A new science is emerging that promises to become the defining field of the 21st century. More than a narrow specialization, it is not just a new discipline but a new way of doing science—a new way of organizing intellectual domains and endeavors. Due to its wide impact, it goes by several names, but the one that encompasses its full potential is complexity. Today I want to briefly introduce why it is already so important and why it will likely define the boundaries of human research for decades to come.
The science of complexity
I am writing this essay after starting on the book titled Foundational Papers in Complexity Science. Volume One, 1922-1962. It is part of an intended four-volume set to be published by the incomparable Santa Fe Institute (SFI). As the title promises, the book contains key documents in the development of complexity as a field. However, what really makes the book worthwhile is that each article contains an introduction written by a contemporary researcher and commented by that scholar. Even better, the first part contains a masterful introduction to the field by David Krakauer, head of the SFÚ.
In this introduction, Krakauer makes a clear, incisive case for why complexity science is so important and why it is such a break with a long history of scientific thought. It presents the idea of ​​two different kinds of subjects of study in the world: AND and B systems. The AND systems exhibit basic regularities, follow simple laws, require minimal assumptions, and require minimal initial conditions. The objectives of celestial mechanics (ie, the hourly behavior of the Solar System) are representative of an AND System. The B systems are very different. Their description requires conditional histories with new structures and behaviors that emerge from nested hierarchies of subcomponents. The most important is, B systems are always far from equilibrium. Energy and entropy flow through them, allowing them to self-organize into self-adaptive structures where evolution (i.e. selection) plays a vital role.
As Krakauer points out, AND and B systems are so different that even the most perfect tool used for a AND system—think, for example, of a superpower microscope that could resolve everything down to the subatomic scale—would be almost useless for B systems.
A key aspect B systems is their organization, which cannot be fully understood by reducing them to their basic (or “basal”) 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. The dynamic patterns of information in their organization are decisive. As Krakauer puts it, “reductionism… not only fails to account for complexity; it fails to detect.”
4 key elements of complexity
Complexity science deals with all that is complicated B systems. Its scope runs the gamut from hurricanes to viruses to cells to the nervous system to societies to machines that might be able to think. In this way, Krakauer identifies four domains that underlie complexity.
The first is development. When systems evolve through selection, this means that some features persist and change while others are eliminated. In this way, entirely new orders of behavior are possible.
The second one is entropy. This is a recognition that complex systems are not just complex. Instead, they are engines of energy transformation. They extract energy from their surroundings, making them thermodynamically “open” and convert the free part of this energy into work. This work usually involves building and maintaining the system itself. In this process, entropy flows are generated that pass through the system and out into the environment.
Another function is dynamicswhich goes hand in hand with entropy. Complex systems can often be described using “dynamical 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 storage, copying, transmission and processing. Rocks do not use information. Complex systems do.
The overlap of these different features means that complexity science is more than physics, more than biology, more than computer science, and more than mathematics. It is not multidisciplinary – it is transdisciplinary. He rises above all and creates something completely new. The old power that gave us separate disciplines will still exist, but the walls that separate them will have to be porous.
In terms of importance, complexity science will define the forefront of 21st century science as it drives transformative change. The major issues we face, from climate change to threats to democracy to artificial intelligence, all fall within the domain of complex science. Complex science will be just as convincing as the engine for answering the most interesting questions of the 21st century: What is life? How do minds work? What drives the direction of social organization? How does the biosphere evolve along with the rest of the planet?
While older science addressing these questions will continue and still discover amazing things, it is no longer the most fertile ground for pushing the edge of the future. That’s because the future belongs to complexity.