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To inform a community strategy for building and maintaining U.S. leadership in software engineering and AI engineering, the Carnegie Mellon University’s Software Engineering Institute (CMU SEI) and the Software Productivity, Sustainability, and Quality (SPSQ) Interagency Working Group co-hosted the workshop at the National Science Foundation from June 20th to the 21st, 2023…
This document reports current trends and examples of federal R&D investments, program information, and activities in AI that directly address the R&D challenges and opportunities noted in the National Artificial Intelligence Research and Development Strategic Plan: 2023 Update https://www.nitrd.gov/pubs/National-Artificial-Intelligence-Research-and-Development-Strategic-Plan-2023-Update.pdf
This document includes relevant text from the 2016 and 2019 national AI R&D strategic plans, along with updates prepared in 2023 based on Administration and interagency evaluation of the National AI R&D Strategic Plan: 2019 Update as well as community responses to a Request for Information on updating the Plan. The 2019 strategies were broadly determined to be valid going forward. The 2023 update adds a new Strategy 9, which establishes a principled and coordinated approach to international collaboration in AI research.
The Blueprint for an AI Bill of Rights is a guide for a society that protects all people from these threats—and uses technologies in ways that reinforce our highest values. Responding to the experiences of the American public, and informed by insights from researchers, technologists, advocates, journalists, and policymakers, this framework is accompanied by From Principles to Practice—a handbook for anyone seeking to incorporate these protections into policy and practice, including detailed steps toward actualizing these principles in the technological design process. These principles help provide guidance whenever automated systems can meaningfully impact the public’s rights, opportunities, or access to critical needs.
Arguably one of the greatest areas of progress in computing research over the last decade has been Artificial Intelligence and Machine Learning. The field has seen an AI/robotics revolution, and an explosion of new technologies, establishing itself as one of the underpinnings of society. Panel 3: AI/ML, moderated by Liz Bradley (University of Colorado Boulder) and starring panelists Charles Isbell (Georgia Tech), Chad Jenkins (UM), Talitha Washington (CAU), and Patti Ordóñez Franco (UPRRP) celebrated these federally funded advances and discussed the challenges these new innovations bring with them.
The Office of Science and Technology Policy, on behalf of the National Science and Technology Council’s (NSTC) Select Committee on Artificial Intelligence (Select Committee), the NSTC Machine Learning and AI Subcommittee (MLAI-SC), the National AI Initiative Office (NAIIO), and the Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO), requests input from all interested parties on updating the National Artificial Intelligence Research and Development Strategic Plan. Through this Request for Information (RFI), OSTP, the Select Committee, NAIIO, and NITRD NCO seek input from the public, including academic, State, and industry groups; those directly performing Artificial Intelligence (AI) research and development (R&D); and those directly affected by such R&D, on the ways in which the strategic plan should be revised and improved. The public input provided in response to this RFI will assist OSTP, the Select Committee, MLAI-SC, NAIIO, and NITRD NCO in updating the National Artificial Intelligence Research and Development Strategic Plan.
A searchable directory of AI-relevant Federal grant programs. Grant programs can be filtered by the offering department or agency, the particular AI strategy topic that is covered, and whether it is considered “core AI”, which advances the foundations of AI, or “other AI”, which refers to use-inspired AI research in fields such as cybersecurity or materials discovery.
Testbeds provide environments to support development of real-world applications of AI that are robust and trustworthy. They embody key mechanisms to support research progress by creating benchmarking standards, enabling reproducibility testing, and building communities of discovery and practice. Locate Federally-supported testbed and testing resources that can support AI research.
This report is a product of interagency collaboration, led by the National Science and Technology Council (NSTC) Select Committee on AI and Subcommittee on Machine Learning and AI (MLAI), that is one of several measures responding to the February 11, 2019, Executive Order on Maintaining American Leadership in Artificial Intelligence.
In support of Executive Order 13859, “Maintaining American Leadership in Artificial Intelligence”, and The National Artificial Intelligence Research and Development Strategic Plan: 2019 Update, NITRD worked with Federal agencies to establish a …
