No one can accuse Michael Muthukrishna of thinking small. His first book, titled A Theory of Everyone, sets out to explain “who we are, how we got here, and where we’re going.”
Muthukrishna, a professor of economic psychology at the London School of Economics, weaves together thinking from psychology, economics, evolutionary biology, anthropology, and other fields to offer a theory of us.
“Physicists refer to a unifying theory that connects diverse effective theoretical frameworks, such as general relativity—the physics of the very vast—and quantum mechanics—the physics of the extremely tiny—as a theory of everything,” he writes. He describes his attempt to integrate the science of the vast and tiny worlds of human beings, including genes, culture, and the environment, as “a theory of everyone.”
An important goal of articulating this theory, Muthukrishna says, is to help move social and behavioral science from a young science to a more mature one.
“A young science behaves like a child. It spends most of its time observing the world and coming up with explanations for what it sees,” he writes. “It gets into everything, plays with switches, knobs, and runs whatever experiments it comes up with. But it doesn’t yet know how to properly make sense of what it sees, how things connect with one another, or how to confidently act in the world.”
The next stage, Muthukrishna writes, is a sort of scientific puberty. “Like human puberty, this is an exciting, embarrassing, and often awkward affair, and requires some major changes. Chief among these is the discovery of an overarching theoretical framework that can sift sense from nonsense, make trustworthy and useful predictions, and offer pathways from discoveries to technologies.”
Where are the social and behavioral sciences currently? “Right now . . . we’re in that pre-Darwinian world where you notice that there are butterflies and birds have different beaks. Or the alchemy world where Newton is turning lead into gold,” he told me.
This progression of social and behavioral science is the subject of the first of a two-part interview with Muthukrisha. In the second part, we’ll consider how energy, its sources and relative abundance, has shaped who we are and limits (or doesn’t) who we can become.
The interview has been edited for length and clarity.
Evan Nesterak: We meet in an elevator. I learn you’ve written a book and I ask you what it’s about. I say, “Tell me the theory of everyone.” What do you say?
Michael Muthukrishna: This is a bit like asking me to give the elevator pitch for general relativity! The theory of everyone, at its core, is that there are four laws that have always governed the evolution of all of life. They manifest in different ways for different life, but they are the same laws, and they apply just as much to bacteria as to businesses, to cells and to societies. They apply just as much to our individual behavior as they do to our collective behavior.
Those laws are the availability of energy, the law of energy; the law of innovation, by which we innovate new and efficient ways to use that energy to out compete others; the law of cooperation, by which we work together to outcompete others, but also to facilitate innovation; and the law of evolution, which has three ingredients: diversity, transmission, and selection. It works for genetic evolution, and it also works for cultural evolution.
The theory of everyone calls to mind a tension I’ve been interested in for some time, one that goes back to Ken Gergen’s paper “Social Psychology as History.” In other sciences, like physics, our theories of how planets move around the sun doesn’t change how they move. But our theories of human nature can change behavior. For instance, how we design our institutions will change based on who we think people are, which will then influence how people behave, influencing who we think people are, and so on. How do you think about that argument in terms of a theory of everyone? The challenge of setting down laws for a moving target, so to speak.
In A Theory of Everyone, I’m not trying to give you physics, which is designed around fairly well-behaved systems. I think the successes of biology are a much better model for a behavioral scientist. In biology you don’t have that predictive power in quite the same way. What you do have is the rules by which a biological system evolves and changes.
What I’m trying to say in A Theory of Everyone is these are the rules by which the system works. It’s energy. It’s innovation.. It’s cooperation. It’s the laws of evolution. It is the fact that humans are a dual-inherited animal with three sources of information guiding our behavior: genetics from our parents, culture from our societies, and a short lifetime of experience. Those are just the rules.
Now, what is that software [the part determined by cultural evolution]? That’s a different question. I have a paper with a similar title, “Psychology as a Historical Science.” The software is a result of this path dependence. If your ancestors were struggling over resources, maybe you’re more tightly cooperative, you’re maybe a little less generous to out-groups. You can escape that, but that’s your starting point.
If our world looked different, if we had gone down a different historical path, then my specific policy suggestions in the second half of the book would be different because the suggestions come out of the theory, but not in the sense of they’re the only conclusion. They’re the way that the theory interacts with the world as it is today. It’s the way the theory interacts with humans as they generally are, as well as humans as they specifically are in our cultural context, in this moment in history.
I’ve been thinking about your idea that the social and behavioral sciences need to move to the next stage of development as a science, from alchemy to chemistry as you put it. What feels like alchemy to you? Where are we trying to lead into gold?
If you look at the heuristics and biases we use, default bias or loss aversion for instance, because we’ve just discovered them completely empirically, we have no basis upon which to say, Will this generalize? So we resort to saying things like, There are individual differences, and, Context matters. But it doesn’t have to be that way.
You’re saying social and behavioral science needs to become more formalized. That we need to be asking what’s the theory connecting observations like default bias or loss aversion.
When Mendeleev and Lavoisier were coming up with the periodic table, they had a bunch of evidence in front of them. Then they were able to see these patterns. If we think about loss aversion from a theoretical perspective, you can’t just look at the empirical data. It would be shocking if people of low income in more deprived environments didn’t have some kind of loss aversion because that kind of loss really is catastrophic for them. Whereas if you’re a fairly affluent person, you may or may not show loss aversion in the way that it’s measured for these small stakes or even large stake games.
Defaults are another example that we’re looking at cross-culturally. We want to understand, Is this really about trust? Is it about social norms? These things that we really understand well. Or is it these more amorphous, lead-into-gold type things like [psychological] inertia? What does that even mean? Why would we have inertia? Under what conditions?
Laying things on a theoretical foundation is that move from alchemy to chemistry. But the very first step before you even get to laying it on deeper theoretical foundations is you have to have the right model.
Laying things on a theoretical foundation is that move from alchemy to chemistry. But the very first step . . . is you have to have the right model.
The analogy that I use in the book is that you can develop a pretty accurate model of the solar system with Earth in the center and the Sun rotating around the Earth. That was the Ptolemaic model, and it was incredibly predictive. It was predictive because the model wasn’t a real model. It had circular orbits and it had little epicycles that corrected for the fact that in reality the orbits are elliptical and so on.
In Copernicus’s original model, and in part why I think Galileo had such a hard time, he still had circular orbits even though he put the sun in the center. He still needed these little epicycles.
I sometimes think a lot of economic theory looks like that. You have these hidden assumptions that you’re stuck with and then you have to compensate. You’re like, Here’s the utility model, people don’t behave like the Nash equilibrium suggests. Maybe they have inequity aversion, maybe they have this or that. You’re trying to patch it with all these things.
But the moment you realize, Oh, the Sun is in the center and the orbits are elliptical is when you go, Aha, now everything follows from that. We can build a cleaner, more parsimonious model of the universe.
The key insight for pushing forward the behavioral sciences is that humans are a new kind of animal. We’re governed not just by millions of years of genetic evolution that apply across the animal kingdom but also by thousands of years of cultural evolution. That is the deep software that plays out differently in different parts of the world.
We have a new paper under review where we show people the Coffer illusion. Can I show this to you?
Sure.
Tell me, do you see rectangles or circles?
I see rectangles. Wait, now I see circles as well.
It turns out when we tried this in the U.K. and in the U.S, 80 percent of people see only the rectangles, and something like another 19 percent of people see rectangles and then circles.
That would be me.
That’s me, and that’s every author of this paper. When we ran this in Namibia, 48 percent of people only saw circles and another 48 percent saw the circles first and then managed to see the rectangles.
Wow. What’s the explanation there?
We don’t know, but it’s consistent with the carpentered corner hypothesis. I’m looking at a computer screen that has neat, clean edges. Rectangles are not a natural thing. In the natural environment, you don’t have these clean edges, trees don’t grow like that. Everything is jagged, and circles and curved edges are much more common. Your visual system is attuned to seeing that more than you see these things.
We did this in villages. When we go to the semiurban environments, people are still seeing a lot of circles compared to the West, but it’s starting to balance out.
That’s an example of software. Humans everywhere have the same visual system; if that perception can change, you have to imagine how much the software varies around the world.
But we’re not butterfly collectors. It’s not enough to just do the first step, which is to show the effect. You have to explain it. We have millions of years of genetic evolution, thousands of years of cultural evolution, and then a short lifetime of experience that is also shaped by our ecology and our experiences. Things like risk aversion and the marshmallow test and so on are going to be products of these things.
So you’re basically saying we’ve been doing a lot of …
Blind empiricism.
We had to start somewhere to get a foothold, and people have been running experiments to do that. But it sounds like you’re saying, we’re ready to move on, to ask, how does this all fit together?
Exactly. Don’t be like a home chef following recipes. Become a chef that understands flavors. Science isn’t induction or deduction, it’s abduction, where you’re moving toward the best explanation, connecting the theory to the evidence. Otherwise, you can’t narrow down the large space of possibilities. I think we’re at the point where we can move to Newtonian physics, if that makes sense. That would be a massive improvement. F = m * a. We’re at that point.
Where we can get a good enough understanding of the world that we can model it really, really well, and then eventually we’ll come to …
Quantum mechanics.
But with the first move to Newtonian physics, we’re modeling our world really, really well.
That’s right. We’re at the point where we can transition into modeling it. Right now, we’re just empiricists, we’re just measuring stuff. We’re in that pre-Darwinian world where you just notice that there are butterflies and birds that have different beaks and so on. Or, you’re in that alchemy world where Newton is turning lead into gold.
So how do we get to the next stage?
It’s dual inheritance theory—the modeling of genetic evolution and cultural evolution, along with the lifetime of experience.
How does the way we do behavioral science change with dual-inheritance theory in mind?
First, there’s a lot of basic science to be done trying to lay these heuristics and biases and ways of nudging people onto firmer theoretical foundations. There have been a few attempts in this direction, but we want to make those first models.
The best work I’ve seen in this sphere are people like Charles Efferson, who wants to move people away from female genital cutting. He’s got a really nice model of how to understand whether it’s a coordination problem or if it’s a norm problem, whom you should target depending on that, and what you should measure.
That is what I would call applied cultural evolutionary behavioral science. You have a mathematical model, and it’s making testable predictions. It is not an abstract model out of nowhere like we sometimes build in economics, but one that is actually grounded in a framework of models, around social learning and cooperation and norm psychology, as well as error management theory or genetic evolution, and so on.
You’re building these models, they’ve got precise, testable predictions. You test them in the lab across the world, you check if your expectations are there, then you take them and you start to apply them.
And now you’re thinking with a periodic table, you’re thinking with a theoretical framework. You’re not just using your own life intuitions about what you think is going to work and not work, which are limited.
Is there anything we didn’t get to that you’d like to add?
The book itself not only lays out a theory of everyone (in terms of cooperation and innovation and intelligence and how humans came to be where we are) but also specifically applies it to issues that we care about. Many of the problems we see in the world, we currently see as disconnected—the climate crisis, immigration troubles, rise of right wing authoritarianism, innovation stagnation, society falling apart, inflation, our education system not keeping up. They are not disconnected. They are part of the same process. By solving the root, we fix the whole damn thing.
In part two of our interview, Muthukrishna and I discuss how energy—everything from photosynthesis to ATP, fossil fuels to fission—shape and constrain our behavior. “We cannot move without energy, cannot reproduce, cannot do anything at all,” Muthukrishna says. “And yet since the Industrial Revolution, which unlocked unfathomable quantities of unexploited energy in the form of fossil fuels, we have stopped thinking about it.”
“Ultimately energy is at the heart of all that we do and all we can do,” he writes. “And when we see energy in this light, we are like the fish finally seeing the water around us. Suddenly our experiences and potential futures come into clearer vision.” Read part 2 here. — Evan Nesterak, Editor-in-Chief
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