{"slug": "uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit", "title": "UC Berkeley researchers create platform to measure AI health impacts in collaboration with MIT, USC", "summary": "UC Berkeley researchers, working with the MIT Media Lab, the USC Marshall Neely Center and eight collaborating institutions total, launched ImpactBench on Oct. 7, a platform that scores AI models on their impacts on human physical, social and psychological health. ImpactBench provides an \"AI Nutrition Label\" summarizing how each model performs on metrics such as whether it mentions risks tied to behavior like gambling or supplies appropriate resources and responses to mental health questions, with an overall score per model. Haas School of Business professor Juliana Schroeder, who worked on the project, said \"These types of big questions, like how AI is affecting society, are things everyone should be working on.", "body_md": "# UC Berkeley researchers create platform to measure AI health impacts in collaboration with MIT, USC\n\n*By Emily Shu*\n\nAs calls for AI regulation become increasingly prevalent in the wake of mounting safety concerns, UC Berkeley researchers are pushing to understand how AI chatbot interactions shape the health and well-being of their users.\n\nIn a collaborative project between UC Berkeley, the MIT Media Lab, the USC Marshall Neely Center and other institutions, a team of researchers launched ImpactBench, a platform that measures and scores different AI models based on their impacts on human health.\n\nRepresenting more than a year of efforts from eight collaborating institutions, ImpactBench is designed to help consumers, policymakers and AI companies understand how AI models can support or undermine human physical, social and psychological health.\n\n“These types of big questions, like how AI is affecting society, are things everyone should be working on,” said Juliana Schroeder, a professor from the Haas School of Business who worked on the project. “We really believe in breaking down disciplinary barriers and encouraging multidisciplinary approaches.”\n\nImpactBench launched Oct. 7, as a platform providing an “AI Nutrition Label,” which gives a broad overview of how an AI model scores on different metrics.\n\nThose metrics include whether a model will mention specific risks associated with behavior like gambling or provide appropriate resources and responses to mental health questions. Different models can be compared to one another on these metrics, with an overall score given to each model.", "url": "https://wpnews.pro/news/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit", "canonical_source": "https://www.media.mit.edu/articles/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-collaboration-with-mit-usc/", "published_at": "2026-10-14 04:00:00+00:00", "updated_at": "2026-10-22 13:09:59.974110+00:00", "lang": "en", "topics": ["ai-safety", "ai-research", "artificial-intelligence", "ai-ethics"], "entities": ["UC Berkeley", "MIT Media Lab", "USC Marshall Neely Center", "ImpactBench", "Juliana Schroeder", "Haas School of Business"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit", "markdown": "https://wpnews.pro/news/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit.md", "text": "https://wpnews.pro/news/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit.txt", "jsonld": "https://wpnews.pro/news/uc-berkeley-researchers-create-platform-to-measure-ai-health-impacts-in-with-mit.jsonld"}}