Samuel J. Gordy, General Manager, Chief Strategy Officer, Public and Federal Market, IBM Corporation
AI and the Future of Work: Creating an Adaptable Workforce
A robust pipeline of talent with expertise in AI is essential for national security and economic growth. At the epicenter for AI tech talent demand, leadership from Commonwealth Universities discuss challenges and novel approaches to developing a resilient, adaptable, AI ready-workforce.
Moderator: Kelly Demaitre, Chief Human Resource Officer, Dovel Technologies
Irma Becerra, President, Marymount University
Anne Kress, President, Northern Virginia Community College
Anne Holton, President, George Mason University
Peggy Agouris, Provost, William & Mary
Tech Talk 1
Artificial Intelligence in Radiology: Lessons Learned Over the Past 30 Years
The radiology community has been developing computer aided diagnosis (CAD) tools over the past 30 years before artificial intelligence hype. Recent publications reported that the commercial CAD products used for digital mammograms provided no statistically significant benefits over the performance of radiologists. Conversely, a CAD system for lung cancer screening showed a significant improvement in accuracy and efficiency. The research and investments are increasing on the use of AI tools for a wide range of radiology applications. In spite of the explosive amount of interest in the use of AI for medical imaging, and highly speculative stories in the press, clinical adoption and commercial success of these AI tools remains elusive.
In this presentation we will highlight how imaging AI products are developed and tested for FDA. FDA approval however does not assure clinical and commercial success. We will summarize remaining issues of wider adoption of this potentially power technology.
Seong K. Mun, PhD, Professor and Director Arlington Innovation Center; Health Research Virginia Tech, Arlington, VA
Questions and Answers
Ben Snively, Principal Solutions Architect in Data Science at Amazon Web Services
AI in Content Bias
During this panel, the various dimensions of “bias” and the role “AI” plays in content bias will be discussed. This is a hot topic in media and, unfortunately, a lot of the media has created confusion around the meanings of ‘bias’ and ‘artificial intelligence,’ with ‘bias’ being portrayed as something bad. Usually this is because the media is using a pretty narrow term for ‘bias’ in the demographic and social sense.
People often blame algorithms for bias, when in reality the whole system needs to be studied to understand the ways in which bias may be introduced since algorithms are only one part of that system.
Setting aside that in the mathematical sense that ‘bias’ is how machine learning works, bias can be good and bad. This creates ethical, policy, regulatory, legal and social issues. Two primary concerns many people have are around the use of AI where bias is of chief concern is in military and law enforcement applications.
Charles Onstott, SVP and CTO, SAIC
Patrick Grother, Scientist, NIST
Chuck Cohen, Vice President, NW3C, The National White Collar Crime Center
Dr. Steve Kramer, Chief Science Officer, Kung FU AI
Questions and Answers
Tech Talk 2
Computers Who Understand You
Computers can now understand what you say and write like never before. Learn how this is possible and how it will transform everything and expand the reach of machine learning to functions which were previously thought impossible.
Paul Nelson, Innovation Lead for Accenture Applied Intelligence, Accenture
AI in Professional Sports
Can Artificial Intelligent create a competitive advantage in professional sports? From enhancing the Fan experience, to improving player safety, IoT coupled with AI technologies is changing the landscape of professional sports and stadium design. Listen to a discussion of how AI can impact our favorite pastimes.
Brad Antle, CEO, Antle Advisors
Richard (Dick) Darden, Distinguished Engineer and Digital Human Evangelist, North America Government, IBM
Adam Heintz, SVP Business Intelligence, Monumental Sports and Entertainment
Dan Waldschmidt, Co-CEO, EDGY Inc.
Tech Talk 3
Challenges and Opportunities in Autonomous Navigation
Advancements in reliable navigation and mapping rest to a large extent on robust, efficient and scalable understanding of the surrounding environment. The success in recent years have been propelled by the use using deep convolutional neural networks (CNNs) for capturing geometry and semantics of environment from video and range sensors.
Jana Kosecka will discuss challenges of deploying these systems in real-world settings and outline some strategies for jointly optimizing perception and decision making algorithms in the context of elementary navigation tasks. The presented explorations open interesting avenues for control of embodied physical agents and general strategies for design and development of general purpose autonomous systems.
Jana Kosecka, Professor, Department of Computer Science, George Mason University
Questions and Answers
Protecting AI Inventions: Current Issues and Best Practices
The IP panel will discuss current issues with and best practices for obtaining IP protection for AI inventions. The panel will address protecting the various aspects of AI inventions such as the AI engine, training methods, and data sets. For example, how does current law treat ownership of AI-generated inventions and content? The panel will also discuss AI IP policy at the US Patent and Trademark Office and their recent efforts regarding the regulation of AI and information gathering on how to promote the patenting of AI inventions.
Moderator: Jim Daniel, Chief Legal Officer, ICF International
Charles Kim, Director, Office of Petitions, USPTO
Sean O’Connor, Professor, George Mason University Scalia School of Law
Sameer Gokhale, Partner, Oblon
Tech Talk 4
Challenges and Solutions for AI Adoption at Scale
Over the past five years, techniques like computer vision and machine learning for military planning have made great strides, but significant technical, operational, and psychological barriers to widespread adoption remain. This presentation provides a provocative exposition of some of the key challenges to orientation in an environment of massive disinformation, democratized social media, pervasive sensors, and exploding data volumes. We frame modern AI challenges using John Boyd’s OODA (Observe-Orient-Decide-Act) Loop model and highlight key questions that must be answered to move technology forward. This presentation references numerous (and humorous) examples of AI-gone-wrong in the modern literature and highlights approaches and techniques to solve real-world problems.
Patrick Biltgen, Director of Analytics, Perspecta
The Race for Leadership in AI
The race for global leadership in AI has already started. But what does leadership mean in the context of AI? What’s at stake, what are the different strategies, and how are they being implemented? This panel explores the planning and implementation of national AI policies in the U.S. and around the world. The discussion will also cover issues related to innovation, adoption, and commercialization of AI as well as the potential challenges of taking different approaches.
Moderator: Billy Mitchell, Editor-in-chief, FedScoop
Chris Dain, Foreign and Commonwealth Office, British Embassy
Meg King, Strategic and National Security Advisor to the Wilson Center’s CEO & President, Coordinator of the Science and Technology Innovation Program, Director, Wilson Center’s AI Lab for Congressional Staff
Michael Nelson, Senior Fellow and Director, Technology and International Affairs, Carnegie Endowment for International Peace
Questions and Answers