Good AI Starts With a Trained Workforce, Government Experts Say

According to a panel of government technology experts, government digital transformation efforts in areas like artificial intelligence must also consider human resource needs.

At an ATARC event on Thursday, panellists explained that it doesn’t matter how good the data or the AI ​​is if people don’t know how to use it properly or don’t understand it. As a result, panelists emphasized the need for data literacy, education, and training.

“I can build the best AI model, but if I put it in the hands of my investigator and he has a lot of questions, then we just lost them,” says Ben Joseph, chief data officer for the United States Postal Service Office of Inspector General , said. “Earlier this year we actually launched a small program related to data literacy … so we’re training my staff, investigators, accountants and everyone else, e.g. B. ‘How do you interpret data?’”

“It’s almost like sizing AI education for the position or role that the individual plays in the lifecycle,” said William Streilein, chief technology officer in the US’s Office of the Chief Digital and Artificial Intelligence Officer – Department of Defense. said. “Someone working in acquisitions is certainly capable of knowing all the details, but they don’t necessarily have to. They need to know enough and know what is relevant to their role.”

While data literacy and training are important, Joseph emphasized the need to have a diverse workforce.

“We don’t want to spend a lot of time making everyone data scientists,” Joseph said. “We need a mix of people like data analysts, data engineers, data scientists and people who can respond, communicate, change and all of that.”

Meanwhile, the Department of Homeland Security is working on a program to bring together existing senior experts in various fields from across the agency.

“What we’re trying to do with the Black Belt program is to find out who the experts are in the DHS organization,” said David Larrimore, chief technology officer for DHS.

The DHS program evaluates three components: level of education, which can be a certification; the amount of personal or professional experience on a particular topic; and results to demonstrate one’s knowledge and expertise in a particular area.

“Because it’s impossible that out of the 350 or so acquisition programs that are currently underway, everyone has someone who could be considered an AI black belt,” Larrimore said. “But wouldn’t it be great if a black belt from CBP could attend a FEMA program for six months to help them get ahead.”

In addition to building expertise in advanced technologies like AI, the experts found that employees need to understand the value of not just random data, but high-quality data.

“We have to get our data in order, because the data gives you the fuel for the analysis,” said Streilein. “Teaching best practices around data is probably the most important thing. We like to say: “No new bad”. Data is created all the time, and it’s so easy to create it without putting the right labels on it, not in the right place. We use the term VAULTIS – an acronym for Visible, Accessible, Understandable, Connected, Trusted, Interoperable and Secure. So that’s a lot. But if you can turn your data into VAULTIS, then hopefully you’re AI-enabled. This is certainly a good bar to shoot at.”

According to Larrimore, the quality of the data must be checked continuously.

“We constantly need to challenge the data we’re looking at, and that’s only possible by working with components, with the data providers, and with the data stewards,” Larrimore said. “Do we actually understand where the rubber meets the road, the brass nails, the end result, prior to what was presented to us, right? And it’s only when those conversations happen that everyone comes to a consensus about what information actually adds value.”

Panelists also highlighted the importance of different parts of an agency working together to understand how their part impacts the agency’s overall mission.

“Often we don’t allow procurement staff to see the full results of their work,” said Udaya Patnaik, chief innovation strategist for the Office of Information Technology at the Federal Acquisition Service of the General Services Administration. “You have to know how the work that you’re doing on certain acquisitions is being leveraged in agencies and be able to connect all the dots that’s like, ‘Oh, because we did this action over here, the data is working far down here.”