DRogers@SUMEX-AIM.ARPA@sri-unix.UUCP (09/14/83)
From: David Rogers <DRogers@SUMEX-AIM.ARPA> [This continues a discussion on Human-Nets. My original statement, printed below, was shot down by several people. Individuals certainly derive satisfaction from hobbies at which they will never excel. It would take much of the fun out of my life, however, if I could not even imagine excelling at anything because cybernetic life had surpassed humans in every way. -- KIL] From: Ken Laws <Laws@SRI-AI.ARPA> Life will get even worse if AI succeeds in automating true creativity. What point would there be in learning to paint, write, etc., if your home computer could knock out more artistic creations than you could ever hope to master? I was rather surprised that this suggestion was taken so quickly as it stands. Most people in AI believe that we will someday create an "intelligent" machine, but Ken's claim seems to go beyond that; "automating true creativity" seems to be saying that we can create not just intelligent, but "genius" systems, at will. The automation of genius is a more sticky claim in my mind. For example, if we create an intelligent system, do we make it a genius system by just turning up the speed or increasing its memory? That"s like saying a painter could become Rembrandt if he/she just painted 1000 times more. More likely is that the wrong (or uncreative) ideas would simply pour out faster, or be remembered longer. Turning up the speed of the early blind-search chess programs made them marginally better players, but no more creative. Or let's say we stumble onto the creation of some genius system, call it "Einstein". Do we get all of the new genius systems we need by merely duplicating "Einstein", something impossible to do with human systems? Again, we hit a dead end... "Einstein" will only be useful in a small domain of creativity, and will never be a Bach or a Rembrandt no matter how many we clone. Even more discouraging, if we xerox off 1000 of our "Einstein" systems, do we get 1000 times the creative ideas? Probably not; we will cover the range of "Einstein's" potential creativity better, but that's it. Even a genius has only a range of creativity. What is it about genius systems that makes them so intractable? If we will someday create intelligent systems consistently and reliably, what stands in the way of creating genius systems on demand? I would suggest that statistics get in our way here; that genius systems cannot be created out of dust, but that every once in a while, an intelligent system has the proper conditioning and evolves into a genius system. In this light, the number of genius systems possible depends on the pool of intelligent systems that are available as substrate. In short, while I feel we will be able to create intelligent systems, we will not be able to directly construct superintelligent ones. While there will be advantages in duplicating, speeding up, or otherwise manipulating a genius system once created, the process of creating one will remain maddeningly elusive. David Rogers DRogers@SUMEX-AIM.ARPA [I would like to stake out a middle ground: creative systems. We will certainly have intelligent systems, and we will certainly have trouble devising genius systems. (Genius in human terms: I don't want to get into whether an AI program can be >>sui generis<< if we can produce a thousand variations of it before breakfast.) A [scientific] genius is someone who develops an idea for which there is, or at least seems to be, no precedent. Creativity, however, can exist in a lesser being. Forget Picasso, just consider an ordinary artist who sees a new style of bold, imaginative painting. The artist has certain inborn or learned measures of artistic merit: color harmony, representational accuracy, vividness, brush technique, etc. He evaluates the new painting and finds that it exists in a part of his artistic "parameter space" that he has never explored. He is excited, and carefully studies the painting for clues as to the techniques that were used. He hypothesizes rules for creating similar visual effects, trys them out, modifies them, iterates, adds additional constraints (yes, but can I do it with just rectangles ...), etc. This is creativity. Nothing that I have said above precludes our artist from being a machine. Another example, which I believe I heard from a recent Stanford Ph.D. (sorry, can't remember who): consider Solomon's famous decision. Everyone knows that a dispute over property can often be settled by dividing the property, providing that the value of the property is not destroyed by the act of division. Solomon's creative decision involved the realization (at least, we hope he realized it) that in a particular case, if the rule was implemented in a particular theatrical manner, the precondition could be ignored and the rule would still achieve its goal. We can then imagine Solomon to be a rule-based system with a metasystem that is constantly checking for generalizations, specializations, and heuristic shortcuts to the normal rule sequences. I think that Doug Lenat's EURISKO program has something of this flavor, as do other learning programs. In the limit, we can imagine a system with nearly infinite computing power that builds models of its environment in its memory. It carries out experiments on this model, and verifies the experiments by carrying them out in the real world when it can. It can solve ordinary problems through various applicable rule invocations, unifications, planning, etc. Problems requiring creativity can often be solved by applying inappropriate rules and techniques (i.e., violating their preconditions) just to see what will happen -- sometimes it will turn out that the preconditions were unnecessarily strict. [The system I have just described is a fair approximation to a human -- or even to a monkey, dog, or elephant.] True genius in such a system would require that it construct new paradigms of thought and problem solving. This will be much more difficult, but I don't doubt that we and our cybernetic offspring will even be able to construct such progeny someday. -- Ken Laws ]
POURNE%MIT-MC@sri-unix.UUCP (01/11/84)
From: Jerry E. Pournelle <POURNE @ MIT-MC> I should have thought that if you can make a machine more or less intelligent; and make another machine ABLE TO RECOGNIZE GENIUS (it need not itself be able to "be" or "have" genius) then the "genius machine " problem is probably solved: have the somewhat intelligent one generate lots of ideas, with random factors thrown in, and have the second "recognizing" machine judge the products. Obviously they could be combined into one machine.
andree@uokvax.UUCP (01/24/84)
#R:sri-arpa:-1568100:uokvax:900008:000:548 uokvax!andree Jan 22 00:59:00 1984 This sounds very similar to the "Truth Recognizers" in Hofstadter's and Rucker's writing - machines that will tell if an arbitrary statement (or theorem) is true. Hook them up to a statement/theorem generator, and you can find out if any statement/theorom is true by waiting long enough. The problem is, defining "true" is a hard problem - rucker claims you can't do it in any finite amount of space/time. [I tend to believe him.] Something tells me "genious" will suffer from the same problem. Something to do with context-sensitivity... <mike
simon@psuvax.UUCP (Janos Simon) (01/27/84)
It would be useful if people thought or learned something about subjects they write about. Theorem-proving (as in proving any theorem of a sufficiently string theory) is impossible - it is not recursive for theories as weak as Peano Arithmetic, it cannot be done in less than exponential time for almost trivial decidable theories (like 1st order theory of real addition), and it is co-NP complete (and therefore probably not doable in polynomial time) even for the propositional calculus. Obviously this has nothing to do with context sensitivity. What is "genious"? *Down with intellectual pollution!* js
sew@minn-ua.UUCP (01/30/84)
#R:sri-arpa:-1568100:minn-ua:2300001:000:756 minn-ua!sew Jan 30 10:30:00 1984 An article in Nature (June 83? Also a few months later in Psychology Today) suggested that mammal brains might use a related approach to help determine reality. The idea is that when mammals dream, the "lower" brain is feeding random signals into the "higher" brain and whatever responds is inhibited. Thus many false connections would get broken, along with some infrequently reinforced good connections. The concept seems to be simple. If a connection responds to a random signal, it is probably a random connection. Remove random connections what what will be left is connections which are part of patterns. "To make a statue of an elephant, remove everything which does not look like an elephant." Scot E. Wilcoxon ...ihnp4!umn-cs!minn-ua!sew
andree@uokvax.UUCP (01/31/84)
#R:sri-arpa:-1568100:uokvax:900010:000:653 uokvax!andree Jan 29 13:53:00 1984 Sorry, js@psuvax, but I DO know something about what I spoke, even if I do have trouble typing. I am aware that theorom-proving machines are impossible. It's also fairly obvious that they would use lots of time and space. However, I didn't even MENTION them. I talked about two flavors of machine. One generated well-formed strings, and the other said whether they were true or not. I didn't say either machine proved them. My point was that the second of these machines is also impossible, and is closely related to Jerry's genius finding machines. [I assume that any statement containing genius is true.] Down with replying without reading! <mike