “evolvability”. What’s more, it might even help to solve some long-running curiosities in evolutionary biology.

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