Looking Backwards to Revitalize Systems Science
Complexity, cybernetics, and systems science are closely related yet distinct approaches to transdisciplinary science.1
They each started gaining traction in the middle of the 20th century. It was becoming clear that reductionist approaches from the siloed disciplinary sciences weren’t sufficient for gaining deep and causal understanding of complex phenomena — the behavior of the human mind, environmental dynamics, or war and peace.
While the disciplines share common theoretical roots and several thinkers contributed to all three, they’ve also competed for mindshare in the world of academia and in public discourse.
Complexity science has enjoyed the most popularity by a long shot, in large part thanks to the efforts of The Santa Fe Institute, which has helped turn complexity science into the poster child for transdisciplinary research. Stephen Hawking proclaimed in the year 2000 that “the 21st century would be the century of complexity.”2 Last month computational astrophysicist Adam Frank argued that complexity science could transform 21st-century research by “shift[ing] scientific inquiry from predictable laws to studying dynamic, emergent systems.”3
Cybernetics doesn’t enjoy nearly as much popularity as complexity, but has developed and maintained a strong niche in academia. Cybernetic approaches are well understood and appreciated in the world of systems. We are also witnessing a resurgence of interest in the field from blockchain researchers and engineers who see an opportunity to use cybernetic principles in the design of crypto-based “decentralized autonomous organizations” (DAOs).45
Systems science, however, isn’t showing nearly as many signs of life. For most people the discipline seems to be either not real or not relevant. There are only a handful of college programs dedicated to systems science in the United States. Often when I mention I’m studying systems science, I’m met with blank stares and confusion. The ISSS, originally founded as the SGSR in 1954 in order to advance the theoretical framework at the heart of systems science, General System Theory (GST), is working to find its footing.
Why did history play out this way?
This is an important question for me because, despite the fact that systems science has less mindshare than complexity or cybernetics, I think it represents one of the most exciting frontiers for transdisciplinary research.6
So, I was very happy to recently stumble across a relevant, wonderful, and inspiring book review of Ludwig von Bertalanffy’s General System Theory. It was written in 2009 by Susan Stepney, a computer scientist focused on non-standard computing and bio-inspired algorithms.78
Stepney does a great job of summarizing Bertalanffy's core ideas and concludes by identifying a few potential reasons why GST never went mainstream.
It was ahead of its time.
There was still plenty of progress to be made in the reductionist paradigm, for example in biology with genes to sequence and data to mine. It’s only now becoming clear that we lack the frameworks necessary to “put all the pieces back together.”
The mathematics wasn't ready. We still don’t have a unified theory of material information processing, of open systems that process both matter and information.
She goes on to argue that advances in computing might be the key factor enabling us to “do better” than the GST pioneers. Computers can handle complexity and explore behavior and dynamics in ways humans simply can’t.
But she also emphasizes that progress requires we remember our history so we “don’t waste time reinventing the wheel.”
“We need to stand on the shoulders of giants, and Bertalanffy seems to have a good set of shoulders on him.”
I can’t recommend her review highly enough for anyone interested in the history of GST, and concerned with the future of systems science.
Metcalf, G. S., & Kauffman, S. A. (2021). Systems Science, Cybernetics, and Complexity. In G. S. Metcalf, K. Kijima, & H. Deguchi (Eds.), Handbook of Systems Sciences (pp. 29–63). Springer. https://doi.org/10.1007/978-981-15-0720-5_67
Jogalekar, A. (n.d.). Stephen Hawking’s advice for twenty-first century grads: Embrace complexity. Scientific American. https://www.scientificamerican.com/blog/the-curious-wavefunction/stephen-hawkings-advice-for-twenty-first-century-grads-embrace-complexity/
Complexity science could transform 21st-century research. Here’s how. (2024, June 13). Big Think. https://bigthink.com/13-8/complexity-science-could-transform-21st-century-research-heres-how/
Zargham, M., & Nabben, K. (2023). Aligning ‘Decentralized Autonomous Organization’ to Precedents in Cybernetics. MIT Computational Law Report. https://law.mit.edu/pub/dao-precedents-cybernetics/release/1
Shapiro, G. (2024, March 11). THE METALEX WHITEPAPER [Substack newsletter]. MetaLeX Newsletter. https://metalex.substack.com/p/the-metalex-whitepaper
Back to School—By Shingai—System Explorers. (n.d.). https://systemexplorers.substack.com/p/back-to-school
Susan Stepney. (2024). In Wikipedia. https://en.wikipedia.org/w/index.php?title=Susan_Stepney
SS > book reviews > Ludwig von Bertalanffy. (n.d.). https://www-users.york.ac.uk/~ss44/books/pages/v/LudwigvonBertalanffy.htm