A human cannot learn from and re/produce work they view at the speed, volume, and scale that “AI” does, nor can that human be infinitely replicated and farmed out. When describing this gap in capabilities, or the consequences of “learning”, “orders of magnitude” would be a comical understatement.

Existing conventions around “learning” are built on assumptions of human scale, and the expected consequences thereof.

I can’t understand why one would expect people to go “oh it’s technically ‘learning’ I guess I’ll ignore all the consequences that weren’t present when it was just humans”.

That's completely subjective. What you describe is a spectrum. If that were true, thesis' would not have to be run through plagiarism scans (they are), and there would be no copyright lawsuits for familiarity such as Ed Sheeran's Marvin Gaye lawsuit.

It's also important to note these laws were always intended to strike a fair balance between the copyright owner and the good of society as a whole. Copyright is not an end in itself.

This is such an important point that I think escapes a lot of people, both on the pro-AI and anti-AI side.

Although everyone probably wishes otherwise, there isn't really a hard objective line for determining if something is infringing or not. And that's actually a good thing! But it means that, in the end, it's up to a judge to weigh a bunch of different, rather fuzzy, factors.

Law is not a static entity, it's morphing and evolving to suit our ideals today. Learning wasn't an issue until it is.

We could very well distinguish between machine learning and human learning although they're no different from each other in principle.

And although, we can't say that ML is plagiarism, at scale it breaches our other moral principles like privacy and individual identity.

Let's say in 10 years from now Google'll train ML on (close to) all the data available in the world, be it text, visual or audio. Would they be able to prompt this AI: "You are George Wilkinson from Colorado ** st. 23". How close will it be from real George on whose data it was trained on?

We can't tune our human learning to this level of precision, but it is only a matter of time for the machine.

The situation you describe is exactly that which has already existed for the last two decades with Google using that data for their search engine. If it's public it can be read.

Public book libraries have been free to read since centuries, and yet no single human has ever read even 1% of them. We can't ignore that different scales = different consequences. (and to put them together the authors were paid)

So what are these "consequences" you keep referring to?

Wow. It’s like the printing press! Reproduction has hit the next jump in scale point

This is a great analogy.

A human cannot perform arithmetic at the speed, volume, and scale that “computation” does, nor can that human be infinitely replicated and farmed out. When describing this gap in capabilities, or the consequences of “mathematics”, “orders of magnitude” would be a comical understatement. Existing conventions around “ariithmetic” are built on assumptions of human scale, and the expected consequences thereof. I can’t understand why one would expect people to go “oh it’s technically ‘math’ I guess I’ll ignore all the consequences that weren’t present when it was just humans doing the mathematical operations”.

Yet we have not banned the calculator but accept it empowers even people who did not spent time in school to learn math.

Do you actually think that as a society we don't view maths differently after the computer?

We absolutely do, and expectations of what's possible are completely different.

It's a good thing, but at the moment language copyrights is wielded by corporations and ignored by corporations. Either we make copyrights like maths and discard them, or we hold corporation's to the same standards that they hold us to.

Do you really think that of I train my model on Mickey Mouse and then go ahead and generate "not Mickey" that Disney won't try and sue the crap out of me? Almost all these complaints boil down to different standards for them versus us.