Well, Traumadumpling isn’t going to read this, so I’m just amusing myself.

we cannot bridge the gap between subjective internal experience and objective external physical processes, not even hypothetically, there is not even a theoretical experiment you could design for it, there is not even theoretical language to describe it without metaphor. We could learn and simulate literally every single specific feature of the brain and it would not tell us about internal subjective experiences, because it is simply not the kind of phenomena that is understood by the field of information processing.

This is all because subjectivity isn’t falsifiable and is not currently something that the scientific method can interact with. As far as the scientific method is concerned it doesn’t exist. idk why people are even interested in it, I don’t see why it’s important. The answer to “P-zombies” is that it doesn’t matter and isn’t interesting. If something performs all the observable functions of an intelligent mind with a subjective experience… well… it performs all the observable functions of an intelligent mind. Why are you interested in subjectivity if you can’t evaluate whether it’s even happening? You can’t test it, you can’t confirm or deny it. So just put it back in the drawer and move on with your life. It’s not even a question of whether it does or doesn’t exist. It’s that the question isn’t important or interesting. It has no practical consequences at all unless people, for cultural reasons, decide that something that performs the functions of an intelligent mind doesn’t deserve recognition as a person because of their ingrained cultural belief3 in the existence and importance of a soul.

I do see this as directly tied to atheism. Part of making the leap to atheism and giving up on magic is admitting that you can’t know, but based on what you can observe the gods aren’t there. No one can find them, no one can talk to them, they never do anything. If there are transcendental magic people it’s not relevant to your life.

Phenomenology is the same way. It just doesn’t matter, and continuing to carry it around with you is an indication of immaturity, a refusal to let go and accept that some things are unknowable and probably always will be. Hammering on and on that we can’t explain how subjectivity arises from physical processes doesn’t change the facts on the ground; We’ve never observed anything but physical processes, and as such it is reasonable to assume that there is a process by which subjectivity emerges from the physical. Because there’s nothing else. There’s nothing else that could be giving rise to subjectivity. And, again, we don’t know. Maybe there is a magic extradimensional puppeteer. But we don’t know in the same sense that we don’t know that the sun will rise tomorrow. It’s one of the not particularly interesting problems with the theory of science - We assume that things that happened in the past predict things that will happen in the future. We do not, and cannot know if the sun will rise tomorrow. But as a practical matter it isn’t important. With nothing else to explain the phenomena we observe, we can assume within the limits in which anything at all is predictable that the subjective experience is an emergent property of the crude, physical, boring, terrifyingly mortal meat.

More and more philosophy’s dogged adherence to these ideas strikes me as an refusal to let go, to grow up, to embrace the unpredictable violence of a cold, hostile, meaningless universe. Instead of saying we don’t and cannot know, and therefor it’s not worth worrying about, philosophers cling to this security blanket of belief that we are, somehow, special. That we’re unique and our existence has meaning and purpose. That we’re different from the unthinking matter of stars or cosmic dust.

mechanistic physicalist reductionist worldview

https://en.wikipedia.org/wiki/Physicalism

Like this is just materialism. Physicalism isn’t a belief, it’s a scientific observation. We haven’t found anything except the physical and as much as philosophers obsess about subjectivity and qualia and what have you those concepts, while mildly interesting intellectual topics, aren’t relevant to science. You can’t measure them, you cannot prove if they exist or do not exist. Maybe someday we’ll have a qualia detector and we’ll actually be able to do something with them, but right now they’re not relevant. I’m a reductionist physicalist mechanist because I’m tired of hearing about ghosts and souls and magic. No question is being raised. There’s no investigation that can proceed from these concepts. You can’t do anything with them except yell at people who think, based on evidence, that physics is the only system that we can observe and investigate. And it’s not “these things don’t exist”, it’s whether they exist or not, we can’t observe or interact with them so we can’t do anything with them. You can’t test qualia, you can’t measure it. If we can some day, cool. But until then it’s just… not useful.

AI is everywhere.

I didn’t read the article, just commented on the excerpts. And when I do read the article this is the first line? Conflating LLMs and neural nets with AI? Accepting the tech bro marketing buzzword at face value?

Terms like “neural networks” certainly have not helped and, from Musk to Hawking, some of the greatest minds have propagated this myth.

Neural networks are called that because they’re modeled on the behavior of neurons, not the other way around. Hawking could be a dork about some things but why put him in the same sentence as an ignorant buffoon like Musk?

Is what we’re arguing here actually that psychologists and philosophers are yelling at tech bros because they think that neuroscientists using computer metaphors actually believe a seventy year old theory of cognition originating from psychology when psychologists were still mostly criminals and butchers?

Like saying the brain is a biological organ? That’s not a gotcha when biological computers exist and research teams are encoding gigabytes of data, like computer readable data, 1s and 0s, as DNA. Whatever the brain is, we can build computers out of meat, we’ve done it, it works. There is no distinction between biological and machine, artifact and organ, meat and metal. It’s an illusion of scale combined with, frankly, superstition. A living cell operates according to physical law just like everything else. It has a lot of componenents, some of them are very small, some of them we don’t understand and I’m sure there are processes and systems we haven’t identified, but all those pieces and processes and systems follow physical laws the same as everything else in creation. There’s no spooky ghosts or quintessence down there.

Like, if the message here is to tell completely ignorant laypeople and tech bros who haven’t read a book that wasn’t about webdev that the brain does not literally have circuitry in it, fine, but say that. But right now we’re very literally bridging the perceived gap between mechanical human artifacts and biology. We’re building biological machines, biological computers. These are not completely different categories of things that can never be unified under a single theory to explain their function.

Let’s take a step back, look at “Capitalism as a real god”, what Marx called it, or “Holy shit capitalism is literally Cthulu” which is the formulation many people are independently arriving at these days. Capitalism is a gigantic system that emerges from the interactions of billions of humans. It’s not located in any single human, or any subset of humans. It emerges from all of us, as we interact with each other and the world. There’s no quintessence, no “subjectivity” that we could ever evaluate or interogate or find. We can’t say whether capitalism has a subjective experience or cosciousness, whether there is an “I think therefore I am” drifting across the maddening complexity of financial transactions, commodity fetishism, resource extraction, and cooking dinner.

The brain has ~80 million neurons (plus glial matter I know I know bear with me). There are about 8 billion humans, and each of us is vastly more complex than a brain cell. So if humans actually are components in an emergent system that is intelligent and maybe self-aware, there’s only one order of magnitude fewer humans than there are cells in a human brain that, given lack of any other explanations, we must assume give rise to a thinking mind.

Is it impossible for such a system to have a subjective experience? Is it a serious problem? As it stands we can’t assess whether such subjectivity exists in the system, whether the system has something meaningfully resembling a human mind. The difference in experience is likely so vast as to be utterly unbridgeable. A super-organism existing on a global level would, likely, not be able to communicate with us due to lack of any shared referents or experiences at all. A totally alien being unlike us except that it emerges from the interaction of less complex systems, seeks homeostasis, and reacts to its environment.

But, like, who cares? Whether capitalism is a dumb system or an emergent intelligence there’s nothing we can do about it. We can’t investigate the question and an answer wouldn’t be useful. So move along. Have your moment of existential horror and then get on with your life.

I think that’s what really bothers me about this whole subjectivity, qualia, consciousness thing. It’s boring. It’s just… boring. Being stuck on it doesn’t increase my knowledge or understanding. It doesn’t open up new avenues of investigation.

The conclusion I’m coming to is this whole argument isn’t about computers or brains or minds, but rather phenomenology having reached a dead end. It’s a reaction to the discipline’s descent in to irrelevance. The “Hard Problem of Consciousness” simply is not a problem.

Unless the author redefines the words used in the bit that you quoted from them, I addressed their argument just fine.

so you aren’t going to read the article then.

No Investigation, No Right to Speak.

Here follows some selections from the article that deal with exactly the issues you focus on.

I strongly advise reading the entire article, and the two it is in response to, and furthermore reading about what a Turing Machine actually is and what it can be used to analyze.

The debate on whether the brain is a computer or not seems to have died down given the recent success of computer science ideas in both neuroscience and machine learning. I have seen a few recent articles on this subject from scientists, who have made strong claims that the brain is in fact literally a computer, and not just a useful metaphor backed up with their reasons to believe so. One such article is this one by Dr. Blake Richards (and here is another one by Dr. Mark Humphries). I will mainly deal with the first one — a really good and extensive article. I would encourage readers to go through it slowly, and in detail for it provides a good look at how to think about what a computer is, and deals well with a lot of the weaker arguments brought against the ‘brain is a computer’ claim (like the ones here.) Dr. Richards addressed a good variety of objections that people might rise to the claim that “the brain is a computer” towards the end of his article. I will raise an argument here that I feel lies at the heart of this discussion, not addressed in the post and is often overlooked or dismissed as non-existent. The reason I think it is important to discuss this question (and/or objection) in detail is that I strongly believe it affects how we study the brain. Describing the brain like a computer allows for a useful computational picture that has been very successful in the fields of neuroscience and artificial intelligence (specifically the sub-area of machine learning over the recent past). However as an engineer interested in building intelligent systems, I think this view of the brain as a computer is beginning to hurt us in our ability to engineer systems that can efficiently emulate their capabilities over a wide range of tasks.

the bolded part above is ‘why the author has a problem with the computer metaphor’ since you seem so confused by that.

There are a few minor/major problems (depends on how you look at it) in the definitions used to get to the conclusion that the brain is in fact a computer. Using the definitions put forward in the blog post —

(1) an algorithm is anything a Turing machine can do, (2) computable functions are defined as those functions that we have algorithms for, (3) a computer is anything which physically implements algorithms in order to solve computable functions.

these are the definitions the author is using, not ones he made up but ones he got from one of the articles he is arguing against. note the similarities with the definitions on https://en.wikipedia.org/wiki/Algorithm :

One informal definition is “a set of rules that precisely defines a sequence of operations”,[11][need quotation to verify] which would include all computer programs (including programs that do not perform numeric calculations), and (for example) any prescribed bureaucratic procedure[12] or cook-book recipe.[13] In general, a program is an algorithm only if it stops eventually[14]—even though infinite loops may sometimes prove desirable. Boolos, Jeffrey & 1974, 1999 define an algorithm to be a set of instructions for determining an output, given explicitly, in a form that can be followed by either a computing machine, or a human who could only carry out specific elementary operations on symbols.[15]

note the triviality criticism of the informal definition that this author previously addressed, and the ‘human who could only carry out specific elementary operation on symbols’ is a reference to Turing Machines and the Chinese Room thought experiment, both of which i recommend reading about.

The concept of algorithm is also used to define the notion of decidability—a notion that is central for explaining how formal systems come into being starting from a small set of axioms and rules. In logic, the time that an algorithm requires to complete cannot be measured, as it is not apparently related to the customary physical dimension. From such uncertainties, that characterize ongoing work, stems the unavailability of a definition of algorithm that suits both concrete (in some sense) and abstract usage of the term.

this is still a matter under academic discussion, there are not widely agreed on definitions of these terms that suit all uses in all fields.

Most algorithms are intended to be implemented as computer programs. However, algorithms are also implemented by other means, such as in a biological neural network (for example, the human brain implementing arithmetic or an insect looking for food), in an electrical circuit, or in a mechanical device.

algorithms can be implemented by humans, intentionally or not, the hardware is irrelevant to the discussion of Turing machines since they are an idealized abstraction of computing.

enough wikipedia now back to the article

Number (3) is the one we will focus on for it is vitally important. To complete those definitions, I will go ahead an introduce from the same blog post, an intuitive definition of algorithm — “ an algorithm is a finite set of instructions that can be followed mechanically, with no insight required, in order to give some specific output (e.g. an answer to yes/no integer roots) for a specific input (e.g. a specific polynomial like 6x³yz⁴ + 4y²z + z — 9).” And the more technical definition of algorithm in (1) as “ An algorithm is anything that a Turing machine can do.” This equivalence of course arises since attempts to achieve the intuitive definition about following instructions mechanically can always be reduced to a Turing machine. The author of the post recognizes that under this definition, any physical system can be said to be ‘computing’ it’s time evolution function and the meaning of the word loses it’s importance /significance. In order to avoid that, he subscribes to Wittgenstein and suggests that since when we think about modern day computers, we are thinking about machines like our laptops, desktops, phones which achieve extremely powerful and useful computation, we should hence restrict the word computers to these type of systems (hint: the problem is right here!!). Since our brains also achieve the same, we find that our brains are (uber) computers as well (I might be simplifying/shortening the argument, but I believe I have captured it’s essence and will once again recommend reading the complete article here.) Furthermore, he points out that our modern day computers and brains, have the capability of being Turing complete, but are not of course due to physical constraints on memory, time and energy expenditure. And if we do not have a problem with calling our non-Turing complete, von Neumann architecture machines as computers, then we should not let the physical constraints that prevent the brain from being Turing complete stop us from calling it a computer as well. I agree that we should not restrict ourselves to only referring to Turing complete systems as computers, for that is far too restrictive. The term ‘computer’ does have a popular usage and meaning in everyday life that is independent on whether or not the system is Turing complete. It makes a lot more sense to instead refer to those computers that are in fact Turing complete as ‘Turing complete computers’.

this explains the author’s reasoning for their definitions further, he is not making these up, these are the common definitions in use in the discourse.