Testing evolutionary hypotheses through large-scale behavioral simulations

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Along with the human brain, human cognition is a product of evolution. The complexities of human cognition, both individually and collectively, include sharing information, innovating, and developing complex technologies, institutions and norms. Why and how these aspects of human cognition and behavior came to be is a question that crosses many disciplines, including biology, psychology, linguistics, archaeology and anthropology. It is also an important one, as understanding how various aspects of human cognition and behavior came to be what they are could have implications for engineering artificially intelligent systems, enhancing and augmenting human capabilities, and improving upon societal conditions. Traditionally, the evolution of human cognition has been investigated in either of two ways: 1) through computer simulations of possible evolutionary processes that took place over long periods of time and many generations, or 2) through laboratory experiments that examine the behavior of modern humans to test evolutionary hypotheses about aspects of human cognition. This research project develops an innovative third approach that combines the two existing approaches. In this approach, rather than needing to simulate hypothetical human cognitive processes on a computer, a real human being can complete a relevant task online. This allows for real human cognitive processes to be measured and then incorporated into the computer simulation of evolutionary processes. Each participant will perform a computerized task much like in many cognitive science experiments. To incorporate these real human data into computer simulations of evolutionary processes, each person's data will influence the next iteration of the computer simulation. Specifically, the task given to the next set of participants will be affected by the performance of the participants that preceded them. For example, the nature of the available information for a later set of participants might be altered based on the performance of the earlier set of participants. Across many sets of participants and corresponding iterations of the simulation, hypothetical evolutionary processes can be examined to better understand how genes and culture interacted over time and generations to produce present-day human cognitive capabilities and behaviors. The investigators will use crowdsourcing technology to recruit large numbers of participants, and will explore questions about the evolution of language, how complex learning processes evolved, and how genes and culture interact. The software developed to run these simulations will be distributed freely, making it possible for other researchers and educators to run similar simulations to address a wide range of questions about the evolution of human cognition. A version of the software will also be created for educational purposes to teach students about evolutionary processes.