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Offloading Cognition onto the Web

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2 Author(s)
Carr, L. ; EPSRC Web Sci. Doctoral Training Center, Univ. of Southampton, Southampton, UK ; Harnad, S.

Neuropsychology and neuroimaging studies have confirmed what we all knew already from introspection: some of our know-how is conscious, but most of it is not. Learning, skill, knowledge, and memory all come in two forms: explicit, in which we are aware of-and can hence describe in words-how we are able to do something, and implicit, in which we are unaware of how we are doing something. Most cognitive science is devoted to discovering the implicit mechanisms underlying our cognitive competence and making them explicit. Conscious introspection does not reveal what they are. The explanatory goal of cognitive science is to reverse-engineer what it takes to pass the Turing Test. That is, once we can successfully design a system that is capable of doing whatever any normal person can do, indistinguishably from any person, to any person, then we have a candidate explanation of how the human brain does it. In modeling human cognitive capacity, we must consider what to build into our candidate mechanism and what to offload onto external cognitive technology, such as Google Web searches. Word meanings can be internally represented in two ways: sensorimotor and verbal. In this work we tested conjunctive and disjunctive Google searches for target terms that have their own Wikipedia entries, using either the target terms themselves or the three words that had the highest co occurrence frequency with the target words in WordNet. We found that the highly co-occurring words were surprisingly ineffective in retrieving the target word and there was no significant correlation with age of acquisition or concreteness. This raises some questions about the similarity between human associative memory and Google-based associative search.

Published in:

Intelligent Systems, IEEE  (Volume:26 ,  Issue: 1 )