Readers of texts created to use the styles of famous authors prefer works written by AI to 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 emulate the style of human writers.

Stony Brook University researcher Sima Mofakham develops SeeMe, an AI tool that detects subtle facial movements to spot consciousness in brain-injured patients up to four days earlier than doctors. Non-invasive and low-cost, it could be scaled for widespread hospital use and paired with therapies to improve recovery. The program provides an extra layer of insight to guide treatment and support families without replacing clinical judgment.

State University of New York Chancellor John B. King Jr. today announced the inaugural class of SUNY's AI for the Public Good Fellows. The 20 SUNY faculty and staff fellows are experts in their fields of study – ranging from health sciences to sustainable resources management to English.