The big question for this segment is, can we define complexity as a concept? Why is understanding complexity important for analyzing problems? [MUSIC] Complexity is everywhere. It is found in any system in the universe that is, was, or ever will be. Complexity can be seen in the stars and galaxies in the night sky. It can be seen in nature, in plants and animals. It can be seen in culture, in planes, trains, and automobiles. Even in the intricate web of global civilization itself. By in large, it is a system of varied and diverse building blocks that produce effects that are greater than the sum of its parts. All complex systems hold common elements. They all hold common trends. All forms of complexity are connected to each other. Indeed, in the history of the universe, we've seen them arise out of each other. Stars create elements, elements form life, and some of that life puts forth technology and culture. The whole thing is united in a continuum. As such, an understanding of complexity can be useful for approaching problems in any field, any workplace, and any topic, whether it be scientific, ethical, or business related and the list goes on and on at infinitum. Looking at a complex problem from a transdisciplinary point of view can augment our ability to devise solutions to that problem. The origin of the modern scientific use of the word complexity is found in 20th century geometry in mathematics, 20th century biological classifications and the study of irreversible thermodynamics. Complexity science now spends across of the academic disciplines being applied to business management. One looking at the relationship of many variables in the company. And how to achieve better outcomes. In economics, when looking at the macro-scale comprehensive resources and state and non-state actors. In meteorology, when looking at the quick and rapid changes in the weather. In neuroscience, when looking at the tangle of interactions and the emergence of consciousness in the brain. In anthropology, when looking at the weave of relationships, dependencies, and exchanges that make up the human system. And even in the question of creating and improving artificial intelligence, AI. Here is the problem. There is no single satisfactory definition of complexity among experts. Definitions are close but differ subtly in their wording. But these subtle differences make all the difference in how complexity is assessed. Whether we consider one system more or less complex than another. How we measure that complexity. And above all, how we take what we know to device a solution to complex problems. This also results in a lot of semantic debates and differences of opinion that keep experts arguing for hours whenever they try to define complexity. What is more, complexity in science is hugely impeded by the idiomatic use of the word complex from its use in common language way before it was a scientific concept. Complexity can commonly mean something that is hard to understand. This is not so helpful. You may have difficulty understanding how nuclear fusion in the belly of the star works, but there is no question that the lump of hydrogen and helium in our night sky is way less complex in the minds of most scientists. Compared to the string of heavier elements, intellectual design, manufacturing networks, and city power grids that go in to building and powering a light bulb. Here are two attempts at defining complexity. Firstly, a state of intricacy, complication, variety, or involvement as in the interconnected parts of the system. A quality of having many different interacting components. And secondly, when more and more varied connections and interactions take place among increasing numbers of more varied building blocks. Do we notice any problems here? Let me give you a hint. All of it. Words, words, words. A string of adjectives and nouns impeded by idiomatic impressions of complexity that sneak into the conversation. Pros that can be interpreted in different ways and lead people in two separate directions when deciding what complexity is, where it comes from, and what single thing is more complex than another. Let's put a light bulb against our brain this time. And one person might say, quite reasonably, that there is no way my brain, with all its firing neurons and calculating power, with more nodes than there are stars in the galaxy, is less complex than a light bulb. But another might person might counter with, yes, but that light bulb comes from a long process of cultural evolution where millions and millions of brains built up more and more knowledge over thousands of years to not only invent, but mass produce and distribute those light bulbs. If we are basing our understanding of complexity entirely on prose-based arguments, we are going to have a heck of a time defining complexity. Much less, getting a clear perspective on how it works. If complexity is a universal physical phenomenon, there should be a way to quantify it empirically and mathematically, just like most things in physics. Language is a heavy burden when defining scientific concepts. Each word can be very imprecise and slippery. Language is a representation of reality. One language that very accurately represents reality is mathematics. So, let's go back to basics. When we look at the complex systems in the universe over 13.8 billion years, what do we see? The rise of more complex systems, from stars to life to societies. We see an increase in the number and variety of building blocks to form their systems. We also see an increase in free energy rate density to sustain or increase the complexity of those systems. A life form needs way more energy per gram per second than a star needs to keep going, which is why it actively goes out and seeks food. A society needs even more energy. So, here we have an objective metric, a certain amount of free energy going through a certain amount of mass in a certain amount of time. A bacterium does not have more total energy than a star, not even close. But the energy required to keep something as complex as an organism going is much denser, much more concentrated. The same goes for today's society. Energy flows to create all these building blocks, sustain them and over time, increase their connections. With this measurement, one that is fairly easy to make, we get a rough metric for all complexity in the universe. One that is not dependent on prose-based arguments and slippery words. Why is understanding complexity important for analyzing problems today? Well, because we exist at a time when complexity is reaching an all-time high. This is not just because our societies involve legions of brains and many different interacting building blocks and technologies, but because the energy required to keep that system going has been intensified. Most of the problems threatening global stability in the modern era come from our global society's need for the energy to either sustain or increase our complexity and the adverse effects upon the biosphere when we harvest that energy. As such, we face a bunch of interrelated problems. How to keep the economy stable and growing? How to minimize any reparable impact on the environment? How to keep developed communities afloat while tackling a growing problem of poverty and immiserating conditions in the developing world? To do so, we need to understand complexity vary not just in business, management, ecology, government, and so forth in isolation, but understand how this each of this sectors connect to each other. To do that, we may solve one piece of the puzzle in our own workplaces while recognizing that it connects deeply with a wider network of problems and perils. Perhaps the most complex tangle of problems and perils that humanity has ever faced. [MUSIC]
