A new science is emerging that promises to become the defining field of the 21st century. More than just a narrow specialization, it is not just a new field, but a new way of doing science – a new way of organizing intellectual domains and endeavors. Given its broad impact, it goes by several names, but the one that embraces its full potential is complexity science. Today I would like to briefly introduce why it is already so important and why it will likely define the boundaries of human research for decades to come.
Complexity of science
I’m writing this essay after starting a door jam of a book called Fundamental papers in complexity science. Part one, 1922-1962. It is part of a planned four-volume set to be published by the incomparable Santa Fe Institute (SFI). As promised in the title, the book contains important articles in the development of complexity as a field. What really makes the book worthwhile, however, is that each article contains an introduction written by a current researcher and annotated by that scientist. Even better, the first part contains a masterful introduction to the field by David Krakauer, the head of SFI.
In that introduction, Krakauer lays out a clear, compelling argument for what makes complexity science so important and such a break with the long history of scientific thinking. He introduces the idea of two different types of subjects of study in the world: the a And b systems. The a systems exhibit fundamental regularities, obey simple laws, require minimal assumptions, and require minimal initial conditions. The goals of celestial mechanics (i.e. the clockwork behavior of the solar system) are representative of one a system. The b systems are very different. Their description requires contingent histories with new structures and behaviors arising from nested hierarchies of subcomponents. The most important thing is that the b systems are always far from equilibrium. Energy and entropy flow through them, allowing them to organize themselves into self-adaptive structures in which evolution (i.e. selection) plays an essential role.
As Krakauer notes, the a And b systems are so different that even the most perfect tool for one a system – think, for example, of a super-powerful microscope that could resolve everything down to the subatomic scale – would be virtually useless for the B systems.
The most important aspect of b systems is their organization, which cannot be fully understood by reducing them to their fundamental (or ‘basic’) components. For example, consider an ecosystem like a rainforest. The interactions between plants, animals, microorganisms and the environment create a complex web of relationships that cannot be understood by studying individual components in isolation. It is the dynamic information patterns within their organization that are crucial. As Krakauer puts it, “reductionism… not only fails to explain complexity; it fails to detect it.”
4 key elements of complexity
Complexity science deals with all those complicated things b systems. Its scope extends from hurricanes to viruses, from cells to nervous systems, from societies to machines that can possibly think. In this way, Krakauer identifies four domains that underlie complexity.
The first is evolution. When systems evolve through selection, it means that some characteristics persist and change, while others are eliminated. In this way, completely new orders of behavior become possible.
The second is entropy. This is a recognition that complex systems are not just complicated. Instead, they are engines of energy transformation. They take energy from their environment, make it thermodynamically ‘open’ and convert the free part of that energy into work. That work usually involves the system creating and maintaining itself. During this process, entropy flows are generated that wash through the system and are released into the environment.
The next function is dynamics, which goes hand in hand with entropy. Complex systems can often be described using ‘dynamic systems theory’, where rich, non-linear and often chaotic behavior allows rich behavior to emerge.
The last feature is calculation. Complex systems are best described in terms of their use of information. Use here means storing, copying, sending and processing. Rocks don’t use information. Complex systems do that.
The overlap of these different characteristics means that complexity science is more than physics, more than biology, more than computer science and more than mathematics. It’s not multidisciplinary – it is transdisciplinary. It rises above everything and creates something completely new. The old silos that gave us separate disciplines will still exist, but the walls that separate them will have to become porous.
In terms of importance, complexity science will define the cutting edge of 21st century science as it will drive transformative change. The big problems we face, from climate change to threats to democracy and artificial intelligence, all fall within the scope of complexity science. Just as compellingly, complexity science will be the engine for answering the most interesting questions of the 21st century: What is life? How do ghosts work? What drives the directions of social organization? How does a biosphere evolve together with the rest of a planet?
While the older science that focuses on these A questions will continue and continue to discover amazing things, it is no longer the most fertile ground for exploring the edge of the future. That’s because the future belongs to complexity.