DHS ‘Black Belt’ Program Aims to Boost Workforce’s AI Skills

Federal agencies, like employers in the private sector, are recognizing the potential that artificial intelligence (AI) has to change and improve the way work gets done. 

Harnessing that potential is another matter. But government entities like the Department of Homeland Security (DHS) are making strides.

For example, the United States government’s third-largest Cabinet department is in the midst of creating a “black belt” program designed to help identify internal AI champions and experts, as the agency’s Chief Technology Officer David Larrimore recently told attendees at the ATARC Federal AI & Data Summit.

“What we’re trying to do around our black belt program is find who the experts are in the DHS organization, and we want to create a black belt for that specific concept,” said Lattimore at the Nov. 17 event, adding that the agency aims to identify AI experts in areas that include fraud, biometrics and statistic modeling.

As Federal News Network recently reported, the DHS program is in its early stages, and will rely on its “AI champions” to promote AI and data analytics across all aspects of the agency.

“Ultimately, you become a part of a larger community to help where people like you aren’t available,” Larrimore said at the ATARC summit. “Because there is no way that, of the 350 or so acquisition programs going on right now, everyone has someone who could be considered an AI black belt. Wouldn’t it be great if a black belt from [Customers and Border Protection] could go spend six months over in a FEMA program to help them get up and running?”

Noting that the department has made “huge strides” in data sharing in recent years, Lattimore said that DHS data maturity has been especially useful in immigration operations, and that the agency is seeking ways to use data to improve its customer experience and reduce the burden on its customers, according to Federal News Network.

Experimenting with AI

The DHS is not the only federal agency working to improve the overall data literacy of its workforce.

The Department of Defense (DoD), for example, has set a goal of being “AI-ready” by 2025, according to Federal News Network.

AI readiness will vary across the department, and the DoD’s Office of the Chief Digital and Artificial Intelligence Officer (CDAO) is taking steps to “right-size” AI education across a broad spectrum of positions, according to William Streilein, the CDAO’s chief technology officer, who noted that the DoD is also concentrating on data interoperability standards across the department.

“Somebody who’s in acquisition … at a high level, I would think somebody in that position needs to know that innovation is par for the course. You may not be able to actually inspect and provide requirements for how the model’s working, but you need to know what it needs to do. And so [performance] metrics are absolutely key,” Federal News Network reported.

“The first priority is data. It’s quality data, and so we’re bringing that message across the DoD, to our partners, to vendors, even internationally to help focus people on the fact that you need good data before you can leverage analytics and AI to bring new insights and things like that.”

Udaya Patnaik, the chief innovation strategist at the General Service Administration’s Federal Acquisition Service (FAS), told Federal News Network that agencies are looking for help on ways to start experimenting with AI and machine learning.

“We have agencies that are saying, ‘Help, we’ve got petabytes of data here, that we would love to be able to turn on some of the automated machine-learning-as-a-service tools that we could deploy onto it. We’re just scared of what comes out on the other side of this.’ And that’s a legitimate fear,” Patnaik said, adding that FAS is looking to provide “safe spaces” such as test beds and sandboxes with limited sets of data to test AI and machine learning before scaling projects beyond the pilot phase.

“It doesn’t have to be something that is scary, or that’s going to put people at risk. That’s something that we just try to keep reminding folks of,” Patnaik said.

“At the same point, within GSA, we’re looking at and thinking, ‘What can we do to be able to enable that? What can we do to be able to create those experimentation areas, so that it doesn’t become something that’s daunting for everybody?’”