Cyclical Population Dynamics of Automatic Versus Controlled Processing: An Evolutionary Pendulum

David G. Rand

doi:10.1037/rev0000079

Cyclical Population Dynamics of Automatic Versus Controlled Processing: An Evolutionary Pendulum

2017-10-01

27

OA

AI

DOI：10.1037/rev0000079

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Psychologists, neuroscientists, and economists often conceptualize decisions as arising from processes that lie along a continuum from automatic (i.e., hardwired or overlearned, but relatively inflexible) to controlled (less efficient and effortful, but more flexible). Control is central to human cognition, and plays a key role in our ability to modify the world to suit our needs. Given its advantages, reliance on controlled processing may seem predestined to increase within the population over time. Here, we examine whether this is so by introducing an evolutionary game theoretic model of agents that vary in their use of automatic versus controlled processes, and in which cognitive processing modifies the environment in which the agents interact. We find that, under a wide range of parameters and model assumptions, cycles emerge in which the prevalence of each type of processing in the population oscillates between 2 extremes. Rather than inexorably increasing, the emergence of control often creates conditions that lead to its own demise by allowing automaticity to also flourish, thereby undermining the progress made by the initial emergence of controlled processing. We speculate that this observation may have relevance for understanding similar cycles across human history, and may lend insight into some of the circumstances and challenges currently faced by our species.

Keyword:

automaticity

cognitive control

cognitive processing

evolution

mathematical modeling

Cyclical Population Dynamics of Automatic Versus Controlled Processing: An Evolutionary Pendulum

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