The Earth is full of examples of social behavior. When bacteria, insects, primates, and even self-driving cars make productive choices about their interactions with other individuals, that’s sociality. We can trace social behavior back to single-celled organisms that became the building blocks of life on our planet. And humans, by becoming social, have gained a great advantage in the evolutionary race for survival. If we could turn back the Earth’s clock, would social behavior emerge again, and could we expect to find it elsewhere in the Universe? “Probably yes,” concludes a new book from SFI Press.
In “Ex Machina: Coevolutionary Machines and the Origins of the Social Universe,” External Professor John H. Miller (Carnegie Mellon University) of the Santa Fe Institute merges ideas from the study of games, the fundamentals of computation, and from Darwin’s theory of evolution to look at dynamic social systems through a computer lens. This new approach, he writes, is like a time machine that allows us to observe and analyze the advent of social behavior – a question that cannot be answered using the knowledge of just one person. domain.
“This work, at its core, embraces the SFI way of doing science,” says Miller, who is an economist and social scientist. “The most interesting and important scientific questions often lie between traditional fields.”
But when working across disciplines, even seemingly simple things — like defining social behavior — can be difficult, Miller says. “Different researchers have very different notions about whether this can happen across species, whether it requires special forms of intelligence, and so on.” His ultimate definition was quite general – “a relief to dog owners everywhere”, he says – and it allows for the possibility that social behavior may have emerged early in the history of life on Earth.
To answer questions about the emergence of sociality, Miller uses finite automata, which are simple computing machines capable of responding to inputs produced by other automata and of evolving inside a computer. Computations captured by finite automata illustrate the amount of interaction and “reflection” needed for a system to become social, providing rich insights into the complex and multifaceted nature of social behavior. Miller began working on the fundamental ideas presented in the book at SFI when he was a postdoctoral fellow – the Institute’s first – more than thirty years ago. But it was only recently, aided by dramatic advances in computing power, that he was able to complete the project.
The book became his path to discovery: a way for Miller to explore and understand, with deeper insight, what it takes to make a system social. It also provided an opportunity to answer questions about the origins of social behavior, which Miller had raised in his 2007 book with Scott Page, “Complex Adaptive Systems.”
This new project offers readers a unique and technical insight into the emergence of social behavior in a system. His work reveals that systems can move from asocial to social, or vice versa, when they cross certain thresholds. “If agents are very limited in their ability to process information – to make choices or to be ‘thoughtful’ – or in the extent to which they interact with each other, the system falls into asocial outcomes,” explains Miller. “Amazingly, even though these systems are driven by small evolutionary changes, the shift from asocial to social (and back again) can happen very quickly – evolutionary revolutions.”
Understanding these thresholds of social behavior could not only explain how social life arose, but also give us insight into social upheavals such as political movements and revolutions, the rapid acceptance of new social norms, and even the emergence or the collapse of a social whole. order. Such events can lead to deep and rapid transitions that ultimately define our collective future.
Book: Ex Machina: co-evolving machines and the origins of the social universe
Written by John H. Miller
$9.99 (paperback); Free PDF
Publisher and Disclaimer: The SFI Press Scholars Series
Paperback ISBN: 978-1947864429
Release date: December 6, 2022
Available on Amazon.com
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