Imagine that you’re locked in a room. You don’t know any Chinese, but you have a huge instruction book written in English that tells you exactly how to respond to Chinese writing. Someone outside the room slides you a piece of paper with Chinese writing on it. You can’t understand it, but you can look up the characters in your book and follow the instructions to write a response.
You slide your response back out to the person waiting outside. From their perspective, it seems like you understand Chinese because you’re providing accurate responses, but actually, you don’t understand a word. You’re just following instructions in the book.
Its a thought experiment involving a room where people write letters and shove them under the door of the Chinese kid’s dorm room. He doesn’t understand what’s in the letters so he just forwards the mail randomly to his Russian and Indian neighbours who sometimes react angrily or happily depending on the content. Over time the Chinese kid learns which symbols make the Russian happy and which symbols make the Indian kid happy, and so forwards the mail correspondingly until he starts dating and gets a girlfriend that tells him that people really shouldn’t be shoving mail under his door, and he shouldn’t be forwarding mail he doesnt understand for free.
Wow, solid wiki article! It’s very hard to say anything on the subject that hasn’t been said.
I didn’t see the simple phrasing:
“What if the human brain is a Chinese Room?”
but that seems to fall under eliminative materialism replies.
Part of the Chinese Room program (both in our heads and in an AI) could be dedicated to creating the experience of consciousness.
Searle has no substantial logical reply to this criticism. He openly takes it on faith that humans have consciousness, which is funny because an AI could say the same thing.
Man, I love coming across terms like this.
Chinese Room, Chinese Walls, Dutch Treat, Dutch Uncle, Dutch Oven.
The Chinese room argument makes no sense to me. I cant see how its different from how young children understand and learn language.
My 2 year old sometimes unmistakable start counting when playing. (Countdown for lift off) Most numbers are gibberish but often he says a real number in the midst of it. He clearly is just copying and does not understand what counting is. At some point though he will not only count correctly but he will also be able to answer math questions. At what point does he “understand” at what point would you consider that chatgpt “understands”  There was this old tv programm where some then ai experts discussed the chinese room but they used a chinese restaurant for a more realistic setting. This ended with “So if i walk into a chinese restaurant, pick sm out on the chinese menu and can answer anything the waiter may ask, in chinese. Do i know or understand chinese? I remember the parties agreeing to disagree at that point.
Yes… the chinese experiment misses the point, because the Turing test was never really about figuring out whether or not an algorithm has “conscience” (what is that even?)… but about determining if an algorithm can exhibit inteligent behavior that’s equivalent/indistinguishable from a human.
The chinese room is useless because the only thing it proves is that people don’t know what conscience is, or what are they even are trying to test.
ChatGPT will never understand. LLMs have no capacity to do so.
To understand you need underlying models of real world truth to build your word salad on top of. LLMs have none of that.
What are your underlying models of the world built out of? Because I’m human, and mine are primarily built out of words.
How do you draw a line between knowing and understanding? Does a dog understand the commands it’s been trained to obey?
https://thegradient.pub/othello/
LLMs are neural networks and are absolutely capable of understanding.
Note that “real world truth” is something you can never accurately map with just your senses.
No model of the “real world” is accurate, and not everyone maps the “real world truth” they personally experience through their senses in the same way… or even necessarily in a way that’s really truly “correct”, since the senses are often deceiving.
A person who is blind experiences the “real world truth” by mapping it to a different set of models than someone who has additional visual information to mix into that model.
However, that doesn’t mean that the blind person can “never understand” the “real world truth” …it just means that the extent at which they experience that truth is different, since they need to rely in other senses to form their model.
Of course, the more different the senses and experiences between two intelligent beings, the harder it will be for them to communicate with each other in a way they can truly empathize. At the end of the day, when we say we “understand” someone, what we mean is that we have found enough evidence to hold the belief that some aspects of our models are similar enough. It doesn’t really mean that what we modeled is truly accurate, nor that if we didn’t understand them then our model (or theirs) is somehow invalid. Sometimes people are both technically referring to the same “real world truth”, they simply don’t understand each other and focus on different aspects/perceptions of it.
Someone (or something) not understanding an idea you hold doesn’t mean that they (or you) aren’t intelligent. It just means you both perceive/model reality in different ways.
For one thing, understanding implies that a word is linked to a mental concept. So if you say “The car is red”, you first need to mentally compare the mental concept of “red” to the car in question.
The Chinese room bypasses all of that, it can say “The car is red” without ever having seen a red object at all.
Do you maintain this line of reasoning if it only says “the car is red” when the car is in fact red. And is capable of changing the answer to correctly mentioned a different color when the item In question is a different question.
Some ai demos show that programs like gpt-4 are already way passed this when provided with, it can not only accurate describe whats in the image but also the context.
Some examples, mind these where shown in an openAI demo for gpt4, Open ai has not yet made their version of this tech publicly available.
When i see these examples, i am not convinced that the ai truly understands everything it is saying. But it does seem to understand context, One of the theories on how it can do this (they are still a black box) is talked about in some papers that large language models may actually create an internal model of the world similar to humans and use that for logical reasoning and context.
For me, I think the criteria I’d use for saying someone has a decent understanding of math is knowing that math has underlying rules and most things can be understood from those basic rules (each problem is not just an arbitrary magic trick to get an answer that was impossible figure out) and perhaps also being able to ask “novel” questions (compared that what you already know) and taking reasonable steps to answer it with the rules you do know and the tools you have (doesn’t need to be successful). I think counting could be done with any consistent set of sounds and it doesn’t matter whether yours just reading those sounds for a list or not as long as you know roughly what they correspond to in terms of time. I don’t think a lot of humans have much understanding of math, I think some computers already beat a lot of humans with respect to that.
My gripe with the Chinese room is that Searle argues that his inability to understand Chinese means the program doesn’t understand Chinese, but I could say the same thing about the human body.
The neurons that operate your vocal chords have no idea what they’re saying, nor the ones in your hands any idea what they’re writing, yet they can speak and write exactly because your brain tells them what to do. Your brain is exactly like that book as far as your mouth and hand neurons are concerned.
They don’t need to understand language at all for your brain to be able to understand it and give instructions based on that understanding.
My only argument is at what point does an algorithm become sufficiently advanced that it is indistinguishable from a conscious being?
Because at the end of the day, most of what a brain does is information processing based on what it has previously learnt, and that’s exactly what the algorithm is doing based on training data. A sufficient enough algorithm should surely be able to replicate understanding.
Sure, that isn’t ChatGPT as we know it, as you can tell from its sometimes very zany responses that while it understands what words are valid responses, it doesn’t understand what the words themselves mean, but we should reach that at some point, no?
Keep in mind ChatGPT is a language model. It’s designed specifically to simulate sounding like a human. It does that… Okay. It doesn’t understand the information or concepts it is using. It just sounds like it does. It can’t reliably do basic maths and doesn’t try or need to. It just needs to talk about it in a believably conversational way.
The brain does far more than process information. And ChatGPT doesn’t even really do that.
Okay. It doesn’t understand the information or concepts it is using.
That’s just utter nonsense. ChatGPT by every definition of the word very much understands a lot of what it is talking about. People complaining about ChatGPT not “understanding” seems to have a hard time grasping how insanely difficult it is to produce natural language answers and how much you need to understand of the context to do so successfully.
It can’t reliably do basic maths
Neither can many humans, but my $5 calculator is great at it. There are without a doubt a lot of things that ChatGPT can’t do, sometimes fundamentally so, like math. It can’t do loops and it doesn’t even get to see the digits of the numbers it should calculate on, so not a terribly big surprise that it can’t do math very well. English language, and a whole bunch of other ones, on the other side, that it understands surprisingly well.
Basically, if you want to complain about ChatGPT, complain about things it actually gets wrong, saying “it doesn’t understand” just makes you sound like a parrot and note even a clover one.
Well mostly the flaw is people assigning the test abilities it was never intended. Like testing intelligence. Turing outright as first thing in the paper presenting “imitation game” noted moving away from testing intelligence, since he didn’t know to do that. Even on the realm of “testing intelligent kind of behavior” well more like human like behavior and human being here proxy for intelligent, it was mostly an academic research idea. Not a concrete test meant to be some milestone.
If the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly useit is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.
Turing wanted a way to step away from stuff like “thinking” and “intelligence” directly and then proposed “imitation game” mostly to the rest of the academia as way to develop computer systemics more towards “intelligent behavior”. It was mostly like “hey we need some goal to have as a goal to have something to move towards with these intelligence things. This isn’t intelligence, but it might be usefull goal or tool for development work”. Since without some goal/project/aim to have project don’t advance. So it was “how about we try to develop a thing, that can beat this imitation game. Wouldn’t that be good stepping stone. Then we can move to the actual serious stuff. Just an idea”.
However since this academic “thinking out aloud spitballing ideas” was uttered by the Alan Turing, it became the Turing Test and everyone started taking it way too seriously. Specially outside academia. Who yes did play the imitation game with their programs as it was intended as research and development tool.
exemplified by for example this little exerpt of “not trying to do anything too complete and ground breaking here”:
In any case there is no intention to investigate here the theory of the game, and it will be assumed that the best strategy is to try to provide answers that would naturally be given by a man
It is pretty literally “I had a thought”. Turin makes no claims of machine beating the game having any significance other than “machine beat this game I came up with, neat”. There is no argument of if machine beats imitation game, then X or then it means Y is reached.
Rest of the paper is actually about objections to the core idea of “it could ever be possible for machine to think” and even as such said imitation game is kinda lead in or introduction to Turing’s treatise various objections of various “it would be impossible for machine to think” arguments. Starting with theological argument of “only human soul can think. Hence no animal or machine can think.” … since it was 1950’s.
I don’t understand how Chinese room is a valuable argument. To me, while the person inside the room doesn’t understand Chinese, the system room-person-instructions does. You don’t argue that you don’t understand your language because none of your individual neurons understand it.
I don’t claim that chatGPT “understands” the language, I just don’t think that this argument applies in general.
So? The room as a whole can speak chinese, what do i care how it works in the inside?
Also, can you give me a convincing argument that our brain doesn’t work in essentially the same way?
@Barbarian772 so? If the cookie tastes sweet, what do I care what sweetening agent is used inside?
No? But how can you even prove that our brain works differently than a chinese room?
Or at some point, we have to accept that AI has consciousness. If it can pass every test that we can devise, then it has consciousness.
There’s an unusually strong bias in these experiments… Like the goal isn’t to sincerely test for consciousness. Instead we start with the conclusion: obviously a machine can’t be conscious. How do we prove this?
Of course, for the purposes of human power structures, this line of thinking just makes humans more disposable. If we’re all just machines, then why should anyone inherently have rights?
