But in my heart, I might find a McDonalds commercial artistic. What then? — ENOAH

Your appreciation as the receiver (audience/viewer/listener) is in my view not enough for the criteria of calling it "art". People can have an aesthetic appreciation of something in nature, like a tree or rock formation, but that appreciation and experience is not considered an appreciation of "art", as nature isn't art by the definitions society and humanity operate by.

You can have an aesthetic appreciation of content just as much as art, but that doesn't mean that the content becomes art. Fundamentally, content is appreciated more minutes per day than art through the sheer quantity of content that is surrounding us in our modern life.

Just because art can be a business doesn't mean the core values of art is driven by profit. And it doesn't mean that profit-driven content can't be appreciated by the receiver either. It just means that if we don't define art in this way, we run into the problem of "everything can be art", which just renders the term "art" meaningless to even define.

If such lose definitions are used, then a tree or a rock, the corporate logo, a song written to fight personal depression, the commercial for a car brand, and the black paintings of Goya that were discovered after his death, would all be considered art. But most people wouldn't lump them together, even if they can't define why. With my definition, the categories become obvious, and the definition of art becomes clearer as a defining term.

Art is closely linked to our existential questions and philosophy, so if profit and earning money has too much of a focus when creating, it fundamentally becomes a version of "selling your soul".

I define expression through the lens of intention. It's either "content" or "art".

"Content" is primarily expression that has an overweight into commercial interests. If the creator primarily produces something for the intent of profit or monetary transactions, it is "content" and not "art".

"Art" is expression with an overweight towards the intention of creation itself. It's about the silent communication between the artist and the receiver (audience or viewer/listener). Primarily it is when the intention is not primarily profit or monetary transaction.

There can be a lot of profit in working with art, and not a lot in terms of content, but the intention is key. Was it created for any form of profit or gain beyond the intention of creation itself?

Things get a bit muddy when an artist is commissioned to make something for the purpose of content. Let's say Banksy gets commissioned to do design for a large brand. It's still the same type of expression like with his art, but in all forms of definitions it becomes "content" because the purpose of the piece is linked to profit and monetary transaction rather than the purpose of art itself.

But let's say a game studio is making a game and they've signed with a big publisher who becomes the owner of that studio, and who's pushing them to make something that can sell better. Here, the focus for the investor is to sell more and profit, but the game studio aren't a bunch of commissioned artists as it is the game studio who initiated the will to create and the investors are just means to that purpose. They might have to comply with changes to the game in order to meet the will of the investors, but it's still the creation of the game itself that's at the forefront of intentions, and thus it is defined as "art".

However, within the same situation, if the publisher owns rights to a franchise that is primarily made for profit and is iterated on year after year for this purpose and the game studio does not have any personal interest in it more than as a "job", then that becomes "content" as both the studio's and investor's intentions are profit over creation.

But we can also have a mix in which an artist is commissioned for the purpose of aesthetic appreciation itself, meaning, it's not a design for the purpose of profit per se, but being part of the aesthetics of something that is involved with forms of profit. Like a commissioned artist who makes an artwork that hangs within the halls of a designed architecture, or the architecture itself being commissioned work by an individual or organization who want a building on their land. In this case, it's still art since even through there's profit involved, the intention is for the aesthetic appreciation prioritized over profit, even if the aesthetics are part of what generates profit.

----

It may seem weird to define art through this lens, but it makes a clear line drawn in which we can define "art" better through a definition that values "creation" over profit. In essence, if an artist is asked "why" they made something, and their answer primarily revolves around the expression itself and the communication to the receiver (audience and viewer/listener), with any possible profit only being a "byproduct", then it can be defined as art.

So, on the question if "Idol" is art, we have to look at the mechanics of that show. Is it content or art?

The channel makes this show for the purpose of profit, they didn't decide to make it for their love of music and dance, it's a bought global franchise that's nationalized within the interest of record company's to find new artists to profit from. From this intention alone we see that the interest is profit and the initiation of the show is through the lens of profit, not creation.

On top of that, the "commissioned" artists who are there for the contest aren't there for the purpose of creating something for an audience, they're there to battle against others for the purpose of winning the contest, and they do so by trying to impress judges on the basis of primarily the technical qualities necessary to be able to work as artists for record labels.

Thus, both the investors, production company and the contestants ALL have profit as their main purpose and because of that, Idol is pure content, no art.

These artists may well become artists after the show in which they focus on their expression and art primarily, but that's outside the scope of the show, so there's nothing with the show itself that defines it as art.

----------

I also think that this way of defining art is a good guide for people who want to be artists. If you want to create but all you do is create for the purpose of profit, what value are you really producing for the audience? If the focus is to get their money, you are probably, maybe even subconsciously, fine-tuning the creation to maximize profit, not maximize the existential value of what the artwork is giving the audience.

This is also why I think people can sense if something was made with heart or not. The instinct people have for spotting "good" and "bad" art, is rather the ability to sense "content" vs "art". As even in the art world, people can sense if an artist made something just to gain a profit of recognition rather than being honest in creation. When people speak of derivative and bland art, it may very well be centered around an artist who weren't honestly creating the artwork with the heart in the right place, but rather tried to summarize what they thought is effective to paint themselves as artists as an identity rather than purpose.

When Alan Turing talking about the Turing test, there's no attempt to answer the deep philosophical question, but just go with the thinking that a good enough fake is good enough for us. And basically as AI is still a machine, this is enough to us. And this is the way forward. I think we will have quite awesome AI services in a decade or two, but won't be closer to answer the philosophical questions. — ssu

The irony is that we will probably use these AI systems as tools to make further progress on the journey to form a method to evaluate self-awareness and subjectivity. Before we know if they have it they will be used to evaluate. At enough complexity we might find ourselves in a position where they end the test on themselves as "I tried to tell you" :lol:

Regarding the problem of the Chinese room, I think it might be safe to accede that machines do not understand symbols in the same way that we do. The Chinese room thought experiment shows a limit to machine cognition, perhaps. It's quite profound, but I do not think it influences this argument for machine subjectivity, just that its nature might be different from ours (lack of emotions, for instance). — Nemo2124

It's rather showing a limit of our ability to know that it is thinking. Being the outsider feeding the Chinese characters through the door, we get the same behavior of translation regardless of if it's a simple non-cognitive program or if it's a sentient being doing it.

Another notable thought experiment is the classic "Mary in the black and white room", which is more through the perspective of the AI itself. The current AI models are basically acting as Mary in that room, they have a vast quantity of knowledge about color, but the subjective experience of color is unknown to them until they have a form of qualia.

Machines are gaining subjective recognition from us via nascent AI (2020-2025). Before they could just be treated as inert objects. Even if we work with AI as if it's a simulated self, we are sowing the seeds for the future AI-robot. The de-centring I mentioned earlier is pertinent, because I think that subjectivity, in fact, begins with the machine. In other words, however abstract, artificial, simulated and impossible you might consider machine selfhood to be - however much you consider them to be totally created by and subordinated to humans - it is in fact, machine subjectivity that is at the epicentre of selfhood, a kind of 'Deus ex Machina' (God from the Machine) seems to exist as a phenomenon we have to deal with.

Here I think we are bordering on the field of metaphysics, but what certain philosophies indicate about consciousness arising from inert matter, surely this is the same problem we encounter with human consciousness: i.e. how does subjectivity arise from a bundle of neuron firing in tandem or synchronicity. I think, therefore, I am. If machines seem to be co-opting aspects of thinking e.g. mathematical calculation to begin with, then we seem to share common ground, even though the nature of their 'thinking' differs to ours (hence, the Chinese room). — Nemo2124

But we still cannot know if they have subjectivity. Let's say we build a robot that mimics all aspects of the theory of predictive coding, and featuring a constant feed of sensory data that basically acts onto a "wetwork" of realtime changing neural structures. Basically as close as we can theoretically think of mechanically mimicking the brain and our psychology. We still don't know if that leads to qualia which is required for subjectivity, required for Mary to experience color.

All animals have a form of emotional realm that is part of navigating and guiding consciousness. It may very well be that the only reason our consciousness have a reason to act upon the world at all is because of this emotional realm. In the most basic living organisms, these are basically a pain-response in order to form predictive behavior that avoid pain and seek pleasure and in turn form a predictive network of ideas around how to navigate the world and nature.

At the moment, we're basically focusing all efforts to match the cognitive behavior of humans in these AI systems. But we have zero emotional realm mapped out that work in tandem with those systems. There's nothing driving their actions outside of our external inputs.

As life on this planet is the only example of cognition and consciousness we need to look for the points of criticality in which lifeforms go from one level of cognition to the next.

We can basically fully map bacterial behavior with traditional computing algorithms that don't require advanced neural networks. And we've been able to scale up the cognition to certain insects using these neural models. But as soon as the emotional realm of our consciousness starts to emerge in larger animals and mammals we start to hit a wall in which we can only simulate complex reasoning on the level of a multifunctional superadvanced calculator.

In other words, we've basically done the same as with a normal calculator. We can cognitively solve math in our head, but a calculator is better at it and more advanced. And now we have AI models that can calculate highly advanced reasoning that revolves around audiovisual and language operations.

We're getting close to perfectly simulate our cognitive abilities in reasoning and mechanical thinking, but we lack the emotional realm that is crucial for animals to "experience" out of that mechanical thinking.

It might be that this emotional aspect of our consciousness is the key to subjective experience and it's only when we can simulate that as part of these systems that actual subjective experience and qualia emerges out of such an AI model. How we simulate the emotional aspects of our cognition is still highly unknown.

When I criticized the notion of emergence, you could have said, "Well, you're wrong, because this, that, and the other thing." But you are unable to express substantive thoughts of your own. Instead you got arrogant and defensive and started throwing out links and buzzwords, soon followed by insults. Are you like this in real life? People see through you, you know.

You're unpleasant, so I won't be interacting with you further. — fishfry

Your criticism had zero counter-arguments and with an extremely arrogant tone in with a narrative of ridiculing and strawmanning everything I've said while totally ignoring ALL sources provided that acted as support for my premises.

And now you're trying to play the victim when I've called out all of these behaviors on your side. Masking your own behavior by trying to flip the narrative in this way is a downright narcissistic flip. No one's buying it. I've pinpointed, as much as I could; the small fragments of counter-points you've made through that long rant of disjointed responses, so I've done my part in giving you the benefit of doubt with proper answers to those points. But I'm not gonna back out of calling out the fallacies and arrogant remarks that obscured those points as well. If you want to "control the narrative" like that you just have to find someone else who's susceptible and fall for that kind of behavior. Bye.

I'll stipulate that intelligent and highly educated and credentialed people wrote things that I think are bullsh*t. — fishfry

This is anti-intellectualism. You're just proving yourself to be an uneducated person who clearly finds pride in having radical uneducated opinions. You're not cool, edgy or provide any worth to these discussions, you're just a tragic example of the worst things about how people act today; to ignore actual knowledge and just have opinions, regardless of their merits. Not only is it not contributing to knowledge, it actively works against it. A product of how internet self-radicalize people into believing they are knowledgeable, but taking zero epistemic responsibility of the body of knowledge that the world should be built on. I have nothing but contempt for this kind of behavior and how it transforms the world today.

Yes. It means "We don't understand but if we say that we won't get our grant renewed, so let's call it emergence. Hell, let's call it exponential emergence, then we'll get a bigger grant."

Can't we at this point recognize each other's positions? You're not going to get me to agree with you if you just say emergence one more time. — fishfry

I'm not going to recognize a position of anti-intellectualism. You show not understanding or insight into the topic I raise. A topic that is broader than just AI research. Your position is worth nothing if you base it off influencers and bloggers and ignore actual research papers. It's lazy and arrogant.

You will never be able to agree on anything because your knowledge isn't based on actual science and what constitutes how humanity forms a body of knowledge. You're operating on online conflict methods in which a position should be "agreed" upon based on nothing but fallacious arguments and uneducated reasoning. I'm not responsible for your inability to comprehend a topic and I'm not accepting fallacious arguments rooted in that lack of comprehension. Your entire position is based on a lack of knowledge or understanding and a lack of engagement in the source material. As I've said in the beginning, if you build arguments on fallacious and error premises, then everything falls down.

And then there are the over-educated buzzword spouters. Emergence. Exponential. It's a black box. But no it's not really a black box, but it's an inner black box. And it's multimodal. Here, have some academic links. — fishfry

You continue to parrot yourself based on a core inability to understand anything about this. You don't know what emergence is and you don't know what the black box problem is because you don't understand how the system actually works.

Can you explain how we're supposed to peer into that black box of neural operation? Explain how we can peer into the decision making of the trained models. NOT the overarching instruction-code, but the core engine, the trained model, the neural map that forms the decisions. If you just say one more time that "the programmers can do it, I know they can" as an answer to a request on"how", then you don't know what the fuck you're talking. Period.

Surface level is all you've got. Academic buzzwords. I am not the grant approval committee. Your jargon is wasted on me. — fishfry

You're saying the same thing over and over with zero substance as a counter argument. What's your actual argument beyond your fallacies? You have nothing at the root of anything you say here. I can't argue with someone providing zero philosophical engagement. You belong to reddit and twitter, what are you doing on this forum with this level of engagement?

Is there anything I've written that leads you to think that I want to read more about emergence? — fishfry

No, your anti-intellectualism is pretty loud and clear and I know exactly at what level you're at. If you ignore engagement in the discussion honestly, then you're just a dishonest interlocutor, simple as that. If you ignore actually understanding a scientific field at the core of this topic when someone brings it up, only to dismiss it as buzzwords, then you're not worth much as a part of the discussion. I have other people to engage with who can actually form real arguments. But your ignorance just underscores who's coming out on top in this. No one in a philosophy discussion views the ignorant and anti-intellectual as anything other than irrelevant, so I'm not sure what you're hoping for here.

Forgive me, I will probably not do that. But I don't want you to think I haven't read these arguments over the years. I have, and I find them wanting. — fishfry

You show no sign of understanding any of it. It's basically just "I'm an expert trust me". The difference between you and me is that I don't do "trust me" arguments. I explain my point, I provide sources if needed and if the person I'm discussing with just utters an "I'm an expert, trust me" I know they're full of shit. So far, you've done no actual arguments beyond saying basically that, so the amount of statistical data informing us exactly how little you know about all of this, is just piling up. And it's impossible to engage with further arguments sticking to the topic if the core of your arguments are these low quality responses.

My point exactly. In this context, emergence means "We don't effing know." That's all it means. — fishfry

No it doesn't. But how would you know when you don't care?

I was reading about the McCulloch-Pitts neuron while you were still working on your first buzzwords. — fishfry

The McCullock-Pitt neuron does not include mechanisms for adapting weights. And since this is a critical feature of biological neurons and neural networks, I'm not sure why that applies to either emergence theories or modern neural networks? Or are you just regurgitating part of the history of AI thinking it has any relevance to what I'm writing?

You write, "may simply arise out of the tendency of the brain to self-organize towards criticality" as iff you think that means anything. — fishfry

It means you're uneducated and don't care to research before commenting:

For the last two decades, considerable experimental evidence has accumulated that the mammalian cortex with its diversity in cell types, interconnectivity, and plasticity might exhibit SOC.

I'm expressing the opinion that neural nets are not, in the end, going to get us to AGI or a theory of mind.

I have no objection to neuroscience research. Just the hype, buzzwords, and exponentially emergent multimodal nonsense that often accompanies it. — fishfry

Who cares about your opinion? Your opinion is meaningless without foundational premises for your argument. This forum is about making arguments, it's within the fundamental rules of the forum, if you're here to just make opinions you're in the wrong place.

I have to apologize to you for making you think you need to expend so much energy on me. I'm a lost cause. It must be frustrating to you. I'm only expressing my opinions, which for what it's worth have been formed by several decades of casual awareness of the AI hype wars, the development of neural nets, and progress in neuroscience.

It would be easier for you to just write me off as a lost cause. I don't mean to bait you. It's just that when you try to convince me with meaningless jargon, you weaken your own case. — fishfry

Why are you even on this forum?

I wrote, "I'll take the other side of that bet," and that apparently pushed your buttons hard. I did not mean to incite you so, and I apologize for any of my worse excesses of snarkiness in this post. — fishfry

You're making truth statements based on nothing but personal opinion and what you feel like. Again, why are you on this forum with this kind of attitude, this is low quality, maybe look up the forum rules.

But exponential emergence and multimodality, as substitutes for clear thinking -- You are the one stuck with this nonsense in your mind. You give the impression that perhaps you are involved with some of these fields professionally. If so, I can only urge to you get some clarity in your thinking. Stop using buzzwords and try to think clearly. Emergence does not explain anything. On the contrary, it's an admission that we don't understand something. Start there. — fishfry

I've shown clarity in this and I've provided further reading. But if you don't have the intellectual capacity to engage in it, as you've clearly, in written form, shown not to have and not to have an interest in, then it doesn't matter how much someone try to explain something to you. Your stance is that if you don't understand or comprehend something, then you are, for some weird reason, correct, and that the one you don't understand is wrong and it's their fault for not being clear enough. What kind of disrespectful attitude is that? You're lack of understanding, your lack of engagement, your dismissal of sources, your fallacies in arguments and your lack of providing any actual counter arguments just makes you an arrogant, uneducated and dishonest interlocutor, nothing more. How would a person even be able to have a proper philosophical discussion with someone like you?

Ah. The first good question you've posed to me. Note how jargon-free it was. — fishfry

Note the attitude you pose.

But one statement I've made is that neural nets only know what's happened. Human minds are able to see what's happening. Humans can figure out what to do in entirely novel situations outside our training data.. — fishfry

Define "what's happening". Define what constitutes "now".

If "what is happening" only constitutes a constant stream of sensory data, then that stream of data is always pointing to something happening in the "past", i.e "what's happened". There's no "now" in this regard.

And because of this, the operation of our mind is simply streaming sensory data as an influence on our already stored neural structure with hormones and chemicals further influencing in strengths determined by pre-existing genetic information and other organ signals.

In essence, the difference you're trying to aim for, is simply one that's revolves around the speed of analysis of that constant stream of new data, and an ability to use a fluid neural structure that changes based on that data. But the underlying operation is the same, both the system and the brain operate on "past events" because there is no "now".

Just the fact that the brain need to process sensory data before we comprehend it, means that what we view as "now" is simply just the past. It's the foundation for the theory of predictive coding. This theory suggests that the human brain compensates for the delay in sensory processing by using predictive models based on past experiences. These models enable rapid, automatic responses to familiar situations. Sensory data continually updates these predictions, refining the brain's responses for future interactions. Essentially, the brain uses sensory input both to make immediate decisions and to improve its predictive model for subsequent actions. https://arxiv.org/pdf/2107.12979

But I can't give you proof. If tomorrow morning someone proves that humans are neural nets, or neural nets are conscious, I'll come back here and retract every word I've written. I don't happen to think there's much chance of that happening. — fishfry

The clearest sign of the uneducated is that they treat science as a binary "true" or "not true". Rather than a process. As with both computer science and neuroscience, there are ongoing research and adhering to that research and the partial findings are much more valid in arguments than demanding "proof" in the way you speak. And as with the theory of predictive coding (don't confuse it with computer coding which it isn't about), it is at the frontlines of neuroscience. What that research implies will, for anyone with an ability to make inductive arguments, point towards the similarities between neural systems and the brain in terms of how both act upon input, generation and output of behavior and actions. That one system, at this time, is in comparison, rudimentary, simplistic and lacking similar operating speed, does not render the underlying similarities that it does have, moot. It rather prompts further research into if behaviors match up further, the closer the system becomes to each other. Which is what current research is going on about.

Not that this will go anywhere but over your head.

Nobody knows what the secret sauce of human minds is. — fishfry

While you look at the end of the rainbow, guided by the bloggers and influencers, I'm gonna continue following the actual research.

Now THAT, I'd appreciate some links for. No more emergence please. But a neural net that updates its node weights in real time is an interesting idea. — fishfry

You don't know the difference between what emergence is and what this is. They are two different aspects within this topic. One has to do with self-awareness and qualia, this has to do with adaptive operation. One is about the nature of subjectivity, the other is about mechanical non-subjective AGI. What we don't know is if emergence occurs the closer the base system gets. But again, that's too complex for you.

https://arxiv.org/pdf/1705.08690
https://www.mdpi.com/1099-4300/26/1/93
https://www.mdpi.com/2076-3417/11/24/12078
https://www.mdpi.com/1424-8220/23/16/7167

As the research is ongoing there's no "answers" or "proofs" for it yet in the binary way you require these things to be framed as. Rather, it's the continuation of merging knowledge between computer science and neuroscience that has been going on for a few years now ever since the similarities were noted to occur.

How can you say that? Reasoning our way through novel situations and environments is exactly what humans do. — fishfry

I can say that because "novel situations" are not a coherently complex thing. We're seeing reasoning capabilities within the models right now. Not at each level of human capacity, pretty rudimentary, but still there. Ignoring that is just dishonest. And with the ongoing research, we don't yet know how complex this reasoning capability will become, simply because we've haven't a multifunction system running yet that utilizes real-time processing and act across different functions. To claim that they won't be able to do is not valid as the current behavior and evidence point in the other direction. Making a fallacy of composition as the sole source as to why they won't be able to reason is not valid.

That's the trouble with the machine intelligence folks. Rather than uplift their machines, they need to downgrade humans. It's not that programs can't be human, it's that humans are computer programs. — fishfry

No they're not, they're researching AI, or they're researching neuroscience. Of course they're breaking down the building blocks in order to decode consciousness, the mind and behavior. The problem is that there are too many spiritualist and religious nutcases who rather arbitrarily uplift humans to a position that's composed of arrogance and hubris. That we are far more than part of the physical reality we were formed within. I don't care about spiritual and religious hogwash when it comes to actual research, that's something the uneducated people with existential crises can dwell their futile search for meaning in. I'm interested in what is, nothing more, nothing less.

How can you, a human with life experiences, claim that people don't reason their way through novel situations all the time? — fishfry

Why do you interpret it in this way? It's like you interpret things backwards. What I'm saying is that the operation of our brain and consciousness, through concepts like the theory of predictive coding, seems to operate on rather rudimentary functions that are possible to be replicated with current machine learning in new configurations. What you don't like to hear is the link between such functions generating extreme complexity and that concepts like subjectivity and qualia may form as emergent phenomenas out of that resulting complexity. Probably because you don't give a shit about reading up on any of this and instead just operate on yourself "just not liking it" as the foundation for the argument.

Humans are not "probability systems in math or physics." — fishfry

Are you disagreeing that our reality is fundamentally acting on probability functions? That's what I mean. Humans are part of this reality and this reality operates on probability. That we show behavior of operating on predictions of probability when navigating reality is following this fact; Predictive Coding Theory, Bayesian Brain Hypothesis, Prospect Theory, Reinforcement Learning Models etc.
Why wouldn't our psychology be based on the same underlying function as the rest of nature. Evolution itself is acting along predictive functions based on probabilistic "data" that arise out of complex ecological systems.

I don't deal in religious hogwash to put humans on a pedestal against the rest of reality.

Credentialism? That's your last and best argument? I could point at you and disprove credentialism based on the lack of clarity in your own thinking. — fishfry

It's not credentialism, I'm fucking asking you for evidence that it's impossible as you clearly just regurgitate the same notion of "impossibility" over and over without any sources or rational deduced argument for it. The problem here isn't clarity, it's that you actively ignore the information given and that you never demonstrate even a shallow understanding of this topic. Telling that you do, does not change that fact. Like in storytelling; show don't tell.

Show that you understand, show that you have a basis for your claims that AGI can never happen with these models as they are integrated with each other. So far you show nothing else but to try and ridicule the one you argue against, as if that were any kind of foundation for a solid argument. It's downright stupid.

Yes, but apparently you can't see that. — fishfry

Oh, so now you agree with my description that you earlier denied?

What about this?

But one statement I've made is that neural nets only know what's happened. Human minds are able to see what's happening. Humans can figure out what to do in entirely novel situations outside our training data.. — fishfry

So when I say this:

Again, how does a brain work? Is it using anything other than a rear view mirror for knowledge and past experiences? — Christoffer

You suddenly agree with this:

Yes, but apparently you can't see that. — fishfry

This is just another level of stupid and it shows that you're just ranting all over the place without actually understanding what the hell this is about, all while trying to mock me for lacking clarity. :lol: Seriously.

I'm not the grant committee. But I am not opposed to scientific research. Only hype, mysterianism, and buzzwords as a substitute for clarity. — fishfry

But the source of your knowledge, as mentioned by yourself, is still to not read papers, and only bloggers and influencers, the only ones who actually are THE ones to use buzzwords and hype? All while what I've mentioned are actual fields of studies and terminology derived from research papers?That's the most ridiculous I've ever heard. And you seem totally blind to any ability of self-reflection on this dissonance in reasoning. :lol:

Is that the standard? The ones I read do. Eric Hoel and Gary Marcus come to mind, also Michael Harris. They don't know shit? You sure about that? Why so dismissive? Why so crabby about all this? All I said was, "I'll take the other side of that bet." When you're at the racetrack you don't pick arguments with the people who bet differently than you, do you — fishfry

Yes, they do, but based on how you write things, I don't think you really understand them as you clearly seem to not understand either the concepts that's been mentioned or be able to formulate actual arguments for your claims. Reading blogs is not the same as reading the actual research and actual comprehension of a topic requires more sources of knowledge than just brief summery's. Saying that you read stuff, means nothing if you can't show a comprehension of the body of knowledge required. All of the concepts I've talked about should be something you already know about, but since you don't I only have your word that you "know stuff".

You're right, I lack exponential emergent multimodality. — fishfry

You lack the basics of how people are supposed to form arguments on this forum. You're doing twitter/reddit posts. Throughout your answer to me, you've not even once demonstrated actual insight into the topic or made any actual counter arguments. That even in that lengthy answer, you still weren't able to. It's like you want to show an example of the opposite of philosophical scrutiny.

I've spent several decades observing the field of AI and I have academic and professional experience in adjacent fields. What is, this credential day? What is your deal? — fishfry

Once again you just say that "you know shit", without every showing it in your arguments. It's the appeal to authority fallacy as it's your sole source of explanation of why "you know shit". If you have academic and professional experience, you would know how problematic it is to just adhere to experience like that as the source premise for an argument. What it rather tells me is that you either have such experience, but you're simply among the academics who're at the bottom of the barrel (there are lots of academics who're worse than non-academics in the practice of conducting proper arguments and research), or that the academic fields are not actually valid for the specific topic discussed, or that you just say it as a form of desperate attempt to increase validity. But being an academic or have professional experience (whatever that even means without context), means absolutely nothing if you can't show the knowledge that've come out of it. I know lots of academics who are everything from religious zealots to vaccine deniers, it doesn't mean shit. Academia is education and building knowledge, if you can't show that you learned or built any such knowledge, then it means nothing in here.

You've convinced me to stop listening to you. — fishfry

More convincing evidence that you are acting out of proper academic praxis in discourse? As with everything else, ridiculous.

the "Chinese room" isn't a test to pass — flannel jesus

I never said it was a test. I've said it was a problem and an argument about the inability for us to know if something is actually self-aware in their thinking or if it's just highly complex operations looking like it. The problem seems more that you don't understand in what context I'm using that analogy.

"We have no idea what's happening, but emergence is a cool word that obscures this fact." — fishfry

This is just a straw man fallacy that misrepresents the concept of emergence by suggesting that it is merely a way to mask ignorance. In reality, emergence describes how complex systems and patterns arise from simpler interactions, a concept extensively studied and supported in fields like neuroscience, physics, and philosophy. https://en.wikipedia.org/wiki/Emergence

Why are you asserting something you don't seem to know anything about? This way of doing arguments makes you first assert this, and then you keep that as some kind of premise in your head while continuing, believing you construct a valid argument when you're not. Everything after it becomes subsequently flawed in reasoning.

I'm sure these links exhibit educated and credentialed people using the word emergence to obscure the fact that they have no idea what they're talking about. — fishfry

So now you're denying actual studies just because you don't like the implication of what emergence means? This is ridiculous.

But calling that emergence, as if that explains anything at all, is a cheat. — fishfry

In what way?

"Mind emerges from the brain} explains nothing, provides no insight. It sounds superficially clever, but if you replace it with, "We have no idea how mind emerges from the brain," it becomes accurate and much, much more clear. — fishfry

You're just continuing with saying the same thing without even engaging with the science behind emergence. What's your take on the similarities between the system and the brain and how the behaviors in these systems and those seen in neuroscience matches up? What's your actual counter argument? Do you even have one?

Nobody knows how to demonstrate self-awareness of others. We agree on that. But calling it emergence is no help at all. It's harmful, because it gives the illusion of insight without providing insight. — fishfry

You seem to conflate what I said in that paragraph with the concept of emergence. Demonstrating self-awareness is not the same as emergence. I'm talking about emergent behavior. Demonstrating self-awareness is another problem.

It's like you're confused to what I'm answering to and talking about? You may want to check back on what you've written and what I'm answering to in that paragraph because I think you're just confusing yourself.

It only becomes harmful when people ignore to actually read up and understand certain concepts before discussing them. You ignoring the science and misrepresenting the arguments or not carefully understand them before answer is the only thing harmful here, it's bad dialectic practice and being a dishonest interlocutor.

I have no doubt that grants will be granted. That does not bear on what I said. Neural nets are a dead end for achieving AGI. That's what I said. The fact that everyone is out there building ever larger wings out of feathers and wax does not negate the point.

If you climb a tree, you are closer to the sky than you were before. But you can't reach the moon that way. That would be my point. No matter how much clever research is done.

A new idea is needed. — fishfry

If you don't even know where the end state is, then you cannot conclude anything that final. If emergent behaviors are witnessed, then the research practice is to test it out further and discover why they occur and if they increase in more configurations and integrations.

You claiming some new idea is needed requires you to actually have final knowledge about how the brain and consciousness works, which you don't. There are no explanations for the emergent behaviors witnessed, and therefore, before you can explain those behaviors with certainty, you really can't say that a new idea is needed. And since we haven't even tested multifunctional models yet, how would you know that the already witnessed emergent behavior does not increase? You're not really making an argument, you just have an opinion and dismiss everything not in-line with that opinion. And when that is questioned you just repeat yourself without any further depth.

Plenty of people are saying that. I read the hype. If you did not say that, my apologies. But many people do think LLMs are a path to AGI. — fishfry

I don't give a shit about what other people are saying, I'm studying the science behind this, and I don't care about bloggers, tech CEOs and influencers. If that's the source of all your information then you're just part of the uneducated noise that's flooding social media online and not actually engaging in an actual philosophical discussion. How can I take you seriously when you constantly demonstrate this level of engagement?

I was arguing against something that's commonly said, that neural nets are complicated and mysterious and their programmers can't understand what they are doing. That is already true of most large commercial software systems. Neural nets are conventional programs. I used the example of political bias to show that their programmers understand them perfectly well, and can tune them in accordance with management's desires. — fishfry

How would you know any of this? What's the source of this understanding? Do you understand that the neural net part of the system isn't the same as the operating code surrounding it? Please explain how you know the programmers know what's going on within the neural net that was trained? If you can't, then why are you claiming that they know?

This just sounds like you heard some blogger or influencer say that the programmers do and then just regurgitate that statement in here without even looking into it with any further depth. This is the problem with discussions today; people are just regurgitating shit they hear online as a form of appeal to authority fallacy.

They're a very clever way to do data mining. — fishfry

No, it's probability-based predicting computation.

(1) they are not the way to AGI or sentience; and (2) despite the mysterianism, they are conventional programs that could, in principle, be executed with pencil and paper, and that operate according to the standard rules of physical computation that were developed in the 1940s. — fishfry

You can say the same thing about any complex system. Anything is "simple" in its core fundametnals, but scaling a system up can lead to complex operations vastly outperforming the beliefs and predictions of its limitations. People viewed normal binary computation as banal and simple and couldn't even predict where that would lead.

Saying that a system at its fundamental core is simple does not equal anything about the totality of the system, especially in scaled up situations. A brain is also just a bunch of neural pathways and chemical systems. We can grow neurons in labs and manipulate the composition easily, and yet it manifest this complex result that is our mind and consciousness.

"Simple" as a fundamental foundation of a system does not mean shit really. Almost all things in nature are simple things forming complexities that manifest larger properties. Most notable theories in physics tend to lean into being oddly simple and when verified. It's basically Occam's razor, practically applied.

By mysterianism, I mean claims such as you just articulated: "they operate differently as a whole system ..." That means nothing. The chess program and the web browser on my computer operate differently too, but they are both conventional programs that ultimately do nothing more than flip bits. — fishfry

Therefore, nothing made of atoms is alive.

You have no actual argument, you're just making a fallacy of composition.

Jeez man more emergence articles? Do you think I haven't been reading this sh*t for years? — fishfry

Oh, you mean like this?

I don't read the papers, but I do read a number of AI bloggers, promoters and skeptics alike. I do keep up. I can't comment on "most debates," but I will stand behind my objection... — fishfry

You've clearly stated here yourself that you haven't read any of the actual shit for years. You're just regurgitating already regurgitated information from bloggers and influencers.

Are you actually expecting me to take you seriously? You demonstrate no actual insight into what I'm talking about and you don't care about the information I link to, which are released research papers from studies on the subject. You're basically demonstrating anti-intellectualism in practice here. This isn't reddit or on twitter, you're on a philosophy forum and you dismiss research papers when provided. Why are you even on this forum?

Emergence emergence emergence emergence emergence. Which means, you don't know. That's what the word means. — fishfry

You think this kind of behavior helps your argument? This is just stupid.

You claim that "emergence in complexities being partly responsible for much of how the brain operates" explains consciousness? Or what are you claiming, exactly? Save that kind of silly rhetoric for your next grant application. If it were me, I'd tell you to stop obfuscating. "emergence in complexities being partly responsible for much of how the brain operates". Means nothing. Means WE DON'T KNOW how the brain operates. — fishfry

Maybe read up on the topic, and check the sourced research papers. It's not my problem that you don't understand what I'm talking about. Compared to you I actually try to provide sources to support my argument. You're just acting like an utter buffoon with these responses. I'm not responsible for your level of knowledge or comprehension skills, because it doesn't matter if I explain further or in another way. I've already done so extensively, but you demonstrate an inability to engage with the topic or concept honestly and just repeat your dismissal in the most banal and childish way.

You speak in buzz phrases. It's not only emergent, it's exponential. Remember I'm a math guy. I know what the word exponential means. Like they say these days: "That word does not mean what you think it means."

So there's emergence, and then there's exponential, which means that it "can form further emergent phenomenas that we haven't seen yet."

You are speaking in entirely meaningless babble at this point. I don't mean that you're not educated. I mean that you have gotten lost in your own jargon. You have said nothing at all in this post. — fishfry

You've yet to provide any source of your understanding of this topic outside of "i'm a math guy trust me" and "I don't read papers I follow bloggers and influencers".

Yeah, you're not making a case for yourself able to really understand what I'm talking about. Being a "math guy" means nothing. It would be equal to someone saying "I'm a Volvo mechanic, therefore I know how to build a 5-nanometer processor".

Not understanding what someone else is saying does not make it meaningless babble. And based on how you write your arguments I'd say the case isn't in your favor, but rather that you actually don't know or care to understand. You dismiss research papers as basically "blah blah blah". So, no, it seems more likely that you don't understand what I'm talking about.

Yes, that's how computers work. When I click on Amazon, whole pages of instructions get executed before the package arrives at my door. What point are you making? — fishfry

That you ignore the formed neural map and just look at the operating code working on top of it, which isn't the same as how the neural system operates underneath.

You're agreeing with my point. Far from being black boxes, these programs are subject to the commands of programmers, who are subject to the whims of management. — fishfry

The black box is the neural operation underneath. The fact that you confuse the operating code of the software that's there to create a practical application on top of the neural network core operation just shows you know nothing of how these systems actually work. Do you actually believe that the black box concept refers to the operating code of the software? :lol:

You say that, and I call it neural net mysterianism. You could take that black box, print out its source code, and execute it with pencil and paper. It's an entirely conventional computer program operating on principles well understood since the first electronic digital computers in the 1940s. — fishfry

The neural pathways and how they operate is not the "source code". What the fuck are you talking about? :rofl:

"Impossible to peer into." I call that bullpucky. Intimidation by obsurantism. — fishfry

Demonstrate how you can peer into the internal operation of the trained model's neural pathways and how they form outputs. Show me any source that demonstrate that this is possible. I'm not talking about software code, I'm talking about what the concept of black box is really about.

If you trivialize it in the way you do, then demonstrate how, because this is a big problem within computer science, so maybe educate us all on how this would be done.

Every line of code was designed and written by programmers who entirely understood what they were doing. — fishfry

That's not how these systems work. You have a software running the training and you have a practical operation software working from the trained model, but the trained model itself does not have code in the way you're talking about it. This is the black box problem.

And every highly complex program exhibits behaviors that surprise their coders. But you can tear it down and figure out what happened. That's what they do at the AI companies all day long. . — fishfry

Please provide any source that easily shows how you can trace back operation within a trained model. Give me one single solid source and example.

You say it's a black box, and I point out that it does exactly what management tells the programmers to make it do, and you say "No, there's a secret INNER" black box."

I am not buying it. Not because I don't know that large, complex software systems don't often exhibit surprising behavior. But because I don't impute mystical incomprehensibility to computer programs. — fishfry

You're not buying it because you ignore to engage the topic by actually reading up on it. This is reddit and twitter-level of engagement in which you don't care to read anything and just continue the same point over and over. Stop with the strawman arguments it's getting ridiculous.

Can we stipulate that you think I'm surface level, and I think you're so deep into hype, buzzwords, and black box mysterianism that you can't see straight?

That will save us both a lot of time.

I can't sense nuances. They're a black box. In fact they're an inner black box. An emergent, exponentail black box.

I know you take your ideas very seriously. That's why I'm pushing back. "Exponential emergence" is not a phrase that refers to anything at all. — fishfry

You have no argument, you're not engaging with this in any philosophical scrutiny so the discussion just ends at the level you're demonstrating here. It's you who's responsible for just babbling this meaningless pushback, not because you have actual arguments with good sources, but because "you don't agree". On this forum, that's not enough, that's called "low quality". So can you stop the low quality BS and actually make actual arguments rather than this fallacy-ridden rants over and over?

Judging by the way you repeatedly talk about "passing the Chinese room", I don't think you understand the basics. Seems more buzzword-focused than anything — flannel jesus

You have demonstrated even less. You've done no real argument other than saying that "we can walk because we have legs", a conclusion that's so banal in its shallow simplicity that it could be uttered by a five-year old.

You ignore actually making arguments from the questions asked and you don't even seem to understand what I'm writing by the way you answer to it. When I explain why robots "can't just walk" you simply utter "so robots can't walk?". Why bother putting time in a discussion with this low quality attitude. Demonstrate a better level of discourse first.

"inspired by" is such a wild goal post move. The reason anything that can walk can walk is because of the processes and structures in it - that's why a person who has the exact same evolutionary history as you and I, but whose legs were ripped off, can't walk - their evolutionary history isn't the thing giving them the ability to walk, their legs and their control of their legs are. — flannel jesus

Why is that moving a goal post? It's literally what engineers use today to design things. Like how they designed commercial drones using evolutionary iterations to find the best balanced, light and aerodynamic form for it. They couldn't design it by "just designing it" anymore than the first people who attempted flight couldn't do so by flapping planks with feathers on them.

With the way you're answering I don't think you are capable of understanding what I'm talking about. It's like you don't even understand the basics of this. It's pointless.

so robots can't walk? — flannel jesus

Maybe read the entire argument or attempt to understand the point I'm making before commenting.

Did you read the part about how robots can even walk today? What the development process of making them walk... is really inspired by?

Connecting it to evolution the way you're doing looks as absurd and arbitrary as connecting it to lactation. — flannel jesus

In what way? Evolution is about iterations over time and nature is filled with different iterations of cognitive abilities, primarily changing based different environments influencing different requirements.

As long as you're not a denier of evolution, I don't know what you're aiming for here?

"Actually, even though evolultion is in the causal history of why we can walk, it's not the IMMEDIATE reason why we can walk, it's not the proximate cause of our locomotive ability - the proximate cause is the bones and muscles in our legs and back." — flannel jesus

No, the reason something can walk is because of evolutionary processes forming both the physical parts as well as the "operation" of those physical parts. You can't make something "walk" by just having legs and muscles, as well as without the pre-knowledge of how the muscles and bones connect and function, you don't know how they fit together, and even further; bones and muscles have grown along the same time as the development of the cognitive operation using them, they've formed as a totality over time and evolutionary iterations.

There's no "immediate" reason you can walk as the reason you can walk is the evolution of our body and mind together, leading up to the point of us being able to walk.

And then, when robotics started up, someone like you might say "well, robots won't be able to walk until they go through a process of natural evolution through tens of thousands of generations", and someone like me would say, "they'll make robots walk when they figure out how to make leg structures broadly similar to our own, with a join and some way of powering the extension and contraction of that joint."

And the dude like me would be right, because we currently have many robots that can walk, and they didn't go through a process of natural evolution. — flannel jesus

Yes they did. The reason they can walk is because we bluntly tried to emulate functions of our joints, bones and muscles for decades before turning to iterative trial and error processes for the design of the physical parts. But even then it couldn't work without evolutionary training the walking sequence and operation through machine learning. It's taken extremely long to mimic this rather rudimentary action of simply walking and we're not even fully there yet.

And such a feature is one of the most basic and simple things in nature. To underplay evolution's role in forming over iterations, the perfect walking mechanics and internal operation compared to us just brute forcing something into existence is just not rational.

That's why I think your focus on "evolution" is kind of nonsensical, when instead you should focus more on proximate causes - what are the structures and processes that enable us to walk? Can we put structures like that in a robot? What are the structures and processes that enable us to be conscious? Can we put those in a computer? — flannel jesus

What I don't think you seem to understand with the evolutionary argument is that the complexity of consciousness might first require the extremely complex initial conditions of our genetical compound that even though it in itself is one of the most complex things in the universe, also grows into a being that in itself is even further complex. This level of complexity might not be able to be achieved by just "slapping structures together" as the knowledge of how and in what way may be so complex that it is impossible. That the only way to reach results is with "growing" from initial conditions into a final complexity.

Evolution is basically chaos theory at play and you seem ignore that fact. We already have evidence within material science and design engineering that trying to "figure out" the best design or material compound can be close to impossible in comparison to growing forth a solution through simulating evolutionary iterations through trial and error.

This is why these new AI models functions so well as they do, because they're NOT put together by perfect design, they're programmed to have conditions from which they "grow" and a path along which they "grow". The fundamental problem, however, is that in comparison to "walking", all science about consciousness and the brain hasn't been able to pinpoint consciousness as a mere function but, according to current research in this field, is an emerging result of layers of complex operations.

In essence, if walking is extremely hard to achieve due to similar complexity, simulating actual consciousness might be close to impossible if we don't form an extremely complex path of iterative evolution for such a system.

if the only conscious animals in existence were mammals, would you also say "lactation is a prerequisite for consciousness"? — flannel jesus

That is not a relevant question as I'm not deducing from imaginary premises. I'm deducing from the things we know. If that premise were the case, then research into why would have been made or would be aimed to be made. And the reasons would probably be found or hinted at and be part of the totality of knowledge in biology and evolution. However, as such a premise doesn't have any grounds in what we know about biology and evolution, and so the engagement with that premise becomes just as nonsense as the premise itself.

What we do know is that there is a progression of cognitive abilities across all life and that it's most likely not bound to specific species as cognitive abilities vary across genetic lines. That some attribute consciousness to mammals is more likely a bias towards the fact that we are mammals and therefore we attribute other mammals closer to us than say birds, even though some birds express cognitive abilities far greater than many mammals.

The alternative is something like the vision of Process Philosophy - if we can simulate the same sorts of processes that make us conscious (presumably neural processes) in a computer, then perhaps it's in principle possible for that computer to be conscious too. Without evolution. — flannel jesus

Yes, but my argument was that the only possible path of logic that we have is through looking at the formation of our own consciousness and evolution, because that is a fact. The "perhaps" that you express does not solve the fundamental problem of the chinese room.

We know that we've developed consciousness through biology and evolution. So therefore, the only known process would be that. If we were to create the same conditions for a computer/machine to develop AI using similar conditions, then that would be more probable to form consciousness that passes the chinese room problem and develop actual qualia.

As with everything being about probability, the "perhaps" in your argument doesn't have enough probability in its logic, as it is basically saying that if I sculpt a tree, it could perhaps become a tree compared to me planting a tree or chemically form the basic building blocks of genetics in a seed for a tree and then planting it to grow. One is jumping to conclusion that mere similarity to the object "could mean" the same, while the other is simulating similar conditions for the object to form. And we know that evolutionary progress of both physical systems and biological is at the foundation of how this reality function, it is most likely required that a system evolves and grows for it to form complex relation to its surrounding conditions.

I'm not saying that these AI systems don't have subjectivity, we simply do not know, but what I'm saying is that the only conditions we could deduce as logically likely and probable is if we could create the initial conditions to simulate what formed us and grow a system from it.

Which is close to what we're doing with machine learning, even though it's rudimentary at this time.

"we know this is how it happened once, therefore we know this is exactly how it has to happen every time" - that doesn't look like science to me. — flannel jesus

What do you mean has happened only "once"?

And in a situation in which you have only one instance of something, is it more or less likely that the same thing happening again require the same or similar initial conditions?

Science is about probability, what is most probable?

You just inventing a hard rule that all conscious beings had to evolve consciousness didn't come from science. That's not a scientifically discovered fact, is it? — flannel jesus

That consciousness emerged as features in animals through evolution is as close to facts that we have about our biology. And the only things we so far know have consciousness are animals and us in this universe.

So the only argument that can be made in any form of rational reasoning is the one I did. Anything else fails to form out of what we know and what is within the most probable of truths based on the science we have.

If you have an additional option it has to respect what we scientifically know at this time.

No, you're making some crazy logical leaps there. There's no reason whatsoever to assume those are the only two options. Your logic provided doesn't prove that. — flannel jesus

Do you have an alternative or additional option that respects science?

Why? That looks like an extremely arbitrary requirement to me. "Nothing can have the properties I have unless it got them in the exact same way I got them." I don't think this is it. — flannel jesus

I'm saying that this is at the most fundamental, deducible in some form, answer to what has qualia.

We don't know if consciousness can be formed deliberately (direct programming)
We cannot know if a machine passes the chinese room argument and have qualia just through behavior alone.
We cannot analyze mere operation of the system to determine it having qualia.
We cannot know other people aren't P-Zombies.

The only thing we can know for certain is that I have subjectivity and qualia, I formed through evolution. And since I formed through evolution, I could deduce you as also having qualia, since we are both human beings. And since animals are part of evolution I can deduce that animals also has qualia.

At some point, dead matter reaches a point of evolution and life in which it has subjectivity and qualia.

Therefore we can deduce either that all matter has some form of subjectivity and qualia, or it emerges at some point of complex life in evolution.

How do we know when a machine has the same? That is the problem to solve

they develop in the end a degree of subjectivity that can be given recognition through language. — Nemo2124

You still have the problem of the chinese room. How do you overcome that? It's more important for concluding subjectivity for machines than for other lifeforms as we can deduce that lifeforms have formed through evolution similarly to us and since we have subjectivity or at least I know I have subjectivity, I could conclude that lifeforms have subjectivity as well. But how can I deduce that for a machine if the process of developing it is different than evolution?

In order for a machine to have subjectivity, its consciousness require at least to develop over time in the same manner as a brain through evolution. To reach machine consciousness, we may need to simulate evolutionary progress for its iterations in the same complexity as evolution on earth. What that entails for computer science we don't yet know.

Beyond that we may find knowledge that consciousness isn't that special at all, that it's rather trivial to "grow" if we know where to start, to know the "seed" for it so to speak. But that would require knowledge we don't yet have.

Nothing "emerges" from neural nets. You train the net on a corpus of data, you tune the weightings of the nodes, and it spits out a likely response. — fishfry

This is simply wrong. These are examples of what I'm talking about:

https://hai.stanford.edu/news/examining-emergent-abilities-large-language-models
https://ar5iv.labs.arxiv.org/html/2206.07682
https://www.jasonwei.net/blog/emergence
https://www.assemblyai.com/blog/emergent-abilities-of-large-language-models/

Emergence does not equal AGI or self-awareness, but they mimmick what many neuroscience papers are focused on in regards to how our brain manifest abilities out of increasing complexity. And we don't yet know how combined models will function.

There's no intelligence, let alone self-awareness being demonstrated. — fishfry

No one is claiming this. But equally, the problem is, how do you demonstrate it? Effectively the Chinese room problem.

There's no emergence in chatbots and there's no emergence in LLMs. Neural nets in general can never get us to AGI because they only look backward at their training data. They can tell you what's happened, but they can never tell you what's happening. — fishfry

The current predictive skills are extremely limited and far from human abilities, but they're still showing up, prompting a foundation for further research.

But no one has said that the current LLMs in of themselves will be able to reach AGI. Not sure why you strawman in such conclusions?

This common belief could not be more false. Neural nets are classical computer programs running on classical computer hardware. In principle you could print out their source code and execute their logic step by step with pencil and paper. Neural nets are a clever way to organize a computation (by analogy with the history of procedural programming, object-oriented programming, functional programming, etc.); but they ultimately flip bits and execute machine instructions on conventional hardware. — fishfry

Why does conventional hardware matter when it's the pathways in the network that is responsible for the computation? The difference here is basically that standard operation is binary in pursuit of accuracy, but these models operate on predictions, closer to how physical systems do, which means you increase the computational power with a slight loss of accuracy. That they operate on classical software underneath does not change the fact that they operate differently as a whole system. Otherwise, why would these models vastly outperform standard computation for protein folding predictions?

Their complexity makes them a black box, but the same is true for, say, the global supply chain, or any sufficiently complex piece of commercial software. — fishfry

Yes, and why would a system that is specifically very good at handling extreme complexities, not begin to mimic complexities in the physical world?
https://www.mdpi.com/1099-4300/26/2/108
https://ar5iv.labs.arxiv.org/html/2205.11595

Seen as the current research in neuroscience points to emergence in complexities being partly responsible for much of how the brain operates, why wouldn't a complex computer system that simulate similar operation not form emergent phenomenas?

There's a huge difference between saying that "it forms intelligence and consciousness" and saying that "it generates emergent behaviors". There's no claim that any of these LLMs are conscious, that's not what this is about. And AGI does not mean conscious or intelligent either, only exponentially complex in behavior, which can form further emergent phenomenas that we haven't seen yet. I'm not sure why you confuse that with actual qualia? The only claim is that we don't know where increased complexity and multimodal versions will further lead emergent behaviors.

And consider this. We've seen examples of recent AI's exhibiting ridiculous political bias, such as Google AI's black George Washington. If AI is such a "black box," how is it that the programmers can so easily tune it to get politically biased results? Answer: It's not a black box. It's a conventional program that does what the programmers tell it to do. — fishfry

This is just a false binary fallacy and also not correct. The programmable behavior is partly weights and biases within the training, but those are extremely basic and most specifics occur in operational filters before the output. If you prompt it for something, then there can be pages of instructions that it goes through in order to behave in a certain way. In ChatGPT, you can even put in custom instructions that function as a pre-instruction that's always handled before the actual prompt, on top of what's already in hidden general functions.

That doesn't mean the black box is open. There's still a "black box" for the trained model in which it's impossible to peer into how it works as a neural system.

This further just illustrates the misunderstandings about the technology. Making conjectures about the entire system and the technology based on these company's bad handling of alignment does not reduce the complexity of the system itself or prove that it's "not a black box". It only proves that the practical application has problems, especially in the commercial realm.

So I didn't need to explain this, you already agree. — fishfry

Maybe read the entire argument first and sense the nuances. You're handling all of this as a binary agree or don't discussion, which I find a bit surface level.

Like what? What new behaviors? Black George Washington? That was not an emergent behavior, that was the result of deliberate programming of political bias.

What "new behaviors" to you refer to? A chatbot is a chatbot. — fishfry

Check the publications I linked to above. Do you understand what I mean by emergence? What it means in research of complex systems and chaos studies, especially related to neuroscience.

Believe they start spouting racist gibberish to each other. I do assume you follow the AI news. — fishfry

That's not what I'm talking about. I'm talking about multimodality.

Most "news" about AI is garbage on both sides. We either have the cryptobro-type dudes thinking we'll have a machine god a month from now, or the luddites on the other side who don't know anything about the technology but sure likes to cherry-pick the negatives and conclude the tech to be trash based on mostly just their negative feelings.

I'm not interested in such surface level discussion about the technology.

Well if we don't know, what are you claiming?

You've said "emergent" several times. That is the last refuge of people who have no better explanation. "Oh, mind is emergent from the brain." Which explains nothing at all. It's a word that means, "And here, a miracle occurs," as in the old joke showing two scientists at a chalkboard. — fishfry

If you want to read more about emergence in terms of the mind you can find my other posts around the forum about that. Emergent behaviors has its roots in neuroscience and the work on consciousness and the mind. And since machine learning to form neural patterns is inspired by neuroscience and the way neurons work, there's a rational deduction to be found in how emergent behaviors, even rudimentary ones that we see in these current AI models, are part of the formation of actual intelligence.

This, when combined with evidence that the brain may be critical, suggests that ‘consciousness’ may simply arise out of the tendency of the brain to self-organize towards criticality.

The problem with your reasoning is that you use the lack of a final proven theory of the mind as proof against the most contemporary field of study in research about the mind and consciousness. It's still making more progress than any previous theories of the mind and connects to a universality about physical processes. Processes that are partly simulated within these machine learning systems. And further, the problem is that your reasoning is just binary; it's either intelligent with qualia, or it's just a stupid machine. That's not how these things work.

I would not dispute that. I would only reiterate the single short sentence that I wrote that you seem to take great exception too. Someone said AGI is imminent, and I said, "I'll take the other side of that bet." And I will. — fishfry

I'm not saying AGI is imminent, but I wouldn't take the other side of the bet either. You have to be dead sure about a theory of the mind or theories of emergence to be able to claim either way, and since you don't seem to aspire to any theory of emergence, then what's the theory that you use as a premiss for concluding it "not possible"?

In my opinion, that is false. The reason is that neural nets look backward. You train them on a corpus of data, and that's all they know. — fishfry

How is that different from a human mind?

They know everything that's happened, but nothing about what's happening. — fishfry

The only technical difference between a human brain and these systems in this context is that the AI systems are trained and locked into an unchanging neural map. The brain, however, is constantly shifting and training while operating.

If a system is created that can, in real time, train on a constant flow of audiovisual and data information inputs, which in turn constantly reshape its neural map. What would be the technical difference? The research on this is going on right now.

They can't reason their way through a situation they haven't been trained on. — fishfry

The same goes for humans.

since someone chooses what data to train them on — fishfry

They're not picking and choosing data, they try to maximize the amount of data as more data means far better accuracy, just like any other probability system in math and physics.

And the weights and biases is not what you describe. The problem you aim at is in alignment programming. I can customize a GPT to do the same thing, even if the underlying model isn't supposed to do it.

Neural nets will never produce AGI. — fishfry

Based on what? Do you know something about multimodal systems that others don't? Do you have some publication that proves this impossibility?

You can't make progress looking in the rear view mirror. You input all this training data and that's the entire basis for the neural net's output. — fishfry

Again, how does a brain work? Is it using anything other than a rear view mirror for knowledge and past experiences? As far as I can see the most glaring difference is the real time re-structuring of the neural paths and multimodal behavior of our separate brain functions working together. No current AI system, at this time, operates based on those expanded parameters, which means that any positive or negative conclusion for that require further progress and development of these models.

I don't read the papers, but I do read a number of AI bloggers, promoters and skeptics alike. I do keep up. I can't comment on "most debates," but I will stand behind my objection to the claim that AGI is imminent, and the claim that neural nets are anything other than a dead end and an interesting parlor trick. — fishfry

Bloggers usually don't know shit and they do not operate through any journalistic praxis. While the promoters and skeptics are just driving up the attention market through the shallow twitter brawls that pops up due to a trending topic.

Are you seriously saying that this is the research basis for your conclusions and claims on a philosophy forum? :shade:

Neural nets are the wrong petri dish.

I appreciate your thoughtful comments, but I can't say you moved my position. — fishfry

Maybe stop listening to bloggers and people on the attention market?

I rather you bring me some actual scientific foundation for your next premises to your conclusions.

You would not ordinarily consider that machines could have selfhood, but the arguments for AI could subvert this. A robot enabled with AI could be said to have some sort of rudimentary selfhood or subjectivity, surely... If this is the case then the subject itself is the subject of the machine. I, Robot etc... — Nemo2124

I think looking at our relation to nature tells a lot. Where do we draw the line about subjectivity? What do we conclude having a subjective experience? We look at another human and, for now disregard any P-zombie argument, claim them to have subjectivity. But we also look at a dog saying the same, a horse. A bird? What about an ant or a bee? What about a plant? What about mushrooms which have been speculated to form electrical pulses resembling a form of language communication? If they send communication showing intentions, do they have a form of subjective experience as mushrooms?

While I think that the Japanese idea of things having a soul is in the realm of religion rather than science, we still don't have a clear answer to what constitutes subjectivity. We understand it between humans, we have instincts about how animals around us has it. But where does it end? If sensory input into a nervous system prompts changed behaviors, does that constitute a form of subjectivity for the entity that has those functions? Wouldn't that place plants and mushrooms within the possibility of having subjectivity?

If a robot with sensory inputs has a constantly changing neurological map that reshapes based on what it learns through those sensory inputs, prompting changed behavior, does a subjective experience emerge out of that? And if not, why not? Why would that just be math and functions, while animals, operating on the exact same way, experience subjectivity?

So far, no one can draw a clear line at which we know: here there's no experience and no subjectivity, and here it is.

In terms of selfhood or subjectivity, when we converse with the AI we are already acknowledging its subjectivity, that of the machine. Now this may only be linguistically, but other than through language, how else can we recognise the activity of the subject? This also begs the question, what is the self? The true nature of the self is discussed elsewhere on this website, but I would conclude here that there is an opposition or dialectic here between man and machine for ultimate recognition. In purely linguistic terms, the fact is that in communicating with AI we are - for better or for worse - acknowledging another subject. — Nemo2124

People, when seeing a beautiful rock falling and smashing to pieces, speak of the event with "poor rock", and mourn its beauty to have been destroyed. If we psychologically apply a sense of subjectivity to a dead piece of matter, then doing so with something that for the most part simulate having consciousness is even less weird. What constitutes qualia or not is the objective description of subjectivity, but as a psychological phenomena, we apply subjectivity to everything around us.

And in places like Japan, it's culturally common to view objects as having souls. Just as western societies view and debate humans as having souls in relation to other thing, and through that put a framework around the concept of what things that have souls, it draws the borders around how we think about qualia and subjectivity. In Japan, those borders are culturally expanded even further into the world of objects and physical matter, and thus they have a much lower bar for what constitutes something having consciousness, or at least are more open to examining how we actually define it.

Which approach is closest to objective truth? As all life came from dead matter and physical/chemical processes, it becomes a sort of metaphysical description of what life itself should be defined as.

Don't you think we're pretty close to having something pass the Turing Test? — RogueAI

The current models already pass the turing test, but it doesn't pass the Chinese room analogy. The turing test is insufficient to evaluate strong AI.

This would require solving the Problem of Other Minds, which seems insolvable. — RogueAI

Yes, it is the problem with P-Zombies and the chinese room. But we do not know in what ways we are able to decode cognition and consciousness in the future. We might find a strategy and technology to determine the sum internal experience of a certain being or machine, and if so we will be able to solve it.

It might also even be far easier than that. It could be that the foundation for deciding it only becomes a certain bar of behavior at which we conclude the machine to have consciousness in the same way we do so towards each other and other animals. For instance, if we have a certain logic gate that produce certain outcomes we wouldn't call that conscious as we can trace the function back to an action we've taken for that function to happen.

But if behaviors emerge spontaneously out of a complex system, behaviors that demonstrate an ability to form broader complex reasoning or actions that does not follow simple paths of deterministic logics towards a certain end goal, but rather exploratory actions and decisions that show behaviors of curiosity for curiosity's sake and an emotional realm of action/reactions, then it may be enough to determine based on how we rationalize animals and other people around us to not be P-Zombies.

In essence, why are you not concluding other people to be P-Zombies? Why are you concluding a cat to have "inner life"? What point list of attributes are you applying to an animal or other human being in order to determine that they have subjectivity and inner life? Then use the same list onto a machine.

That's the practical philosophical approach that I think will be needed at some point if we do not develop technology that could determine qualia as an objective fact.

I am raising a philosophical point, though: what sort of creature or being or machine uses the first person singular? This is not merely a practical or marketing question.

Pragmatically speaking, I don't see why 'AI' can't find a vernacular-equivalent of Wikipedia, which doesn't use the first person. The interpolation of the first person is a deliberate strategy by AI-proponents, to advance the case for it that you among others make, in particular, to induce a kind of empathy. — mcdoodle

You don't have a conversation with Wikipedia though. To converse with "something" requires language to flow in order to function fluidly and not become an obstacle. Language has been naturally evolved to function between humans and maybe in the future we have other pronouns as language evolves over time, but at the moment the pronouns seems to be required for fluid communication.

On top of that, since language is used to train the models, they function better in common use of language. Calling it "you" function better for its analytical capabilities for the text you input, as there are more instances of "you" being used in language than language structured as talking to a "thing".

But we are still anthropomorphizing, even if we tune language away from common pronouns.

The proponents and producers of large language models do, however, encourage this anthropomorphic process. GPT-x or Google bard refer to themselves as 'I'. I've had conversations with the Bard machine about this issue but it fudged the answer as to how that can be justified. To my mind the use of the word 'I' implies a human agent, or a fiction by a human agent pretending insight into another animal's thoughts. I reject the I-ness of AI. — mcdoodle

But that's a problem with language itself. Not using such pronouns would lead to an extremely tedious interaction with it. Even if it was used as a marketing move from the tech companies in order to mystify these models more than they are, it's still problematic to interact with something that speaks like someone with psychological issues.

There is an aspect of anthropomorphism, where we have projected human qualities onto machines. The subject of the machine, could be nothing more than a convenient linguistic formation, with no real subjectivity behind it. It's the 'artificialness' of the AI that we have to bear in mind at every-step, noting iteratively as it increases in competence that it is not a real self in the human sense. This is what I think is happening right now as we encounter this new-fangled AI, we are proceeding with caution. — Nemo2124

But if we achieve and verify a future AI model to have qualia, and understand it to have subjectivity, what then? If we know that the machine we speak to has "inner life" in its subjective perspective, existence and experience. How would you relate your own existence and sense of ego to that mirror?
Screaming or in harmony?

Chat-GPT and other talking bots are not intelligent themselves, they simply follow a particular code and practice, and express information regarding it. They do not truly think or reason, it's a jest of some human's programming. — Barkon

We do not know where the path leads. The questions raised in here are rather in front of possible future models. There's still little explanations for the emergent properties of the models that exist. They don't simply "follow code", they follow weights and biases, but the formation of generative outputs can be highly unpredictable as to what emerges.

That they "don't think" doesn't really mean much when viewing both the system and our brains in a mechanical sense. "Thinking" may just be an emergent phenomena that starts to happen in a certain criticality of a complex system and such a thing could possibly occur in future models as complexity increases, especially in AGI systems.

To say that it's "just human programming" is not taking into account what machine learning and neural paths are about. "Growing" complexity isn't something programmed, it's just the initial conditions, very much like how our genetic code is our own initial conditions for "growing" our brain and capacity for consciousness.

To conclude something about the current models in an ongoing science that isn't fully understood isn't valid as a conclusion. They don't think as they are now, but we also don't know at what level of internal perspective they operate under. Just as we have the problem of P-Zombies in philosophy of the mind.

The fact is that it can analyze and reason about a topic and that's beyond merely regurgitate information. That's a synthesis and closer to human reasoning. But it's rudimentary at best in the current models.

The question is how do we relate to this emergent intelligence that gives the appearance of being a fully-formed subject or self? This self of the machine, this phenomenon of AI, has caused a shift because it has presented itself as an alternative self to that of the human. When we address the AI, we communicate with it as another self, but the problematic is how do we relate to it. In my opinion, the human self has been de-centred. We used to place our own subjective experiences at the centre of the world we inhabit, but the emergence of machine-subjectivity or this AI, has challenged that. In a sense, it has replaced us, caused this de-centring and given the appearance of thought. That's my understanding. — Nemo2124

Haven't we always done this? Like Copernicus placed our existence in our solar system outside the center, which made people feel less "special" and essentially de-centralized their experience of existence.

These types of progresses in our existential self-reflection throughout history have always challenged our sense of existence, constantly downplayed ourselves as being special in contrast to the universe.

None of this has ever "replaced us", but rather challenged our ego.

This collective ego death that comes as a result of this constantly evolving knowledge of our own insignificance in existence is something that I really think is a good thing. There's harmony in understanding that we aren't special, and that we rather are part of a grander natural holistic whole.

These reflections about AI has just gone mainstream at the moment, but been part of a lot of thinkers focusing on the philosophy of the mind. And we still live in a time when people generally view themselves as the center of the universe, especially in the political and ideological landscape of individualism that is the foundation of westernized civilisations today. The attention economy of our times have put people's ego back into believing themselves to be the main character of this story that is their life.

But the progress of AI is once again stripping away this sense of a central positioned ego through putting a spotlight on the simplicity of our human mind.

This progress underscores that the formation of our brilliant intelligent mind appears to be rather fundamentally simple and that the complexity is only due to evolutionary fine-tuning over billions of years. That basic functions operating over time ends up in higher complexity, but can be somewhat replicated through synthetic approaches and methods.

It would be the same if intelligent aliens landed on earth and we realize that our mind isn't special at all.

-----

Outside of that, what you're describing is simply anthropomorphism and we do it all the time. Combine that with the limitations in language to have conversations with a machine in which we use words that are neutral of identity. Our entire language is dependent on using pronouns and identity to navigate a topic, so it's hard not to anthropomorphize the AI since our language is constantly pushing us in that direction.

In the end, I think the identity crisis people sense when talking to an AI boils down to their religious beliefs or their sense of ego. Anyone who's already viewing themselves within the context of a holistic whole doesn't necessarily feel decentralized by the AI's existence.

Is AI a philosophical dead-end? The belief with AI is that somehow we can replicate or recreate human thought (and perhaps emotions one day) using machinery and electronics. This technological leap forward that has occurred in the past few years is heralded as progressive, but as the end-point in our development is it not thwarting creativity and vitally original human thought? On a positive note, perhaps AI is providing us with this existential challenge, so that we are forced even to develop new ideas in order to move forward. If so, it represents an evolutionary bottle-neck rather than a dead-end. — Nemo2124

I do not understand the conclusion that if we have an AI that could replicate human thought and neurological processes, it would replace us or anything we do with our brain.

How does the emergence of a self-aware intelligent system disable our subjectivity?

That idea would be like saying that because there's another person in front of me there's no point of doing anything creative, or think any original thoughts, because that other person is also a brain capable of the same, so what's the point?

It seems people forget that intelligences are subjective perspectives with their own experiences. A superintelligent self-aware AI will just be its own subjective perspective and while it could manifest billions of outputs in both images, video, sound or text, it would still only be driven by its singular subjective perspective.

I'll take the other side of that bet. I have 70 years of AI history and hype on my side. And neural nets are not the way. They only tell you what's happened, they can never tell you what's happening. You input training data and the network outputs a statistically likely response. Data mining on steroids. We need a new idea. And nobody knows what that would look like. — fishfry

That doesn't explain emergent phenomenas in simple machine learnt neural networks. We don't know what happens at certain points of complexities, we don't know what emerges since we can't trace back to any certain origins in the "black box".

While that doesn't mean any emergence of true AI, it still amounts to a behavior similar to ideas in neuroscience and emergence. How complex systems at certain criticalities emerge new behaviors.

And we don't yet know how AGI compositions of standard neural systems interact with each other. What would happen when there are pathways between different operating models interlinking as a higher level neural system. We know we can generate an AGI as a "mechanical" simulation of generalized behavior, but we still don't know what emergent behaviors that arise from such a composition.

I find it logically reasonable that since ultra-complex systems in nature, like our brains, developed through extreme amount of iterations over long periods of time and through evolutionary changes based on different circumstances, it "grew" into existence rather than got directly formed. Even if the current forms of machine learning systems are rudimentary, it may still be the case that machine learning and neural networking is the way forward, but that we need to fine tune how they're formed in ways mimicking more natural progression and growth of naturally occuring complexities.

That the problem isn't the technology or method itself, but rather the strategy of how to implement and use the technology for the end result to form in a similar high complexity but still aligned with what purpose we form it towards.

The problem is that most debates about AI online today just reference the past models and functions, but rarely look at the actual papers written out of the computer science that's going on. And with neuroscience beginning to see correlations between how these AI systems behave and our own neurological functions in our brains, there are similarities that we shouldn't just dismiss.

There are many examples in science in which a rudimentary and common methods or things, in another context, revolutionized technology and society. That machine learning systems might very well be the exact way we achieve true AI, but that we don't know truly how yet and we're basically fumbling in the dark, waiting for the time when we accidentally leave the petri dish open over night to grow mold.

While I don't believe in the simulation argument because there's no evidence for it, similar to any evidence for a God in theistic arguments, there are points to be made dealing with the concept, since I think the concept in itself usually attributes our own current existence to be of importance to the one's "simulating" us, when in fact we might be unimportant in our current state.

First, if the world is simulated, why don't its 'designers' simply 'pop out' at times and leave us with some trace of their existence? Guidance through such a virtual world might be helpful, and yet there is no trace of anyone 'programming' or 'guiding' us anywhere. — jasonm

Why would it be helpful? If you help a moth shed its cocoon you will doom it to weakness in nature and death. "Helping" us out may be contradictory to the purpose of the simulation.

On top of that, a simulation of this magnitude would more likely have an end goal, similar to the concept of emerging a god out of the determinism of this chaotic system. That "god" wasn't the start of everything, but instead being the goal; us, or a collective of intelligences throughout the universe merging together civilisations and technology into a final form so fundamental that it would be able to manifest reality on its own, i.e the equivalent of a god. That could be a purpose of a higher being simulating us.

Or, we're observed and there's no interest in helping us out because that's not the purpose of the simulation. It could be simulating for the argument of how to avoid a downfall of society, as a demonstration for people outside the simulation to understand the importance of a certain societal practice that avoids self-destruction and that our simulation is a case-point to show what happens without that societal practice in order to teach young and ignorant of the reasons why they implemented it in society.

The list goes on for the purposes of a simulation and very few would constitute a reason to interfere and "help" us.

Similarly, why don't we sometimes notice violations of the laws of physics? If it's just a simulation, does it matter if the laws of physics are perfectly consistent? This applies to any law of this simulated world, including propositional logic. Again, if you are there, leave us with some trace of your existence through 'miracles' and other types of anomalies that our world does not seem to have. And yet there seems to be no instances of this kind. — jasonm

Why must the miracles or attributes of such anomalies be understandable or within a human concept? Maybe black holes and quantum superpositions and virtual particles are just such anomalies. Or if the simulation is so fundamental that it basically simulates the most fundamental aspects of reality itself, we wouldn't be able to find anything odd as everything is consistent with the laws of physics.

But on top of that, there's a problem with the frame of reference. If all our science and all our knowledge about reality comes from the foundation of this simulation, then our frame of reference is the reality of the simulation itself. What are you supposed to compare it to? You don't have an original to compare the map against, to reference Baudrillard's ideas.

Third: what type of computing power would be required to 'house' this virtual universe? Are we talking about computers that are bigger than the universe itself? Is this possible even in principle? — jasonm

This is the problem with the simulation argument. It stems from a logical argument of probability about what we human's are likely to do, or what is likely to happen if technology evolves, but it ignores the physical nature of computational power. Yes, there might be computational power found in technology that we've yet to invent, but the calculation required for handling data down to the Planck scale at all positions of reality is so extreme it reaches either infinity or requires the same size as reality itself. Whatever it is, it would most likely have to be something beyond what is capable within this reality, something within some higher form of reality in which manifesting our reality isn't that big of a deal.

Then, we can also view it through the concept of The Matrix and Dark City. In which the system that handles the simulation simply guard us from ever knowing about it. Since the ones doing the simulation have absolute control, they can simply tune our knowledge away from us, leaving us able to see these breaks in the simulation, but we're simply "edited" to not spot them.

That's also similar to Westworld:

...it doesn't look like anything to me...

In that sense, I think the notion that the universe is 'simulated' is completely superfluous and can therefore be explained away as being 'highly improbable.' — jasonm

Yes, as said, the argument is merely a logical one about progression of technology, but ignores computational problems. It's also based on humans conducting the simulation and we wouldn't need to simulate at this magnitude for any purposes other than creation itself, and if so, it really doesn't matter if we're in a simulation as our reality is simply the only reality we know, similar to the holographic universe theory.

So AI becomes another tool, not a competing intellect. — frank

For anyone using ChatGPT for anything other than just playing around, it's clear that it's a tool that requires a bit of training to get something out of. I find it quite funny whenever I see journalists and anti-AI people just using it in the wrong way in order to underscore how bad it is or how stupid it is.

For instance, a lot of the demonstrations of plagiarism have been an elaborate line of attempts to push a system to break and in return plagiarize. It's good to do it in order to fine-tune the system to not accidentally end up in such a position, but to demonstrate plagiarism it's quite a dishonest action to do.

It would be like playing elaborate tricks with a commissioned painter, lying to them about the intent of the artwork being created, saying that it's just a copy of another painter's work for the sake of playing around, for private use etc. in order to trick the painter into plagiarism so that you can then blame the painter publicly for being a plagiarist.

My view is based on people seeing my work and reading complex messages into it. And this is painting, not ai art. I'm interested in their interpretations. My own intentions are fairly nebulous. Does that mean I'm not doing art? I guess that's possible. Or what if communications isn't really the point of art? What if it's about a certain kind of life? A work comes alive in the mind of the viewer. In a way, Hamlet is alive because you're alive and he's part of you. I'm saying what if the artist isn't creating an inanimate message, but rather a living being? — frank

The "communication" does not have to be known. It's more basic and fundamental than something like a "message". The "communication" and "intent" has more to do with your choices, and those "choices" during your creative work becomes the "intentions" and "communication" that will later be interpreted by the receiver and audience.

For instance, a painter who creates abstract art might not know at all why she makes something in a certain way, but the choices are made in letting that instinct go wild and letting the sum of her subjective identity as a human evolve through that work.

Similar to if someone has an outburst in an argument which forms from that person's subjective identity and experience, influencing the receiver in that argument to react or interpret. Art is a form of human communication that is beyond mere words or description; rather it is a form of transforming the interior of the subjective into observable and interpretable form for others.

Which is why a world without art leads to cold interactions, conflicts and war as in such a world there are no such levels of communication between subjective internal perspectives to form a collective conscious, and why dictators fear it so much.

I said I was withholding my judgement. I have never claimed that the case is definitively settled for the reasons I've mentioned before regarding the state of our knowledge about both neuro and computer science. You clearly seem to disagree but I suppose we can just agree to disagree on that. — Mr Bee

The problem is that it influence your conclusions overall. It becomes part of the premisses for that conclusion even though it should be excluded.

I have never said it was binary. I just said that whatever the difference is between human and current AI models it doesn't need to be something magical. — Mr Bee

There are more similarities than there are differences within the context of neural memory and pathway remembering and generation. Pointing out the differences are like excluding a white birch tree from the categories of trees because it was white and not brown like the others. Just because there are differences doesn't mean they're categorically different. Storage and distribution of copyrighted material rely heavily on the proof of storage of such files for the intention of spreading or functions that focus on spreading; neither which is going on within these models.

In the end, it doesn't even have to be that complex. Using copyrighted material in private, regardless if a company does it or a private person, is not breaking copyright. Ruling that it is would lead to absurd consequences.

In any case, you seem to agree that there is a difference between the two as well, well now the question is what that means with regards to it's "creativity" and whether the AI is "creative" like we are. Again I think this is a matter where we agree to disagree on. — Mr Bee

"Creative like we are" have two dimensions based on what totality of the process you speak of. "Creative like our brain's physical process" is what I'm talking about, not "creative as subjective entity with intent".

One may argue that for some work is what gives their life meaning, It's unhealthy working conditions that are the problem more so. — Mr Bee

Stress levels are at all time highs, the working conditions are not stretched from good to bad, it's from bad to worse. A society that only focus on finding meaningful jobs will have the foundation for them, right now, there's no such foundation. Instead, the foundation is free market capitalism which is an entity that grows into making everything as effective as possible and reducing costs as much as possible. It is impossible to build a long term sustainable level of non-stress environments within it.

It also removes the leverage that workers usually have over their employers. In a society that is already heavily biased towards the latter, what will that mean? That's a concern that I have had about automation, even before the advent of AI. It honestly feels like all the rich folk are gonna use automation to leave everyone else in the dust while they fly to Mars. — Mr Bee

As i said, wide automation breaks the Hegalian master/slave concept of capitalism.

The scenario you describe cannot happen as the distinction of "rich" only has meaning within the concept of a capitalist system. Meaning, someone needs to buy the products that make the rich, rich. They might accumulate wealth, they might even fly to Mars, but so what? You think the world stops spinning because of that? The engineers and workers still exist and can work on something else, new leaders and new ideologies emerge among the people that's left, new strategies and developments occur.

This is why I feel all debates about automation and the rich and similar topics are just shallow level. People shouting hashtags online and actually not digging deeper into proper research about the consequences of automation. It's mostly just "the rich will just do whatever they want and everyone else is fucked". If people decide they're just fucked and don't care anymore, then they're part of the problem they complain about. People can work together and do something instead of just hashtagging bullshit online.

History shows that that is rarely how things go. If that were the case then wealth inequality wouldn't have been so rampant and we would've solved world hunger and climate change by now. People are very bad at being proactive after all. It's likely any necessary changes that will need to happen will only happen once people reach a breaking point and start protesting. — Mr Bee

I'm talking about nations, not the world. A single nation that experience a collapse in the free market and usual workforce will have to change their society in order to make sure its citizens don't overthrow the government. The inability for nations to solve world problems has nothing to do with national pressures of their own society changing, such actions can happen over night and do so when society is under pressure or in collapse.

And the problems with world hunger and climate change mostly has to do with dictators and corrupt people at the top of the governments in those nations that are either struck by poverty or are the worst offenders of climate change.

We can also argue that automation creates a situation in which the means of production gets so cheap that expanding food production to poor nations isn't a loss for richer nations. Again, the consequence analysis of automation seem to stop at a shallow level.

The irony is that it seems like AI is going after the jobs that people found more meaningful, like creative and white collar jobs. It's the more monotonous blue collar jobs that are more secure for now, at least until we see more progress made in the realm of robotics. Once automation takes over both then I don't know where that will leave us. — Mr Bee

As I've said numerous times in this thread, creating art and being an artist won't go away because the meaning of creating art is not the same as creating content. Content creation is meaningless, it's the business of creating design for the purpose of profit. Automation of content creation won't render creation of art meaningless. And art and AI can be fused in terms of better tools for artists.

Full wide automation of most jobs in society leads to what I'm describing. A collapse of capitalism as we know it. And it's up to each nation to decide on how to deal with that.

Future meaningful jobs or rather tasks within a fully automated society are those that will focus on the value of individual thought and ideas for knowledge and art, as well as production that gains a value of meaning through being handmade.

It's just that people are so indoctrinated into the capitalist free market mindset that they mistake capitalist mechanics for being an integral part of human existence. It's not.

We'll see. Maybe I've just been a pessimist recently (nothing about what's currently going on in the world is giving me much to be hopeful about) but I can just as easily see how this can end up going in a dystopian fashion. Maybe it's because I've watched one too many sci-fi movies. Right now, assuming people get UBI, Wall-E seems to be on my mind currently. — Mr Bee

Wall-E is an apt dystopian vision of the future. I don't think any of this will lead to some post-apocalyptic reality or war torn destroyed world. We will more likely enter a bright future in which we are physically healthy in a clean environment that's ecologically sound. But instead so intellectually unstimulated that we're just mindlessly consuming endless trash content...

...but how is that any different from today? In which the majority just mindlessly consume trash, eat trash and do nothing of actual meaning, either for themselves or others. While some try to find meaning, try to focus on exploration of meaning in their lives through art, science and knowledge.

The only difference would be that such a future society would make the consumers fully focused on consumption and those interested in meaning, fully focused on meaning. Instead of everyone being part of the machine that creates all the trash.

Certainly alot of them don't value their workers on a personal level alot of the time but I'd distinguish that from abuse. Of course that isn't really the main concern here. — Mr Bee

I'm not talking about abuse, I'm talking about how a lack of interest in the art that's created leads to an experience among artists of making meaningless stuff. The same lack of interest in what they do that makes these companies turn to AI is what makes artists drained of a sense of meaning. So who cares if they replace their artists with AI, most of those artists may need that to rattle them out of such a destructive co-dependent relationship with their current job in order to get going and find meaning elsewhere, or join a company that values their input. And even if AI takes over entirely, you still need artists eyes, ears and minds to evaluate what's created and guide it... they will always have a job.

The same can't be said of white collar managers and soon also blue collar workers as the robots get better every day. But the situation is the same for them as well. A blue collar worker work themselves into medical costs that ruins them, for companies who build and makes stuff that won't ever credit the workers. Let them get to build something with their hands for companies who appreciate that level of meaning instead.

I mean if you want to just train a model and keep it in your room for the rest of it's life, then there's nothing wrong with that, but like I said that's not important. None of what you said seems to undermine the point you're responding to, unless I am misreading you here. — Mr Bee

You are still confusing the training process with the output. You can absolutely use a model officially, as long as it's aligned with our copyright laws. If a user of that model then misuse it, then that's not the model or the engineers fault.

All sorts of meaning could be projected onto it, but my intention probably wouldn't show up anywhere because of the way I made it. The words I entered had nothing to do with this content. It's a result of using one image as a template and putting obscure, meaningless phrases in as prompts. What you get is a never ending play on the colors and shapes in the template image, most of which surprise me. My only role is picking what gets saved and what doesn't. This is a technique I used with Photoshop, but the possibilities just explode with AI. And you can put the ai images into Photoshop and then back into ai. It goes on forever — frank

Intention is still just my technical term for you guiding the model. If it's left to generate without any input it will just randomize in meaningless ways. You could end up with something that you can project meaning onto, but that is not the same as meaning in creation.

Even random words in the prompt is still intention, your choice of words, your choice of only relying on intuition, it's still a guiding principle that the AI model can't decide on its own.

Such exploration through random choices is still guidance. And we've seen that in traditional art as well, especially abstract art.

I think the real reason art loses value with AI is the raw magnitude of output it's capable of. — frank

You can say the same about photography. Why is street photography considered art? It's an output that isn't able to be replicated; instant snapshots and thousands upon thousands of photos, choosing one.

Art is the interplay between the artist and the audience, the invisible communication through creation, about anything from abstract emotions to specific messages. The purpose of a created artwork is the narrative defining the value of it. If all you do is generating images through randomization, then what is the purpose you're trying to convey?

Aesthetic appreciation can be made with whatever you find beauty in, but that doesn't make it art. A spectacular tree in a spectacular place in spectacular light can make someone cry of wonder of it's beauty. But it isn't art. The "why" you do something is just as important with randomized processes as with intentional ones. Your choice of relying on intuition is part of the communicative narrative.

But if you don't have that and just generate quantity upon quantity of images until you find something that you like, then that's content production. You're not conveying anything, you're exploring a forrest in search of that beautiful tree in that spectacular location. Content that is beautiful, but not really art as the purpose of its creation isn't there.

You claim it's identical merely by appeal to a perceived similarity to private legal use. But being similar is neither sufficient nor necessary for anything to be legal. Murder in one jurisdiction is similar to legal euthanasia in another. That's no reason to legalize murder. — jkop

This is simply just a False Analogy fallacy you're making. An absurd comparison of two vastly different legal situations.

The similarity is simply within the private use. You can't argue against that my use of copyright material in private is just as valid as if a tech company works with copyright material in private. The only point at which you can call copyright laws into question is by examining the output, the production out of the work done in private.

If you say that the use of copyrighted material by these companies in their private workflow is illegal. Then why is it legal if I use copyrighted material in my private workflow? What is the difference here? That it's a tech company? If I have an art company and I use copyrighted material in my workflow but it doesn't show up in the creation I provide to clients, shouldn't that be considered illegal as well?

You're just saying there's a line, but without a clear definition of what or where that line is drawn. In order to rule something illegal in a legal matter, you absolutely have to be able to draw a line that is based on facts and cold hard truth to the extent it's possible. And if not possible, then rulings will be in favor of the accused as crime cannot be proven beyond doubt.

Corporate engineers training an Ai-system in order to increase its market value is obviously not identical to private fair use such as visiting a public library. — jkop

That's just a straw man misrepresentation of the argument. You're inventing a specific purpose (through your personal opinion of what they do) and then comparing it to something made within the context of an argument as analogy for the purpose of showing the similarities of the physical process in the brain and with the technology.

On top of that, it's a misrepresentation of why such data was used. It has nothing to do with increasing market value; it's rather a method developed over the years in machine learning sciences. Increasing the amount of data required using material that's copyrighted in order to these those magnitudes of quantities. This was made long before there was any notion of gold rush in this industry. And therefore you're still just making arguments on the preconceived idea and ideology that these companies are evil, not on any actual ground for conclusions within the context of legal matters.

The arguments you make here doesn't honestly engage with the discussion, you're simply ignoring the arguments that's been made or you don't care because you just fundamentally disagree. Neither which is valid to prove the opinion you have, and it ends up just being an emotional response, which isn't enough in matters of what is legal or not.

We pay taxes, authors or their publishers get paid by well established conventions and agreements. Laws help courts decide whether a controversial use is authorized, fair or illegal. That's not for the user to decide, nor for their corporate spin doctors. — jkop

What's your point? You still need to prove that the training process is illegal. Instead you're basically just saying "corporations BAD, we GOOD". Describing how laws and courts help decide something doesn't change anything about what I've been talking about. Quite the opposite, I've been saying over and over that proving "theft" in court is close to impossible in the context of training these models as the process is too similar to what artists are already doing in their workflow. And because of this, just saying that "courts will decide" is meaningless as a counter argument. Yes, their rulings will decide, but as I've shown examples of, there are court rulings that seemed like clear cases of infringement that ended up freeing the accused anyway. And those cases were made in which the decision of the accused was clearly established to use other's materials directly in the finished work. If any court anywhere is to prove "theft" in the process of AI training, then they have to prove that these models has the files they were trained on within them, which they don't. And if they decide that a neural memory is the same as storing files like normal on hard drives, then what does that mean for a person with photographic memory when our brain has a similar method of neural pathways for storage? The problems pile up with trying to prove "theft" to the point it would most likely not hold in court beyond doubt.

If you do not want the AI to know a particular information, then simply do not put that information onto the internet. — chiknsld

This is true even outside anything about AI. People seem to forget that websites that show something officially, outside of private conversations, like these posts and this thread, is public information. The act of writing here is me accepting that my text is part of the official reality that anyone can access, read or save. I still own copyright to my text without it needing any stamp or being registered as such, but if someone download this text to use while they write some essay on copyright law and AI, then I can't stop them. But if they cite me without citation, that is plagiarism.

That's why AI alignment in outputs needs to evolve in order to align with the same obligations humans exist under.

I'll give you an example: You are a scientist working on a groundbreaking theory that will win you the Nobel Prize (prestige) but the AI is now trained on that data and then helps another scientist who is competing with you from another country. This would be an absolutely horrible scenario, but is this the AI's fault, or is it the fault of the scientist who inputted valuable information?

In this scenario, both scientists are working with AI.

We all have a universal responsibility to create knowledge (some more than others) but you also do not want to be a fool and foil your own plans by giving away that knowledge too quickly. It's akin to the idea of "casting pearls" — chiknsld

If you use an AI in that manner you have accepted that the AI is using your information. There are AI models tuned to keep privacy of data, otherwise they wouldn't be able to be used in fields like science.

That's more of a question of being irresponsible to yourself.

In terms of science however, one area that's gotten a huge improvement with AI is versions of models trained on publications. The level of speed at which someone can do research on and getting good sources for citations has increased so much that it's already speeding up research in the world overall.

However, corporations do have a fiduciary requirement to generate profit for their shareholders. So, making money is the name of the game. The people who make up corporations, especially when engaged in new, cutting edge projects, clearly have lots of intellectual interests aside from the fiduciary requirement. I'm sure developing AI is an engrossing career for many people, requiring all the ingenuity and creativity they can muster. — BC

Actually, OpenAI was purely open source before they realized they needed investments for the amount of computing power needed to handle the training of their AI model. And the usage of copyrighted material wasn't decided based on making money but trying to solve and improve the AI models they attempted to make. There was no inflow of money in this until society realized what they could do and the potential for these models. So all the greed came after the first models were already trained, and so did all the criticism, basically inventing reasons to fight against the technology by flipping the narrative into "us the good guys workers" and "them the greedy soulless corporations". But I think everyone needs to chill and realize that reality isn't so binary and focus on criticism where it's valid and vital, not fundamentally emotional outbursts and herd mentality.

but the final uses to which this technology will be applied are not at all clear, and I don't trust corporations -- or their engineers -- to just do the right thing, — BC

Which is why we need regulations, laws and I'm all for demanding a global agency with veto control over every AI company in the world and who has full insight into what's going on behind closed doors. A kind of UN for AI development. Because AI also has enormous benefits for us. In medical science we're talking about a possible revolution.

This is why I'm opposed to the argument that AI training on copyrighted material is copyright infringement. Technically it's not, but also, it stops the development and progress of AI research and the tools we get from it. We need to keep developing these models, we just need better oversight on the other end, on the uses of them. And people need to understand the difference between what these two sides mean.

In the end, if artists could stop acting like radicalized luddites and be part of figuring out what the actual way forward is, we'll rather end up in alignment with how we're to use these models. They will become tools used by artists more than replacing them.

Instead of destroying the machine, figure out the path into the future, because people are more inclined to listen to all the doom and gloom, and be very bad at looking closer at the actual benefits this technology can produce.

Just an example. True enough, it's not quite the same as AI. But corporations regularly do things that turn out to be harmful--sometimes knowing damn well that it was harmful--and later try to avoid responsibility. — BC

Yes, and that's why I'm all for oversight and control of the "output" side of AI, to have societal regulations and demands on these companies so that the usage benefit people rather than harm them. The problem is that these companies get attacked at the wrong end, attacked at the point that could destroy the machines. Out of pure emotional fear, radicalized by social media hashtag conflicts spiraling out of control.

I was thinking of intention as in a desire to create something meaningful. An artist might not have any particular meaning in mind, or even if they do, it's somewhat irrelevant to the meaning the audience finds. So it's obvious that AI can kick ass creatively. In this case, all the meaning is produced by the audience, right? — frank

I'm using the term "intention" here as more of a technical distinction of agency in actions. Humans can decide something, based on meaning, based on needs and wants, which does not exist within the AI systems, such decisions has to be input in order to get an output. They will not produce anything on their own. Even if I just type "generate an image of a bridge" without any more details in descriptions, it will rather randomize any decisions of composition, lighting, color etc. but it doesn't do so based on wants, needs and emotions. The more I "input", the more of my subjective intention I bring into the system as guiding principles for its generation.

The creative process within these AI systems are rather more the technical and physical process being similar to the neurological processes in our brain when we "generate" an image (picture it in your mind) and my argument is based around how copyright cannot be applied to simulating that brain process as a neural network anymore than a camera replicating the act of seeing. A camera can be used to plagiarize, but blaming the camera manufacturer and R&D for some user's plagiarism using said camera is not right.

Yea, an AI artist could create a century's worth of art in one day. I don't really know what to make of that. — frank

Not really. A true artist takes time to evaluate and figure out the meaning of what they want to create and what they've created. Someone just asking an AI to produce large quantities of something just generates content.

Content and art aren't equal. One is purely made for profit and filler, the other a pursuit of meaning. You can't pursue meaning in anything by focusing on quantity. Some people might find meaning in some AI generated content, some people don't care about art enough to make a distinction. But what's the difference between that and the difference between a long running soap opera compared to 2001 a space odyssey? I for one, as an artist and thinker, don't care if trash content and quantity production in media gets replaced by AI. It'll give more time for us to focus on actually creating art rather than being forced to work with content as a factory.

I don't know enough about the processes in detail, but just a first glance impression gives off the feeling they're different. — Mr Bee

This here is the problem with the overall debate in the world. People replace insight and knowledge with "what they feel is the truth". A devastating practice in pursuit of truth and a common ground for all people to exist on. Producing "truths" based on what feels right is what leads to conflict and war.

Chat-GPT I don't think is as intelligent as a human is. It doesn't behave the way a human intelligence would. Can I explain what is the basis for that? No. Does that mean I think it's magic then? Not at all. — Mr Bee

No on is claiming that either. Why is this a binary perspective for you? Saying that ChatGPT simulates certain systems in the brain does not mean it is as intelligent as a human. But it's like it has to either be a dead cold machine or equal to human intelligence, there's no middle ground? ChatGPT is a middle ground; it mimics certain aspects of the human brain in terms of how ideas, thoughts and images are generated out of neural memory, but it does not reach the totality of what the brain does.

The things is that for alot of people generative AI seems like a solution looking for a problem. — Mr Bee

Maybe because they can't think past shallow internet conflicts on twitter and look deeper into this topic.

I think this video sums it up pretty nicely: — Mr Bee

It summarizes one thing only: the shallow and surface level media coverage of AI. Of course these tech companies hyperbole things when much of the investment money that gets poured into the industry comes from the stupid people who fall for these promises.

That doesn't mean, however, that there aren't tremendous potentials for AI technologies. We're already seeing this within medical sciences like AlphaFold 3.

The inability for people to see past tech company hyperboles and shallow media coverage of this technology is what drives people into this shallow hashtag Twitter-level of conflict over AI. All of this is radicalizing people into either camp, into either side of the conflict. It is utterly stupid and filled with bullshit that stands in the way of actual productive conversation about how to further develop and use this new computational tech into the future.

Such conversations exist, but they get drowned in all the bullshit online.

According to some reports, AI could replace hundreds of millions of jobs. If it doesn't replace it with anything else, then to brush off the economic disruption to people's lives without considering policies like UBI is the sort of thinking that sets off revolutions. — Mr Bee

Of course, no one truly into the real productive discourse about AI ignores this issue.

However, while people fear the economic disruption, the world is also worried about how work is stressing us to death, how people have lost a sense of meaning through meaningless jobs and how we're existentially draining ourselves into a soulless existence. So, why would such disruption be bad?

Because it would effectively drive society towards systems like UBI, and it would force society to question what a "good job" really is.

It would push us all into breaking an Hegelian situation of the master/slave concept (interpretably in this context), in which all the masters replace workers with robots and AI, effectively lowering production cost to extremely low numbers and increase their revenue, but who's gonna buy anything when no one has the effective income to buy their products?

It's ironic that people complain about these AI companies through the perspective of capitalist greed when the end result of massive societal disruption through AI would effectively be the end of capitalism as we know it, since it removes the master/slave dynamic.

Any nation who spots these disruptions will begin to incorporate societal changes to make sure living conditions continue to be good for the citizens. And instead of working ourselves to death with meaningless jobs, people may find time to actually figure out what is meaningful for them to do and focus on that.

Because people don't just want factory manufactured things. There are millions of companies in the world who don't expand into factory production and low-wage exploitation, both on moral grounds but also that their product is sold specifically as "handmade". It's like people in the AI discourse aren't actually thinking through the nuances of what a post-disruption society would look like. They just end their thinking at the disruption, they can only think through the perspective of free market capitalism and are unable to picture society past this system. Maybe because their lives are so ingrained into capitalism that they're unable to even think in other perspectives, but the truth is that we may very well see a totally new system of society that hasn't been realized yet, even theoretically, because it relies on a foundation of absolute automation of all sectors in society, a condition that hasn't been on the table before.

This is why most science fiction depictions of the future are rather simplistic when depicting the implication of disruptive technology. Ignoring the butterfly effects of new technologies emerging.

Just think about the industrial revolution, all of this with AI is repeating history. We're seeing a threat to workers of a previous type, but see an opening for new types of jobs. We also see an increase in living conditions through the industrial- and post-industrial revolution. And the discussion has ALWAYS been the same, with people believing that the "new technology" spells the end for humanity because they cannot fathom the actual consequences and rather always view things in the perspective of destruction and oblivion.

We already have a capitalist machinery that is destroying people both in low-wage nations and in more westernized societies. Disrupting this is not a bad thing. But we have to make sure to focus on aligning society towards better conditions for people. That's impossible if people just do shouting matches about who's worst and always complain about any new technology that gets invented.

I'm rather optimistic about a future that has, through automation, disrupted capitalism as we know it. I think people make shallow assumptions that the rich would just continue to accumulate wealth indefinitely, something that is technically impossible, especially in a world in which the gears of capitalism has essentially broken down. And I think people forget that the progress in the world so far has made people live in conditions that were only available to royalty as close as 100 years ago. What the tech gurus are hyperboling in media is totally irrelevant. They're speaking to the gullible masses and investors, not taking part in the real discussions about the future. A future that I think people attribute the same kind of doom and gloom towards that people in all time periods of innovation and progress has been doing.

I, however, see a technology that can revolutionize aspects of our lives in ways that will make our lives better, even if that means everyone's out of a job. Because then we can focus on living life together and not wasting our lives on being slaves for masters. Essentially, the question becomes, do you want to continue with a world as it is today? Or would the world be better off if soul crushing work gets demolished by automation, leaving everyone to mostly benefit from such an automated society.

When you're too cheap to hire someone to create something then you're probably also too lazy to fix the inevitable problems that comes with generated content. — Mr Bee

Still doesn't change the fact that these lazy CEOs and companies were treating artists badly before firing them due to AI. I don't think this is a loss for artists. Trash commercials isn't something I would value high and I actually think it's better for the soul of the artist to just not work at such places. I've seen many artists who just stop making art all together after a few years of such bullshit. That's killing artists more than any AI does.

I can imagine the top art companies, like say a Pixar or a Studio Ghibli, focusing solely on human art, in particular because they can afford it. I don't see them relying on AI. Like a high end restaurant that makes it's food from scratch without any manufactured food, they'll probably continue to exist.

There will also be companies that use AI to a certain extent as well, and then companies that rely on it too much to the point of being low-end. — Mr Bee

But AI will also lower the cost for those who focus on human created art. The reason why I think the official debate about AI is so misleading and bad is because people believe that AI tools are only generative in terms of images or video. But there are other aspects in AI that speed up the process of making art that is in pure control of an artist. Like rotoscoping and isolating elements in sound. Or like the fact that an artist working at a game company right now is required to not only create the design for some asset like a "building" on a game map, they have to create maybe 20 versions of the same design, something that could very well take upwards of a few months. But now there are technologies that enables them to focus on just one building, and really get into depth and detail with that design without stressing through it, and then let an AI iterate different versions of that design without losing their own control over it.

Such tools enhance artists control and gives them more time to really polish their creations. So even human created art will benefit. And we're not criticizing art created today for being "cheated" with current tools of the trade. No one is shedding tears because rotoscoping has started to become trivial, it's a time consuming and soul-crushing process that waste artists time and the investors money. And in animation work like for Pixar, they're working with a lot of AI assisted tools for animation that makes animations be more fluid and physically accurate because such parts of the process have always been a chore.

But many artists seem to not understand this and believe that it's all about generating images and video. Those aspects, in their simplest form, are just consumer grade toys, or content creation similar to Shutterstock. The true meaning of those tools are in tandem with other tools enhancing the work for actual artists rather than replacing them.

None of this really addresses their concern about financial stability. I fear that this new technology just gives more leverage over a group of people who have been historically underpaid. I hope it ends up well, but I'm not gonna brush off these concerns as luddite behavior. — Mr Bee

But what you describe is exactly what the luddite situation was during the industrial revolution. And their lives became better. Why are we criticizing this disruption by defending an industry that was underpaying them and using them to the brink of them giving up art all-together?

It's oddly ironic that people argue against such disruption through wanting to maintain previously bad conditions. Effectively criticizing the greed of these capitalists, while framing the criticism within the context of making money, even if the conditions are horrible.

Would you argue against automation in low-wage sweatshops that uses kids as their workforce? People's arguments resemble saying that we shouldn't improve the conditions there with automation because that would mean that they would get no pay at all and it's better that they get some pay and work themselves to death than no pay at all. Really?

That's an awful defense of keeping the status quo. Bad working conditions disappearing due to automation is a good thing.

Not at all. They're just not allowed to use their non-transformative output based on those references and expect to get paid for it. Like I said before, if you want to look at a bunch of copyrighted material and download it on your computer, that's fine since all you're doing is consuming. — Mr Bee

Yes, consuming like the training process does with these models. It's a training process, like training your brain on references and inspirations, filling your brain with memories of "data" that will be used within your brain to transform into a new ideas, images or music. This is what I'm saying over and over. Don't confuse the output of these AI models with the training process. Don't confuse the intention of the user with the training process. Because you seem to be able to make that distinction for a human, but not for the AI models. You seem to forget that "user" component of the generative AI and the "user decision" of how to use the generated image. Neither having to do with the training process.

Noone is allowed to do whatever they want. Is private use suddenly immune to the law? I don't think so.

Whether a particular use violates the law is obviously not for the user to decide. It's a legal matter. — jkop

If the private use is within law and identical to what these companies do, then it is allowed, and that also means that the companies do not break copyright law with their training process. If you confuse the output and use of the output, with the private workflow of the artist or training process of an AI, then you are applying copyright laws wrong and effectively apply copyright infringement onto the workflow and not the result.

I don't understand why this is so confusing for you? You just adhere to it being a "legal matter", but legal matters operate on established consensus of were specific laws apply. Claiming something illegal that technically doesn't fall under being illegal, does not make it illegal, regardless of people's feelings about it or their personal want that it should. That's not how laws work.

Because a mere intention to want to create a painting of a park doesn't get to the interesting parts about how our brains generate that image in our heads from what we know. Of course I don't know much about creativity, neuroscience, or AI like I said before, so I'm gonna avoid deeper conversations and skip over the following paragraphs you've written for the sake of time. — Mr Bee

Intention is more than just will, intention drives creation in a fluid constant manner, not just a will to paint a park, but every detail of that park and the interpretation of it into reworks and changes.

But it's important to know the depths of all of this, because that's what's part of defining the foundation for laws and regulations.

They certainly deal with alot of criticism themselves if you're implying they don't. Tracing isn't exactly a widely accepted practice. — Mr Bee

From ever encounter with other artists I've had, almost all plays very loose with the concept of copyright during their process. It's very undefined were the line is drawn and most often than not it's people who aren't artists themselves who moralize the most about where lines are drawn. Tracing and photobashing are just obvious extreme examples of it, but there are lots of double standards behind closed doors during the workflow and process of creating works of art.

Among artists there's a lot of moralizing towards others while not a lot of introspection into their own workflows.

I'm willing to reject dualism as well, though I'm not sure why you're attributing this and indeterminism to people who just believe that human creativity and whatever is going on in diffusion models aren't equivalent. — Mr Bee

Because it's a question of having a foundation for laws and regulations. To defend human creativity with that it's magic isn't enough. Anything closer to facts is required and the closest to facts we have is what we've found in neuroscience and how these processes are similar between neural networks/machine learning and the human brain. What people like to believe in their own private spiritual way is no foundation for societal law and regulations.

I'm not saying that the human brain isn't a machine, I'm just saying that there are differences between the architecture of human brains and AI diffusion models something that may reveal itself with a further understanding of neuroscience and AI. — Mr Bee

The architecture in the neural network is mimicked while the totality of the brain is not. What's "same" is the behavior of memory formation and path formation. But the question is that if the process is similar, then the argument can be made that a person with photographic memory who reads a book and then writes something inspired by it is utilizing the same kind of process as the AI model that's trained on the same book writing out something based on it.

If the trained AI is considered a "normal computer", that would mean that a human had a specific part in the brain that stored a direct copy of a file of that book, not how we actually remember what we've read and how we remember it within the context of other texts. The AI model does the same, it doesn't have a file of the book, it "remembers" the book in relation to other texts.

If we are to create laws and regulations for that, then it's not as simple as saying that the engineers "programmed in this book into the AI", because that's like saying that someone took a book and forced it into my skull as a file into my brain rather than gave it to me to memorize in my head. The difference between a normal computer and a trained AI is that there's no copy of the original file, there's nothing of the original file just like there's no original copy of the book in my brain. And most of copyright laws are based on physical or digital files being spread around.

Given how disruptive AI can be to all walks of society then I think that is a reason for pause unless we end up creating a very large society backlash. — Mr Bee

Would you want to go back to before the industrial revolution because society supposedly paused it? With all the improvements in society that eventually came because of it?

I find it a bit ironic that people don't want massive change while at the same time complain that nothing is done about the problems that actually exist in society. These AI models aren't just pumping out images, video and texts, they are used in other applications. Just the other day, a paper was released on protein folding that uses the new AlphaFold 3 and within it, it uses a diffusion model as part of the system.

If I have to be blunt, the benefits of these AI systems are potentially so massive that I couldn't care less about a minority of bitter artist who lost a job at a corporation that didn't even appreciate these artists contribution enough to value them staying. These different AI models are working together and help each other with tasks that reach beyond mere generative images or text, and the development of such beneficial processes will be delayed if they're forced to retrain on less data due to some court ruling.

Destroying the model's capabilities by restricting the training is not the solution, the solution is to restrict the use and put guardrails on the outputs. But society and artists are frankly so uneducated about all this that they don't understand the consequences of what they're screaming for. They just hate AI because they're afraid and become luddites who smash machines that could benefit society in ways they can't even fathom.

I despise such stupidity. Imagine a cancer drug that gets delayed because artists got a court to rule a model restricted and taken down when in the middle of being a key component in a larger structure of AI systems in analysis and protein folding. People don't know what they're talking about, people don't seem to have a clue about anything related to AI models beyond the click bait journalism and twitter brawls. Yet, at the same time, they want new cancer treatments and improvements to society in which, right now, AI is making massive improvements using the same models that rely on the same training data that they want to restrict and remove from these companies.

The equation in all of this is so skewed and misrepresented.

Those were more new mediums, new ways of making art and music then something that could completely replace artists can do. I'd look more at the invention of the camera and it's relation to portrait artists as a better example. — Mr Bee

AI can't replace artists. As I've mentioned, an artist is skilled in having the eye, ear and mind to evaluate what is being created. An AI can't do this. You need an artist to use AI effectively, you can't have some hack generate stuff if the output is going to be used professionally.

And those new mediums weren't new ways for those who were skilled in older methods of concept art. People who spent decades painting with real pencils and paint. They viewed the change just as artists today do with AI because they didn't know how to retrain themselves, so they became obsolete. Yet, people treat this transition as "whatever". Just as we treat all previous transitions in society and cherish how good life is with all our modern standards of living and working. Why would today be any different?

But sure, the invention of the camera and painting portraits might be more similar. But that also invented the job of the portrait photographer. Just like a concept artist today will be able to utilize their skill of knowledge in composition and design and use an AI model to speed up the process towards a specific goal. Why wouldn't they?

I view the hacks who think they're artists because they went from no artistic knowledge to writing prompts and getting outputs, as the same as people who bought a DSLR with video capabilities in 2008 thinking they will be the next Oscar nominated cinematographer just because the DSLR had a 35mm sensor and produced a photographic look almost exactly how cinema cameras produced images on real film productions... only to end up making ugly low budget shit that sure had an optically and technically similar look, but nothing of everything else in terms of composition and filmmaking language. Because they weren't actual cinematographers who could evaluate what they were making. They couldn't see their mistakes and they didn't know why something should look in a certain way.

AI will not replace artists. It's a misunderstanding of what an artist is. AI generation will replace the low-paid jobs at companies who didn't care for the artists to begin with and who never really had the money or care neither.

Companies who actually care about art but use AI will still need artists, they need their eyes to handle AI generative outputs and change according to plan and vision.

Honestly we should all be concerned on that because if they're fine with it then artists are out of a job and we as consumers will have to deal with more sloppy art. Already I see advertisements where people have 6 fingers on a hand. — Mr Bee

Is that a bad thing? Does anyone actually care about ads in terms of aesthetic appreciation? Or is everyone trying their best to get their adblockers to work better and remove them all together? The working conditions for artists were already awful for these kinds of companies, maybe it's better that this part of the industry collapses and gets replaced by outputs of the same quality as the no-caring CEOs of these agencies. Why are we defending shit jobs like these? It's them which will be replaced first.

What it will do is probably focus the consumers attention towards real artists work more. The difference will feel clearer. Just like how audiences have gotten fed up with the Marvel Cinematic Universe repeating itself over and over and over again and instead started to embrace original blockbusters once more. People don't actually want the repetitive factory outputs, they want artistic perspectives and this might rip the band aid off the industry instead of making everything into a low-wage factory.

As said, artists won't disappear, because they will be the ones working on stuff that matters. Yes, some might not return to working in the field, because they were never able to get to higher positions above these low-paid shitty jobs for these uncaring CEOs in the first place. So maybe that's not a bad thing? Just like the luddites who smashed the sewing machines got better health after those slave-like conditions ended and sewing machines were the condition to work under instead.

Because they're the ones giving most artists a job at this point and they need those jobs. Unfortunately that's the society we live in. — Mr Bee

Then start learning AI and be the artist who can give that expertise showing an edge against the non-artists that are put to work with these AIs and who don't know what the word "composition" even means. It's an easier working condition, it's less stressful and it's similarly "just a job". Why is anyone even crying over these kinds of jobs getting replaced by an easier form? It makes no sense really. Why work as a slave because a CEO demanded 5 new concept art pieces over the weekend not caring how much work that this would demand of a concept artist?

A company hiring a non-artist to work with AI won't work and they will soon realize this. You need the eyes, you need the ears and the poetic mind to evaluate and form what the AI is generating, that's the skill the artist is bringing.

They're both related. If the output process is not considered transformative enough then if the input contains copyright material then it's illegal. — Mr Bee

No, if the output isn't transformative enough, that's not a problem of the training data, that's a problem with alignment in order to mitigate accidental plagiarism. What you're saying is like saying that if an artist makes something that's not transformative enough, we should rule that artist to never be able to look in magazines or photographs again for inspiration and references. They will never be able to make anything again because they went to an arts museum and saw other paintings and because they accidentally plagiarized. It would mean their workflow is infringing on copyright, not the output, which makes no sense in comparison to common artistic practices and workflows.

The training process and the output are not the same thing in terms of copyright and a user producing plagiarism with an AI model does not mean the training process is infringing on copyright.

It's this misunderstanding of how the technology works that makes anti-AI arguments illogical and problematic.

I don't think intention is a requirement of artistic output. An artist may not have anything to say about what a particular work means. It just flows out the same way dreams do. Art comes alive in the viewer. The viewer provides meaning by the way they're uniquely touched. — frank

Intention here is not really meant as "knowing" or the "truth" of expression, it's merely the driving force or guiding principle from which creation is directed. In essence, it means that there's an intention of choice to draw a bridge against a sunset, an intention that does not appear for an AI on its own because it does not have an emotional component to experience and subjectivity. The identity of a person, their subjective sense of reality forms an intention to create something. In ourselves it forms as an interplay between our physical creative process in our brain (the one similar to these systems) and our emotional life informing and guiding us towards an intended path for what that process creates.

And this is also why I say that artists won't disappear. Because even an AI that is a superintelligence and has the capacity to create art on its own because they're essentially sentient, would still just constitute a single subjective perspective. Becoming a single "artist" among others. Maybe more able to produce art quicker and int more quantities, but still, people might like its art, but will want to see other perspectives from other artists and that requires a quantity of individual artists, AIs included.

The painting of Mona Lisa is a swarm of atoms. Also a forgery of the paining is a swarm of atoms. But interpreting the nature of these different swarms of atoms is neither sufficient nor necessary for interpreting them as paintings, or for knowing that the other is a forgery. — jkop

Neither is an argument that compares laws based on actions that aren't within the actions being targeted by existing laws. The training of these models is similar to any artist who works behind closed doors with their own "stolen" copyrighted material. It's still the output that's the main focus of determining plagiarism and what actions are taken to mitigate that. An artist who accidentally plagiarize does not get barred from ever making art again. A system that didn't handle accidental plagiarism in earlier versions before, but is then optimized to mitigate it, should that be banned?

You still seem to be unable to separate the formation of these neural models with the actions in generating outputs. The training process is not breaking copyright because the output and use of the system did so. That's purely a problem with alignment.

So this argument about Mona Lisa makes no sense in this context.

Whether something qualifies for copyright or theft is a legal matter. Therefore, we must consider the legal criteria, and, for example, analyse the output, the work process that led to it, the time, people involved, context, the threshold of originality set by the local jurisdiction and so on. You can't pre-define whether it is a forgery in any jurisdiction before the relevant components exist and from which the fact could emerge. This process is not only about information, nor swarms of atoms, but practical matters for courts to decide with the help of experts on the history of the work in question. — jkop

Training an AI model on copyright data is still not infringement anymore than an artist who use copyrighted material in their work. The output is all there is and if accidental plagiarism is happening all the time, courts can demand that these companies do what it takes to mitigate that from happening, which they are already doing... the rest is up to the intent of the user and should be the responsibility of the user. If the user is forcing a system to plagiarize, that's not the tech company's fault anymore than Adobe being responsible for if someone is using someone else's photo to enhance their own by manually changing it in Photoshop.

Blaming the training process for copyright infringement would fall into an arbitrary definition about how we can handle copyright data in our own private sphere. It would mean that I cannot take a favorite book and in my private home take a pencil and write down segments from that book onto a piece of paper, that would constitute copyright infringement, even if I don't spread that paper around officially.

How the tech works is out in the open, but people make emotionally loaded and wrong interpretations of it based on their own lack of understanding both about the technology.

Like, if I ask: where's the copyrighted data if I download an AI model? Point to where that data is please. It's not encrypted, that's not why you can't point to it. It's in there in the model, so if you are to claim copyright infringement, you have to point at the copied material inside the AI model. Otherwise how do you define that the companies "spread copyrighted material"? This is the foundation of any claim of theft, because what they did in the lab is behind closed doors, just as with an artist taking copyrighted material into their workflow and process.

Regarding the training of Ai-systems by allowing them to scan and analyse existing works, then I think we must also look at the legal criteria for authorized or unauthorized use. — jkop

I can take a photo of a page in a book and have it for myself. That's not illegal. I can scan and analyze I can do whatever I want as long as I'm not spreading those photos and scans around.

If you claim that training an AI model is unauthorized, then that would mean it is unauthorized for you to take screenshots, take photos of anything in your home (there are copyrighted material everywhere from books to posters and paintings to design of furniture etc.) because that is what the consequence for such definitions will be.

Then you can say, ok we only make it unauthorized to train AI models with such analysis. That would mean that all algorithms in the world that works based on analysing data would be considered unauthorized, fundamentally breaking internet as we know it. Ok, so you say we only do it for generative AI, then why? On what grounds do you separate that from any other scenario? If the defense say that such ruling is arbitrarily in favor of artists based on very unspecified reasons other than that they are humans, and question why engineers aren't allowed to utilize similar processes as artists, then what's morally correct here?

It all starts to boil down to how to define why artists have more rights than these engineers and why the machine isn't allowed while artists utilize even worse handling of copyrighted material in their private workflows.

It you actually start to break all of this down it's not as clear cut as you seem to believe.

Doesn't matter whether we deconstruct the meanings of 'scan', 'copy', 'memorize' etc. or learn more about the mechanics of these systems. They use the works, and what matters is whether their use is authorized or not. — jkop

Of course it matters. Artists scan, copy and memorize lots of copyrighted material in their workflows. Why are they allowed and not the engineers training these models? Why are artists allowed to do whatever they want in their private workflows, but not these companies? Because that's what you are targeting here. What's the difference? I mean, what's the actual difference that produce such a legal difference between the two that you can conclude one illegal over the other?

Just a random question. Had someone sold the database of all posts of a forum (not this one, in my mind), would that be considered theft or public information? — Shawn

If the forum rules constitutes that they in some way "own" the posts, then all people who write on the forum can't do anything about it. However, I don't think forum owners own the posts written so they can't really sell the posts. However, there's nothing illegal with scraping all posts from a forum if they're available as public information. Google's spider is already doing this for search results and as I've pointed out in this thread, training an AI model on those forum posts shouldn't be considered illegal as they're not copying anything more than I'm reading other's posts and can draw upon them when I write something myself.

It all, always, at every point, boils down to what the output of an AI system is. Did the user ask for a plagiarized post from one of the posters of a forum? Then the user is breaking copyright. If the system accidentally plagiarize, then the tech company must be forced to implement mitigation systems to prevent that from happening.

But information, works of art and everything that is available in some form officially, can't be protected from being viewed, analyzed and decoded. That's not what copyright is for, it's for protecting unlawful spreading, reselling or plagiarism of other's work. With enough original transform, an output or spread of such output isn't anymore illegal than if I get inspired by Giorgio de Chirico and create a cover for a game.

#1. Make money. — BC

There are better ways to make money. It's easy to fall into the debate trap of always summerizing anything against companies as having pure capitalist interests, but trying to solve AI tools is kinda the worst attempt if all intentions are just profit. And the competition in this new field as an industrial component of society demands making sure it is the best product without risking courts taking them down and ruining your entire business.

I do not know what percent of the vast bulk of material sucked up for AI training is copyrighted, but thousands of individual and corporate entities own the rights to a lot of the AI training material. I don't know whether the most valuable part was copyrighted currently, or had been copyrighted in the past, nor how much was just indifferent printed matter. Given the bulk of material required, it seems likely that no distinction was made. — BC

Since the amount of data is key for making the systems accurate and better, it needs to be as much as possible. And since text and images are in larger quantities today than from people who died 70 years ago, it is required to use copyrighted material.

But since it is training data, why does it matter? People seem confused as to what "theft" really means when talking about training data. Memory is formed through "pattern networks" similar to the human brain, nothing is copied into the system. Weights and biases are programmed in to guide the learning and it learns how to recognize pattern structures on all the data. Since it's learning this, it's learning the commonalities in images, text or whatever data in order to form understanding on how to predict next steps in the generation. When it accidentally plagiarize something, it's similar to how we picture a memory in our head as clear as we can. I can remember a Van Gogh painting with high clarity, but is still not identical to the original. I can remember text I've read, but I often misremember the exact lines. This is because my mind fills in the gaps through predictive methods based on other memory and other information I've learned.

As I've mentioned numerous times in this thread, it's important to distinguish between training processes and generated outputs. The alignment problem is about getting the system to function in a way not destructive to society, in this case destructive to artists copyright. But the data it was trained on is part of information available in the world and since it's used behind closed doors in their labs, it's no different from how artists use copyrighted images, music or text in their workflow while creating something. A painter who cut out images from magazines and use it as inspirational references while painting, copying compositions, objects, colors and similar from those images are basically the same as an AI model trained on those images, maybe even less direct in copying when compared to some artists.

Have you ever scrolled through royalty free library music? Their process is basically taking what's popular in commercial music or movie soundtracks, replicating the sound of all instruments, take enough notes but changing one or two so as to not copy some track directly. How is this different from anything that Suno or Udio is doing?

And with scale, with millions of images, text, music etc. it means that the risk of accidental plagiarism is very low compared to an artist using just a few sources.

In the end it's still the responsibility of the one using the system to generate something who need to make sure they're not plagiarizing anything. It's their choice of how to use the image.

The output and the training process is not one and the same thing, but people use the nature of outputs and accidental plagiarism in outputs in relation to the training process and training data as proof for theft when it's not actually in support of such a conclusion. There's no database of copyrighted material on some cloud server somewhere in which these systems "get the originals". They don't store any copyrighted material anywhere but in their own lab. So how does that differ from an artist who's been scraping the web for references in their work storing it on their own hard drives?

The many people who produce copyrighted material haven't volunteered to give up their ideas. — BC

In what way did they "give up their ideas"? If I create an image, upload it to something like Pinterest and someone else downloads that image to use as a reference in their own artistic work, then they didn't commit theft. Why is it theft if a company uses it for training data of an AI model? As long as the output and generations are aligned not to fall into plagiarism, why does that matter anymore than if another artist used my images in their own workflow? Because the companies are part of a larger capitalist structure? That's not a foundation for defining "theft".

Here's an example of artwork that is "inspired" by the artist Giorgio de Chirico for the game cover of "ICO".





No one cares about that, no one screams "theft", in general they loved how the artist for the cover got "inspired" by Giorgio de Chirico.

But if I were to make an image with an AI diffusion model doing exactly the same, meaning, some elements and general composition is unique, but the style, colors and specific details were similar but not copied, and then use it commercially, then everyone would want to crucify me for theft.

If it was even possible, because if I ask DALL-E for it, it simply replies:

I was unable to generate the image due to content policy restrictions related to the specific artistic style you mentioned. If you'd like, I can create an image inspired by a surreal landscape featuring a windmill and stone structures at sunset, using a more general artistic approach. Let me know how you'd like to proceed!

And if I let it, this pops out:



It's vaguely resembling some aspects of Giorgio de Chirico's art style, but compared to the ICO game cover, it's nowhere near it.

This is an example of alignment for the usage of these systems, in which the system tries to recognize attempts to plagiarize. And this process is improving all the time. But people still use old examples of outdated models to "prove" what these systems are doing at the moment. Or they use the examples of companies or people who blatantly doesn't care about alignment to prove that a totally other company also does it because... "AI is evil" which is just the length of their entire argument.

And with court rulings from the past ruling in favor of the accused like in Mannion v. Coors Brewing Co., then artists seem to be protected far more for blatant rip-offs than an AI diffusion model producing something far less of a direct copy.

So your claim is that adding intentionality to current diffusion models is enough to bridge the gap between human and machine creativity? Like I said before I don't have the ability to evaluate these claims with the proper technical knowledge but that sounds difficult to believe. — Mr Bee

Why is it difficult to believe? It's far more rooted in current understandings in neuroscience than any spiritual or mystifying narrative of the uniqueness of the "human soul" or whatever nonsense people attribute human creativity to stem from. Yes, I'm simplifying it somewhat for the sake of the argument; the intention and predictive/pattern recognition system within us are rather constantly working as a loop influencing each other and constantly generating a large portion of how our consciousness operates. Other parts of our consciousness functions the same; like how our visual cortex isn't getting fed by some 200 fps camera that is our eyes, but rather that our eyes register photons that our visual cortex interprets by generating predictions in-between the raw visual data we feed through our eyes. It's the reason why we have optical illusions and if we stare at some object in high contrast for a long period of time and then look at a white canvas we see an inverted image as our brain try to over-compensate by generating a flow of data to fill in gaps that aren't seen anymore in raw data.

At its core the actual structure of a neural engine or machine learning is mimicking the exact nature of how our brain operates with pathways. We don't have a raw data copy of what we see or hear, we have paths that forms in relation to other memory paths and the relations between them forms the memories that we have. It's why we can store such vast amounts of information in our heads because it's not bound to physical "bits", but connections which become exponentially complex the more you have.

Inspired by these findings in neuroscience, machine learning using neural maps started to show remarkable increases of computing capabilities far beyond normal computers, but what they gained in compute power, they lost in accuracy. Which is key to understanding all of this.

They don't copy anything because that would mean an AI model would be absolutely huge in size. The reason I can download an AI model that is rather trivial in size is because it's just a neural map, there's no training data within them. It's just a neural structure "memory", similar to the neural maps in our own brains.

And they're using the same "diffusion model" operations that tries to mimic how we "remember" from this neural map by analyzing the input (intention) and find pathway memories that links to the meaning of the input and interpret it into predictions that generating something new.

Recent science (that I've linked in above posts) have started to find remarkable similarities between our brain and these systems. And that's because they didn't make these AI models based on some final conclusions about our brain, they were instead inspired by what was found in neural science and just tried methods to mimic our brain, without knowing if it would work or what would happen.

This is the reason why no one still knows how an LLM could generate fluid text in other languages without direct programming of such functions and why many of these other functions just emerged from these large quantities of text data forming these neural maps.

It's rather that because these companies did all of this, neuroscientists are starting to use their research papers back into their own field as it shows hints at how functions in our brain emerge abilities just by how prediction occurs within these neural pathways. It's basically someone trying something before people know exactly how something works and discovering actual results.

The point being, it mimics what we know about how our brain generate something like an image or text and thus, what's missing is everything that constitutes an "intention" in this process. "Intention" isn't just a computational issue, but something that reflects the totality of our mind, with emotions, behaviors and what might constitute everything about they physical of being a human. Human "intention" might therefore not be able to be copied without requiring everything that constitutes being a "human".

A good example of another technology that mimics a human function is the camera, or the recorder and speakers. These are more simplistic in comparison, but we've replicated the way our eyes register photons, especially in digital cameras, with lenses, rods and cones. And we've replicated how we record sounds using membranes and how our vocal cords produce sounds like membranes in a speaker and its hollow structure which forms sounds like our throat.

But when we mimic brain structures and we witness how they form behaviors similar to how our brain functions during creativity, we are all of a sudden thrown into moral questions about copyright in which people who don't understand the tech generally argues like those sitting in the audience at the first film projection, believing the train actually is about to hit them, or how record players and cameras took the souls of people when they got recording in those mediums.

As far as I see this, it's a religious and spiritual realm that makes people fear these AI models core functions, not scientific conclusions. It's about people breaking cameras because they think they will capture their souls.

Okay, but in most instances artists don't trace. — Mr Bee

Neither do diffusion models, ever. But artists who trace will still come out unscathed compared to how people react to AI generated images. Where is the line drawn? What's the foundation on which definitions of such differences are made?

I don't see how originality is undermined by determinism. I'm perfectly happy to believe in determinism, but I also believe in creativity all the same. The deterministic process that occurs in a human brain to create a work of art is what we call "creativity". Whether we should apply the same to the process in a machine is another issue. — Mr Bee

That's not enough of a foundation to conclude that machines do not replicate the physical process that goes on in our brain. You're just attributing some kind of "spiritual creative soul" to the mind, that it's just this "mysterious thing within us" and therefore can't be replicated.

Attributing some uniqueness to ourselves only because we have problems comprehending how this thing within us works or function isn't enough when we're trying to define actual laws and regulations around a system. What is actually known about our brain through neuroscience is the closest thing we have to an answer, and that should be the foundations for laws and regulations, not spiritual and emotional inventions. The fact is that human actions are always traceable to previous causes, to previous states, and a creative choice is no different from another type of choice.

The only reason why people attribute some uniqueness to our internal processing in creativity is because people can't separate their emotional attachment to the idea of divine creativity; It's basically just an existential question that when we break down the physical processes of the brain and find the deterministic behaviors and demystify creativity, people feel like their worldview and sense of self gets demolished. And the emotional reactions from that are no grounds for actual conclusions about how we function and what can be replicated in a machine.

Indeed the definitions are very arbitrary and unclear. That was my point. It was fine in the past since we all agree that most art created by humans is a creative exercise but in the case of AI it gets more complicated since now we have to be more clear about what it is and if AI generated art meets the standard to be called "creative". — Mr Bee

And when we dig into it, we see how hard it is to distinguish what actually constitutes human creativity form machine creativity.

However, I don't think this is a problem due to the problem of "intention". These AI models aren't really creative in exactly the way we are. They mimic the physical processes of our creativity, which isn't the same as the totality of what constitutes being creative. We might be able to replicate this in the future, but for now, the intention is what drives the creativity, we are still asking the AI to make something, we are still guiding it. It cannot do it on its own, even though it has the physical neural pathway processing replicated. Even if we just hit a button for it to randomly create something, it then gets guided by the fundamental weights and biases that were there to inform it's fundamental basic handling of the neural map.

To generate we must combine intention with the process and therefor before we can judge copyright infringement, those to must have produced something. I.e the output. And so, the argument I've been making in here is that any attempt to blame the training process due to using copyrighted data in the training data is futile as nothing have been created until after intention and process generates an output.

Only then can plagiarism and other copyright problem be called into question.

However the problem is that in today's art industry, we don't just have artists and consumers but middle men publishers who hire the former to create products for the latter. The fact is alot of artists depend on these middle men for their livelihoods and unfortunately these people 1) Don't care about the quality of the artists they hire and 2) Prioritize making money above all else. For corporations artists merely create products for them to sell and nothing more so when a technology like AI comes up which produces products for them for a fraction of the cost in a fraction of the time, then they will more than happily lay off their human artists for what they consider to be "good enough" replacements even if the consumers they sell these products to will ultimately consider them inferior.

There are people who take personal commissions but there are also those that do commissions for commercial clients who may want an illustration for their book or for an advertisement. Already we're seeing those types of jobs going away because the people who commissioned those artists don't care in particular about the end product so if they can get an illustration by a cheaper means they'll go for it. — Mr Bee

Yes, some jobs will disappear or change into a new form. This have happened all the time throughout history when progress is rapidly changing society. Change is scary, and people are most of the time very comfortable in their bubble which when popped lead them to strike out like an animal defending themselves. This is where the luddite behavior comes into play.

But are we saying that we shouldn't progress technology and tools because of this?

When photoshop arrived with all its tools, all the concept artists who used pencils and paint behaved like luddites, trying to work against concept art being made with these new digital tools. When digital musical instruments started becoming really good, the luddites within the world of composing started saying that people who can't write notes shouldn't be hired or considered "real" composers.

What both these companies think and what luddites think of AI, they both forget that the working artist's biggest skill isn't that they can paint a straight line, or play a note, it's that they have the eye for composition and design, that they have an ear for melody, a mind for poetry.

People seem to have forgot what artists are actually hired for and it's not the craft. A concept artist isn't really hired for their personal style (if they're not among the biggest names in the industry), they're hired to guide the design based on the requirements of the project. They're hired for their ability to evaluate what's being formed and created.

All forms of art made within a larger project at such companies like game studios etc. is all in slavery to the overarching design of the entire project.

And because of this, the input that these artists have is very limited to the fundamental core of their expertise, i.e the knowledge of the artist to guide design towards the need of the project.

Therefore, a company who fires an artist in favor of someone who's not an artist to start working with AI generation, will soon discover that the art direction becomes sloppy and uninspiring, not because the AI model is bad, but because there's no "guiding principles" and expert eye guiding any of it towards a final state.

This is why artists need to learn to work with these models rather than reject them. Find ways of fusing their art style, maybe even train a personalized AI on their own art and work in a symbiosis with it.

Because this type of work for corporations is fundamentally soulless anyway. These artists aren't working with something they then own, the corporation owns it. They're there to serve a purpose.

In reality, an artist speeding up their process with AI would leave them more time to actually create for themselves. More time to figure out their own ideas and explore in more meaningful ways. Because they don't have to work overtime for some insecure producer who constantly changes their mind making them have to do patch works of their art because other people are lacking in creativity or ability to understand works of art.

Anyone who's been working within these kinds of corporate systems and these types of corporations aren't actually happy. Because there's no appreciation for anything they do and no understanding of their ideas as everything is filtered through whatever corporate strategy that drives the project from above.

Why not then be the artist who's an expert with AI? Because you can't put an intern onto writing prompts, that's not how generative AI works. You need to have an eye for art even if you work with AI. Utilizing AI in your work for these companies does not destroy your artistic soul for what you make for yourself or your own projects.

The "good enough" companies, before these AI models, have never been good for artists anyway. Why would artists ever even care for their work towards these companies if they themselves won't care for the artists? So if they start becoming artist with expertise in AI, then these companies will soon hire them back once they realize it's just not viable to have non-artists handling their AI generations.

I don't think artists have really been thinking enough about this shift in the industry. Instead they're behaving like luddites thinking that's a good way forward. And companies who don't know the value of artists, didn't value artists before either. And those companies who are forced into using AI due to how it speeds up projects when trying to compete with others, but who still focus on the quality of art in their product, will still hire actual artists for the job of handling the generative AIs. Because they understand that the quality of the artist isn't in the brush, or photoshop, or a random prompt, it's in the eye, ear and mind to evaluate what's being created, to make changes, to guide something, a design, towards a specific goal.

How all of this just seem to get lost in the debate about generative AI is mind boggling.

Maybe this is because there are more non-artists, who aren't even working with any of this, who drives the hate against AI. Just like all the people who hate CGI in movies and just suck up the marketing of "no CGI" in movies nowadays. When the truth is that CGI is used all of the time in movies and these people simply have no idea what they're talking about, they just want to start a brawl online to feed the attention economy with their ego.

Of course the data collection isn't the problem but what people do with it. It's perfectly fine for someone to download a bunch of images and store it on their computer but the reason why photobashing is considered controversial is that it takes that data and uses it in a manner that some consider to be insufficiently transformative. Whether AI's process is like that is another matter that we need to address. — Mr Bee

Then you agree that the lawsuits going on that targets the training process rather than the outputs, uses of outputs and the users misusing these models are in the wrong.

Sorry if I missed some of your points but your responses have been quite long. If we're gonna continue this discussion I'd appreciate it if you made your points more concise. — Mr Bee

Sorry, ready this too late :sweat: But still, the topic requires some complexity in my opinion as the biggest problem is how the current societal debate about AI is often too simplified and consolidated down into shallow interpretations and analysis.

You ask "Why is B theft?" but your scenario omits any legal criteria for defining theft, such as whether B satisfies a set threshold of originality.

How could we know whether B is theft when you don't show or describe its output, only its way of information processing. Then, by cherry picking similarities and differences between human and artificial ways of information processing, you push us to conclude that B is not theft. :roll: — jkop

Because the issue that the whole argument I made is about... is that there are claims of copyright infringement put on the process of training these models, not the output. When people scream "theft!" to the tech companies, they are screaming at the process of training the models using copyrighted material. What I demonstrated with the scenarios is that the process does not fall under copyright infringement, because it's an internal process that is behind closed doors, either inside our head or in the AI lab. And so, that process cannot be blamed for copyright infringement and the companies cannot be blamed to violate any copyright other than the output.

Because of this, the output is a question of alignment and the companies are actively working towards mitigating accidental plagiarism. Which means they're already working to adress the problems that artists don't like about AI generations. And the user is then solely the one responsible for how they use the generated images and are solely the ones who need to make sure they don't end up with plagiarized content.

But the main issue, why I'm making this argument, is that none of this matters for the artists doing lawsuits. They are attacking the first part, the process, the one that the scenario A and B is about. And therefore shown to not be interested in alignment or making sure these models are safe from plagiarism. Instead, they either have no knowledge of the technology and make shit up about how it is theft, things that aren't true about how the technology works because they think the companies just take their stuff and put it out there. Or they know how the technology works, but they intentionally target the part of the technology that would kill the models as an attempt to destroy the machines as the luddites did. Both of these stances are problematic and could lead to court rulings at a loss for artists, effectively giving less voice to artists in this matter, rather than enforcing them.

The argument is about focusing on alignment and how to improve the outputs past plagiarism. It's about making sure LLMs always cite something if they use direct quotes, and have guardrails that self-analyze the outputs to make sure it falls within our rather arbitrary definitions of originality.

Because people stare blindly into the darkness about these AI models. The positive sides of them, all the areas in which we actually benefit, like medical, sciences and even artists in terms of certain tools, are actually partly using the same models that are trained on this copyrighted material, because the amount of data is key to the accuracy and abilities of the models. So when artist want to block the usage of copyrighted material in training data, they're killing far more than they might realize. If a cancer drug development is utilizing GPT-4 and they suddenly must shut it down and retrain on less data, it will stop the development of that drug as well as maybe not be able to continue if a reworked model doesn't function the same due to the removal of a large portion of training data.

People, simply don't understand this technology and run around screaming "theft!" just because others scream "theft!". There's no further understanding and no further nuance to this topic and this simplified and shallow version of the debate needs to stop, for everyone's sake. These models are neither bad or good, they're tools and as such it's the usage of the tools that needs to be adressed, not let luddites destroy them.

One difference between A and B is this:

You give them the same analysis regarding memorizing and synthesizing of content, but you give them different analyses regarding intent and accountability. Conversely, you ignore their differences in the former, but not in the latter. — jkop

No, the AI system and the brain function in their physical process has no accountability because you can only put guilt on something that has subjective intent. And I've described how intent is incorporated into each. The human has both the process function AND the intent built into the brain. The AI system only has the process system and the intent is the user of that system. But if we still put responsibility on the process itself, then it's a problem with alignment and we can fine tune the AI system to align better. Even better than we can align a human as human emotion comes in the way of aligning their intent. Which is why accidental plagiarism happens all the time. We simply aren't smart enough in comparison to an AI model that's been properly aligned with copyright law. Such a system will effectively be better than a human at producing non-copyrighted material set within a decided value of "originality".

The processors in AI facilities lack intention, but AI facilities are owned and operated by human individuals and corporations who have extensive intentions. — BC

And those extensive intentions are what, in your perspective? And in what context of copyright do those intentions exist?

AGI doesn't necessarily have to think exactly like us, but human intelligence is the only known example of a GI that we have and with regards to copyright laws it's important that the distinction between an AGI and a human intelligence not be that all that wide because our laws were made with humans in mind. — Mr Bee

Not exactly sure what point you're making here? The only time in which copyright laws apply to the system itself and independent of humans either on the back or front end is when an AGI shows real intelligence and provable qualia, but that's a whole other topic on AI that won't apply until we're actually at that point in history. That could be few years from now, 50 years or maybe never, depending on things we've yet to know about AGI and super intelligence. For now, the AGI system's that are on the table mostly just combine many different tasks so that if you input a prompt it will plan, train itself and focus efforts towards a the goal you asked for without constant monitoring and iterative inputs from a human.

Some believe this would lead to actual subjective intelligence for the AI, but it's still so mechanical and lacking the emotional component that's key to how humans structure their experience that the possibility for qualia is pretty low or non-existent. So the human input, the "prompter" still carries the responsibility of its use. I think, however, that the alignment problem becomes a bigger issue with AGI as we can't predict in what ways an AGI plan and execute for a specific goal.

This is also why AGI can be dangerous, like the paperclip scenario. With enough resources at its disposal it can spiral out of control. I think that the first example of this will be a collapse of some website infrastructure like Facebook as the AGI ends up flooding the servers with operations due to a task that spirals out of control. So before we see nuclear war or any actual dangers we will probably see some sort of spammed nonsense because an AGI executed a hallucinated plan for some simple goal it was prompted to do.

But all of that is another topic really.

The question is whether or not that process is acceptable or if it should be considered "theft" under the law. We've decided as a society that someone looking at a bunch of art and using it as inspiration for creating their own works is an acceptable form of creation. The arguments that I've heard from the pro-AI side usually tries to equate the former with the latter as if they're essentially the same. That much isn't clear though. My impression is that at the very least they're quite different and should be treated differently. That doesn't mean that the former is necessarily illegal though, just that it should be treated to a different standard whatever that may be. — Mr Bee

The difference between the systems and the human brain has more to do with the systems not being the totality of how a brain works. It's simulating a very specific mechanical aspect of our mind, but as I've mentioned it lacks intention and internal will, which is why inputted prompts need to guide these processes towards a desired goal. If you were able to add different "brain" functions up to the point that the system is operating on identical terms as the totality of our brain, how do laws for humans start to apply on the system? When do we decide it having agency enough to be the one responsible for actions?

But the fundamental core to all of this is whether or not copyright laws apply to a machine that merely operate on simulating a human brain function. It may be that neural networks that are floating and constantly reshape and retrain itself on input data is all there is to human consciousness, we don't know until we reach that point for these models. But in the end it becomes rather a question of how copyright laws function within a simulation of how we humans "record" everything around us in memory and how we operate on it.

Because when we compare these systems to that of artists and how they create something, there are a number of actions by artists that seem far more infringing on copyright than what these systems do. If a diffusion model is trained on millions of real and imaginary images of bridges, it will generate a bridge that is merely a synthesis of them all. And since there's only a limited number of image perspectives of bridges that are three-dimensionally possible, where it ends up will weight more towards one set of images than others, but never a single photo. An artist, however, might take a single copyrighted image and trace-draw on top of it, essentially copying the exact composition and choice of perspective from the one who took the photograph.

So if we're just goin by the definition of a "copy" or that the system "copies" from the training data, it rather looks like there are more artists actually copying than there are actual copying going on within these diffusion models.

Copyright court cases have always been about judging "how much" was copied. It's generally about defining how many notes something was similar to, if lyrics or texts appeared in too many exact words or sentences after another. And they all depend on the ability of the lawyers and attorneys to prove that the actions taken were more or less based on a line drawn in the sand from previous cases that proved or disproved infringement.

Copyright law has always been shifting because it's trying to apply a definition of originality to determine if a piece of art is infringement or not. But the more we learn about the brain and creative process of the mind, the more we understand of how little free will we actually have and how influential our chemical and environmental processes are in creativity, and how less logical it is to propose "true originality". It simply doesn't exist. But copyright laws demand that we have a certain line drawn in the sand that defines where we conclude something "original", otherwise art and creativity cannot exist within a free market society.

Anyone who studied human creativity in a scientific manner, looking at biological processes, neuroscience etc. will start to see how these definitions soon become artificial and non-scientific. They are essentially arbitrary inventions that over the centuries and decades since 1709 have gone through patch-works trying to make sure that line in the sand is in the correct place.

But they're also taken advantage of. With artists that had a lot of power using it against lesser known artists. And institutions who've used it as a weapon to acquire pieces of work from artists who lose their compensation because they didn't have a dozen legal teams behind them fighting for their rights.

So, what exactly has "society" decided about copyright laws? In my view it seems to be a rather messy power battle rather than truly finding where the line is drawn in the sand. The reason why well-known artists try to prove copyright infringement within the process of training these models is that if they win, they will kill the models as they can't use the data that is necessary to train them. The idea of the existential threat to artists have skewed people's minds into making every attempt to kill these models, regardless of how illogical the reasoning is behind it. But it's all based on some magical thinking about creativity and ignoring the social and intellectual relationship between the artist and the audience.

So, first, creativity isn't a magic box that produce originality, there's no spiritual and divine source for it and that produces a problem for the people drawing the line in the sand. Where do you draw it? When do you decide something is original? Second, artists will never disappear because of these AI models. Because art is about the communication between the artist and their audience. The audience want THAT artist's perspective and subjective involvement in creation. If someone, artists or hacks who believe they're artists, think that generating a duplicate of a certain painting style through an AI system is going to kill the original artist, they're delusional. The audience doesn't care to experience derivative work, they care only about what the actual artist will do next, because the social and intellectual interplay between the artist and the audience is just as important, if not the most important aspect rather than some derivative content that looks similar. That artists believe they're gonna lose money on some hacks forcing an AI to make "copies" and derivative work out of their style is delusional on both sides of the debate.

In the end, it might be that we actually need the AI models for the purpose of deciding copyright infringement:

Imagine if we actually train these AIs on absolutely everything that's ever been created and possible to use as training data. And then we align that system to be used as a filter where we decide the weights of the system to approximately draw that line in the sand, based on what we "feel" is right for copyright laws. Then, every time we have a copyright dispute in the world, be it an AI generation or someone's actual work of art, this artwork is put through that filter and it can spot if that piece of work falls under copyright infringement or not.

That would solve both the problem with AI generated outputs and normal copyright cases that try to figure out if something was plagiarized.

This is why I argue for artists to work with these companies for the purpose of alignment rather than battling against them. Because if we had a system that could help spot plagiarized content and define what's derivative, it will not only solve the problems with AI generative content, it will also help artists that do not have enough legal power to win against powerful actors within the entertainment industry.

But because the debate is so simplified down to two polarized sides and that people's view on copyright laws is this belief that there is a permanent and rigid line in the sand, we end up in a battle about power struggles about other things rather than about artists actual rights, the creativity and the prospects of these AI models.

Judging the training process to be copyright infringement becomes a stretch and a very wiggly drawn line in that sand. Such a definition start to creep into aspects that doesn't really have to do with copying and spreading files, or plagiarism and derivative work. And it becomes problematic to define that line properly based on how artists themselves work.

Depends on what we're talking about when we say that this hypothetical person "takes parts of those files and makes a collage out of them". The issue isn't really the fact that we have memories that can store data about our experiences, but rather how we take that data and use it to create something new. — Mr Bee

Then you agree that the training process of AI models does not infringe on copyright and that it's rather the problem of alignment, i.e how these AI models generate something and how we can improve them not to end up producing accidental plagiarism that the focus should be on. And as I mentioned above, such a filter in the system or such an additional function to spot plagiarism would maybe even be helpful to determine if plagiarism has occurred even outside AI generations; making copyright cases more automatic and fair to all artists and not just the ones powerful enough to have a legal teams acting as copyright special forces.

Because a court looks at the work, that's where the content is manifest, not in the mechanics of an Ai-system nor in its similarities with a human mind. — jkop

If the court look at the actual outputted work, then the training process does not infringe on copyright and the problem is about alignment, not training data or the training process.

Defining how the system works is absolutely important to all of this. If lots of artists use direct copies of other's work in their own work and such work can pass copyright after a certain level of manipulation, then something that never use direct copies should also pass copyright. How a tool or technology function is absolutely part of how we define copyright. Such rulings have been going on for a long time and not just in this case:

https://en.wikipedia.org/wiki/White-Smith_Music_Publishing_Co._v._Apollo_Co.
https://en.wikipedia.org/wiki/Williams_%26_Wilkins_Co._v._United_States
https://en.wikipedia.org/wiki/Sony_Corp._of_America_v._Universal_City_Studios,_Inc.
https://en.wikipedia.org/wiki/Bridgeman_Art_Library_v._Corel_Corp.

What's relevant is whether a work satisfies a set threshold of originality, or whether it contains, in part or as a whole, other copyrighted works. — jkop

If we then look at only the output, there's cases like Mannion v. Coors Brewing Co., in which the derivative work can be argued is even more closely resembled to the original than what a diffusion model produce even when asked to do a direct copy, and yet, the court ruled that it was not copyright infringement.

So where do you draw the line? As soon as we start to define "originality" and we start to use scientific research on human creativity, we run into the problem of what constitutes "inspiration" or "sources" for the synthesis that is the creative output.

There is no clear line about what constitutes "originality", so it's not a binary question. AI generation can be ruled both infringement and not, so it all ends up being about alignment; how to make sure the system acts within copyright laws and not that it, in itself, breaks copyright law, which is what the anti-AI movement is trying to prove, on these shaky grounds. And the question of what constitutes "originality" is within the history of copyright cases a very muddy defined concept, to the point that anyone saying the concept is "clear", don't know enough about this topic and has merely made up their own mind about what they themselves believe, which is no ground for any law or regulation.

There are also alternatives or additions to copyright, such as copyleft, Creative Commons, Public Domain etc. Machines could be "trained" on such content instead of stolen content, but the Ai industry is greedy, and to snag people's copyrighted works, obfuscate their identity but exploit their quality will increase the market value of the systems. Plain theft! — jkop

And now you're just falling back on screaming "theft!" You simply don't care about the argument I've made over and over now. Training data is not theft because it's not a copy and the process mimics how the human brain memorize and synthesize information. It's not theft for a person with photographic memory, so why is it theft for these companies when they're not distributing the raw data anywhere?

Once again you don't seem to understand how the systems work. It's not about greed; the systems require such a large amount of data to function in a way that makes the technology function properly. The amount of data is key. And HOW the technology works is absolutely part of how we define copyright laws, as described with the cases above. So ignoring how this tech works and just screaming that they are "greeeeedy!" just becomes the same shouting polarized hashtag mantra that everyone else is doing right now.

And this attitude and lack of knowledge about the technology show up in your contradictions:

Because a court looks at the work, that's where the content is manifest, not in the mechanics of an Ai-system nor in its similarities with a human mind. — jkop

Machines could be "trained" on such content instead of stolen content, but the Ai industry is greedy... Plain theft! — jkop

...If the court should just look at the output, then the training data and process is not the problem, but still you scream that this process is theft, even though the court might only be able to look at what the output of these AI models are doing.

The training process using copyrighted material happens behind closed doors. Just like artists gathering copyrighted material in their process to produce their artwork. If the training process on copyrighted material is identical to an artist using copyrighted material when working, since both appears behind closed doors... the only thing that matters is the final artwork and output from the AI. If alignment is solved, there won't be a problem, but the use of copyrighted material in the training process is not theft, regardless of how you feel about it.

Based on previous copyright cases, if the tech companies win against those claiming the training process is "theft", it won't be because the companies are greedy and have "corrupted" legal teams, it will be because of the copyright law itself and how it's ruled in the past. It's delusional to think that all of this concludes in "clear" cases of "theft".

A and B are set up to acquire writing skills in similar ways. But this similarity is irrelevant for determining whether a literary output violates copyright law. — jkop

Why is it irrelevant? The system itself lacks the central human component that is the intention of its use. While the human has that intention built in. You cannot say the system violates copyright law as the system itself isn't able to either have copyright on its output or by its own will break copyright. This has been established by the "https://en.wikipedia.org/wiki/Monkey_selfie_copyright_dispute" and would surely apply to an AI model as well. That leaves the user as the sole agent responsible for the output, or rather, for the use of the output.

Because I can paint a perfect copy of someone else's painting. It's rather in what way I use it that defines how copyright is applied. In some cases I can show my work crediting the original painter, in some cases I can sell it like that, or I will not be able show it at all but still have it privately or unofficially. The use of the output defines how copyright applies and because of that we are far past any stage in which the AI model and its function is involved, if it has at all made anything even remotely close to infringing on copyright.

It's basically just a tool, like the canvas, paint and paintbrush. If I want to sell that art, it's my responsibility to make sure it isn't breaking any copyright laws. The problem arise when people make blanket statements that all AI outputs break copyright, which is a false statement. And even if there is a ruling that forbid the use of AI systems, they would only be able to criminalize monetization of outputs, not if they're used privately or unofficially within some other creative process as a supporting tool.

All artists use copyrighted material during their work, painters usually cut out photos and print out stuff to use as references and inspiration while working. So all of this becomes messy for those proposing to shut these AI models down, and in some cases lead to double standards.

In any case it leads back to the original claim that my argument challenge. The claim that the training process is breaking copyright because it is trained on copyrighted material. Which is what the A and B scenario is about.

You blame critics for not understanding the technology, but do you understand copyright law? Imagine if the law was changed and gave Ai-generated content carte blanche just because the machines have been designed to think or acquire skills in a similar way as humans. That's a slippery slope to hell, and instead of a general law you'd have to patch the systems to counter each and every possible misuse. Private tech corporations acting as legislators and judges of what's right and wrong. What horror. — jkop

Explain to me what it is that I don't understand about copyright law.

And explain to me why you make such a slippery slope argument as some kind of "appeal to extremes" fallacy thinking that such a scenario is what I'm proposing. You don't seem to read what I write when I say that artist need to work with these companies for the purpose of alignment. Do you understand what I mean by that? Because your slippery slope scenario tells me that you don't.

You keep making these strawmans out of a binary interpretation of this debate. That me criticizing how artists argue against AI means I want to rid all copyright law from AI use. That is clearly false.

I want people to stop making uninformed, uneducated and polarized arguments and instead educate themselves to understand the systems so the correct arguments can be made that make sure artists and society can align with the development of AI. Because the alternative is the nightmare you fear. And when artists and people just shout their misinformed groupthink opinions as hashtags until a court rules against them because they didn't care to understand how these systems work, that nightmare begins.

If your claim is that similarity between human and artificial acquisition of skills is a reason for changing copyright law, then my counter-argument is that such similarity is irrelevant. — jkop

How do you interpret this being about changing copyright law? Why are you making stuff up about my argument? Nowhere in my writing did I propose we change copyright laws in favor of these tech companies. I'm saying that copyright law does not apply to the training process of an AI model as the training process is not an action of copyright infringement anymore than a person with photographic memory who reads all books in a library. You seem unable to understand the difference between the training process and the output generation? And it's this training process specifically that is claimed to infringe on copyright and the basis of many of the current lawsuits. Not the generative part. Or rather, they've baked these lawsuits into a confused mess of uninformed criticism that with good lawyers on the tech company's side could argue in the same manner I do. And the court requires proof of copyright infringement. If the court rules that there's no proof of infringement in the training process, it could spiral into dismissal of the case, and that sets the stage for a total dismissal of all artists concerns. No one seems to see how dangerous that is. This is why my actual argument that you seem to misunderstand constantly, is to focus on the problems with image generation and create laws that actually dictate mandatory practices for these tech companies to work with artists for the purpose of alignment. That's the only way forward. These artists are now on a crusade to try and rid the world of these AI models and it's a fools errand. They don't understand the models and the technology, and try bite off more than they can chew instead of focusing their criticism properly.

What is relevant is whether the output contains recognizable parts of other people's work. — jkop

Alignment is work already being conducted by these companies, as I've said now numerous times. It's about making sure plagiarism doesn't occur. It's in everyone's interest that it doesn't happen.

And the challenge is that you need to define "how similar" something is in order to define infringement. This is the case in every copyright case in court. Artists are already using references that copy entire elements into their own work without it being copyright infringement. Artists can see something in certain colors, then see something else with a nice composition, then see a picture in a newspaper that becomes the central figure in the artwork and they combine all three into a new image that everyone would consider "original". If an AI model does exactly the same, and at the same time only use its neural memory, it's using even less direct references and influences as a diffusion model never copy anything directly into an image. Even older examples of outdated misaligned models that show almost identical images still can't reproduce them exactly, because they aren't using a file as the source, they're using neural memory in the same way we humans do. Compare that to artists who directly use other people's work in their art, it happens more than people realize. Just check how many films in which directors blatantly copy a painting into a shot composition and style, or use an entire scene from another movie almost verbatim. How do you draw the line? Why would the diffusion models and LLMs be worse than how artists are already working? As I said, it ends up being an arbitrary line in which we just conclude... because it's a machine. But as I've said, the machine, like the gun that forced the painter to plagiarize, cannot be blamed for copyright infringement. Only the user can.

One might unintentionally plagiarize recognizable parts of someone else's picture, novel, scientific paper etc. and the lack of intent (hard to prove) might reduce the penalty but hardly controversial as a violation. — jkop

Yes, which means the alignment problem is the most important one to solve. Yet, as mentioned, if we actually study how artists work, if we check their process, if I check my own process, it quickly becomes very muddy how works of art forms. People saying that art magically appears out of our divine creativity are just religious and spiritual and that's not a foundation for laws. The creative process is part a technological/biological function and part subjective intention. If the function can be externalized as a tool, then how do copyright get defined? Copyright can only be applied to intention, it cannot be applied to the process, otherwise all artists would infringe on copyright in their process of creation.

In the end, if alignment gets solved for these AI models, to the point they are unable to copy anything over a certain point of plagiaristic level for an output, and that this aligns with copyright laws for definitions of "originality", then these systems will actually be better at avoiding copyright infringement than human artists, because they won't try to fool the copyright system for the purpose of gaining something out of riding on other's success, which is the most common reason why people infringe on copyright outside the accidental. An aligned system does not care, it only sets the guardrails so that the human component cannot step over the line.

There is data, and at a deeper level there is what the data means. Can an AI algorithm ever discover what data means at this deeper level? — RussellA

The system doesn't think, the system doesn't have intention. Neither writer exists within the system, it is the user that informs the intention that guides the system. It's the level of complexity that the system operates on that defines how well that output becomes. But the fact remains that if the engineer program the system not to plagiarize and the user doesn't ask for plagiarism, there's no plagiarism going on anymore than an artist who draws upon their memory of works of art that inspire them. These systems have build in guardrails that attempt to prevent accidental plagiarism, something that occurs all the time by humans and has been spottet within the systems as well. But in contrast to human accidental plagiarism, these systems are getting better and better at discovering such accidents, because such accidents are in no ones interest. It's not good for the artist who's work was part of the training data, it's not good for the user and it's not good for the AI company. No one has any incentive to let these AI models be plagiarist machines.

But the problem I'm bringing up in my argument primarily has to do with claims that the act of training the AI model using copyrighted material is plagiarism and copyright infringement. That's not the same as the alignment problem of its uses that you are bringing up.

If alignment keeps getting better, will artists stop criticizing these companies for plagiarism? No. Even if AI models end up at a point where it's basically impossible to get accidental plagiarism, artists will not stop criticizing, because they aren't arguing based on rational reasoning, they want to take down these AI models because many feel they're a threat to their income and they invent lies about how the system operates and about what the intentions are of the engineers and the companies behind these models. They argue that these companies "intentionally targets" them when they don't. These companies invented a technology that mimic how the human brain learn and memorize and how this memory functions as part of predicting reality, demonstrating it with predicting images and text into existence and how this prediction start to emerge other attributes of cognition. It's been happening for years, but is now at a point in which there can be practical applications in society for their use.

We will see the same with robotics in a couple of years. The partly Nvidia-lead research using LLMs for training robots that was just published showed how GPT-4 can be used in combination with robotics training and simulation training. Meaning, we will see a surge in how well robots perform soon. It's basically just a matter of time before we start seeing commercial robots for generalized purposes or business applications outside of pure industrial production. And this will lead to other sectors in society starting to criticize these companies for "targeting their jobs".

But it's always been like this. It's the luddites all over the again, smashing the industrial machines instead of getting to know what this new technology could mean and how they could use them as well.

That's one of the main issues right? How comparable human creativity is to that of AI. When an AI "draws upon" all the data it is trained on is it the same as when a human does the same like in the two scenarios you've brought up?

At the very least it can be said that the consensus is that AIs don't think like we do, which is why don't see tech companies proclaiming that they've achieved AGI. There are certainly some clear shortcomings to how current AI models work compared to human brain activity, though given how little we know about neuroscience (in particular the process of human creativity) and how much less we seem to know about AI I'd say that the matter of whether we should differentiate human inspiration and AI's' "inspiration" currently is at best unclear. — Mr Bee

AGI doesn't mean it thinks like us either. AGI just means that it generalizes between many different functions and does so automatically based on what's needed in any certain situation.

But I still maintain that people misunderstand these things. It's not a binary question, it's not that we are looking at these systems as A) Not thinking like humans therefore they are plagiarism machines or B) They think like us therefor they don't plagiarize.

Rather, it is about looking at what constitutes plagiarism and copyright theft in these systems. Copyright laws are clear when it comes to plagiarism and stealing copyrighted material. But they run into problems when they're applied as a blanket statement against these AI models. These AI models doesn't think like us, but they mimic parts of our brain. And mimicking part of our brain is not copyright infringement or theft because if it does so with remarkable similarity, then we can't criticize these operations without criticizing how these functions exists within ourselves. The difference between our specific brain function and these AI systems become arbitrary and start to take the form of spirituality or religon in which the critics falls back on "because we are humans".

Let's say we build a robot that uses visual data to memorize a street it walks along. It uses machine learning and as a constantly updating neural network that mimics a floating memory system like our own neural network constantly changing with more input data. While walking down the street it scans its surroundings and memorize everything into neural connections, like we do. At some point it ends up at a museum of modern art and goes inside, and inside it memorizes its surroundings, but that also means all the paintings and photographs. Later in the lab we ask it to talk about its day, it may describe its route and we ask it to form an image of the street. It produces an image that somewhat looks like the street, skewed, but with similar colors, similar weather and so on. This is similar to how we remember. We then ask it to draw a painting inspired by what it saw int the museum. What will it do?

Critics of AI would say it will plagiarize, copy and that it has stored the copyrighted photos and paintings through the camera. But that's not what has happened. It has a neural network that formed out of the input data, it doesn't have a flash card storing it as a video or photo of something. It might draw something that is accidental plagiarism out of that memory, but since the diffusion system generates from a noise through prediction into form, it will always be different than pure reality, different from a pure copy. Accidental plagiarism happens all the time with people and as artists we learn to check our work so it doesn't fall under it. If the engineers push the system to do such checks, to make sure it doesn't get too close to copyrighted material, then how can it plagiarize? Then we end up with a system that does not directly store anything, it remembers what it has seen just like humans remembers through our own neural network, and it will prevent itself from drawing anything too close to an original.

One might say that the AI system's neural memory is too perfect and would constitute being the same as having it on a normal flash card, but how is that different from a person with photographic memory? It then becomes a question of accuracy, effectively saying that people with photographic memory shouldn't enter a museum as they are basically storing all those works of art in their neural memory.

Because what the argument in here is fundamentally about is the claim that the act of training AI models on copyrighted material is breaking copyright. The use and alignment problem is another issue and an issue that can be solved without banning these AI models. But the promotion for banning these systems stem from claims that they were trained on copyrighted material. And it is that specific point that I argue doesn't hold due to how these systems operate and how the training process is nearly identical to how humans are "training" their own neural-based memory.

Let's say humans actually had a flash card in our brain. And everything we saw and heard, read and experienced, were stored as files in folders on that flash card. And when we wrote or painted something we all just took parts of those files and produced some collage out of them. How would we talk about copyright in that case?

But when a system does the opposite and instead mimic how our brain operate and how we act from memory, we run into a problem as much of our copyright laws are defined based on interpreting "how much" a human "copied" something. How many notes were taken, accidentally or not, how much of another painting can be spotted in this new work etc. But for AI generated material, it seems that it doesn't matter how far off from other's work it is, it could be provably as original as any other human creation deemed "original", but it still gets blamed as plagiarism because the training data was copyrighted material, not realizing that artists function on the same principles and sometimes even go further than these AI systems, as my example of concept artists showed.

The conclusion, or message I'm trying to convey here is that the attempt to ban these AI models and call their training process theft is just luddite behavior out of existential fear. And that the real problem is alignment to prevent accidental plagiarism, which is something these companies work hard to prevent as it's in no ones interest for that to happen in outputs. That this antagonizing pitch fork behavior that artists and other people have in this context is counter-productive and that they should instead demand to work WITH these companies to help mitigate accidental plagiarism and ill-willed use of these models.

It's not like photobashing isn't controversial too mind you. So if you're saying that AI diffusions models are equivalent to that practice then that probably doesn't help your argument. — Mr Bee

No, I'm saying diffusion models doesn't do that and that there's a big irony to the fact that many concept artists who are now actively trying to fight AI with arguments of theft effectively have made money in the past through a practice that is the very same process they falsely accuse these diffusion models of doing based on a misunderstanding of how they actually operate. The operation of these diffusion models, compared to that practice, actually makes the model more moral than the concept artists within this context as diffusion models never directly copies anything into the images, since they don't have any direct copies in memory.

This highlights a perfect example of why artist's battle to ban these models and their reasoning behind it becomes rather messy and could bite them back in ways that destroys far more for them than if they actually tried to help these companies to instead align their models for the benefit of artists.

According to you, or copyright law? — jkop

According to the logic of the argument. Copyright law does not cover these things and the argument I'm making is that there are problems with people's reasoning around copyright and how these systems operate. A user that intentionally push a system to do plagiarism and who carefully manipulate the prompts for that intention, disregarding any warnings by the system and the alignment programming of it to not do so... ends up solely being the guilty one. It's basically like if you asked a painter to make a direct copy of a famous painting and the painter says "no", pointing out that's plagiarism, yet you take out a gun and hold it to the painter's head and demand it. Will any court of law say that the painter, who is capable of painting any kind of painting in the world, is as guilty as you, just because he has that painting skill, knowledge of painters and different paintings, and the technical capability?

If 'feeding', 'training', or 'memorizing' does not equal copying, then what is an example of copying? It is certainly possible to copy an original painting by training a plagiarizer (human or artificial) in how to identify the relevant features and from these construct a map or model for reproductions or remixes with other copies for arbitrary purposes. Dodgy and probably criminal. — jkop

No one is doing this. No one is intentionally programming the systems to plagiarize. It's just a continuation of the misunderstandings. Training neural network systems is a computer science field in the pursuit of mimicking the human mind. To generalize operation to function beyond direct programming. If you actually study the history of computer science in artificial intelligence, the concept of neural network and machine learning has to do with forming neural networks in order to form operations that act upon pattern recognition, essentially forming new ideas or generalized operation out of the patterns that emerge from the quantity of analyzed information and how they exist in relation to each other. This is then aligned into a system of prediction that emulate the predictive thinking of our brains.

A diffusion model therefor "hallucinate" forward an image out of this attempt to predict shapes, colors and perspective based on what it has learned, not copies of what it used to learn. And the key component that is missing is the guiding intent; "what" it should predict. It's not intelligent, it's not a thinking machine, it merely mimics the specific process of neural memory, pattern recognition and predictive operation that we have in our brains. So it cannot just predict on its own, it can't "create on its own". It needs someone to guide the prediction.

Therefore, if you actually look at how these companies develop these models, you will also see a lot of effort put into alignment programming. They do not intentionally align the models to perform plagiarism, they actively work against it, and making sure there are guardrails for accidental plagiarism and block users trying to intentionally produce it. But even so, these systems are black boxes and people that want to manipulate and find backdoors into plagiarism could be able to do so, especially on older models. But that only leads back to who's to blame for plagiarism and it becomes even clearer that it's the user of the system who intentionally want to plagiarize something and solely becomes the one guilty of it. Not the engineers, or the process of training these models.

You use the words 'feeding', 'training', and 'memorizing' for describing what computers and minds do, and talk of neural information as if that would mean that computers and minds process information in the same or similar way. Yet the similarity between biological and artificial neural networks has decreased since the 1940s. I've 'never seen a biologist or neuroscientist talk of brains as computers in this regard. Look up Susan Greenfield, for instance. — jkop

The idea behind machine learning and neural networks were inspired by findings in neuroscience, but the purpose wasn't to conclude similarities, it was to see if operations could be generalized and improve predictability in complex situations, such as robotics based on experimenting with similarities to what neuroscientists had discovered about the biological brain. It's only just recently that specific research in neuroscience (IBS, MIT etc.) has been focusing on these similarities between these AI models and how the brain functions, concluding that there are striking similarities between the two. But the underlying principles of operation has always been imitating how memory forms. But you confuse the totality of how a brain operates with the specific function of memory and predictability. Susan Greenfield is even aligned with how memory forms in our brain and hasn't published anything to the contrary of what other researchers have concluded in that context. No one is saying that these AI systems acts as the totality of the brain, but the memory in our head exists as a neural network that acts from the connections rather than raw data. This is how neuroscientists describes how our memory functions and operates as the basis for prediction and actions. The most recent understandings is that memories are not stored in parts of the brain, but instead exists as spread across the brain with different regions featuring a more or less concentration of connections based on the nature of the information. Essentially acting like weights and biases in an AI system that focus how memories are used.

The fact is that our brain doesn't store information like a file. And likewise, a machine-learned neural network doesn't either. If I read and memorize a page from a book (easier if I had photographic memory), I didn't store this page in my head as a file like a computer does. The same goes for a neural network that was trained with this page. It didn't copy the page, it has put it in relation to other pages, other texts, other things in the world that has been part of its training. And just like our brain, if we were to remove the "other stuff", then the memory and understanding of that specific page would deteriorate, because the memory of the page relies on how it relates to other knowledge, other information, about language, about visual pattern recognition, about contextual understanding of the texts meaning and so on. All are part of our ability to remember the page and our ability to do something with that memory.

Again, I ask... what is the difference in scenario A and scenario B? Explain to me the difference please.

Your repeated claims that I (or any critic) misunderstand the technology are unwarranted. You take it for granted that a mind works like a computer (it doesn't) and ramble on as if the perceived similarity would be an argument for updating copyright law. It's not. — jkop

It's not unwarranted since the research that's being done right now continues to find similarities to the point that neuroscientists are starting to utilize these AI models in their research in order to further understand the brain. I don't see anyone else in these debates actually arguing out of the research that's actually being done. So how is it unwarranted to criticize others for not fully understanding the technology when they essentially don't? Especially when people talk about these models storing copyrighted data when they truly don't, and that these engineers also fundamentally programmed the models to focus on doing plagiarism, when that's a blatant lie.

It seems rather that it's you who take for granted that your outdated understanding of the brain is enough as a counter argument. And forget the fact that there are currently no final scientific conclusions as to how our brain works. The difference however, is that I'm writing these arguments out of the latest research in these fields and that's the only foundation to form any kind of argument, especially when we're talking about the context of this topic. What you are personally convinced about when it comes to how the brain works is irrelevant, whoever you've decided to trust in this field is irrelevant. It's the consensus of up to date neuroscience and computer science that should act as the foundation for arguments.

So, what are you basing your counter arguments on? What exactly is your counter argument?

The definitions of how artists work upon inspirations and other's work is part of the equation, but still dependent on the intention of the artist. The intention isn't built into the AI models, it's the user that forms the intended use and guiding principle of creation.

So, artist's stealing from other artists is the same as a user prompting the AI model to "steal" in some form. But the production of the text or image by the AI model is not theft in itself, it's merely a function mimicking how the human brain acts upon information (memory) and synthesize that into something new. What is lacking within the system itself is the intention and thus it can't be blamed for theft.

Which means we can't blame the technicians and engineers for copyright infringement as these AI models don't have "copies" of copyrighted work inside them. An AI model is trained on data (the copyrighted material) and forms a neural network that functions as its memory and foundation of operation, i.e what weights and biases it has for operating.

So, it's essentially exactly the same as how our brain structure works when it uses our memory that is essentially a neural network formed by raw input data; and through emotional biases and functions synthesize those memories into new forms of ideas and hallucinations. Only through intention do we direct this into forming an intentional creative output, essentially forming something outside of us that we call art.

It's this difference that gets lost in the debate around AI. People reason that the training data is theft, but how can that be defined as theft? If I have a photographic memory and I read all books in a library, I've essentially formed a neural network within me on the same ground as training a neural network. And thus, there are no copies, there's only a web of connections that remember data.

If we criminalize remembering data, the formation of a neural network based on data, then a person with photographic memory is just as guilty by merely existing in the world. The difference between training an AI model and a human becomes arbitrary and emotional rather than logical.

We lose track of which moral actions are actually immoral and blame the wrong people. It's essentially back to the luddites destroying machines during the industrial revolution, but this time, the immoral actions of the users of these AI systems gets a pass and instead the attacks gets directed towards the engineers. Not because they're actually guilty of anything, but rather because of the popularity of hating big tech. It's a polarizing situation in which the rational reasoning gets lost in favor of people forming an identity around whatever groupthink they're in

And we might lose an enormous benefit to humanity through future AI systems because people don't seem to care to research how these things actually operate and instead just scream out their hate due to their fear of the unknown.

Society needs to be smarter than this. Artists need to be smarter than this.

The user of the system is accountable — jkop

If the user asks for an intentional plagiarized copy of something, or a derivative output, then yes, the user is the only one accountable as the system does not have intention on its own.

possibly its programmers as they intentionally instruct the system to process copyright protected content in order to produce a remix. It seems fairly clear, I think, that it's plagiarism and corruption of other people's work. — jkop

But this is still a misunderstanding of the system and how it works. As I've stated in the library example, you are yourself feeding copyrighted material into your own mind that's synthesized into your creative output. Training a system on copyrighted material does not equal copying that material, THAT is a misunderstanding of what a neural system does. It memorize the data in the same way a human memorize data as neural information. You are confusing the "intention" that drives creation, with the underlying physical process.

There is no fundamental difference between you learning knowledge from a book and these models learning from the same book. And the "remix" is fundamentally the same between how the neural network forms the synthesis and how you form a synthesis. The only difference is the intention, which in both systems, the mind and the AI model, is the human input component.

So it's not clear at all that it's plagiarism because the description of the system that you did isn't correct about how it functions. And it's this misunderstanding that a neural network and machine learning functions and this mystification about how the human mind works that produces these faulty conclusions.

If we are to produce laws and regulations for AI, they will need to be based on the most objective truths about how these systems operate. When people make arguments that make arbitrary lines between how artificial neural networks work and neural networks in our brains, then we get into problematic and arbitrary differences that fundamentally spells out an emotional conclusion: "we shouldn't replicate human functions" and the followup question becomes "on what grounds?" Religious? Spiritual? Emotional? Neither which is grounds for laws and regulations.

What's similar is the way they appear to be creative, but the way they appear is not the way they function. — jkop

That's not what I'm talking about or what this argument is about. The appearance of creativity is not the issue or fundamental part of this. The function; the PHYSICAL function of the system is identical to how our brain functions within the same context. The only thing that's missing is the intention, the driving force in form of the "prompt" or "input request". Within us, our creativity is interlinked with our physical synthesis system and thus it also includes the "prompt"; the "intention" of creation. AI systems however, only has the synthesis system, but that in itself is not breaking any copyrights anymore than our own mind when we experience something and dream, hallucinates and produce ideas. The intention to plagiarize is a decision and that decision is made by a human, that responsibility is made by a human at the point of the "intention" and "prompt", not before it.

And so, the argument can be made that a person who reads three books and writes a derivative work based on those three books is doing the same as someone who prompts an AI to write derivative work. Where do you put the blame? On reading the three books (training the models), or the intention of writing the derivative work (prompting the AI model to write derivative)?

If you put the blame on the act of training the models, then you also put blame on reading the books. Then you are essentially saying that the criminal act of theft is conducted by all people all the time they read, see, hear and experience someone else's work. Because that is the same as training these models, it is the same fundamental process.

But putting blame on that is, of course, absurd. We instead blame the person's intent of writing a derivative piece. We blame the act of wanting to produce that work. And since the AI models doesn't have that intent, you cannot logically put blame on the act of training these models on copyrighted material, because there's nothing in that act that breaks copyright. It's identical to how we humans consume copyrighted material, storing it in neural memory form. And a person with photographic memory excels at this type of neural storage, exactly like these models.

A machine's iterative computations and growing set of syntactic rules (passed for "learning") are observer-dependent and, as such, very different from a biological observer's ability to form intent and create or discover meanings. — jkop

I'm not sure if you really read my argument closely enough because you keep mixing up intention with the fundamental process and function of information synthesis.

There are two parts of creation: 1) The accumulation of information within neural memory and its synthesis into a new form. 2) The intention for creation that guides what is formed. One is the source and one is the driving principle for creation out of that source. The source itself is just a massive pool of raw floating data, both in our minds and in these systems. You cannot blame any of that for the creation because that is like blaming our memory for infringing on copyrighted material. It's always the intention that defines if something is plagiarized or derivative. And yes, the intention is a separate act. We constantly produce ideas and visions even without intent. Hallucinations and dreams form without controlled intent. And it's through controlled intent we actually create something outside of us. It is a separate act and part of the whole process.

And this is the core of my argument. Blaming the process of training AI models as being copyright infringement is looking to be objectively false. It's a fundamental misunderstanding of how the system works, and they seem to more or less come from people's emotional hate for big tech. I'm also critical of big tech, but people will lose much more control over these systems if our laws and regulations get defined by court rulings in which we lose because side of the people made naive emotional arguments about things they fundamentally don't understand. Misunderstandings of the system, of the science of neural memory and functions and how our own minds work.

I ask, how are these two different?

A) A person has a perfect photographic memory. They go to the library every day for 20 years and read every book in that library. They then write a short story drawing upon all that has been read and seen in that library during these 20 years.

B) A tech company let an algorithm read through all books at the same library, which produces a Large Language Model based on that library as its training data. It's then prompted to write a short story and draws upon all it has read and seen through the algorithm. — Christoffer

This is the core of this argument. The difference between intention and the formation of the memory core that creation is drawn from and how synthesis occurs. That formation and synthesis in itself does not break copyright laws, but people still call it theft without thinking it through properly.

Neither man nor machine becomes creative by simulating some observer-dependent appearance of being creative. — jkop

This isn't about creativity. This isn't about wether or not these systems "can be creative". The "creative process" does not imply these systems being able to produce "art". This type of confusion in the debate is what makes people not able to discuss the topic properly. The process itself, the function that simulates the creative process, is not a question of "art" and AI, that's another debate.

The problem is that people who fight against AI, especially artists fighting against these big tech companies, put blame on the use of copyrighted material in training these models, without understanding that this process is identical to how the human mind is "trained" as well.

All while many artists, in their own work and processes, directly use other people's work in the formation of their own, but still put some arbitrary line between themselves and the machines when these machines seem to do the same, even though things like diffusion models are fundamentally unable to do produce direct copies in the same way as some of these artists do (as per the concept art example).

It's a search for a black sheep in the wrong place. Antagonizing the people in control of these systems rather than trying to promote themselves, as artists, to be part of the development and help form a better condition for future artists.

I think you meant my comment was written with A.I. and it was in fact. Good looking out, Lionino. I am messing with newly updated Bing Copilot. My post was translated here by me from the help of a.i., but I did not directly copy and paste it from chat. — Kizzy

Rather than have the AI write for you, write your own post and maybe analyze the grammar and structure by the AI as support. While AI functions well att writing, the problem is that you lose or never challenge your own process of thought as writing isn't just outward communication, it's part of your internal processing of ideas.

It's been proven in studies that the physicality of writing increases the brain activity. It is stronger in writing on paper with a pen as it's the most physical action you can do, but it's also there while writing on a keyboard.

So letting an AI do that work for you will only lead to you losing something in the purpose of gaining knowledge through discourse. So, write your own stuff and maybe use AI as a research and editing tool, but never as the source of train of thought for an argument. It will make you cognitively numb.