It's very clear that in order to make progress in understanding some of the most challenging and important things about intelligence, studying the best example we have of an intelligent system is a way to do that. Often, people who argue against that make the analogy that if we were trying to understand how to build jet airplanes, then starting with birds is not necessarily a good way to do that.                                 

That analogy is pretty telling. The thing that's critical to both making jet airplanes work and making birds fly is the structure of the underlying problem that they're solving. That problem is keeping an object airborne, and the structure of that problem is constrained by aerodynamics. By studying how birds fly and the structure of their wings, you can learn something important about aerodynamics. And what you learn about aerodynamics is equally relevant to then being able to make jet engines.                                 

The kind of work that I do is focused on trying to identify the equivalent of aerodynamics for cognition. What are the real abstract mathematical principles that constrain intelligence? What can we learn about those principles by studying human beings? 

TOM GRIFFITHS is a professor of psychology and cognitive science and director of the Computational Cognitive Science Lab and the Institute of Cognitive and Brain Sciences at the University of California, Berkeley. He is co-author (with Brian Christian) of Algorithms to Live By. Tom Griffiths's Edge Bio page [2]