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Strong AI Thesis

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The Strong AI Thesis was named by American philosopher John Searle (born 1931), to describe the belief that AI (artificial intelligence) may possess actual consciousness like that of a human being.

The idea is expressed as follows:

The appropriately programmed digital computer with the right inputs and outputs would thereby have a mind in exactly the sense that human beings have minds”¹

Searle, himself, rejects the Strong AI Thesis. He believes that computer intelligence simulates but doesn’t possess real thought, a position called “Weak AI.” His Chinese Room thought experiment gives us a compelling argument in support of his position.

English: Mica (Brionne Dawson) is trapped in t...

Mica (Brionne Dawson) is trapped in the Chinese Room. It is an imaginary space first described by philosopher John Searle, though this is from the 2009 fiction narrative feature The Chinese Room, inspired by Searle’s thought experiment. (Photo credit: Wikipedia)

Others believe that Strong AI isn’t too far-fetched, considering that human beings are, at least in part, made up of electrochemical interactions. If Strong AI is true, we can reduce idea down to the simplest levels and argue that even your refrigerator, toaster or iPad have some kind of unique electro-organizational consciousness that would distinguish them from, say, a pile of rocks.

These ideas are explored in many science fiction novels, TV-shows and films. One of the better treatments is found in the reimagined Battlestar Galactica, where the line between humans and Cylons sometimes seems very thin.

¹ John Searle, 1998 in Dennett, Damiel C. Consciousness Explained, Boston: Little, Brown and Company, 1991 p. 435.

Related Posts » Isaac Asimov, Commander Data, Hal 9000, Panpsychism

 

 

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Author: Earthpages.ca

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2 thoughts on “Strong AI Thesis

  1. searle is the one who argues that strong AI is impossible.

    Like

  2. Thanks. I just revised the entry. If you see any other errors please don’t hesitate to point them out.

    Much appreciated…

    Like

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