The editing test for the deep problem of AI

Collins, Harold Maurice ORCID: https://orcid.org/0000-0003-2909-9035 1997. The editing test for the deep problem of AI. Psycoloquy 8 (1) , 8.

Full text not available from this repository.

Abstract

All the problems of AI are surface transformations of one deep problem: how to make a computer that can learn from its surroundings, including social surroundings, in the same way that humans learn. The Turing Test can be adapted to check whether or not the deep problem has been solved by looking at one of its surface transformations -- the problem of "interpretative asymmetry." Interpretative asymmetry refers to the skillful way in which humans "repair" deficiencies in speech, written texts, handwriting, etc., and the failure of computers to achieve the same interpretative competence. Short passages of typed text are quite enough to reveal interpretative asymmetry, and therefore a Turing-like test, turning on the differential ability to sub-edit such short passages, is sufficient to reveal whether the deep problem of AI has been solved.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Social Sciences (Includes Criminology and Education)
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ISSN:	1055-0143
Last Modified:	01 Nov 2022 09:47
URI:	https://orca.cardiff.ac.uk/id/eprint/89218

Citation Data

Cited 3 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item