How Intractability Spans the Cognitive and Evolutionary Levels of Explanation

The challenge of explaining how cognition can be tractably realized is widely recognized. Classical rationality is thought to be intractable due to its assumptions of optimization and/or domain generality, and proposed solutions therefore drop one or both of these assumptions. We consider three such proposals: Resource-Rationality, the Adaptive Toolbox theory, and Massive Modularity. All three seek to ensure tractability of cognition by shifting part of the explanation from the cognitive to the evolutionary level: evolution is responsible for producing the tractable architecture. We consider the three proposals and show that, in each case, the intractability challenge is not thereby resolved, but only relocated from the cognitive level to the evolutionary level. We explain how non-classical accounts do not currently have the upper hand on the new playing field.

The Ecological Rationality of Situations

The study of situations involves asking how people behave in particular environmental settings, often in terms of their individual personality differences. The ecological rationality research program explains people’s behavior in terms of the specific decision-making tools they select and use from their mind’s adaptive toolbox when faced with specific types of environment structure. These two approaches can be integrated to provide a more precise mapping from features of situation structure to decision heuristics used and behavioral outcomes. This chapter presents three examples illustrating research on ecological rationality and its foundations, along with initial directions for incorporating it into an integrated situation theory.

A cue for rational reasoning: Introducing a reference point in cognitive reflection tasks

The dual process framework posits that we reason using the quick System 1, and the deliberate System 2, both of which are part of our “adaptive toolbox”. The Cognitive Reflection Test (CRT) estimates which system was used to solve a reasoning problem. Usually, the CRT tasks are solved incorrectly by using System 1, and correctly through System 2. We have applied the reference point hypothesis to the tasks of the CRT and proposed that this change would facilitate the switch between systems, resulting in better performance on the version of the test with a reference point, compared to the CRT without one. The results confirmed our assumptions, as evidenced by a generally higher score on the CRT with a reference point, albeit with different effects between items.

Optimizing the Psychological Benefits of Choice

This paper suggests that the paradox of choice can be resolved in game environments by promoting heuristics-based decision-making, thereby maintaining player freedom while also avoiding the potential negative consequences of excessive deliberation. To do this, the informational cues relevant to such decisions must be made transparent, allowing players to employ fast and frugal tools from the brain’s adaptive toolbox to make the same optimal choices that they might otherwise make after extended deliberation. Developers can design for such transparency not only by creating choice experiences in which options can be assessed and compared through clear metrics and attributes, but also by designing social systems in which the choices and successes of others can be easily identified and used for informing one’s own future decisions.