Darwinian designs

Pavel Chvykov, Ph.D.
BS cubed
Published in
2 min readJan 6, 2021
Photo by Jennifer Chen on Unsplash

What is the difference between the amazing designs of biology, and those built by humans? Well, as we’ve discussed in the last couple posts, this is perhaps more subtle than initially seems. Both are outcomes of a selection process, where poor designs are cleared from the “gene pool” as they get outcompeted by more adept, faster reproducing, or more desirable counterparts. In the case of biology, this is termed “natural selection,” where only the “fittest” survive to reproduce. But in the case of human designs, the selection is no less “natural,” and only the designs best addressing the preferences of the fickle markets survive.

Such selection mechanisms may all be seen as feedback loops: they take certain properties of a design (e.g., how fast it runs, how pretty it looks), and based on these “evaluate” whether the design is viable for its respective ecosystem. Importantly, this “evaluation” is carried out by the animal’s interaction with its environment over the course of its lifetime — and so we may think of its livelihood as a “physical computation”! In this sense the only difference between biological and human designs is what “algorithm” carries out this computation (i.e., manifests this selection feedback loop). For biology, feedback is established through the organism’s performance in the physical world, according to the laws of physics and its ecosystem. For human designs, this feedback is realized according to the laws of our social world and consumer preferences.

I find it really cool how with enough abstraction, we can put such seemingly different systems and processes on the same footing. In a sense, this is really the appeal of complexity science for me.

Alright, so does it seem reasonable that the distinction between biological and human designs can be boiled down to how the selection feedback loop is being “computed”? How could we manipulate this computation process to produce better designs (e.g., cars that can self-heal and don’t pollute)? In the next post I’ll circle back to the “growing cars” business of my last couple posts and actually think about how we might practically implement this whole thing.

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Pavel Chvykov, Ph.D.
BS cubed

Post-doc researcher at MIT, excited about complexity science, digital nomad.