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.
An LLM is a series of immutable nodes that pass results on to the next series of nodes until an output is generated, a functionality that could be perfectly imitated with a very large number of people seeing a series of values passed to them from other people, doing a bit of rigidly defined basic math with them, and passing it on to the next set of people who play the part of the next set of nodes.
The fact that these nodes are immutable, have no persistent state, and only process information in one direction (input to output, and no more) means that an LLM has no persistence of experience. You could potentially argue that the information, as it exists, is a form of fleeting consciousness, but it would be so incredibly alien compared to the lived experience of humans that it would be impossible to relate to in any meaningful way - and it would also mean that every time an LLM is run, the consciousness is created and destroyed for every single word that it outputs… unless you can somehow argue that the consciousness is contained in the set of tokens that gets fed back into the LLM with each word it outputs, which would also mean that any string of text is the equivalent of latent consciousness, which is patently absurd.
You could potentially argue that the information, as it exists, is a form of fleeting consciousness, but it would be so incredibly alien compared to the lived experience of humans that it would be impossible to relate to in any meaningful way
Curiously, one of the approaches to the consciousness, and a more Zen-ish one, is that clinging to a persistent ‘self’ is erroneous and it’s better seen as a process rather than an entity. Granted, it still assumes a ‘self’ that is changed by each passing experience.
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.
That’s not what I understood from the Wikipedia article. In any case, an LLM doesn’t look up responses from a table.
An LLM is a series of immutable nodes that pass results on to the next series of nodes until an output is generated, a functionality that could be perfectly imitated with a very large number of people seeing a series of values passed to them from other people, doing a bit of rigidly defined basic math with them, and passing it on to the next set of people who play the part of the next set of nodes.
The fact that these nodes are immutable, have no persistent state, and only process information in one direction (input to output, and no more) means that an LLM has no persistence of experience. You could potentially argue that the information, as it exists, is a form of fleeting consciousness, but it would be so incredibly alien compared to the lived experience of humans that it would be impossible to relate to in any meaningful way - and it would also mean that every time an LLM is run, the consciousness is created and destroyed for every single word that it outputs… unless you can somehow argue that the consciousness is contained in the set of tokens that gets fed back into the LLM with each word it outputs, which would also mean that any string of text is the equivalent of latent consciousness, which is patently absurd.
Curiously, one of the approaches to the consciousness, and a more Zen-ish one, is that clinging to a persistent ‘self’ is erroneous and it’s better seen as a process rather than an entity. Granted, it still assumes a ‘self’ that is changed by each passing experience.
How can you call it absurd when we have no idea what makes something conscious in the first place?