Whenever we can, we like to explain things in terms of simple cause and effect. We explained the case of Professor Challenger by assuming that my wish to Work came first, then Work exploited Anger's aptitude for fighting Sleep. But in real life the causal relations between feelings and thoughts are rarely so simple. My desire to work and my annoyance with Challenger were probably so intermingled, all along, that it is inappropriate to ask which came first, Anger or Work. Most likely, both agencies exploited one another simultaneously, thus combining both into a single fiendish synthesis that accomplished two goals at once; Work thus got to do its work — and, thereby, injured Challenger! (In an academic rivalry, a technical accomplishment can hurt more than a fist.) Two goals can support each other.
A causes B John wanted to go home because he felt tired of work. B causes A John felt tired of work because he wanted to go home.
There need be no first cause since John could start out with both distaste for work and inclination to go home. Then a loop of circular causality ensues, in which each goal gains support from the other until their combined urge becomes irresistible. We're always enmeshed in causal loops. Suppose you had borrowed past your means and later had to borrow more in order to pay the interest on your loan. If you were asked what the difficulty was, it would not be enough to say simply, Because I have to pay the interest, or to say only, Because I have to pay the principal. Neither alone is the actual cause, and you'd have to explain that you're caught in a loop.
We often speak of straightening things out when we're involved in situations that seem too complicated. It seems to me that this metaphor reflects how hard it is to find one's way through a maze that has complicated loops in it. In such a situation, we always try to find a path through it by seeking causal explanations that go in only one direction. There's a good reason for doing this.
There are countless different types of networks that contain loops. But all networks that contain no loops are basically the
same: each has the form of a simple chain.
Because of this, we can apply the very same types of reasoning to everything we can represent in terms of chains of causes and effects. Whenever we accomplish that, we can proceed from start to end without any need for a novel thought; that's what we mean by straightening out. But frequently, to construct such a path, we have to ignore important interactions and dependencies that run in other directions.