Isn't any answer to a question which hasn't been previously answered a derivative work? Or when a human write a parody of a song, or when a new type of music is influenced by something which came before.
This argument is so bizarre to me. Humans create new, spontaneous thoughts. AI doesn’t have that. Even if someone’s comment is influenced by all the data they have ingested over their lives, their style is distinct and deliberate, to the point where people have been doxxed before/anonymous accounts have been uncovered because someone recognized the writing style. There’s no deliberation behind AI, just statistical probabilities. There’s no new or spontaneous thoughts, at most pseudorandomness introduced by the author of the model interface.
Even if you give GenAI unlimited time, it will not develop its own writing/drawing/painting style or come up with a novel idea, because strictly by how it works it can only create „new” work by interpolating its dataset
There is no evidence whatsoever to support that humans create "new, spontaneous thoughts" in any materially, qualitatively different way than an AI. In other words: As a Turing-computable function over the current state. It may be that current AI's can't, but the notion that there is some fundamental barrier is a hypothesis with no evidence to support it.
> Even if you give GenAI unlimited time, it will not develop its own writing/drawing/painting style or come up with a novel idea, because strictly by how it works it can only create „new” work by interpolating its dataset
If you know of any mechanism whereby humans can do anything qualitatively different, then you'd have the basis for a Nobel Prize-winning discovery. We know of no mechanism that could allow humans to exceed the Turing computability that AI models are limited to.
We don't even know how to formalize what it would mean to "come up with a novel idea" in the sense you appear to mean, as presumably, something purely random would not satisfy you, yet something purely Turing computable would also not do, but we don't know of any computable functions that are not Turing computable.
This argument, by now a common refrain from defenders of companies like OpenAI, misses the entire putative point of intellectual property, and the point of law in general. It is a distraction of a common sort - an attempt to reframe a moral and legal question into an abstract ontological one
The question of whether the mechanism of learning in a human brain and that in an artificial neural network is similar is a philosophical and perhaps technical one that is interesting, but not relevant to why intellectual property law was conceived: To economically incentivize human citizens to spend their time producing creative works. I don't actually think property law is a good way to do this. Nonetheless the question when massive capital investments are used to scrape artists' work in order to undercut their ability to make a living from that work for the benefit of private corporations that do not have their consent to do this is whether this should violate this artificial notion of intellectual property that we have constructed for this purpose, and in that sense, it's fairly obvious that the answer is yes
Yea I'll give you that. But many people seem to have the argument you've made - which is dubious on its own terms, by the way, as we don't really have a complete picture of human learning and the assumption that it simply follows the mechanisms we understand from machine learning is not a null hypothesis that doesn't demand justification - loaded up for these conversations, and it needs to be addressed wherever possible that the ontological question is not what matters here
> which is dubious on its own terms, by the way, as we don't really have a complete picture of human learning and the assumption that it simply follows the mechanisms we understand from machine learning is not a null hypothesis that doesn't demand justification
The argument I made in no way rests on a "complete picture of human learning". The only thing they rest on is lack of evidence of computation exceeding the Turing computable set. Finding evidence of such computation would upend physics, symbolic logic, maths. It'd be a finding that'd guarantee a Nobel Prize.
I gave the justification. It's a simple one, and it stands on its own. There is no known computable function that exceeds the Turing computable, and all Turing computable functions can be computed on any Turing complete system. Per the extended Church Turing thesis this includes any natural system given the limitations of known physics. In other words: Unless you can show knew, unknown physics, human brains are computers with the same limitations as any electronic computer, and the notion of "something new" arising from humans, other than as a computation over pre-existing state, in a way an electronic computer can't also do, is an entirely unsupportable hypothesis.
> and it needs to be addressed wherever possible that the ontological question is not what matters here
It may not be what matters to you, but to me the question you clearly would prefer to discuss is largely uninteresting.
> In other words: As a Turing-computable function over the current state.
You need to be a bit more expansive. Turing-computable functions need to halt and return eventually. (And they need to be proven to halt.)
> We know of no mechanism that could allow humans to exceed the Turing computability that AI models are limited to.
Depends on which AI models you are talking about? When generating content, humans have access to vastly more computational resources than current AI models. To give a really silly example: as a human I can swirl some water around in a bucket and be inspired by the sight. A current AI model does not have the computational resources to simulate the bucket of water (nor does it have a robotic arm and a camera to interact with the real thing instead.)
> You need to be a bit more expansive. Turing-computable functions need to halt and return eventually. (And they need to be proven to halt.)
This is pedantry. Any non-halting function can be decomposed into a step function and a loop. What matters is that step function. But ignoring that, human existence halts, and so human thought processes can be treated as a singular function that halts.
> Depends on which AI models you are talking about? When generating content, humans have access to vastly more computational resources than current AI models. To give a really silly example: as a human I can swirl some water around in a bucket and be inspired by the sight. A current AI model does not have the computational resources to simulate the bucket of water (nor does it have a robotic arm and a camera to interact with the real thing instead.)
An AI model does not have computational resources. It's a bunch of numbers. The point is not the actual execution but theoretical computational power if unconstrained by execution environment.
The Church-Turing thesis also presupposes an unlimited amount of time and storage.
Basically, what the brain can do in reasonable amounts of time (eg polynomial time), computers can also do in polynomial time. To make it a thesis something like this might work: "no physically realisable computing machine (including the brain) can do more in polynomial time than BQP already allows" https://en.wikipedia.org/wiki/BQP
If people were claiming that a computer might be able to, but will be to slow, that might be an angle to take, but to date, in these discussions, none of the people arguing that brains can do more have argued that they're just more efficient, but that they inherently have more capabilities, so it's an unnecessarily convoluted argument.
>Humans create new, spontaneous thoughts
I don't believe we do; just look to media, very few plot-lines in Movies/TV are little more than "boy meets girl Pocahontas".
And if you say that a model could not create anything new because of it's static data set but humans could...I disagree with that because us humans are working with a data set that we add to some days, but if we use the example of writing a TV script, the writer draw from their knowledge (gained thru life experience) that is as finite as a model's training set is.
I've made this sort of comment before. Even look to high fantasy; what are elves but humans with different ears? Goblins are just little humans with green skin. Dragons are just big lizards. Minotaurs are just humans but mixed with a bull. We basically create no new ideas - 99% of human "creativity" is just us riffing on things we know of that already exist.
I'd say the incidences of humans having a brand new thought or experience not rooted in something that already exists is very, very low.
Even just asking free chat gpt to make me a fantasy species with some culture and some images of the various things it described does pretty well; https://imgchest.com/p/lqyeapqkk7d. But it's all rooted in existing concepts, same as anything most humans would produce.
The compatibility of determinism and freedom of will is still controversially debated. There is a good chance that Humans don’t „create“.
> There’s no deliberation behind AI, just statistical probabilities. There’s no new or spontaneous thoughts, at most pseudorandomness introduced by the author of the model interface.
You can say exactly the same about deterministic humans since it is often argued that the randomness of thermodynamic or quantum mechanical processes is irrelevant to the question of whether free will is possible. This is justified by the fact that our concept of freedom means a decision that is self-determined by reasons and not a sequence of events determined by chance.
> The compatibility of determinism and freedom of will is still controversially debated. There is a good chance that Humans don’t „create“.
Determinism and free will are pretty irrelevant here.
Unless P=NP, there's no way for us to distinguish in general between eg pseudo random systems and truly random systems from the outside.
Btw, I don't think determinism in humans/AI has anything to do with deliberation.
The newest AI models are allowed to deliberate. At least by some meanings of the word.
> This is justified by the fact that our concept of freedom means a decision that is self-determined by reasons and not a sequence of events determined by chance.
Well, different people have different definitions here. None of them very satisfying.
As far as we can tell, all the laws of the universe are completely deterministic. (And that includes quantum mechanics.) As far as we can tell, human beings obey the laws of physics.
(To explain: quantum mechanics as a theory is completely deterministic and even linear. Some outdated interpretations of quantum mechanics, like Copenhagen, use randomisation. But interpretations don't make a difference to what the underlying theory actually is. And more widely accepted interpretations like 'Many Worlds' preserve the determinism of the underlying theory.)
Btw, neural nets are typically sampled from, and you can use as good a random number generator (even a physical random number generator) as there is, if you want to. I don't think it'll change what we think neural nets are capable of.
That's exactly their point (and mine), with respect to the person above arguing humans unlike AI can create "new things". For that distinction to make sense "new things" must be interpreted as "something that can't be deterministically derived from the current world state", as they're trying to create a distinction between a purely deterministic algorithm and human consciousness.
