Yep. I’d probably be a lot less chastised in some circles for using Claude Code at work if it wasn’t misconstrued as being in support of, I don’t know, encroaching on the hypothetical commissions of a chronically online instagram furry artist or something.
It is very tiring to say “I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains” for the umpteenth time.
I am skeptical of there being sufficient data to build “ethical” training datasets, and I’m confident that much of the same contingent will (somewhat rightfully) argue that ‘second-generation’ copyrighted AI material has already irreversibly made its way into every modern dataset.
> It is very tiring to say “I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains” for the umpteenth time.
That’s not a justification. If a company were poisoning the water to your home as a byproduct, would you be satisfied if they told you “we don’t necessarily disagree with you about polluting the water, but in our field—which you do not understand, and in which the underlying build process is often not the water pollution—what we’re doing presents very real productivity gains”?
> I am skeptical of there being sufficient data to build “ethical” training datasets
Then you don’t build any. What fucked up world we live in where people think it’s OK to be unethical because they want something and can’t think of any other way to do it. What monumentally selfish rotten babies.
> has already irreversibly made its way into every modern dataset
The "gray goo" scenario finally happens... for AI. That's actually the good ending for humanity. I love it! Poetic and believable. Data doesn't "heal" like nature. :D
I think you can train on math /science using synthetic generation to a significant extent. Training for coding requires more of the "scraping github / stackoverflow" angle but IMO that's a shallower hill to climb than scraping copyrighted art and literature.
There are actual models trained on ethical datasets but they are obviously not very high powered. If companies with the resources of an anthropic or openai were doing it (ha) it would be more feasible
>“I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains”
Being able to prove such gains in better products would be a start. And an emphasis on how it assists existing engineers/mathmaticians/researchers, not that any accomplishment made with AI assistance is "AI solves problem".
I don't know whatever happened to "words are cheap". I guess it literally made money to say words, so that adage is false for the time being.
>I am skeptical of there being sufficient data to build “ethical” training datasets
Well if all those scam job ads paying 100/hr to create AI training content was not a scam and instead the approach from the start, there may have been a chance to bridge that gap ethically. The industry chose to break things and is trying to act mad that people are mad at all the broken stuff.
These results are entirely a consequences of the actions chosen. And I don't believe there was ever an honest consideration of there being ethical training datasets. They just thought they could brute force society with fearmongering and bribes. The BOTD was already low in the beginning but completely gone now.
Yeah and it only took stealing all the intellectual output of everyone ever made.
But sure, there's um, an ethical way of doing that?
A reasonable next move, if the US was interested in acting like a democracy, would be legislation forcing this decision:
- prove that you had the rights for all of your training data
- open source the model
Give the labs a 3 month grace period in which to comply, so competition can persist even with dubiously sourced data, but the people can't be locked away from derivatives of their contributions for any significant amount of time.