Information is Fundamental

“Normal science, the activity in which most scientists inevitably spend almost all their time, is predicated on the assumption that the scientific community knows what the world is like”
― Thomas S. Kuhn, The Structure of Scientific Revolutions

Physical scientists have become increasingly committed to physicalism over the past four centuries. Physicalism is intentionally a closed-minded philosophy: it says that only physical things exist, where physical includes matter and energy in spacetime. It seems, at first glance, to be obviously true given our modern perspective: there are no ghosts, and if there were, we should reasonably expect to see some physical evidence of them. Therefore, all that is left is physical. But this attitude is woefully blind; it completely misses the better part our existence, the world of ideas. Of course, physicalism has an answer for that — thought is physical. But are we really supposed to believe that concepts like three, red, hockey, pride, and concept are physical? They aren’t. But the physicalists are not deterred. They simply say that, sure, these things can exist in a free-floating, hypothetical sense, but that isn’t anything “real”; what “really” exists for any of these things in our minds is just a physical configuration of neurons and their associated neurochemistry. To which I would say, it is all very easy for you to declare that concepts and ideas we use every day only exist as physical configurations, but if you adopt this view you will never understand life, the brain, or the mind, or, for that matter, what understanding is. Studying by ignoring is not very illuminating.

Now, it is certainly quite true that the physicalist perspective has been amazingly successful for studying many physical things, including everything unrelated to life. However, once life enters the picture, philosophical quandaries arise around these three problems:

(a) the origin of life,
(b) the mind-body problem and
(c) the explanatory gap.

In 1859, Charles Darwin proposed an apparent solution to (a) the origin of life in On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. His answer was that life evolved naturally through small incremental changes made possible by competitive natural selection between individuals. The idea of evolution is now nearly universally endorsed by the scientific community because a vast and ever-growing body of evidence supports it while no convincing evidence refutes it. Exactly how small incremental changes can be selected was not understood in Darwin’s time, and even today’s models are superficial and miss much of the bigger picture. Two big unresolved problems in Darwin’s time were the inadequate upper limit of 100 million years for the age of the Earth and the great similarity of animals from different continents. It was nearly a century before the earth was found to be 4.5 billion years old (with life originating at least 4 billion years ago) and plate tectonics explained the separation of the continents. By the mid-20th century, evolutionary theory had developed into a paradigm known as the Modern Synthesis that standardized notions of how traits are inherited. This now classical view of vertical-descent speciation by natural selection from random mutations has been challenged by a massive increase in our knowledge of molecular biology. Some of that new knowledge will directly impact my explanation of the mind, but for now it is sufficient to recognize that life and the mind evolved over billions of years from incremental changes.

Science still draws a blank trying to solve (b) the mind-body problem. In 1637, René Descartes, after thinking about his own thoughts, concluded “that I, who was thinking them, had to be something; and observing this truth, I am thinking therefore I exist”1, which is popularly shortened to Cogito ergo sum or I think, therefore I am. Now, we still know that “three” is something that exists that is persistent and can be shared among us regardless of the myriad ways we might use our brain’s neurochemistry to hold it as an idea, so intuitively we know that Descartes was right. But officially, under the inflexible auspices of physicalism, three doesn’t exist at all. Descartes saw that ideas were a wholly different kind of thing than physical objects and that somehow the two “interacted” in the brain. The idea that two kinds of things exist at a fundamental level and that they can interact is called interactionist dualism. And I will demonstrate that interactionist dualism is the correct ontology of the natural world (an ontology is a philosophy itemizing what kinds of things exist), but not, as it turns out, the brand that Descartes devised. Descartes famously, but incorrectly, proposed that a special mental substance existed that interacted with the physical substance of the brain in the pineal gland. He presumed his mental substance occupied a realm of existence independent from our physical world which had some kind of extent in time and possibly its own kind of space, which made it similar to physical substance. We call his dualism substance dualism. We know now substance dualism is incorrect because the substance of our brains alone is sufficient to create thought.

Physicalism is an ontological monism that says only one kind of thing, physical things, exist. But what is existence? Something that exists can be discriminated on some basis or another as being distinct from other things that exist and is able to interact with them in various ways. Physical things certainly qualify, but I am claiming that concepts also qualify. They can certainly be discriminated and have their own logic of interactions. This doesn’t quite get us down to their fundamental nature, but bear with me I and I will get there soon. Physicalism sees the mind is an activity of the brain, and activities are physical events in spacetime, so it just another way of talking about the same thing. At a low level, the mind/brain consists of neurons connected in some kind of web. Physicalism endorses the idea that one can model higher levels as convenient, aggregated ways of describing lower levels with fewer words. In principle, though, higher levels can always be “reduced” to lower levels incrementally by breaking them down in enough detail. So we may see cells and organs and thoughts as conveniences of higher-level perspectives which arise from purely physical forms. I am going to demonstrate that this is false, and that cells, organs, and thoughts do not fully reduce to physical existence. The physicalists are partly right. The mind is a computational process of the brain like digestion is a biological process of the gastrointestinal system. Just as computers bundle data into variables, thinking bundles data into thoughts and concepts which may be stored as memories in neurons. Computers are clearly physical machines, so physicalists conclude that brains are also just physical machines with a “mind” process that is set up to “experience” things. This view misses the forest for the trees because neither computers nor brains are just physical machines… something more is going on that physical laws alone don’t explain.

This brings us to the third problem, (c) the explanatory gap. The explanatory gap is “the difficulty that physicalist theories have in explaining how physical properties give rise to the way things feel when they are experienced.” In the prototypical example, Joseph Levine said, “Pain is the firing of C fibers”, which provides the neurological basis but doesn’t explain the feeling of pain. Of course, we know, independently of how it feels, that the function of pain is to inform the brain that something is happening that threatens the body’s physical integrity. That the brain should have feedback loops that can assist with the maintenance of health sounds analogous to physical feedback mechanisms, so a physical explanation seems sufficient to explain pain. But why things feel the way they do, or why we should have any subjective experience at all, does not seem to follow from physical laws. Bridging this gap is called the hard problem of consciousness because no physical solution seems possible. However, once we recognize that certain nonphysical things exist as well, this problem will go away.

We can resolve these three philosophical quandaries by correcting the underlying mistake of physicalism. That mistake is in assuming that information is physical, or, alternatively, that it doesn’t exist. But information is not physical and it does exist. Ideas are information, but information is much more than just ideas. The ontology of science needs to be reframed to encompass information. I am going to iterate on this idea from several directions to build my case, but let’s start with how life, and later minds, expanded the playing field of ordinary physics. Living systems are a privileged class of physical objects that act as information processing systems, or information processors (IPs) for short. They manage heritable information using DNA as their information repository. While the information resides in the DNA, its meaning is only revealed when it is translated into biological functions via biochemical processes. Most famously, the genetic code of DNA uses four nucleotide letters to spell 64 3-letter words that map to twenty amino acids (plus start and stop). A string of amino acids forms a protein, and proteins do most of the heavy lifting of cell maintenance. But only two percent of the DNA in humans codes for proteins. Much of the rest regulates when proteins get translated, which most critically controls cell differentiation and specialization in multicellular organisms. Though we can only speculate for now about additional functions of non-coding DNA, these functions are likely to transform our understanding of genetics completely, so I will discuss some hypotheses about them later on. But, back to the storage of information, just knowing the sequence of DNA and proteins doesn’t reveal their functions; only careful study of their effects can do that. We have sequenced the human genome, but we still have a rather superficial understanding of what it does.

Animals take information a step further by processing and storing real-time information using neurochemistry in brains2. While non-animals are reactive to their environments, their reactions are either at the cellular level or are slow and rather inflexible. Animals need to vary their behavior and prioritize their actions across a much wider range of activities than plants, so an ability to assess their current circumstances and apply generalized logic to select the best course of action is critical to their survival and success. And animals go further still by using agent-centric processes within brains called minds that represent the external world to them through sensory information that is felt or experienced, They then use experienced cognition processes with cognitive information (i.e. ideas) to make decisions. This seems to fit uncontroversially into current thinking until we start asking what information really is. So long as we take it for granted as something we all understand, we can’t see it for what it is. This oversight allows physicalists to either ignore its nonphysical aspects or say that timeless features of information don’t exist in any meaningful sense. But it does exist and in a very meaningful way. In fact, meaning itself only exists nonphysically as information. So I propose that information has an entirely different kind of existence, which I generically call functional existence for reasons I will soon make apparent.

Colloquially, information is facts (as opposed to opinions) that provide reliable details about things. More formally, information is “something that exists that provides the answer to a question of some kind or resolves uncertainty.” But provides answers to who? I’m going to use the word “knowledge” to describe information within our minds’ awareness. So knowledge provides answers to us in a form we can think about. I’m going to refer to knowledge and information separately going forward so we can keep things happening in our minds distinct from things happening outside them, but keep in mind that knowledge is a kind of information. Let’s consider what questions we can answer with physical information. Suppose we have one gram of pure water at 40 degrees Fahrenheit at sea level at 41°20’N 70°0’W (which is in Nantucket Harbor). This information tells us everything knowable by our science about that gram of matter, and so could be used to answer any question or resolve any uncertainty we might have about it. Of course, the universe doesn’t represent that gram of water using the above sentence, it uses molecules, of which there are sextillions in that gram. Although it seems like this would produce astronomically complex behavior, the prevailing paradigm of physics claims a uniformity of nature in which all water molecules behave the same. Chemistry and materials science then provide many macroscopic properties that work with great uniformity as well. Materials science reduces to chemistry, and chemistry to physics, so these properties are just conveniences and not fundamentally different. So, in principle, physical laws can be used to predict the behavior of any physical thing. Quantity, temperature, pressure, and location provide the local details and the laws of the universe take care of the rest. Our knowledge of those laws is incomplete but can make quite accurate predictions in almost any situation where we have enough physical information. However, we don’t know enough to predict what living things will do.

Living things are complicated because they have microstructure down to the molecular level. Cells are pretty small but still big enough to contain trillions of molecules, all potentially doing different things, which is a lot of complexity. We can’t collect all that information and project what each molecule will do using either physics or chemistry alone. But we have found many important biochemical reactions that illuminate considerably how living things collect and use energy and matter. And physicalism maintains that given a complete enough picture of such reactions we can completely understand how life works. But this is not true at all. Perfect knowledge of the biochemistry involved would still leave us unable to predict almost anything about how a living thing will behave. Physical laws alone provide essentially no insight at all. Our understanding of biological systems depends mostly on theories of macroscopic properties that don’t reduce to physical laws. We theorize that living things are somehow internally organized so as to maintain cell walls and multicellular structure, and further to behave so as to bring in energy and materials for growth and to eliminate them as waste. From a high level, we know quite a bit about how this internal structure works, and we know it was created across billions of years of incremental changes, but we don’t have a detailed idea of how those changes came about. How did we arrive at the organizing principles of biology that suggest organisms “persist” and “replicate” using cells? “Persists” suggests a continuity analogous to rocks, and “replicate” is perhaps analogous to growth and division, like growth of a crystal and division when part of it shears off. No, it’s not that; nobody has ever seriously thought these analogies were helpful. The principles of biology came from the assumption that biological structures have functions. That life is about the survival and replication of bodies that protect their integrity has been abundantly obvious since ancient times, and our grasp of biological things also has an instinctive basis. We are living and we relate to living things. But this assumption of function is not supported by physical theory at all. Nothing about our physical theories foresaw life as a likely consequence, and we would never have even guessed machinery of this complexity could even be possible if we didn’t have it staring us in the face every day. But we see intuitively see function everywhere in life, and we freely cite it in our scientific explanations. So we can, for example, see bodies as complex machines that change over time, bringing in new material for growth and expelling old waste material, because that is their function. But how do we justify that on a physical basis if life is too complex to foresee as a physical consequence?

The justification comes from Darwin. Darwin proposed that biological function was a consequence of inductive trial and error. Ways of doing things, or functions, could become favored over time by natural selection. This at first seems counterintuitive to us, because our personal experience in life suggests that function only arises from intent, where intent is an effect or goal reached by a deductive cause. Goals reached by intent are purposes, and strategies that accomplish purposes are designs. I call actions with planning or intent maneuvers. Intent, cause, effect, goal, deduction, purpose, strategy, design, planning and maneuver are all roughly synonymous mental constructs whose substructure I will be investigating in much more detail further on, but none of them have any place or corollary in evolutionary processes. My point, for now, is only that Darwin says that function can exist without intent, and thus biology can freely cite function as a foundational principle. To the extent they ever use intent-based terminology, it is understood that this is not meant to be taken literally and inductive function is not really the same as deductive purpose. But wait, something small but important was overlooked while we were being careful to keep trial and error distinct from cause and effect. We assumed function is a physical consequence of a large number of purely physical events, and it isn’t. Function is something altogether different from the physical events that can help create it. Yes, it is true that we can now see the physical events down below, and it is tempting to reduce function to those physical events, but it doesn’t and wishful thinking won’t help.

The universe and its internal laws manage physical information in universally consistent ways. But living things collect a different kind of information at a higher level and preserve it and pass it down to succeeding generations. This biological information is derived from the feedback loops of natural selection and encoded in DNA. All information thus breaks down into physical information and derived information. For the purposes of this book, I will not need to refer again to physical information, which the universe manages quite well, so unless I say physical information explicitly all my references to information will henceforth refer to derived information. Beyond biological information, brains derive information in real-time and humans derive specific kinds of information according to many schemes. In fact, we have become accustomed to think of information in this digital age as just being the part that is encoded, but that encoded part takes for granted the existence of an IP that can use it. For organisms overall, the IP is the body and its metabolism with information stored in DNA, for the top-level control of organisms it is the brain and its processes with information stored neurochemically, and for computers it is their hardware and software and digital information. But information is not just the incremental capacity to answer a specific question, it is the whole capacity to process and act on information. The part that is encoded is usually the more interesting part because we can usually take the rest of the IP for granted, but if our goal is to understand how the IP works (in this case, the mind), then we can’t focus on just the incremental part.

Consider the following incremental piece of biological information. Bees can see ultraviolet light and we can’t. This fact builds on prevailing biological paradigms, e.g. that bees and people see light with eyes. Taken as an incremental amount of information, we knew before that animals could see, and now we know that some animals see ultraviolet as well. This fact extends what we knew, which seems simple enough. If we are a child who only knows that animals can see and bees are small flying animals that like flowers, we can now understand that bees see things in flowers that we can’t. This implicitly endorses a paradigm of animals with a functional imperative to stay alive with the help of sensory information. If we are a biologist working on bee vision, this same paradigm is sufficient for our purposes. We don’t need to know where bees came from or why they stay alive; we can just focus on the incremental information of our specialty. But if our goal is to explain bees or minds in general, we have to think about the underlying IP.

Our biological paradigm needs to define what animals and sight are, but the three philosophical quandaries of life cited above stand in the way of a detailed answer. Physicalists would say that lifeforms are just like clocks but more intricate. That is true; they are intricate machines, but, like clocks, an explanation of all their pieces, interconnections, and enabling physical forces says nothing about why they have the form they do. Living things, unlike glaciers, are shaped by feedback processes that gradually make them a better fit for what they are doing. Everything that happened to them back to their earliest ancestors about four billion years ago has contributed. It wasn’t just a series of events, but feedback events that created biological information which, I will show, can only be explained using laws of function, although information processors do this by leveraging physical laws. What is it, exactly, about the feedback processes that created life that creates this new kind of entity called information and what is the substance of the information? The answer to both questions is actually the same definition given for information above, the reduction of uncertainty, which can also be phrased as an ability to predict the future with better odds than random chance. One could only know the future in advance with certainty given perfect knowledge of the present and a perfectly deterministic universe. But we can never get perfect knowledge because we can’t measure everything and because quantum uncertainty limits what we can know about how it will behave. But biological information is not about perfect predictions, only approximate ones. A prediction that is right more than it is wrong can arise in a physical system if it can use feedback from a set of situations to make generalized guesses about future situations that can be deemed similar. That similarity, measured any way you like, carries predictive information by exploiting the uniformity of nature, which makes situations that are sufficiently similar usually behave similarly. It’s not magic, but it seems like magic relative to conventional laws of physics, which have no framework for measuring similarity. Such a framework can only arise from generalizations made from feedback, and those generalizations are the biological information. A physical system with this capacity is exceptionally nontrivial — living systems took billions of years to evolve into impressive IPs that now centrally manage their heritable information using DNA. Animals then spent hundreds of millions of years evolving minds that manage real-time information using neurochemistry. Finally, we humans have built IPs that manage small sets of information (relative to living things and minds) using either standardized practices (e.g. by institutions) or computers.

A functional entity has the capacity to do something useful, where useful means to be able to engage in the sorts of actions that will result in outcomes substantially similar to outcomes seen previously. A function can apply information to predict the future which can then be used to change the future, but the function itself is the capacity to do these things, regardless of whether they are done. Physical matter and energy are comprised of a vast number of small pieces whose behavior is relatively well-understood using physical laws. Functional entities are comprised of capacities. Both are natural phenomena. Until information processing came along through life, there was no function on earth. But now life has introduced an uncountable number of functions in the form of biological traits. As Eugene Koonin of the National Center for Biotechnology Information puts it, “The biologically relevant concept of information has to do with ‘meaning’, i.e. encoding various biological functions with various degrees of evolutionary conservation.”3 The mechanism behind each trait is itself purely physical, but the fact that the trait “works” across a certain “range” of circumstances is because “works” and “range” generalize an abstract capacity, which one could call the reason for the trait or its function. The traits don’t know why they work, because knowledge is a function of minds, but utility across a generalized range of situations causes them to form. That why is not a physical property of the DNA, it is a functional property.

The moment functional existence starts to arise independent of physical existence is the moment that feedback from prior situations starts to be applied to new situations, which necessarily employs generalized, statistical approaches. Being able to use this experience, captured somehow as information, constitutes a functional performance rather than merely a physical action. The act of generalizing creates abstractions, which can loosely be thought of as categories, that are about something else that is not directly connected to them. This act of indirection is the point of detachment where functional existence arises and (in a sense) leaves physical existence behind. This generalized, indirect “link” is actually a capacity to make a connection or correlation in the future based on similarity. Note that this kind of indirect information can arise from inductive trial-and-error or deductive cause-and-effect. I am not suggesting that all information is representational; that is too strong a position. Information is necessarily “about” something else, but only in the sense that its application does go from a generality to something specific. The defining characteristic of information is only that it is useful, where useful means that it can help lead to performances that have a better than random chance of producing expected results.

To clarify further, we can now see that all functional entities are necessarily generalities and all physical entities are necessarily specifics. We can break a generality down into increasingly specific subcategories, but they still always be generalities because they are still categories that could potentially refer to multiple physical things. Even proper nouns are still generalities… a given quark detected in a particle accelerator, or my left foot, or Paris refer to specific physical things, but are generalized across time and subject to general properties of how we model them. But those things themselves do have specific parts.

Biological change results from small physical changes to DNA which impact its functions, but natural selection is focused entirely on the functions and not the physical changes, so that is what it captures. You could say that information and function piggyback off physical mechanisms. Sometimes the physical nature closely aligns with the functional nature and we can speak confidently about two together without significant fear of inaccuracy or confusion. Hearts pump blood because bodies need circulation. The form and function line up very closely in an obvious way. We can pretty confidently expect that all animals with hearts will continue to have them in future designs to fulfill their need for circulation. On the other hand, the genetic trigger that results in an organism being male or female has shifted in some gene lines to a completely different physical mechanism using entirely different chromosomes (volumes of DNA in each cell), but males and females still exist as before to fulfill the necessary function of sex. For example, two species of mole voles, small rodents of Asia, have no Y chromosome, so males have XX chromosomes like females. We don’t know what trigger creates male mole voles, but this change is not entirely unexpected because Y chromosomes shrink and will eventually fail.456 A physical mechanism is necessary, and so only possible physical mechanisms can be employed, but the selection between physical mechanisms has nothing to do with their physical merits and only to do with their functional contribution. As we move into the area of mental functions, the link between physical mechanisms and mental functions becomes increasingly abstracted, effectively making the prediction of animal behavior based on physical knowledge alone impossible.

One can’t define or count generalities with perfect precision, but that doesn’t mean they don’t exist and can’t be delineated. It just means that our study of traits and functions in general is itself a generalized exercise, subject to its own constraints of similarity of matching. That said, we can achieve a very high level of confidence that we have correctly described certain traits, even though our information is still incomplete. For example, we know that bee eyes have cone cells with a photopigment that is most sensitive to 344nm light in the ultraviolet range and the human eyes do not. We know bees need to be good at discriminating flowers, and so we can be fairly certain that the function of seeing ultraviolet light is a rather discrete function that is preserved in bees for this reason.78 Again, physical mechanisms are limiting factors, but not nearly so limiting as the constraint by natural selection to useful functions.

It is important to note that evolution creates capacities, which are functional entities whose defining characteristics relate to their utility, but it does not record the reasons it creates the capacities. As I just noted above, we can sometimes infer reasons for these capacities that are highly predictive and which we therefore may be inclined to think of as “right”. But we have to keep in mind that our attempts to explain evolutionary systems using deductive cause-and-effect is not the way they were formed. They were formed with inductive trial-and-error. Feedback from many trials and errors and successes will produce a solution that has been subtly influenced by a much longer list of factors than any deductive model could ever enumerate. Our feeling of understanding depends on deductive models that are supported by inductive information, but biological information below the upper levels of minds are all inductive, not deductive, and so can’t really be fully understood. Understanding is inherently an approximate venture. It characterizes things into buckets which may usually hold but won’t always hold. Or, rather, deductive models can be internally perfect, but once we imply them to circumstances not governed strictly by their perfect logic, we have to expect that the match will only be approximate.

Let’s review where we are. An information processor or IP is physical construction like a living thing or a computer that manages information. Information consists of functional entities that are nonphysical generalizations that are abstracted away from any physical referent by virtue of not necessarily referring to anything specific. Something exists if it can be distinctly discriminated from other things that exist and can interact with them in various ways. Physical things exist specifically and functional things exist generally, and both of these kinds of existence can be distinguished and can form interactions. Consequently, we can conclude that interactionist dualism is true after all. The idea that something’s existence can be defined in terms of the value it produces is called functionalism. For this reason, I call my brand of interactionist dualism form and function dualism, in which physical substance is “form” and information is “function”. As an interactionist, I hold that form and function somehow interact in the mind. To clarify that interaction, I am going to further subdivide function into five groups, the first two of which apply to form as well:

Noumenon – the thing-in-itself. Daniel Dennett calls a functional entity’s noumenon its “free-floating rationale”9

Phenomenon – that which can be observed about a noumenon

Perception – first-order information from the reception of phenomena by an information processor (IP) and their conversion into information

Comprehension – second-order information from deductive models with the inductive information supporting them

Reflection – third-order information from steering information processing in potentially any direction in an exploratory way, including back on itself

I’m going to discuss these briefly in turn before returning to the three philosophical quandaries of life.

We believe that physical matter and energy exist, but we can’t know for sure because they are in one place and we are in another. The term for the existence of a physical object completely independent of us is noumenon, or thing-in-itself (what Kant called das Ding an sich). The only way we can ever come to know anything about noumena is through phenomena, which are emanations from or interactions with the noumenon. Features of noumena that exhibit no phenomena are completely unknowable outside the things themselves. Example phenomena include light or sound bouncing off an object, but can also include matter and energy interactions like touch, smell, and temperature. Since all our knowledge of the world must be contained in our minds, it is all indirect knowledge based on phenomena. But because of the uniformity of nature, we can be quite confident of many things about the noumena to which they refer, even though we can never be certain of their real nature. Now, for my purposes here, if a tree falls in the forest and there is nobody to hear it, there was a phenomenon but no perception. Perception is the receipt of a phenomenon by a sensor and sufficient concomitant information processing to create information about it. Perception creates first-order information, which is based on inductive trial-and-error. Inductive reasoning or “bottom-up logic” generalizes conclusions from multiple experiences based on similarities. Although the term perception is usually restricted to a mental activity, I have generalized the definition here to say that all inherited genetic information is created through perception.

Comprehension is qualitatively more elaborate than perception because it invokes deductive models based on causes and effects. A model is a system of information that can be followed or imitated based on similarities. Models are therefore necessarily representational, but are not necessarily deductive as the mind creates models inductively as well. Deductive reasoning or “top-down logic” involves use of a model with clear logical rules that link premises to conclusions or causes to effects. Those premises and conclusions in the model are then frequently mapped to sufficiently similar circumstances in the physical world using inductive mapping techniques. Usually, but not always, a substantial part of our understanding of a deductive model depends on our inductive sense of the meaning of the premises and conclusions. This inductive sense is based on our senses, feelings, common sense and intuitions about things, which do not themselves give us a comprehension of them. While can’t say we comprehend these inductive senses because we don’t know why we have them, but we will sometimes say we understand them, which is a lower bar than comprehension that can include knowing how to use information without knowing why. The premises and conclusions of deductive models are called concepts, which are the self-contained building blocks of deductive logic. I will go into more detail on concepts later on.

Reflection is a term I have coined for which I know no better common name, though free association comes close. Reflection is the ability to think about what we are thinking about so as to steer our thought in promising directions. It builds on comprehension because in order to manipulate thoughts we have to compartmentalize them into concepts first, which requires deductive modeling. But this is not to say all thinking is deductive; we can think about our senses, feelings, common sense and intuitions as well and form concepts about them which we can reflect on. Reflection is arguably the cognitive trait that most separates humans from other animals. We are both capable and inclined to let our thoughts move in directions that we feel are likely to lead to useful solutions. Just why humans are more inclined is a subject I will explore later.

Both physical things and functional things that leverage physical IPs can produce physical effects in the physical world. I call purely physical effects “actions” and physical effects caused by functional things “performances” to indicate their functional origin. Functional things can also produce functional effects without any physical effects. They can do this on a hypothetical basis, in which case nothing physical happens at all, we just recognize that a given functional system has the capacity to produce certain effects in a “free-floating” way. Or, they can do it using simulations, which are physical processes that project functional implications without acting on them further.

Physical things have noumena and phenomena, but never have perception, comprehension or reflection as they contain no derived information. Functional things, of course, include perception, comprehension, and reflection, but can also be said to have noumena and phenomena. Daniel Dennett calls the explanations behind evolutionary designs “free-floating rationales”, because they don’t exist in time or space or require anyone to understand them or even know they are there. Like the number of corners on a cube, the underlying value of an evolutionary design has a claim to existence whether anyone knows it or not.10 This is a good way of putting it, though we have to remember that evolutionary rationales are based on inductive trial-and-error while the corners of a cube are based on deductive cause-and-effect, because cubes and their corners are concepts in certain mathematical deductive models. Unlike physical noumena, which are apart from us and hence not directly knowable, deductive functional noumena are defined by us and hence fully knowable. But inductive functional noumena that were created from the subtle effects of many events are also apart from us and so our knowledge of them must be gathered from their phenomena. Functional noumena have phenomena which we observe by considering the effects of performances produced by them. In other words, the inductive functional noumena themselves are capacities which we can’t know directly, but when they perform we can evaluate their effects to gain insight into their underlying function. These functions define the functional noumena, because information is defined in terms of the value it produces. We learn evolutionary functions by studying living things looking for patterns and then use reverse-engineering to propose cause and effect explanations that approximate the functional noumena that are really based on trial and error. Although we can’t truly know these inductive noumena directly, our deductive explanations of them can approximate them to a high degree of effectiveness. In a similar way, the laws of physics and chemistry are deductive explanations of inductive systems that approximate them very effectively but don’t really reveal the underlying fabric of matter or energy. In both cases, the uniformity of nature is our best friend in getting deductive models to actually align with inductive observations.

We generally don’t need to contemplate phenomena of deductive noumena because we know the rules the things-themselves follow. However, sometimes rules get complicated and it can be hard to work out all their implications, and for these cases it can be helpful to run simulations and evaluate the generated phenomena to get a better idea how the model behaves. This creates a composite deductive/inductive model because the information we glean from the phenomena is inductive, at least until we can figure out a way to prove it.

Let’s review our three quandaries in the light of form and function dualism. First, the origin of life. Phenomena naturally occur and their effects comprise the canon of the laws of physics, chemistry, materials science and all physical sciences. These sciences work out rules that describe the interactions of matter and energy. They essentially define matter and energy in terms of their interactions without really concerning themselves with their noumenal nature. A new kind of existence, functional in nature, arises with perception, which finds patterns in nature that can be exploited in “useful’ ways. The use that concerns them is survival, or the propagation of function for its own sake, but that use is sufficient to drive functional change. But perception forms its own rules transcendent to physical laws because it uses patterns to learn new patterns. It exploits that fact that natural systems configured to do so can be shaped by functional objectives and not just physical destiny.

Next, let’s consider the mind-body problem. The essence of this problem is the perception that what is happening in the mind is of an entirely different quality than the physical events of the external world. Form and function dualism tells us that they do have an entirely different quality, because the mind is entirely concerned with functional entities and the external world is largely concerned with physical entities, although a particularly relevant part is external functional entities like other people, living things, and artifacts. This division is not reducible at all, as physicalists would have us believe, because function is concerned with and defined by what is possible and physical things have no concerns. Concern and purpose only exist in a hypothetical sense, but that sense is a legitimate form of existence because our minds have the physical means to manipulate these abstractions and apply them to the world. One could fairly call our functional essence the “soul”, not as a supernatural entity but as a natural entity comprised of a complex of functional capacities implemented using the physical machinery of the brain.

Finally, let’s look at the explanatory gap. I said this gap would evaporate with an expanded ontology. By recognizing functional existence for what it is, we can see that it opens up a vastly richer space that physical existence because it can relate anything to anything in any number of ways. The world of imagination is unbounded, while the physical world is closely ruled by seemingly very rigid laws. The creation of IPs that can generalize first inductively and then deductively gave them the capacity to access this unbounded world. Physical circumstances are always finite, but through finite access one can gain unlimited capacities because capacities are not yet constrained to specific circumstances. So to close the explanatory gap and explain what it is like to feel something, we should first recognize that the target range of experience and understanding was never physical, it was functional. Next, it stand to reason that things will “feel” like what they can do, their capacity. This makes no sense from a physical perspective, but it is entirely what we should expect from function at things, which are defined by what they can do. But what would that look like in practice? Keeping in mind that I haven’t yet broached the question of why brains have minds that experience things consciously, if we accept that they do and that minds help brains with their task of controlling the body, and brains develop and use information relevant to that control, then it follows that if minds had a subjective perspective (which they do), it would center around developing control information. If the computational theory of mind is true that the mind is a process running in the brain, then its whole reality is information processing in our heads and is not our bodies or the external world, although it seems to us that our minds have direct access to those things. This means that feelings are just information, and since information is just the capacity to do things, we can conclude that feelings are a translation of what that information empowers us to do.

Let’s take a look at our world of experience to see how it feels like what it can do. Senses seem at first indifferent to what we might do with the information. Colors and sounds are pretty or interesting but don’t seem to feel like what they can do. But that isn’t really true. Yes, most of the colors and sounds we see and hear don’t carry information that we need to act on. We still automatically categorize them into thousands or millions of varieties. Those colors and sounds can trigger any number of instinctive or learned associations and associated behaviors, based on the raw sensory impressions themselves or on objects or experiences recognized from them. Blues and greens are famously considered to feel more safe and calming than reds and yellows, presumably because both instinct and experience are likely to suggest that blues and greens are harmless background colors but reds and yellows represent dangerous or helpful items. Sudden loud noises feel scary because both instinct and experience suggest they are dangerous, while continuous noises are more likely to be harmless features of the background. Extrapolating further, all our emotions inspire us to act in ways that use their implied information in helpful ways. Arguably, the brain could come up with other ways to lead it to act in helpful ways without having a subprocess of mind “feel” functionality in a visceral way, but what if this approach just worked a lot better than any other alternative. I will argue later that this is exactly what is happening. For now though, just to show that the explanatory gap can be closed, we only have to recognize that minds have subjective experiences because it is a way of processing the functions relevant to them in an effective way. Although the feelings seem somewhat amazing to us, this is just an artifact of how the brain runs the specific process we call consciousness to implement high-level functions in the brain. States of mind can thus be seen to be analogous to functions of the bodily organs: the organs perform distinct physical functions in a physical environment, while the mind performs distinct functional functions in a functional environment. That functions can be segregated this way is therefore not surprising. Later I will provide a more detailed argument as to why subjectivity is necessary and why feelings feel precisely as they do.

To summarize this initial defense of dualism, I propose that form and function, also called physical and functional existence, encompass the totality of possible existence. We have evidence of physical things in our natural universe. We could potentially someday acquire evidence of other kinds of physical things from other universes, and they would still be physical, just not in the way we know. Functional existence needs no time or space, but for physical creatures to benefit from it there must be a way for functional existence to manifest in a physical universe. Fortunately, the feedback loops necessary for that to happen are physically possible and have arisen through evolution, and have then gone further to develop minds which can not only perceive, but can also comprehend and reflect. Note that this naturalistic view is entirely scientific, provided one expands the ontology of science to include functional things (which I will discuss more later), and yet it is entirely consistent with both common sense and conventional wisdom, which hold that “life force” is something fundamentally lacking in inanimate matter. That “life force” is also evident in artifacts because what we are really sensing is the presence of function through derived information. It isn’t magic, but some of its noumenal mystery is intrinsically beyond complete understanding. But our understanding of life and the mind through closer and closer approximation from deductive cause and effect models will continue to grow until it rivals our understanding of things not shaped by life.

  1. René Descartes, Discourse on the Method, 1637, Oxford University Press, 2006, part four, p 28
  2. Though plants, and probably all lifeforms, also have limited real-time information processing and storage capacities; more on this later
  3. Eugene V. Koonin, The meaning of biological information, Philos Trans A Math Phys Eng Sci. 2016 Mar 13; 374(2063): 20150065.
  4. Jennifer A Marshall Graves and Catherine L Peichel, Are homologies in vertebrate sex determination due to shared ancestry or to limited options?
  5. Transcaucasian mole vole, Wikipedia
  6. Emily Singer, The Incredible Shrinking Sex Chromosome, Quanta Magazine
  7. Could humans acquire the ability to see ultraviolet light? Well, reindeer did acquire this ability, presumably because the Arctic is rich in UV-light from snow and ice, but they don’t have a specific photopigment like bees. “Genetic analysis reveals that sensitivity to such short wavelengths is not mediated by a separate UV receptor.” It seems instead that reindeer see UV light using blue photopigments much like ours. We can’t see it because UV is filtered out to prevent damage to our retinas. Reindeer didn’t so much evolve an ability to see UV as an ability to protect their retinas from UV damage.
  8. Christopher Hog et al, Arctic reindeer extend their visual range into the ultraviolet, Journal of Experimental Biology 2011 214: 2014-2019; doi: 10.1242/jeb.053553
  9. Dennett, Daniel C., From Bacteria to Bach and Back Again: The Evolution of Minds, W. W. Norton & Co, 2017
  10. Dennett, Daniel C., From Bacteria to Bach and Back Again: The Evolution of Minds, W. W. Norton & Co, 2017

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