RAISE: C-Accel Pilot- Track B1 (AI and Future Jobs): Unlocking the Power of Data and Science to Empower American Workers
Project Outcomes Statement
In the field of Economics, this project developed new estimations for the Return-on-Investment to labor training programs using Causal Machine Learning (CML) and state administrative data that had never been used before. We found significant heterogeneity in training program effectiveness, suggesting room for policy improvement by contracting with providers with pay-for-performance capital, and giving clear information on the value-added of training programs to individuals when making a decision about enrolling in a training program. The combination of workers selecting training programs with high returns, performance contracting, and a technological platform to support policymakers in owning and operating the solution moving forward will incentivize a virtuous cycle of training program improvement and effective reskilling for American workers.
In the field of Computer Science, this project developed a new open-source, cloud-based research architecture for governments to unlock administrative data for policy insights. The Research Data Lake (RDL) system built through this project is flexible and extensible, empowering government to meet needs in crisis and innovate to improve. A recent example includes the COVID-19 Pandemic Unemployment Insurance (PUA) Claims system that our team deployed in partnership with Rhode Island, which delivered critical benefits to tens of thousands of Rhode Islanders in 2020. Because we had already launched an RDL with RI, we were able to spin up a PUA system within 10 days, which enabled RI to successfully and seamlessly handle the surge of UI claims from the COVID-19 shutdown and CARES Act UI expansion. It served as a proof point as to how the RDL model can be coupled with a user interface to deliver and collect program eligibility/application information, and how the science-as-service module can support validation of program data without needing to exchange PII. This solution made Rhode Island the first state in the nation to pay PUA claims, and provided immediate technological help for families in crisis due to the economic shutdown from the pandemic. The RDL system is now being employed by several state partners to improve public policy decisions, including the Hawai’i Department of Labor and Industrial Relations and the New Jersey Department of Labor.
In the field of Public Policy, this project developed a new technological platform for governments to use administrative data, CML, and Artificial Intelligence (AI) to connect jobseekers to high-value training programs. Our team partnered with Rhode Island to develop the Data for Opportunity in Occupation Reskilling Solution (DOORS, branded as “CareerCompass Rhode Island” in its RI pilot), a first-of-its-kind tool system to inspire jobseekers toward new and successful career paths. Powered by ML, AI, and Rhode Island’s own administrative data, the CareerCompass delivers personalized, data-driven new career recommendations straight to Rhode Islanders to launch them onto successful and rewarding new careers. The tool then matches individuals with highly relevant job openings in in-demand careers or recommend proven-effective reskilling opportunities. DOORS implementations are being developed in partnership in Hawai’i, New Jersey, and Colorado for launch in 2022.
The science and technology developed under this grant will support both policymakers and jobseekers across the country. Jobseekers can be confident that their recommendations are data-driven, based on successes of the many people like them who have tried new careers and reskilling programs in the past. DOORS connects jobseekers in each state with existing resources like job counseling in a customized way while also aiding those jobseekers and career counselors with metrics to better understand the career and employment returns to investing in specific trainings and careers.
DOORS also gives policy leaders real-time access to data and insights about the effectiveness of the state’s workforce development programs and forecasts of upcoming high-demand skills and careers, helping policy leaders deliver the best value to state residents from the state’s workforce investments. Our scalable approach delivers an end-to-end, sustainable solution that empowers government to support a community and culture of continuous, data-driven improvement.
Supported by the National Science Foundation grant #1937061
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