JB: How do you define the word "robot."

BROOKS: I mean a physical robot made of metal, not a soft-bot. Most recently I've been working on Cog, a humanoid robot which has human size, form, and sits and acts in the world. There are a few curious things that have come out of that which I didn't quite expect. One is that the system with very little content inside it, seems eerily human to people. We get its vision system running, with its eyes and its head moving, and it hears a sound and it saccades to that, and then the head moves to follow the eyes to get them back into roughly the center of their range of motion. When it does that, people feel it has a human presence. Even to the graduate students who designed the thing, and know that there's nothing in there, it feels eerily human.

The second thing is that people are starting to interact with it in a human like way. They will lead it on, so it will do something interesting in the world. People come up and play with it. And the robot is now doing things that we haven't programmed it to do; not that it's really doing them. The human is taking advantage of those little pieces of dynamics and leading it through a series of sub-interactions, so that to a naive observer it looks like the robot is doing a lot of stuff that it's not doing. The easiest example of this is turn-taking. One of my graduate students, Cynthia Ferrell, who had been the major designer of the robot, had been doing something with the robot so we could videotape how the arms interacted in physical space. When we looked at the videotape, Cynthia and it were taking turns playing with an whiteboard eraser, picking it up, putting it down, the two of them going back and forth. But we didn't put turn-taking into the robot, it was Cynthia pumping the available dynamics, much like a human mother leads a child through a series of things. The child is never as good as the human mother thinks it is. The mother keeps doing things with the kid, that the kid isn't quite capable of. She's using whatever little pieces of dynamics are there, getting them into this more complex behavior, and then the kid learns from that experience, and learns those behaviors. We found that humans can't help themselves; that's what they do with these systems such as kids and robots. The adults unconsciously put pieces of the kid's or robot's dynamics together without thinking. That was a surprise to us - that we didn't have to have a trained teacher for the robot. Humans just do that. So it seems to me that what makes us human, besides our genetic makeup, is this cultural transferral that keeps making us human, again and again, generation to generation.

Of course it's involved with genetics somehow, but it's missing from the great apes. Naturally raised chimpanzees are very different from chimpanzees that have been raised in human households. My hypothesis here is that the humans engage in this activity, and drag the chimpanzee up beyond the fixed point solution in chimpanzee space of chimpanzee to chimpanzee transfer of culture. They transfer a bit of human culture into that chimpanzee and pull him/her along to a slightly different level. The chimpanzees almost have the stuff there, but they don't quite have enough. But they have enough that humans can pull them along a bit further. And humans have enough of this stuff that now a self-satisfying set of equations gets transferred from generation to generation. Perhaps with better nurturing humans could be dragged a little further too.

JB: Let's talk about your background.

BROOKS: I have always been fascinated by building physical things and spent my childhood doing that. When I first came to MIT as a post-doc I got involved in what I call classical robotics, applying artificial intelligence to automating manufacturing. My earlier Ph.D. thesis was on getting computers to see 3-dimensional objects. At MIT I started to worry about how to move a robot arm around without collisions, and you had to have a model, you had to know where everything was. It built up more and more mathematical structures where the computations were just getting way out of hand - tons of symbolic algebra, in real time, to try and make some decision about moving the fingers around. And at some point it got to the point that I decided that it just couldn't be right. We had a very complex mathematical approach, but that couldn't be what was going on with animals moving their limbs about. Look at an insect, it can fly around and navigate with just a hundred thousand neurons. It can't be doing this very complex symbolic mathematical computations. There must be something different going on.

I was married at the time to a woman from Thailand, the mother of my three kids, and I got stuck in a house on stilts in a river in southern Thailand for a month, not allowed out of the house because it was supposedly dangerous outside, and the relatives couldn't speak a word of English. I sat in this house on stilts for a month, with no one talking to me because they were all gossiping in Thai the whole time. I had nothing to do but think and I realized that I had to invert the whole thing. Instead of having top-down decomposition into pieces that had sensing going into a world model, then the planner looks at that world model and builds a plan, then a task execution module takes steps of the plan one by one and almost blindly executes them, etc., what must be happening in biological systems is that sensing is connected to action very quickly. The connectivity diameter of the brain is only five or six neurons, if you view it as a graph, so there must be all these quick connections of sensing to action, and evolution must have built on having those early ones there doing something very simple, then evolution added more stuff. It didn't take it all apart at each step and rewire it, because you wouldn't be able to get from a viable creature to a viable creature at each generation. You can only do it by accretion, and modulation of existing neural circuitry. This idea came out of thinking of having sensors and actuators and having very quick connections between them, but lots of them. As a very approximate hand waving model of evolution, things get built up and accreted over time, and maybe new accretions interfere with the lower levels. That's how I came to this approach of using very low small amounts of computation in the systems that I build to operate in the real world.