The Wrights invented the airplane using an empirical, trial-and-error approach. They had to learn from experience. They couldn’t have solved the control problem without actually building and testing a plane. There was no theory sufficient to guide them, and what theory did exist was often wrong. (In fact, the Wrights had to throw out the published tables of aerodynamic data, and make their own measurements, for which they designed and built their own wind tunnel.)
This part in particular is where I think there’s a whole bunch of useful lessons for alignment to draw from the Wright brothers.
First things first: “They couldn’t have solved the control problem without actually building and testing a plane” is… kinda technically true, but misleading. What makes the Wright brothers such an interesting case study is that they had to solve the large majority of the problem (i.e. “get the large majority of the bits of optimization/information”) without building an airplane, precisely because it was very dangerous to test a plane without the ability to control it. Furthermore, they had to do it without reliable theory. And the Wright brothers are an excellent real-world case study in creating a successful design mostly without relying on either robust theory or trial-and-error on the airplane itself.
Instead of just iterating on an airplane, the Wright brothers relied on all sorts of models. They built kites. They studied birds. They built a wind tunnel. They tested pieces in isolation—e.g. collecting their own aerodynamic data. All that allowed them to figure out how to control an airplane, while needing relatively-few dangerous attempts to directly control the airplane. That’s where there’s lots of potentially-useful analogies to mine for AI. What would be the equivalent of a wind tunnel, for AI control? Or the equivalent of a kite? How did the Wright brothers get their bits of information other than direct tests of airplanes, and what would analogies of those methods look like?
This part in particular is where I think there’s a whole bunch of useful lessons for alignment to draw from the Wright brothers.
First things first: “They couldn’t have solved the control problem without actually building and testing a plane” is… kinda technically true, but misleading. What makes the Wright brothers such an interesting case study is that they had to solve the large majority of the problem (i.e. “get the large majority of the bits of optimization/information”) without building an airplane, precisely because it was very dangerous to test a plane without the ability to control it. Furthermore, they had to do it without reliable theory. And the Wright brothers are an excellent real-world case study in creating a successful design mostly without relying on either robust theory or trial-and-error on the airplane itself.
Instead of just iterating on an airplane, the Wright brothers relied on all sorts of models. They built kites. They studied birds. They built a wind tunnel. They tested pieces in isolation—e.g. collecting their own aerodynamic data. All that allowed them to figure out how to control an airplane, while needing relatively-few dangerous attempts to directly control the airplane. That’s where there’s lots of potentially-useful analogies to mine for AI. What would be the equivalent of a wind tunnel, for AI control? Or the equivalent of a kite? How did the Wright brothers get their bits of information other than direct tests of airplanes, and what would analogies of those methods look like?