As the use of artificial intelligence tools in healthcare increases at a dramatic rate, the conversation about usage has focused on efficiency and innovation. But in a new article published in Nature Mental Health, Stony Brook University’s Briana Last argues that a more pressing question has been largely overlooked: who gets to decide how AI is used in mental healthcare, and in whose interests are those decisions made?
Ann Kirschner writes, "Colleges and universities are a public good—or we’re supposed to be. While the challenge is real, so is the price of paralysis. AI won’t wait for anyone’s permission to reshape learning and work. The question isn't whether we'll change—it's whether we'll be relevant when we do. That 'A' in AI? It can still stand for anxiety. Better if it stands for action. The choice, for now, is still ours."
The United States Army has awarded a Small Business Innovation Research (SBIR) contract to enterprise browser developer HERE to build an artificial intelligence–based data interoperability layer for Army command-and-control systems. The project will be carried out in partnership with Stony Brook University, involving Dr. Manoj D. Mahajan, director of special programs at CEWIT, and Dr. Pawel Polak of Stony Brook’s AMS department.
Jove Equities CEO David Calone gives his insight on how AI and biotech will continue to impact Long Island.
AI’s ability to copy an author’s writing style isn’t just about how advanced the technology is—it’s about how people use it. And the way it’s used could have major effects on creativity, jobs, and even the law.
Stony Brook University, in partnership with Redshred, has been awarded a Phase I Small Business Technology Transfer (STTR) contract from the Defense Threat Reduction Agency (DTRA) to develop the Radiation AI Decision and Information Assistant for Nuclear Tasks (RADIANT).
This innovative AI-powered platform is designed to support military operations and nuclear safety through real-time, data-driven radiation guidance.
If economic and technological transformations have changed our relationship with literature before, they could do so again.
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and maintenance costs.
Researchers at Stony Brook University and Columbia Law School found that AI models fine-tuned on a specific author produce texts that readers rate as more stylistically accurate and higher in quality than those written by professional imitators, regardless of the author's publication history.
