It sounds like transferring an owned print book to digital and using it to train AI was deemed permissable. But downloading a book from the Internet and using it was training data is not allowed, even if you later purchase the pirated book. So, no one will be knocking down your door for scanning your books.

This does raise an interesting case where libraries could end up training and distributing public domain AI models.

You think that 150,000 dollars, or roughly 180 weeks of full time pretax wages at 15$ an hour, is a reasonable fine for making a copy of one book which doe no material harm to the copyright holder?

None of the above. Every professional in the world, including me, owes our careers to looking at examples of other people's work and incorporating their work into our own work without paying a penny for it. Freely copying and imitating what we see around us has been a human norm for thousands of years - in a process known as "the spread of civilization". Relatively recently it was demonized - for purely business reasons, not moral ones - by people who got rich selling copies of other people's work and paying them a pittance known as a "royalty". That little piece of bait on the hook has convinced a lot of people to put a black hat on behavior that had been considered normal forever. If angry modern enlightened justice warriors want to treat a business concept like a moral principle and get all sweaty about it, that's fine with me, but I'm more of a traditionalist in that area.

One point I would refute here is determinism. AI models are, by default, deterministic. They are made from deterministic parts and "any combination of deterministic components will result in a deterministic system". Randomness has to be externally injected into e.g. current LLMs to produce 'non-deterministic' output.

There is the notable exception of newer models like ChatGPT4 which seemingly produces non-deterministic outputs (i.e. give it the same sentence and it produces different outputs even with its temperature set to 0) - but my understanding is this is due to floating point number inaccuracies which lead to different token selection and thus a function of our current processor architectures and not inherent in the model itself.

I've hand calculated forward propagation (neural networks). AI does not learn, its statically optimized. AI "learning" is curve fitting. Human learning requires understanding, which AI is not capable of.

If this is the ruling which causes you to lose trust that any legal system (not just the US') aligns with morality, then I have to question where you've been all this time.

No I don’t, but we’re not talking about a single copy of one book, and it is grovellingly insidious to imply that we are.

We are talking about a company taking the work of an author, of thousands of authors, and using it as the backbone of a machine that’s goal is to make those authors obsolete.

When the people who own the slop-machine are making millions of dollars off the back of stolen works, they can very much afford to pay those authors. If you can’t afford to run your business without STEALING, then your business is a pile of flaming shit that deserves to fail.

Nobody who is mad at this situation thinks that taking inspiration, riffing on, or referencing other people’s work is the problem when a human being does it. When a person writes, there is intention behind it.

The issue is when a business, owned by those people you think ‘demonised’ inspiration, take the works of authors and mulch them into something they lovingly named “The Pile”, in order to create derivative slop off the backs of creatives.

When you, as a “professional”, ask AI to write you a novel, who is being inspired? Who is making the connections between themes? Who is carefully crafting the text to pay loving reference to another authors work? Not you. Not the algorithm that is guessing what word to shit out next based on math.

These businesses have tricked you into thinking that what they are doing is noble.

Human learning requires understanding, which AI is not capable of.

How could anyone know this?

Is there some test of understanding that humans can pass and AIs can't? And if there are humans who can't pass it, do we consider then unintelligent?

We don't even need to set the bar that high. Is there some definition of "understanding" that humans meet and AIs don't?

It's literally in the phrase "statically optimized." This is like arguing for your preferred deity. It'll never be proven but we have evidence to make our own conclusions. As it is now, AI doesn't learn or understand the same way humans do.

So you’re confident that human learning involves “understanding” which is distinct from “statistical optimization”. Is this something you feel in your soul or can you define the difference?

I'll repeat what you said with emphasis:

AI can “learn” from and “read” a book in the same way a person can and does

The emphasized part is incorrect. It's not the same, yet your argument seems to be that because (your claim) it is the same, then it's no different from a human reading all of these books.

Regarding your last point, copyright law doesn't just kick in because you try to pass something off as an original (by, for ex, marketing a book as being from a best selling author). It applies based on similarity whether you mention the original author or not.

If you want to go to the extreme: delete first copy.

You can; as I understand it, the only legal requirement is that you only use one copy at a time.

ie. I can give my book to a friend after I'm done reading it; I can make a copy of a book and keep them at home and at the office and switch off between reading them; I'm not allowed to make a copy of the book hand one to a friend and then both of us read it at the same time.

Yes. You learned not to touch a hot stove either from experience or a warning. That fear was immortalized by your understanding that it would hurt. An AI will tell you not to touch a hot stove (most of the time) because the words "hot" "stove" "pain" etc... pop up in its dataset together millions of times. As things are, they're barely comparable. The only reason people keep arguing is because the output is very convincing. Go and download pytorch and read some stuff, or Google it. I've even asked deepseek for you:

Can AI learn and understand like people?

AI can learn and perform many tasks similarly to humans, but its understanding is fundamentally different. Here’s how AI compares to human learning and understanding:

1. Learning: Similar in Some Ways, Different in Others

• AI Learns from Data: AI (especially deep learning models) improves by processing vast amounts of data, identifying patterns, and adjusting its internal parameters.
• Humans Learn More Efficiently: Humans can generalize from few examples, use reasoning, and apply knowledge across different contexts—something AI struggles with unless trained extensively.

2. Understanding: AI vs. Human Cognition

• AI "Understands" Statistically: AI recognizes patterns and makes predictions based on probabilities, but it lacks true comprehension, consciousness, or awareness.
• Humans Understand Semantically: Humans grasp meaning, context, emotions, and abstract concepts in a way AI cannot (yet).

3. Strengths & Weaknesses

AI Excels At:

• Processing huge datasets quickly.
• Recognizing patterns (e.g., images, speech).
• Automating repetitive tasks.

AI Falls Short At:

• Common-sense reasoning (e.g., knowing ice melts when heated without being explicitly told).
• Emotional intelligence (e.g., empathy, humor).
• Creativity and abstract thinking (though AI can mimic it).

4. Current AI (Like ChatGPT) is a "Stochastic Parrot"

• It generates plausible responses based on training but doesn’t truly "know" what it’s saying.
• Unlike humans, it doesn’t have beliefs, desires, or self-awareness.

5. Future Possibilities (AGI)

• Artificial General Intelligence (AGI)—a hypothetical AI with human-like reasoning—could bridge this gap, but we’re not there yet.

Conclusion:

AI can simulate learning and understanding impressively, but it doesn’t experience them like humans do. It’s a powerful tool, not a mind.

Would you like examples of where AI mimics vs. truly understands?