In the second scenario, there is no “native speaker” that is telling you what to write. There is a list of instructions that you are following that is the same as the instructions that the computer was following with the first scenario.
The argument is that if, by following the exact instructions that the computer is following, you still do not understand the Chinese conversation, why would you say that the machine understands?
I haven’t thought about the idea enough to say I agree or disagree, but I hope I understood your comment and that the explanation helps.
No, it doesn’t make any sense at all. If I couldn’t understand when a native speaker was replying, how does me not understanding when a neural network does it make it any less significant?
In the Chinese Room scenario, cards with Chinese written on them are inserted into a box.
Inside there is a man who doesn’t understand Chinese but has a lookup list of which symbols to write as a response to every possible sentence you can write on the inserted card.
For anyone observing from outside the box it looks as if whatever is in the box is fluent in Chinese and can hold a conversation. But the man inside does not understand anything about Chinese.
This is used as an analogy to explain that machines, very much like the man in the box, do not actually understand the data they are fed, nor the data they output, no matter how human the response might seem.
It was an argument against the Turing test, which is about whether machines showing behaviour indistinguishable from a human is a sign that they can think.
The Chinese Room argument is that they must also show understanding of the data itself, rather than just human-like responses, to say that they think.
In the second scenario, there is no “native speaker” that is telling you what to write. There is a list of instructions that you are following that is the same as the instructions that the computer was following with the first scenario.
The argument is that if, by following the exact instructions that the computer is following, you still do not understand the Chinese conversation, why would you say that the machine understands?
I haven’t thought about the idea enough to say I agree or disagree, but I hope I understood your comment and that the explanation helps.
No, it doesn’t make any sense at all. If I couldn’t understand when a native speaker was replying, how does me not understanding when a neural network does it make it any less significant?
In the Chinese Room scenario, cards with Chinese written on them are inserted into a box.
Inside there is a man who doesn’t understand Chinese but has a lookup list of which symbols to write as a response to every possible sentence you can write on the inserted card.
For anyone observing from outside the box it looks as if whatever is in the box is fluent in Chinese and can hold a conversation. But the man inside does not understand anything about Chinese.
This is used as an analogy to explain that machines, very much like the man in the box, do not actually understand the data they are fed, nor the data they output, no matter how human the response might seem.
It was an argument against the Turing test, which is about whether machines showing behaviour indistinguishable from a human is a sign that they can think.
The Chinese Room argument is that they must also show understanding of the data itself, rather than just human-like responses, to say that they think.