Can Copyright be Reduced to Privacy?

arXiv:2305.14822v2 Announce Type: replace-cross
Abstract: There is a growing concern that generative AI models will generate outputs closely resembling the copyrighted materials for which they are trained. This worry has intensified as the quality and complexity of generative models have immensely improved, and the availability of extensive datasets containing copyrighted material has expanded. Researchers are actively exploring strategies to mitigate the risk of generating infringing samples, with a recent line of work suggesting to employ techniques such as differential privacy …

ai models arxiv availability can complexity copyright cs.cr cs.lg datasets generative generative ai generative models material materials privacy quality researchers