For his research on emerging experimental methods that combine cognitive-behavioral studies with machine learning algorithms to trace how knowledge is transmitted between people, William (Bill) Thompson is the winner of the 2022 NOMIS & Science Young Explorer Award .
Thompson's prize-winning essay illustrates how understanding the cultural evolution of human cognitive abilities provides insight into how our cognitive algorithms can be shaped by social interactions, supporting the view that sociality and cognitive diversity are central to human intelligence.
The NOMIS Foundation & Science Young Explorer Award recognizes bold early-career researchers who ask fundamental questions at the intersection of the life and social sciences. The winner receives $15,000 and the publication of his or her essay in Science.
"The NOMIS prize aims to highlight interdisciplinary science at the interface between the social and life sciences," said Stella Hurtley, deputy editor at Science. "This year's winning essay by [Thompson] explores how ideas and problem-solving can pass from person to person to perpetuate the 'best' solution in a process, similar to biological evolution of competitively advantageous physical traits."
Since evolution is mostly discussed in the context of biological and physical sciences, there has been less research conducted into the cultural evolution of cognition. There has been a lack of technology and methods for large-scale experiments — but Thompson and collaborators at the University of California Berkeley Experimental Cognition Laboratory have worked to recreate and study these cognitive patterns with the help of online studies and mathematical models.
"Each generation transmits their insights and discoveries to the next generation using language, demonstration, or teaching," Thompson said. "Over time, this creates an evolutionary process: the objects being evolved are not organisms — they are cognitive algorithms; and the mechanisms of transmission are not genes — they are thinking, talking people."
Designing a Cognitive Roadmap
Thompson was inspired by 19th century British biologist William Dallinger's early work on experimental evolution, in which he gradually changed the environment experienced by hundreds of generations of unicellular organisms. With their colleagues, Thompson and his postdoctoral mentor Tom Griffiths worked to apply Dallinger's framework to cognitive science, focusing on cognitive representations.
Creating a new infrastructure to conduct studies in structured experimental populations required years of deep investment of time, resources, and collaboration with teams of software developers to make sure the studies could elicit new ways of thinking from participants, focusing on what makes human intelligence so open-ended and creative.
"The questions I study have to do with how people discover counterintuitive ways of thinking about a problem, and how these discoveries are preserved over generations," said Thompson.
In one example, Thompson described laying down six images in front of a participant and asking them if they could find the hidden order. The cognitive process shaping this decision can then be compared to an algorithm designed to solve sorting problems to analyze its strategies against those from participants, seeking out any discernable patterns.
In another example, participants are presented with a familiar technological tool that is augmented to work differently than expected, to test one's ability to adapt to unexpected or counterintuitive challenges.
The Value of Generational Wisdom
The results from Thompson's studies showed that participants were excellent at adapting to new situations. This was especially true when they had the opportunity to build on the knowledge discovered by those who took part in the experiment before them, representing the value of accumulated generational knowledge.
"This study of human problem-solving abilities showed how powerfully our cognitive algorithms can be shaped by social learning, shedding light on processes that occur in all societies and cultures," Thompson explained.
These insights further serve the idea that complex human cognitive functions such as language and theory of mind arise not just from the neural architecture of individual brains, but from their embedding in larger processes of social interaction and cultural inheritance in populations.
"Experimental evolution in cognitive science can help us contribute to one of the newest and most pressing challenges facing modern information societies, by providing a safe, ethical, transparent testing ground for controlled scientific studies of social networking algorithms and their impacts on thinking and reasoning in human populations," Thompson said.
This approach to the cultural evolution of cognition is relatively new, and Thompson notes that more studies are needed to understand how cognitive algorithms evolve in and out of the laboratory, especially when looking at social media platforms and the immense influence those networks may have over the cognitive formation of young people.
"To answer fundamental research questions, enable discoveries, and advance human progress, we must engage innovative, unconventional approaches. But for early-career researchers this is extremely risky, and not always even possible. Through the NOMIS & Science Young Explorer Award, we are able to extend critical support to promising young researchers at a crucial phase in their careers," said NOMIS Foundation Managing Director Markus Reinhard.
Célia Lacaux is a finalist for her essay "The borderland between wakefulness and sleep promotes creativity." Lacaux's work revealed that the sleep-onset period promotes creativity, and posed that future tools could target this creative sweet spot and awaken us in time to capture inspirations before they are lost to sleep. After completing her Ph.D. in 2021, she moved to the lab of Sophie Schwartz at the Geneva University Neurocenter for a postdoctoral position focusing on the relationship between sleep and creativity.
Stephen Kissler is a finalist for his essay "Mathematical models help predict and manage the course of pandemics." Kissler's work used mathematical models to measure the level of response needed for the COVID-19 pandemic, reveal the value of vaccination, and identify at-risk groups. In 2023 he will start a lab in the University of Colorado's Department of Computer Science to research how immunological and behavioral factors influence the spread of respiratory viruses.