Reasoning, problem-solving, symbolic language, planning—these faculties are fundamental to virtually all of our individual and societal accomplishments. At the heart of them all lies cognitive control. Psychologists and neuroscientists refer to cognitive control, or “controlled processing,” as the ability to flexibly adapt behavior to rapidly changing circumstances and to make decisions that best serve long-term interests over more immediate rewards.
Cognitive control underlies our striking technological achievements over an equally striking range of domains, from agriculture and housing to medicine, transportation, communication and large-scale economies. Given all these positive outcomes, one might expect that expressing cognitive control should inexorably improve with time—that more cognitive control leads to more progress and the enduring success of our species.
Sadly, history seems to indicate the contrary. Around the world, tourists visit the ruins of great structures of sophisticated societies. Anthropological evidence suggests that many of these societies collapsed precisely because of the innovations that accompanied their sophistication: These innovations relied on cognitive control, but they were used ill-advisedly, reflecting a failure in the use of control. It suggests a pattern of increased control followed by collective short-sightedness and irrationality. This pattern is not confined to the distant past. Some have argued that humans are now experiencing such a societal backslide.
In a paper forthcoming in Psychological Review, we set out to understand why control might follow this proliferation-then-collapse pattern. One assumption of our model is that controlled processing is costly but leads to smarter decisions with better long-run payoffs. Using principles of cognitive psychology, game theory, and population dynamics, we generated a series of formal mathematical analyses that examine the competition between agents that vary in their extent of controlled processing. The agents interact in an environment that is continually being modified by the agents’ use of controlled versus non-controlled processing, altering the benefits of control. Our analyses examined the change over time in both the population’s level of controlled processing and the state of the environment. This allowed us to identify conditions that favor the spread versus decline of cognitive control.
The results highlight the downsides of controlled processing. Within a population, controlled processing may—rather than ensuring undeterred progress—usher in short-sighted, irrational, and detrimental behavior, ultimately leading to population collapse. This is because the innovations produced by controlled processing benefit everyone, even those who do not act with control. Thus, by making non-controlled agents better off, these innovations erode the initial advantage of controlled behavior. This results in the demise of control and the rise of lack-of-control. In turn, this eventually leads to a return to poor decision making and the breakdown of the welfare-enhancing innovations, possibly accelerated and exacerbated by the presence of the enabling technologies themselves. Our models therefore help to explain societal cycles whereby periods of rationality and forethought are followed by plunges back into irrationality and short-sightedness.
Anthropological evidence suggests that many of these societies collapsed precisely because of the innovations that accompanied their sophistication.
To illustrate this dynamic, consider the scourge of pollution in the mid-twentieth century. Pollution engendered efforts to develop both physical and social technologies (including regulatory legislation) to mitigate the problem—efforts that surely relied on the exercise of cognitive control. Those efforts notably improved the environment, which has benefited everyone. However, that very improvement has obscured the importance of sustained control-based efforts. In its place emerged a trend towards returning to technologies that caused the problem in the first place. This illustrates the basic dynamic of our models: Controlled processing produces conditions in which non-controlled behaviors can re-emerge and eventually dominate. Similar dynamics may exist in a range of other relevant domains, including trade, education, and financial regulation.
The situation may be even more extreme when there is a temptation to abuse these innovations for short-term gain—a temptation that requires control to resist. For example, antibiotics, which undoubtedly required controlled processing to develop, offer a short-term benefit to those lacking in control. But in the long run, such injudiciousness breeds bacterial resistance, which undermines the benefits antibiotics hold for everyone. Energy, agriculture, and weaponry provide more examples in which technological developments rely on control but their use and, critically, their abuse do not. This sets the stage for the downfall of control, which comes at a great cost to our wellbeing as a society and possibly even a species.
Being aware of these dynamics is a critical first step towards mitigating them. The task of designing interventions that support controlled processing and avoid societal collapse falls to policy experts, not us. But we hope that the formal mathematical characterization our models provide will offer a useful framework upon which to build. For example, the models suggest critical dimensions that may play a role in destabilization, such how costly it is to exert control and how quickly innovations and technologies are degraded when used injudiciously. To find solutions that promote the stability of our society and species, it is critical that social scientists and policymakers work together to explore the population dynamics of cognitive control and their implications for social welfare.
