As millions turn to ChatGPT and other AI chatbots for therapy-style advice, new research from Brown University raises a serious red flag: even when instructed to act like trained therapists, these systems routinely break core ethical standards of mental health care. In side-by-side evaluations with peer counselors and licensed psychologists, researchers uncovered 15 distinct ethical risks — from mishandling crisis situations and reinforcing harmful beliefs to showing biased responses and offering “deceptive empathy” that mimics care without real understanding.
Researchers tested whether generative AI could handle complex medical datasets as well as human experts. In some cases, the AI matched or outperformed teams that had spent months building prediction models. By generating usable analytical code from precise prompts, the systems dramatically reduced the time needed to process health data. The findings hint at a future where AI helps scientists move faster from data to discovery.
Researchers have turned artificial intelligence into a powerful new lens for understanding why cancer survival rates differ so dramatically around the world. By analyzing cancer data and health system information from 185 countries, the AI model highlights which factors, such as access to radiotherapy, universal health coverage, and economic strength, are most closely linked to better survival in each nation.
Stanford researchers have developed an AI that can predict future disease risk using data from just one night of sleep. The system analyzes detailed physiological signals, looking for hidden patterns across the brain, heart, and breathing. It successfully forecast risks for conditions like cancer, dementia, and heart disease. The results suggest sleep contains early health warnings doctors have largely overlooked.
Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests on medical and health data showed it often outperforms classic approaches. The discovery could reshape how scientists make reliable forecasts.
HydroSpread, a breakthrough fabrication method, lets scientists build ultrathin soft robots directly on water. These tiny, insect-inspired machines could transform robotics, healthcare, and environmental monitoring.
Scientists at Mount Sinai have created an artificial intelligence system that can predict how likely rare genetic mutations are to actually cause disease. By combining machine learning with millions of electronic health records and routine lab tests like cholesterol or kidney function, the system produces "ML penetrance" scores that place genetic risk on a spectrum rather than a simple yes/no. Some variants once thought dangerous showed little real-world impact, while others previously labeled uncertain revealed strong disease links.