Xref: utzoo comp.ai:6140 sci.philosophy.tech:2177 Path: utzoo!utgpu!jarvis.csri.toronto.edu!cs.utexas.edu!swrinde!zaphod.mps.ohio-state.edu!mips!apple!amdahl!kp From: kp@uts.amdahl.com (Ken Presting) Newsgroups: comp.ai,sci.philosophy.tech Subject: Re: Another letter to the New York Review Summary: On Determinism, Empiricism, and Observation Keywords: Penrose, Moravec Message-ID: Date: 2 Mar 90 23:20:33 GMT References: <18883@bcsaic.UUCP> <1589@skye.ed.ac.uk> <11488@venera.UUCP> <1754@skye.ed.ac.uk> <90Feb15.231415est.6212@neat.cs.toronto.edu> <2al902Zg8bnn01@amdahl.uts.amdahl.com> <3750@uceng.UC.EDU> Reply-To: kp@amdahl.uts.amdahl.com (Ken Presting) Organization: Amdahl Corporation, Sunnyvale CA Lines: 136 In article <3750@uceng.UC.EDU> dmocsny@uceng.UC.EDU (daniel mocsny) writes: >In article <2al902Zg8bnn01@amdahl.uts.amdahl.com> kp@amdahl.uts.amdahl.com (Ken Presting) writes: >> . . . If nobody >>noticed and described "that certain something", then no way can we build >>it into anything. But if we can build it, we can also program it. > >I disagree. The analog builders might "get lucky," and be able to >reproduce their success even though they can't explicate any >programmable underlying mechanism. . . . > . . . (Thumb through the _Chemical Engineer's >Handbook_ the next time you get bored with determinism. The extent to >which our economy depends on practically uncomputable phenomena is >rather appalling.) Here (and below) I think I can salvage some useful conclusions from my original argument. I had focused on Penrose' arguments, which depend on the possible existence of uncomputable functions in the laws of physics. But I propose a simulation technique which depends on deduction rather than numerical solution of differential equations. The standard logical operation which represents the determinist metaphysical thesis is *deduction*, not computation. Of course, computers are entirely adequate to implement deductive systems, by the Church-Turing thesis. If there is any way at all to predict a future state from a past state, computers can do it as well as any mere physicist. Using deduction doesn't really change the power of the simulator, it just puts the focus on a different issue. I do think this eliminates any concerns with the computability of the functions which are used to state the laws, given that the laws are stated in a complete logic. Recursive enumerability is sufficient, supposing that real-time performance is not required, or that machines with non- deterministic performance exist (such as associative memory). The computability or uncomputability of every other process is irrelevant. Even if we lack a theoretical account of a measured phenomenon, so that we are unable to deduce our measurements from a more general theory, we still have the expedient of adding the tabulated data points themselves to the data base of a simulation. One point I am urging against Penrose is that whatever the scientists can state about the phenomenon we want to model, AI workers can implement, because deduction itself is a computable process. Penrose goes on to suppose that non-deductive processes have a role in mathematics and science, but that is a different subject, with huge controversies of its own. Hypothesis formation is non-deductive, but you need deductions from the hypothesis to get testable predictions, and it's the test of the hypothesis that gets published. The only relevant non-deductive process I can think of is measurement, which causes no problems for my argument. Quite the contrary: >I concede that the likely complexity of an intelligent machine greatly >lowers the probability that a dirty-handed empiricist could build one >by accident. But I don't think empiricism and theory have to be so >nicely interchangeable as you imply, especially in the short run. This is why I made a very big deal out of *measuring* the robot. In engineering, theory most often has a background role if anything, and need have no role at all. As you observe, the bang is no smaller for being unexplainable. But a measuring device without a theoretical explanation is no measuring device at all - it's just another mysterious correlation! This point is crucial to my argument. Penrose can speculate at will about possible laws. But if he is presented with a robot, and wants to criticize its behavior, he'll need some sort of observation on which to base the criticism. If he knows how to make the measurement, then there is a way to simulate the same effect. This dependency of measurement on theory holds pretty well for complex measuring devices, but stops irritatingly short of providing a rationalist reduction of empiricism (it irritates me, anyway). And I should grant right away that a device (X-rays are a good example) can make useful measurements before it's explained by the theorists, once the experimentalists have a resonably thorough description of its performance. But a new form of measurement is not going to topple any old theories until it's explained by a new theory itself. (Via E-mail, Dan made further comments, which I'll address indirectly here. btw, Dan, that letter made my day!) It is possible to finesse the actuator issue by restricting the observer in a Turing test to a limited interface with the simulator. Dan suggests using the simulator to drive a light and sound source, thus reproducing most of an observer's experience of interacting with a person. This would be like substituting a "virtual reality" environment for Turing's original teletype. I have considered an even more radically restricted interface - present the "observer" with two sets of descriptions, one set generated by the simulator, and the other set recorded by hand by technicians watching, measuring, X-raying, etc a live human. The observer then must decide which is the description of the real person versus the output of the simulator. The observer is allowed to specify any situation, any measurement, any dialogue, to his heart's content. The technicians who report on the real human are required to couch their reports in the same notation as used by the simulator. My approach suffers severely from the "simulations don't fly" problem, which is why I stayed with the actuators. But any proposal for a success condition for AI which involves restricting the observations allowed to the judges has a deeper problem. In order to claim that "observations of types X, Y ... provide adequate information to determine the presence of thought in the observed system" it is necessary to show that other types of observations are irrelevant. For example, the familiar Turing test says "Observations of language behavior are sufficient...". This is OK if you can show that (at least some aspect of) thought is independent of all the other things people do, and all the other attributes they posess. But you *can't* do that until you have some independently motivated account of what thought is. I don't think AI is going to get the amateur speculators off its back (and out of the general press) until there is a good reason for saying "We don't care that our duck don't waddle. It's STILL a duck". Or else settle for Weak AI. >In the long run, who knows? Can any phenomenon be so truly uncomputable >that no logical process could behave equivalently (if not exactly)? >The presence of such phenomena would seem to imply a universe where >theory is of no value at all. I hope we all agree that's not true... :-) Agreed! I'd emphasize deduction as the crucial logical process, rather than computation. And we have to be quite forgiving wrt the time scale of the simulation (cf Dunning's comments on chaotic systems), or else focus on the finiteness of the equivalency-checking process. I have a hard time believing that we could ever convince ourselves that we have discovered an absolutely non-simulable process. I bet that if a candidate ever arose, there'd be lots of talk about "hidden variables" or some such nonsense... :-} >Dan Mocsny >dmocsny@uceng.uc.edu Thanks again for a very stimulating article. Ken Presting