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Thoughts from Our Fellows: Make Government AI-Ready

November 30, 2021

November 30, 2021

Welcome to Thoughts from Our Fellows, a collection of recent activity regarding the Academy's Grand Challenge of each Month. In November, the Academy focused on Make Government AI-Ready. Below you will find:

  • The recommendations from our Election 2020 project regarding the first year of the new administration,
  • Recommendations from our fellows for the next few years of the Biden Administration,
  • Management Matters podcasts related to this grand challenge, and
  • The top 5 clicked articles on this grand challenge from our Management Matters online newsletter.
Election 2020

In November of 2020, the Academy published a paper on this topic as a part of its Election 2020 Project. The Working Group recommended the following actions for its paper, Artificial Intelligence: An Agenda for 2021.

  1. Build trustworthy AI by establishing a single, authoritative, and recognized federal entity that focuses on AI’s social, cultural, and political effects and leverages existing investments to create guidance and solutions.
  2. Use ethical frameworks to identify and reduce bias in AI by demonstrating a federal government commitment to ethical principles and standards in AI development and use.
  3. Build intergovernmental partnerships and knowledge sharing around public sector uses of AI by developing an interagency and intergovernmental mechanism that addresses the need to share practices between different levels of government, incentivizes and stimulates broader AI adoption, and addresses gaps in readiness to build an AI workforce for all levels of government.
  4. Increase investments in AI research and translation of research to practice by increasing public access to federal government data, increasing by at least 50% investment into unclassified AI research, ensuring the protection of privacy at the individual level, and removing biases from programming to ensure equitable treatment.
  5. Build an AI-ready workforce by providing funding to support the growth of an AI-competent federal workforce, develop policies and fund incentives that encourage the AI R&D to use multidisciplinary teams, and support studies to increase understanding of current and future national workforce needs for AI R&D.

Thoughts from Our Fellows

In addition to our Election 2020 papers, which focused on recommended actions for the first year of a new administration, the Academy also asked its Fellows

“What should federal, state, and local leaders do now and over the next few years to ease concerns regarding the trustworthiness and transparency of AI? How can they spur innovation? What should they prioritize?”

Lee Feldman: The National Institute for Standard and Technology (NIST) should consider creating uniform standards for the implementation of AI by local government vendors.

James Hendler: The priority for leaders really needs to be on educating first themselves and their staffs, and then their 'constituencies' on what AI can and cannot do and where AI systems should and shouldn't be used. The policy space around AI is not as obvious as many people think, and the technology space comes with many misconceptions. Building trust in any system, and AI is not really different, requires knowing what the system can and cannot do, what the failsafes are, and how the deployment impacts current functions. Without this knowledge, vendors can push products claiming to be AI which aren't, or deploy AI in inappropriate ways. Either of these can lead to at the minimum bad publicity and in some cases very tragic outcomes, which undermine the appropriate deployments. Prioritization and innovation without knowledge will lead to more, not less, problems. Work with universities and other neutral (non-vendor) organizations to get training to the appropriate workforce. Anything else is a recipe for disaster.

Alan Shark: Since it appears that academic institutions have been unable to step up to the challenges regarding AI and technology leadership. In particular this unmet challenge impacts federal state and local governments who will need to supplement this deficit through developing their own training and workforce development programs that focus on AI and governance. Academia is weakest when it comes to inter-disciplinary (silos) programs and leadership. Government can and should create specific program requirements and seek competitive bids. Innovation of any kind, including AI, is about continuous process improvement and augmented decision making. The number one priority should be to develop programs that help government workers think critically and should also consider new management and governance schemes that allow for more creative management across the board. AI while dependent on technology must be managed by interdisciplinary teams that can view AI through multiple and critical lenses. Technology is now everyone's business and should not be relegated to IT or to computer scientists. AI and all its implications and possibilities must drive public management to a new techno-policy domain.

Related Podcasts

Grand Challenge: Make Government AI Ready
NAPA podcast-logo
AI Tools in the Federal Procurement Process With Soraya Correa

Fellow: Soraya Correa

Season: 1 Episode:80 | November 15, 2021

Grand Challenge: Make Government AI Ready Grand Challenge: Data Security
NAPA podcast-logo
Fall Meeting Preview: Technology, Innovation, and Digital Equity for the Future with Jane Fountain

Fellow: Jane Fountain

Season: 1 Episode:76 | October 18, 2021

Grand Challenge: Make Government AI Ready
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Preparing the AI Workforce of the Future with Kaye Husbands Fealing

Fellow: Kaye Husbands Fealing

Season: 1 Episode:32 | November 30, 2020

Grand Challenge: Make Government AI Ready
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Harnessing AI for State Governance with Doug Robinson

Fellow: Douglas Robinson

Season: 1 Episode:31 | November 23, 2020

Grand Challenge: Make Government AI Ready
NAPA podcast-logo
Public Administration, Technology, and the Future with Jay Walder

Fellow: Jay Walder

Season: 1 Episode:30 | November 16, 2020

Grand Challenge: Make Government AI Ready
NAPA podcast-logo
Using Technology at Different Levels of Government with Alan Shark

Fellow: Alan Shark

Season: 1 Episode:29 | November 02, 2020

Top 5 Articles on Make Government AI-Ready

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Artificial intelligence is present in everyday life, from booking flights and applying for loans to steering driverless cars. It is also used in specialized fields such as cancer screening or to help create inclusive environments for the disabled.

According to UNESCO, AI is also supporting the decision-making of governments and the private sector, as well as helping combat global problems such as climate change and world hunger.

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Over the last year, public safety teams have tested a new tool in western states like California and Oregon, and results have been promising. The tests involve imagery taken by a 360-degree camera both before and after a fire. Thanks to cloud computing and machine learning, that visual product can be transformed into mapping data that shows "what was damaged, where it was damaged and how badly it was damaged," said David Blankinship, chief technology adviser with WFCA.


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The press event was associated with DISA’s Forecast to Industry and the release of its strategic plan for 2022 through 2024.

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Federal News Network: Could AI help stave off the brain drain of federal retirement? by, Amelia Brust

Agencies need a way to transfer the knowledge of soon-to-be retiring employees, and one option might be artificial intelligence. Natural language processing (NLP) and automation are some of the technologies agencies are considering both to cope with an aging-out of the federal workforce, and to respond to new employee expectations resulting from the pandemic.

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