The Process That Solves All Possible Problems

Problem-Solving

I want to talk about problem solving , and make some connections to art appreciation. Specifically, the single process that has the ability to solve all possible problems.

You might know it by different names:

Trial and Error
Guess and Check
Variation and Selection
Conjecture and Criticism
Blind Variation and Selective Retention

These all just about mean the same thing, describing the necessary process for the growth of knowledge in all domains.

This is our interest: knowledge creation. In biology, in science, in art, in relationships, in all domains.

But beyond just knowledge creation, we want to specifically solve any possible problem in all domains, so we have to expand this process.

We know we need an expansion because biological evolution and human thought both involve variation and selection, but human knowledge creation is much more powerful than biological creation.

One big difference is that for the growth of knowledge in biology, every variation must be in an organism that can survive and reproduce. In human knowledge creation, not every idea has to be individually viable to progress the growth of knowledge.

So it must involve something more than just variation and selection.

I am starting mostly with ideas from David Deutsch’s The Fabric of Reality (Chapter 3: Problem Solving), and I am expanding and translating it to fit my thinking on the subject.

I’ll give you the full 5-Step Process and then fill in the details.

The 5-Step Process

Attention
Guess
Alternatives
Selection
Progress

To have a mind that is able to solve all possible problems, it is important for each step in this process to be present, and for the criteria of each to be open-ended. None of these should be fixed.

By open-ended, I do not mean “anything goes.” It just means no criteria is final. Each criteria is always subject to replacement.

If any step is removed, you come to very special errors and inefficiencies. With each step present, it is possible to begin the unbounded growth of knowledge, without the need for ultimate justifications or foundations.

I will describe each step in detail.

1. Attention

Attention is where we typically think of “finding problems.” Really, this is where we notice any inadequacy of any theory or idea. You can think of this as a conflict between two ideas. But really, it can be any reason to have your attention directed somewhere.

This is highly personal and based on the context of your life. What you think is a problem is up to you. Problems are always personal. David Deutsch likes to say all problems are parochial.

It is fine to just think of this step as the identification of a problem. Attention is just a little more broad.

If you have no attention, then all of your guesses are totally random.

It also makes other things more difficult. Like, how could you determine what is an alternative guess if there is no problem? How do you select the best of the alternatives if you have nothing to address? You cannot.

If you do not have attention, problems will be solved very inefficiently.

An example here is biological evolution. There is no systematic way to direct which DNA strand mutates. This all just happens randomly and accidentally. Many problems are solved, indeed, but they are solved without any problem being identified.

This act of solving a problem before it is identified will commonly happen for people too, but for a different reason: Because the definition of the problem is open-ended, it could be defined after the solution exists.

If the criteria for identifying a problem is fixed, there are also problems. When fixed, we will only be able to notice a narrow range of things, meaning we would not be able to solve any possible problem. If our criteria for attention is fixed, there will be some potential for progress that always lies outside of our attention.

Our attention must be free to roam.

What is considered a conflict of ideas—and what is considered a synthesis of ideas—may be more subtle than you have seen in the past. This is why the criteria for a problem must be open-ended.

For art appreciation specifically, you want to be able to focus on any aspect of a work of art to appreciate the beauty. You do not want to be stuck only able to notice the lyrics of a song, or only the emotional component of a narrative.

You need to be able to look at anything to be free to guess the beauty that fits.

Any two elements may be conflicting or synthesized. You should be free to notice if the harmony aligns with the lyrics, or if the background visuals of a movie align with the emotion of the scene. You have the ability to notice that each of these elements of a work of art convey some information, and that information can be conflicting such that you need a theory to understand why they are what they are.

To have a mind that is able to solve all possible problems, the ability to direct attention and identify problems needs to exist, and the criteria for directing attention needs to be open-ended.

2. Guess

A guess is a potential solution to your problem. This potentially resolves the conflict between ideas.

All problems are personal, but sometimes solutions are universal. However, there is no way to confirm that a solution is universal; you just attempt to use it in a new context and see if it works. This is why it is called a guess—because you never know if it will fit in a new context.

A guess is novelty. A guess is creation. A guess is newness.

This is where something genuinely new can be introduced into the world. We may call it trials, variations, or conjectures.

This can be directly thinking of something new, or it could be mixing previously existing ideas (some form of hybridization). It could be randomly changing an idea or systematically varying an idea.

It could also come from an accidental mutation, a mistaken error-prone replication. Just misunderstanding an idea is a form of creating a new variation.

The methods to create guesses are open-ended. So a guess could literally be any idea from the space of all possible ideas—the space which must include the solution to every possible problem.

If you cannot make guesses, you have no novelty. So automatically you get nothing new. Without guesses, you could not solve new problems.

Without a new guess you may be able to see what problems you have, and you may be able to choose from the best available options to address it. But with no new guesses, you can only address a narrow range of problems. You’re just handicapped by not being able to make anything new.

Surely you have depressed friends who cannot create new guesses—maybe it’s been you. But you know the situation: no new ideas, just looping on the existing possible solutions. You can do fine if you already have access to a wide set of alternatives, but that can only go so far without the addition of something new.

Because you will always have new problems.

If your system of making new guesses is fixed, then you only have a limited type of novelty. A system that cannot create new guesses, or cannot create new ways to create new guesses, will be predictable.

An example of this is our current LLMs (Large Language Models). They are lacking in many ways, but this is one that is quite obvious. They are great at combining the things that are known, but are severely limited in novelty creation. And so, we do not see the creation of new types of art, nor scientific breakthroughs coming from them.

To have a mind that is able to solve all possible problems, the ability to create guesses needs to exist and be open-ended.

3. Alternatives

Alternatives are alternative guesses. This may seem like it is redundant with the last step, but this is about the categorization of various guesses.

We need criteria for determining when guesses are variations of each other. We need criteria to determine if the same guess is being presented in different words. We need criteria for when different guesses are actually addressing the same problem, and are thus rival theories.

This allows us to properly compare how well rival theories address a particular problem.

Determining the applicability of various guesses is helpful here. Some solutions have universal applicability. Some are narrowly applicable. Some may be logically inadequate to the point that they are totally inapplicable.

If multiple solutions have the same applicability, they are likely the same solutions reformulated in different words.
If two solutions have mostly overlapping applicability except for a small few differences, one has wider reach compared to the other.

This process of categorization is highly valuable and often overlooked. Where these guesses are stored, how they are stored, and their extended implications all become highly relevant in this step.

If you cannot categorize alternatives, you cannot compare two rival theories. When you cannot compare theories, your only option for a standard is: “Is this guess ultimately certifiably true?”

You are stuck with only selecting based on some ultimate justification, rather than successively creating guesses that are better than all previous. Without categorizing, you are stuck with impossible standards.

If you cannot categorize alternatives, you cannot remove multiple guesses in the selection phase.

You may end up looping, always re-guessing and re-selecting exact copies of the same guess. One simple thing would be to equate all guesses that have internal logical contradictions—due to the fact that any contradiction can imply everything. And so there is no way to prefer one contradiction over another.

Without alternatives you indeed can select, but you cannot select the best. You must always select an immediately viable option.

If you only have a fixed criteria for what guesses are similar to others, you’re in trouble. Presumably, as you progress with problem solving, your problems become more subtle and the differences between your guesses also become more subtle. If your standard for distinguishing or equating guesses is fixed, you will not be able to accommodate higher precision. Thus you come to an end of progress.

For example, you need something to say that Newtonian Mechanics and Relativistic Mechanics are related, that they are alternatives to be compared to each other. But you need very sophisticated criteria to consider them similar, because really they are quite different physically and computationally.

Another example of where we need criteria for categorizing alternatives is the overlap of language. For example:

One may say, “Freewill is being able to do anything you want.”
Another person may say, “Determinism is the fact that the motion of fundamental particles is perfectly described by classical physics equations.”
And another may say, “Freewill is when the explanation of a person’s actions terminates at the person.”

You need sophisticated criteria to determine if each of these concepts are addressing the same problem. Are these even alternatives at all? Do they overlap or contradict in any form? Or do they just have similar sounding labels?

Of course, for my purposes of art appreciation, it sometimes becomes quite the puzzle to determine what is an alternative solution in a work of art.

However, when this isn’t such a puzzle, the audience should be able to create alternative solutions, and in the best case, they cannot find better alternatives than presented in the work of art.

It is best when the solutions within the work feel inevitable.

4. Selection

Selection is the process of removing alternative guesses. In a typical situation this involves removing the guesses that do not adequately solve the problem, or removing the guesses with less applicability than others.

The process leaves you with the best of the available options.

When only a few guesses are left, specialized tests create new subtle contexts to help decide between rival theories. This is a special case of comparing the range of applicability of two theories. Experimental tests comparing two rival theories is an example of this.

After a selection process, it is sufficient to use the best known theory as the basis of action and judgment. You should also use the best known theory as the base for future, more subtle problems to solve.

It is very important that there are different types of selection:

In Biology: Individual replicators die with an individual. That is selection, and it compounds over many instances.
In Coding: We may keep a record of the inadequate alternatives, while also systematically replacing them from all existing instances. You do not wait for a user to discover an error and delete the program; you systematically remove the error by pushing an update.
In Art: We may keep a record of older alternatives, yet we may also return to them and iterate on them. Obsolete styles may be reborn and progress can restart from there.

These are all different types of selection. The proper approach to this is open-ended; it must not be stuck in one form.

If there is no selection, you just are stuck with a flood of guesses. There is no removal of guesses that are not useful. This leads to total chaos. Perhaps you can create the right things, but if you cannot remove or ignore the wrong things, progress is muted.

Carlos gives a funny example of a Lion playing touch football with a Gazelle. Yes, it can determine which is the slowest, but if it does not eliminate, if it does not select, then they will eventually all become slow. There is no optimization to remove errors and allow for the best knowledge to progress.

For art appreciation, this is a matter of throwing out inadequate solutions, replacing them with better alternatives. If you are left with the best possible solution, the beauty becomes inevitable. While if it is easily replaceable, it feels arbitrary.

If we could not select in art, we as the audience would not be able to determine if the artist created the best version of their work or if our own immediate imagination were better.

To have a mind that can solve all possible problems, the ability to select and the criteria to select need to exist and both be open-ended.

5. Progress

The final step is Progress.

This should allow for newer, more subtle, better problems. Perhaps also the creation of new transformations that were not previously possible. However, as with all the other steps, the criteria for this is open-ended.

After selection we need to determine if we have moved forward. We need criteria for what progress is, and what type of new problems are appropriate (if any). Spoiler: There are problems. You have to have problems. They are inevitable.

A lot of people think that progress needs to have no problems. This leads to more issues.

This step helps direct our attention to either continue the whole process, or continue to something new. If we do not have a criteria for progress, then we cannot determine if our new problems are better than our old problems. We may even fall into the error of expecting our solutions to have no problems at all!

Having no criteria for progress will throw off our attention, and may keep the process of generating new guesses going longer than necessary.

If we do not know that our new problems are better than the old problems, we may continue to remove guesses. This is the common problem of needing ultimate justification, and thus not accepting any progress, and thus spinning your wheels on the same problems.

If the criteria for progress is fixed, then we come to a dead end.

This is because our problems will become more and more subtle. So our criteria for progress should also become more subtle, or we will no longer be able to identify progress.

This error happens in social commentary often. Someone may dismiss a new, better and more subtle problem as a “first world problem.” They think being sensitive to the particular firmness and temperature of their beds is not a valid problem, because the standards of what is progress are fixed at the survival level.

Or maybe they call kids “snowflakes” because of the kid’s sensitivity to subtle social behaviors. The brute then cannot see that these kids have progressed beyond the social problems of cavemen. We should have more subtle problems. That is the marker of progress.

For art appreciation, we have to recognize when new art is doing something more subtle than we are used to. We have to watch out for the error of dulling our senses, and praising insensitivity. This error will fix our criteria for progress and stagnate our problem solving.

To have a mind that can solve all possible problems, the ability to determine what is progress and what are acceptable new problems needs to exist and both need to be open-ended.

The Nested Loop

When each of these steps are present together and open-ended, there is the possibility of open-ended progress. If any step is removed, unbounded progress cannot happen. If any is fixed, progress is limited and will eventually come to a dead end.

The way to create the criteria for any one of these steps follows the same overall process. This becomes a nested loop.

You need the full 5-step process to determine what the problem is.

You need the full 5-step process to determine what progress is.

You can only guess a new criteria for alternatives after an inadequacy comes to your attention.

The criteria for each step is created by the 5-step process.

If at any point you are having trouble solving a problem in your life, you can see if any of these steps have been neglected, or if the criteria have been fixed.

I hope this is helpful for you to see how these errors show up, so that you may more easily identify these mistakes in your own life.

Lamarckism as a General Theory of Knowledge

Lamarckism is a false theory of biological evolution, which began losing favor after Dawin’s theory of evolution.

Why care about Lamarckism? Because the structure of Lamarck’s error continues to show up in every place there is a growth of knowledge.

As it turns out, both Lamarckism and Darwinian evolution are general theories of knowledge.

It is extremely important to identify where Lamarckism appears because it will slow down the growth of knowledge. If knowledge of the theory affects the system that is growing knowledge.

Lamarck’s error can show up in art appreciation, education, relationships, emotions, and many other places.

Jean-Baptiste Lamarck was a French naturalist, pre-dating Darwin, who had a theory of evolution based on the inheritance of acquired characteristics.

In more detail we can formalize his theory, and then generalize it into a general theory of knowledge.

Lamarckism:
1. Influence of the Environment: New organs in an animal body result from new requirements in the environment that continue to be felt.
2. Inheritance of Acquired Characteristics: All traits acquired in an organ’s lifetime will be preserved and transmitted to the next generation.
3. The Complexifying Force: Organisms move up a ladder of progress.
4. The Adaptive Force, Use and Disuse: Use of an organ will develop the organ, while disuse deteriorates an organ.

This is very close to the technical understanding that Lamarck had of the theory himself.

Each of these is quite a disaster in a general theory of knowledge. To make this much more clear I will expand these each to single concept points and generalize them into broader theories of knowledge.

The most important problem to look at is the misunderstanding of where the knowledge is stored.

This list expanded to be in more natural language follows.

Lamarckism as a General Theory of Knowledge:
1.1. Internal knowledge is instructed by external knowledge in the environment.
1.2. Knowledge growth will end once the external requirements are met.
2.1. Knowledge will be faithfully stored.
2.2. Knowledge will be automatically translated to a transferrable form.
3.1. Knowledge will always become more complex.
3.2. Groups of knowledge will always become more complex.
4.1. The use of knowledge will develop the knowledge.
4.2. Not using knowledge will deteriorate the knowledge.

Each of these are mistakes in biology, and they are equally mistakes in other knowledge growth situations.

For this essay I will only focus on the first half. We will save use/disuse, and the complexifying force for another day.

To see how this logic of Lamarckism plays out, I’ll describe a classic example.

When a pre-giraffe looks at a tall tree, it sees the knowledge of how to reach the leaves. It is obviously encoded in the environment. That knowledge is “have a long neck to reach the leaves.” That knowledge is transferred directly to the pre-giraffe who stretches its neck. That stretched neck is knowledge literally stored as the body, it is an acquired characteristic. That knowledge is then transferred to the genes which can be given to its offspring.

In this scenario there is no “new” knowledge, it was there all along. In Lamarckism the idea of new knowledge is almost completely thrown out. What you have is knowledge embodied in the environment which transfers to the target. The knowledge in the organism can never go beyond the source knowledge embodied in the environment.

With that picture in mind, let’s go back through those four aspects of Lamarckism. I want to explain exactly why they are wrong by contrasting them with how Darwinian knowledge growth actually works. Then, once the mechanism is clear, I’ll show you a few examples of this error in action.

1.1. Internal knowledge is instructed by external knowledge in the environment.

The original phrase “a new organ” generalizes to “internal knowledge.” We know today that organs are built by DNA sequences, that is the internal knowledge in biology.
The original phrase “a need from the environment” generalizes to “external knowledge.”

A “need from the environment” is “knowledge in the environment.” That may sound weird, and it should, because the exterior knowledge in the environment is not of the same form of the internal knowledge in DNA.

And that is exactly why this error is so common. If you do not recognize different types of knowledge then you will not understand that specialized mechanisms for translating them are required.

So, for our pre-giraffe, even if the environment did directly encode the knowledge “have a long neck to reach the leaves,” it would need some specific mechanism to translate that knowledge into a DNA gene sequence, and then have a specific mechanism to accurately edit its own DNA. Since no such mechanism exists, this whole chain of logic falls apart. For this reason, Lamarckism is false.

The actual process is Darwinian. In Darwinian evolution, external knowledge can never direct the internal knowledge growth. There is no mechanism that ‘notices’ a problem outside and tells the specific relevant gene to mutate. The genes are blind to the environment.

The knowledge in the DNA is varied randomly, without any reference to the environment. And the variations that fit better in the environment replicate more widely.

1.2. Knowledge growth will end once the external requirements are met.

The original phrasing is a “need from the environment that continues to be felt.” This generalizes to “growth will stop when there is no need.”

Lamarckism always has an endpoint for knowledge growth, and really there’s no creativity. Knowledge is just being transferred from an external source, and once the transfer is complete knowledge growth ends.

If this were the case, there would be no explanation of mistakes. There would be no possibility for a “happy little accident” to create knowledge greater than is embodied in the environment. In Lamarckism knowledge growth will always be limited to what is instructed by the environment.

This limitation would be tragic, because people would be permanently limited to knowledge already present in their environment.

Lucky for us, real knowledge growth is Darwinian.

In Darwinian evolution, knowledge growth is constantly happening. There are mutations and variations very frequently in the genes without any foresight. Most are error corrected, but occasionally a mutation is better than the original. If the variant is better than the original, it will replicate more widely.

This is one of Darwin’s main insights. The solutions, the knowledge, is always generated first, and then placed into new contexts to be tested.

Biological evolution is blind. Knowledge does not start growing due to external knowledge, or due to some need. Knowledge can not grow due to external instruction.

Knowledge growth never stops because it is not directed. So there is no endpoint for Darwinian knowledge growth. Knowledge may go beyond the limitations of the knowledge already embodied in the environment.

2.1 Knowledge will be faithfully stored.

In the original “All that is acquired will be preserved,” is generalized to “knowledge will be faithfully stored.”

Lamarckism expects reliable faithful storage of knowledge to an incredible degree. “All traits acquired in an organ’s lifetime will be preserved…” This reliable faithful storage occurs passively with no specific mechanism proposed.

This would be a disaster, because many acquired traits are defects and injuries. If each were preserved from generation to generation, genetic mistakes and defects would build up and overwhelm the system.

Contrast that to Darwinian evolution, where knowledge is not faithfully stored passively. Storage only appears faithful due to active error correction mechanisms. These error correction mechanisms detect and correct changes due to entropy and random fluctuations of the physical medium, because they happen frequently.

DNA will mutate, but also, behaviors will change, bodies will change, other aspects of the physiology and phenotype which are not stored in DNA will make several changes. The storage of knowledge for each of these will be in flux. From the brain, to the nervous system, memes, genes, and so on.

Darwinian evolution relies on natural selection as a filter. Instead of preserving every change, most mistakes are corrected. As for mistakes that are not corrected, when mistakes fail to meet the standard of the environment, they fail to replicate widely, and die out.

2.2. Knowledge will be automatically translated to a transferrable form.

The original says “all that is acquired is transmitted to the next generation.” The generalization makes it clear that knowledge that is acquired traits are of one form and must be translated to another form to be passed on. The highlight is the automatic translation.

Lamarckism expects instant translation of any form of knowledge to other forms of knowledge, but proposes no specialized mechanism for causing that change.

In biology this will be in the form of acquired ideas and behaviors being automatically translated into genes which can be transferred to offspring.

The change of external knowledge into the form of internal knowledge is mirrored in the changing of various forms of internal knowledge. Mental knowledge, behaviors, the state of the body, and DNA are all internal knowledge. However they are not all of the same form. One would need a special mechanism to turn mental knowledge into behaviors, or to turn behaviors into bodily states, or the body into DNA.

Without a direct translation mechanism, trial and error is the only way to make these changes.

Turning mental knowledge, an idea, into behavior is fairly easy for anyone with basic bodily coordination. Notice that children have to go through a long trial and error process, and so do adults for unfamiliar behaviors, but this is generally quite easy.

Turning a behavior into a changed body can be quite difficult. Imagine exercise turning into a fit body. This takes some time, and some consistency. But the body is quite well prepared for this! It is already set up to turn certain stimuli (the behaviors) into bodily changes (the muscles).

Turning bodily changes into DNA introduces the difficulty. This is biologically impossible. There is no normal way for an organism to modify their own DNA. Even for a modern person with advances in gene editing technology, it is not clear which gene sequence would cause large muscles without the need for the gym.

So if the knowledge is stored in your mind, or your behavior, or your body, it cannot be directly transferred to your genes, and thus cannot be directly transferred to your offspring. Lamarckism misunderstands this.

In Darwinian evolution, only the DNA is passed on to the next generation, and even that is error-prone. The only way for this DNA to develop new knowledge is through blind variation, and selection. All other knowledge in the form of memes or physiology must be re-learned from scratch.

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If we look at the big picture, Lamarckism is fundamentally misunderstanding what form knowledge is stored in and how that knowledge changes.

Lamarck did not have the notion of genes, (nor did Darwin). Without understanding the different forms of knowledge, he could not understand how different forms of knowledge interact, (if they interact at all). The notion of instruction feels intuitive, while Darwin’s selection feels counter-intuitive. Darwin’s variation and selection is an entirely new and unfamiliar mode of evaluation.

Knowledge does not come from outside. It cannot come from instruction. It must “come from” inside. The knowledge inside mutates, or guesses, or otherwise creatively varies; and then errors are removed.

Even if the environment could change the genes, which it cannot, it would have to know which specific genes to change to cause a specific effect. The genetic coding is messy and different for each species, so an environment would have to contain vast knowledge to be able to directly affect these in the right way. This sophisticated understanding is not present.

Knowledge has no sources. We don’t copy knowledge from a source, we create it within ourselves. New knowledge is genuinely the introduction of something new to reality. It can only happen given the Darwinian process of variation and selection, which we can call trial and error.

Knowledge is not automatically changed into different forms. If knowledge is translated into a new form, say human theories translated to DNA gene sequences, or code; this process of creating something new without a source through variation and selection must occur. The new knowledge of the new form must be compared to the existing knowledge. If it does not meet the standards, it will be destroyed (or continue to vary), if it does meet the standards, then the process of translation is complete.

Knowledge is not faithfully stored. Knowledge is really always in flux. There are always minor deviations which must be corrected. Because these errors are unpredictable, occasionally they create something better, or provide a pathway for something better. This means knowledge growth is constantly occurring, and there is no endpoint for the growth of knowledge.

This is the case for all knowledge.

There are some important differences between biological knowledge creation and human knowledge creation.

With human knowledge creation we have open-ended control of our attention. This means we can deliberately find problems (or direct our attention for any other reason), then allow our ideas to be varied. Or alternatively we can keep our ideas from varying. The reasoning for doing this and the way to do this are both totally open-ended. We can use or create any standards we want for this process.

With human knowledge creation we have open-ended control of our variations. This means we can make variations in any way that we like. They may be systematic variations, or random, large, or subtle. We can do it in any way or for any reason.

With human knowledge creation we have open-ended standards for grouping ideas. This means we can determine if several ideas are the same in different forms, or determine if various ideas are variations of each other, or determine that two ideas are rivals to each other, or any such grouping. Again, this may be done in any way and for any reason, it is open-ended.

With human knowledge creation we have open-ended standards for selection. This means we can delete ideas freely, or we can remember ideas as failed variants, or we can demote ideas to approximations of other better ideas. The reasoning for selection and the methods of selection are both open-ended.

And finally with human knowledge creation we have open-ended standards for progress. This means we determine when a new idea constitutes progress. The standards for identifying progress are open-ended.

This is all quite different to what is possible in biological knowledge creation, where each of these are severely limited. There is almost no attention. All new ideas are random variations of genes that occur blindly. The only grouping of ideas is the physical closeness of genes in an environment. All selection is the death of a single gene at a time. And there are no standards of progress that can guide attention, variation, grouping, or selection.

And yet, for both human knowledge creation and biological knowledge creation, all of the principles of Lamarckism are impossible.

Now that we’ve clarified the mechanics of Lamarckism, let’s look at how this error shows up in our lives.

I will start with Art just because it is my main interest for learning theories of knowledge.

Knowledge creation in art can be broadly categorized into two groups: Art Creation and Art Appreciation.

While creating, an artist may have the mistaken idea that the environment already embodies all of the available beauty, and the only function of the artist is to receive instruction from the environment.

This may be instruction from nature, or instruction from human situations, or instruction from muses/gods. In each of these cases, the artist mistakenly believes art is a sort of data transfer of knowledge from some source to the target.

Of course, they would never use this language, because the knowledge view of reality is not widely appreciated, but when described plainly it is clear to see.

“Nature embodies all beauty” or “God embodies all beauty” or “Beauty must be received from beyond” and such sentiments. “All creativity is really the re-combination of things that already exist.”

This is the Lamarckist error of expecting internal knowledge growth to be instructed by external sources. This also completely erases the possibility of human creativity. By this sentiment, a human cannot create anything genuinely new, they can only re-create what already exists.

However, even if there was beauty already embodied in nature or embodied by god, the translation and transfer to human minds and human art must be error-prone. This means some of the errors must be able to be better than the original. (I will just assume no one has achieved perfection, not even god.) Which means it is possible for either errors, or human creativity, to improve upon the beauty already embodied in the environment.

Human creation of beauty must come through trial and error, and it must be possible to create something genuinely new outside of what is already embodied in the environment.

On the side of art appreciation, there is a common error to expect the beauty embodied in a work of art must have been placed there by the artist, and the audience cannot create new beauty given the existing work of art.

This is the common case of the audience ignoring their own creativity, in favor of whatever the artist says is the knowledge. Internal knowledge being instructed by external knowledge. And so the growth of beauty is limited to the beauty already embodied in the work of art. No space for new interpretations, no space for new beauty from the audience.

This also occurs with the obsession of purity, obsessions with ethnic/cultural accuracy, obsessions with sticking to the historical tradition. These are all the same error.

Sometimes in art creation, there is the expectation that art must always become more complex. The only standard of progress is higher complexity. This is outside of what I have mentioned so far in the essay, but it is a Lamarckist error, and it is a restriction on the standards of progress.

The structure of Lamarckism also shows up in relationships.

The Lamarckist issue in relationships is the general issue of not knowing where the knowledge is, nor how it interacts. This applies broadly to all forms of relationships, not just 1-on-1 romantic relationships. I mean romantic relationships, friendships, larger groups, and so on.

One may expect that having a goal for the relationship within one mind is automatically enough to properly steer the connections between people. This is the expectation that knowledge is automatically translated into a transferable form. Unfortunately, the cohesion of a group of people is not caused by an idea of the mind of an individual alone. Even if the idea were placed into the mind of several or all people involved, that would not automatically be enough.

The knowledge in large systems is highly distributed. There is no obvious method of storage nor copying nor changing the knowledge embodied in a group. Knowledge will often extend outside of mental ideas, extending to their environment. Their literal bodies. Their house and local community. Their behavior. The weather.

If one wanted to steer a relationship, there are many parameters to play with. And it would all have to be done without disrupting each individual’s knowledge creation systems.

I feel I am being overly abstract with this example, so I will give a more clear version of it. Say I see a celebrity relationship, Kylie Jenner and Timothée Chalemet, and I want my relationship to match it.

An immediate problem is I do not have access to their personal lives. I only see glimpses of their relationship through videos and interviews online. If I were to just recreate the videos with my girlfriend, or act out the interviews, I would not have replicated their relationship structure. I would not have copied the underlying knowledge causing the success of their relationship.

But the fact of not having access to their life is hiding the real problem. Even with total access, I do not know which details are relevant to their relationship.

Kylie is an amazing business woman and Timothée is a fantastic artist. Perhaps that is the thing we should copy? Or maybe it is the weather in California that makes their relationship successful? Really, the knowledge is highly distributed across various forms. I would need the incredible ability to see the details of their life, translate everything into mental ideas, prune them for only the relevant ideas, and then translate them into the proper form to be copied into my relationship.

Alternatively, we can go the Darwinian approach. Our own relationship can create new knowledge to generate a unique structure for our connection. This makes for very error-prone and creative situations. There is no authority to follow, there is no possibility to copy an external source, and there is no endpoint to the growth!

This brings us to Authority.

Lamarckism shows up in all forms of authority. It is the error of external knowledge instructing the internal knowledge.

In education, the authority is the teacher, and the target is the student. The student is expected to learn, sometimes immediately, sometimes without any error, always without creativity.

What is often missed is that forcing learning is impossible. Why? Because teachers do not have direct access to the neuronal connections of the student. Teachers don’t even have access to their own neurons. There is no reliable mechanism for copying the teacher’s neuronal connections to the student’s. Even if there were, do you expect the student’s brain to be able to directly and sensibly import the teacher’s brain state?

This is obviously absurd, and I am intentionally heightening the absurdity. Just to highlight that the student’s only option is trial and error. The part of the student’s mind that understands concepts must create the understanding through creative variation, and then check that their understanding is correct.

Some teachers (and other authorities) expect that a student will understand something fully immediately, but this is a misunderstanding of how knowledge is created. Additionally, assuming the student does create the proper understanding, teachers often expect 100% accurate recall. The Lamarckist error that all knowledge be faithfully stored.

However the mind is constantly in flux, this is a property of physics and all physical systems, and it requires active error-correction to counteract. Yet this in itself creates the possibility of improvements. Variants may be better than the originals, removing errors or creating something genuinely new.

This instability, perhaps we can even call it disobedience, is required for the growth of knowledge. Imagine the disaster if all knowledge were faithfully stored and accurately transferred to every student. We would be irreparably stuck.

We can generalize this even further to just instruction from the past. An attempt to copy the moral behaviors of cultures thousands of years passed. This is the error of not understanding the distribution of knowledge from the source and the target. While also implicitly expecting no further growth of knowledge, (this is the inverse of wanting 100% accuracy).

But we have improved our moral knowledge (and thus our behaviors) over time, and will continue to do so. And our moral knowledge heavily depends on the institutions around us. The knowledge is distributed in our modern lives, our modern culture, our technologies. While the moral knowledge and behaviors of the past was distributed and embedded in their culture and technology.

Instruction from a Government is similar. Attempting to control behaviors and the flow of money without having specific control of where the knowledge is actually stored.

Instruction from some Spirit Realm that has perfect knowledge is the same error. We do not need to tap into some other world for our scientific and artistic achievements. We create it ourselves.

Naive Empiricism itself is of a similar structure. Empiricism is the idea that our senses are a window to the world, and through observation we absorb knowledge. This follows the Lamarckist idea that the environment instructs the organism, and carries the limitation that knowledge cannot grow beyond what is already embodied in the environment.

Something even as simple as emotions are incorrectly seen through a Lamarckist lens. It starts with the assumption that the emotions are some perfect unchanging gift from reality. When, in reality, the emotions are constructs. They have been created, in part by biology and in part by human culture.

No emotion should be seen as a perfect endpoint to achieve and settle on. There is no reason to find the current pinnacle of contentment and consider it an endpoint, to stop all progress and just die happy. No, every emotion that you value today can be improved.

Believing that happiness is some kind of gift from reality to appreciate as an endpoint is a Lamarckist error.

With all these examples along with the more abstract descriptions, I hope you can see the structure of Lamarckism. Holding to a Lamarckist theory of knowledge can disrupt the growth of knowledge. We should do what we can to remove this way of thinking from our worldview.

The proper way to view knowledge and the growth of knowledge is through the Darwinian lens.