I'm not sure exactly where I land on this, but I think it's important to consider that restricting the data companies can train on could influence the architectures they use. Self-supervised autoregressive models a-la GPT-3 seem a lot more benign than full-fledged RL agents. The latter is a lot less data hungry than the former (especially in terms of copyrighted data). There are enough other factors here to not make me completely confident in this analysis, but it's worth thinking about.
I'm not a lawyer and this is not legal advice, but I think the current US legal framework isn't going to work to challenge training on publicly available data.
One argument that something is fair use is that it is transformative [1]. And taking an image or text and using it to slightly influence a giant matrix of numbers, in such a way that the original is not recoverable, and which allows new kinds of expression, seems likely to count as transformative.
So if you think that restricting access to public data for training purposes is a promising approach [2], you should probably focus on trying to create a new regulatory framework.
Having said that, this is all US analysis. Other countries have other frameworks and may not have exact analogs of fair use. Perhaps in the EU legal challenges are more viable.
[1] https://www.nolo.com/legal-encyclopedia/fair-use-what-transformative.html
[2] You should think about what the side effects would be like. For instance, this will advantage giant companies that can pay to license or create data, and places that have low respect for law. Whether that's desirable is worth thinking through.
It's already happening https://githubcopilotinvestigation.com/ (which I've learned yesterday from is-github-copilot-in-legal-trouble post)
I think it would be interesting plot twist: humanity saved from AI FOOM by the big IT companies having to obey intellectual property rights they themselves defended for so many years :)
If you want to ban or monopolize such models, push for that directly. Indirectly banning them is evil.
They're already illegal. GPT-3 is based in large part on what appear to be pirated books. (I wonder if google's models are covered by its settlements with publishers.)
Yes but only because I want to make sure that anyone who runs a copy of my soul gets a license for it from me first. it's not going to slow down capabilities except differentially moving capabilities to other groups.
Too late. Much too late. Bird has flown the coop. No use shutting the barn doors after the cows have run away. Also, since the majority of the training data is just 'the internet', you can't get rid of this except by monitoring everyone's use of the internet to make sure they aren't making webscrapes for the purpose of later training an AI on that data. If all you do is cause some bureaucratic hassle for US companies, you give an edge to non-US groups and probably also encourage US groups to go elsewhere.
We frequently speak about AI capability gain being bad because it shortens the timeframe for AI safety research. In that logic, taking steps to decrease AI capability would be worthwhile.
At the moment the large language models are trained with a lot of data without the company, that trains the language model, licensing the data. If there would be a requirement to license the required data, that would severely reduce the available data for language models and reduce their capabilities.
It's expensive to fight lawsuits in the United States. Currently, there are artists who feel like their rights are violated by Dalle 2 using their art as training data. Similar to how Thiel funded the Gawker lawsuits, it would be possible to support artists in a suit against OpenAI to require OpenAI to license images for training Dalle 2. If such a lawsuit is well-funded it will be much more likely that a precedent for requiring data licensing gets set which would slow down AI development.
I'm curious about what people who think more about AI safety than myself think about such a move. Would it be helpful?