The Origami Brain and Cognitive Depth
Are you ready to have your mind blown? The parallels between Transformer models (i.e., GPT-3) and Nick Chater’s “The Mind is Flat” are too intriguing to ignore. Chater’s thesis challenges the notion of cognitive depth, arguing that our minds are actually shallow and driven by a just-in-time fluency and improvisation. This groundbreaking idea is bound to spark a lively debate and change the way we think about the human mind.
Feynman’s famous words, “The first principle is that you must not fool yourself,” have long been considered the cornerstone of scientific inquiry. But what if this principle goes even deeper than we think? The mind is flat thesis delves into the idea of self-deception, challenging our very understanding of the human mind. Are we truly as self-aware as we believe, or are we all just fooling ourselves?
The mystery of consciousness is closely related to the idea of the mind being flat, as both concepts challenge our understanding of the self and the human mind. The illusion of depth, or the idea that our minds are capable of complex and deep thought, is orthogonal to the illusion of continuity that consciousness creates. Continuity is necessary to generate the illusion of identity, which is the foundation of our sense of self. Without this sense of identity, we would not have a concept of self. This suggests that the illusion of depth and the illusion of continuity are intertwined, and both are essential to the experience of consciousness.
But can we function without the illusion of depth? Why is this illusion so crucial for our human cognition? It seems intuitive that human cognition must be deeper than animal cognition. But what does a theory of mind without depth imply?
Do you ever stop to think about where your thoughts come from? The question we must unravel is: where does cognitive depth come from? The model we carry around is that there’s a continuous brain process that churns through our past experiences. It’s like an ocean where unconscious thoughts surface from the depths. But is this model accurate?
If this is all true, how is the illusion of depth rendered? Is it rendered in the same way as GPT-3, where it’s nothing more than an automatic process of deception? Is the human mind just a con artist, tricking us into thinking we have deep thoughts when we don’t?
Ian McChilchrist writes about the left and right brain and the differences between the two hemispheres. One interesting aspect he discusses is the behavior of split-brain patients, who have had the corpus callosum (the nerve fibers that connect the two hemispheres) severed. In these patients, the left hemisphere is known to be a “BS artist,” meaning that it will come up with explanations for things that are not supported by evidence. This suggests that the left brain is devoid of grounding, and that fluency (the ability to speak or write easily and fluently) is not necessarily a reflection of comprehension. This is intriguing because it challenges the idea that the left hemisphere is always the logical and rational part of the brain, and suggests that it can sometimes be prone to making up stories and explanations without any basis in reality.
The behavior of split-brain patients described above can be linked to the idea of the left and right hemispheres working in parallel to evaluate and make sense of the world. The left hemisphere is known to act like a generator, coming up with explanations and stories, while the right hemisphere acts like a scorer, evaluating these explanations and determining whether they are true or not. In split-brain patients, the left hemisphere is able to generate explanations without the right hemisphere to evaluate them, which is why it can sometimes come up with false or baseless explanations. This suggests that the left and right hemispheres play complementary roles in our cognitive processes, with the left generating ideas and the right evaluating them. These two processes work in parallel to coordinate our thoughts and understand the world around us.
The illusion of depth in our thinking may originate in the right hemisphere of the brain, the empathic side that processes emotional and intuitive information. Empathy is a type of cognition that relies on our ability to understand and respond to the emotions and intentions of others. It is an intuitive process, often referred to as System 1 cognition, that allows us to quickly and automatically interpret the subtle, implicit cues that we receive from others. Through empathy, we are able to recognize another person’s emotions and intentions, even in complex and unique contexts. This ability to understand others on an intuitive level may be the source of the illusion of depth in our thinking, as it allows us to see beyond the surface level of a situation and understand the underlying emotions and intentions that drive it.
The right side of the brain is critical for decision making because it is responsible for evaluating different options and determining the best course of action. Without access to the right hemisphere, a person would be unable to make decisions effectively. This is because the right hemisphere is involved in both conscious and subconscious processes, and is able to evaluate information on both a conscious and intuitive level. The illusion of depth in our thinking may be a consequence of this ability to access and evaluate information on both a conscious and subconscious level, as the right hemisphere allows us to understand and respond to the world in a more nuanced and sophisticated way. This ability to evaluate options on multiple levels is what enables us to make effective decisions.
The idea of symbol grounding and relevance realization is closely connected to the processes that take place in the right hemisphere of the brain. Symbol grounding refers to the process by which we give meaning to words and symbols, while relevance realization is the ability to understand the relevance of information in a given context. Both of these processes rely on intuition and empathy, which are abilities that are forged through participatory knowing. In other words, our understanding of the meaning and relevance of words comes from our ability to participate in and understand the emotions and intentions of others. This is why the right hemisphere is so critical for these processes, as it is the part of the brain that is responsible for our ability to empathize and understand others.
Contrary to the idea that cognitive depth is an illusion, it may actually be a consequence of the iterative and recursive nature of the process of knowing. Knowing is not a one-time event, but rather a continuous process of building and refining our understanding of the world. It is this iterative nature of knowing that gives rise to the concept of depth in our cognition. However, our tendency to focus on end-states and final outcomes often leads us to overlook the richness and complexity of this process. This is why our substance metaphysics, which emphasizes the end-states of knowing, can lead us to see the mind as shallow rather than deep. In reality, the depth of our cognition is a consequence of the iterative and recursive nature of the process of knowing.
In mathematics, there is a concept known as logical depth, which was introduced by the computer scientist Charles Bennett. Logical depth is a measure of the complexity of a computational process, and is distinct from the complexity of the resulting output. In other words, logical depth is a measure of the difficulty and intricacy of the process that leads to a given result, rather than the complexity of the result itself. Unfortunately, from the perspective of substance metaphysics, which emphasizes the end-states of knowing, it can be unintuitive to think that a complex process can lead to a less complex output. However, this is exactly what happens in many computational processes, where a complex series of steps can lead to a relatively simple result. Understanding the concept of logical depth can help us to see the mind and cognition in a new light, and appreciate the complexity and depth of the processes that underlie our thoughts and actions.
In computer science, it is important to note that pessimistic algorithms, which are designed to prevent exceptional conditions, are typically more complex than optimistic algorithms, which are designed to handle exceptional conditions on the fly. This is because pessimistic algorithms must anticipate and account for a wide range of potential exceptional conditions, whereas optimistic algorithms can rely on just-in-time resolution to handle these conditions as they arise. This preference for just-in-time algorithms is reflected in the improvisational nature of the human brain, which is able to quickly adapt to changing circumstances and resolve exceptional conditions on the fly. This suggests that the human brain may have evolved to prioritize efficiency and flexibility over absolute certainty, and that our preference for just-in-time algorithms may be a reflection of this evolutionary preference.
The use of just-in-time algorithms in both computer science and the human brain is an example of the pervasive idea of balance that is found throughout biology. Just-in-time algorithms are homeostatic algorithms that seek to maintain a dynamic balance of identity within the context of a complex and constantly changing environment. This allows organisms to adapt to their surroundings and maintain their identity even as the external environment shifts and changes. This kind of rote adaptiveness has been forged through billions of years of evolution, and is a fundamental characteristic of biological systems.
Rote adaptive algorithms are algorithms that are designed to quickly and automatically adapt to changing conditions. These algorithms are intrinsically creative, because they rely on the interpretation of non-symbolic signs to generate variation. This variation is a consequence of the use of inductive and abductive inference, which are forms of reasoning that allow us to draw conclusions and make predictions based on incomplete or uncertain information. As the complexity of the algorithm increases, so too does the amount of variation that it is able to generate. This is because the logical depth of an algorithm, which is a measure of its complexity, directly influences the amount of variation that it can produce. In this way, rote adaptive algorithms are able to harness the power of creativity and variation to adapt to changing conditions and thrive in complex environments.
In conclusion, the mind is not flat, as previously thought, but rather is a complex and dynamic structure that is analogous to origami. Just as an origami structure is created by folding paper in specific ways to create intricate and beautiful patterns, the mind is created by folding information and experience in specific ways to create deep and sophisticated cognitive processes. Each fold in the mind leads to a greater logical depth, allowing us to think and reason in increasingly complex and sophisticated ways. But these folds are not literal folds in the brain, but rather are virtual folds, the result of a long and complex evolutionary process that has shaped the human mind over millions of years. In this way, the mind is a dynamic and ever-evolving structure, constantly adapting and changing to meet the demands of a complex and changing world.
Disclaimer: This text and image are generated with the aid of Artificial Intelligence.