Overview of NSF investments and administration activities in AI Jim - PowerPoint PPT Presentation

Overview of NSF investments and administration activities in AI Jim Kurose Assistant Director for Computer and Information Science and Engineering National Science Foundation Assistant Director for Artificial Intelligence Office of Science and Technology Policy National Science Board Meeting, July 17, 2018

Artificial Intelligence  AI is critical to: • national economic competitiveness • national security • national health, welfare • global leadership  investments in fundamental research have positioned the US in a leadership position • many countries are increasing their investments in AI R&D “NSF is where all  NSF is the agency that makes largest interesting investment in fundamental AI research research gets started…” - Eric • what NSF does matters to the country Schmidt

CISE “core” programs and AI Core AI areas Allied AI areas machine computer learning vision computational social reasoning and databases data mining neuroscience computing representation speech and information multi-agent collaborative robotics bioinformatics language extraction systems systems human-robot visual augmented intelligent interaction analytics human interfaces NSF/CISE Division of Information and Intelligent Systems

NSF Investments in AI Research Cross cutting AI Smart & Autonomous CISE “core” AI $ 12 M Systems National Robotics $ 28 M Initiative 2. 0 Smart & Connected $ 24 M $ 104 M Communities Smart & Connected $ 12 M Health  Robust Intelligence $ 16 M Cyberlearning (RI) Computational Neuroscience  $ 4 M Information Integration and $ 28 M BIGDATA Informatics (III)  Cyber-Human Cyber-Physical Systems $ 34.5 M Systems (CHS)

NSF Investments in AI Research Cross cutting AI Smart & Autonomous CISE “core” AI $ 12 M Systems National Robotics $ 28 M Initiative 2. 0 Smart & Connected $ 24 M $ 104 M CISE Communities Smart & Connected $ 12 M Health  Robust Intelligence $ 16 M Cyberlearning (RI) Computational Neuroscience  $ 4 M Information, Integration and $ 28 M BIGDATA Informatics (III)  Cyber-Human Cyber-Physical Systems $ 34.5 M Systems (CHS)

NSF Investments in AI Research Cross cutting AI Smart & Autonomous CISE “core” AI $ 12 M Systems National Robotics $ 28 M Initiative 2. 0 BIO Smart & Connected $ 24 M $ 104 M CISE Communities Smart & Connected $ 12 M ENG Health  Robust Intelligence $ 16 M Cyberlearning EHR (RI) Computational Neuroscience  $ 4 M Information GEO Integration and $ 28 M BIGDATA MPS Informatics (III)  Cyber-Human SBE Cyber-Physical Systems $ 34.5 M Systems (CHS)

NSF Investments in AI Research Cross cutting AI Partners Smart & Autonomous CISE “core” AI Systems USDA, DOE, DARPA, National Robotics AFOSR, ONR Initiative 2. 0 Smart & Connected Communities Smart & Connected NIH (9 Institutes) Health  Robust Intelligence Cyberlearning (RI) ANR, BMBF, BSF, Computational Neuroscience  Information NICT, NIH Integration and Amazon, Google, BIGDATA Informatics (III) Microsoft, IBM  Cyber-Human DHS, DOT, NASA, Cyber-Physical Systems Systems (CHS) NIH, USDA

NSF’s 10 Big Ideas for Future Investment “ … bold questions that will RESEARCH IDEAS drive NSF's long-term research Windows on the Quantum Work at the agenda -- questions that will Universe: Leap: Human- Multi-messenger Leading the Technology ensure future generations Astrophysics Next Frontier: Quantum Shaping the continue to reap the benefits of Revolution Future Harnessing fundamental S&E research. ” Data for 21 st Understanding Century Navigating the Rules of Science and the Life: Engineering New Arctic Predicting Phenotype “AI is the universal connector PROCESS IDEAS that interweaves all of our Big Ideas; data science is changing Mid-scale Research NSF 2026 the very nature of scientific Infrastructure inquiry, and AI’s use of data has Growing NSF INCLUDES: the potential to revolutionize Convergence Enhancing STEM everything we do in science.” Research at NSF through Diversity and Inclusion F. Córdova , Director, NSF, Sept. 2017

Artificial Intelligence: an Administration Priority FY 2019 R&D Budget Priorities memo “autonomous systems, … machine learning, and quantum computing ….. coordinated interagency initiatives, … STEM education, including computer science education " National Security Strategy National Defense Strategy “prioritize emerging technologies critical to “.. invest broadly in military application of economic growth and security, such as data autonomy, artificial intelligence, and science, encryption, autonomous machine learning, including rapid technologies,… advanced computing application of commercial technologies, and artificial intelligence. “ breakthroughs.” “Artificial intelligence holds tremendous potential as a tool to empower the American worker, drive growth in American industry, and improve the lives of the American people. Our free market approach to scientific discovery harnesses the combined strengths of government, industry, and academia, and uniquely positions us to leverage this technology for the betterment of our great nation.” - Michael Kratsios, Deputy Assistant to the President for Technology Policy

Artificial Intelligence for the American People  Prioritizing funding for AI R&D  Achieving strategic military advantage: including, machine learning, recognizing need to lead in AI, with autonomous systems, research DoD investing accordingly cyberinfrastructure  Leveraging AI for government services:  Ensuring an AI-ready future applying AI to improve the provision of American workforce: K-12, re- government services training/Re-skilling,  Leading international AI negotiations: undergraduate, R&D workforce OSTP-led US delegations to 2017 &  Barriers to AI Innovation: removing 2018 G7 Innovation and Technology regulatory barriers to deployment Ministerials, working with allies to of AI-powered technologies recognize potential benefits of AI, promote AI R&D

2018 White House Summit on AI for American Industry  May 10, 2018  100+ participants: senior government officials, top AI academics, heads of industrial research labs, American business leaders  two sets of breakout sessions: • cross-cutting issues: AI R&D, workforce development, regulatory barriers to AI innovation • sector-specific applications : food and agriculture, energy and manufacturing, financial services, healthcare, and transportation and logistics

NSTC Select Committee on AI ... Membership: most senior Committee on Committee on Select Committee Technology S&T Enterprise Federal R&D officials (co-chairs: on AI F. Córdova (NSF), M. Kratsios (OSTP), S. Walker (DARPA) Subcommittees  advise White House on interagency AI Networking and Machine Information ... R&D priorities; Technology Research Learning and and Development  consider creation of Federal AI (MLAI) ( NITRD) Subcommittee partnerships with industry and Subcommittee academia;  establish structures to improve Working groups coordination of AI R&D; and AI R&D Interagency  identify opportunities to leverage Working Federal data, computational resources Group (IWG) in support of AI R&D ecosystem National Science and Technology Council (NSTC)

Looking forward: what’s needed  robust AI research ecosystem: • foundational research, AI in application domains, systems architecture, research cyberinfrastructure  workforce: • K-12 STEM workforce, computational thinking • lifelong learning, retraining, reskilling • R&D workforce Prescription 3:  partnerships: leverage unique US research ecosystem Establishing a More Robust National of academia (driven by federal R&D investment), Government- industry, federal government University-Industry Research Partnership