Symbol grounding

According to a widely held theory of cognition called "computationalism," cognition (i.e., thinking) is a form of computation. But computation can be reduced to formal symbol manipulation: symbols are manipulated according to rules that are based on the symbols' shapes, not their meanings.

The symbol grounding problem is related to the problem of how words (symbols) get their meanings, and hence to the problem of what meaning itself really is. The problem of meaning is in turn related to the problem of consciousness, or how it is that are meaningful.

How are those symbols (e.g., the words in our heads) connected to the things they refer to? It cannot be through the mediation of an external interpreter's head, because that would lead to an infinite regress, just as looking up the meanings of words in a (unilingual) dictionary of a language that one does not understand would lead to an infinite regress.

The symbols in an autonomous hybrid symbolic+sensorimotor system—a Turing-scale robot consisting of both a symbol system and a sensorimotor system that reliably connects its internal symbols to the external objects they refer to, so it can interact with them Turing-indistinguishably from the way a person does—would be grounded. But whether its symbols would have meaning rather than just grounding is something that even the robotic Turing test—hence cognitive science itself—cannot determine, or explain.

A symbol is any object that is part of a symbol system, a set of symbols and syntactic rules for manipulating them on the basis of their shapes. The symbols are systematically interpretable as having meanings and referents, but their shape is arbitrary in relation to their meanings and the shape of their referents. Only in our minds do they take on meaning (Harnad 1994).

A numeral is as good an example as any: Numerals (e.g., "1," "2," "3,") are part of a symbol system (arithmetic) consisting of shape-based rules for combining the symbols into ruleful strings. "2" means what we mean by "two", but its shape in no way resembles, nor is it connected to, "two-ness." Yet the symbol system is systematically interpretable as making true statements about numbers (e.g. "1 + 1 = 2").

This is not to depreciate the property of systematic interpretability: We select and design formal symbol systems (algorithms) precisely because we want to know and use their systematic properties; the systematic correspondence between scratches on paper and quantities in the universe is a remarkable and extremely powerful property. But it is not the same thing as meaning, which is a property of certain things going on in our heads.

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