Air Force Partners with academia, industry to host three-part Trusted AI Challenge series
Rome, N.Y. – The Air Force Research Laboratory Information Directorate is teaming up with academia, industry and government agencies to ensure the trustworthiness of future Artificial Intelligence (AI) systems.
Innovare Advancement Center, in partnership with AFRL, The State University of New York (SUNY), and supported by NYSTEC, Griffiss Institute (GI), National Security Innovation Network (NSIN), The Research Foundation for SUNY, and the Innovation Collective, will host a challenge series to “Build the Vision – Formalize Challenges – Advance the Art” of next generation AI systems.
The series, which is designed to cultivate, define and fund creative solutions to a set of challenge problems in trustworthy AI with a particular focus on dynamic, autonomous systems that learn and adapt behaviors, will kick off Oct. 14, 2020 with a half-day webinar beginning at 12 p.m. Eastern.
“Intelligent systems are optimizing our lives and are more and more expected to construct courses of action, make decisions, and act at machine to machine speeds with reduced human oversight,” said Dr. Bryant Wysocki, United States Air Force Technical Advisor for Command, Control, Communications, Computing, Intelligence & Cyber, Air Force Research Laboratory. “The Trusted AI Challenge Series is designed to get at the technical challenges associated with certifying self-aware learning systems to safely and reliably operate in society with the appropriate level of autonomy.”
“SUNY is delighted to host and participate in this important event that will identify key requirements for trustworthy AI technologies”, said Dr. Meera Sampath, Associate Vice Chancellor for Research. “Trust is crucial for the widespread adoption and acceptance of AI. This challenge series is designed to enable critical advances in the field with its strong focus on translating vision into practical solutions.”
With a set of thought-provoking talks and an interactive panel covering industry, research, and government perspectives, this first event of the Trusted AI Challenge series will provide insights into the critical path requirements for building reliable, robust AI and autonomous systems that can be widely adopted.
The distinguished panel of speakers for this event include:
- Professor David Doermann, State University of New York, University at Buffalo
- Dr. Peter Friedland, Consultant and Senior Scientific Advisor to the Air Force Office of Scientific Research
- Dr. David Goldstein, Director of Special Programs, SpaceX
- Michael Graniero, Small Business Professional, Air Force Research Laboratory, Information Directorate
- Heather Hage, Vice President, Industry and External Affairs, The Research Foundation for SUNY
- Professor Scott Hubbard, Stanford University, former Director NASA Ames Research Center
- Professor Pramod Khargonekar, Vice Chancellor for Research, University of California Irvine
- Karen Roth, Chief Engineer, Air Force Research Laboratory, Information Directorate
- Dr. Meera Sampath, Associate Vice Chancellor for Research, State University of New York
- Dr. Elham Tabassi, Chief of Staff, Information Technology Laboratory, National Institute of Standards and Technology
- Dr. Bryant Wysocki, United States Air Force Technical Advisor for Command, Control, Communications, Computing, Intelligence & Cyber, Air Force Research Laboratory
The event will conclude with a “Coffee and Concepts” networking session. During this 30-45 minute online gathering, attendees will mix together into small breakout rooms to meet and discuss all things Artificial Intelligence.
“The Griffiss Institute is proud to play a significant role in fostering the collaboration among the Air Force Research Laboratory, small business, and academia, in the critical technology area of Trusted AI,” said Mike Wessing, Griffiss Institute Acting President/Chief Engineer. “This first event of three will continue the vision of the Innovare Advancement Center, bringing world class researchers together to cultivate and define creative solutions to a set of challenging research problems.”
AFRL is one of Innovare’s key strategic collaborators seeking to achieve the team’s vision: engage partners to initiate entrepreneurial ventures and tech startups in key strategic areas, including artificial intelligence/machine learning, cybersecurity, and quantum, in addition to building a robust talent pipeline at a time when scientific advancement across boundaries is needed now more than ever to remain economically and strategically competitive in this fast-changing world.
This event is designed for those interested in understanding the challenges that lie ahead as AI systems become increasingly autonomous, dynamically acquire information, and adapt behaviors, including academic and government researchers, university students, and small businesses.
The second and third events of this series, “Grounding the Critical Path,” and “Accelerating Progress,” will take place in Spring 2021.
To register for the first event, view the agenda, and to learn more about the three-part series, please visit: https://www.innovare.org/events/trusted-ai-challenge-series-1
About Innovare Advancement Center
Innovare Advancement Center aims to be a global catalyst to converge world-class talent with cutting-edge facilities and focused technology challenges to accelerate the development of game-changing capabilities that protect and empower our country. An open innovation environment immediately adjacent to Air Force Research Laboratory’s Information Directorate in Rome, NY, Innovare Advancement Center offers a globally connected innovation ecosystem in which world-class scientific, engineering, and entrepreneurial talent from universities, government, and industry can leverage highly specialized resources in critical research areas, including artificial intelligence/machine learning, cybersecurity, quantum, and unmanned aerial systems to tackle the country’s greatest challenges to national security and economic competitiveness. To learn more, visit www.innovare.org.