Project Grant 2203212

Award Date 2/1/22
Completion Date 1/31/24
Dollars Obligated $285K
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Boston, MA 02115, USA
Similar Awards
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) for $446,473 provides funding to Northeastern University to develop AI-enhanced digital tools to support online freelance workers. The project aims to create prototypes that help freelancers better manage their profiles, workloads, and task performance within online labor markets, which often have policies and algorithms that disadvantage workers. Over a 4-year period,...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $468,760 to Northeastern University to design new tools that enable gig knowledge workers to collectively address workplace challenges. The research aims to 1) develop methods for workers to collect and analyze job, wage, and employer data as a group, 2) create collaborative tools to help workers identify shared issues and develop solutions,...
This Project Grant award, valued at $465,495, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The goal of this 4-year research project, awarded to Syracuse University, is to create AI-enhanced digital tools to empower online freelance workers. The research team will collaborate with online freelancers to develop and evaluate prototype tools that can help these workers better manage their...
The National Science Foundation (NSF) awarded a $279,235 Project Grant under the CISE (Computer and Information Science and Engineering) program (CFDA 47.070) to Skidmore College in Saratoga Springs, NY. The goal of this 4-year research project is to create AI-enhanced digital tools that empower online freelance workers to better manage their professional profiles, workload, and task performance in online labor markets. The project team will collaborate with online freelancers to develop and...
This National Science Foundation (NSF) CAREER award, under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program, provides $242,907 in funding to Syracuse University from June 1, 2025 to May 31, 2030. The project investigates the impact of generative artificial intelligence on worker productivity, job satisfaction, and skill development in the American workforce. The research consists of three interconnected studies: 1) a two-wave panel survey of 1,500 workers to analyze...
This National Science Foundation (NSF) Division of Social and Economic Science award, under the CFDA 47.075 Social, Behavioral, and Economic Sciences program, provides $503,800 to the University of Michigan to research using artificial intelligence (AI) and machine learning to improve job matching for low-skilled workers displaced by the COVID-19 pandemic. The 2-year project will use a randomized controlled trial to evaluate whether AI-assisted algorithmic matching of jobseeker skills and...
This $599,974 Project Grant was awarded by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Arizona (Tucson, AZ). The purpose of this 3-year award is to leverage big data and machine learning to improve the efficiency and efficacy of online labor markets (OLMs). The project will focus on three key aims: 1) developing novel technical solutions for...
This Project Grant award from the National Science Foundation (NSF) under the CFDA 47.084 Technology, Innovation, and Partnerships (TIP) program provides $300,000 in funding to Carnegie Mellon University. The project aims to develop and improve methods for evaluating the potential workforce readiness of regional labor markets to meet skill demands created by large-scale industrial transitions and technological change. Key deliverables include an empirically validated user-tool that estimates the...
This $150,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a collaborative research effort between Oakland University and Worcester Polytechnic Institute. The project aims to increase awareness and promote broader adoption of the National AI Research Resource (NAIRR) pilot. It will organize two 12-workshop series over two years, providing hands-on training for emerging researchers to...
This $298,882 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund a collaboration led by the University of Wyoming, in partnership with the Computing Research Association, Loyola University of Chicago, and the College of Charleston. The goal is to increase Artificial Intelligence (AI) education capacity and community at research-emerging institutions with small-to-medium computing programs. The project will...

This $284,971 project grant from the National Science Foundation's Office of Emerging Frontiers and Multidisciplinary Activities, under the Engineering program (CFDA 47.041), will support research and development of methods to transition marginalized rural and urban digital workers into higher-skilled, creative digital jobs. A team from Northeastern University, Carnegie Mellon University, West Virginia University, Pennsylvania State University, and the University of Pennsylvania will collaborate with rural and urban partners to provide training to workers. Workers will be scaffolded through basic computer fluency, working with AI tools, and finally innovation and creativity skills while earning money performing progressively advanced digital work. The goal is to develop sustainable models for workers to build skills in crowd work that is unlikely to be automated, through collaboration with AI to both improve work outcomes and enable skill development. Outcomes have the potential to advance research at the human-AI frontier and lay a foundation for the future of crowd work.

Generated 1/6/24, 2:26 PM