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> does the person just doing a "hash-table lookup" But this is Searle's sleight-of-hand. The question isn't whether the person in the Chinese room understands

> does the person just doing a "hash-table lookup" But this is Searle's sleight-of-hand. The question isn't whether the person in the Chinese room understands Chinese, but whether the system as a whole understands Chinese. The man is analogous to the CPU in a computer, but the CPU is embedded in a larger system and it is the entire system that performs operations of the computer. You can't focus on one component to the exclusion of the rest of the system and expect to derive valid conclusions about the system. >The challenge is to specify the environment computationally I agree, but this presents no in principle challenge to a computational system reaching such a detailed description of the environment. >The issue here is that if "computer" isnt just a trivial property it has to include, eg., measurability, determinism, etc. Properties that reality lacks. Reality isnt a computer. I don't follow. The issues of measurability and determinism in QM (assuming that's what you are referring to) aren't necessarily problems at the scale of physical systems. Computational systems can certainly make distinctions to within some margin of error, which is sufficient as a substrate for gathering information about the external environment.

mjburgess 5y ago
No, there's no sleight of hand. It seems you just agree that the man doesnt understand Chinese. > at the scale of physical systems. Alas, they are. Even classical mechanics isn't deterministic. Most systems are chaotic and require infinite precision in measurement to be deterministic. Since QM precludes this, most chaotic systems literally can only be predicted over short horizons. Eg., there is moon in our solar system, i believe, with a chaotic orbit. At maximum possible measurement fidelity we can predict 20yrs. Consider that all the particles of our body are just these little chaotic moons, and their aggregate chaos dramatically dimishes this 20yr horizon. There is, quite literally, not enough information present in this moment to predict the next moment. Most systems are sufficiently chaotic in a sufficiently large number of parameters to preclude this. This reaches all the way up to classical scales. Reality isnt a computer.
- burkaman 5y ago
  Everyone agrees that the man doesn't understand Chinese. The sleight of hand is that Searle compares a full computer to a component of the Chinese Room, when he should be comparing a computer to the room as a whole. The man in this thought experiment is analogous to an internal component of a computer, not the whole thing. Put another way, Searle separates a "computer" from the instructions it is running, but there is no such separation. It's like separating a brain from the electrical brain activity. It's true that a brain without electrical activity cannot understand Chinese just like a computer without a program cannot, but that's not a very interesting observation.
  - mjburgess 5y ago
    A computer is just an implementation of a function (in mathematical sense), ie., a finite set of pairs (IN, OUT) where (IN, OUT) in {0,1}^N, {0,1}^N. Ie., its an implementation of {010101, ...} -> {010101010, 01010...} . If we all agree that the function the man performs can be set to be whatever you wish (ie., any {input sentences} -> {output sentences}) and we agree that the man doesnt understand chinese... then the question arises: what is missing? I dont think the "systems reply" actually deals with this point -- it rather just "assumes it does" by "assuming some system" to be specified. If using a language isnt equivalent to a finite computable function -- what is it? The systems reply needs to include that the reason a reply is given is that the system is caused to give the reply by the relevant causal history / environment / experiences. Ie., that the system says "it's sunny" because it has been acquainted with the sun, and it observes that the day is sunny. This shows the "systems reply" prima facie fails: it is no reply at all to "presume that the system can be so-implemented so as to make the systems reply correct". You actually need to show it can be so-implemented. No one has done this. There are lots of reasons to suppose it can be done, not least, that most things arent computable (ie., via non-determinism, chaos, and the like). Given the environment is chaotic, it is a profoundly open question whether computers can be built to "respond to the right causes" and computational systems may be incapable of doing this. If they cannot, then searle is right. That man, and whatever he may be a part of, will never understand chinese. It is insufficient to "look up the answers", "proper causation" is required.
    - 5y ago
bobthechef 5y ago
> whether the system as a whole understands Chinese. "The system" isn't the kind of thing that understands. If I give n people a letter each and a number indicating the position the letter should occupy on some grid, it does not follow that the group knows the sentence because groups are not knowing subjects. If they arrange the letters on the grid, then each individual person in the group now knows the sentence when they read it. Only individual knowing agents know and understand. Abusing the definition of "knowing" or "understanding" doesn't help clarify anything. All it does is lead to equivocation.
- hackinthebochs 5y ago
  You could say the same thing about neurons and brains. Clearly something is wrong with this argument.
  - mannykannot 5y ago
    Indeed - there are, in fact, several things wrong with it. Firstly, it is a circular argument in which an unargued-for intuition - '"The system" isn't the kind of thing that understands' - is used in trying to justify that intuition. Secondly, no-one is suggesting, and Strong AI certainly does not imply, that the utterly simple 'system' here is capable of understanding anything. The fact that it does not proves nothing. Thirdly, it is irrelevant (a variant of the homunculus fallacy) to see any significance in what the actors understand and when they do so, as they are being employed to act as unthinking automata. Replace each of them with a simple mechanism for placing a letter in a predetermined spot, and you have an equivalent system, also mindless, that is equally useless for demonstrating anything about the feasibility of Strong AI.

mjburgess 5y ago

No, there's no sleight of hand. It seems you just agree that the man doesnt understand Chinese. > at the scale of physical systems. Alas, they are. Even classical mechanics isn't deterministic. Most systems are chaotic and require infinite precision in measurement to be deterministic. Since QM precludes this, most chaotic systems literally can only be predicted over short horizons. Eg., there is moon in our solar system, i believe, with a chaotic orbit. At maximum possible measurement fidelity we can predict 20yrs. Consider that all the particles of our body are just these little chaotic moons, and their aggregate chaos dramatically dimishes this 20yr horizon. There is, quite literally, not enough information present in this moment to predict the next moment. Most systems are sufficiently chaotic in a sufficiently large number of parameters to preclude this. This reaches all the way up to classical scales. Reality isnt a computer.

burkaman 5y ago
Everyone agrees that the man doesn't understand Chinese. The sleight of hand is that Searle compares a full computer to a component of the Chinese Room, when he should be comparing a computer to the room as a whole. The man in this thought experiment is analogous to an internal component of a computer, not the whole thing. Put another way, Searle separates a "computer" from the instructions it is running, but there is no such separation. It's like separating a brain from the electrical brain activity. It's true that a brain without electrical activity cannot understand Chinese just like a computer without a program cannot, but that's not a very interesting observation.
- mjburgess 5y ago
  A computer is just an implementation of a function (in mathematical sense), ie., a finite set of pairs (IN, OUT) where (IN, OUT) in {0,1}^N, {0,1}^N. Ie., its an implementation of {010101, ...} -> {010101010, 01010...} . If we all agree that the function the man performs can be set to be whatever you wish (ie., any {input sentences} -> {output sentences}) and we agree that the man doesnt understand chinese... then the question arises: what is missing? I dont think the "systems reply" actually deals with this point -- it rather just "assumes it does" by "assuming some system" to be specified. If using a language isnt equivalent to a finite computable function -- what is it? The systems reply needs to include that the reason a reply is given is that the system is caused to give the reply by the relevant causal history / environment / experiences. Ie., that the system says "it's sunny" because it has been acquainted with the sun, and it observes that the day is sunny. This shows the "systems reply" prima facie fails: it is no reply at all to "presume that the system can be so-implemented so as to make the systems reply correct". You actually need to show it can be so-implemented. No one has done this. There are lots of reasons to suppose it can be done, not least, that most things arent computable (ie., via non-determinism, chaos, and the like). Given the environment is chaotic, it is a profoundly open question whether computers can be built to "respond to the right causes" and computational systems may be incapable of doing this. If they cannot, then searle is right. That man, and whatever he may be a part of, will never understand chinese. It is insufficient to "look up the answers", "proper causation" is required.
  - 5y ago

bobthechef 5y ago

> whether the system as a whole understands Chinese. "The system" isn't the kind of thing that understands. If I give n people a letter each and a number indicating the position the letter should occupy on some grid, it does not follow that the group knows the sentence because groups are not knowing subjects. If they arrange the letters on the grid, then each individual person in the group now knows the sentence when they read it. Only individual knowing agents know and understand. Abusing the definition of "knowing" or "understanding" doesn't help clarify anything. All it does is lead to equivocation.

hackinthebochs 5y ago
You could say the same thing about neurons and brains. Clearly something is wrong with this argument.
- mannykannot 5y ago
  Indeed - there are, in fact, several things wrong with it. Firstly, it is a circular argument in which an unargued-for intuition - '"The system" isn't the kind of thing that understands' - is used in trying to justify that intuition. Secondly, no-one is suggesting, and Strong AI certainly does not imply, that the utterly simple 'system' here is capable of understanding anything. The fact that it does not proves nothing. Thirdly, it is irrelevant (a variant of the homunculus fallacy) to see any significance in what the actors understand and when they do so, as they are being employed to act as unthinking automata. Replace each of them with a simple mechanism for placing a letter in a predetermined spot, and you have an equivalent system, also mindless, that is equally useless for demonstrating anything about the feasibility of Strong AI.