Complexity science can transform 21st century research. Here’s how.

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 field, but a new way of doing science—a new way of organizing intellectual fields and endeavors. Given its wide influence, it goes by several names, but one that embraces its full potential is complexity science. Today, I want to briefly introduce why it is already so important and why it is likely to define the frontiers of human research for decades to come.

The science of complexity

I’m writing this essay after starting a book block called Basic 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 promised in the title, the book contains key documents in the development of complexity as a field. What really makes the book worthwhile, however, is that each paper contains an introduction written by an actual scholar and annotated by that scholar. Even better, the first volume contains a masterful introduction to the field by David Krakauer, head of the SFI.

In that introduction, Krakauer presents a clear, insightful argument for what makes complex science so important and such a break with the long history of scientific thinking. He introduces the idea of ​​two different types of study topics in the world: or AND B systems. of or systems exhibit fundamental regularities, obey simple laws, require minimal assumptions, and require minimal initial conditions. The objectives of celestial mechanics (ie, the behavior of the Solar System clock) are representative of a or the system. of B systems are very different. Their description requires contingent histories with new structures and behaviors emerging from nested hierarchies of sub-components. Most important, B systems are always far from equilibrium. Energy and entropy flow through them allowing them to self-organize into self-adaptive structures where evolution (ie, selection) plays an essential role.

As Krakauer points out, or AND B systems are so different that even the most perfect tool used for one or system—think, for example, a super-powerful microscope that can resolve everything down to the sub-atomic scale—would be nearly useless for B systems.

The main aspect of 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. It is the dynamic patterns of information within their organization that are crucial. As Krakauer says, “reductionism… not only fails to explain complexity; fails to detect it.”

4 main elements of complexity

Complexity science deals with all that is complicated B systems. Its scope extends from hurricanes, viruses, cells, nervous systems, societies and machines that may be able to think. In this way, Krakauer identifies four areas that support complexity.

The first is EVOLUTION. 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 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 draw energy from their surroundings, making them thermodynamically “open”, and transform the free part of this energy into work. This work usually involves making the system self-creating and self-sustaining. In this process, entropy flows are generated that wash through the system and out into the environment.

The other feature is dynamics, which goes hand in hand with entropy. Complex systems can often be described using “dynamical system theory”, where rich, nonlinear and often chaotic behavior allows rich behavior to emerge.

The last feature is calculation. Complex systems are best described in terms of the 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’s not multidisciplinary – it is transdisciplinary. It rises above all, creating 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.

Importantly, complexity science will define the forefront of 21st century science because it will drive transformative change. The major problems we face, from climate change to threats to democracy to artificial intelligence, all fall within the domain of complexity science. Equally compelling, complexity science will be the engine for answering the most interesting questions of the 21st century: What is life? How do minds work? What drives the directions of social organization? How does a biosphere evolve with the rest of the planet?

While the old science focused on those questions will continue and still discover amazing things, it no longer represents the most fertile ground for pushing into the edge of the future. This is because the future belongs to complexity.

Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top