Artificial Intelligence at NSF
NSF ARTIFICIAL INTELLIGENCE RESEARCH INSTITUTES
The U.S. National Science Foundation announced the establishment of 11 new NSF National Artificial Intelligence Research Institutes, building on the first round of seven institutes funded in 2020. The combined investment of $220 million expands the reach of these institutes to include a total of 40 states and the District of Columbia.
The institutes are focused on AI-based technologies that will bring about a range of advances: helping older adults lead more independent lives and improving the quality of their care; transforming AI into a more accessible “plug-and-play” technology; creating solutions to improve agriculture and food supply chains; enhancing adult online learning by introducing AI as a foundational element; and supporting underrepresented students in elementary to post-doctoral STEM education to improve equity and representation in AI research.
“I am delighted to announce the establishment of new NSF National AI Research Institutes as we look to expand into all 50 states,” said National Science Foundation Director Sethuraman Panchanathan. “These institutes are hubs for academia, industry and government to accelerate discovery and innovation in AI. Inspiring talent and ideas everywhere in this important area will lead to new capabilities that improve our lives from medicine to entertainment to transportation and cybersecurity and position us in the vanguard of competitiveness and prosperity.”
Led by NSF, and in partnership with the U.S. Department of Agriculture National Institute of Food and Agriculture, U.S. Department of Homeland Security, Google, Amazon, Intel and Accenture, the National AI Research Institutes will act as connections in a broader nationwide network to pursue transformational advances in a range of economic sectors, and science and engineering fields — from food system security to next-generation edge networks.
“In the tradition of USDA-NIFA investments, these new institutes leverage the scientific power of U.S. land-grant universities informed by close partnership with farmers, producers, educators and innovators to provide sustainable crop production solutions and address these pressing societal challenges,” said USDA-NIFA Director Carrie Castille. “These innovation centers will speed our ability to meet the critical needs in the future agricultural workforce, providing equitable and fair market access, increasing nutrition security and providing tools for climate-smart agriculture.”
The new awards, each at about $20 million over five years, will support 11 institutes spanning seven research areas:
- Human-AI Interaction and Collaboration
- AI for Advances in Optimization
- AI and Advanced Cyberinfrastructure
- AI in Computer and Network Systems
- AI in Dynamic Systems
- AI-Augmented Learning
- AI-Driven Innovation in Agriculture and the Food System.
ENABLING RESEARCH ADVANCES IN AI
Through the NSF-led AI Research Institutes, as well as a range of ongoing programs, NSF supports fundamental research, education and workforce development, and advanced, scalable computing resources that collectively enhance 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 and philosophy, uniquely positions the agency to lead the nation in expanding the frontiers of AI. NSF's roots in these topics go back decades. 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 and philosophy, uniquely positions the agency to lead the nation in expanding the frontiers of AI.
NSF-funding will help the U.S. capitalize on the full potential of AI to strengthen the economy, advance job growth, and bring benefits to society for decades to come.
AI AND NSF's 10 BIG IDEAS
For AI, key among NSF's 10 Big Ideas are Harnessing the Data Revolution and Future of Work at the Human-Technology Frontier.
Harnessing the Data Revolution engages the 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.
Future of Work builds 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 brings NSF research communities together 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.
AI IN CORE AND CROSSCUTTING PROGRAMS
Core and crosscutting programs that support advances in AI include (in alphabetical order):
- Behavioral and Cognitive Sciences programs
- Civil, Mechanical, and Manufacturing Innovation programs
- Cyber-Physical Systems
- Electrical Communications, and Cyber Systems programs
- Information and Intelligent Systems: Core Programs
- Mathematical Sciences programs
- National Robotics Initiative 2.0: Ubiquitous Collaborative Robots
- Smart and Autonomous Systems
- Smart and Connected Health
- Smart and Connected Communities
- Social and Economic Sciences programs
FUNDING OPPORTUNITIES WITH SPECIAL EMPHASIS ON AI
AI and Society, supported jointly with the Partnership on AI — NSF's directorates for Computer and Information Science and Engineering and Social, Behavioral and Economic Sciences, together with the Partnership on AI, have jointly supported Early-concept Grants for Exploratory Research 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 — NSF 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 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 consideration of inclusivity.
Real-Time Machine Learning — 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 issued calls for proposals focused on real-time machine learning and are now offering collaboration opportunities to awardees from both programs throughout the duration of their projects. This partnership is contributing significantly to the foundation for next-generation co-design of algorithms and hardware.
DATA AND ADVANCED COMPUTING: A DRIVER OF MODERN AI
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's CISE Directorate has funded CloudBank, an entity that can establish partnerships with various public cloud computing providers, and enable the research and education community to access cloud computing platforms.
- Exploring Clouds for Acceleration of Science — 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 — 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 S&E, including AI. For example, in September 2019, the NSF-funded Frontera supercomputer came online at The University of Texas at Austin's Texas Advanced Computing Center as the fifth fastest supercomputer in the world. Frontera is enabling 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 including pre-K-12, colleges/universities and continuing education programs.
Computer Science for All: Researcher Practitioner Partnerships — This program aims to provide all U.S. students with the opportunity to participate in computer science and computational thinking education in their schools at the pre-K-12 levels. NSF focuses on researcher-practitioner partnerships that foster the R&D needed to bring computer science and computational thinking to all schools.
Improving Undergraduate STEM Education: Computing in Undergraduate Education — 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 understanding and competence 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 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 — 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 — The traineeship program is designed to encourage the development and implementation of bold, new and potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high-priority interdisciplinary or convergent research areas.
NSF LEADERSHIP IN AI ACROSS THE U.S. GOVERNMENT
NSF leadership plays an important role in helping to drive and coordinate AI R&D across federal agencies through the National Science and Technology Council, 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 Deputy 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. The NSF Assistant Director for CISE co-chairs the Networking and Information Technology Research and Development Subcommittee of the NSTC Committee on Science and Technology Enterprise. NITRD Coordinates efforts by the U.S. federal agencies that together comprise the nation's primary source of federally funded research on advanced information technologies in computing, networking and software.
The NSF Division Director for CISE's Information and Intelligent Systems division co-chairs the NITRD Artificial Intelligence Research and Development Interagency Working Group.
NSF joined other federal agency partners in announcing the release of an update to The National Artificial Intelligence Research and Development Strategic Plan in June 2019, as well as the release of a three-year Progress Report on Advancing Artificial Intelligence R&D in November 2019.
- Understanding Artificial Intelligence and Bias: A Summary of NSF Investments, March 3, 2022
- Readout of the First National Artificial Intelligence Research Resource Task Force Meeting, July 29, 2021
- National Artificial Intelligence Research Resource Task Force (NAIRR TF), May 2021
- Biden Administration launches the National Artificial Intelligence Research Resource Task Force, News Release 21-006
- National Artificial Intelligence Initiative, May 2021
- 2016-2019 Progress Report: Advancing Artificial Intelligence R&D, November 2019
- NSF leads federal partners in accelerating the development of transformational, AI-powered innovation, Oct. 8, 2019
- The National Artificial Intelligence Research and Development Strategic Plan: 2019 Update, June 21, 2019
- Artificial Intelligence Past and Present, June 24, 2019
- NSF joins federal partners in announcing update to national AI research and development strategic plan, June 21, 2019
- Statement on executive order to maintain American leadership in artificial intelligence, Feb. 11, 2019
- Executive Order on Maintaining American Leadership in Artificial Intelligence, Feb. 11, 2019
- Comments Received in Response to the Request for Information on Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan, Dec. 19, 2018
- Update from the NSTC Select Committee on AI, Nov. 30, 2018
- Request for Information on Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan, Sept. 26, 2018
- A New NITRD IWG for AI R&D, July 2, 2018
- Summary of the 2018 White House Summit on Artificial Intelligence for American Industry, May 10, 2018
- Statement on Artificial Intelligence for American Industry, May 10, 2018
- Testimony of Dr. Jim Kurose, CISE AD, before the Subcommittee on Information Technology for the Committee on Oversight and Government Reform, U.S. House of Representatives, March 7, 2018
- Remarks of Dr. France Córdova, NSF Director, at the NVIDIA GPU Technology Conference, November 1, 2017
- Remarks of Dr. France Córdova, NSF Director, at the NVIDIA GPU Conference, Oct. 26, 2016
- NSF statement of support for National Artificial Intelligence Research and Development Strategic Plan, Oct. 26, 2016
- The National Artificial Intelligence Research and Development Strategic Plan, Oct. 2016
Webpage last updated July 30, 2021