Simplicity and Cognitive Models

Simplicity is as intuitive as it is popular. ¹ Simple explanations are easier to understand, simple formulae are easier to use, and when a single equation describes radically different systems, the world appears to be united through simplification. Comparative cognition is no stranger to erring on the side of simplicity, as can be seen in the long-standing debate about chimpanzee mindreading abilities. ² One of the most common heuristics in experimental comparative cognition advises that, all else being equal, one ought to prefer the simplest explanation of animal behavior: one that interprets observed behavior in terms of the simplest cognitive mechanism or ability. Unfortunately, the theoretical basis for this “simplicity heuristic” has not been adequately established. ³ In this chapter, I examine how the simplicity heuristic adversely affects a relatively new tool in experimental comparative cognition: cognitive models. It does so, I argue, by directing intellectual resources into the development and refinement of putatively simple cognitive models at the expense of putatively more complex ones, which in turn directs experimenters to develop tests to rule out these simple models. The result is a state of affairs wherein putatively simple models appear more successful than less simple ones not in virtue of their epistemic superiority, but, rather, because a disproportionate amount of resources have been devoted to their development and evaluation. This has, in turn, adversely affected the design and direction of behavioral experimentation aimed at describing cognitive processes in animals, shutting down alternative research programs. I conclude that moving toward a more quantitative science of animal minds is likely to improve the explanatory and predictive power of animal cognition research, but only if these models do not fall prey to existing biases such as the simplicity heuristic.