This $349,667 Project Grant was awarded by the National Science Foundation (NSF) Division of Social, Behavioral, and Economic Sciences (CFDA 47.075) to the National Center for State Courts (NCSC). This 3-year project, beginning July 1, 2024, aims to examine the potential impacts of artificial intelligence (AI) integration in state court operations. The key products and services to be delivered under this award include: 1) Mapping the state court workforce using a multi-team systems approach to...
This $200,000 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program will fund research at Bowling Green State University to increase equity and transparency in juvenile justice risk assessment scores. The researchers will develop automated, interpretable machine learning explanations for juvenile risk scores currently generated through a proprietary algorithm. They will test if these more transparent scores help youth and decision-makers...
The National Science Foundation Office of Emerging Frontiers and Multidisciplinary Activities awarded a $2,000,000 Project Grant to the Regents of the University of California, doing business as the University of California, Berkeley, to support the Human-Machine Teaming for Effective Data Work at Scale: Upskilling Defense Lawyers Working with Police and Court Process Data project. The funding period is from October 1, 2021 to September 30, 2024. The grant will support research and development...
The National Center for State Courts received a $149,962 project grant award from the National Science Foundation Office of Emerging Frontiers and Multidisciplinary Activities on October 1, 2021 to study the impacts of artificial intelligence and remote conferencing on work practices and equity in state courts. The grant is part of the Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education in computing,...
This $150,000 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program will fund research to develop impact-aware machine learning models for risk assessment in juvenile justice systems. The University of Arizona will design a framework that incorporates the effects of interventions on recidivism risk while achieving individual fairness and data privacy. The researchers will adapt potential outcomes frameworks from causal inference to build models...
This $166,500 Project Grant was awarded by the National Institute of Justice (NIJ) under the National Institute of Justice Research, Evaluation, and Development Project Grants program (CFDA 16.560). The purpose of the grant is to conduct research examining the intersection of legal and technical concepts of fairness in artificial intelligence (AI) used for criminal risk assessment, with a focus on recidivism prediction models. The key research questions include: 1) At which technical stage of...
The National Science Foundation (NSF) awarded a $174,200 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) program to the University of North Carolina at Chapel Hill (UNC-CH) to develop new resource allocation policies for optimizing the scheduling of parallelizable machine learning (ML) training workloads on shared hardware clusters. The goal is to enable the rapid and efficient training of highly accurate ML models using limited computing resources. This...
The National Science Foundation (NSF) awarded a $1,182,881 Project Grant to the University of California, San Diego (UCSD) under the NSF's Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of new methods to ensure that machine learning models assigned to decisions such as lending and hiring can be changed through individual actions, protecting the right to access these services. The project will create techniques for (1) detecting...
This $325,925 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at the University of Houston System to develop computational methods for addressing data challenges and enhancing fairness in machine learning models. The key research objectives are to: 1) explore and extract data characteristics to assess fairness, 2) expand and refine prior knowledge to guide the...
This $625,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research into end-to-end fairness for algorithm-in-the-loop decision making in the public sector. New York University will lead the development of novel methods for identifying and correcting biases in massive, multivariate data used for algorithmic decision making. This will include building models to represent human decision making processes, auditing tools to...