A University of Minnesota Twin Cities-led team is leading a new $2 million National Science Foundation (NSF) project aimed at developing a system to help researchers better study AI-powered news recommender systems.
The project is part of a $16.1 million NSF’s Computer and Information Science and Engineering Community Research Infrastructure (CCRI) program investment to support shared research infrastructure that provides artificial intelligence researchers and students across the nation with access to transformative resources including high-quality data on human-machine interactions in the context of collaborative teams, automated driving, and news recommendation. The University of Minnesota Twin Cities is one of only five institutions leading collaborative projects supported by the NSF CCRI investment.
The University of Minnesota-led project aims to develop a shared news recommender system that will enable researchers nationwide to carry out live one-time and longitudinal experiences on users of AI systems that personalize the news-reading experience.
“The University of Minnesota has been a leader in recommender systems research for decades because we’ve had the ability to run live experiments when many others were limited to simulating systems using collected datasets,” said Joe Konstan, the project’s lead investigator and a Distinguished McKnight University Professor in the University of Minnesota Department of Computer Science & Engineering. “This is our chance to bring the power of experimentation to the broader human-centered AI research community.”
Konstan leads a team of accomplished experimental researchers with extensive experience both in AI recommender systems and with human-centered research—including issues of research ethics, privacy, and consent. They will also bring together an advisory board of researchers, news experts, and ethics experts to help guide the development and operation of this infrastructure and associated use guidelines.
This research grows out of Konstan’s 25-year history of leading MovieLens, an experimental news recommender system project that has had hundreds of thousands of users and has been used for more than a hundred experiments.
Recommender systems have extraordinarily broad impact through, for example, the products ranked and shown to an online shopper based on past shopping behaviors. Recommender systems are also behind most online news sources, and can shape which news people see. Given the importance of these systems, it is critical for researchers to be able to carry out studies to evaluate different design choices and their impact on users.
This project will be conducted in collaboration with Clemson University, Boise State University, Northwestern University, and the University of Colorado Boulder.
“A critical element to the success of the AI research revolution is ensuring that researchers have access to the data and platforms required to continue to drive innovation and scalability in AI technologies and systems,” said NSF Director Sethuraman Panchanathan. “This infrastructure must be accessible to a full breadth and diversity of talent interested in AI research and development, as that is the driving force behind modern discoveries.”
The other collaborative projects awarded grants by NSF’s CCRI program are led by the University of Central Florida; the University of Pennsylvania; the University of California Los Angeles; and Pennsylvania State University.
