Introducing Three of the Teleological Stance's Tools for Self-Optimization and Self-Actualization
How can the free energy principle, the law of requisite variety, and Bayesian reasoning improve your life? By tuning your model to match the complexity of the world around you, you can live optimally.
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This article builds on the last one—Turn Your Life Into a Game With the Teleological Stance and Learn to Live Life Optimally—which is available to all, but only scratches the surface of the subject. It is recommended that one read it before reading this post, though not required. Simply stated, the teleological stance is a system for self-optimization and self-actualization that emerges from the Integrated Evolutionary Synthesis, the unifying theory of reality described in my new book The Romance of Reality: How the Universe Organizes Itself to Create Life, Consciousness, and Cosmic Complexity.
This unifying theory can be told in terms of a simple cosmic story, and it is a story that involves you, so its relevance to your life quickly becomes apparent. It is also a way to teach almost all of the major sciences at once, and this framing is already revolutionizing the world of biology, neuroscience, psychology, and artificial intelligence. While I discovered this story through the field of non-equilibrium thermodynamics—which is essentially the science of self-organized systems—I soon found the same narrative in Karl Friston’s free energy principle.
The magazine Wired recently called the free energy principle “the most all-encompassing idea since the theory of natural selection,” also adding that it “could hold the key to true AI.” The Integrated Evolutionary Synthesis integrates the free energy principle with the theory of natural selection into a coherent framework that Friston called “a quite remarkable synthesis of all my favorite things.” This article will briefly introduce the free energy principle in the context of the game we have called the “Game of Life.”
Since the previous article on the teleological stance explained quite a bit about its cosmic context and potential benefits, this article is going to get right into the meat of the system, with a specific focus on how you can tune your “world model” (your lens for understanding and predicting the world) to be optimally accurately and sufficiently complex, which means not overly simple but also not overly complicated. These insights are based on 1) the free energy principle, 2) the law of requisite variety, and 3) Bayesian reasoning. The first few paragraphs are taken verbatim from the last post to orient the reader before moving on to the new concepts.
Optimizing Your World Model With The Teleological Stance
The Integrated Evolutionary Synthesis starts with what many consider to be the most important law in all of physics, the almighty second law of thermodynamics. The second law can be summarized simply as “Things fall apart.” In other words, systems naturally tend toward decay and disorder. The technical term for disorder is “entropy,” and because the second law says entropy tends to increase, nature is constantly pulling us toward death.
In his 1944 book What is LIfe?, the quantum physicist Erwin Schrodinger explained that a biological system can avoid the tendency toward decay (or keep its internal entropy low) by feeding on “negative entropy” in the environment. Negative entropy was Schrodinger’s name for free energy—which is simply the available energy in the world that can be used to do physical work. Free energy allows an ordered system to stay ordered so that it may continue playing the Game of Life.
As animals, we consume free energy by eating food, which gets turned into mechanical work through the process of metabolism. Similarly, plants absorb free energy from sunlight and convert it into work through the process of photosynthesis. If an organism does not continually absorb energy, it will die and it will undergo entropic decay until the ordered system is no longer intact. When an energy-starved organism succumbs to the effects of the second law, the Game of Life has come to end for that player. If we choose not to play the game—that is, if we do nothing at all—we will soon cease to exist.
This fact makes it easy to see how the natural tendency toward disorder creates an intrinsic goal for all living systems, which turns life into a game of sorts and gives it a purpose. To continue persisting in a world that abides by the second law—to continue playing the Game of Life—we must be able to capture free energy, and we must be able to do so while avoiding threats.
However, navigating one’s environment in a chaotic and constantly changing world is no easy task. It requires that the living system acquire information about the environment, because that information reduces the organism’s uncertainty or ignorance about the relevant variables of the world it is embedded in. We may call the information that reduces an organism’s uncertainty knowledge. Evolutionary adaptation is therefore a learning process, and learning processes can also be seen as a form of adaptation. This was the insight of Karl Popper, and the basis for the influential philosophy known as evolutionary epistemology (which provided a basis for universal Darwinism, proposed by Richard Dawkins and Daniel Dennett).
Based on the same logic, one may also say that to survive an organism must acquire a map or model of its environment. This model is the result of knowledge accumulation, and an agent’s model can be thought of as being comprised of “beliefs” about the world, or what it expects to encounter. This model is a predictive model, which allows the organism to anticipate events in a complex world.
In humans and other animals, this predictive model is encoded in our brains, and it represents what we think of as the “mind.” Our mind consists of many different mental models that allow us to achieve our goals and make sense of a complicated and confusing reality. The teleological stance is an example of a mental model that represents a small slice of our more comprehensive world model (the sum of all our mental models).
Want proof that you are an observer with a model of the world inside your head? Close your eyes and try to envision yourself in a room. Zoom out to see your house and your neighborhood from a bird’s-eye view. Zoom out and see the planet Earth from space. Now imagine a friend sitting next to you in your room. You have not only modeled the world in your brain, you have modeled other modelers, and those familiar agents come to life in your dreams, complete with personalities and trademark quirks!
Because you exist as an agent in the world you are modeling, you have also modeled yourself. Close your eyes and try to picture yourself from above right now. Now ask yourself, how accurate is your model of you?
Even the simple organisms that lack brains can be said to encode an abstract model of the world in their genome, which is the first type of knowledge repository (memory system) that evolution produced. For example, a bacterium performing a function known as chemotaxis will swim toward chemical food and away from poisonous toxins. A plant will perform an analogous function known as heliotropism, such that it will track the sun across the sky, continuously moving in its general direction. These organisms would not be able to perform these functions if they did not have some internal representation of the biologically-relevant variables of the world encoded in memory.
David Krakauer, an evolutionary biologist who is President of the Santa Fe Institute, explains that the essence of life is its tendency to model the world:
“Life seeks to represent the world in which it lives: to encode reality. That is what a genome does. That is what a brain does. And the initial impetus towards that kind of reflection of the universe in living matter is not that well understood, I’d say.”
At this point in the story we have firmly established why life can be understood as a system that maintains its existence against the tendency toward disorder by mapping out the relevant features of the world it must survive in. Out of this simple idea—that the success of an organism depends on the accuracy and adaptability of its world model—comes a plethora of principles for optimizing that model, which can improve your decision-making and strategies for success.
The teleological stance is not your traditional self-help system because it has an empirical basis. While it is easy enough to see why all organisms must contain some map of the world that allows them to survive, the good regulator theorem is a principle from cybernetics that provides a mathematical expression for why this must be true. The good regulator theorem was introduced by Ross Ashby and Roger Conant in an influential 1970 paper titled “Every Good Regulator of a System Must Be a Model of That System”. Six years later, the theorem would be repackaged as the internal model principle, which is a critical component of the engineering field known as control theory. The good regulator theorem—as applied to evolutionary biology—states that any adaptive system must possess a model of the environment to continue persisting. This theorem is important because it provides a foundation for three principles that we will keep coming back to when we talk about the teleological stance: the free energy principle, the law of requisite variety, and Bayes’ rule.