How evolution creates problem-solving machines | Michael Levin

Evolution doesn’t fix things — it reinvents them. Michael Levin, a biologist, explains.

This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @TempletonFoundation.

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Esteemed biologist Michael Levin explores a captivating biological perspective of evolution — one that’s hard for engineers to come to terms with. In their work, making random changes to a system usually makes things worse, not better.

But evolution, on the other hand, doesn't just produce specific solutions to specific challenges; instead, it creates what Levin calls "problem-solving machines." These machines are made up of hierarchical biological hardware with incredible adaptability, capable of tackling various challenges without assuming specific environmental conditions.

Contrary to commonly held ideas about evolution, it doesn't just search for the best possible physical characteristics in organisms. It also uses signals and behaviors to shape how organisms function, so when things change or get damaged, the different parts of an organism can continue to function. From metabolic to physiological dilemmas, Levin highlights evolution’s remarkable ability to adapt.

Read the full video transcript

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About Michael Levin:

Michael Levin is a developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor and serves as director of the Allen Discovery Center at Tufts and the Tufts Center for Regenerative and Developmental Biology.

Prior to college, Michael Levin worked as a software engineer and independent contractor in the field of scientific computing. He attended Tufts University, interested in artificial intelligence and unconventional computation. To explore the algorithms by which the biological world implemented complex adaptive behavior, he got dual B.S. degrees, in CS and in Biology and then received a PhD from Harvard University.

He led an independent laboratory from 2000 to 2007 at Forsyth Institute, Harvard. Now, his lab at Tufts studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems.

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