Considering the limitations of psychology today, I discussed ways in which we can move beyond WEIRD (Western, Educated, Industrialized, Rich, and Democratic) psychology in a global collaborative manner and strengthen the links between basic and applied policy research. I also discussed the importance of historical psychology.
Today’s episode is a conversation with Dr. Michael Muthukrishna, an Associate Professor of Economic Psychology at the London School of Economics.
Michael’s research takes on a suite of topics that all start from a single big question: Why are we so different from other animals? Part of the answer has to do with our neural hardware. There’s no question we’ve got big brains—and Michael has some cool things to say about why they may have gotten so big. But Michael is just as focused on our cultural software—the tools and ideas we develop, tweak, share, and accumulate over time. You might say he’s more impressed by our collective brains than by our individual brains. To study all this, Michael builds formal theories and computational models; he runs experiments; and he constructs and analyzes huge databases.
We cover a lot of ground in this episode. We talk about the finding that the size and interconnectedness of a social group affects the cultural skills that group can develop and maintain. We consider what actually powers innovation (hint: it’s not lone geniuses). We discuss how diversity is a bit double-edged and why psychology needs to become a historical science. And that, my friends, is hardly all—we also touch on cetaceans, religious history, and spinning plates.
I’ve been hoping to have Michael on the show for months now. His work is deeply theoretical, advancing the basic science of what it means to be human. But it’s also engaged with important practical issues—issues like corruption and cultural diversity. Without further ado, here’s my conversation with Dr. Michael Muthukrishna. Enjoy!
Diversity is a double edged sword. Governments and organizations often push for greater diversity and tolerance for diversity, because the human tendency is toward squashing difference and selecting others like ourselves. But diversity can both help and harm innovation.
On the one hand, there’s intellectual arbitrage: discoveries and technologies situated in one discipline that draw on a key insight from another. Here diversity is a fuel for the engine of innovation.
On the other hand, diversity is, by definition, divisive. Without a common understanding, common goals, and common language, the flow of ideas in social networks is stymied, preventing recombination and reducing innovation. How do we reap the benefits without paying the costs?
Consider the challenge of collaborations between scientists and humanities scholars (or even between scientists in different disciplines). The key is to find common ground through strategies such as optimal assimilation, translators and bridges, or division into subgroups.
Resolving the tension between diversity and selection is at the core of a successful innovation strategy. And there are many possible solutions.
Some dimensions of diversity matter more than others—without a common language, communication is difficult. On the other hand, food preferences create little more than an easily solved coordination challenge for lunch.
But between these are many dimensions where optimal assimilation may be desirable and traits can be optimized, such as psychological safety so people feel free to share unorthodox ideas.
Other strategies include interdisciplinary translators. In my role at the Database of Religious History (DRH)—a large science and humanities collaboration—we have benefited from a few scholars trained in both to bridge the gap.
Innovation can also be divided into independent groups, coordinating within the group but competing against others trying different strategies (e.g. competition between firms).
Check out the full issue here: https://www.nae.edu/244665/Winter-Issue-of-The-Bridge-on-Complex-Unifiable-Systems
I spent the last week back at Harvard University discussing research on cultural evolution and innovation with the Learning Innovations Laboratory (LILA), part of Project Zero at the Harvard Graduate School of Education. The LILA group include people from industry and the military. Every year the group invites two academics to discuss their research and how it might be applied to problems faced by members of the group. This year, Mary Ann Glynn and I were invited. It was an intellectually enriching opportunity to apply my work to current challenges in corporations and other organizations.
The ideas presented in my two talks were beautifully captured in the graphics below:
The Science of Cultural Evolution: What Makes Humans So Different
Sources of Innovation: The Secret of Human Success
I spent the last couple of days at a small conference on cumulative culture organized by Claudio Tennie and his two PhD students Elisa Bandini and Eva Reindl. The theme was “When and How does Cumulative Culture Emerge”. It was an excellent meeting – large enough to have a diversity of views, small enough to have interesting conversations with almost all participants.
To very briefly summarize, innovation is often assumed to be an individual endeavor driven by geniuses and then passed on to the masses. Consider Thomas Edison and the lightbulb or Gutenberg and the printing press. We argue that rather than a result of far-sighted geniuses, innovations are an emergent property of our species’ cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains.
Innovations, large or small, do not require heroic geniuses any more than your thoughts hinge on a particular neuron.
We argue that rates of innovation are heavily influenced by:
transmission fidelity, and
We discuss some of the forces that affect these factors. These factors can also shape each other. For example, we provide preliminary evidence that transmission efficiency is affected by sociality—languages with more speakers are more efficient.
We argue that collective brains can make each of their constituent cultural brains more innovative. This perspective sheds light on traits, such as IQ, that have been implicated in innovation. A collective brain perspective can help us understand otherwise puzzling findings in the IQ literature, including group differences, heritability differences, and the dramatic increase in IQ test scores over time.