MIT study finds AI attribution fails at scale

MIT CSAIL researchers found that as diffusion models train on more data, individual training images become unattributable to outputs, a phenomenon called attribution decay. Removing any single image, artist, or person often leaves generated samples unchanged, complicating copyright and fair use questions.