16 karma · joined May 3, 2015
I still assert that a relative black box will lie at the core of any "strong" AI.
This might be intuitive if A weighted each N of some class equally, and N>>Kevin for each _class_, but observation indicates this is not the case. Also certain N tend to be overweighted regardless of the knowledge class to which they belong.
IRL I have observed that B can work around A's bias by framing knowledge expressed as a question.
> Sounds like narcissism.
I think this is a common bias with implications in the "machine consciousness" question, but I'll have to wait ton finish that point. Look for an edit.
I believe that the primary issue is the formation of heuristics about knowledge sources. e.g. Person B provides person A with knowledge of class "low-value in domain D" N times and knowledge of class "higher-value in domain D" K times in some time period T. At some time T_n A internalizes a heuristic about Person B's overall knowledge set. Depending on internal characteristics of A, all subsequent knowledge expressed by B may be ignored.
This is problematic. Not only does A ignore that the difference set of A and B's knowledge (even in D) is likely nonzero, it effectively assumes that A's knowledge is a superset of B, and that A's rate of knowledge aquisition is greater than that of B for all T. It ignores that A and B are dynamical systems.
In my opinion, formation of these kinds of heuristics and being dismissive of knowledge is a sign of intellectual weakness. It's akin to internalizing knowledge to the point of belief and belief is bounding.