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The Chinese Room Argument (Stanford Encyclopedia of Philosophy)
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The Chinese Room Argument<br>First published Fri Mar 19, 2004; substantive revision Wed Oct 23, 2024
The argument and thought-experiment now generally known as the Chinese<br>Room Argument was first published in a 1980 article by American<br>philosopher John Searle (1932–2025). It has become one of the<br>best-known arguments in recent philosophy. Searle imagines himself<br>alone in a room following a computer program for responding to Chinese<br>characters slipped under the door. Searle understands nothing of<br>Chinese, and yet, by following the program for manipulating symbols<br>and numerals just as a computer does, he sends appropriate strings of<br>Chinese characters back out under the door, and this leads those<br>outside to mistakenly suppose there is a Chinese speaker in the room.
The narrow conclusion Searle draws from the argument is that<br>programming a digital computer may make it appear to understand<br>language but could not produce real understanding. Hence the<br>“Turing Test” is inadequate. Searle argues that the<br>thought experiment underscores the fact that computers merely use<br>syntactic rules to manipulate symbol strings, but have no<br>understanding of meaning or semantics. The broader conclusion of the<br>argument is that the theory that human minds are computer-like<br>computational or information processing systems is refuted. Instead<br>minds must result from biological processes; computers can at best<br>simulate these biological processes. Thus the argument has large<br>implications for semantics, philosophy of language and mind, theories<br>of consciousness, computer science, and cognitive science generally.<br>As a result, there have been many critical replies to the<br>argument.
1. Overview
2. Historical Background
2.1 Leibniz’ Mill
2.2 Turing’s Paper Machine
2.3 The Chinese Nation
3. The Chinese Room Argument
4. Replies to the Chinese Room Argument
4.1 The Systems Reply
4.2 The Robot Reply
4.3 The Brain Simulator Reply
4.4 The Other Minds Reply
4.5 The Intuition Reply
4.6 Advances in Artificial intelligence
5. The Larger Philosophical Issues
5.1 Syntax and Semantics
5.2 Intentionality
5.3 Mind and Body
5.4 Simulation, duplication and evolution
Conclusion
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1. Overview
Work in Artificial Intelligence (AI) has produced computer programs<br>that can beat the world chess champion, control autonomous vehicles,<br>and defeat the best human players on the television quiz show<br>Jeopardy. By 2022 AI had evolved from personal digital<br>assistants (Alexa, Siri, Google Assistant) translating and answering<br>questions to using Large Language Models (LLMs) that could write<br>poems, college level essays, and computer programs, and could pass<br>exams designed to screen the entrants into graduate schools, the study<br>and practice of Law, and other “learned professions”. Our<br>experience shows that playing chess or Jeopardy, writing<br>essays, passing difficult exams, and carrying on a conversation, are<br>activities that require understanding and intelligence. Does computer<br>prowess at conversation, writing essays, and passing difficult<br>examinations then show that computers can understand language and be<br>intelligent? Will further development result in digital computers that<br>fully match or even exceed human intelligence?
Alan Turing<br>(1950), one of the pioneer theoreticians of computing, believed the<br>answer to these questions was “yes”. Turing proposed what<br>is now known as<br>‘The Turing Test’:<br>if a computer can pass for human in online chat, we should grant that<br>it is intelligent. By the late 1970s some AI researchers claimed that<br>computers already understood at least some natural language. In 1980<br>U.C. Berkeley philosopher John Searle introduced a short and<br>widely-discussed argument intended to show conclusively that it is<br>impossible for digital computers to understand language or think, now<br>or in the future
Searle argues that a good way to test a theory of mind, say a theory<br>that holds that understanding can be created by doing such and such,<br>is to imagine what it would be like to actually do what the theory<br>says will create understanding. Searle (1999) summarized his Chinese<br>Room Argument (hereinafter, CRA) concisely:
Imagine a native English speaker who knows no Chinese locked in a room<br>full of boxes of Chinese symbols (a data base) together with a book of<br>instructions for manipulating the symbols (the...