Explanation in Probabilistic Systems: Is It Feasible? Will It Work?
Marek J. Drużdżel · 2001
. Reasoning within such domains as engineering, science, management, or medicine is traditionally based on formal methods employing probabilistic treatment of uncertainty. It seems natural to base artificial reasoning systems in these domains on the normative foundations of probability theory. Two usual objections to this approach are (1) probabilistic inference is computationally intractable in the worst case, and (2) probability theory is incomprehensible for humans and, hence, probabilistic systems may be hardly usable. The first objection has been addressed effectively in the last decade by a variety of efficient exact and approximate schemes for probabilistic reasoning, applied in several practical systems. In this paper, I review the state of the art with respect to the second objection. First I argue that the observed discrepancies between human and probabilistic reasoning and the anticipated difficulties in building user interfaces are not a good reason for rejecting probabilit...