Readers of texts created to use the styles of famous authors prefer works written by AI to human human-written imitations, but only after developers fine-tune AI models to understand an author’s output.

This finding, academics argue, means the courts need to rethink assumptions about allowing AI training on authors' works as a fair use exception to copyright liability.

In a preprint paper titled "Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers," Tuhin Chakrabarty, assistant professor of computer science at Stony Brook University, Jane C. Ginsburg, professor of law at Columbia University, and Paramveer Dhillon, associate professor in the School of Information at the University of Michigan, describe how they assessed the impact of AI models that can emul

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