I published this in The Valve in March of 2010. It's a guide on how to get on board with the computational thinking that's the driver in the so-called "cognitive revolution" — which, BTW, has peaked and is now deep into routinization. Computational thinking is a style of thought, a way of looking at the world. Alas, the most familiar example of computation, arithmetic, is not a very good way to get a feel for the style, not as you need it to investigate literature, the arts, or even the human mind. This post is a brief guide to THAT style.
Note that the first book I recommend is a comic about comics. Forget about MLA-authorized easings into literary cognitivism and similar things and forget about Turner and Lakoff, More than Cool Reason. Move them down on your list. Put McCloud first. Why? Because cognitivism is in fact about building things, about how the mind builds perceptual and conceptual structures. McCloud is about how comics are built. And, in one way or another, the other books give you a sense of construction as well. The Braitenberg constructs a mind, mechanism by mechanism. There's NO sense of mechanism in Turner and Lakoff. See also Cognitivism and the Critic 2: Symbol Processing.
It has long been obvious to me that the cognitive sciences are what happened when the computation and the computer hit the behavioral sciences as a source of models and metaphors. And that is what is missing from almost all of the work I’ve seen in cognitive approaches to literature. In this post I list and annotate four modest books that can help restore the sense of computation, and the constructive, that’s otherwise absent. I list them in order of suggested reading, starting with a comic book about comic books. After that we have a bonus section, a parable about computation based on passages from Simon about a drunken ant walking on the beach.
(1) Scott McCloud (1993). Understanding Comics. New York: HarperPerennial.
In some odd, but wonderful, ways this may be the best single introduction to the cognitive study of literature. It's not an academic book; there's no scholarly apparatus. But it yields a superb sense of what it is like to think about story-telling from a cognitive point of view. It takes the form of a comic book, words and images in panels cover every page - McCloud is a cartoonist. The pictorial form is what makes it so effective. So, McCloud has the reader thinking about visual objects and how they're constructed and how those constructions are organized into stories. It conveys a sense of design, engineering, and construction which is very important and which is missing in much of the current literary cognition literature. It gives the reader a whiff of mechanism without the pain involved in understanding the computational models of the cognitive sciences.
(2) Valentine Braitenberg (1999). Vehicles: Experiments in Synthetic Psychology. Cambridge, MA: MIT Press.
This is a cumulative series of thought experiments, 14 of them in the first 83 pages. Braitenberg asks us to imagine a simple (artificial) creature in a simple environment. Here’s how he begins to describe the first one: “Vehicle 1 is equipped with one sensor and one motor. The connection is a very simple one. The more there is of the quality to which the sensor is tuned, the faster the motor goes” (p. 3). He then works out the consequences of this very simple creature, how it moves about. In the second chapter he gives the vehicle two sensors and two motors and from that constructs primitive fear and aggression. And so it goes for the rest of these 14 chapters. In each chapter he adds a little bit to the vehicle from the previous chapter and explores the behavior consequences, e.g.: love (vehicle 3), concepts (#7), getting ideas (#10), egotism and optimism (#14). The last 50 pages contain biological notes on the vehicles, thus relating to the real nervous systems of real animals. Like the McCloud, it conveys a sense of design, engineering, and construction that is essential to the cognitive science.
(3) Herbert A Simon (1981). The Sciences of the Artificial, Second Edition. Cambridge, MA: MIT Press.
Trained in political science, Simon became one of the founding fathers of artificial intelligence, computing, and cognitive science during the 1950s and 60s. This is a relatively informal collection of essays that has been widely, and justly, influential. From the preface (xi): “Engineering, medicine, business, architecture, and painting are concerned, not with how things are but with how they might be—in short, with design. . . . These essays then attempt to explain how a science of the artificial is possible and to illustrate its nature. I have taken as my main examples the fields of economics (chapter 2), the psychology of cognition (chapters 3 and 4), and planning and engineering design (chapters 5 and 6).” Chapter 7 is entitled “The Architecture of Complexity” (originally published in 1962) and takes up the problem of biological evolution. The bonus section of this post is based on a thought experiment or parable from chapter 3, “The Psychology of Thinking: Embedding Artifice in Nature.”
(4) John von Neumann (1958). The Computer and the Brain. New Haven: Yale University Press.
Von Neumann was an mathematician who made contributions in many fields. But he is best known for his work in computing. This slender volume (82 pages) is the last project he worked on and is incomplete. Brain cancer took him before he could finish. It is about two ways a computing process can be embodied in physical matter, the analog and the digital, and addresses, among other things, the limitations these modes impose on the process. Though the book contains no math, it is quite abstract, its details at some remove from all the complex details about existing computers (then and now) or the messy wetware of the brain. That is to say, it is about the essential. Forget about the fact that computers are now quite different from those von Neumann knew, and forget about the fact that most of what we know about the brain was discovered since von Neumann’s death. In this book first class mind grappls with deep questions in simple, if abstract, terms. Reading it is a good work out.
Bonus: Simon’s Ant and Slocum’s Pilot
Think of this as a parable about computation, about how computational requirements depend on the problem to be solved. Stated that way, it is an obvious truism. But Simon’s thought experiment invites you to consider this truism where the “problem to be solved” is an environment external to the computer – it is thus reminiscent of Braitenberg’s primitive vehicles.