AMSLER@SRI-AI.ARPA (06/25/84)
From: Robert Amsler <AMSLER@SRI-AI.ARPA> If one changed the content of a Spelling corrector to be a list of predicates containing `facts' rather than sequences of letters, and then one used such a program against the output of a parser which reduced incoming text to similarly structured predicates, and the `fact checker' then emitted confirmations or `corrections' of the facts in the parsed text (e.g. South-Of San-Francisco San Jose; Capital-of USSR Moscow; etc.) would this be a knowledge-based system? What has changed from sequences of letters being acceptable `truths' to the mechanical use of predicates? I fail to see how this is very different from having a spelling corrector look over a string of letters and note that MAN and DOG are correct truths whereas DOA (= Capital-of USSR San-Francisco) and MNA = (South-Of San-Jose San-Francisco) are actually `misspellings' of DOG and MAN. It might well be one doesn't want to call a system that uses this strategy to proofcheck student's essays about geography an AI program, but it sure would be hard to tell from its performance whether it was an AI program or a non-AI program `pretending' to be an AI program.
MJackson.Wbst@XEROX.ARPA (06/25/84)
"It might well be one doesn't want to call a system that uses this
strategy to proofcheck student's essays about geography an AI program,
but it sure would be hard to tell from its performance whether it
was an AI program or a non-AI program `pretending' to be an AI program."
-- Robert Amsler <AMSLER@SRI-AI>
If one cannot distinguish a non-artificial intelligence program from an
artificial intelligence program by, say, interacting with it freely for
a couple of hours, then would not one be compelled to conclude that the
non-artificial intelligence program was displaying true artificial
artificial intelligence?
Mark