Written by Lindy Kyzer, as featured on ClearanceJobs. --
Artificial intelligence, machine learning, big data. It’s clear the issue today isn’t information – it’s how to process it most effectively. That is the conundrum facing the federal government as it looks to implement continuous evaluation of security clearance holders. CE is largely seen as the key to reducing the size of the security clearance backlog and improving security clearance process times. And in fact, we’ve already seen major gains in reducing security clearance costs and driving down the backlog – largely enabled through enrolling more security clearance holders due for periodic reinvestigations into the CE program.
But the issue the government faces is – how does it take all of the data available about its workforce (from credit reports to social media postings), and filter or analyze it in meaningful ways?
A new partnership between data and behavior science firm Giant Oak and consumer credit reporting agency TransUnion aims to help the federal government accomplish its personnel security screening mission more efficiently. The partnership enables the kind of continuous vetting process the government sees as crucial to a modern personnel security program. Dr. Gary Shiffman, founder and CEO of Giant Oak and John McDonald, vice president, public sector at TransUnion recently spoke with ClearedCast about the partnership.
“We understand the growth and proliferation of data, the deluge of data,” said Shiffman. “As humans we’re overwhelmed by that amount of data. So in theory, data makes our jobs easier and it makes us more secure. But in practice, we mostly just get overwhelmed by data and machine-learning is kind of this new generation of technology which allows humans to take advantage of the amount of data in a way that’s human-friendly.”
While data can be an asset – without the right people analyzing it, it can be a liability.
“The mission is critical, the mission is vital and we believe very passionately in the importance of not only having this cadre of cleared and vetted individuals, but in having that system efficient and easy so that the most talented people are actually drawn to, and excited to work in positions of trust in the U.S. government,” said Shiffman. “In order to do that, we need to take advantage of all of the data that we have available. But we have to do that in a way that’s efficient.”
The first step is to access the data – and that’s where TransUnion comes in.
“We have over a billion people in our systems across both, financial and public records information,” said McDonald. “We can help the government prioritize who they look at in terms of who’s most likely to get through the clearance process quickly, so they can put those to the top of the list and quickly get through those.”
McDonald noted how data can be used to help the government streamline cases by quickly flagging which cases will take more investigative and adjudicative work. The system can also work to help clearance holders remove inaccurate records and information.
“The way I like to think about it is, what we’re doing is we’re measuring risk or we’re measuring the absence of risk,” said Shiffman. “If you think about it, most people in positions of trust are not risky. We just need some very efficient way to automate and continuously vet people in positions of trust for the absence of risk and also the measurement of risk.”
SAVING CLEARANCE COSTS BY SAVING INVESTIGATOR TIME