Page 11 - FCW, November/December 2021
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blueprint for the National AI Research Resource (NAIRR), as specified in the National AI Initiative Act of 2020. The
White House described NAIRR as “a
shared research infrastructure providing AI researchers and students across all scientific disciplines with access to computational resources, high-quality data, educational tools and user support” with the goal of spurring AI innovation and economic prosperity.
The National Science Foundation recently announced that it was adding 11 National
AI Research Institutes to the seven institutes NSF funded in 2020. That brings the agency’s investment to $220 million across 40 states and the District of Columbia. NSF’s announcement states that the institutes focus on a range of advances, including “helping older adults lead more independent lives
and improving the quality of their care; transforming AI into a more accessible ‘plug- and-play’ technology; creating solutions to improve agriculture and food supply chains;... and supporting underrepresented students in elementary to post-doctoral STEM education to improve equity and representation in AI research.”
Several state governments have also launched AI policy initiatives. For example, Vermont’s AI Task Force issued a report that recommends establishing a permanent AI commission and creating a framework for policy development “that will harness [AI’s] power for the greater good of Vermonters.” Washington state and Alabama have created commissions to establish guidelines on the procurement and use of AI.
A bright future for AI in government
According to a report commissioned by the Administrative Conference of the United
States, 45% of federal agencies have dabbled in AI. The category of “regulatory research, analysis and monitoring” had the most use cases, followed by “enforcement” and “public services and engagement.” However, the report notes that agencies are at different stages of AI adoption, and only 33% of the use cases were fully deployed.
by the numbers
FCW survey respondents who said their agencies are using AI-based tools for data analysis
Government organizations that will establish formal accountability structures for data sharing by 2023
Robotic process automation solutions in the federal RPA Use Case Inventory
$40 billion
National Security Commission on AI’s proposed investment to expand and democratize federal AI research and development
Sources:, FCW, Gartner, National Security Commission on AI
In the recent survey of FCW
readers, the most common AI
projects involved cybersecurity
(50%), data science (38%) and
data labeling (25%). Furthermore, 47% of respondents said their agencies were using AI-based tools for data analysis and 44% were using them to streamline workflows.
Many agencies first deploy AI to automate routine processes. When they were overwhelmed by record demand
for information from the public during
the pandemic, a number of agencies turned to robotic process automation.
For example, state and local governments deployed chatbots to help with the deluge of unemployment insurance applications, and the Centers for Disease Control and Prevention launched the Coronavirus Self- Checker to help people decide when they should seek testing or medical care.
Beyond the pandemic, the Securities and Exchange Commission has developed the Corporate Issuer Risk Assessment to detect fraud in accounting and financial reporting. The machine learning tool can detect anomalies in financial reporting and identify potential misconduct.
Research firm Gartner sees a bright future for AI in government. In terms
of the technology changes necessary to boost the government’s ability to adopt AI, Gartner predicts that more than 50% of agencies will have modernized critical core legacy applications to improve resilience and agility by 2025. Gartner also said
75% of governments will have at least
three enterprisewide hyperautomation initiatives launched or underway by 2024. Hyperautomation refers to the orchestrated use of multiple technologies, tools or platforms to automate as many processes as possible.
AI isn’t as new as it might seem. John McCarthy coined the term “artificial intelligence” in 1956 and defined it as “the science and engineering of making intelligent machines.” Although it has taken some time for the technology to evolve, industry leaders are now working closely with government agencies to achieve the promise of AI by making tools easier to scale, manage and use in real-world applications. Thanks to those ongoing technological advancements and the growing number of government initiatives, the AI revolution is picking up speed.

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