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Prepping data
Data preparation, especially for agencies that have mas- sive stores of information, is a time-consuming step before deploying an AI system, Enthoven said.
“Data might be spread all over the place, and it might be in formats that are hard to use,” he added. “There may be data you need but don’t yet have. In some cases, data scientists go upstream to ask for data and even reengineer processes to get the data they need.”
Agencies need good data scientists who will work with the team to “understand how they can get the data they need to fulfill the objective,” Enthoven said. After the team collects the data, it will need to be cleaned up or normalized.
A big part of data preparation often involves dealing with duplication, he added. “If you have hundreds of analysts spread across multiple locations and they’re all working in the same problem area, you can bet that many are looking at the same datasets [and] doing the same cleaning,” he said. “It’s hard for any one person to know what has already been looked at and what data has been deemed useful or non-usable.”
Some companies, such as Tamr, have begun to offer tools to clean up and consolidate data, and most AI sys- tems will offer services to fix data problems, Metzger said. But data scrubbing is still a major activity that must hap- pen before AI technology is deployed.
IT “SEEMS LIKE A NO-BRAINER THAT CITIZENS SHOULD BE ABLE TO SEE
“Of the AI tools we have worked with, the biggest ques- tion for their customers is always ‘what state is the data in?’” she said. “Often the data is messy or needs cleansing before these tools can work effectively.”
WHERE AND
The way the federal government categorizes its spending data is another example of the problems agencies face, said Peter Viechnicki, a data scientist at Deloitte’s Center for Government Insights and co-author of the AI paper with Eggers. Money spent on contracts is stored in one format while money spent on grants is stored in another, he said, adding that agencies have been making progress on standardizing their approach to spending data.
HOW OUR TAX
It “seems like a no-brainer that citizens should be able to see where and how our tax dollars are being spent, but legacy IT systems make this more challenging,” Viech- nicki said.
SYSTEMS MAKE THIS MORE
Still, many AI experts believe the widespread use of the technology in government is inevitable. And Metzger is among those who recommend that agencies start edu- cating themselves now.
“Because there are real problems that can be solved with AI today, don’t think of it as ‘we’re adopting artificial intelligence,’” she said. “Just think of it as you would any other IT modernization effort. It’s going to happen, so you need to figure out how to embrace it.” n
CHALLENGING.”
DOLLARS ARE
BEING SPENT,
BUT LEGACY IT
PETER VIECHNICKI, DELOITTE
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