AI Bright Spot: Collaborative AI leadership at the Government Accountability Office

The Partnership for Public Service AI Center for Government^® is publishing a series of blogs to celebrate how artificial intelligence and intelligent automation are being used in government to serve the public. 

Our team recently spoke with Sterling Thomas, chief scientist at the Government Accountability Office, to learn how the agency uses AI and the role of collaborative processes in successfully implementing new AI tools. 

This interview has been edited and condensed for clarity.

When it comes to how your team at GAO is using AI, what is the problem you are trying to solve or the outcome you are hoping to achieve? 

“We’re taking advantage of several opportunities. One of the bigger ones is fully using our own institutional knowledge. It’s a vast resource, because we’re an agency that’s over 100 years old, and our purview is over how federal dollars are spent by all executive agencies.  

“One of the things we’ve developed is a large language model that lets our staff retrieve and summarize work that we’ve done on a particular topic over the past 20 years or so.  

“Another place that we use AI tools [is that] we get a lot of data from Congress and from the executive branch on things that we are responsible for providing oversight into, and so we use AI to evaluate that data, do some basic analysis and produce results that we need.” 

What factors went into the decision-making process for building these AI tools? 

“We saw an opportunity to free up the time of our staff so they could identify improvements in their workflow. We’ve been using machine learning and those types of tools for a long time, and we have an analytical core here at GAO that supports that type of work. When large language models became commercially available, we said, ‘Wait a second, there’s a way here we can do more with the text information we already have.’” 

How did your team prepare to implement these new tools? 

“We have an AI Council that I chair that [consists of] GAO executives who decide what we need to do to bring a tool in for our analysts. 

“Within any agency, the foundation for training is what you can do with AI and what you can’t do. When we meet as a council, that’s when we say, ‘These are the rules of the road that our analysts need to follow in order to use these tools,’ and we put that into a training.” 

It sounds like there was a focus on the implementation process being collaborative. 

“Yes, and that works well with the way GAO operates because we do a lot of different things. So, it’s better for us to have a collaborative nature where the executives hold individual accountability for each one of our mission areas.” 

Is there a particular recent AI success your team has celebrated? 

“One that uses both machine learning and artificial intelligence is called Facet. It’s a tool that goes through and does an analysis on the Federal Audit Clearinghouse, which is a resource maintained by [the General Services Administration] that has all the audit results from a little over a trillion dollars’ worth of federal spending each year. 

“[Facet] goes through those audit reports and produces a series of metrics that represent areas of concern and where there’s potential improvements in a way that a program’s finances are being managed. 

“This tool’s been running for a couple of years now, and it has allowed us to go back to the Federal Audit Clearinghouse and say, ‘Here are some things that we could do to make this program work even better and ensure the government’s money is being spent effectively and appropriately.’” 

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Continuing the conversation   

The AI Center for Government champions AI innovators across all levels of government. If your agency is taking steps to lead AI well, we’d love to hear from you. Join us as we highlight real-world AI use cases and convene public sector leaders from across the country to share tools and insights to lead confidently in the age of AI.

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