AI in Policy Virtual Panel
On Thursday, November 14th from 6pm-7:30pm EST, join us for our “Virtual AI” panel event that will shed light on the current status of AI within the policy realm, the role of data, how AI is impacting policy and policy professionals and researchers at the federal and state levels, and their views about its current status regarding accessibility and diversity of the data being used for AI. Join us as we bring together 5 leaders from many backgrounds like NAIRR, the NJ State Department of Labor, the American Enterprise Institute, and more where they'll present their key work and research on AI and answer pressing questions on the future of AI and how it will impact us all. Our speakers include: Julia Lane, Nancy Potok, Lesley Hirsch, Brent Orrell, and Manish Parashar, and you can learn more about them below!
Julia Lane: Julia Lane is a distinguished economist and professor at New York University's Wagner Graduate School of Public Service. Her extensive career encompasses significant contributions to data science, public policy, and the development of data infrastructures that support evidence-based decision-making. Lane has been instrumental in creating and leading initiatives such as the Longitudinal Employer-Household Dynamics (LEHD) program at the U.S. Census Bureau and the Coleridge Initiative, which focuses on data-driven research and policy innovation.
Lane's work emphasizes democratizing data access and integrating artificial intelligence (AI) into public policy frameworks. She has authored numerous publications on the impact of science investments and the role of data in policy development. Her recent efforts include developing training programs aimed at enhancing data literacy among policymakers and researchers, ensuring that AI and data analytics are effectively utilized in the public sector.
In recognition of her contributions, Lane has been elected as a fellow of the National Academy of Public Administration, the American Association for the Advancement of Science, and the American Statistical Association. She continues to advocate for the ethical use of data and AI in public policy, focusing on transparency, accountability, and the promotion of public trust. You can find out more about her here: https://wagner.nyu.edu/community/faculty/julia-lane
Nancy Potok: Nancy Potok is a highly respected leader in data governance and statistical policy, with extensive experience in both the federal government and academia. As the former Chief Statistician of the United States, she played a crucial role in setting quality standards for federal data and advancing evidence-based policymaking. Her work emphasizes the responsible use of data and AI, focusing on transparency and accountability within government operations.
Potok is a fellow of both the American Statistical Association and the National Academy of Public Administration, reflecting her commitment to rigorous standards in data and statistics. She also serves as a senior fellow at The George Washington University Center for Excellence in Public Leadership and is an advocate for leadership development in public service. Additionally, Potok serves on the Board of Directors for the Data Foundation and the Board of Trustees for the Institute of Pure and Applied Mathematics at UCLA, furthering her impact on data policy and infrastructure.
Her academic background in Environmental Studies and her Ph.D. from the Trachtenberg School of Public Policy and Public Administration at GWU inform her interdisciplinary approach to public policy, particularly her efforts to integrate AI in federal governance in ways that respect both ethical standards and regulatory requirements. In her current role, Potok teaches senior executives in the federal government about using AI for improved decision-making and efficient operations, balancing innovation with the government’s ethical and regulatory obligations. Her insights contribute significantly to discussions on fostering public trust in AI within public administration. You can find out more about her here: https://en.wikipedia.org/wiki/Nancy_Potok
Lesley Hirsch: Lesley Hirsch brings a wealth of expertise in workforce development, labor market analytics, and the integration of AI for labor and workforce insights. As Assistant Commissioner of Research and Information at the New Jersey Department of Labor and Workforce Development, Hirsch oversees research and data initiatives that guide workforce policy. She is also the Chair of the Secretary of Labor’s Workforce Innovation Advisory Committee, where she works to advance innovative approaches to workforce development. Her recent work has focused on leveraging AI and data science to create more adaptive, efficient workforce policies that address opportunity gaps, employment trends, and economic needs.
Hirsch’s research and initiatives are especially concerned with using AI to gain real-time insights into workforce dynamics, enabling policymakers to develop responsive, data-driven solutions to labor challenges. Her involvement with the Workforce Innovation Advisory Committee highlights her commitment to ensuring that AI’s role in workforce development is both equitable and forward-looking. You can find out more about her here: https://www.brookings.edu/people/lesley-hirsch/
Brent Orrell: Brent Orrell is a senior fellow at the American Enterprise Institute (AEI), where he focuses on workforce development, criminal justice reform, and the role of technology in the labor market. His expertise includes the intersection of emerging technologies like AI with workforce dynamics, particularly in areas like skills development, employment challenges, and socioeconomic implications. He has published extensively on the future of work, exploring how AI and automation are reshaping labor markets and what policy responses are necessary to mitigate potential negative effects while maximizing opportunities for workers.
Orrell’s work also touches on the broader societal impacts of AI, including concerns about displacement, inequality, and the need for reskilling initiatives. He advocates for policies that promote workforce resilience in the face of automation and AI, emphasizing the importance of human dignity and meaningful work in a rapidly changing technological landscape. You can find out more about him here: https://www.aei.org/profile/brent-orrell/
Manish Parashar: Manish Parashar is currently Director of the Scientific Computing and Imaging (SCI) Institute, Chair in Computational Science and Engineering, and Presidential Professor, Kalhert School of Computing at the University of Utah. He is also leading efforts at the University of Utah to build the National Data Platform, a project designed to facilitate the sharing and analysis of large-scale data across the U.S.
Manish recently completed an IPA appointment at the National Science Foundation as Office Director of the NSF Office of Advanced Cyberinfrastructure where he oversaw investments in national cyberinfrastructure. He also served as co-chair of the National Science and Technology Council’s Subcommittee on the Future Advanced Computing Ecosystem and the National Artificial Intelligence Research Resource Task Force. Manish’s expertise is in high performance parallel and distributed computing and cyberinfrastructure, and he has made pioneering contributions towards enabling new insights through large-scale computations and data in a range of science and engineering domains.
Manish has received several awards for his research and leadership, including most recently the 2023 IEEE Computer Society Sidney Fernbach Award and the 2024 CRA Distinguished Service Award. Manish is the founding chair of the IEEE Technical Consortium on High Performance Computing (TCHPC), and is Fellow of AAAS, ACM, and IEEE/IEEE Computer Society. For more information, please visit http://manishparashar.org.
This event is for NYU students, staff, and faculty only. Attendees must register with an NYU email address.