カンファレンスプログラムと分科会






( 全体セッションに登場予定の講演者 )


6月25日(火) | 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 Plenary Roundtable: The Role of Data in AI, the Intersection Between Physical and Digital Data, Security, Ethics and Privacy

Seseri_RudinaModerator: Rudina Seseri, Founder and Managing Partner, Glasswing Ventures


Davis_KevinPanelists: Kevin Davis, CSO, Armored Things 


Hazel_ThomasThomas Hazel, Founder, CTO, and Chief Scientist, CHAOSSEARCH 


Noble_PaulPaul Noble, Founder, CEO, Verusen


10:40 Coffee Break in the Exhibit Hall


11:15 Keynote: Towards Explainable and Ethical AI

Minhas_RajRaj Minhas, PhD, Vice President, Director of Interaction and Analytics Laboratory, 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 Keynote: Connecting the Nation’s Healthcare Data

Mona Siddiqui, MD, Chief Data Officer, U.S. Department of Health & Human Services

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.

 

12:10 Lunch Break


12:20 Luncheon Keynote: Unlocking the Value of AI/ML – a VMware Perspective

Ames_RobertRobert 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

6月26日(水) | 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


Kanaan_Mike9:00 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: Building Public/Private Coalitions to Promote Shared Approaches to AI Governance, Big Data & Ethics 

Our exponential era is creating ripple effects that impact how we co-exist as communities and societies regarding AI Governance, Big Data, and Ethics. Some experts are concerned about what they call “surveillance capitalism” and others are concerned that open societies cannot survive waves of misinformation and disinformation.   

A coalition needs to come together from across sectors (public and private) and nations to advance a shared approach to AI Governance, Big Data, and Ethics.  This coalition should be an influential voice when open, pluralistic societies head into the exponential era ahead. 

Moderator: Bill Valdez, President, Senior Executives Association


Furgione_LauraPanelist: Laura Furgione, Chief, Program, Performance and Stateholder Integration, Department of Commerce, Census Bureau


Mattingly-Jordan_Sara11:35 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 Closing Plenary Session: 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


McCarthy_ShawnPanelists: Shawn McCarthy, Research Director, IDC Government Insights, IDC 


OBrien_AdelaideAdelaide O’Brien, Research Director, Government Insights, IDC


Savoie_Curt Curt Savoie, Research Director – Smart Cities, IDC




OVERCOMING THE AI & BIG DATA CHALLENGE

( AIとビッグデータの課題克服 )

各国の政府機関は、長年にわたってデータを蓄積していますが、これらのデータセットが十分に活用されていないという点も認識しています。この背景には、非構造化データが増えているだけではなく、データフォーマットの種類も増えているという問題があります。記録や条項などの行政データは近年範囲が広がっており、主要なデータタイプとして画像や音声、動画、センサーデータまで包含するようになっています。

行政機関の多くは、ビッグデータプロジェクトの規模が急速に拡大するという点を考慮していないため、プロジェクトを中断して新たにリソースを追加し、時間を割いてデータ解析を行わざるを得ないといった事態がしばしば発生します。データの種類とその整合性 (完全性、正確さ、バイアス、信頼性) を評価するには、アナリストによる長時間の作業が必要であり、異なるデータソースの統合やビッグデータの保護といった作業が加わることで、この問題はさらに深刻化します。

この分科会では、保存されているデータの種類を特定し、追加データを収集し、データを体系化し、クリーンなデータを確保し、機械学習で利用するデータを準備する方法や、政府機関のITシステムにアプリケーションを統合し、拡張する方法などにスポットライトを当てながら、ビッグデータ環境が直面する主な課題について議論します。

6月25日(火) | 1:30 - 5:00 pm

Track Chair: Shawn MccarthyShawn 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. 

Iyer_SukumarModerator: Sukumar R. Iyer,CEO, Brillient and Chair of Intelligent Automation Working Group, ACT-IAC


Panelists:

Jeff Butler, Director of Data Management, IRS


Devaney_ChrisChris Devaney, Chief Operating Officer Executive - Business Operations, DataRobot


Ruderman_LoriLori Ruderman, Senior Advisor, US Department of Health and Human Services, HHS ReImagine BuySmarter 


Michael Conlin, Chief Data Officer, U.S. Department of Defense 


Preble-Edward2:30 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


USING AI FOR STRATEGIC GOVERNMENT FUNCTIONS

( 政府機関の戦略的な業務にAIを活用する取り組み )

インテリジェントオートメーションの有望な応用分野を評価する際には、「どのような形でAIの導入作業に着手すれば良いのか、AIの導入が可能あるいは導入すべき最適な応用分野はどこなのか」という根本的な問いへの答えを見つけ出す必要があります。こうした問いへの答えは、往々にして技術の選択よりも、組織の文化や考え方の進化に大きな影響を及ぼします。ビジネスインテリジェンスやパフォーマンス管理から、AIやデータを駆使した戦略的な任務や機能へとプロセスを移行させる過程で、行政機関や部局における今後の仕事のあり方を改善するチャンスが生まれるのです。

この分科会では、データサイエンスチームを構成するための方策やデータ重視の労働環境を実現するための戦略が焦点となります。

6月25日(火) | 1:30 - 5:00 pm

Track Chair: Adelaide ObrienAdelaide 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 From Artificial to Real: Examples and Stories About AI Making a Difference in the Public Sector Around the World

Bennett_SteveSteve Bennett, Director, Global Government Practice, SAS, Former Director of the U.S. National Biosurveillance Integration Center in the Department of Homeland Security 

 

Traditional approaches to gleaning insights from data are no longer sufficient given the volume, velocity and variety that modern governments must manage. It is becoming increasingly critical for governments to find new ways to transform data into actionable information – new ways that include techniques like artificial intelligence (AI) and machine learning.  

In this session, we will briefly review government domain areas with the largest potential for benefit from AI, and then spend most of our time talking about stories from around the world in which these techniques have made a difference in the public sector. 

 

Lofdahl_Corey2:00 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. 

Sheppard_Lindsey2:30 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 Automatically Extracting Meaning from Government Documents

Stephen Strong, Sr. Lead Technologist, Booz Allen Hamilton 

Boujakjian HaroutHarout Boujakjian, Data Scientist, Booz Allen Hamilton

 

This presentation will describe and show new online tools in the current phase of a long-range project in argument mining (extracting reasoning patterns from governmental documents). These tools extract meaningful spans of text from decisions of the Board of Veterans’ Appeals, which are the same spans of text that a lawyer would want to read from those decisions. Such extracted spans are useful components for summarizing past decisions, for making the decision process more efficient, or for suggesting arguments in new cases. These tools and methodologies are applicable to any legal area and to any claims process, as well as to any area requiring regulatory compliance. 

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:

Crichton_DanielDaniel Crichton, Program Manager, Principal Investigator, and Principal Computer Scientist, NASA's Jet Propulsion Laboratory


Oza_NikunjNikunj Oza, PhD, Leader of the Data Sciences Group, NASA Ames Research Center


Thompson_BarbaraBarbara 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


ACCELERATING SMART CITIES WITH AI-POWERED SERVICES

( AIを利用したサービスによるスマートシティ実現に向けた作業の加速 )

Track Description: 自治体がスマートシティの称号を得るには、既存のサービスを強化すると同時に、新たな応用技術や機能を開発し、配備する必要があります。既存のサービスに関しては、多くの組織が予測モデルを利用した業務効率の改善に取り組んでおり、データを駆使してアセットロケーションを強化するなどの動きも生まれています。またビッグデータをユーザーエクスペリエンス (UX) の改善に役立てるための取り組みに加え、自動運転車やスマートモビリティシステムの導入に向けた準備、新たなサービスを提供するための計画立案や規制整備など、個別の分野にAIを応用する動きも広がっています。

この分科会は、データとインテリジェントオートメーション技術を利用したスマートシティの設計とガバナンスについて考えるもので、デジタルガバメントと市民サービス、輸送、公衆安全というスマートシティの3つの具体的な側面が焦点となります。

6月25日(火) | 1:30 - 5:00 pm

Savoie_Curt 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 AI and the Future of Cities

Savoie_Curt Curt Savoie, Program Manager – Global Smart Cities Strategies, IDC


2:00 pm Delivering Effective Citizen Services

Nguyen_ThanhThanh 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? 

Brooks_AlisonModerator: Alison Brooks, PhD, Research Vice President, Smart Cities and Communities – Public Safety, IDC


Panelists:

Brown_Rich Rich Brown, Director, Project VIC International


Spitzer-Williams_NoahNoah 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

Zannoni_MarkModerator: Mark Zannoni, Research Director, Smart Cities & Transportation, IDC


Panelists:

Diana Furchtgott-Roth, Deputy Assistant Secretary for Research and Technology, U.S. Department of Transportation


Ricks_KarinaKarina Ricks, Director of Mobility and Infrastructure, City of Pittsburgh 


Jeff Marootian, Director, District Department of Transportation  


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? 

 

Ruthbea ClarkeModerator: Ruthbea Clarke, Vice President IDC Government Insights, IDC


Savoie_CurtPanelists: Curt Savoie, Program Manager – Global Smart Cities Strategies, IDC


Kim Nelson, Executive Director, State and Local Government Solutions, Microsoft  


Jennifer Robinson, Director of Local Government Solutions, SAS 

 

 


Wines LindsayLindsay Wines, Chief of Staff, City of Baltimore


5:00 Networking Reception in the Exhibit Hall

6:00 Meetup Groups

7:30 Close of Day


SERVICES & BENEFITS OF AI-POWERED BIG DATA

( AIを利用したビッグデータがもたらすサービスと恩恵 )

当初指摘されたビッグデータの課題が克服された後浮上したのは、データを利用して何をするのか、AIを使ってデジタルトランスフォーメーション戦略を加速させるにはどうすれば良いのかといった問いであり、データの量が増えたからといって実用的な識見が得られるとは限らないという事実でした。現在データサイエンスの研究チームは、明確な目標を見極め、最も影響の大きい問題を決着させるという重要課題に取り組んでおり、行政機関の側も、重要なパターンが特定された後、ビッグデータがもたらす価値を実証するための作業を行って、必要な改革を実施するための準備を整える必要があります。

この分科会では、学習機能を備えたシステムを利用して各種のサービスや応用技術を実現する方法について考えます。

6月26日(水) | 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.

Carroll_Mark1:15 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: Speaker to be Announced

 

Singh_PrabhdeepPanelists: Prabhdeep (PD) Singh, Vice President, AI, UiPath



2:15 Networking Break

2:25 DoD AI Applications at the Joint Artificial Intelligence Center (JAIC)

Beall_MarkMark Beall, Chief of Strategic Engagement and Policy, Joint Artificial Intelligence Center's (JAIC)


Maj Daniel Tadross, Predictive Maintenance, Joint Artificial Intelligence Center's (JAIC)

 

The DoD Joint Artificial Intelligence Center was established in 2018 to accelerate DoD’s adoption and integration of AI to achieve mission impact at scale. Since then, the JAIC has taken a holistic approach to operationally preparing the Department for the strategic advantages that a human-centered AI capability will bring to all functions – from business to the battlefield.

 

Sung-Woo Cho3:00 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


EMERGING AI TECHNOLOGIES

( 新たなAI技術 )

アルゴリズミックモデルを利用したデータ分析や情報収集に対する関心は近年高まっていますが、基本的な手法やプロトコルの有効性は数10年前に実証済みであり、現在多くの研究者が実績のあるこれらのフレームワークを利用した新たな着想の実験を行っています。

この分科会では、今後数年間のAI技術の進化についての展望が示され、将来の機械学習ソリューションの重要な要素となる信頼性と説明可能性の問題を解決するための方策、近い将来実用化され、生産性向上に貢献する新たな種類の応用技術へとつながる可能性のある最新のAIソリューションや技術、AIに対して最適化された次世代ハードウェアの姿、次世代のバイオメトリック技術に盛り込まれる機能などが紹介されます。

6月26日(水) | 1:15 - 4:00 pm

Track Chair: Jeff OrrJeff 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

Dimitry FisherDimitry Fisher, Chief AI Officer, Analytics Ventures/Dynam.AI 

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:

Mascho_BradBrad Mascho, Chief Artificial Intelligence Officer, NCI Information Systems, Inc.


Jackson_JesusJesus Jackson, Senior Director & Head, eGT Labs


Kashyap_KompellaKashyap Kompella, CFA, CEO and Chief Analyst, rpa2ai


2:15 Networking Break

2:25 Application Concepts for AI at the Edge

Antigone PeytonAntigone 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

Wood_LarsLars 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

 


USING INTELLIGENT AUTOMATION FOR COMPLIANCE, SECURITY & TRUST

( コンプライアンス、セキュリティ、信頼性の強化に向けたインテリジェントオートメーション技術の活用 )

今後デジタルプラットフォームへの移行が進めば、ガバナンスや危機管理、コンプライアンス、セキュリティなどの分野で自動化技術を効果的に活用することができるようになります。現在データ管理の分野では、データの所有権、保持、公記録管理などに関する改革が進められており、アルゴリズミックモデリングソリューションによる効率的な分析も可能になっていますが、透明性と監査可能性が求められる領域での情報の入手方法に関する「ブラックボックス」の問題は解決されていません。

この分科会では、AIや自動化技術を既存のコンプライアンスレポート作成業務に利用する可能性、データのプライバシーと保護に関する新たな立法措置への準備などのトピックが焦点となります。

6月26日(水) | 1:15 - 4:00 pm

Track Chair: Sumeet Vij, Chief Technologist, Strategic Innovation Group, Booz Allen Hamilton

 

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 Track Chair Introduction

Sumeet Vij, Chief Technologist, Strategic Innovation Group, Booz Allen Hamilton

Kuehn_David1:40 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

Wu_Daniel2:25 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. 

Heider_Jun3:00 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

* 不測の事態により、事前の予告なしにプログラムが変更される場合があります。

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更新履歴
2019/06/11
アジェンダ・講演者・スポンサー更新
2019/05/13
スポンサー更新
2019/04/26
アジェンダ・講演者・スポンサー更新
2019/04/05
スポンサー更新
2019/03/25
アジェンダ・講演者・スポンサー更新




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