It is worth noting that the power of representational explanation is not simply some story we tell ourselves and each other sustained by our own (possibly mistaken) views of ourselves. One way to appreciate the power of such explanations is to appreciate them in the context of explaining the behaviors of non-human animals. The literature is filled with such examples. Here are just a few.
Consider the impressive feats of maze learning exhibited by rats. A Morris water maze is filled with water rendered opaque to obscure a platform that will offer a rat a chance to rest without having to tread water. When placed in the maze for a first time, a rat will explore the area and eventually find the platform. When the rat is returned to the starting position, the rat does not repeat the exploratory strategy but instead swims straight to the remembered location of the platform. Apparently, the perceptual inputs gained during the exploration were utilized to compute the straight-line path to the platform. The ratâ€™s behavior is thus explicable in terms of psychological states such as perceptions and memories and computations that operate over them.
Gallistel (1990, The Organization of Learning) describes another such example:
Every day two naturalists go out to a pond where some ducks are overwintering and station themselves about 30 yards apart. Each carries a sack of bread chunks. Each day a randomly chosen one of the naturalists throws a chunk every 5 seconds; the other throws every 10 seconds. After a few days experience with this drill, the ducks divide themselves in proportion to the throwing rates; within 1 minute after the onset of throwing, there are twice as many ducks in front of the naturalist that throws at twice the rate of the other. One day, however, the slower thrower throws chunks twice as big. At first the ducks distribute themselves two to one in favor of the faster thrower, but within 5 minutes they are divided fifty-fifty between the two â€œforaging patches.â€ â€¦ Ducks and other foraging animals can represent rates of return, the number of items per unit time multiplied by the average size of an item.
In both the cases of the rats and the ducks, the ultimate explanation called for is going to require mention of some relatively subtle mechanisms inside of the animals that are sensitive to properties of the environment. To get a feel for what might be called for, contrast the way in which we would explain, on the one hand, the movements of the rat toward the platform or the duck toward the bread and, on the other hand, a rock falling toward the earth. The rockâ€™s movement is explained by a direct appeal to a fundamental force of nature that constitutes the attraction between the respective masses of the earth and the rock. Such a direct appeal to a fundamental force will not explain the ratâ€™s movement to the platform. This is not to say, of course, that something non-physical is transpiring between the rat and the platform. There is of course energy flowing between the two that impacts the rat in ways that ultimately explain its behavior. But unlike the case of the rock, the transference of energy from platform to rat will only have an impact on the ratâ€™s behavior insofar as the rat is able to transduce the information carried by that energy into a code that can be utilized by information processing mechanisms in its central nervous system. Such mechanisms will be able to store information in the form of encoded memories and make comparisons between encoded memories and current sensory input to compute a course of action toward a goal state.
(Adapted from Mandik, Collins, and Vereschagin (in press). “Evolving artificial Minds and Brans“. in Mental States. Vol.1: Evolution, Function, Nature, eds. Andrea C. Schalley and Drew Khlentzos. John Benjamins Publishing Company.)