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:
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.
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.
United Nations: 193 Countries adopt first-ever global agreement on the ethics of artificial intelligence, by UN Staff
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.
However, the agency warns that the technology ‘is bringing unprecedented challenges’.
Brookings: How robotic process and intelligent automation are altering government performance, by Darrell M. West
Government agencies are changing to become more efficient and effective. Set up for industrial-era operations, many public sector organizations are hierarchical, function on command and control principles, are labor intensive, and do not sufficiently employ digital tools for handling routine processes.
The results are high costs, unresponsive organizations, and public dissatisfaction. People see government as bloated and inefficient, and not serving the public interest. They worry whether government is up to the task of dealing with new challenges in public health, education, transportation, commerce, and national defense. Many individuals do not see government agencies rising to the needs of the 21st century and fear America is slipping behind other nations.
Governing: Can artificial intelligence help improve wildfire recovery, by Jed PressgroveArtificial intelligence stands to change wildfire recovery and containment forever during a time when fires in the West are doing things that seasoned firefighters of 40 years have never seen.
Nextgov: DISA moves to combat intensifying cyber threats with artificial intelligence, by Brandi Vincent
In the near term, Defense Information Systems Agency officials plan to strategically employ artificial intelligence capabilities for defensive cyber operations.
“First of all, the threat has never been higher. It's also been commoditized: Malware has become commercialized as essentially organized crime on an international scale,” Deputy Commander of the Joint Force Headquarters-Department of Defense Information Network Rear Adm. William Chase III, told reporters during a media roundtable last week. “So, one of the first questions we have to ask ourselves is: ‘What are we actually vulnerable to?’”
The press event was associated with DISA’s Forecast to Industry and the release of its strategic plan for 2022 through 2024.
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.
About half of NASA’s workforce will be eligible to retire in the next five years. That represents a lot of institutional knowledge, subject matter expertise and activity that needs to be passed on to the next generation. John Dankanitch, chief technologist at NASA Marshall Space Flight Center, said natural language process can help, specifically by making that expertise searchable.Read The Full Article