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This should be really "react to" or "answer to", instead of "understand". These are not the same. Edit: Anthropomorphizing algorithms and pattern stores doesn'

This should be really "react to" or "answer to", instead of "understand". These are not the same. Edit: Anthropomorphizing algorithms and pattern stores doesn't really help understanding. Instead, it's apt to spread misunderstanding. Remember how long it took to purge the popular idea of "electronic brains" actually thinking, and to establish that these were restricted to executing what's actually in code? We don't need to start another level of this with "AI". (Understanding is closely related to self-awareness and consciousness, and this is dangerous ground of misunderstanding when it comes to AI. As we've seen, even staff of pioneering companies, like Google, is prone to fall for this.)

cercatrova 4y ago
This is a philosophical question, really. Is there ever true understanding, or just pattern matching? The Chinese Room thought experiment talks about this: > Searle's thought experiment begins with this hypothetical premise: suppose that artificial intelligence research has succeeded in constructing a computer that behaves as if it understands Chinese. It takes Chinese characters as input and, by following the instructions of a computer program, produces other Chinese characters, which it presents as output. Suppose, says Searle, that this computer performs its task so convincingly that it comfortably passes the Turing test: it convinces a human Chinese speaker that the program is itself a live Chinese speaker. To all of the questions that the person asks, it makes appropriate responses, such that any Chinese speaker would be convinced that they are talking to another Chinese-speaking human being. > The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese? Searle calls the first position "strong AI" and the latter "weak AI." > Searle then supposes that he is in a closed room and has a book with an English version of the computer program, along with sufficient papers, pencils, erasers, and filing cabinets. Searle could receive Chinese characters through a slot in the door, process them according to the program's instructions, and produce Chinese characters as output, without understanding any of the content of the Chinese writing. If the computer had passed the Turing test this way, it follows, says Searle, that he would do so as well, simply by running the program manually. > Searle asserts that there is no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program, step-by-step, producing behavior that is then interpreted by the user as demonstrating intelligent conversation. However, Searle himself would not be able to understand the conversation. ("I don't speak a word of Chinese," he points out.) Therefore, he argues, it follows that the computer would not be able to understand the conversation either. > Searle argues that, without "understanding" (or "intentionality"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that the "strong AI" hypothesis is false. https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room
- masswerk 4y ago
  Well, this, the Chinese Room, is still pretty much a behavioristic work-around (as it is still attempting to argue without any reference to internal states.) Even, if we don't (clearly) understand what "understanding" means, or, at least, aren't able to provide a sane definition, we do know about the semantics of the term and the kind of connotations that come with it. Like a reflexive component. (Which wasn't much of a problem in the age of behaviorism, as this had to be ignored by requirement anyway. If there is no acknowledged difference between a human and a pigeon, what is the problem with computers, as far as the model is concerned?) So we do have a notion of the semantic field and its implications. And these are, well, quite disastrous for this purpose.
  - masswerk 4y ago
    P.S.: In non-behavoristic terms: The term "understanding" is linked not only to the internal semantic field and its structure, as maintained by an individual, but also to its state of mind. We crucially expect the state of mind to be altered by an "act" of understanding. (Commonly expressed by an utterance like "aha!", which asserts this change in state of mind.) So, do we have to consider a state of mind (of some complexity) or a hypothesis of this, as in a theory of mind, in order to predict the productions of GPT-3, or does this further our hopes in a more precise prediction? Do we have to consider such a theory of mind in order to understand it on our side? Probably not.

cercatrova 4y ago

This is a philosophical question, really. Is there ever true understanding, or just pattern matching? The Chinese Room thought experiment talks about this: > Searle's thought experiment begins with this hypothetical premise: suppose that artificial intelligence research has succeeded in constructing a computer that behaves as if it understands Chinese. It takes Chinese characters as input and, by following the instructions of a computer program, produces other Chinese characters, which it presents as output. Suppose, says Searle, that this computer performs its task so convincingly that it comfortably passes the Turing test: it convinces a human Chinese speaker that the program is itself a live Chinese speaker. To all of the questions that the person asks, it makes appropriate responses, such that any Chinese speaker would be convinced that they are talking to another Chinese-speaking human being. > The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese? Searle calls the first position "strong AI" and the latter "weak AI." > Searle then supposes that he is in a closed room and has a book with an English version of the computer program, along with sufficient papers, pencils, erasers, and filing cabinets. Searle could receive Chinese characters through a slot in the door, process them according to the program's instructions, and produce Chinese characters as output, without understanding any of the content of the Chinese writing. If the computer had passed the Turing test this way, it follows, says Searle, that he would do so as well, simply by running the program manually. > Searle asserts that there is no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program, step-by-step, producing behavior that is then interpreted by the user as demonstrating intelligent conversation. However, Searle himself would not be able to understand the conversation. ("I don't speak a word of Chinese," he points out.) Therefore, he argues, it follows that the computer would not be able to understand the conversation either. > Searle argues that, without "understanding" (or "intentionality"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that the "strong AI" hypothesis is false. https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room

masswerk 4y ago
Well, this, the Chinese Room, is still pretty much a behavioristic work-around (as it is still attempting to argue without any reference to internal states.) Even, if we don't (clearly) understand what "understanding" means, or, at least, aren't able to provide a sane definition, we do know about the semantics of the term and the kind of connotations that come with it. Like a reflexive component. (Which wasn't much of a problem in the age of behaviorism, as this had to be ignored by requirement anyway. If there is no acknowledged difference between a human and a pigeon, what is the problem with computers, as far as the model is concerned?) So we do have a notion of the semantic field and its implications. And these are, well, quite disastrous for this purpose.
- masswerk 4y ago
  P.S.: In non-behavoristic terms: The term "understanding" is linked not only to the internal semantic field and its structure, as maintained by an individual, but also to its state of mind. We crucially expect the state of mind to be altered by an "act" of understanding. (Commonly expressed by an utterance like "aha!", which asserts this change in state of mind.) So, do we have to consider a state of mind (of some complexity) or a hypothesis of this, as in a theory of mind, in order to predict the productions of GPT-3, or does this further our hopes in a more precise prediction? Do we have to consider such a theory of mind in order to understand it on our side? Probably not.