Human beings inherit many genetic traits directly from their parents. However, cultural traits — tools, beliefs and behaviors that are transmitted by learning — can be passed on not only by parents but also teachers and peers. Many animals have learned behaviors, but people are uniquely good at building on existing knowledge to innovate further. This capacity, known as cumulative culture, was captured by Sir Isaac Newton when he said, “If I have seen further, it is by standing on the shoulders of giants.”
We can see evidence of this cumulative culture in the archaeological record; over time, there’s an accelerating increase in the number of tools people use. But the archaeological record reveals another pattern, too: there’s also evidence for large-scale losses of culture. For example, archaeological excavation suggests that Aboriginal populations in Tasmania lost numerous technologies over time, including nets, bone tools and warm clothing, even though these tools might still have been useful.
And it doesn’t seem like cultural accumulation just proceeds through time at a regular pace. The archaeological record shows some evidence of large bursts of innovation occurring after relatively long periods of little change. For example, the early human archaeological record is composed primarily of stone tools for approximately two million years. Then, from about 60,000 to 30,000 years ago, archaeologists find a burst of creative activity, such as burial sites, art forms including cave paintings and statues, and engraved bone and antler tools.
The process of change in the frequency and distribution of cultural traits over time is known as cultural evolution. But what drives it? Why would the inventory of tools expand at some times and diminish at others? These are questions that have intrigued archaeologists for decades. We propose a new model we think addresses some aspects of how cultural evolution happens — and, crucially, it’s based on the idea that not all innovations occur in the same way.
Modeling how culture advances
Since it’s not possible (or ethical) to experimentally manipulate large groups of people, scientists make mathematical models to try to understand how cultural traits evolve. A model of this kind is a set of rules that describe mechanisms that may underlie the process we’re interested in.
For example, a model of cultural evolution could use equations to describe the rate at which individuals invent new things, transmit their knowledge and learn from others. These equations would depend on a number of parameters — things like population size and the rates of invention and learning.
A model can be explored analytically, by calculating what patterns the set of equations predicts, or it could be explored using computer simulations. In our research, we did both.
Most of the models of cultural evolution study the spread of technologies and behaviors that already exist in a population. In our recent PNAS paper, coauthored with Stanford’s Marcus Feldman, we introduce a new model of cultural evolution. What’s different about our model is quite simple: we don’t assume all human innovations are created in the same way.
Watching our model’s predictions unfold
Working with a model is kind of like playing a scientifically minded game of The Sims. On the computer, we simulate a human population of a certain size. We set the rules for a number of interdependent innovation processes to occur at different rates. For example, inventions that can be viewed as “strokes of genius” may be rare, while the invention of tools that are versions of existing ones might be more frequent.
The Latest on: Cultural Evolution
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The Latest on: Cultural Evolution
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