[curious_yogurt]

The Chinese Room is a reductio against Strong AI. Strong AI is the idea that a program that programme that is able, for example, to converse in Chinese thereby understands Chinese. The Room, if successful, drives a wedge between "acting as if one knows Chinese" and "understanding Chinese". This may be applied to the any number of programs. But with such a wedge, we do not actually have Strong AI—the appearance of intelligence (grounded in syntax) is different from actual intelligence (presumably grounded in semantics).

In other words, assume strong AI. Strong AI implies machines have understanding. But the Chinese Room argues machines can never have understanding. So, strong AI is not possible.

In the background is Turing's attempt to provide an account of intelligence. Turing skirts the issue in his famous paper "Computing Machinery and Intelligence"[1]: instead of defining intelligence, Turing proposes a test. But the Chinese Room argues that even if we had a machine pass this test, we would not thereby be bound to say that the machine was intelligent.

[1] https://www.csee.umbc.edu/courses/471/papers/turing.pdf

[Retric]

You have presupposed the answer.

Replace a book with a person in that example and have the human walk up to the person and ask a question. Now in that case would saying the person moving the note does not understand something mean the room does not contain something that does understand? Nope.

Therefore, saying the human in the original example does not understand something does not in fact answer your question. My lungs don’t speak English, but I can’t speak English without them.

[curious_yogurt]

I do not believe I have presupposed the answer; I have simply articulated how I believe the reductio to work.

The key, of course, is whether we think that the person in the Room actually understands Chinese. The inference Searle wants us to draw, based on our intuition, is that the person does not understand Chinese just because the person is following a lookup table. The way to get around the argument is to claim either (i) that the inference doesn't work—that is, Strong AI does not imply machines understand, or (ii) that the Chinese Room does not imply machines do not understand.

I think (i) is a reasonable claim that follows from understanding what is intended by the term "Strong AI." (ii) is the tricky one. It seems to me the best route out is to find a way to substantiate a claim alluded to by another commentator, viz. the property of intelligence does not exist (though I would say "understanding does not apply" or something like that). The thing is, it does seem to me that understanding is a reasonable category for this case; and anyone who thinks this is likely to feel the force of the argument.

[Retric]

> The key, of course, is whether we think that the person in the Room actually understands Chinese.

As I said that’s no more relevant than if the paint on the walls understands Chinease. You can’t answer the question of if the room understands something by saying if a single element understands something or not.

Or consider this, does Microsoft the company understand French? It seems like a simple question, but you can easily support yes or no. In some situations it can respond to a French speaker, but not all situations.

[curious_yogurt]

To be fair, I did not ask the question of whether "the room understands." The question was whether "the person in the room understands," which seems perfectly reasonable.

In order to grasp what you are saying about "Microsoft the company understand French" one needs to define what we mean by "understand." As you (correctly) say, our answer will depend on that definition.

But to say everything depends on our definition of understanding is to miss the point of the Chinese Room. The point of the argument is to support the claim that the sort of thing we normally classify as understanding—such as when we say someone understands Chinese—is not a property of the person following a lookup table (or by analogy, a machine with instructions). Thus, neither the person in the room, nor the machine, understands in the same sense as when we say "this person understands Chinese."

This is how the Chinese Room is supposed to work against Strong AI. Strong AI supposes that when you have appropriate instructions, a machine is said to understand in the same sense in which you say a human understands. The Chinese Room argument is meant to prompt the claim that the machine does not understand—or at the very least does not understand in the same sense that a human understands.

[Retric]

While you say you are only talking about “the machine” it’s rather pointless. Fine, my hair is not sentient either again it’s not an argument.

Strong AI is a system not a machine. The person using a lookup table is just a portion of the system and thus can’t be used to limit the entire system.

Twins don’t nessisarily understand the same languages based on their training. Referring to the Human in “the room” as the machine following specific instructions is the same as saying human DNA don’t understand English. It’s might be true, but it’s definitely irrelevant.

Machine code is binary data used by computers that ideally maps 1:1 with ASM. A human can know ASM and with the aid of a computer produce, read, edit, etc Machine code they don’t directly understand. In effect they are part of a system that understands something that they themselves don’t.

Thus “the Chinese Room” has an inescapable though easily missed failure in logic. Saying the machine is nor the room, seems like an unreasonable objection. But, talking about the machine it’s just as relevant as saying people without exposure don’t know specific languages.

PS: Starting with a glass of water you can separate it into smaller places up to a point. But in the end water is H20, if you just look at the H that’s not water because you reached the point where subdivision results in a different substance. Saying H is not water thus water does not exist is a silly argument.

[joe_the_user]

The argument is not about simple decomposition.

The argument is non-speaker+room doesn't write Chinese but lungs+rest-of-person does speak Chinese.

The Chinese room is intended to be decomposition that shows something different than decomposing a person.

[Retric]

The argument is exactly of the form: A person follows instructions to build an ikea desk. They don’t understand the instructions only individual steps.Therefore they don’t understand the construction of the desk. Therefore the system of them plus the desk does not understand how to construct a desk.

Except in this case it’s more clear the person does understand how to get the outcome. Just follow the instructions, thus the system of them plus the instructions understands how to build a desk.

Sure, computer hardware just like human DNA for example does not understand English. But, that says nothing about systems created by human DNA or computer hardware.

[ForHackernews]

Wait, so you're claiming that being able to mechanistically follow instructions to get to desired result X counts as the "system" of instructions+follower understanding X?

So if I follow a React.js tutorial and get to a working Todo App example, that means me + tutorial page "understands" React.js? What am I missing?

[Retric]

Can get the outcome of the tutorial is not the same as understanding React.js.

Basically, cookbooks allow people to create food that they don’t know how or create without the cookbook. But, that only applies to what’s actually listed in the cook book. For a tutorial to allow somone to ‘know’ react it would need to encompass all edge cases etc.

Given all nessisary tools and resources like reference materials somone might be able to create arbitrary React.js pages which is closer to what your example. The remaining difference is time to completion and quality of output. But, if the tools allow somone to get the same quality of output in the same fine frame as somone that knows React.js then the system effectively knows React.js.

Consider, somone knows ASM but not machine code. Given the right tooling that coverts back and forth 1:1 to machine code it’s functionally identical to somone knowing machine code. Which is why nobody learns machine code over ASM as there is no benifit to learning machine code.

[joefourier]

Why would the room being successful reveal anything useful? Why does it matter if a program is executed on pencil and paper or electronically? The thought experiment does not bring any novel insights and just misdirects the reader by focusing on the human.

You could execute the Strong AI program on any Turing complete system. Asking if the human understands Chinese is just as absurd as asking if a universal Turing machine understands Chinese given the same program. The machine just follows the instructions given, the philosophical questions reside entirely on the side of the program and the execution of it.

[curious_yogurt]

I think you have put your finger on exactly what is at issue: it does not matter whether the program is pencil or paper or electronically. It's an analogy. The point is that we do not (says Searle) impute understanding to the person in the room, therefore we should not impute understanding to a computer running a program. But Strong AI requires us to impute understanding; and this is exactly what is impossible. Therefore Strong AI does not exist. I take that to be the force of the argument.