Sam Arbesman’s newest book, Overcomplicated, looks at how many technological systems have grown so complex that they defy easy understanding. In the following lightly edited excerpt, he argues that we need to learn to think more like biologists in order to work with the technology we’ve created.
Within physics there is a distinct trend toward unifying and simplifying the phenomena observed. It is embodied by the work of Einstein or Newton or James Clerk Maxwell, who developed a handful of equations to explain the workings of electricity and magnetism. Simplification, even oversimplification, is often revered within the realm of physics.
Biologists, as a rule, have a greater comfort with diversity and bundles of facts, even if they are left unexplained by any single sweeping theory. A smaller, more qualified and modest model is just fine. Of course, this is not always true, as Charles Darwin was clearly a unifying force within biology, and many other types of biologists also tend toward this unifying approach.
I term these two perspectives physics thinking and biological thinking.
Both of these traditions seek the development of theories that are general and predictive. However, the two modes of thinking go about this in different ways, and their differences, driven by the properties and relative complexity of the systems they study, can be examined through their relative comfort with abstraction. For example, the use of mathematics to abstract away details at a grand level is found everywhere in physics, but less often in biology.
Abstraction has its place, but it is not in assuming spherical cows. When details are abstracted away in biology, not only is information lost, but you often end up losing significant portions of what the world contains and fail to explain what’s important, such as the edge cases. Biological thinking and physics thinking are distinct, and often complementary, approaches to the world, and ones that are appropriate for different kinds of systems.
How should we think about complex technologies? Are they biological systems, or physics systems? Which mode of thinking does technology require?
To answer that, we can explore the characteristics of each type of system and compare them to what we know about technology.
First, biological systems are generally more complicated than those in physics. In physics, the components are often identical—think of a system of nothing but gas particles, for example, or a single monolithic material, like a diamond. Physical interactions can often be uniform throughout an entire system, such as satellites orbiting a planet.
Not so with biology. In biology, there are a huge number of types of components, such as the diversity of proteins in a cell or the distinct types of tissues within a single creature; when studying, say, the mating behavior of blue whales, marine biologists may have to consider everything from their DNA to the temperature of the oceans.
Not only is each component in a biological system distinctive, but it is also a lot harder to disentangle from the whole. For example, you can look at the nucleus of an amoeba and try to understand it on its own, but you generally need the rest of the organism to have a sense of how the nucleus fits in to the operation of the amoeba, how it provides the core genetic information involved in the many functions of the entire cell. As our technologies become more complex and intertwined, it’s clear that they resemble biological systems more than those of physics.
Second, biological systems are distinct from many physical systems in that they have a history. Living things evolve over time. While the objects of physics clearly do not emerge from thin air—astrophysicists even talk about the evolution of stars—biological systems are especially subject to evolutionary pressures; in fact, that is one of their defining features. The complicated structures of biology have the forms they do because of these complex historical paths, ones that have been affected by numerous factors over huge amounts of time. And, because any small change can create unexpected effects, the changes that have happened over time have been through tinkering: modifying a system in small ways to adapt to a new environment.
In both these senses, biological systems clearly parallel our modern technological systems, which are collections of interacting modules, often built on a complex historical legacy. But
the similarities between biology and technology can also be seen in the concept of highly optimized tolerance. Technologies can appear robust until they are confronted with some minor disturbance, that unexpectedly triggers a catastrophe. The same thing can happen to living things. For example, humans can adapt incredibly well to a large array of environments, but a tiny change in a person’s genome can cause dwarfism, and two copies of that mutation invariably cause death.
We are of a different scale and material from a particle accelerator or a computer network, and yet these systems have profound similarities in their complexity and fragility. Overall, there is a deep kinship between biology and technology—which means there is something to be learned from how biologists think.
Biological thinking, with its focus on details and diversity, is a critical perspective for dealing with a messy evolved technology that can be completely understood only through a lot of initial prodding and testing. The way biologists, particularly field biologists, study the massively complex diversity of organisms is therefore particularly appropriate for understanding our technologies.
Field biologists often act as naturalists—collecting, recording, and cataloging what they find around them. But when confronted with an enormously complex ecosystem, they don’t immediately try to understand it all in its totality. Instead, they recognize that they can study only a tiny part of such a system at a time, even if imperfectly. They’ll look at the interactions of a handful of species, for example, rather than examine the complete web of species within a single region. Field biologists are supremely aware of the assumptions they are making, and know they are looking at only a sliver of the complexity around them at any one moment.
Similarly, when encountering a complicated tangle of a technological system, whether a piece of software, a country’s laws, or the entirety of the Internet, a physics mind-set will take us only so far if we try to impose our sense of elegance or simplicity upon its entirety. If we want to understand our technological systems and predict their behavior, we need to become field biologists for technology.
Samuel Arbesman is Scientist in Residence at Lux Capital. He is the author of Overcomplicated: Technology at the Limits of Comprehension as well as The Half-Life of Facts. He is also a Senior Fellow of the Silicon Flatirons Center for Law, Technology, and Entrepreneurship at the University of Colorado and Research Fellow at the Long Now Foundation. He is @arbesman on Twitter.