In this exploratory report, the authors consider the security clearance process through the lens of racial justice. Some sources suggest that topics and questions covered in the background investigation process may exclude qualified applicants from minoritized racial and ethnic backgrounds. The authors identify areas where systemic factors and bias might contribute to the underrepresentation of Black Americans in the national security workforce.
- Is there evidence that racial disparities exist in the security clearance process?
- What factors might contribute to the potential for racial bias in the security clearance process?
- What steps can be taken to mitigate bias in the security clearance process, if it exists?
Because security clearances are required for designated national security positions, results of the background investigation and adjudication process can affect an individual's recruitment, hiring, retention, promotion, and ability to pursue a career in the U.S. Department of Defense and in the broader national security community—including government contractors.
Some sources suggest that topics and questions covered in the background investigation process may exclude qualified applicants from minoritized racial/ethnic backgrounds. Such exclusion is problematic not only because it is inconsistent with equal opportunity legislation and ethical principles but also because the practice may result in a national security workforce that lacks the breadth of capabilities and experiences needed for the mission. Currently in the security clearance process, data are not collected on the race of applicants, which is needed to determine whether racial disparities exist in the submission of an application, completion of an interview, adjudication, or appeal decision.
In this exploratory report, the authors consider the security clearance process through the lens of racial justice. They identify areas where bias might create an unjustifiable barrier for Black Americans seeking positions or career advancement in U.S. departments and agencies with a national security mission. The authors describe societal factors (financial, drug-related, and criminal) and human judgment factors (affinity bias, confirmation bias, and statistical discrimination) that may contribute to racial bias. They analyze the reasons for denials of eligibility for security risks and perceptions of bias and recommend areas for improvement and further exploration in transparency, training, and awareness of bias.
- Nowhere in the security clearance process are data on race gathered. Thus, it cannot be definitively determined whether any racial disparities exist during the security clearance process.
- There are societal factors (financial, drug-related, and criminal) and human judgment factors (affinity bias, confirmation bias, and statistical discrimination) that might contribute to racial bias in the security clearance process.
- As technology and automation evolve, racial bias could surface within the algorithms used in the clearance process, potentially as the result of programmer biases or historical racial differences.
- Individuals might not have a clear understanding of the data collected about them during the investigation process that inform adjudicative decisions.
- Collect data on the race of applicants to determine whether racial disparities exist in the submission of an application, completion of an interview, adjudication, or appeal decision.
- Prioritize the maintenance of the Defense Office of Hearings and Appeals' website to ensure accessibility to valuable and detailed information about the appeals process.
- Ensure that training is in place for investigators and adjudicators to recognize and mitigate any biases that might correlate to unjustifiable associations of race with an increased risk to national security.
- Conduct an independent assessment to review a subset of applications to determine whether racial bias might have affected their outcomes.
- Raise awareness among governmental organizations responsible for oversight and accountability that algorithmic or machine learning models can reflect the biases of organizational teams and societal factors.
- Encourage applicants to request their security clearance investigation records from the Defense Counterintelligence and Security Agency.