In a move that Oz might be tempted to call the “reverse Scarecrow,” Fuster takes care to give the brain a body. The prefrontal and premotor regions of the action-planning brain are part of what he calls the “perception-action cycle,” which is “the circular flow of information from the environment to sensory structures, to motor structures, back again to the environment, to sensory structures, and so on, during the processing of goal-directed behavior.” Pushing this point further, Trimmer, whose team specializes in designing soft-bodied robots to test ideas about how caterpillars move and modulate their behavior, said at our meeting, “The body is doing the computational work of interacting with the environment.” But what is the nature of the “computational work” being done?
The body of Tadro3 “computes” everything that the microcontroller running the Interactive C program (see Figure 5.1) doesn’t: all the really difficult physics. By virtue of being in the real world, interacting with real water, Tadro3 automatically solves the intensely complex dynamics of a flexible propeller transducing an oscillating uniaxial bending couple into a propagating bending moment that flexes the tail, which, in turn, is also loaded hydromechanically in a time-varying manner as its relative motion in the water changes. In response to the tail’s coupled internal and external force computations, the body, to which the tail is attached, undergoes the yaw wobbles—recoil and turning maneuvers—that we talked about in Chapter 4. Coupled computations that allow elastic and fluid forces to interact have been elegantly simulated by Eric Tytell, of Tufts University, and his colleagues at the University of Maryland using the “immersed boundary method” for a steadily swimming lamprey.[70]
But wait. Order before midnight and your Tadro3 comes with free motor and sensory computations. Tadro’s rotational and translational motion has angular and linear components of both velocity and acceleration that interact to produce the overall motion of the Tadro according to Newton’s laws of motion. As the Tadro3 wobbles and winds its way through the water world, it presents its attached photoresistor, acting as an eyespot, to a gradient of light. As the light intensity at any place on the water’s surface changes as the Tadro moves, the photoresistor continuously recomputes light intensity as a change in voltage by virtue of being part of a little electric circuit that works via Ohm’s law.
FIGURE 5.2. The neurocentric view: thinking is planning. Planning is something we do “in our heads,” in our brain, with input from our senses, to create actions. This view is consistent with our subjective experience, coupled with information from neuroscientific studies of brain activity correlated with what we are thinking. The neurocentric view dominates in nearly every field concerned with human thought, language, and behavior.
However impressive Tadro3 might be as a student of physics, you may be objecting to the notion that Tadro3 is “computing” or “solving” anything with its body. “Computing” has a formal definition that goes back to Turing. We talk about “Turing-computable algorithms” as those procedures that can be solved, ultimately, with the simple deterministic rules a digital machine puts into play. Meanwhile, “solving” has a more mathematical flavor because we talk about solving a set of equations, like the Newtonian equations that govern the motion of an object. In both formal systems symbols are being manipulated according to a set of rules. Not so with Tadro. With the exception of what’s going on in its microcontroller (see Figure 5.1), Tadro manipulates only its body as it interacts with the rule-based physical world.
Just because we can represent physical rules—by computing physical interactions within and among physical entities—doesn’t mean that the world is hosting physical interactions in the same way. Borrowing a page from Searle now, we’d say that the computer is not having the actual physical interactions but is, instead, simulating them via symbol manipulation.
By saying that the body does the “computational work,” what Trimmer means is that the ongoing body-environment interaction, by virtue of its being an actual physical phenomenon, doesn’t necessarily need to be mediated through a nervous system. From the neuro centric perspective (see Figure 5.2), the brain doesn’t need to control how the tail interacts with the water because brainless physics governs that interaction. The brain doesn’t need to solve Newtonian equations of motion. The physics takes care of itself according to its own rules. Without a neural imperative to “control behavior,” what, therefore, does a nervous system need to do?
It’s not that brains are unimportant. Brains do something—when they are present. The paradox is that some behaving animals and robots don’t have any structure or program that we would say is a “brain.” But before we talk about brainless behavior, we need to delve deeper into what we think brains are and what we think they do.
A huge body of physical evidence shows that the embodied-brain in a variety of animals is involved in some of the functional events that create the behavior that we recognize as an agent interacting with its environment. Are we happy now? Isn’t this what we’ve been intuiting all along about the importance of brains? No, no. Academics are never happy because the world is never that simple. And what brains do is not simple.
Let’s go back to the contrasting paradigms of Turing and Searle. Turing gets the blame (or credit) for this whole “brain is a computer” problem, having argued that if every kind of thought that a human might have was an algorithm—where an algorithm is a mathematically expressible series of instructions for completing a specified task—then a computer was working IN THE SAME WAY as a brain, manipulating symbols in a deterministic manner.[71]
In case you missed my subtle use of capitalization, the key phrase here is “in the same way.” This gets us to the heart of the matter: if two different types of physical contraption are operating “in the same way,” does that mean that they are the same thing? For example, if a coal-fired locomotive and a diesel automobile both operate by expanding gases in a chamber and using that pressure-volume work to push a cylinder, are they the same thing? On the level of pressure-volume work transduced to linear displacement, yes. On another, no. The locomotive heats a boiler filled with water that is turned into steam; the automobile compresses the vaporized diesel fuel, which then explodes. My ten-year-old daughter would also point out that locomotives run on tracks, whereas cars run on the road; locomotives pull huge numbers of cars behind them; automobiles are smaller and have rubber tires.
Several of you reading this are snickering, I can tell, because you love trains and have thought of something wicked to disturb our little thought experiment: turn the coal-fired locomotive into a diesel-powered one, just like the automobile. Now locomotive and automobile use power plants that operate in an identical fashion. Size still a problem? You may have ridden on small-scale trains that are about the size of automobiles (or buses). Tires and tracks? You see the game: in the face of objections to sameness, change the objecting feature to be the same, ad infinitum.
70
E. Tytell, C-Y. Hsui, T. L. Williams, A. V. Cohen, and L. Fauci, “Interactions Between Internal Forces, Body Stiffness and Fluid Environment in a Neuromechanical Model of Lamprey Swimming,”
71
Alan Mathison Turing, “Computing Machinery and Intelligence,”