Backlog of Security Clearance Investigations Declines
After years of cumulative and seemingly irreversible growth, the backlog of pending security clearance investigations declined in the last three months in response to new policy guidance.
Since June, the National Background Investigation Bureau has reduced its background investigation inventory from 725,000 cases to 657,000 cases, according to a new quarterly report on security clearance policy. “Reductions are expected to continue as policy changes are further implemented.”
The backlog of pending investigations had increased from about 190,000 in August 2014 to more than 710,000 in February 2018. As recently as last March, the Government Accounting Office said that “NBIB leadership has not developed a plan to reduce the backlog to a manageable level.”
But that was then. Now, the new quarterly report says, background investigations are on track to be reduced to “a steady and sustainable state” by March 2021.
The decline is attributed to “thoughtful, risk-based modifications to the background investigation process” as well as to a significant increase in the number of investigators. “NBIB increased the capacity of its investigative workforce from 5,843 Federal and contractor investigators on October 1, 2016 to over 8,400 Federal and contractor investigators today,” according to a new NBIB report obtained by ClearanceJobs.com.
Much remains to be done. A June 2018 deadline for producing “updated standards for denying, suspending, and revoking Federal credentials” was missed, the quarterly report said.
An efficient and judicious security clearance system excludes persons who might pose a threat to national security. But an inefficient and backlogged system excludes qualified persons who cannot wait a year or longer for a clearance. In this way, a poorly performing clearance system may itself pose a threat to national security.
Commercial artificial intelligence tools have recently emerged that are able to produce police reports. If the resulting reports are inaccurate, incomplete or biased, or if the process leaks confidential information, this could undermine the criminal justice system and harm citizens.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.