The State Department sees artificial intelligence as an increasingly valuable tool to meet its mission, and is looking at generative AI to help its employees chart the next step in their careers.

Don Bauer, the chief technology officer of the State Department’s Bureau of Global Talent Management, said last month that the department recently obtained an Authority to Operate (ATO) to use AI on sensitive internal data.

“We’re literally looking at the next steps of how do we now leverage internal information and start making decisions that way,” Bauer said Feb. 29 during a Federal News Network-moderated panel at ATARC’s AI Summit in Reston, Virginia.

Before President Joe Biden’s sweeping executive order on AI in government last October,  agencies such as the Department of the Navy, General Services Administration and the Environmental Protection Agency had put limits on how their staffs could use generative AI tools in the workplace.

But Bauer said the State Department is taking a closer look at what generative AI means for its mission.

“The ability to summarize and pull data from multiple sources, and do a lot of information gathering really resonates with the diplomatic community,” Bauer said. “The State Department’s been very much forward-leaning on just telling everyone, ‘Go out and get an account and get familiar with the technology. Just make sure you don’t put any sensitive information into it.’”

The bureau is looking at generative AI to help develop career paths for State Department employees.

“We have a demonstration project to extract skills from resumes and start building out pipelines for civil servants, as far as career progression,” Bauer said. “If I identify a career path for you, then I’m using publicly available position descriptions, extracting those out, and then building up the ability for you to recognize skills you need. Then we’re going to tie that with our learning management system, so we can actually say, ‘If you want to be this person, here’s the skills you need and here’s how you can go get trained.'”

Along with this culture of experimentation, Bauer said the State Department is prioritizing workforce training around AI.

“We need training, we need to have a common understanding of what AI is to the organization,” he added.

Generative AI ‘on guardrails’ at DOE

Bridget Carper, the Energy Department’s deputy CIO for architecture, engineering, technology and innovation, and its responsible AI official, said the department is giving employees a sandbox environment to experiment with generative AI.

“We actually took the initial stance of, ‘Oh, ChatGPT, we’re going to block it.’ Then, we realized that everyone was just doing it on their personal computer. So, then we started putting in guardrails,” Carper said. “Now we’re going in it with the education aspects, or doing training across the board,” Carper said.

Carper said DOE is currently using AI for enhanced cybersecurity, and to improve the customer experience of individuals and organizations applying for federal grants.

“We were fortunate enough to have funding to be able to provide to different communities, but how do they access that? Most people don’t have the time to go through the different sites — is it EPA? Is it IRS, to be able to obtain that information? So we’re using AI to help put that out there, to make it more readily accessible for users.”

‘You have to have good data’

Bauer said the rise of AI use cases puts increased pressure on agencies to improve their data maturity.

“I’m under tremendous pressure for very accurate HR data — whether it’s positions , whether it’s where people are assigned, how the department moves around at large.

“We’re looking at opportunities, for use cases, around using AI to help us find bad data and clean it up,” he said. “When you have somebody that retires after 30 years and retirement tells them you’re in the wrong retirement code, and you owe the government $25,000 before you can leave — you say, ‘Well, how can that happen? It should be really easy to root those things out.’ But there’s so many different legal authorities and combinations of information that  human beings could probably do it, but we’re really honing in on the ability to actually start looking at that as a data cleanup exercise,  because we’re all under pressure now to have these very very robust data models that decision makers are all wanting. Everything’s decision data driven now, so you have to have good data.”

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