An Overview of the ‘National Security Commission on AI’ Report
The Department of Defense thrives off the speed of critical decision making. The ability to get raw data and intelligence in a form to be used to make real-time decisions can often be the difference between success and failure. With such massive complex as DoD, the initiatives in and around AI are difficult to fathom. The ability to harness the common pursuits and learn from similar failures, as well as coordinate initiatives across the defense complex, can speed the timeline for solving some of the unique challenges facing our military services. Come listen to our Keynote speaker and panelists to hear where DoD is heading with AI applications and where there is significant help still required.
The Honorable Katharina McFarland, Commissioner, National Security Commission on AI; Chair, National Academies of Science Board of Army Research and Development
Michael Scruggs, Senior Vice President of Artificial Intelligence, SAIC
Dr. Arlene Espinal, Vice President, Analytics | Automation | Artificial Intelligence (A3) Innovation & Capabilities Office (ICO), ManTech
Dr. Cheryl Howard, Principal Data Scientist, IBM Data and AI Expert Labs, North American Government
Dr. Ian McCulloh, Chief Data Scientist, Accenture Federal Services
Keys to Successfully Deploying AI Applications: Applying AI/ML Applications to Helicopter Predictive Maintenance
This talk will go into detail how a classification AI/ML application was built in nine months and applied to the U.S. Army T700 Engineering Review Board. This talk will walk through how the data was gathered, analyzed and applied to build an AI/ML application to solve the customers problem. We will explore how the application was built to be rapidly integrated into the customer’s environment to easily deploy and scale for future sustainability. Lastly, the talk will explain how the interactions with the customer lead to identifying gaps in the data and how solutions were made with the subject matter experts to apply AI/ML to their environment.
Cameron Izzi, Lead Machine Learning Engineer, Novetta
Leveraging Artificial Intelligence for Biomedical Research at the NIH
Dr. Susan Gregurick, Associate Director for Data Science and Director, Office of Data Science Strategy at the National Institutes of Health (NIH), will discuss the agency’s breadth of activities aimed at effectively leveraging artificial intelligence for biomedical research. Notably, NIH is addressing ways to make its data more AI- and machine learning-ready, to increase the workforce’s AI skillset, and to ensure AI is being used in an ethical manner when applied to biomedical research.
Dr. Susan Gregurick, Associate Director for Data Science and Director of the Office of Data Science Strategy (ODSS), National Institutes of Health (NIH)
AI in Health – The Good, The Bad and the Ugly
AI is, and will continue to touch our lives in a multitude of ways. Few, if any of those ways, are as important as how AI will impact our health and well-being. While no one disputes the value of identifying a tumor missed by the oncologist in a digital image, improved efficiencies in the vaccine supply chain, or even something as mundane as reduced wait times for regular visit through more efficient scheduling, yet it’s not that simple.
Do you trust an AI algorithm? Does the care provider understand what the AI algorithm is telling her? Are recommendations biased in a way that disadvantages certain populations or indeed are such improved techniques only available to a subset of the population further widening the digital and socioeconomic divide? Join us with a panel of experts as they unravel the intricacies of the promise of AI in health as well as the threats.
Dr. Phil Bourne, Dean, School of Data Science, University of Virginia
Dr. Gil Alterovitz, Director of the Veterans Affairs National Artificial Intelligence Institute
Dr. Gerhard Pilcher, CEO, ElderResearch
Swathi Young, CTO, Integrity Management Services, Inc.
AI Delivers Innovation, Accuracy and Hope to Healthcare
There’s a lot of money chasing AI right now and for good reason. Accenture predicts that AI apps will start saving the U.S. healthcare system an annual $150 billion beginning in 2026. AI is the next best thing to having a crystal ball when it comes to pinpointing health risk, extracting the meaningful signals from all the noise generated by the Internet of Medical Things. Imagine being able to identify the highest-risk cardio or diabetic patient and focusing resources there. The opportunities to reshape the healthcare landscape with AI seem endless, but one critical benefit after a year of pandemic turmoil is reducing burnout among healthcare providers. AI will let providers focus on patients instead of mundane tasks, which also improves the patient experience. This is just one way in which AI makes humans more human!
Ashish Kachru, President, Altruista Health
AI has the power to both threaten cybersecurity as well as reinforce, augment, and ensure cybersecurity. Today’s keynote, panel and speakers will discuss how the widespread advancement of AI across many applications such as smart cities, manufacturing, public health, and national security presents new challenges but is also driving new tools to ensure cybersecurity.
Dr. Malek Ben Salem, Director Security R&D, Accenture Security
Commonwealth Cyber Initiative (CCI) AI Test Bed
This panel will present the CCI AI Assurance Testbed and Software factory, a research infrastructure developed by the Commonwealth Cyber Initiative for use by CCI academia, industry and government partners across Virginia. The panel will describe the specific infrastructure, its capability and example current project applications. Panelists will discuss the need for the infrastructure to evaluate the level of trust and assurance of AI algorithms. The testbed will provide pre-trained models, pre-built containers, test suite generators, and data in a plug-and-play interface. This new resource is poised to accelerate research, support training and lead to new innovations.
Liza Wilson Durant, PhD, Director, Commonwealth Cyber Initiative (CCI), NoVa Node, George Mason University
Abdul Rahman, Director, CCI AI Testbed
Dave Ihrie, CTO, CIT
Zachary Tudor, Associate Lab Director Idaho Lab and Homeland Security Science and Technology Directorate
Milos Manic, CCI Faculty Fellow, Director Cybersecurity Center, Virginia Commonwealth University
Cyber is the New Cold War and AI is the Arms Race
The Russian attacks on Ukraine from 2014-present, China’s continued theft of intellectual property, and the recent Solarwinds attack all make it clear that cyber is the new Cold War. Daily activities are just below the level of “armed conflict”. The arsenal is composed of malware and zero-day exploits, and offensive and defensive operations are global and in real-time. The current DoD cyber strategy is on information dominance and defending forward. The crucial step is of course decision superiority – that AI tools provide augmenting analytics for real-time decision-making. This need applies equally across DoD, civilian and commercial organizations. In this talk we’ll look at cyber as a field of data science, and the role and vulnerabilities of AI applied to this field.
Dr. Nancy Grady, Chief Data Scientist, SAIC
Democratizing Hiring: Prioritizing fast, friendly, and fair hiring practices in a digital-first world
When humans are involved and the in the decision making loop, the presumption is that their background and life experiences will influence their decision making process. Applying filters to all of the stimulus is the way we deal with complexity and vast quantities of data that comes at us virtually every waking minute of the day. The result of these influencers in our decision making process is often referred to as bias. The elimination of bias is a goal in many areas of our life and the hope is that the application of Artificial Intelligence can achieve that end. But who develops the AI and can bias be eliminated from AI as well? From screening of online content to the job interviewing process, bias prevents the best outcome. Come listen to our Keynote speaker and panelists discuss where we are today towards the goal of eliminating or reducing bias through AI.
Kevin Parker, Chairman and CEO, HireVue
Infusing our AI work with Ethical Awareness
Addressing the key principles for Responsible AI: Transparency, Fairness, Privacy, Inclusiveness, Accountability and Reliability.
Rod Fontecilla, Senior Vice President, Chief Innovation Officer and Chief Data Scientist, Dovel Technologies
Ronald Fricker, Interim Dean College of Science and Professor of Statistics, Virginia Tech
Ron Kenett, Chairman, KPA Group
Yevgeniy Sirotin, Senior Scientist Manager and Fellow, SAIC
Laura Freeman, Director, Hume Center’s Intelligent Systems Lab, Virginia Tech
Using Low-Code Automation to Minimize Bias
Learn how Appian’s low-code automation platform orchestrates workflow, bots and AI to minimize bias. Appian enables humans to deal with exceptions and AI to take care of the mundane activities without bias. Learn about specific use cases of how the world’s largest organizations can improve customer experience, achieve operational excellence and deliver high value business outcomes.
Michael Beckley, Founder and CTO, Appian