Unfortunately, you pretty much have to specify a specific time and place for it to be actionable. These guys are very familiar with how those laws work and know exactly how to avoid getting caught by them.

Upvoting your own material is a Michael Scott thing to do.\

- PabloDiscobar

- Michael Scott

If what you're going to give me is an oversimplified analogy that puts too much faith in what AI devs are trying to sell and not enough faith in what a human brain is doing, then don't bother because I will dismiss it as a fairy tale.

I'm curious, how do you feel about global warming? Do you pick and choose the scientists you listen to? You know that the people who develop these AIs are computer scientists and researchers, right?

If you're a global warming denier, at least you're consistent. But if out of one side of you're mouth you're calling what AI researchers talk about a "fairy tail", and out of the other side of your mouth you're criticizing other people for ignoring science when it suits them, then maybe you need to take time for introspection.

You can stop reading here. The rest of this is for people who are actually curious, and you've clearly made up your mind. Until you've actually learned a bit about how they actually work, though, you have absolutely no business opining about how policies ought to apply to them, because your views are rooted in misconceptions.

In any case, curious folks, I'm sure there are fancy flowcharts around about how data flows through the human brain as well. The human brain is arranged in groups of neurons that feed back into each other, where as an AI neural network is arranged in more ordered layers. There structure isn't precisely the same. Notably, an AI (at least, as they are commonly structured right now) doesn't experience "time" per se, because once it's been trained its neural connections don't change anymore. As it turns out, consciousness isn't necessary for learning and reasoning as the parent comment seems to think.

Human brains and neural networks are similar in the way that I explained in my original comment -- neither of them store a database, neither of them do statistical analysis or take averages, and both learn concepts by making modifications to their neural connections (a human does this all the time, whereas an AI does this only while it's being trained). The actual neural network in the above diagram that OP googled and pasted in here lives in the "feed forward" boxes. That's where the actual reasoning and learning is being done. As this particular diagram is a diagram of the entire system and not a diagram of the layers of the feed-forward network, it's not even the right diagram to be comparing to the human brain (although again, the structures wouldn't match up exactly).

Except an AI is not taking inspiration, it's compiling information to determine mathematical averages.

The AIs we're talking about are neural networks. They don't do statistics, they don't have databases, and they don't take mathematical averages. They simulate neurons, and their ability to learn concepts is emergent from that, the same way the human brain is. Nothing about an artificial neuron ever takes an average of anything, reads any database, or does any statistical calculations. If an artificial neural network can be said to be doing those things, then so is the human brain.

There is nothing magical about how human neurons work. Researchers are already growing small networks out of animal neurons and using them the same way that we use artificial neural networks.

There are a lot of "how AI works" articles in there that put things in layman's terms (and use phrases like "statistical analysis" and "mathematical averages", and unfortunately people (including many very smart people) extrapolate from the incorrect information in those articles and end up making bad assumptions about how AI actually works.

A human being is paid for the work they do, an AI program's creator is paid for the work it did. And if that creator used copyrighted work, then he should be having to get permission to use it, because he's profitting off this AI program.

If an artist uses a copyrighted work on their mood board or as inspiration, then they should pay for that, because they're making a profit from that copyrighted work. Human beings should, as you said, be paid for the work they do. Right? If an artist goes to art school, they should pay all of the artists whose work they learned from, right? If a teacher teaches children in a class, that teacher should be paid a royalty each time those children make use of the knowledge they were taught, right? (I sense a sidetrack -- yes, teachers are horribly underpaid and we desperately need to fix that, so please don't misconstrue that previous sentence.)

There's a reason we don't copyright facts, styles, and concepts.

Oh, and if you want to talk about something that stores an actual database of scraped data, makes mathematical and statistical inferences, and reproduces things exactly, look no further than Google. It's already been determined in court that what Google does is fair use.

AI is more than just ChatGPT.

When we talk about reinterpreting copyright law in a way that makes AI training essentially illegal for anything useful, it also restricts smaller and potentially more focused networks. They're discovering that smaller networks can perform very well (not at the level of GPT-4, but well enough to be useful) if they're trained in a specific way where reasoning steps are spelled out in the training.

Also, there are used nvidia cards currently selling on Amazon for under $300 with 24 gigs of ram and AI performance almost equal to a 3090, which puts group-of-experts models like a smaller version of GPT-4 within reach of people who aren't ultra-wealthy.

There's also the fact that there are plenty of companies currently working on hardware that will make AI significantly cheaper and more accessible to home users. Systems like ChatGPT aren't always going to be restricted to giant data centers, unless (as some people really want) laws are passed to prevent that hardware from being sold to regular people.

Losing their life because an AI has been improperly placed in a decision making position because it was sold as having more capabilities than it actually has.

I would tend to agree with you on this one, although we don't need bad copyright legislation to deal with it, since laws can deal with it more directly. I would personally put in place an organization that requires rigorous proof that AI in those roles is significantly safer than a human, like the FDA does for medication.

As for the average person who has the computer hardware and time to train an AI (bear in mind Google Bard and Open AI use human contractors to correct misinformation in the answers as well as scanning), there is a ton of public domain writing out there.

Corporations would love if regular people were only allowed to train their AIs on things that are 75 years out of date. Creative interpretations of copyright law aren't going to stop billion- and trillion-dollar companies from licensing things to train AI on, either by paying a tiny percentage of their war chests or just ignoring the law altogether the way Meta always does, and getting a customary slap on the wrist. What will end up happening is that Meta, Alphabet, Microsoft, Elon Musk and his companies, government organizations, etc. will all have access to AIs that know current, useful, and relevant things, and the rest of us will not, or we'll have to pay monthly for the privilege of access to a limited version of that knowledge, further enriching those groups.

Furthermore, if they're using people's creativity to make a product, it's just WRONG not to have permission or to not credit them.

Let's talk about Stable Diffusion for a moment. Stable Diffusion models can be compressed down to about 2 gigabytes and still produce art. Stable Diffusion was trained on 5 billion images and finetuned on a subset of 600 million images, which means that the average image contributes 2B/600M, or a little bit over three bytes, to the final dataset. With the exception of a few mostly public domain images that appeared in the dataset hundreds of times, Stable Diffusion learned broad concepts from large numbers of images, similarly to how a human artist would learn art concepts. If people need permission to learn a teeny bit of information from each image (3 bytes of information isn't copyrightable, btw), then artists should have to get permission for every single image they put on their mood boards or use for inspiration, because they're taking orders of magnitude more than three bytes of information from each image they use for inspiration on a given work.

Why do you think people will build data centers in Europe when they can build them elsewhere?

For something to be a fact, it needs to actually be true. AI is currently accessible to everyone.

Wow, you have this all planned out, don't you?

If that's what Europe is like, they'll build their data centers somewhere else. Like the corrupt USA. Again, you'll be taking away your access to AI, not theirs.

I'm not sure what you're getting at with this. It will only be a privilege for these groups of we choose to artificially make it that way. And why would you want to do that?

Do you want to give AI exclusively to the rich? If so, why?

The end result is going to be basically the same regardless. Plenty of people (such as myself) who believe in the huge potential of AI to give creative power to regular people will volunteer our voices. Giving that creative power to everyone is worth far more, in my opinion, than gatekeeping the creation of art.

Unless they're planning on making it illegal for a computer to imitate any human voice, I don't see where making a law against using a voice without consent would make a big substantive difference. Just re-voice the existing lines in Skyrim with new voices to maintain consistency and you're good (there's a Serana mod that already does this, for instance).

Unfortunately, the courts and legislatures may craft their opinions and laws, respectively, without knowing how machine learning actually works.