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Talent Identification

Centralized Promotions in the Blind

By Sgt. Maj. Jason M. Payne & Sgt. Maj. Francine Chapman

U.S. Army Sergeants Major Academy

July 13, 2020

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U.S. Army Command Sgt. Maj. Escolithia Stackhouse

“Effective 1 August 2020, the requirement for officer, warrant officer and enlisted selection boards to include the DA Photo as part of the board file is suspended. Data that identifies a Soldier’s race, ethnicity, and gender on the Officer Record Brief and the Enlisted Record Brief will be redacted as a part of the board file. These changes will help ensure that selection boards are as fair and impartial as possible.”

—McCarthy & McConville, 2020, para. 4

Like many modern American industries, the U.S. Army faces a steep challenge in recruiting, retaining, and promoting the nation's top talent to meet its operational requirements. Regarding promotions, the Army's current centralized senior enlisted evaluation process is inherently vulnerable to unconscious bias from panel members. In order to improve the evaluation process, the Army has elected to suspend the use of Department of the Army (DA) photos and redact all information regarding race, ethnicity, and gender from both officer and enlisted record briefs during promotion boards starting August of 2020 (Rempfer, 2020). These steps toward a blind centralized evaluation system (BCES) will curb personal preferences based on Soldiers' physical characteristics, promote diversity amongst the Army's enlisted and officer population, and better identify the most talented individuals for advancement based on merit.


Army centralized selections for promotion to the senior noncommissioned officer (NCO) ranks began in 1969. Fifty years later, the Army is overhauling the traditional time-in-grade/service system and switching to a merit-based promotion system to ensure the most-qualified Soldiers are eligible to be promoted quickly (Suits, 2019). With so many resources invested in the training, retention, development, and welfare of its Soldiers, the Army cannot afford biases that degrade its talent identification capabilities.


Voting members of centralized evaluation boards, at times, have explicit biases that are not related to individual performance (e.g., male Soldiers who wear mustaches within Army regulatory guidance); however, their unconscious biases can unknowingly produce gender and racially discriminatory undertones across the force, despite an Equal Opportunity program that actively prohibits these prejudices. Many empirical studies acknowledge the presence of such bias both in and out of the military environment (Hausman, 2012; Asch et al., 2012; Rempfer, 2020).

In 2018, in order to study if bias was actively effecting promotion boards, the Army conducted an experiment utilizing two nearly identical selection boards — one including professional photos and the other without.

Researchers found that when the Department of the Army photo was removed, there was less variance between voters' scoring, meaning voters ranked candidates more similarly across the board. After removing the photo, voters also took less time to make decisions on each individual file, and the outcomes for minorities and women improved. (Rempfer, 2020, para. 6)

Racial Disparity

From 2002 to 2012, more than three million voluntary participants completed the Race Implicit Association Test (IAT), which captured metrics pertaining to the implicit and explicit racial attitudes of all respondents (Xu et al., 2014). When the PEW Research Center conducted its own research using the IAT model, it found that:

About three-quarters of respondents in each of the five racial groups, including those who are biracial, demonstrated some degree of implicit racial bias. Across the groups, only about 20% to 30% of those in the study were found to have little or no bias toward the races they were tested against (Morin, 2015, para. 5)

When looking at sergeant first class statistics from 2010 to 2019, the Army observed a 6% to 8% reduction of Black sergeants first classes and a 14% to 17% increase for White sergeants first classes, which was the only significant jump for any racial or ethnic population during that period (see Figure 1). While it can't be proven that there is racial bias in the Army's centralized evaluation board process, it can be concluded from the IAT research, and from the information from the Defense Manpower Data Center in Figure 1, that inherent bias—whether conscious or unconscious—may exist.

2010 vs. 2019 active Army SFC comparison

Gender Disparity

Indicators of gender-based promotion bias may, or may not, be present in the Army's senior enlisted ranks. For example, gender ratios for male and female senior enlisted NCOs remained relatively the same when comparing Fiscal Year 2010 to Fiscal Year 2019. In both years, male Soldiers accounted for 89% and 88% of the senior NCO population respectively (see Figure 2). Female Soldiers only accounted for the remaining 11% of senior NCOs in 2010 and 12% in 2019 despite registering 12.92% (an almost 2% disparity) and 14.69% (an almost 3% disparity) of the Army's enlisted active duty workforce during those years (Defense Manpower Data Center, n.d.). Now, of course, these fluctuations could be attributed to modern recruiting initiatives where there will be a several year lag time between new recruits and senior NCOs, or any number of other influences, but gender bias cannot be counted out.

2010 vs. 2019 active Army gender comparison

To further prove the point, a study conducted by the Rand Corporation in 2012 determined that 14% more male officers were promoted to major than their female counterparts of the same ethnicity (Asch et al., 2012). The study could not conclude the gap was strictly due to gender bias because the rate of leaving the military is higher in females, especially when starting a family, but the new blind evaluation system will reduce the potential for such discrimination.


A BCES is a logical step forward for the Army to remove race- and gender-biased results through a deliberate focus on performance and leadership potential. Blind hiring practices—also referred to as blind curriculums—are already practiced in the civilian sector to minimize the risk of bias in many private businesses. “The idea is that any information that doesn't relate to a person's work capabilities shouldn't be included” (Laboy, 2019, para. 2).

DA Photo Elimination

Official DA photos provided board members with the ability to view a Soldier's military appearance in uniform, yet they should not be used to gauge an individual's compliance with Army body composition standards or grooming standards in accordance with Army Regulation 670-1 (Department of the Army, 2017). “The DA photo is not a rational or appropriate way to measure [fitness, proper wear of the uniform, or display of authorized awards]. All it does instead is undermine the Army's meritocracy” (Kearney, 2020, para. 2). DA photos are unnecessary because prominent features and physical characteristics have no bearing on performance or potential to lead Soldiers and organizations.

OMPF Redaction

The Official Military Personnel File (OMPF) contains a host of digital records that Soldiers accumulate and update throughout the course of their careers. Files available in a Soldier's OMPF typically include emergency contact information, military orders, certificates, and performance evaluations. Along with eliminating DA photos and redacting certain fields (race, ethnicity, and gender) on Soldier record briefs (SRB), the Army should take it a step further by redacting Soldiers' names and gender-based pronouns from any OMPF records screened during the board proceedings. These records include NCOERs, academic evaluations, award citations, certificates of achievement or training, letters to the board, and disciplinary correspondence. This will allow board members to evaluate Soldiers' records solely on merit without implications of gender bias, ethnic bias, or favoritism—especially if names can be indicators of gender and ethnicity.

Future AI Solutions

In keeping with the Army Modernization Strategy, there are two potential solutions that could further remove bias by infusing emerging artificial intelligence (AI) technology to the selection process:

1.) A sole reliance on AI to generate senior enlisted promotion order of merit lists (OML)

2.) A blended evaluation system that utilizes AI to generate OMLs with a reduced board panel to validate results prior to publication (Department of the Army, 2019).

The first option—an AI-centric selection process—would completely eliminate the need for SRB, DA photo, and OMPF file redaction. This would require programmers from the Army's Talent Management Task Force to code AI algorithms for OML generation using talent parameters determined by each career management field (CMF) (Sheftick, 2019). While this approach aligns with the Army Modernization Strategy, the potential for bias unrelated to Soldier performance is still possible. For example, Amazon's AI hiring engine taught itself to be biased towards women (Dastin, 2018).

The latter alternative course of action—a blended evaluation process—would leverage AI with human talent identification methods to produce OMLs. Using this method, a small evaluation panel of two to three individuals from each CMF would review automated OMLs prior to publication and ensure quality assurance and control. Reducing the amount of personnel required to serve as evaluation board panel members would also significantly reduce annual costs for temporary duty and the number of senior leaders absent from their formations. The Army could further mitigate unnecessary costs and time associated with this course of action by allowing select individuals to validate OMLs remotely using collaborative, virtual remote environments such as Microsoft Teams.


The Army's conversion to a BCES is a non-materiel solution to a personnel-oriented capability gap. By eliminating professional photos and making targeted redactions to enlisted board files, the Army will likely produce a cohort of senior NCOs more aligned with service-wide gender and racial demographics; however, it can be taken further in also redacting names and pronouns from selection board criteria as well as the Army investing in technology that further reduces the possibility of bias and/or prejudice. The goal is to improve the service's talent identification process in a manner that fully promotes merit-based evaluations, diversity, equality, and inclusion.


Asch, B. J., Miller, T., Malchiodi, A. (2012). A new look at gender and minority differences in officer career progression in the military. RAND Corp.

Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters.

Defense Manpower Data Center. (n.d.). Distribution of active duty services (EEO).!/reports/606?filter=3&filter=A&filter=201911

Department of the Army. (2014). AR 600-20: Army command policy.

Department of the Army. (2015). Memorandum for president and members, fiscal year 2015 (FY 15) regular Army (RA) and Army reserve active guard reserve (AGR) sergeant first class (SFC) promotion and staff sergeant (SSG) qualitative service program boards.

Department of the Army. (2017). AR 670-1: Wear and appearance of Army uniforms and insignia.

Department of the Army. (2019). Army Modernization Strategy: Investing in the future.

Hausman, D. (2012). How Congress could reduce job discrimination by promoting anonymous hiring. Stanford Law Review, 64(5), 1343-1369.

Kearney, P. (2020). Not worth a thousand words: Abandoning the DA photo. War Room: United States Army War College.

Laboy, C. (2019). What is a blind CV? FactorialHR.

McCarthy, R. D., & McConville, J. C. (2020). Elimination of Department of Army (DA) photos, and race, ethnicity and gender identification data for officer, warrant officer, and enlisted selection boards.

Morin, R. (2015). Exploring racial bias among biracial and single-race adults: The IAT. PEW Research Center.

Rempfer, K. (2020). Army ditches officer promotion photos as part of an effort to eliminate unconscious bias Army Times.

Sheftick, G. (2019). AI task force taking giant leaps forward.

Suits, D. (2019). Army makes big changes to centralized promotion board system.

Xu, K. Nosek, B., & Greenwald, A. G. (2014). Psychology data from the race implicit association test on the Project Implicit demo website. Journal of Open Psychology Data2(1).


Sgt. Maj. Jason M. Payne is a recent graduate of the U.S. Army Sergeants Major Academy and is currently assigned to the U.S. Army Cyber Center of Excellence. He holds a Bachelor of Science in Criminal Justice from Troy University and is pursuing a Master of Science in International Relations.

Sgt. Maj. Fran Chapman is a recent graduate of the U.S. Army Sergeants Major Academy at Fort Bliss, Texas. She is currently the Plans and Operations Division sergeant major for the 1st Human Resources Sustainment Center (HRSC) in Kaiserslautern, Germany. She holds a Bachelor of Science in business administration from Hawaii Pacific University and is pursuing a Master of Arts in organizational leadership from Regent University.

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