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The Philosophical Perspective | 756 comments | Create New Account
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The Philosophical Perspective
Authored by: Anonymous on Sunday, July 22 2012 @ 11:10 PM EDT
You're talking about provenance (colour), but that's irrelevant to my point, which is that the man in the chinese room (or rather, the system of man + rules) is indistinguishable from another system (i.e. a native speaker) whom you concede *does* process semantics. You state that some of the rules are non-algorithmic, presumably to argue that a computer in the room can't duplicate those rules, ergo can never process semantics, but in fact "discretion" is rather easy to mimic using weighted probabilities (which can take into account consistency with past choices, and various other heuristics). So I can write an algorithmic program to give to a computer inside the chinese room, and you won't know whether you're talking to a computer or to a human native speaker of Chinese.

The real reason the man-in-the-room scenario is difficult is not that the man (or computer) is incapable of learning semantics, it's that he's deprived of learning opportunities. The rulebook might tell him that an acceptable response to [the chinese characters meaning] "I love you" is "I love you too" and that a frequent response to "I hate you" is "I hate you too", but it would be very difficult to know the difference between love and hate. In contrast, a Chinese child would be afforded the opportunity to associate each of those phrases with very different facial expressions, tone of voice, etc. Give a computer (with suitable hardware e.g. cameras, microphones) those same clues, and it could "do semantics" just as well as any child.

The man-in-the-room scenario may sound a little like Plato's Cave or its more recent mind-trapped-inside-the-skull variations (including the Matrix movies) but it's different. Those are about whether a mind can trust its inputs, and therefore whether a philosopher can ever be confident of what's "real". The man-in-the-room scenario is more like the dilemma of Egyptologists before the Rosetta stone. The man in the room may never learn Chinese semantics, because the scenario is designed to prevent him from ever encountering semantically useful information. It says nothing at all about whether computers can learn semantics, it just says that computers can't learn semantics if you don't give them any semantic information.

Whether the man inside the room has any semantic information is not the same question as whether the system of man+rules has any semantic information. The rules would encode some associations from which you could deduce a few things - certain words appearing together frequently could mean they are semantically related, for example. If you knew some grammatical principles from other languages, you might be able to guess which words were verbs and which were conjunctions. Also, to be convincing, the rules would have to contain some sort of personality model, which might be mined for a few more crumbs. But in a stringent application of the Chinese Room scenario, the rules could be carefully constructed to exclude any information about whether a certain Chinese character means "love" or "hate", "but" or "and", "yes" or "no".

Thus the system of man + rules clearly does not "know" Chinese semantics, at least not more than fractionally. I'm changing my mind: I now see why it's fair to say that the Chinese Room system (man PLUS rules) is faking it, not really "doing semantics", even if you can't tell the difference by looking at the system's output. But the Chinese Room example has nothing to do with the capabilities of computers - it's simply a very artificial situation. Limit a computer's input, and there's a limit to what it can learn.

Your previous post presumes that discretion was in the rules; if it's in the rules it's in the system, thus the system can "do discretion" which is not a terribly interesting result to me.

You seem to think the system can only work with a man (not a computer) inside the room, because discretion is something computers can't do. Maybe I'll think about this some more and conclude that computers can only do fake discretion, or rather maybe I'll conclude that the difference between fake discretion and real discretion is meaningful in some way. Putting that aside for now, I think you'll concede that fake discretion is good enough to get the system to work convincingly.

This is getting far afield for your article, and I'm not sure how much of this is responsive to your last post, but it's interesting.

So to start heading back to where we started: the Chinese Room system (man plus rules) implements ersatz semantics, whoe outputs happen to be indistinguishable from real semantics. You could, indisputably, write a computer program that did ersatz semantics; for example a program could translate between human languages without having any semantic references except from one language to the other. (I've written part of something similar myself; come to think of it, many computer-science students have written something similar: a compiler. It never occured to me that this was something less than real semantics.) I still hold that an actual computer system (including programming and training) is capable of real semantics.

You may object that computers are never given semantic information, just bits which it must process algorithmically. I respond that the human brain is never given semantic information either, just neurotransmitters and action potentials. (Plato's Cave...) It's possible that it's processing these signals in some non-algorithmic way, but I don't see any evidence for that. Semantics aren't all that special, just an association between words and "meaning". "Meaning" is a funny word, since meanings can be imaginary ("unicorn", "leprechaun"), proving that many meanings are simply associations with other words in the language, but ultimately the idea of "semantics" is that some meanings are references to information not contained in syntax. Supply that information to a well-programmed computer, and (real, not ersatz) semantics are a piece of cake.

Totally unrelated question: suppose a computer program does not explicitly give a procedure for accomplishing a task; instead, the program is an algorithm for learning, and to apply it to a specific task, you need a specific set of training data. (Or, the program is a process for applying a learned model, and to apply it to a specific task, you need a data file containing a specific model.) Under US law, can you patent the program+data combination for each specific task?

[ Reply to This | Parent | # ]

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