Plenary Speakers and Tracks
Tuesday, June 25 | 8:50 am – 12:40 pm
7:45 am - 6:30 pm Registration Open
7:45 Morning Coffee & Pastries
8:50 Conference Chair Introduction
Scott Lundstrom, Group Vice President and General Manager, IDC and AI World Government, Conference Co-Chair
9:00 Keynote: Open Data and AI Drive Digital Transformation in Government
Scott Lundstrom, Group Vice President and General Manager, IDC and AI World Government, Conference Co-Chair
Artificial Intelligence is poised to transform every aspect of government over the next decade. Every individual in the transformed organization will be impacted by AI’s ability to inform, augment, and automate decision making - and is just the
beginning! Understanding the opportunity for new services and new models for citizen engagement will change the way we look at technology’s role in government. AI technologies bring threats and opportunities that must be managed to every organization,
and new policies and guidelines will be required to harness these advances.
In this presentation, Scott Lundstrom, IDC Group Vice President and General Manager, will set the stage by sharing IDC’s Artificial Intelligence Framework, IDC’s “use cases” for Government Digital Transformation, and IDC’s
Artificial Intelligence predictions that will impact government IT professionals over the next five years.
9:20 Keynote: AI Update from the White House
Suzette Kent, Federal Chief Information Officer, U.S. Office of Management and Budget
9:45 Plenary Roundtable: Getting Started and Moving Forward – Advice for the next 24 months
Join us for this fast paced panel focused on managing the complexity and turbulence of this quickly evolving market. AI Technology, regulations, and policy objectives are all in flux, and making a meaningful start in your use of AI can be challenging.
Gain perspective on priorities and strategies to being successful and building competences that matter in this next generation of software.
Moderator: Scott Lundstrom, Group Vice President and General Manager of IDC Government and Health Insights, IDC and AI World Government, Conference Co-Chair
Panelists:
William Mark, PhD, President, Information and Computing Sciences, SRI
Anthony Scriffignano, PhD, Senior Vice President & Chief Data Scientist, Dun & Bradstreet
10:15 Late Breaking Presentation
10:40 Coffee Break in the Exhibit Hall
11:15 Keynote: Towards Explainable and Ethical AI
Tolga Kurtoglu, PhD, CEO, PARC
Deep learning AI models are opaque and can institutionalize biases and errors. We are building models that are transparent and make it much easier to spot (and remove) biases in the training data. Such technological advances are necessary but not sufficient.
So, we are developing an AI institutional review board (IRB) to review the data collection and modeling methods to ensure that they are ethical.
11:45 Plenary Roundtable: Connecting the Nation’s Healthcare Data
Dr. Siddiqui will discuss the implementation of HHS’s enterprise data strategy focused on leveraging data for decision making. She will also address the Department’s approach to the development of an AI strategy and the elements of institutional
capacity building required to fully utilize its data assets.
Moderator: Mona Siddiqui, MD, Chief Data Officer, U.S. Department of Health & Human Services
Panelists: Speakers TBA
12:10 Lunch Break
12:20 Luncheon Keynote: Unlocking the Value of AI/ML – a VMware Perspective
Robert Ames, Senior Director,
National Technology Strategy, VMware Research, VMware
Artificial intelligence (AI) and machine learning (ML) offers tremendous opportunities for many organizations, but advancing its use from experimentation to production deployment requires powerful, resilient, and adaptive IT infrastructure to support
the entire AI/ML pipeline. Mr Ames will describe how AI/ML techniques can be used to deliver on the vision of a high-scale resilient, and secure self-driving data center.
12:40 Dessert and Refreshment in the Exhibit Hall
Wednesday, June 26 | 8:50 am – 12:10 pm
7:45 am - 3:00 pm Registration Open
7:45 am Morning Coffee
8:50 Conference Chair Introduction
Scott Lundstrom, Group Vice President and General Manager, IDC and AI World Government, Conference Co-Chair
9:00 Keynote: Putting the “AI” in Air Force: Pragmatic Principles for the Future
Captain Michael Kanaan, Co-Chair for Artificial Intelligence, U.S. Air Force
Those at the forefront of using AI applications to accomplish their personal and organizational pursuits will enjoy significant new opportunities and advantages, including control of tools that analyze more information and prescribe more strategies than
ever before. Along the way, however, there will be costs. Some will be unexpected and some will be significant, particularly for those who lag behind. In the age of AI, second place will be of ever-diminishing value. Hear about the Air Force’s
path forward and lessons learned for organizations also moving along the way.
9:30 Keynote: Infrastructural Components to Enable AI and Machine Learning at NASA
Brian Thomas, PhD, Agency Data Scientist and Program Manager for Open Innovation, NASA
With decades of project and mission data at NASA, the job of managing the data and keeping it accessible is outpacing the capacity of its personnel. Current IT infrastructure is inadequate to tackle many important problems at NASA that require artificial
intelligence and machine learning. This keynote provides insight into the desirable infrastructural components to enable these solutions.
10:00 Keynote: Talk Title to be Announced
Paola M. Santana, Founder & CEO, Social Glass
10:30 Coffee Break
10:50 Plenary Roundtable: Talk Title to be Announced
Moderator: Bill Valdez, President, Senior Executives Association
11:35 Keynote: The Sublime Uses of AI in the Public Sector
Sara Mattingly-Jordan, PhD, IEEE Global Initiative for Ethical AI, Assistant Professor Center for Public Administration & Policy Virginia Tech
Does the public sector have a special obligation to get AI ethics “right”? How would we, in the public sector, know that we had “gotten it right”? Calls for someone, anyone it seems, to intervene on the consequences of the
uses of AI has led to a burgeoning pile of books, reports, articles, listicles, and value statements. Many of these reports imply that the uses of AI by governments is somehow different than the uses of AI by private actors. Wrapping our policies
around the challenge of developing and deploying ethical AI in the public sector requires wrapping our heads around the sublime nature of AI. To do this means we need a vocabulary to describe the enormity of AI and its effects. This brief talk
outlines the resources to build and use just such a vocabulary.
12:10 pm Enjoy Lunch on Your Own
3:30 Panel: Looking to Future in AI in Government
Conference attendees and speakers from AI World Government gather together at this closing plenary session to look at what we’ve learned over the week. Strategic recommendations from industry research firm IDC summarize the challenges and opportunities
that lie ahead for public sector agencies in their quest to accelerate the use of artificial intelligence to help address agency missions.
Moderator: Scott Lundstrom, Group Vice President and General Manager, IDC and AI World Government, Conference Co-Chair
Panelists: Shawn McCarthy, Research Director, IDC Government Insights, IDC
Adelaide O’Brien, Research Director, Government Insights, IDC
Curt Savoie, Research Director – Smart Cities, IDC
Tuesday, June 25 | 1:30 - 5:00 pm
Track Chair: 
Shawn McCarthy, Research Director, IDC Government Insights
Track Description: Agencies have been accumulating data for many years. However, organizations also realize they have not gained many benefits from the datasets. Along with an increase in unstructured data, there has also been a rise
in the number of data formats. Administrative data, such as notes and articles, as the primary data type have expanded to include images, audio, video, and sensors.
Many organizations fail to consider how quickly a big data project scales. Constantly pausing a project to add additional resources cuts into time for data analysis. Assessing what data exists and its integrity – completeness, accuracy, bias
and trust – prolong the analysis effort. This challenge is further compounded by integrating disparate data sources and securing big data.
This track addresses the major challenges faced by Big Data environments with an emphasis on identifying what data you have, how to source additional data, how to organize it, how to clean it, how to prepare the data for use in a machine learning
application, and ultimately, how to integrate and scale the application into the Agency’s IT systems.
1:30 Track Chair Opening Remarks
Shawn McCarthy, Research Director, IDC Government Insights
1:35 pm Panel: Getting Your Data Ready for AI
The basic challenge of working with data is understanding what you have and what you need. From auditing your data to cleaning and labeling it, preparing your data for quality, relevance, and trust is the most important
step you will undertake in your Big Data + AI journey. This panel highlights the importance of identifying the agency objectives, creating a strategy for capturing, structuring, and maintaining data, and steps to monitor and
govern data performance.
Moderator: Sukumar R. Iyer,CEO, Brillient and Chair of Intelligent Automation Working Group, ACT-IAC
Panelists:
Jeff Butler, Director of Data Management, IRS
Chris Devaney,
Chief Operating Officer Executive - Business Operations, DataRobot
Lori Ruderman,
Senior Advisor, US Department of Health and Human Services, HHS ReImagine BuySmarter
Michael Conlin, Chief Data Officer, U.S. Department of Defense
2:30 Finding Early Success with Intelligent Automation and Big Data
Edward Preble, PhD, Research Data Scientist, Center for Data Science, RTI International
This presentation will discuss what works, and what doesn't, in AI related projects. AI-driven use cases for the Bureau of Justice Statistics (BJS) and the National Center for Health Statistics (NCHS) will be presented along with specifics for
how to evaluate projects for AI-readiness, how to pick the right problems to focus on, and how to begin with small projects that then grow into real-world success stories.
3:00 Refreshment Break in the Exhibit Hall
3:30 Government Data Center Analytics
Shawn McCarthy, Research Director, IDC Government Insights
Shawn will provide a presentation on the state of AI as it applies to Data Center Infrastructure Management, and how that can be used to leverage agencies compliance with the requirements of the federal Data Center Optimization Initiative. The
focus of AI in government data centers is on improving energy consumption, network traffic, processor and virtual machine load balancing, and more.
4:15 A Framework for Automating Data Acquisition and Operationalization
Anil Tilbe, Director of Enterprise Measurements & Design, Veterans Experience Office, U.S. Department of Veterans Affairs
Lee Becker, Chief of Staff, Veterans Experience Office, U.S. Department of Veterans Affairs
5:00 Networking Reception in the Exhibit Hall
6:00 Meetup Groups
7:30 Close of Day
tuesday, June 25 | 1:30 - 5:00 pm
Track Chair: 
Adelaide
C. O'Brien, Research Director, Government Insights, IDC
Track Description: In evaluating the potential applications for intelligent automation, fundamental questions revolve around “How do I get started in Artificial Intelligence and what are the best applications where AI can
and should be deployed?” In many cases, the answers have less to do with technology choices and more to do with evolving the organization’s culture and mindset. As processes transition from Business Intelligence and Performance
Management to AI- and data-driven strategic roles and functions, agencies and departments will face common opportunities to refine the future of work.
This track looks at alternatives to building Data Science teams and strategies
for enabling a data-driven workforce.
1:30 Talk Title to be Announced
SAS Executive to be Announced
2:00 Bridging Policy and the Mission with Computer-Based Models
Corey Lofdahl, PhD, Principal Engineer, Systems & Technology Research (STR)
Academic researchers have for decades investigated how computers and Artificial Intelligence (AI) can help address complex government policy problems, but few of these efforts have paid off or proven workable. This talk covers the key policy problems
faced by senior decision makers, the early promise of AI, why AI research has been slow to transition to real-world applications, and how an increased appreciation of human factors supports that transition.
2:30 Personnel, Supply Chain & Logistics
Lindsey Sheppard, Associate Fellow, International Security Program, Center for Strategic & International Studies (CSIS)
Explore the common challenges and opportunities faced in these public sector roles and functions. If we are a nation where we are doing better by our people, how can government personnel be empowered to create more efficient processes supported
by data? This talk examines the organizational challenges to implementing data-driven projects in Personnel, Supply Chain & Logistics.
3:00 Refreshment Break in the Exhibit Hall
3:30 Leveraging AI in the Automation of Government Accounting and Reporting
Speaker to be Announced
Professionals frequently perform activities that may not require their expertise. Utilizing AI could free up their time to perform higher-value tasks. Accountants, for instance, may analyze hundreds of contracts looking for patterns
and anomalies, which relies more on reading skills than accounting skills. The use of intelligent automation and AI technologies could reduce human error and increase workflow by scanning and extracting
contract terms. Similarly, rules exist for standard reporting and compliance content. Automation could speed the process by automatically generating reports for human review. This talk separates fact from fiction about
the use of and value from automation in government accounting and reporting.
4:15 Panel: Intelligent Automation and AI at NASA
In the latest NSF Statement on AI for American Industry, "The effects of AI will be profound. To stay competitive, all companies will, to some extent, have to become AI companies." Compared to both industry and academia, NASA and its research
sites have specific challenges as well as resources that are particularly adapted to the use of AI. They have a wealth of data and information to leverage and "learn" from. And many science- and mission-oriented applications have been identified
that can benefit from learning on previous data and from domain and expert knowledge. This panel of representatives from multiple NASA research centers share how intelligent automation and AI is advising mission planning and operations, discovering
correlations in large amounts of science data, and enabling new tools and intelligent user interfaces to improve outcomes.
Moderator: Jeff Orr, AI World Content Director and AI Trends Editor, Cambridge Innovation Institute
Panelists:
Daniel Crichton, Program Manager, Principal Investigator, and Principal Computer
Scientist, NASA's Jet Propulsion Laboratory
Nikunj Oza, PhD, Leader of the Data Sciences Group, NASA Ames
Research Center
Barbara
Thompson, Solar Physicist, Lead of the Center for HelioAnalytics, NASA Goddard Space Flight Center
5:00 Networking Reception in the Exhibit Hall
6:00 Meetup Groups
7:30 Close of Day
Tuesday, June 25 | 1:30 - 5:00 pm
Track Chair: Curt Savoie, Program Manager, Global Smart Cities Strategies, IDC
Track Description: To achieve the title of Smart City, municipalities must enhance existing services, while at the same time innovate and deploy new applications and capabilities. For existing services, organizations are utilizing
predictive models to gain operational efficiency, such as using data to enhance asset location. Big data is also aiding in the delivery of a better user experience (UX). Artificial intelligence can also be applied in a host of other specific
areas, such as the preparation for autonomous vehicles and smart mobility systems, as well as planning and regulating of new service delivery.
This track examines the design and governance of the Smart City utilizing data and intelligent automation. Focus is given to three specific aspects of the Smart City: digital government and citizen services, transportation, and public safety.
1:30 Late Breaking Presentation
2:00 pm Delivering Effective Citizen Services
Thanh Van Nguyen, Minister of Public Security Ministry, Former Governor of Hai Phong, Vietnam
The world’s population is growing and become more in need of public services. Our current treatment model will not be sustainable in the future. As AI and other technologies are emerging – could this be used preventively and
make public servants guide our citizens well before they even know they’ll need it?
2:30 Panel: Identifying Targeted Public Safety Applications for Your AI Digital Transformation
Public safety agencies globally are leveraging AI in their day-to-day operations to work faster, smarter, and to redress some of the additional difficulties being created by the digital deluge. This panel explores some best practice examples
of agencies on the cutting edge of AI and ML implementations, as well as discusses how to deploy AI responsibly. This is critical to meeting citizen expectations about police capabilities, as well as help with information sharing endeavors,
and rebuilding trust in an era that has witnessed the decline of public confidence in law enforcement agencies. Attendees will learn:
- What are the obvious and less obvious ways in which AI can fundamentally transform data-driven public safety?
- What are some of the lesser known implementation inhibitors for law enforcement agencies?
- What are best practices recommendations from mature AI agencies and organizations?
Moderator: Alison Brooks, PhD, Research Vice President, Smart Cities and Communities –
Public Safety, IDC
Panelists:
Rich
Brown, Director, Project VIC International
Noah Spitzer-Williams, Principal Product Manager, Redaction AI and Transcription AI, Axon Technologies
3:00 Refreshment Break in the Exhibit Hall
3:30 Panel: Strategies for Developing AI-Based Applications & Services for Transportation
As autonomous vehicles come closer to closer to reality in cities and on the nation’s roadways, the decision-making around AI can have significant impacts for government, not only for road safety and traffic management but for urban
society at large. This panel session presents various strategies and perspectives on the topic from an auto OEM to that of a city to capture the progress and thinking on AI decision-making in cars, and where the dialogue stands today
between industry and government
Moderator: Mark Zannoni, Research Director, Smart Cities & Transportation, IDC
Panelists:
Diana Furchtgott-Roth, Deputy Assistant Secretary for Research and Technology, U.S. Department of Transportation
Karina Ricks, Director of Mobility and Infrastructure, City of Pittsburgh
4:15 Panel: AI in Smart Cities, Campuses, and Communities
From public safety to resilience and environmental monitoring, to population health and the government consumer experience, there are many uses cases for AI in smart ecosystems and communities. This panel will explore government services
that rely heavily on large amounts of data and that could be transformed via AI and automation. Thie discussion will focus not only on the transformative effect of AI, but the necessary short and medium terms steps needed to develop
effective AI platforms. This is especially important when looking at services that often transcend municipal boundaries and require the participation of many agencies, community groups, and private sector stakeholders. Takeaways
for attendees include:
- What services and programs can be transformed by AI and automation to deliver key outcomes for public health and safety?
- What must be in place now to develop these services in the future? What do government organizations need to put in place around data architecture, IT policies, and IT infrastructure to enable AI?
- What are best practices for how groups of stakeholders can effectively work together to work on large-scale challenges?
Moderator: Ruthbea Clarke, Vice President IDC Government Insights, IDC
5:00 Networking Reception in the Exhibit Hall
6:00 Meetup Groups
7:30 Close of Day
wednesday, June 26 | 1:15 - 4:00 pm
Track Chair: Kathleen Walch, Managing Partner, Principal Analyst, Cognilytica
Track Description: Once the initial Big Data challenges have been overcome, what does an organization do with the data? How can it use AI to accelerate digital transformation strategies? Having more data doesn’t
necessarily lead to actionable insights. A key challenge for data science teams is to identify a clear objective and determine the most impactful questions. Once key patterns have been identified, agencies must also be prepared
to act and make necessary changes in order to demonstrate value from them.
This track explores the delivery of services and applications powered by learning systems.
1:15 pm The Evolution of a Unified AI Approach to Data Science at NASA GSFC
Mark Carroll, PhD, Research Scientist, Computer and Information Science and Technology Office, NASA
Data holdings at NASA are growing at a geometric rate. Traditional methods of analyzing these data are insufficient to produce answers in a reasonable time frame. Scientists have turned to machine learning and Artificial
Intelligence methods to facilitate the analysis of the large volumes of data. Here we present several of these projects and outline our plan to develop a unified approach to data science that incorporates AI.
1:40 Panel: Adoption, Best Practices, and Successful Deployment of Process Automation
The federal government is facing unprecedented operating challenges as they manage mounting budget constraints while trying to be more agile to increase mission objectives. Unable, in many cases, to hire more employees, federal
agencies are forced to spend dollars on contractor support or shift resources away from mission-critical work to handle routine, manual tasks. Robotic process automation (RPA) provides federal agencies the capability to operate
more efficiently with reduced resources. Hear from government thought leaders and subject matter experts who will discuss their adoption, best practices, and successful deployment of RPA.
Moderator: Prabhdeep (PD) Singh, Vice President, AI, UiPath
Panelists: Speakers TBA
2:15 Networking Break
2:25 Using NLP and Big Data to Deliver High-Value Decision Making
Speaker to be Announced
3:00 Planning for Desired Outcomes with Recommender Systems
Sung-Woo Cho, PhD, Senior Associate/Scientist, Social and Economic Policy, Abt Associates
The abundant data that are regularly collected from federal agencies are ripe for the application of artificial intelligence, provided that they are collected in a secure manner with the benefit of service recipients as the
sole reason for these solutions. Predictive analytics and recommender systems can provide these agencies with the necessary tools to help guide their service recipient clients towards optimal outcomes, by leveraging structured
and unstructured data alike.
4:00 Close of AI World Government 2019
Wednesday, June 26 | 1:15 - 4:00 pm
Track Chair: Jeff Orr, AI World Conference Content Director and AI Trends Editor, Cambridge Innovation Institute
Track Description: Despite the recent interest in using algorithmic models for data analysis and insight, the underlying methodologies and protocols have been proven for decades. Researchers are experimenting
with new ideas that leverage these time-tested frameworks.
This track provides attendees with a roadmap for the evolution of AI technologies in the next few years. How will trust and explainability be resolved
by the industry to become integral components of future machine learning solutions? Which emerging AI solutions and technologies will be evolving out of research labs in the near term, enabling new classes of productive
applications? What will the next generation of AI-optimized hardware look like? What can we expect from the next generation of biometric technologies?
1:15 pm Explainable AI: The Need for Transparency and Auditability of “Black Box” Systems
Speaker TBA
Organizations and end-users need a way to explain why the AI made a prediction. Government watchdogs and regulators are reluctant to embrace intelligent systems without some explanation of how the data input generated the machine
output. This talk further explores the need to audit and report on decision-making and why human interpretable explanations are necessary for multiple audiences.
- Discuss what is meant by explainable AI and what is it that agencies and regulators want to know about predictions
- Understand the trade-off between AI transparency and performance along with the implications for intellectual property
- What is the current state of the technology in delivering truly explainable AI systems?
- As narrow AI implementation scales to address complex business judgments and Artificial General Intelligence (AGI), does the demand for explainable AI increase?
1:40 Panel: Implementing Advanced AI Technologies
Machine learning (ML) is currently viewed as a single tool. However, ML is not a static environment. Researchers have already developed advanced technology to evolve ML to process larger amounts of data even faster. Some developers,
for example, are examining how ML can incorporate blockchain for safety and security within the ML model. ML in its various forms are being integrated into and with other highly advanced intelligent systems such as NLP,
image processing, etc. for multitudes of applications. This panel of AI and data science researchers is pushing the bleeding edge of emerging technology and identifying the future of ML.
Moderator: Ola Olude-Afolabi, PhD, Adjunct Prof., Morgan State University
Panelists:
Brad Mascho, Chief Artificial Intelligence Officer, NCI Information Systems, Inc.
Jesus Jackson, Senior Director & Head, eGT Labs
Kashyap Kompella, CFA, CEO and Chief Analyst, rpa2ai
2:15 Networking Break
2:25 Application Concepts for AI at the Edge
Antigone Peyton, JD, Chair, Intellectual Property and Technology Law Group, Protorae Law
PLLC
As organizations develop a deeper understanding of how AI might be used to support their missions, they must also confront challenges regarding deployment of intelligence in equipment and devices at the edge of networks or
connected through the Internet of Things. This talk will share design considerations for “skinny AI,” use cases ranging from smart cities to field deployment, practical pointers relating to security, anonymity,
and system trust, and edge AI training trends.
3:00 Hardware's New Frontier: Non Deterministic Analog Super Turing Machines
Lars
Wood, CEO & Co-Founder, QAI.ai LLC
Current machine learning is restricted to computable numbers, which limits their application to solving narrowly defined solutions with inherent bias and the tendency to completely forget previously learned information upon
learning new information. Non deterministic super Turing machines solve problems like biological brain networks with uncomputable real numbers. This talk provides an overview of the history of super Turing machines, their
first proof of principle, and how to design and build machine learning systems that use non computable real number analog networks to develop adaptive AI systems.
4:00 Close of AI World Government 2019
Wednesday, June 26 | 1:15 - 4:00 pm
Track Description: Organizations can effectively leverage automation in governance, risk management, compliance and security as they move to a digital platform for the future. Change in stewardship of data
is afoot including how data ownership, retention, and public records are managed. Algorithmic modeling solutions deliver efficient analysis, though the “black box” question of how insights are arrived at remains
an open issue where transparency and auditability are needed.
This track highlights the opportunity to use AI and automation to meet existing compliance reporting, as well as prepare for new legislation on data
privacy and protection.
1:15 Late Breaking Presentation
1:40 De-Identification of Video Data for Public Sector Research
David Kuehn, Program Director, Exploratory Advanced Research Program, Federal Highway Administration
The Second Strategic Highway Research Study (SHRP2) collected over one million hours of driving data from over 3,000 volunteers. To preserve privacy, researchers only can view images of drivers which are critical
for understanding behavior, available to more researchers at a secure data enclave. To make driver image data, which are critical for understanding behavior, available to more researchers, the government is developing
machine learning tools that mask driver identity while preserving head pose and facial behavior.
2:15 Networking Break
2:25 The Regulatory Landscape and Designing Trust into Data-Driven Systems
Daniel Wu, JD, PhD, Privacy Counsel and Legal Engineer, Immuta
To put you one step ahead of the curve, we offer 7 legal principles and 3 tools. The principles give you a framework to interpret and prioritize existing and new data regulations, while the tools help you protect your
customer’s data -- and trust -- by embedding it into the very design of your data operations.
3:00 Creating Organizational Value from Machine Learning
Jun Heider, CTOO, RealEyes Media
The public sector needs to meet compliance standards with limited resources. As media volume grows, compliance success becomes increasingly difficult for human workers alone. Learn to successfully leverage machine
learning to optimize and automate media compliance and monitoring workflows. Attendees will be provided with the knowledge and resources to get started and accelerate their transition to compelling machine learning
workflows: redaction, transcription, translation, and media compliance monitoring.
4:00 Close of AI World Government 2019