51 lines
1.9 KiB
Org Mode
51 lines
1.9 KiB
Org Mode
---
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title: "Reading Notes: \"The Symbol Grounding Problem\", Stevan Harnad"
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date: 2020-02-02
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---
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cite:harnad1990_symbol_groun_probl defined the /symbol grounding
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problem/, which is one of the most influential issues in natural
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language problems since the 1980s. The issue is to determine how a
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formal language system, consisting in simple symbols, can be imbued
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with any /meaning/.
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From the abstract:
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#+begin_quote
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How can the semantic interpretation of a formal symbol system can be
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made /intrinsic/ to the system, rather than just parasitic on the
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meanings in our heads? How can the meanings of the meaningless symbol
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tokens, manipulated solely on the basis of their (arbitrary) shapes,
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can be grounded in anything but other meaningless symbols?
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#+end_quote
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In this landmark paper, Harnad makes the issue explicit, in its
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context of cognitivism and competing theories of mind and
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intelligence. He then proposes an original solution based on a
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combination of symbolic and connectionist properties. The problem
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itself is still highly relevant to today's NLP advances, where the
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issue of extracting /meaning/ is still not solved.
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# cf Gary Marcus, /Rebooting AI/, and post on /The Gradient/
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* What is the symbol grounding problem?
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** Context: cognitivism, symbolism, connectionism
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/Cognitivism/ is the general framework in which all experimental
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psychology takes place. It replaced old-fashioned /behaviorism/,
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replacing it by an empirical science allowing to question the inner
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workings of brains and minds.
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Behaviorism restrained scientific inquiries to external behavior,
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explicitly forbidding to make theories about what goes on inside the
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mind. Cognitivism allowed the scientist to make hypotheses about
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unobservable phenomenons, provided they made predictions testable in
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an experimental setting.
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"Meaning" is one such unobservable phenomenon.
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** Exposing the issue: thought experiments
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* What the human mind does, and what AIs could do
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* References
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