What does Classical AI mean?

Let’s start by describing what classical artificial intelligence is. Feel free to add/comment on whatever is missing/wrong. We can build up a complete picture as we go.

This type of AI is dedicated to the position that the appropriate level to model intelligence/cognition is at the level of the symbol. In fact, in the version that Searle calls 'Strong AI', anything that manipulates symbols in accordance with appropriate formal rules gives rise to a mind and anything that is a mind manipulates symbols in such a fashion. This Physical Symbol System Hypothesis implies that we (our brains) are digital computers. Now the symbol is defined as having both a syntax and a semantics. The syntax comes from defining the way a particular symbol is processed and interacts with other symbols (its rules) and the semantics is derived from the content that the symbol contains (what 'thing' the symbol stands for in the world not how the symbol's content is related to. Contrast with Propositional Attitudes in LOT). It should be noted that the symbol itself is not a physical thing, but tokens of symbol-types can be realised physically (in your brain, say). In this way, the conjunction of syntax and semantics plus physical tokening can allow for mental content to have causation.

If I’m on the right track, I’d say most classicists are functionalists on some level. Anyway, the symbolic level AI has problems. As Mitch has highlighted in lectures, the way we think is not like this. We can handle inconsistent, incomplete information. But the real problem is described by Searle: syntax alone is insufficient for semantics. A digital (symbolic) computer can be defined fully by reference to its rules of symbol-manipulation. No amount of computation can account for semantics; no amount of atomic symbol shuffling produces meaning. Is he right? I feel he’s missed the definition of a symbol being something ‘atomic’ that follows rules and represents something.