Aug. 9, 2022 — Artificial intelligence and machine learning evolve fast. It is crucial that artificial intelligence and machine learning systems be accountable, fair, inclusive and transparent. The U.S. National Science Foundation has been a leader in providing infrastructure, guidance and support for ethically developed and deployed artificial intelligence and machine learning systems.
“These awards are part of NSF’s commitment to pursue scientific discoveries that enable us to achieve the full spectrum of artificial intelligence potential at the same time we address critical questions about their uses and impacts,” said Wendy Nilsen, deputy division director for NSF’s Information and Intelligent Systems Division.
As part of that commitment, NSF, in collaboration with Amazon, announced the 2022 recipients of the Program on Fairness in Artificial Intelligence in Collaboration with Amazon awards. The 2022 awardees will receive up to $9.5 million in financial support. The teams have planned projects that involve rooting out unfairness and bias in artificial intelligence and machine learning technologies, developing principles for human interaction with artificial intelligence systems, theoretical frameworks for algorithms, and improving speech recognition technology so that it is accessible to broader populations.
“The rapidly changing technological landscape and societal needs of artificial intelligence users call for a deeper understanding of the impact of artificial intelligence technology and systems on behaviors and applications. A comprehensive approach to research and development investments that unleashes innovation in technologies support use-inspired outcomes,” said NSF Program Director Todd Leen. The program emphasis on societal needs and impacts is reflected in awards to teams that include social scientists along with artificial intelligence experts.
The 2022 Program on Fairness in Artificial Intelligence in Collaboration with Amazon awardees are listed below:
An Interpretable AI Framework for Care of Critically Ill Patients Involving Matching and Decision Trees, Duke University
Fair Representation Learning: Fundamental Trade-Offs and Algorithms, Michigan State University
A New Paradigm for the Evaluation and Training of Inclusive Automatic Speech Recognition, University of Illinois Urbana-Champaign
A Normative Economic Approach to Fairness in AI, Harvard University
Advancing Optimization for Threshold-Agnostic Fair AI Systems, University of Iowa
Toward Fair Decision Making and Resource Allocation with Application to AI-Assisted Graduate Admissions and Degree Completion, University of Maryland, College Park
BRIMI – Bias Reduction in Medical Information, University of Connecticut
A novel paradigm for fairness-aware deep learning models on data streams, University of Texas at Dallas
Human-Centered Approach to Developing Accessible and Reliable Machine Translation, University of Maryland, College Park
AI Algorithms for Fair Auctions, Pricing, and Marketing, Columbia University
Using Explainable AI to Increase Equity and Transparency in the Juvenile Justice System’s Use of Risk Scores, Bowling Green State University
Breaking the Tradeoff Barrier in Algorithmic Fairness, University of Pennsylvania
Advancing Deep Learning Towards Spatial Fairness, University of Pittsburgh
Visit the NSF awards page to see a list of awards from all three years of the program and learn about the NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon.