Data Poisoning could be a tool we use to identify AI that has used copyritten material, or we use it to mess with AI.
https://www.vice.com/en/article/infinite-ai-homer-simpson-cover-songs-poisoned-soulseek/
https://mosis.eecs.utk.edu/harmonycloak.html
https://mosis.eecs.utk.edu/publications/meerza2024harmonycloak.pdf
Traditionally, with machine learning, it is standard practice to mention what datasets and/or pretrains were used, so that the results are transparent and can be replicated. With GPT-2, it was “the common crawl and our own crawled 8 million web pages”, and since then I feel it’s mostly left out, falling back on (easily manipulated) benchmarks instead 😬
Yep. But just providing a list of millions of URLs and saying “we trained on this” as some models in the past have done also didn’t make it possible to replicate; by the time anyone re-fetches them all, many of the URLs will inevitably have changed or disappeared.
That’s exactly why projects like the common crawl exist though !