On Sat, Aug 9, 2008 at 5:35 PM, Charles Hixson <[EMAIL PROTECTED]> wrote: > Jim Bromer wrote: >> As far as I can tell, the idea of making statistical calculation about >> what we don't know is only relevant for three conditions. >> The accuracy of the calculation is not significant. >> The evaluation is near 1 or 0. >> The problem of what is not known is clearly within a generalization >> category and a measurement of the uncertainty is also made within a >> generalization category valid for the other generalization category. >> >> But we can make choices about things that are not known based on opinion.
> > Could you define "opinion" in an operational manner, i.e. in such a way that > it was specified whether a particular structure in a database satisfied that > or not? Or a particular logical operation? > Otherwise I am forced to consider opinion as a conflation of probability > estimates and desirability evaluations. This doesn't seem consistent with > your assertion (i.e., if you intended opinion to be so defined, you wouldn't > have responded in that way), but I have no other meaning for it. I could define the difference between opinion and general knowledge with abstract terms but it is extremely difficult to come up with an operational principle that could be used to reliably detect opinion. This is true when dealing with human opinion so why wouldn't it be true when dealing with AI opinion? Most facts are supported by opinion and most opinions are supported by some facts, although the connection may be somewhat difficult to see in some cases. Your opinion that opinion itself can be defined, 'as a conflation of probability estimates and desirability evaluations,' avoids the difficulty of the definition by making it dependent on two concepts neither of which are necessary and both of which would require some kind of arbitrary evaluation system for most cases. Opinion can be derived without probability or an evaluation of desirability. And opinion is not necessarily dependent on some kind of weighted system of numerical measurement. But while I cannot provide an operational definition that is absolutely reliable for all cases, I can begin to discuss it as if it were still an open question (as opposed to an arbitrary definition). Opinion will be mixed with facts in almost all cases. One can only start to distinguish them by devising standard systems that attempt to separate and categorize them. This system is going to be imperfect just as it is in everyday life. This idea of creating standard methods that can be used for general classes of kinds of things is significant because it is related to the problem of 'grounding' opinions or theories onto 'observable events'. My imaginary AI program would use categorical reasoning but it would also be able to learn. I would use text-based IO at first. So in this sense 'grounding' would have to based on textual interactions. This kind of grounding would be weaker than the grounding that humans are capable of, but people are limited too, in their own way. Since opinion and fact seem to be gnarly and intertwined, I feel that the use of standard methods to examine the problem are necessary. Why 'standard methods'? Because standard methods would be established only after passing a series of tests to demonstrate the kind of reliability that would be desirable for the kinds of problems that they would be applied to. This kind of reliability could be measurable in some cases, but measurability is not a necessary aspect of detecting opinion. And another aspect of developing standard methods is that by relying on highly reliable components and by narrowing the variations of individual interpretation, these standard methods could act as a base for methods of grounding. Ironically, this helps to bond individual opinions from human society about what is fact and what is not, but this process is helpful as long as it is not totalitarian. So an opinion that contains some truth, but cannot attain a standard of reliability based on the use of established standard methods to examine similar problems would have to continue to be considered as an opinion. Of course, a theory might only be considered to be an opinion after the thinking device is exposed to an alternative theory that explains some reference data in another way. This problem is directly related to the greater problem of artificial judgment the lack of elementary methods that could act as the 'independent variables' to produce higher AI. That means that I think the problem is AI-Complete (to use an interesting phrase that someone in the group has used). Jim Bromer ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
