No computer has ever been designed that is ever aware of what it's doing; but most of the time, we aren't either.

In science, one learns the most by studying what seems to be the least.

Societies need rules that make no sense for individuals. For example, it makes no difference whether a single car drives on the left or on the right. But it makes all the difference when there are many cars!

The secret of what anything means to us depends on how we've connected it to all the other things we know. That's why it's almost always wrong to seek the "real meaning" of anything. A thing with just one meaning has scarcely any meaning at all.

There are three basic approaches to AI: Case-based, rule-based, and connectionist reasoning.

Anyone could learn Lisp in one day, except that if they already knew Fortran, it would take three days.

Each part of the mind sees only a little of what happens in some others, and that little is swiftly refined, reformulated and "represented." We like to believe that these fragments have meanings in themselves - apart from the great webs of structure from which they emerge - and indeed this illusion is valuable to us qua thinkers - but not to us as psychologists - because it leads us to think that expressible knowledge is the first thing to study.