I came across two quotations. Here they are:
Nothing is particularly hard if you divide it into small jobs.
- Henry Ford
If the brain were so simple we could understand it, we would be so simple we couldn’t.
- Lyall Watson
I noticed I had written both of these on the same sheet of paper. Individually I agree with each of them. In particular, I like the Lyall Watson quote, which is both amusing and well thought out. In a few words it dismisses the hopes and dreams of psychologists, neuroscientists, artificial intelligence researchers, and projects that strive toward true self-replicating machines. At least, it does all that if you choose to take it that far. But it also preserves the magic and complexity of the human mind. To my ear, it both resonates with and contradicts Henry Ford’s quote.
I admit I’m taking two things completely out of context. Ford was talking about manufacturing, and Watson was talking about the brain. But let’s give ourselves license here. We’ll take these quotes out of the rich contexts from which they were generated, and set them together in an empty room.
Which, if either, is true? Or can they agree on some level?
Complex decisions have at their root a mass of very simple ones. I’ll hold that hypothesis out for criticism, but as far as I understand the mind it must be true. We don’t have the capacity to hold all of world politics in out minds at once, for example. It’s just too big a subject. Perhaps that’s why we get annoyed when people spout sweeping generalities rather than using detailed arguments. “How did you come to that conclusion,” we ask, or “what makes you say that?” These are the questions we ask in response to a general statement, particularly one we disagree with, and they imply that whole world-views hinge on the smaller details. We question unpopular decisions in the same way.
We act based on our understanding of how the action will affect a series of surrounding events and circumstances. Sometimes we vacillate in the decision-making process because it is difficult to find an ideal solution. “If I tell Jenny about Bob and Jean, I’ll be betraying Bob; but if Jenny finds out later that I know, she’ll never speak to me again.” We are alternately pulled toward two different solutions, based on which consequence we are evaluating in a given moment. In these situations, we often rely on tie-breakers from the realm of morality or experience. “Honesty is always the best policy; I’ll just be honest and Bob will have to understand.” Or: “Putting my nose in other people’s business has only ever caused trouble. I can’t be involved in their problems; I won’t say anything.” One simple factor added into the equation gives us the ability to break the decision loop and return to action.
Maybe we can’t fully understand something as complex as the human brain. I’m not positive we can understand something as complex as a modern automobile or a computer chip, at least not all at once. We can understand their parts. We can even understand fairly intricate parts at one time, but to visualize the whole we are forced to let the parts fade into the background, become blurred, and at best to remember some detail about how they can interact with the parts around them. Often, we switch to a serial mode of thinking. We see the things as a series of events because we can not focus our attention on the entire thing without losing something. We come up with something like: Combustion drives the piston, which turns a shaft, where the force is converted via belts and gears to an axle, which rotates a tire, which translates torque to linear motion along the road. Such an understanding is a simplified construct. The elements of time and synchronicity are lost in the translation, so we have a simple series rather than an orchestra of simultaneous events.
None of that means we can’t make a car, however. I question whether anyone can fully comprehend a car in a single thought, because of the nature of comprehension and of thoughts. But we can still understand a car in the way that we’re good at understanding things, in parts. Computers are similarly gifted, perhaps as a reflection of their makers. So can we make a computer that thinks, and that passes the Turing test, and that passes whatever tests we come up with after that when our pride is injured by the idea that machines could some day rival us as thinkers? Well, nothing is particularly difficult if you divide it into small jobs.
