– by Megan Bishop & Brian Lerch
Large-scale, advanced cooperative action that transverses familial lines is uniquely, exceptionally human. It lies in the foundation of our economic and political infrastructure, our corporate workflow, the small talk we make with the grocery cashier –evidence of our cooperative, pro-social nature is everywhere. Put simply, the evolution of human cooperation has bound us all to each other in a way that far transcends anything seen elsewhere in the animal kingdom. Such an incredible phenomenon begs a multitude of questions, but upon beginning the work leading up to my recent publication, The influence of language upon the evolution of cooperation, I became particularly enthralled by one: how?
Pursuing this broad question led me to another uniquely, exceptionally human development: advanced spoken language proficiency. The evolution of advanced human cooperation and language have been argued to have a reciprocal relationship, where the evolution of one drives the evolution of the other and vice versa. While the existence of large-scale cooperation assumes an ability to coordinate via complex language systems, few mathematical models examined the ways that language promotes cooperative action, despite the utility of mathematical models for analyzing how evolutionary mechanisms align with argued verbal logic.
Human cooperation has important roots in collaborative foraging, which is well modeled by a stag hunt game. Here, a group of early human foragers are presented with two options: individually hunt a hare with a guaranteed fitness benefit or risk the opportunity cost of the hare to collaborate with others in pursuit of hunting a stag. Upon the successful hunt of the stag, the fitness payoff would be evenly split amongst the group, with a much higher payoff than the hare. However, this depends on successful cooperation. Without successful cooperation, the stag hunt fails, leaving cooperators without the fitness benefit from the hare or the stag. Given the important evolutionary origins of collective human foraging, we build upon an existing stag-hunt model and include language in three various mechanisms to analyze its implications on early human cooperation.
First, we analyze an “enhancement” mechanism of language, where we assume better language systems allow for more complex coordination among cooperators, allowing them to pursue larger game with a greater fitness payoff. Here, our findings align with verbal arguments: more proficient language always makes conditions more favorable for cooperation. In our model, cooperation steadily evolves when language proficiency is better. However, this is limited by the proportion of cooperators in the population. Regardless of language proficiency, language cannot promote the evolution of cooperation with too few cooperators present.
Next, we studied an “assortment” mechanism of language, where we assume better language systems allow cooperators to communicate with, and therefore identify, other cooperators. In other words, with better language proficiencies, cooperators are more likely to join groups with other cooperators. Like our “enhancement” mechanism, our findings align with verbal arguments that better languages always favor the evolution of cooperation when enough cooperators are present in the population. However, this “assortment” mechanism is especially beneficial for cooperation when there is a high frequency of cooperators, leading to larger benefits of cooperation than is seen in the “enhancement” mechanism.
Finally, and most interestingly, is our “threshold” mechanism. Here, we assume better language proficiencies allow humans to achieve successful cooperation with fewer cooperators participating. This mechanism challenges the idea that better language proficiencies always favor the evolution of cooperation. We find that while better languages allow cooperation to evolve in populations with fewer cooperators, the overall fitness of individual cooperators decreases with better language. Upon reflection, this makes sense. Even when a smaller group can establish advanced complex coordination with improved communication, more defectors are able to “free-ride” off of the cooperators’ payoffs.
So, I answer my question of how? with an answer that frustrates answer-seeking scientists like myself, yet is universally true about our world: it’s complicated. It is likely a combination of these mechanisms that has influenced the evolution of human cooperation. For instance, perhaps the benefits of our assortment mechanism were slowed by the effects of our “threshold” mechanism. However, certain environments might not allow for the existence of one or more mechanisms, such as an environment with tightly constrained group membership would not enable positive assortment. The nuance between language and cooperation depends greatly on the mechanism of language. This model pokes and probes at our existing understanding and how language influences cooperation, unveiling that there is greater nuance than what is commonly assumed. My hope is that by challenging such a long-standing assumption, the scientific community continues to grow in our study and understanding of the fascinating, unique phenomenon we call human cooperation.
Read the original article: Bishop, M.E., & Lerch, B.A. (2023). The influence of language on the evolution of cooperation. Evolution & Human Behavior, 44(4), 349-358.