By Emily Shu
As 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.
In 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.
Representing 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.
“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.”
ImpactBench 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.
Those 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.