Artificial Intelligence (AI) at NSF

Dr. France A. Cordova

NSF has a long and rich history of supporting transformative research in artificial intelligence and machine learning and is an essential contributor to growing the workforce needed to advance AI research and development...

Advances in AI are crucial for the U.S. science and engineering enterprise, and nearly all sectors of our 21st-century economy. Many of the transformative uses of AI that we are witnessing today are founded in federal government investments in fundamental AI research that reach back over decades. Building the foundations of tomorrow's AI innovations will require new interdisciplinary collaborations, resources, and strategic visions — principles that NSF has championed in its support of fundamental AI research...

The AI innovations that NSF has funded have helped the U.S. capitalize on the full potential of this critical research area, and we are eager to (continue to) strengthen our economy, advance job growth, and better our society.

— France A. Córdova, Director, National Science Foundation
Statement on Executive Order to Maintain American Leadership in Artificial Intelligence
February 11, 2019

NSF supports fundamental research, education and workforce development, and advanced, scalable computing resources that collectively advance fundamental research in AI. NSF's ability to bring together numerous fields of scientific inquiry — including computer and information science and engineering, along with cognitive science and psychology, economics and game theory, engineering and control theory, ethics, linguistics, mathematics, philosophy — uniquely positions the agency to lead the nation in expanding the frontiers of AI. In turn, NSF-funding discovers and discoveries will help the U.S. capitalize on the full potential of AI to strengthen our economy, advance job growth, and better our society for decades to come.


NSF supports foundational as well as translational research in AI through a broad range of programs spanning multiple directorates/offices.


Advances in AI are core to many of the "10 Big Ideas for NSF Future Investment". Key among these are the Harnessing the Data Revolution (HDR) and the Future of Work at the Human-Technology Frontier (FW-HTF) Big Ideas.

HDR engages NSF's research community in the pursuit of fundamental research in data science and engineering; the development of a cohesive, federated, national-scale approach to research data infrastructure; and the development of a 21st -century data-capable workforce. Learn about active funding opportunities here.

FW-HTF is building an understanding of how constantly evolving technologies are actively shaping the lives of workers and how people in turn can shape those technologies, especially in the world of work. This Big Idea is bringing together NSF research communities to conduct fundamental scientific research on the interaction of humans, society, and technology that will help shape the future of work to increase opportunities for workers and productivity for the American economy. Learn about active funding opportunities here.


The core and crosscutting programs that support advances in AI include (in alphabetical order):


AI and Society, supported jointly with the Partnership on AI — NSF's Directorates for Computer and Information Science and Engineering (CISE) and Social, Behavioral and Economic Sciences (SBE) together with the Partnership on AI (PAI) are jointly supporting EArly-concept Grants for Exploratory Research (EAGERs) to understand the social challenges arising from AI technology and enable scientific contributions to overcome them. With increases in the scale and diversity of deployments of AI systems comes the need to better understand AI in the open world, including unforeseen circumstances and social impacts, and to craft approaches to AI that consider these from the start.

Fairness, Ethics, Accountability, and Transparency (FEAT) — NSF's CISE directorate invites researchers to submit proposals to its core programs that contribute to discovery in research and practice related to fairness, ethics, accountability, and transparency in computer and information science and engineering, including AI.

NSF Program on Fairness in Artificial Intelligence in Collaboration with Amazon – NSF’s CISE and SBE directorates and Amazon are partnering to jointly support research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. Specific topics of interest include, but are not limited to, transparency, explainability, accountability, potential adverse biases and effects, mitigation strategies, validation of fairness, and considerations of inclusivity.

Real-Time Machine Learning (RTML) – NSF and the Defense Advanced Research Projects Agency (DARPA) have teamed up to explore high-performance, energy-efficient hardware and machine learning architectures that can learn from a continuous stream of new data in real time. Both agencies have issued calls for proposals focused on RTML, and will offer collaboration opportunities to awardees from both programs throughout the duration of their projects. Overall, this partnership will contribute significantly to the foundation for next-generation co-design of RTML algorithms and hardware.


Advances in AI rely upon the availability of deep, high-quality, and accurate training datasets as well as advanced, scalable computing resources. Recent NSF activities include:

Enabling Access to Cloud Computing Resources for CISE Research and Education (CloudAccess) — Increasingly, data- and compute-intensive research and education efforts are benefiting from access to cloud computing platforms, which provide robust, agile, reliable, and scalable infrastructure. To better support this growing use of cloud computing resources, NSF/CISE seeks to fund an entity that can establish partnerships with the various public cloud computing providers, and enable the research and education community to access cloud computing platforms.

Exploring Clouds for Acceleration of Science (E-CAS) — NSF awarded a new cooperative agreement to Internet2, a nonprofit computer networking consortium, to build partnerships with commercial cloud computing providers and support science applications in new and more effective uses of cloud computing capabilities. E-CAS will investigate the viability of commercial clouds as an option for leading-edge research computing and computational science supporting a range of academic disciplines. Amazon Web Services and Google Cloud Platform have signed on as the initial cloud computing providers in this activity.

High-performance computing (HPC) — NSF supports a range of HPC resources to provide advanced cyberinfrastructure capabilities and/or services for the full range of computational- and data-intensive research across all areas of science and engineering, including AI. For example, in August 2018, NSF made a $60 million award to fund the largest and most powerful supercomputer the agency has ever supported to serve the nation's science and engineering research community. The new high-performance computing (HPC) system, to be called Frontera, will be located at the University of Texas at Austin's Texas Advanced Computing Center. Frontera will enable access to HPC resources for AI research.


NSF's investments in AI research and infrastructure are accompanied by investments in education and workforce development. NSF is funding research and development that is building the necessary foundations for implementing rigorous and engaging computer science education at all levels: preK-12, colleges/universities, and continuing education programs.

Computer Science for All: Researcher Practitioner Partnerships (CSforAll: RPP) — This program aims to provide all U.S. students the opportunity to participate in computer science (CS) and computational thinking (CT) education in their schools at the preK-12 levels. NSF focuses on researcher-practitioner partnerships (RPPs) that foster the research and development needed to bring CS and CT to all schools.

Improving Undergraduate STEM Education: Computing in Undergraduate Education (IUSE: CUE) — Increasingly, undergraduate CS programs are being called upon to prepare larger and more diverse student populations for careers in both CS and non-CS fields, including careers in scientific and non-scientific disciplines. Many of these students aim to acquire the understandings and competencies needed to learn how to use computation collaboratively across different contexts and challenging problems. However, standard CS course sequences do not always serve these students well. With this solicitation, NSF will support teams of Institutions of Higher Education (IHEs) in re-envisioning the role of computing in interdisciplinary collaboration within their institutions. In addition, NSF will encourage partnering IHEs to use this opportunity to integrate the study of ethics into their curricula, both within core CS courses and across the relevant interdisciplinary application areas.

Graduate Research Fellowships (GRF) — The GRF program recognizes and supports outstanding graduate students in NSF-supported STEM disciplines, including AI and data science, who are pursuing research-based Master's and doctoral degrees at accredited U.S. institutions.

NSF Research Traineeship (NRT) — The NRT program is designed to encourage the development and implementation of bold, new, and potentially transformative models for STEM graduate education training. NRT is dedicated to effective training of STEM graduate students in high-priority interdisciplinary or convergent research areas, and includes HDR and FW-HTF among these.


NSF leadership plays an important role in helping drive and coordinate AI research and development across the Federal Government through the National Science and Technology Council (NSTC), a Cabinet-level council that serves as the principal means for the President to coordinate science and technology policies across the Executive Branch.

  • The NSF Director (along with the DARPA Director and the White House Office of Science and Technology Policy Director) co-chairs the NSTC Select Committee on AI, which was formed in May 2018 to “advise The White House on interagency AI R&D priorities; consider the creation of Federal partnerships with industry and academia; establish structures to improve government planning and coordination of AI R&D; and identify opportunities to leverage Federal data and computational resources to support our national AI R&D ecosystem.”
  • The NSF Assistant Director for CISE co-chairs the Machine Learning and AI Subcommittee of the NSTC Committee on Science, which serves as the implementation arm for the Select Committee on AI, and also co-chairs the Networking and Information Technology Research and Development Program (NITRD). NITRD agencies together comprise the nation's primary source of federally-funded research on advanced information technologies (IT) in computing, networking, and software.
  • The NSF/CISE Division Director for Information and Intelligent Systems (IIS) co-chairs the NITRD Artificial Intelligence Research and Development (R&D) Interagency Working Group (IWG). This group is currently updating the 2016 National AI R&D Strategic Plan and producing a National AI R&D Progress Report.


Webpage last updated April 10, 2019