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Outside the concrete wall: a qualitative study of Black women persisting in technology

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Outside the Concrete Wall: A Qualitative Study of Black Women Persisting in Technology
by
Sherry Keating

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

December 2023

© Copyright by Sherry Keating 2023
All Rights Reserved

The Committee for Sherry Keating certifies the approval of this Dissertation

Paula M. Carbone
Stefanie P. Phillips
Jennifer L. Phillips, Committee Chair

Rossier School of Education
University of Southern California
2023

iv
Abstract
Black women make up 3% of the technology industry workforce and less than 1% of the
leadership positions in technology as of January 2023. This number has moved nary a percentage
point in the last two decades. Black women are underrepresented in technology despite a greater
percentage obtaining degrees in computer science and engineering. The underrepresentation of
Black women in the technology industry can hinder the innovation of products and services that
would have been created to benefit a wider market, had Black women been given the opportunity
to contribute to their development The purpose of this study was to understand the experiences
of Black women who have persisted in the technology industry for five or more years. The
research employed a qualitative approach to data collection and 11 Black women were
individually interviewed. The study findings suggested that Black women who persist in
technology have done so strategically, demonstrating high agency and self-efficacy, to work
around the organizational climate and culture of the technology industry that has excluded them
from much of its social fabric. Technology companies can use evidence-based solutions to
recruit, develop, retain, and promote Black women, including targeted recruiting efforts, formal
mentorship and sponsorship programs, and broader education on bias grounded in historical
inequities, systemic and structural racism, and the organizational cultural deficits in the
technology industry.

v
Acknowledgements
This research study is the culmination of nearly three years of learning, research, and
unwavering dedication to this topic. It would not have been possible without the support, love,
and active participation of so many others. First, a big thank you to the women who volunteered
and participated in this study. Their candor, insight, and wisdom made this research possible.
Second, a special thanks to my dissertation committee who provided me with their time,
guidance, and support. Dr. Jennifer Phillips, my chairperson, Dr. Stefanie Phillips, and Dr. Paula
Carbone are all amazing, brilliant women who helped shape this study. Third, a warm hug full of
appreciation for my study group: Dr. C, Dr. K, Dr. L, and Dr. T. Thank you for your support,
friendship, and love. Finally, I want to thank my amazing partner, Michelle, who supported me
during this time and sacrificed so many weekend trips, morning hikes, baseball games, and
evenings out so I could conduct this research. I could not have done it without your love and
support.

vi
Table of Contents
Abstract .......................................................................................................................................... iv
Acknowledgements ......................................................................................................................... v
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
Chapter One: Introduction to the Problem of Practice .................................................................... 1
Background of the Problem ................................................................................................ 2
Field Context and Mission .................................................................................................. 4
Purpose of the Study and Research Questions .................................................................... 5
Importance of the Study ...................................................................................................... 5
Overview of Theoretical Framework and Methodology .................................................... 6
Definitions ........................................................................................................................... 8
Organization of the Dissertation ....................................................................................... 10
Chapter Two: Review of the Literature ........................................................................................ 11
Background of Black Women in Technology .................................................................. 11
Impacts on Technology Industry Resulting From the Absence of Black Women ........... 16
Challenges and Barriers to Black Women Remaining in Technology ............................. 18
Promising Evidence-based Actions to Improve Representation of Black Women .......... 28
Theoretical Framework ..................................................................................................... 32
Conceptual Framework ..................................................................................................... 34
Conclusion ........................................................................................................................ 38
Chapter Three: Methodology ........................................................................................................ 39
Research Questions ........................................................................................................... 39
Overview of Methodology ................................................................................................ 39
The Researcher .................................................................................................................. 41

vii
Data Source: Interviews .................................................................................................... 42
Ethics ................................................................................................................................. 47
Chapter Four: Findings ................................................................................................................. 49
Participants ........................................................................................................................ 50
Findings Organized by Theme .......................................................................................... 51
Summary of Findings ........................................................................................................ 70
Chapter Five: Discussion and Recommendations ......................................................................... 72
Discussion of Findings ...................................................................................................... 72
Recommendations for Practice ......................................................................................... 76
Limitations and Delimitations ........................................................................................... 82
Recommendations for Future Research ............................................................................ 83
Implications for Equity ..................................................................................................... 84
Conclusion ........................................................................................................................ 85
References ..................................................................................................................................... 87
Appendix A: Interview Protocol ................................................................................................. 111
Appendix B: Recruitment Questionnaire .................................................................................... 114

viii
List of Tables

Table 1: Data Sources 40
Table 2: Participants 51
Table B1: Recruitment Questionnaire 114

ix
List of Figures
Figure 1: Conceptual Framework 37

1

Chapter One: Introduction to the Problem of Practice
The underrepresentation of Black women in the technology (tech) industry can lead to
greater income and wealth disparities for Black women (Scott et al., 2018). The diminished
representation of this group also hinders innovation of products and services that would have
been created to benefit a wider market, had Black women been given the opportunity to
contribute to their development (Solomon et al., 2018). Women make up nearly half of the U.S.
workforce, but only 27% of the technology workforce is female (U.S. Department of Labor,
2020). Black women account for a mere 3% of the technology workforce, which is less than half
of the total representation of Black women in the U.S. population (U.S. Bureau of Labor
Statistics, 2020). Technology is one of the most innovative industries (Maddikunta et al., 2022)
and is one of the largest drivers of the U.S. economy, accounting for 9.3% of the U.S. gross
domestic product (Statista, 2022); however, the workforce remains stubbornly homogenous at
73% male and 90% White or Asian (EEOC, 2016).
Between 2007 and 2015, despite efforts to promote diversity, equity, and inclusion (DEI)
in some of the biggest tech firms in Silicon Valley and across the industry (Rangarajan, 2018),
there was a 13% decline in the number of Black professional women in the technology
workforce (Dishman, 2017). This drop was the most precipitous decline across all demographic
groups (Gee & Peck, 2017). The underrepresentation of Black women in the tech workforce not
only hampers industry innovation but also reinforces inadequate access for Black women to
well-paid tech roles and opportunities to create wealth, which exacerbates economic disparities
for Black women (Scott et al., 2018; Solomon et al., 2018; Tedrick, 2020). This study
contributed to a small but growing body of research to better understand the experiences of
2

Black women who have broken into—and remain in—the technology workforce despite its
challenges.
Background of the Problem
There is limited documented history on American Black women in technology. Only
recently did the world discover the obscured existences of Katherine G. Johnson, Dorothy
Vaughan, and Mary Jackson—who worked as human computers in the 1960s Jim Crow era—
when their stories were told by Margot Lee Shetterly in the 2016 book (and later movie) Hidden
Figures. The proportion of women (mostly White) in the technology industry peaked in the
1980s at 40% of all tech workers (Kirkpatrick, 2019); their numbers would slowly decline from
then on. This short-lived era produced some of the most renowned Black women in modern
technology: Marsha R. Williams, the first Black woman to earn a doctoral degree in computer
science; Marian Croak, who earned her PhD in social psychology and quantitative analysis from
the University of Southern California, and who would later invent voice over internet protocol
(VoIP) technology; and Mae Jemison, the first Black female astronaut (Kirkpatrick, 2019).
Today, there are more opportunities for Black women to earn degrees in computer
science or engineering, but these opportunities do not correlate with a career in the tech industry.
Although Black or Latinx students earn 21% of all computer science degrees, they make up only
10% of the tech workforce, which suggests that they are not hired in the same proportion or that
when hired, they do not stay for very long (Scott et al., 2018). Black women continue to exit both
the educational track and tech workforce, a phenomenon dubbed the leaky pipeline, as a result of
social and structural barriers relating to systemic racism, sexism, and Black fatigue (Scott et al.,
2018; Sherbin & Rashid, 2017; Solomon, 2018; Yamaguchi & Burge, 2019; Winters, 2020a).
3

Of the women who work in technology today, 66% of them report there is no clear path
to upward mobility, and 39% report being passed over for a promotion because of gender (Daley,
2021). In addition to the gender-related maladies just mentioned, Black women also contend
with race-related discrimination that compounds their oppressions (Allen & Lewis, 2016;
Beckwith et al., 2016; McGee, 2018; Teich, 2021; Yamaguchi & Burge, 2019). A consensus
exists in the research that Black women in the workforce—including technology—experience a
phenomenon known as double jeopardy or double outsider status, in which they are perceived as
subordinate both to men, on the basis of gender, and to Whites, on the basis of race (Beal, 2008;
McGee, 2018; Rosette & Livingston, 2012).
Paradoxically, the intersectionality of gender and race leads Black women to experience
exclusion both as women and African Americans because society perceives women as
predominantly White and African Americans as predominantly male (Crenshaw, 1989).
Intersectionality, a theory derived from the scholarship of Kimberlé Crenshaw and Patricia Hill
Collins, refers to the interconnected nature of power relations across social categorizations such
as race, gender, sexuality, age, ethnicity, ability, nationality, and class (Collins & Bilge, 2020).
Due to the intersectionality of their race and gender, Black women have little or no power within
the organizational power structure of the technology industry, which is predominantly both
White and male (Solomon et al., 2018; Teich, 2021; Yamaguchi & Burge, 2019). Furthermore,
Black women are excluded from the social fabric of technology organizations in what McGee
(2018) refers to as a concrete wall, which, like the Black ceiling (Sepand, 2015) or concrete
ceiling (Babers, 2016), is nearly unbreakable and offers no transparency to the other side
(Beckwith et al., 2016; Coachman, 2009; Johnson, 2006).
4

Field Context and Mission
For the purposes of this dissertation, the definition of the technology industry is aligned
with the U.S. Government Accountability Office’s (2017) definition: “a group of industries with
the highest concentration of technology workers” (p. 2). Examples of roles in the technology
sector include, but are not limited to technical project managers, software designers, account
managers, coders, engineers, computer system programmers, technical support specialists,
business development, technical writers, user acceptance testers, and quality assurance teams
(GAO, 2017). There are also technology workers in other industries, such as a network
administrator at a financial services organization; however, this study focuses on technology
workers who are employed in the technology sector to better understand the experiences of Black
women who persist in the organizational culture and climate of the technology industry.
Today, the technology industry in the U.S. makes up about 9.3% (or 1.8 trillion dollars)
of the country’s overall gross domestic product (Statista, 2022). As of 2019, it employed
approximately 7.7% of the total U.S. labor force (Zippia, 2022a). White Americans hold 62% of
technology jobs, whereas Black Americans hold only 7%, and fewer than half of these jobs are
held by Black women (Zippia, 2022a). Women make up nearly half of the U.S. workforce, but
only 27% of the technology workforce is female (U.S. Bureau of Labor Statistics, 2016). Black
women account for a mere 3% of the technology workforce, which is less than half of the total
representation of Black women in the U.S. population (U.S. Bureau of Labor Statistics, 2016).
Wall Street defines the technology sector based on companies whose revenue is driven by
technology creation, growth, and development (Johnston, 2021). Although the technology sector
does not have an industry-wide mission, there is a consensus among leading technology
organizations that people and their experiences should be empowered, improved, and enriched
5

(Bresciani, 2021). It is ironic that a field like technology, which aims to empower people, is one
of the industries most oppressive to Black women (Ashcraft et al., 2016; Daley, 2021).
Purpose of the Study and Research Questions
The purpose of this study was to understand the experiences of Black women who have
persisted in the technology industry for five or more years, a cohort that has received limited
attention in research. Moreover, few studies have addressed how Black women entered the
technology industry, with fewer looking at how they have remained, persisted, or, potentially,
thrived year after year. There is some information about White women and underrepresented
groups as a whole and their experiences in technology as it relates to the glass ceiling
(Arulampalam et al., 2007; Lewis, 2017) and glass cliff (Ryan & Haslam, 2007; Ryan et al.,
2007); however, there is a substantial gap in our understanding of the overall complexities of
Black women’s experiences in the technology workplace (Buse, 2017; Yamaguchi & Burge,
2019). The research questions that were addressed in the study are as follows:
What are the experiences of Black women who have persisted in technology?
a. How has organizational culture and climate shaped Black women’s decisions to persist in
the technology industry?
b. How have individual characteristics shaped Black women’s decisions to persist in the
technology industry?
c. How have social factors shaped Black women’s decisions to persist in the technology
industry?
Importance of the Study
Understanding the experiences of Black women who have persisted in technology despite
the barriers within the industry is important to learning how to change the industry to be more
6

inclusive, equitable, and just. Black women’s work experiences are often silenced (Winters,
2020a; Yazeed, 2020), and this is even more common in the technology sector (Solomon et al.,
2018; Teich, 2021; Twine, 2018; Yamaguchi & Burge, 2019). This phenomenon is exacerbated
by the overlapping, subordinate social positions of Black women in being both Black and female
(McGee, 2018; Rosette & Livingston, 2012) in a predominantly White, male industry (EEOC,
2016; U.S. Bureau of Labor, 2016). This research presented an opportunity to not only better
understand how to support Black women in the technology industry, but also to provide
technology organizations with insights into how to better hear Black women’s unique
perspectives and retain, develop, and promote them in order to expand their reach, thereby
creating more innovative and fair products and services (Buse et al., 2017; McGee & Bentley,
2017; Morton & Parsons, 2018; Noble, 2018; Solomon et. al., 2018). If this research
accomplished some or all of its intent in elevating the voices of Black women in technology, not
only will it help the organizational culture of tech improve, but Black women might experience
the workplace liberated from the race, gender, and cultural biases that exist today.
Overview of Theoretical Framework and Methodology
Social cognitive theory (SCT) informed by intersectionality theory is a powerful lens
through which to examine the underrepresentation of Black women in the technology industry.
This lens helped to identify the personal characteristics, social experiences, and environmental
factors (Bandura, 2001) that contributed to the unique experiences of Black women in the
technology industry based on both their gender and race (Collins & Blige, 2020; Crenshaw,
1989; Solomon et al., 2018) and to understand their decisions to continue working in the
predominantly White and male technology industry.
7

Social cognitive theory uses a triadic framework with dynamic and reciprocal interactions
between the individual, their behavior, and the environment (Bandura, 2001). The assumptions
of SCT include that learning is vicarious and that people can learn by observing others. In
addition, the theory posits that learning is an internal process that may or may not result in new
behaviors. Thinking, considering, and other cognitive processes are important in determining
what is learned and the behaviors that become self-regulated (Bandura, 2001). Reinforcement
and punishment indirectly affect learning, behavior, and self-efficacy, including the belief that
one can accomplish a specific task, which can positively influence motivation and learning
(Bandura, 2001; Schunk & Usher, 2019). SCT also provided a lens through which to examine
environmental and behavioral issues (Bandura, 2001), such as racism, sexism, or prejudice, that
impact Black women’s self-efficacy, agency, and their decisions to remain (or not) in the
technology industry.
Intersectionality theory, as an analytical tool, informed SCT in this research. It provided a
framework for identifying and addressing complex social problems as they relate to power
structures (Collins & Blige, 2020). In this research on Black women’s experiences in the
technology industry, the impact of overlapping identities—for example, Black, woman, and
employee in the technology industry—were able to be examined simultaneously; focusing on a
single factor, such as race or gender, would have inevitably overlooked the nuances and
compounded oppressions of these women’s lived experiences (Collins & Blige, 2020; Crenshaw,
1989; Lorde, 1982).
The goal of this research study was to understand the experiences of Black women who
have persisted in the technology industry for five or more years. Because the research aimed to
understand the experiences of Black women, the design of this study was qualitative. I used
8

semi-structured individual interviews to collect the data; this interview format allowed for a
purposeful, somewhat structured interview guide with the flexibility to respond dynamically to
participants’ answers, questions, and comments (Creswell & Creswell, 2018; Merriam & Tisdell,
2016). The study site was the technology industry, and participants were in a location of their
own choosing during the interviews. The study was conducted virtually via Zoom video
conference and automatically recorded for transcription and data analysis. Research study
participants were 11 Black women who have worked and remained in the technology industry
for five or more years.
Definitions
The following terms and definitions are relevant to this study:
• Agency is part of social cognitive theory that refers to the ability to control one’s own
thinking, motivation, and behavior (Bandura, 2001).
• Black fatigue is a feeling of mental, physical, and spiritual exhaustion caused by
continuous microaggressions, racial bias, and systemic racism (Winters, 2020a).
• Black women include individuals who identify as Black or African American women.
• Concrete ceiling is a metaphorical representation of limited career mobility experienced
by Black women despite being qualified for promotion (Bernard et al., 2020).
• Concrete wall is a metaphorical representation of the opaque and nearly unbreakable
barrier that keeps Black women outside of the social power structure in the technology
industry (McGee, 2018).
• Double jeopardy represents the situation or circumstance for people who have two or
more subordinate identities, like Black women or lesbians (Rosette & Livingston, 2012).
9

• Intersectionality is a theory derived from the scholarship of Kimberlé Crenshaw and
Patricia Hill Collins that refers to the interconnected nature of power relations across
social categorizations such as race, gender, sexuality, age, ethnicity, ability, nationality,
and class (Collins & Bilge, 2020).
• Mentorship is formal and informal developmental assistance to offer insight, feedback,
and coaching on specific job skills (Higgins and Kram, 2001).
• Organizational culture refers to the shared belief system, social norms, values, and
dynamics in an organization or industry environment (Clark & Estes, 2008).
• Persist means to continue despite difficulty and was popularized as part of a women’s
movement in 2017 when Senator Mitch McConnell invoked a procedural rule to silence
Senator Elizabeth Warren on the Senate floor, saying “She was warned. She was given an
explanation. Nevertheless, she persisted” (Gluckman, 2018; 163 Cong. Rec S855, 2017;
Victor, 2017).
• Self-efficacy is part of social cognitive theory; it refers to the belief that one can
accomplish a specific task (Bandura, 2001).
• Sponsorship is a relationship with a senior-level leader who brings to light their protégé’s
capabilities in considerations where assignments or promotions are discussed; the leaders
often put their own reputation on the line for the advancement of individuals whom they
sponsor (Sherbin & Rashid, 2017).
• Stereotype threat is the fear or anxiety that an individual feels when they are in a situation
that could confirm a negative stereotype of their group, especially in performance
situations (Casad & Bryant, 2016; Steel and Aronson, 1997).
10

• Technology industry encompasses “a group of industries with the highest concentration
of technology workers” (GAO, 2017, p. 2). Examples of roles in the technology industry
include, but are not limited to technical project managers, software designers, account
managers, coders, engineers, computer system programmers, technical support
specialists, business development, technical writers, user acceptance testers, and quality
assurance teams (GAO, 2017).
Organization of the Dissertation
This dissertation is organized into five chapters. Chapter one contained an overview of
the study including an introduction and background to the problem, the purpose and importance
of the study, the study methodology and research questions, and key definitions. Chapter two
includes the literature review and themes that emerged from the literature related to the problem
of practice. Chapter three provides details about the research study including the methodology,
sample and population, instrumentation, and data collection and analysis. Chapter four provides
detailed information on the study findings and related discussion topics. Finally, chapter five
covers the analysis of the study findings, implications for practice, limitations, and areas for
future research.
11

Chapter Two: Review of the Literature
Chapter two covers an overview of the literature and begins with a section about the
background of Black women in technology, including their absence from history (McGee,
2018;), the leaky pipeline of talent (Blosser, 2019; Klein et al., 2018; Lisberg & Woods, 2018),
the concrete wall (Babers, 2016; Khosroshahi, 2021; McGee, 2018), and the dire consequences
of technological innovations built with the same inherent gender and race biases held by their
human developers (Hill, 2020; Joyce et al., 2021; Lohr, 2018; Zou & Schiebinger, 2018). The
second section covers the challenges and barriers to Black women remaining in the technology
workforce, such as inequitable pay (Miller, 2020; Tucker & Temple, 2017), lack of upward
mobility (Beckwith et al., 2016; Giscombe & Mattis, 2002; Khosrashahi, 2021), stereotype threat
(McGee & Bentley, 2017; Solomon et al., 2018; Spencer et al., 2016), and Black fatigue
(Roberts & Mayo, 2019a, McGirt, 2017; Winters, 2020b). The third section includes promising
evidence-based strategies for how to improve retention, mentorship, and an organizational
environment that is supportive of Black women. The fourth and fifth sections cover the
theoretical and conceptual frameworks used for the research study: Bandura’s (2001) social
cognitive theory informed by Crenshaw’s (1989) intersectionality theory.
Background of Black Women in Technology
This section includes academic literature, research, and empirical data about their
absence and underrepresentation of Black women (Solomon et al., 2019; Suber, 2022); the
attrition data and research about why experts believe Black women are leaving technology (a
phenomenon known as the leaky pipeline) (Espinosa, 2011; Gee & Peck, 2017; Scott et al., 2018;
Yamaguchi & Burge, 2019); and the social experiences of Black women who find themselves
faced with what academics and scholars call the concrete wall. The concrete wall is a
12

metaphorical representation of the social structure in technology that offers no upward mobility
and no visibility to how one might move past their career plateau (Allen & Lewis, 2016; Babers,
2016; Khosroshahi, 2021).
Absence and Underrepresentation
There is a conspicuous absence of information about Black women in U.S. history and
the literature on the technology industry (Kirkpatrick, 2019; Twine, 2018), but this is not because
Black women have not contributed to technological advances. As mentioned in chapter one, the
world learned about the contributions of Katherine G. Johnson, Dorothy Vaughan, and Mary
Jackson only in 2016 with the release of Margot Lee Shetterly’s book Hidden Figures. Indeed,
there are few stories (and even less academic research) about the experiences of Black women in
technology before the 1980s (Kirkpatrick, 2019).
Men make up 73% of the technology workforce in the U.S., whereas Black women
represent just 3% (U.S. Bureau of Labor Statistics, 2020). Black women are underrepresented in
the technology industry by a ratio of 2:1 when compared with their overall U.S. demographic
percentage (U.S. Bureau of Labor Statistics, 2020). In Silicon Valley, a hotspot for both
established and startup technology companies, men make up 70% of the workforce, while Black
women constitute 2% of the workforce and 0.5% of the leadership (Rangarajan, 2018). The
underrepresentation of Black women has resulted from various factors present in the technology
culture and environmental climate that include, but are not limited to exclusion, bias,
discrimination, lack of belonging, and Black fatigue (Babers, 2016; Espinosa, 2011; Gee & Peck,
2017; Khosroshahi, 2021; Scott et al., 2018; Solomon et al., 2018; Twine, 2018; Yamaguchi &
Burge, 2019). The following section examines attrition (referred to as the leaky pipeline) from
school to the professional workforce.
13

Leaky Pipeline
The leaky pipeline is a term researchers use to refer to a group that is exiting a field of
study or path to a specific profession, such as Black women exiting technology (Klein et al.,
2018). There is some disagreement about the specific leaky pipeline of Black girls and women in
science, technology, engineering, and math (STEM) curricula. Research findings are mixed
when determining whether the attrition is due to a lack of interest or exclusion at the elementary
school age, college age, or once employed in the technology workforce. This section will
examine the literature and overall sentiment about when and why Black girls and women fall out
of STEM and the technology industry.
Among practitioners and researchers who believe it is most important to introduce the
technology industry to girls in elementary school, there is significant support for programs like
Black Girls Code (BGC). BGC helps (mostly) girls of color get interested in coding and gain
skills needed to give them experiences to create new technology like video games and robotic
programming (Black Girls Code website). A 2020 study paired intersectionality theory as a lens
with case study methodology to understand how Black women created and encouraged
confidence-inspiring educational experiences for Black girls in STEM. The study found that
Black female teachers uniquely understood Black girls’ positionality, which allowed them to
help bolster their confidence and inspire them to do their best work in STEM (Nash & Peters,
2020). This research suggests that if there were more Black women both in STEM education and
in senior leadership roles in the technology industry to offer mentorship and sponsorship, more
Black girls would persist in the STEM school pipeline (Blosser, 2019; Lisberg & Woods, 2018;
Ong, 2011) and, potentially, in the technology industry (McGee, 2018; Mendez et al., 2020).
14

Another perspective is that young Black women fall out of the STEM curriculum in
college due to continuous race and gender bias and discrimination in the classroom as well as on
campus (Blosser, 2019; Leath & Chavous, 2018; Rankin & Thomas, 2020). A University of
California qualitative study examined the experiences of 21 Black female engineering and
computer science graduate students as they related to their gender and race through the lens of
Black feminist thought (BFT). BFT is a theoretical framework created by Black women that
incorporates, validates, and centers on the unique voices and experiences of Black women
(Collins, 2000; Few et al., 2003). It is important to note that BFT opposes stereotypical ideas of
Black womanhood (Collins, 2000). The study found that Black female students experienced
anxiety, stress, stereotype threat, and additional harmful consequences including the added
psychological burden of code-switching during their tenure as graduate students (Spencer et al.,
2022). Several additional studies have revealed that Black women in STEM college
environments are exposed to sexism, racism, and other intersecting social identities that
collectively contribute to stress, anxiety, and feelings that they do not belong (Blosser, 2019;
Rankin & Thomas, 2020; Solomon et al., 2018; Stitt & Happel-Parkins, 2019)
Conversely, there are research findings indicating that although women of color,
including Black women, are graduating with STEM degrees, they are not being hired into the
technology industry (Xu, 2021). There is also evidence that despite their STEM degree, Black
women have proactively decided not to enter the technology profession due to the
aforementioned experiences in college, mainly racial and gender discrimination and bias
(Blosser, 2019). Men hold 51% of STEM degrees but 76% of tech-related jobs (USGAO, 2017).
Also, in 2021, there were 700,000 open technology roles in the U.S., but only 80,000 computer
science graduates (Code.org Advocacy Coalition, 2022). This data suggest that the problem is
15

not in the college pipeline, but is instead tied to gender and race in the hiring of Black women in
higher-paying jobs in the technology industry (Harrison, 2019; Xu, 2021).
Finally, there is a group of Black women who make it into the technology industry but
eventually leave it for various reasons. Research indicates that they leave because of their
experiences with racism, sexism, discrimination, Black fatigue, and any combination of the
above (Espinosa, 2011; Scott et al., 2018; Yamaguchi & Burge, 2019). From 2007 to 2015,
Black women accounted for 13% of all technology industry attrition—more than any other
demographic (Gee & Peck, 2017). However, despite these challenges, there is a group of Black
women who continue to persist in technology, many of whom are examined in this literature.
One of the most significant challenges Black women in technology face is the concrete wall,
which is reviewed in the next section.
Concrete Wall
The concrete wall is a metaphorical representation of the opaque and nearly unbreakable
barrier that keeps Black women outside of the social power structure in the technology industry
(Beckwith et al., 2016; McGee, 2018). Babers (2016) used concrete as a metaphor to call
attention to the differences in the challenges faced by White women (the glass ceiling) versus
those confronting Black women in corporate settings. The nature of glass is that a person can see
what is on the other side—and it can shatter. Concrete is heavy, opaque, and can merely crack,
suggesting that White women have more likelihood of breaking through to the other side
(Babers, 2016).
While 3% of the technology workforce consists of Black women (U.S. Bureau of Labor
Statistics, 2020), they make up less than half of 1% of the technology C-suite (U.S. EEOC,
2014). Research suggests that social barriers like networking, influential colleagues, the lack of
16

mentors and sponsors, and high visibility initiatives (usually assigned by sponsors) are some of
the main obstacles Black women face in climbing the proverbial career ladder (Beckwith et al.,
2016; Giscombe & Mattis, 2002). Khosrashahi (2021) posits that the technology industry’s
problem with Black women is not hiring them; rather, it is the organizational culture and climate
that cannot keep them. The concrete wall, among other obstacles, continues to keep Black
women out of positions of leadership and influence in many sectors (Bernard et. al, 2021;
Rosette & Livingston, 2012; Sims et al., 2019), including the technology industry (Khosroshahi,
2021; Solomon, 2018; Teich, 2021). The next section addresses the negative impacts on the
technology industry that result from this exclusion.
Impacts on Technology Industry Resulting From the Absence of Black Women
Without Black women substantially contributing to the technology industry in greater
numbers, the industry’s capacity for innovation has been hampered (Delesline, 2022; Lorenzo, et
al., 2017; McCallaghan et al., 2019). In addition, there is evidence of the proliferation of biased
artificial intelligence (AI) algorithms and skewed machine learning (ML) datasets (Hill, 2020;
Joyce et al., 2021; Lohr, 2018; Zou & Schiebinger, 2018). Not only has the absence of Black
women hurt the technology industry’s advancement and contributed to biased innovations, but
also on average, Black (male and female) tech founders receive $36,000 in early-stage venture
capital funding, compared to $1.3 million in funding that White men receive (McGirt, 2017). The
following sections examine how the absence of Black individuals, especially Black women, has
hampered innovation (Lorenzo et al., 2017) and, more importantly, propagated preferential bias
for Whites, (mostly men) and against Blacks (mostly women) (Lohr, 2018).
Black Americans, especially Black women, have historically been excluded from leading
efforts to build new technologies (Delesline, 2022; Lorenzo et al., 2017; McCallaghan et al.,
17

2019). Therefore, the data suggest not only that are there human biases built into the systems
they create, but also that there are additional gaps in the features, products, and services that
could have created more broadly usable technology (Delesline, 2022). When businesses have
inclusive organizational cultures and policies, they may see a 59% increase in innovation
(Lorenzo, et al., 2017) and a 38% better assessment of market interest and consumer demand
(McCallaghan et al., 2019). When Black women are excluded from the technology industry, not
only is innovation stunted and market reach limited, but there are also dire consequences for
Black women—and, to some extent, all people of color as the future is being developed today
through innovations like AI and ML (Buse et al., 2017; Hill, 2020).
New technology, such as AI and ML, often mirrors the same biases as the people who
create it (Hill, 2020; Joyce et al., 2021; Lohr, 2018; Zou & Schiebinger, 2018). For example, a
study out of the MIT Media Lab calculated that when AI is used in facial recognition software,
the error rate on a White man is 1% (Lohr, 2018), whereas the software is 35 times more likely
to make errors in recognizing a Black woman (Lohr, 2018). Every other demographic is
somewhere between a 1% and 35% error rate. This can result in the wrong individuals being
detained or arrested by police, which is exactly what happened in 2020 to Robert Janeenn-
Borchak Williams in Detroit, MI, when he was falsely arrested based on an erroneous match
(Hill, 2020). The research suggests that until we have more people of color—including Black
women—writing less biased, more inclusive, and more accurate code, the technology will
continue to embody the same biases as those held by the people—mostly White men—who
created them, along with the assumptions and non-assumptions being made about the
technology, such as who is using it and how it will or will not be used (Buse et al., 2017; Ireland
et al., 2018; Jackson, 2013; Charleston et al., 2014).
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In addition to the tech workforce building discrimination and prejudice into the code,
another main driver of bias in AI is the data used to train the software (Giovanola & Tiribelli,
2022; Noble, 2018; Obermeyer et al. 2019; Zou & Schiebinger, 2018). Most ML systems are
trained on vast amounts of data. For example, developers typically build datasets by scraping
websites, a process of automatically pulling data from one site, such as Google Images or
Wikipedia, into their software. These methods, wherein some groups are more represented than
others, produce training datasets that teach the machines gender, racial, ethnic, and cultural
biases (Zou & Schiebinger, 2018). This is especially concerning because we rely on AI/ML
technology to make sound and fair decisions about people’s health (Giovanola & Tiribelli,
2022). For example, AI code has been found responsible for recommending that Black patients
receive less health care than White patients with the same conditions (Johnson, 2019; Obermeyer
et al., 2019). To remedy this type of discrimination, the research recommends that Black women
and other women of color be at the forefront of designing, developing, and coding new AI/ML
technology to help ensure inclusivity, equity, and fairness for all people (Buse et al., 2017;
Noble, 2018).
Challenges and Barriers to Black Women Remaining in Technology
There are gender challenges facing women in technology (Arulampalam et al., 2007;
Buse et al., 2017; Lewis, 2017; Ryan & Haslam, 2007; Ryan et al., 2007), just as there are racial
challenges facing Black Americans in technology (Bradley, 2021; Delesline, 2022; Mondisa,
2021; Rodriguez, 2016). These gender and racial challenges are compounded for Black women
in technology (Allen & Lewis, 2016; Beal, 2008; Khosroshahi, 2021; McGee, 2018; Rosette &
Livingston, 2012; Solomon et al., 2018; Tedrick, 2020). This section covers the roles of gender,
race, and the intersectionality of both as they pertain to Black women in the technology industry.
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Role of Gender
Women are underrepresented in the technology industry; nearly 50% of the U.S.
workforce are women, yet only 27% are employed in the technology industry (U.S. Department
of Labor, 2020). All women, regardless of race, are part of the leaky pipeline previously
described for very similar reasons. Women who leave computer science or engineering majors
often do so because they experience gender bias, lack of belonging, and sexual harassment
(Daley, 2021; Scott et al., 2018; Xu, 2021). Moreover, women who remain in technology often
continue to experience the same phenomena (Wilson & VanAntwerp, 2021).
In technology, women continue to lag behind men in earning potential, advancement and
promotion, and senior leadership (Barroso & Brown, 2021; Scott et al., 2018; Semega et al.,
2020). Some progress has been made across multiple industries, especially for White women,
who have made the greatest gains—rising from 22% to 29% of managers between 1985 and
2000—and have since plateaued there, but Black women still lag behind (Dobbin & Kalev,
2016). According to a recent study of feminist women in the workforce, the majority reported
being challenged by gender discrimination, felt underemployed, or were passed over in their
current positions (Diekmann, 2022). In a small but powerful phenomenological research study on
Black women in positions of power and influence, all participants unanimously agreed that the
progress of Black women is not keeping pace with some of the gains that women as a whole
have made in society (Johnson, 2021).
Compensation Inequity
The technology industry as a whole offers above-average earning potential for both its
executives and subordinate employees. In 2015, technology employees earned a median income
of $89,000—compared to a median income of $78,000 for employees outside the technology
20

industry (GAO, 2017). However, as in other U.S. industries, there is a disparity in what men and
women earn in the technology industry (Arulampalam et al., 2007). A 2020 Exabeam
Cybersecurity Professional Survey reported that, on average, men made $91,000 whereas women
averaged $62,000 per year. In addition, according to a 2021 survey from Hired, a technology
recruiting job posting website, men were offered higher salaries than women for the same exact
job title at the same company 59% of the time.
Limited Upward Mobility
Research findings throughout the past two decades indicate that women face gender
discrimination in the form of limited upward mobility (Lewis, 2019; Ryan et al., 2011; Scott et
al., 2019). Of the women who work in technology today, 66% of them report that there is no
clear path to upward mobility, and 39% report being passed over for a promotion because of
their gender (Daley, 2021). The term glass ceiling went mainstream in the 1980s when it was
popularized in books and articles about barriers to working women in corporate roles (Lewis,
2019). In 1991, the U.S. Department of Labor formalized the term glass ceiling to mean real or
perceived barriers for women that prevent qualified candidates from advancing into senior
leadership.
A large, seminal study in 11 E.U. countries between 1995 and 2001 measured wage gaps
in various industries. Results indicated a widespread proliferation of the glass ceiling
phenomenon, specifically with greater disparity of earnings between men and women at the tops
of organizations throughout Europe, except for two countries: Ireland and Spain (Arulampalam
et al., 2007). In addition, Cardador and Hill’s (2018) research revealed disparities in paths of
advancement at some companies that were differentially related to whether the engineer was
21

male or female. Additional research supported this finding in a study investigating why men and
women leave the engineering field (Fouad et al., 2020).
White and Black women also experience the phenomena known as the glass cliff, which
refers to a situation that may appear at first to be an opportunity, but is usually rife with obstacles
and a higher likelihood of failure (Cook & Glass, 2014; Roberts & Mayo, 2019b; Ryan &
Haslam, 2007; Ryan et al., 2011). Research suggests that when there is an opportunity in
leadership with greater risks, women and people of color are more likely to be promoted into
such perilous leadership roles—and with weaker-performing teams (Cook & Glass, 2014). In the
event of failure, women are not afforded the same resources or leeway to recover from mistakes
(Roberts & Mayo, 2019b). In the wake of George Floyd’s murder in 2020, organizations
throughout the U.S. sought to hire Black Americans, many of them women, to lead DEI
programs—but without any real financial or social support that would be needed to make their
jobs successful (Thompson Payton, 2020). After just a couple of years, some of these women
have left because they were unable to make any real headway or change. The role of race as it
relates to Black women in technology is discussed in more detail in the next section.
Role of Race
Black individuals in the technology industry often contend with historical race-based
stereotypes, discrimination, and biases (Basile & Black, 2020; Martin, 2013; McGee & Bentley,
2017). This phenomena is reflected in the data on earnings and compensation: Black Americans
earn significantly less than White Americans. Black men earn, on average, $0.87 for every dollar
White men earn (Gruver, 2019), while Black women—who experience the compounded
oppression of both racism and sexism—earn, on average, $0.63 for every dollar White men earn
(Miller, 2020; Tucker & Temple, 2017).
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The technology industry in the U.S. is projected to grow 13% by 2030 (JFF Labs Report,
2022). However, although Black employees make up nearly 12% of the total U.S. workforce,
they account for less than 8% of the technology workforce (JFF Labs Report, 2022). Across all
industries, Black employees make up 12% of entry-level jobs (McKinsey, 2021), but they
account for only 7% of first line management roles. According to the same 2021 McKinsey
report, only 2% of all U.S. businesses are Black-owned. In 2021, Black founders received more
funding than in any previous year—yet this record-setting sum still accounted for just 1% of all
venture capital funds disbursed in 2021 (Suber, 2022).
In addition to lower pay and little assistance for Black Americans in the technology
industry, historically, there has been weak support for Black tech culture in the mainstream
(Delesline, 2022). There was a blip on the radar in the 1980s when America witnessed the novel
phenomenon of “nerdy” Black characters, both on television (Jaleel White as Steve Urkel on
Family Matters) and in film (Larry B. Scott’s starring role in Space Camp as Rudy Tyler, a
Black genius who accidentally finds himself in outer space). After that role, it could be argued
that he was typecast in Hollywood, since he went on to act in “Revenge of the Nerds” in 1984
and “Revenge of the Nerds II: Nerds in Paradise” in 1987 as the Black, openly gay (and nerdy)
Lamar Latrelle. Black women, some would suggest, are the translators that help bring Black nerd
culture into the mainstream, like Stacey Abrams coming out as a Trekkie, or Lizzo, who touts
her high school band nerd background as a flute player (Bradley, 2021).
Stereotype Threat
Stereotype threat is an overall feeling of consternation and anxiety experienced by
members of a historically marginalized group who fear that they will be seen to confirm negative
group stereotypes; such feelings tend to impair performance (Steele, 1997, 2010; Steel &
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Aronson, 1995; Steele et al. 2002). Cues that can trigger stereotype threat in the workplace
include artifacts in the physical environment, inappropriate diversity training (or lack thereof),
and representation of the same demographic (Duguid, 2011; Emerson & Murphy, 2014). In
technology, where the dominant demographic is White men, the research data indicate that there
are few areas where Black women see artifacts or a critical mass of the same demographic in the
environment to make them feel that they belong (McGee & Bentley, 2017; Tedrick, 2020; Teich,
2021). A 2018 study showed that Black women are more likely than White women to be
sexually objectified at work (Anderson et al., 2018). Research also indicated that Black women
are more likely than Black men to experience institutional and cultural racism (Carter &
Reynolds, 2011; Morton & Parsons, 2018).
Stereotype threat can also be greater or lesser, depending on how the individual
personally subscribes to the stereotype and/or has positive or negative internalized attitudes
toward their own race, as shown in a 2006 study of 98 Black American students. This study
found that those who had lower stereotype threat conditions performed better on tests compared
to students who had higher stereotype threat conditions (Davis et al., 2006). The results of a later
study strongly suggested that the underrepresentation of a marginalized group in a work
environment contributes to the experience of stereotype threat (Block et al., 2011). Finally, there
is ample research and evidence to indicate that Black women experience stereotype threat, which
not only can impact performance, but also can result in added stress, frustration, dread, and
Black fatigue (McGee & Bentley, 2017; Sims & Carter, 2019; Solomon et al., 2018; Spencer et
al., 2016; Winters, 2020b).
Stereotyping and categorization of Black women and other women of color can create
occupational segregation, especially in STEM, as indicated by the findings of Professor Joan
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Williams after conducting 60 in-depth interviews with female scientists of color. Every one of
them reported that, at some point in their careers, they had been mistaken for a janitor at their
workplace (Williams & Dempsey, 2014). Such negative personal, social, and environmental
experiences reinforce the feelings associated with stereotype threat and isolation that are also
reported by Black women in the technology industry (McCluney & Rabelo, 2019). The
following section reviews the literature and research on Black women’s sense of belonging in the
technology industry.
Belonging
Belonging, as defined by psychologists Baumeister and Leary (1995), is a sense of
having frequent and positive interpersonal connections that make a person feel truly cared for.
This psychological comfort in a work environment is essential for positive performance (Wilson
& VanAntwerp, 2021). The data indicated that engagement and performance tend to decrease
among employees who do not feel a sense of belonging to the group (Casad & Bryan, 2016) and
in the technology organizational culture and climate.
Research suggests that Black women in the technology industry contend with multiple
challenges, such as bias, gender and race discrimination, and marginalization, which can make
them feel isolated, demoralized, and fatigued (Burrows et al., 2021; Carr et al., 2019; Casad &
Bryant, 2016; Solomon et al., 2018). McCluney and Rabelo (2019) argue that Black women, in
particular, are challenged by paradoxical friction between others’ perceptions of where they
belong and their own sense of being, which creates undesirable conditions of visibility. These
conditions are perceived through the lens of social power that structurally and hierarchically
normalize Whiteness and maleness in organizations; because of opposing intersectionality, these
conditions inherently devalue the social identities of Black women (McCluney & Rabelo, 2019).
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A narrative-based research study on 93 Black women in technology, which leveraged the
theory of intersectionality, found that the goal for most of the participants was to be
acknowledged, heard, and respected for their expertise (Yamaguchi & Burge, 2019). However,
the authors noted that an experienced, more tenured participant succinctly stated that she strives
for her technology peers to see her first and foremost as a computer scientist (who also happens
to be a Black woman). These findings complement those of Burrows et al. (2021), who
recognized the importance of identity-safety cues (also known as diversity-safety cues or
signals), which indicate that all individuals are valued at an organization. Identity-safety cues not
only make members of an organization feel that they belong, but also enable them to flourish in
their roles. The next section covers additional literature and research on the intersection of
gender and race.
Intersectionality of Gender and Race
Many compounding oppressions exist at the intersection of gender and race for Black
women in the workplace and in life (Collins, 2000; Collins & Bilge, 2020; Crenshaw, 1989). The
data indicated that in predominantly White and male work environments, Black women often
experience unwanted attention for basic cultural differences (Solomon et al., 2018; Xu, 2021).
These differences are uniquely attributed to Black women and as such are neither fully nor even
partially experienced by either White women or Black men. In this section, I examined the
literature and research on the unique intersection of being Black and female as it relates to the
workplace and the technology industry.
Double Jeopardy
A report published by Reveal, a nonprofit dedicated to investigative reporting, found that
in 2016, zero Black woman were employed by ten large technology companies in Silicon Valley
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(Reveal, 2018). In many industries, especially in technology, the data suggest that Black women
experience a double bind or face double jeopardy: being neither White nor male, they are doubly
socially disadvantaged at work (Allen & Lewis, 2016; Beal, 2008; Beckwith et al., 2016;
Charleston et al., 2014; Ong et al., 2011; Teich, 2021). The current technology culture provides
little support and fewer opportunities for Black women, who are typically promoted at a slower
rate than both White women and Black men (Castilla & Benard, 2010; McGee, 2018).
Although the technology industry touts a culture of meritocracy that is aimed at
eliminating bias in promotion and compensation (McGee, 2018), research suggests that tech’s
ostensibly meritocratic system has increased the pay gap between women and men (Castilla &
Benard, 2010; Mun & Kodama, 2021). This outcome is referred to as the meritocracy paradox
(Castilla & Benard, 2010). Research has shown that White men benefit from more favorable
performance reviews than any other demographic in the U.S. (Beckwith et al., 2016; Castilla,
2008). In contrast, the data indicated that Black women feel most stalled in their technology
careers due to mediocre performance reviews and a lack of growth opportunities (Ashcraft et al.,
2016; Sherbin & Rashid, 2017).
Few Black women occupy leadership roles, thus limiting opportunities among Black
women for social connection, mentorship, or sponsorship (Beal, 2008; Sims & Carter, 2019;
Yazeed, 2020). This is especially true in the technology industry (Twine, 2018). The research
suggests that Black women observe that they are often more educated than their White male
peers and overqualified for their roles (Roberts et al., 2019; Smith & Nkomo, 2021). However,
despite such apparent advantages in merit, women of color—especially Black women—are not
advancing at the same rates as their peers (Ashcraft et al., 2016; Wright, 2005) and face a greater
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risk of gender- and race-based workplace harassment (Berdahl & Moore, 2006; Clancy et al.,
2017).
Black Fatigue
Black fatigue, defined by Winters (2020a) as “repeated variations of stress that result in
extreme exhaustion and cause mental, physical, and spiritual maladies” due to systemic racism
(p. 17) is unacknowledged in the workforce in general, and across the technology industry in
particular. Other academics and scholars refer to this added stress as an “emotional tax” or
“Black tax” (Travis et al., 2016). Regardless of the label given to this phenomenon, over time,
according to the research, it leads to Black women growing demoralized in the workplace
(Khosrashahi, 2021; McCluney et al., 2017; McGirt, 2017).
In addition to the Black fatigue women experience in the technology industry, they are
also often asked or volunteered to be the cultural ambassadors responsible for addressing the
needs (and often, complaints) of other Black employees (Roberts & Mayo, 2019a; Roberts et al.,
2019; Sanchez-Hucles & Davis, 2010). This happy-to-do-anything mothering role is a stereotype
depicted as mammy in literature and films that originated when Black women essentially
mothered both White children and their own during Jim Crow and slavery (Reynolds-Dobbs et
al., 2008). Research suggests this stereotype, among others, has hindered career advancement for
Black women for decades (Rabelo et al., 2020). Asking Black women to do two jobs for the
(usually under-market) compensation of one contributes to conflicted feelings between wanting
to support other Black individuals while also avoiding the mammy stereotype and doing the
work they are being paid to do without the added tax. Not only does this contribute Black
fatigue, but it is also a unique type of female Black fatigue that Black women experience because
of the intersectionality of their gender and race.
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Promising Evidence-based Actions to Improve Representation of Black Women
There are ways that technology companies can start to not only improve the
representation of Black women but also work to drive equity for all. The research suggests that
improvement starts with education and accountability in leadership, recruiting and hiring
functions, and throughout all levels of the organization (Dobbin & Kalev, 2017, Roberts &
Mayo, 2019a). Mentoring and sponsoring Black women in STEM and technology has been
shown to help retain and promote Black women employees (Charleston et al., 2014). There is
evidence that creating a culture of inclusivity and belonging holds one of the many critical keys
to hiring, retaining, developing, and promoting Black women in technology (Dobbin & Kalev,
2017; Solomon et al., 2018). The next section starts with leadership education, training, and
accountability.
Leadership Education, Training, and Accountability
Scholars have not reached a consensus on what constitutes effective DEI programming
and what evidence supports its application. Some research suggests that mandatory diversity
training could improve the awareness of both employees and leaders (Burrows et al., 2021;
Onyeader et al., 2021; Rabelo et al., 2020). Other scholars posit that quotas are more effective at
increasing demographic diversity (Hamplová et al., 2022; Velkova, 2015). Yet other researchers
refute the effectiveness of mandatory training and quotas alike, and instead maintain that to
effectively impact an organization’s diversity and inclusion, organizations must change their
culture (Dobbin & Kalev, 2017; Forscher et al., 2019; McCluney & Rabelo, 2019). However, in
their mixed-methods study of 93 Black women in computing through the lens of
intersectionality, Yamaguchi and Burge (2019) found that one of the most important ways to
support Black women in technology is by linking their specific demographic numbers in
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recruiting, retention, growth and development, and promotion to the success metrics of both its
leaders and the organization.
Most scholars can agree on the importance of taking an honest look at the current
employee base through a diversity lens (Dobbin & Kalev, 2017; Forscher et al., 2019;
Yamaguchi & Burge, 2019). Leaders, most of whom are White men, must encourage open
conversations about race and gender (Roberts & Mayo, 2019a) and hold themselves and others
accountable to set standards and goals (Rabelo et al., 2020). Next, they must look at creating
targeted recruiting efforts for underrepresented groups, which have been shown to drive diversity
(Llado-Farrulla et al., 2021; McGee, 2018; Xu, 2021). Finally, DEI departments should be raised
to the C-level (Beckwith et al., 2016; McGee & Bentley, 2017; Roberts & Mayo, 2019b).
Mentorship and Sponsorship
There is strong evidence to suggest that both mentorship and sponsorship are critical to
providing Black women with safe spaces in their careers to grow, develop, and experience
success and failures that are not attributed to their race and gender (Charleston et al., 2014a;
Ireland et al., 2018; Roberts & Mayo, 2019b). A prominent component of SCT is modeling (or
the social aspect of observing others), by which learning can take place vicariously (Bandura,
2001; Schunk, 1987; Schunk & Usher, 2019). The following section covers research on the
relationships among mentors, sponsors, and professional Black women, and how these impact
their ability to persist (or not) on their current path.
Some research that suggests Black individuals benefit most from other Black mentors
(Charleston et al., 2014b, Nash & Peters, 2020). However, there is also empirical data to support
that if White mentors openly self-disclose more to Black mentees about their own professional
path and personal experiences, there is a decreased negative effect (Leitner et al., 2018). Leitner
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et al. (2018) also found that among the mentees who had interactions with the mentor with
increased self-disclosure, they performed better. These findings could open the door for more
non-Black mentors, who greatly outnumber Black mentors, to mentor Black women successfully
and effectively in the technology industry, resulting in less attrition, more development and,
potentially, higher rates of promotion (Ireland et al., 2019; McCluney & Rabelo, 2019).
In their phenomenological study of non-White faculty, Mendez et al. (2020) found that
while all people, at all career levels, seek career development to support engineering promotion,
mid-career engineering faculty showed a greater interest in receiving sponsorship and
mentorship. Mentorship programs that support Black women working within the technology
organizational culture, climate, and environment could help advance their careers (Burrows et
al., 2021; Yamaguchi & Burge, 2019). There is additional evidence and research to suggest that
an environment created to help support underrepresented groups of technical and non-technical
professionals would allow for career development resulting from both mentorship and
sponsorship (Higgins & Kram, 2001; Mendez et al., 2020; Xu, 2021).
Sponsorship, also studied by Mendez, is a critical component in creating visibility, which
can, in turn, create opportunities for greater responsibility and promotion (Burrows et al., 2021;
Mahendran et al., 2022; Sherbin & Rashid, 2017). Sponsorship requires more risk on the part of
the sponsor because they are often putting their own reputation on the line when proactively
recommending an individual who may be unfamiliar to the hiring manager or decision-maker
(Sherbin & Rashid, 2017). A 2021 study on sponsorship in the surgical field, a career industry
with a comparable lack of women and women of color—especially when it comes to female
advancement—found that the lack of sponsorship for women limited their ability for promotion
and, consequently, to sponsor other women themselves (Mahendran et al., 2022).
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Similar themes exist in the technology industry. Until there are more women—
specifically, Black women—in technology leadership roles, there will be limited access to
sponsorship opportunities and, consequently, limited opportunities for other Black women to act
as sponsors themselves (McGee, 2018; Sherbin & Rashid, 2017). To increase the number of
Black women in the technology workforce, the data indicate that the technology industry must
transform the organizational climate by creating a culture of inclusivity and belonging. The next
section discusses how this can be done.
Creating a Culture of Inclusivity and Belonging
By extensively interviewing six influential Black women in the technology industry,
Pasarow (2020) identified two common themes on how to improve the culture and organizational
climate of the tech industry, namely: making space for everyone at the table and creating a sense
of belonging. Although the sample size was relatively small, much of the empirical research on
creating an inclusive culture for everyone generally aligns with Pasarow’s results. If an
organization or industry wants to improve their inclusion efforts, the data indicate that they must
create a psychologically safe space and a sense of belonging for their employees (Blosser, 2019;
Burrows et al., 2021; Carr et al., 2019; Casad & Bryant, 2016; Solomon et al., 2018).
According to some research, making space for Black women may trigger feelings of
inferiority, fear, and fragility among White co-workers (Adu-Gyamfi et al., 2022; DiAngelo,
2011). However, in order to create a culture of inclusivity, everyone—especially the most
minoritized and silenced populations, like Black women—must have a vehicle or venue to be
heard (Rabelo et al., 2020). Counterspaces, a concept discussed by Solórzano et al. in 2000 and
recommended by Blosser (2019) as well as Ong et al. (2018) as a way to support
underrepresented groups, are safe social spaces for Black women who must operate in mostly
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White spaces. The data indicate that creating psychological safety is key to supporting Black
employees (Roberts & Mayo, 2019b). Although the notion of counterspaces may appear to be at
odds with the concept of inclusivity for all, they can create a space in the primarily White and
male environment for Black women to belong and feel included (Burrows et al., 2021; Ong et al.,
2018).
Research suggests that finding a sense of belonging is also critical to supporting Black
women in technology (Burrows et al., 2021; Carr et al., 2019; Casad & Bryant, 2016; Solomon et
al., 2018). As mentioned, a social or physical space in predominantly White organizations can
help Black women feel that they belong (Burrows et al., 2021; McCluney & Rabelo, 2019). In
addition, welcoming feedback from Black women and then acting on that feedback is also a way
to engage and support this group (McCluney & Rabelo, 2019; Solomon et al., 2018). Finally,
research findings indicate that to drive a sense of belonging, an organization must take steps to
alleviate stereotype threat (Casad & Bryant, 2016). Changing the culture of one organization is a
formidable and complex challenge; to change the culture of an entire industry is more daunting
still. Although there is no magic-bullet solution that will increase the proportion of Black women
employed in the technology industry, steady (if perhaps slow) progress can be achieved through
many changes implemented and sustained over many years. This will require redesigning
recruiting efforts, focused retention programs, and diverse workforces that feel they belong
(Blosser, 2019; Burrows et al., 2021; Carr et al., 2019; Harrison, 2019; Sherbin & Rashid, 2017).
Theoretical Framework
Theoretical frameworks, according to Merriam and Tisdell (2016), “underly all research”
(p. 84). They exist in every qualitative study as the underlying architecture in which it is created
(Merriam & Tisdell, 2016). Grant and Osanloo (2014) posit the foundation, structure, support,
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and rationale for all components of the research study from the problem statement to the purpose
of the study, including the research questions and study significance, is the theoretical
framework.
The theoretical framework used in this study was social cognitive theory (SCT) informed
by intersectionality. SCT informed by intersectionality was an appropriate lens through which to
examine the underrepresentation of Black women in the technology industry because it is
effective in identifying the personal characteristics, social experiences, and environmental factors
(Bandura, 2001) that contribute to the unique experiences of Black women in the technology
industry based on both their gender and race (Collins & Blige, 2020; Crenshaw, 1989; Solomon
et al., 2018), as well as in understanding their decisions to remain employed in the predominantly
White and male technology industry.
Social Cognitive Theory
SCT uses a triadic framework with dynamic and reciprocal interactions among the
individual, their behavior, and the environment (Bandura, 2001). SCT assumes that learning is
vicarious and that people can learn by observing others. In addition, SCT posits that learning is
an internal process that may or may not result in new behaviors. Thinking, considering, and other
cognitive processes are important in determining what is learned and which behaviors become
self-regulated (Bandura, 2001). Reinforcement and punishment indirectly affect learning,
behavior, and self-efficacy, including the belief that one can accomplish a specific task, which
can positively influence motivation and learning (Bandura, 2001; Schunk & Usher, 2019).
SCT also provided a lens through which to examine environmental and behavioral issues
(Bandura, 2001), such as racism, sexism or prejudice, that impact Black women’s self-efficacy,
agency, and their decisions to remain (or not) in the technology industry. Self-efficacy (more
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specifically, perceived self-efficacy) is a measure of a person’s belief in their abilities to achieve
a certain goal or perform a set task (Bandura, 1997). Finally, agency is a person’s conviction or
belief in their ability to control their environment (Bandura, 1989). This study used Bandura’s
SCT framework and its key concepts as the primary lens through which it answers the research
questions. In addition, the study was informed by the critical race theory tenet of
intersectionality.
Intersectionality Theory
Intersectionality theory provided a framework for identifying and addressing complex
social problems as they relate to power structures (Collins & Blige, 2020; Crenshaw, 1989). In
this research on Black women’s experiences in the technology industry, the impact of
overlapping or interlocking identities (e.g., Black, woman, part of the technology workforce) was
studied simultaneously, and precisely where they intersected, to understand the unique (and often
compounded) oppressions of lived experiences (Collins & Blige, 2020; Crenshaw, 1989; Lorde,
1982). By bridging intersectionality and SCT, I examined how the technology industry’s culture
and climate, Black women’s social experiences, and their personal agency and self-efficacy
shaped their perceptions and, ultimately, behavior to remain in the technology industry.
Conceptual Framework
This study used a conceptual framework that combined ontological and epistemological
concepts, assumptions, beliefs, and methodological and theoretical paradigms as suggested by
Maxwell (2013). The following section introduces and explains the conceptual framework used
for my research study, starting with an overview of the theories before proceeding to a discussion
of SCT informed by intersectionality as well as the themes in the literature and how they were
applied to this research project.
35

Overview of Theories
The triadic structure of SCT framed this research study in three circles representing Black
women in technology, their social experiences, and the technology industry’s organizational
culture and climate with reciprocal double-sided arrows indicating how each influences the
other. The first circle represents the Black woman as an individual, which includes the concepts
of agency and self-efficacy of Black women. The second represents her social experiences,
which include observations and mentorship relationships. The third is the technology industry’s
organizational culture and climate, which is mostly White, male, and lacking in support for
Black fatigue. All three circles are encompassed by the critical lens of intersectionality that
informed this study.
Agency and Self-Efficacy of Black Women
Bandura (2001) described agency as the ability to control one’s own thinking, motivation,
and behavior. There is consensus, thematically in the literature, that Black women are “on guard”
at work (De La Parra, 2021; Li et al., 2018; Winters, 2020a). This perceived feeling can impact
their cognition and behavior in the work environment (Twine, 2018). The literature also suggests
that Black women in technology typically exhibit high self-efficacy, as exemplified by their
ability to continuously perform and execute specific goals and objectives despite oppressions
from intersectional identities such as stereotype threat, systemic and institutional racism, and
microaggressions from coworkers and managers (Sims & Carter, 2019; Stitt & Happel-Parkins,
2019).
Social Experiences of Black Women
According to the research, few Black women occupy leadership roles, which limits
opportunities among Black women for social connection, mentorship, or sponsorship (Sims &
36

Carter, 2019; Yazeed, 2020). This is particularly evident in the technology industry (Twine,
2018). Thematically, the literature suggests that Black women uniquely—because of their
intersectionality—observe that they are often more educated than their peers and overqualified
for their roles (Roberts et al., 2019; Smith & Nkomo, 2021).
Technology Culture and Climate
The research indicates that being neither White nor male, Black women are doubly
socially disadvantaged at work (Allen & Lewis, 2016; Beckwith et al., 2016; Teich, 2021). The
data show that the current technology culture provides little support and fewer opportunities for
Black women, who are typically promoted at a slower rate than both White women and Black
men (Castilla & Bernard, 2010; McGee, 2018). Finally, the literature also supports that Black
fatigue, defined by Winters (2020b) as “repeated variations of stress that result in extreme
exhaustion and cause mental, physical, and spiritual maladies” due to systemic racism (p. 17)
remains almost universally unacknowledged across the industry.
Intersectionality of Race and Gender
Through the lens of SCT informed by intersectionality, there were several key
relationships among Black women’s decisions to remain in the field; their individual
characteristics, social awareness and experiences; and the technology industry’s culture and
climate. These three concentric components are viewed through the widest lens of
intersectionality, which informed the entire framework for this study. At the center of the
components lies the behavior or decision to remain and persist in the technology industry, as
shown in Figure 1.

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Figure 1
Conceptual Framework for Black Women Persisting in the Tech Industry

38

Conclusion
The literature indicated that Black women’s underrepresentation in technology is a
complex and multifaceted problem. When examining this problem through the lens of SCT, there
were perceived reciprocal relationships between Black women’s social experiences, their
environment, and their own self-efficacy and agency, which coalesced into their decision to
remain in the tech industry. Because of their underrepresentation as well as the intersectionality
of gender, race, and employee in the technology environment, Black women uniquely experience
the social phenomenon called the concrete wall, and many do not remain in the industry. This
study offered a novel contribution to the research that facilitates a better understanding of the
experiences of Black women who remain and persist in the White, male-dominated industry of
technology.
39

Chapter Three: Methodology
The purpose of this study was to understand the experiences of Black women who have
persisted in the technology industry for five or more years. It was framed by social cognitive
theory and informed by intersectionality. This research was guided by an understanding of the
distinct experiences (individual, social, and environmental) of Black women who have unique
gender, racial, and professional social identity intersections. This chapter provides an overview
of the study design and describes the qualitative research methodology, including information
about the participant sample, ethical considerations, recruitment approach, research setting, my
role as the researcher, data collection and analysis, and validity strategies leveraged.
Research Questions
The research questions that were addressed in this study are as follows:
What are the experiences of Black women who have persisted in technology?
a. How has organizational culture and climate shaped Black women’s decisions to persist in
the technology industry?
b. How have individual characteristics shaped Black women’s decisions to persist in the
technology industry?
c. How have social factors shaped Black women’s decisions to persist in the technology
industry?
Overview of Methodology
The design of this study was qualitative, which I deemed appropriate because qualitative
research aims to understand (or create) meaning (Creswell & Creswell, 2018; Merriam &
Tisdell, 2016). Key characteristics of a qualitative study include the following: multiple sources
of data (such as interviews and observations), data are typically collected in the participant’s
40

natural setting, participants are selected purposefully, and the researcher is the main data
collection instrument (Creswell & Creswell, 2018; Merriam & Tisdell, 2016). Qualitative design
uses words as data—rather than numbers—for interpretation and analysis (Braun & Clark, 2013,
as cited in Merriam & Tisdell, 2016) and requires reporting on multiple perspectives to help craft
a holistic picture of the problem (Merriam & Tisdell, 2016). The site of this study was the
technology industry, and participants were in a location of their choosing. This allowed for
participant privacy, convenience, and little or no overhead costs, as recommended by Merriam &
Tisdell (2016). Individual interviews were used for collecting the data to answer the research
questions as shown in Table 1.

Table 1
Data Sources
Research questions Interview
RQ: What are the experiences of Black women who have persisted in
technology?
X
RQa: How has organizational culture and climate shaped Black women’s
decisions to persist in the technology industry?
X
RQb: How have individual characteristics shaped Black women’s
decisions to persist in the technology industry?
X
RQc: How have social factors shaped Black women’s decisions to persist
in the technology industry?
X

41

The Researcher
As a non-Black woman engaging in a critical form of qualitative research with Black
women, I followed Merriam and Tisdell’s (2016) recommendation to be mindful of two key
components: the dynamics of insider–outsider groups and the positionality of participants and
myself as the researcher. To ensure I remained mindful of both factors, I engaged in self-
reflexivity throughout the study and communicated transparently about my positionality and
privilege, as suggested by Merriam and Tisdell (2016). I am aware of my own White privilege
and of the fact that my race can put me in a position of authority or oppressor, depending on the
perceptions of my participants. As someone who does not share the lived experience of Black
women, I prioritized close collaboration with a close-knit group of Black female peers to
candidly review my approach to this research, interview questions, and appropriate inquiry into
their experiences.
The roles that I occupy as they relate to this topic are that of being a woman (albeit not a
Black woman), a researcher, and a leader in a technology organization. The power structures that
intersect with my identity and social roles include, but are not limited to, racism and sexism. My
positionality as a White woman employed at a technology company may have provided research
opportunities that had the potential to expose new obstacles and insights. Being inside a tech
organization provided me with insider information, such as first-hand experiences of the culture
and climate, efforts undertaken to promote employee diversity and equity, and observations of
these policies’ effects on employees.
Another social dynamic I considered is the relationship between the researcher and the
participants. The power in this relationship is “disproportionately on the side of the researcher”
(Glesne, 2011, p. 172), which is a microcosm of the systemic racism that most Black women
42

have experienced throughout their lives. It was of the utmost importance that I be transparent
about my positionality and privilege within our socially constructed society, the technology
industry as a leader, and the researcher–participant relationship. In addition, I continue to explore
how I can leverage my positionality, power, and privilege to adequately propose and bring about
meaningful change.
Data Source: Interviews
Data collection involved individual interviews conducted through the lens of SCT, which
focused on individual characteristics, social observations, and the organizational culture and
climate of the technology industry. This lens was informed by the intersectionality of social
identities including Black, female, and technology employee. Leveraging an interview protocol
for consistency (Creswell & Creswell, 2018; Merriam & Tisdell, 2016), I interviewed
participants to understand their experiences shaped by their intersectionality, social observations,
environment, personal characteristics and, ultimately, their decision to remain in the technology
industry. The following sections provide additional insight into my data collection efforts.
This study used interviews for collecting data. Personal interviews followed a semi-
structured (yet purposeful) format as recommended by Merriam and Tisdell (2016) in which the
researcher’s aim is to extract and understand the participant’s thinking and feeling as prescribed
by Patton (2015). This format provided the flexibility to respond dynamically to participants’
answers, questions, and comments (Creswell & Creswell, 2018; Merriam & Tisdell, 2016). It
also allowed participants to expand on topics that had been vital to their tenures in the
technology industry—which was precisely the data that answered my research questions—while
it also granted both the researcher (me) and the participants the flexibility to delve deeper into
key topics.
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Participants
The target population for my research study were individuals who identified as Black
women, were currently employed in technology, and had remained in the industry for five or
more years. The sampling approach for the study was purposeful and not random, as
recommended (Creswell & Creswell, 2018; Merriam & Tisdell, 2016; Patton, 2015). During the
time of this study, there were about 366,000 Black women in the technology industry in the U.S.
(Zippia, 2022b). The target sample size for this study’s interviews was 10–12 Black women who
had worked and remained in technology for five or more years.
Instrumentation
My interview protocol consisted of an introduction script, 14 semi-structured questions to
collect the data (see Appendix A), and a closing script. The underrepresentation of Black women
through the lens of SCT informed by intersectionality is an under-researched area. This lack of
data necessitated that I create my own instrument because there was not a readily available tool
to adapt or adopt from elsewhere. However, all questions had been field-tested, and adjusted
based on feedback, with two Black women in the target population.
The first question was conversational and general enough for me and the participant to
establish an early rapport and a baseline level of comfort with each other, as recommended by
Patton (2002). The last question asked whether there was anything the participants think I should
know, or that they would like to share with me, which gave the participants the opportunity to
offer additional information not specifically addressed during the interview, as suggested by
Weiss (1994). The other 12 questions addressed the specific parts of the research questions: four
address agency and self-efficacy, three address social experiences and observations, and five
address the organizational environment and culture of the tech industry. All of the questions
44

were open-ended and none of them ask “why,” to support a dynamic and open dialogue, as
recommended by Patton (2002).
Data Collection Procedures
Once I obtained IRB approval of my research study and interview protocol, I identified
potential participants through my professional social network, extended network, Black affinity
groups in my organization, and LinkedIn, the professional social media and job posting website.
The recruitment approach was multifaceted. First, I leveraged my own personal network of
Black women in technology as I have been in the technology sector for over 20 years and have
developed a fairly extensive network. Second, I used word-of-mouth referrals from my personal
technology network to extend the opportunity to their friends, families, and communities. In both
of the preceding approaches, I intentionally excluded any close, personal connections with Black
women who I would consider intimate friends or have close professional ties within my network.
Third, I drove awareness about the opportunity to participate in my research study through my
company’s affinity groups, of which I am a member, as well as through nonprofits such as Black
Women in Technology. Finally, I recruited participants from LinkedIn, the professional social
networking website.
If a candidate expressed interest in participating in the study, I emailed them a link to the
recruitment questionnaire (see Appendix B). The recruitment questionnaire helped determine if
they met the criteria for participation in the study (e.g., they identified as a Black woman; were
currently employed by, and had remained in, the technology industry for five or more years). In
addition to the minimal criteria questions, there were additional demographic questions that
provided supplementary insights into my participants, such as their highest level of education
45

and leadership responsibilities in their past or current role. All of this information helped me, as
the researcher, make a purposeful selection of my research participants.
Once I had identified the study participants and obtained their consent, I scheduled one-
hour interviews with them. I sent email confirmations containing the Zoom video conference
information and calendar attachments. I also sent a reminder two days before the scheduled
interviews as recommended by Creswell and Creswell (2018) and Pazzaglia et al. (2016). Once
the interviews began, I followed my interview protocol, which began with a warm welcome, a
thank-you, a reminder about the purpose of the study, and a request for consent to record and
begin the interview.
Each interview was conducted over Zoom with the transcription and recording features
enabled—with the prior consent of each participant—so I was able to refer back to ensure that I
represented the data accurately; it also enabled me to triangulate data, as recommended by
Merriam & Tisdell (2016). The data for transcription and recording was stored on the Zoom
server, where it was encrypted with the 256-bit Advanced Encryption Standard (AES-256),
which uses a one-time key for the specific Zoom room. Access to the recording and transcription
was limited to the meeting host (i.e., me) and the account administrator (i.e., the University of
Southern California).
In addition to capturing the data via recording and transcription, I also took notes to offer
additional insights and information to refer back to when it was needed. After each interview, I
continued to document observations, thoughts, reflections, and initial intuitions about how the
data tied into my research questions and theoretical and conceptual frameworks. Each interview
lasted between 35 and 55 minutes, which allowed for extra time inside the one-hour commitment
just in case the participant was running late or needed a moment to get acquainted with the
46

technology. It also allowed me to give a brief introduction before requesting another verbal
consent and starting to record the interview.
Data Analysis
Data analysis began with collecting and combing through all of the data generated by the
interviews, including transcripts and field notes. The goal of qualitative data analysis is to extract
meaning and tease out information patterns from the data—in my case, interviews—to answer
the research questions (Merriam & Tisdell, 2016). Once there was a comprehensive review of all
of the data, I began the process of winnowing—that is, focusing in on some of the data, as
recommended by Creswell and Creswell (2018). From there, I created segments (or units) of data
that were identified and labeled, as suggested by Merriam and Tisdell (2016). These segments
included themes that emerged from the data and then compared, assigned codes, and categorized,
as suggested by Merriam and Tisdell (2016). Codes were created to begin the qualitative analysis
of textual data as recommended by Gibbs (2018) and segmented into themes and sub-themes.
The findings that appeared from the themes and sub-themes are described in detail in chapter
four.
Credibility and Trustworthiness
To ensure credibility and trustworthiness of the data and findings from my qualitative
study, I leveraged strategies recommended by the extant literature pertaining to my research
focus. To improve study credibility and researcher trustworthiness, Patton (2002) recommended
beginning with sound engagement in data collection efforts. I documented major decisions
related to the study and maintained an audit trail, as suggested by Patton (2002). My intention
was to provide enough information, logic, and rationale for many of the significant decisions
made in my study to offer transparency and increase trustworthiness. The researcher is the data-
47

collection instrument, and therefore, the trustworthiness of data is dependent on the
trustworthiness of the researcher (Merriam & Tisdell, 2016; Patton, 2002).
During the interviews, I checked in with the participants to confirm that I had clearly
understood them (thereby ensuring that I am collecting accurate data) before I proceeded to the
next point as recommended by Creswell and Creswell (2018). I also incorporated reflexivity, a
practice of reflection about how the researcher’s background, biases, and assumptions have the
potential to shape their understanding or interpretations of the data they collect (Merriam &
Tisdell, 2016). Creswell and Creswell (2018) recommended two points that should be covered:
past experiences with the research problem or setting to help explain the connection between
researcher and the study and how the past experiences might shape researcher interpretations.
Therefore, I followed the Creswell and Creswell (2018) suggestion to incorporate reflexive
thinking into the study with memos or notes that are written while conducting the research as
reflections of the researcher’s personal experiences paying special attention to considerations
about how they might have shaped their interpretations of the results.
Ethics
The research should serve and benefit the participants (Glesne, 2011; Merriam & Tisdell,
2016). Although I designed and scoped the study, I was also assisted in my research by a small—
but essential—group of peers who are representative of the race and gender demographic of the
participant group of focus of this study (i.e., Black women). In addition to peer-reviewing my
interview protocol, this group of Black women also helped ensure that I was checking my own
biases, assumptions, and thought processes so that I was more aware of factors I might otherwise
miss as a non-Black woman. I also considered how participants might be harmed by the research
(Glesne, 2011), such as if an interview question brought up traumatic experiences. My intention
48

was to do no harm with my research, so I informed the participants up front about the purpose of
the study and nature of the interview so they were aware that they could freely opt out if they felt
it would have been an unpleasant or damaging experience for them as recommended by Merriam
and Tisdell (2016) and Rubin and Rubin (2012).
Participants deserve adequate protection, confidentiality, and privacy throughout the
study (Creswell & Creswell, 2018; Glesne, 2011; Merriam & Tisdell, 2016). Accordingly, I
ensured confidentiality by assigning pseudonyms and changing personally identifiable
information (PII). Each participant was presented with study information sheet that explained the
purpose of the study, reminded them that participation is voluntary, assured them that their
information would be kept strictly confidential, and specified how and where their data are
secured, encrypted, protected, and stored.

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Chapter Four: Findings
The purpose of this study was to understand the experiences of Black women who have
persisted in the technology industry for five or more years. It relied on qualitative data collected
through semi-structured interviews conducted by Zoom with 11 participants. The participants
completed a prescreening questionnaire to qualify for the study based on their race, gender, and
longevity in the technology industry. The interview data were examined through the lens of
social cognitive theory (SCT) and informed by intersectionality theory. I interviewed participants
to understand how their experiences have been shaped by their intersectionality, social
observations, environment, personal characteristics, and, ultimately, their decision to remain in
the technology industry. The problem of practice was the underrepresentation of Black women in
the technology industry. The study addressed the following research questions:
What are the experiences of Black women who have persisted in technology?
a. How has organizational culture and climate shaped Black women’s decisions to persist in
the technology industry?
b. How have individual characteristics shaped Black women’s decisions to persist in the
technology industry?
c. How have social factors shaped Black women’s decisions to persist in the technology
industry?
Research findings were organized by theme, which were identified by their prevalence in
the participants’ interviews, that is, the research data. As a threshold for becoming a theme, the
topic, idea, or concept must have been expressed by at least seven of the 11 participants.
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Participants
Between January and March of 2023, I conducted interviews by Zoom with 11 Black
women who have persisted in the technology industry for five or more years. Among the 11
participants, 10 women identified as Black or African American, and one woman identified as
Black or African American and Latina. Nine of the women had at least 10 years of experience in
technology, and three women were managers. Each participant was assigned or chose a
pseudonym. Table 2 lists the relevant data for each participant, including their pseudonym,
occupational function, years in technology, years at their current company, and whether they
manage other employees.

Table 2
Study Participants
Pseudonym Occupational function Years in tech Years at current
company
Manages
others
Sky Sales / Account Management 5-9 years 5-9 years No
Candace Sales / Account Management 20+ years 10-14 years No
Sarah Business Development 20+ years 0-4 years No
Crystal Executive Leadership 20+ years 0-4 years Yes
Janeen Tech Program Management 20+ years 0-4 years Yes
Kassie Sales / Account Management 10-14 years 0-4 years No
Tammy Business Development 5-9 years 5-9 years No
Opal Tech Program Management 20+ years 20+ years No
Mary Technical Writing 20+ years 20+ years No
Lauren Tech Program Management 10-14 years 10-14 years No
Jennifer Executive Leadership 15-19 years 10-14 years Yes

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Findings Organized by Theme
Four thematic findings related to the research questions emerged from the data: (a) Black
women in technology feel they continually need to prove they are competent; (b) Black women
in technology perceive easier inroads for their male and White counterparts; (c) Black women in
technology describe having to learn a language that their male and White counterparts seem to
already know; (d) Black women persist in technology because they love their work. This section
covers each of these themes in more detail.
The themes examined in this section are supported by the evidence presented in the
participant interviews. This data help answer the study research questions about the experiences
of Black women who have persisted in technology for five or more years. Each theme is
organized with broad findings, supported with a synthesis of data from distinct sources, and
whenever contradictory data are uncovered, the conflict is noted.
Theme 1: Black Women in Tech Feel They Continually Need to Prove They Are Competent
Ten of the 11 participants reported feeling that they had to continually prove their
competence. This theme emerged from data interpreted through three sub-themes. First, ten of
these Black women described incessant requests from others to prove their capability and
competence in technology. Second, seven of the women discussed the importance of establishing
and maintaining credibility as a Black woman in technology. Third, four participants discussed
the perils of making a mistake as a Black woman. This section examines the research data for
each sub-theme.
Prove It
Ten of the participants indicated that as Black women in technology, they are required to
repeatedly prove that they are knowledgeable, credible, competent, and capable of performing
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the work they have been assigned. When describing her experiences taking over a project, Opal
expressed frustration at the level of evidence she was expected to provide to stakeholders, “I can
prove everything that’s on my credentials, everything, but you’re still questioning me like this
can’t be.” Candace reported that she overheard an all-male team comment (primarily to one
another), “Oh, we have a girl engineer today,” and as she reflected on the experience she said,
“I’m not a girl engineer. I’m an engineer and I’m running the studio, which they don’t know how
to do.”
Moreover, Sky and Kassie stressed that the technology industry needs to understand and
acknowledge that Black women have the intelligence and ability to do the same jobs as others,
most notably White and Asian men. Sky stated that it is important to have people in the
technology industry who “feel confident in hiring Black women in tech and know that we could
do the same job as a White male.” Kassie explained, “There are so few of us in the industry
[referring to all women], but it’s not because of a lack of intelligence or ability,” suggesting that
those in leadership or other positions of power in the industry might think otherwise.
Only one woman, Tammy, did not specifically address this theme in her interview.
Having entered the technology industry as an intern six years before this study’s interview,
Tammy was the participant with the shortest tenure in the industry and the least experience. She
remained at the company that had offered her an internship after her college graduation. Instead
of feeling that she needed to prove her credibility or competency, Tammy described the
technology culture as “not necessarily catered to you [as a Black woman].” As she went on to
explain, that “can feel isolating.”
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Credibility is Important to Persisting in the Industry for Black Women
The themes of credibility and competency appeared in the data when participants were
asked which personal characteristics or strengths had enabled them to persist in technology for so
many years. Seven of the women mentioned this, including Sarah: “As a Black woman, you
gotta have that credibility. My customers—the vast majority of them—are not Black. To survive
as a Black woman, you have to be able to get credibility and get credibility quickly.” The
sentiment the women expressed, however, was not only that they needed to gain credibility
quickly but also that as Black women, they had to defend their credibility and competence
repeatedly. In the course of explaining how she initiated one project, Opal described that
experience: “I have to go that extra step of getting the extra details, the extra background, and all
of that together before I present. I can never just go into a meeting like I know what I’m talking
about.” She added that despite having run numerous projects, she still has to prove her
competence over and over: “I’ve just learned how to. It’s just a part of being a Black woman in it
[the technology industry]. You’re gonna question me. Okay. I’ve already prepared.”
Opal was not the only participant who described feeling overburdened and undervalued
as a Black woman in technology; eight of the 11 women expressed this sentiment. Candidly
describing her experiences, Crystal noted that she was uncertain whether the skepticism she
faced was tied to gender or race:
The insidious thing about these challenges [is] that as a Black woman, you never know if
it’s because you’re a woman, or if it’s because you’re Black. So, I don’t know which one
of these it is, but I certainly have run into the situation of being underestimated, sharing
my expertise and it being discounted, and, generally, not being listened to.
54

Candace also reported uncertainty about the specific nature of the discrimination she faced: “As
a woman, I don’t know if it’s because I’m a Black woman, it seems like I’m trying to prove
myself. Although the proof is in the pudding. But the people, the decision-makers, don’t really
see it.”
By contrast, Opal reported experiences that revealed the main source of the skepticism
she faced. Several times when she was interviewed by a technology company, the hiring
manager knew she was female but did not realize she was Black. Then, she appeared for the in-
person interview:
My name is just ordinary. There’s nothing different about it, so when I walk into an
interview and there was nothing that indicated on my resume that I was a Black woman,
it kind of makes the people that you’re interviewing with upset. If they haven’t looked at
your LinkedIn, it upsets them. Then, they start questioning your background and start
questioning your schools and your experiences, and that’s where it gets difficult because
it shouldn’t matter.
The repeated experiences of needing to prove their competency and capabilities could
have contributed to seven of the participants obtaining master’s degrees or certifications in
specialty technology or project management, which helped them compete in the industry. When
asked to provide advice to other early-career Black women, Kassie counseled, “Make sure you
are the subject matter expert in whatever area you are in.” Sarah echoed that advice: “You have
to know your stuff and that’s just to get you in the door. To stay there you have to continuously
improve your skills.” Janeen also believed that additional credentials had helped her succeed:
“Get those degrees. Get into those programs. Get the certification and apply.” Mary’s comment
55

summarized the advice: “You are Black and you are a woman, so make sure you can compete.
Learn. Learn everything out there.”
The High Risk of “No Second Chances”
Four participants described the risk of the consequences for any Black woman making a
mistake. A mistake could shatter a Black woman’s credibility and, potentially, her career in
technology, as Lauren stressed when asked about the challenges she faced: “We don’t get the
opportunity for second chances. So, it requires you to be that much more savvy.” Jennifer
expressed a similar sentiment, saying, “I can’t have a day off. I always have to show up.” When
explaining the differences in how she and her White male engineering counterparts could
approach learning new concepts, Candace commented, “We don’t have the luxury of not
worrying about it.”
Whereas many technology employees experience fatigue from the fast pace and constant
demands (Hughes, 2022), Black women have the additional pressure of having to present the
best version of themselves every day, be continually “on”, and produce flawless work. As a
result of that pressure, they are nearly always prepared, and some of them are over-educated for
their positions. Summarizing the situation, Candace stated, “If you’re not curious, if you’re not
thirsting for knowledge, you’re not staying up to date on innovations, then…you’re going to get
left behind.” She added that she drives herself harder than her peers, concluding, “You have to
be three times as qualified” as men to do the same job.
Many of the Black women in this study reported that they have survived in the field by
being more prepared, more knowledgeable, and better educated to perform the same work as
their often White or Asian male counterparts, who may be less experienced. It is especially
difficult, Jennifer commented, “being a Black female and knowing that you’re on average getting
56

paid $.66 to the same dollar that you know a White male is making.” Additionally, all of the
participants expressed being subject to what I call the technology tax: the added mental and
psychological stress of being a Black woman in technology, who cannot make a mistake or have
a bad day without serious or fatal consequences for her career. The next section elaborates on
how Black women working in technology perceive themselves in comparison to their male
counterparts.
Theme 2: Black Women In Tech Perceive Easier Inroads For Their Male and White
Counterparts
All 11 women talked about feeling like men and White peers had easier inroads and
better access to new opportunities and promotions in technology. As a point of clarification, this
meant men of all ethnicities and White women. This theme became evident in data interpreted
through four sub-themes. First, nine of the participants described the challenges of promotion,
sponsorship, and new opportunities in technology as a Black woman. Second, eight women
reported being underpaid for their work in technology. Third, six women reported working
harder than their male peers. Fourth, five women described the need to find their voices in the
technology industry. Fifth, four participants discussed the stereotype of the angry Black woman,
describing having how their awareness of it as well as the need to mitigate it had shaped their
experiences in technology. This section examines the research data for all five sub-themes.
Black Women Perceive Challenges with Promotion, Sponsorship, and New Opportunities
Nine of the participants described how difficult it is for Black women in technology to
find new opportunities or be promoted. “Being a Black woman has hindered promotion
opportunities,” Kassie stated when asked about this central career issue. She added that one of
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the biggest drawbacks in the industry is that Black women are “qualified, [but are] not getting
the opportunities.”
Tammy made similar observations while adopting the perspective of team dynamics and
technology’s organizational culture and climate:
It has felt like in various kinds of team environments that not fitting that kind of norm
and the majority of the team has felt like a disadvantage in some ways. It can manifest
itself in many ways, but it could be both like direct when it comes to working
relationships or opportunities to work on different projects, but also in less direct or more
indirect ways.
These data point to both relational challenges in current projects and, potentially, challenges with
future, higher-level projects, or opportunities for promotion.
Four of the participants identified sponsorship programs as inroads to promotion and
career development and commented that Black women are disadvantaged. Jennifer reported,
“There are many of these for White men, but [we need to] make sure someone is keeping an eye
out for Black women. Make sure people don’t get lost in the fold.” Tammy said, “I think when it
comes to sponsorship, a lot of times similarity does make it easy to build those relationships.”
When asked about her experiences with promotion as a Black woman in technology, Opal
responded, “The trajectory is not as fast. It’s very much slower.” Sky did not mention the speed
of her career trajectory but described technology’s hiring practices and the initial inroads for
White men: “White men are the majority, and they just kind of reach out to their circles if they’re
expanding their teams. They reach out to people they know, which [means they hire]…more
White males.” Mary said, “I have seen my peers, White women, soar,” but indicated that she
enjoys her role as an independent contributor and has not wanted to ascend the ranks.
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Janeen emphasized the challenges related to promotion and career development as a
woman: “Normally, I feel like it’s challenging as just a woman, but then I think there’s been
maybe once or twice where there’s been a challenge as a Black woman.” She also described
behaviors by White men that made her hyperaware of a stereotype about Black women that will
be examined as the next sub-theme. Crystal also indicated that her race may have impeded her
career development less than her status as a wife and mother. She elaborated on this when asked
what had helped her career development:
I’m pretty sure it’s because I’m no longer married. I’m divorced, and I have a son, but for
the last five years, my son has been primarily with his dad. During that time is when my
career did the most upward movement, and it’s because his dad was taking on a lot of
those caretaking responsibilities.
When her son started staying primarily with his father, Crystal had been able to cultivate her
career without the burden of the second shift. Coined by Arlie Hochschild, the term “second
shift” refers to the domestic duties traditionally performed by women for their spouses and
children after they return home from a full day’s work—which in Crystal’s case was spent
building a career in technology.
Finally, Candace had a slightly different perspective than the majority of the participants.
Reflecting on the corporate DEI activities spurred by the 2020 murder of George Floyd, she
remarked, “I’m not sure if I’ve been passed over because I’m Black in the past. Since the
pandemic, it’s almost been a good thing to be Black, because now, all of a sudden, it’s all about
diversity.” While Candace was recently selected for a new opportunity in engineering support,
she noted that she was both the only female member of the new team and the only person of
color.
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Black Women in Technology Are Underpaid
Eight of the participants reported being underpaid for their work in technology. Kassie
related that her manager had let the team know that everyone in the department would be
receiving an increase of 10 to 30 percent, but then spoke to her separately:
I’m doing my job to the best of my ability, training others, being a resource, being there
whenever leadership needed me. But due to the fact that I was a woman of color, I was
not going to receive the maximum increase. That I was only to receive the minimum.
Lauren reported that upon receiving an unexpected pay increase, her initial joy was soon
followed by frustration: “God bless my boss! There’s this slightly bittersweet piece at the end of
it. Like, okay, so I’ve been underpaid this whole time enough for it to be able to be corrected.”
She expressed gratitude toward a boss who had given her a raise though she had not requested it
and possibly did not know how to ask. Requests for raises or promotions and related issues are
addressed in more detail in the third theme, which concerns differences across groups in
familiarity with technology’s language, that is, its unspoken procedures and expectations.
The participants were also asked about challenges that technology’s organizational
culture created for Black women. Mary responded, “It’s a man’s world. Do I believe I’m
underpaid? I do.” She added, “I try not to wear that I am a female or Black. I try not to let people
make it about the difference,” indicating that while men and non-Black women might face fewer
obstacles in the technology industry or be paid more fairly, she refuses to let that deter her from
doing her job well.
Black Women Perceive They Work Harder Than Their Male Peers
Six of the women perceived that Black women have to work harder than their male
counterparts in technology and, for one of the participants, than her White female counterparts.
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When asked whether the organizational culture created challenges, Sky responded directly: “I
feel like we work twice as hard as our White male counterparts.” Opal related the contrast in how
she was treated during different parts of a project. Initially, she explained, she was off-camera:
“So, all you could do is go by my work, my record, and what was being done.” Once the camera
was turned on during a meeting, however, she noticed a striking shift in expectations: “Now,
there is a Black woman on camera and it’s different. The level changes. The bar gets higher, and
you just have to work a lot harder.”
Four women described unfair standards in the technology industry. When asked about the
challenges she faced in the organizational culture of technology, Jennifer responded, “I always
have to be raising that bar and raising that bar, and it just becomes exhausting.” Candace also
described how hard she works compared to her male peers: “I find that I have to do more.”
Sarah’s experiences were similar. “You have to bring a little extra to maintain a basic standard,
just to be able to stay [in technology] and to continue to get respect. You gotta bring a little bit
more than everyone else,” she stated, referring to her male and White female peers.
Finding Their Voices
Five of the women described needing to find their voices or make their perspectives
known while being either ignored or undermined, or experiencing discrimination. Three women
reported finding their voices while being either ignored or mansplained. Although the term was
most likely coined several years later, the concept of mansplaining originated with Rebecca
Solnit's 2008 essay, "Men Explain Things to Me," and refers to men’s condescending
explanations to or over women on topics about which they lack expertise. When recounting her
experiences in technology, Crystal said, “I have been through mansplaining and that situation
where you say something and then someone else repeats exactly what you say, and then people
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listen to that person.” Candace also described having the credit for her work or ideas being taken
by men during meetings: “I find that they would defer to the male on the team, and that male is
not the one putting in all the work.” Jennifer also recounted being a woman in technology meant
being subjected to “mansplaining, being talked over. Not really able to truly find my voice and
really noticing that it was such a man’s world.”
Five women also reported discrimination. Some experiences were so subtle that they
were difficult to grasp and, therefore, challenging to discuss with their leaders. As Candace
described the discrimination, “It’s never outright. It’s like an undercurrent.” Jennifer explained it
similarly: “You know when it’s happening to you, but nobody wants to believe it because it’s not
their lived experience.” She went on to say, “I’ve experienced a lot of micro-aggressions, a lot of
the things that are hard to put a name on.” These types of experiences in technology
environments are difficult to define because when they are discussed, they are subjective in
nature. When describing her challenges with the dynamics of team meetings, Tammy stated, “I
don’t know if it’s because I’m a Black woman, but I think what I’ve internalized or experienced
or observed is that it definitely plays a role.”
Mitigating Stereotype of The Angry Black Woman
Four of the participants mentioned the stereotype of the angry Black woman and how it
affects their behavior at work. Referring to both positive and negative experiences, Opal
commented, “As a Black woman, I have to maintain a certain level. I can’t get as excited as I
want. I have to be really calm.” Kassie also connected her experiences in technology to the
stereotype: “There is a stigma, right, of the angry Black woman because we are in a very
passionate way saying that something needs to be changed or certain things aren’t working.” She
added that having to be hypervigilant about both the environment and her own responses to
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potentially triggering topics made it difficult to broach the topic of leadership opportunities.
Janeen also described the stereotype’s effects:
There’s a stigma for any type of person. But for Black women, it’s the angry Black
woman. I find that I go out of my way to make sure I am not associated with that at all.
So, I take myself very seriously.
She also reported an incident in which she questioned a colleague about the quality of his team’s
work and he replied by yelling, “Why are you getting angry, Janeen?” Continuing, she explained,
“I never raised my voice. I wasn’t even frowning; nothing like that. He said it as loud as he could
so he could plant the seed of an angry Black woman” with the rest of the company’s staff. Sarah,
the fourth woman who discussed the stereotype, described her heightened awareness of it:
You don’t know any time there’s been any contentious situations, I’m always hyper-
aware. You don’t want it to be that angry Black moment. All the stereotypes you know
that you have in common with society, you bring with you to the job. So, you take that
off the table.
Various participants explained how to persist in technology as a Black woman. Mary commented
that it requires “learning how to choose your battles; you can’t wear your feelings on your
shoulders,” and Sarah eloquently noted, “You have to be able to disagree without being
disagreeable.” In the technology environment, Black women have to maneuver within a
treacherous field of cultural landmines, including their leaders’ ignorance. They must advocate
for themselves individually or for what is right more generally without stepping across the
subjective line beyond which they might be perceived as incensed.
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Summary
All 11 participants perceived that men and some White women have easier inroads and
paths to promotion and better access to new opportunities in the technology industry. This theme
was manifested in five sub-themes: (a) Black women perceived challenges with promotion,
sponsorship, and career development; (b) they also believed they are underpaid; (c) they
perceived that they work harder than their male and White peers; (d) they found their voices
despite a tech culture of silencing and ignoring; and (e) they mitigated the possible attribution of
the angry Black woman stereotype for themselves. These themes express key aspects of the
participants’ experiences in technology, including working harder for less money, struggling to
voice their concerns and advocate for themselves, and carefully balancing their passion with
others’ perceptions of them as Black women.
Theme 3: Black Women in Technology Describe Having to Learn a Language that Their
Male and White Counterparts Already Seem to Know
Black women in technology described needing to learn a new way of communicating that
their male and White colleagues seemed to already know. Seven out of the 11 participants
discussed this theme, which is presented in this section as two sub-themes: the lack of
transparency and networking. Seven women identified the technology industry’s lack of
transparency as a barrier to gaining the information needed to develop and be promoted. Seven
women also reported having to learn how to network or how networking is leveraged in the
industry to create opportunities, paths for development, and promotions. This section examines
the research data for both sub-themes.
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The Lack of Transparency
Seven of the participants described having to learn a new way of communicating or
approaching a situation that their male and White colleagues already appeared to understand.
Lauren expressed frustration at the way people are hired and ascend in technology: “I find the
inner workings or mechanisms of these networks to be almost like a closed practice.” In other
words, those who get promoted, usually men, continue to get promoted, whereas she does not
have the language or understanding to break in. Commenting on the industry, Janeen offered, “I
think maybe that’s the thing. It’s just a misconception about how things actually work.” Tammy
also described the problem with language:
There’s so much that’s unspoken or less covered. I think there’s just there’s a lot of coded
language for it sometimes. There are some ways in which people can more easily fit a
mold because it’s the one that you know. It has been built around their style and that’s a
benefit for them. Whereas for me, it’s much more learned.
Tammy went on to say that she has to make an intentional effort to present herself in a certain
way that she would not normally do. Mary indicated there her experiences with White male
bosses differed slightly from her experiences with White female bosses. When she reported to
women, she received raises. When she reported to men, she had to ask for additional
compensation, “I had to go and say, ‘I did this this year. Can you give me a bonus?’”
Of the seven women who described having needed to learn how things work in
technology, five stated that they had learned and used the knowledge. The other two participants
initially expressed frustration about not knowing how things worked and subsequently
exasperation that others already knew. Tammy reported, “I have conversations with people
where I never knew this thing and I have this big Aha! moment, like this is something that
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everyone just knows, and it’s often the White folks that know.” Janeen described learning how
the promotion process works: “I was thinking you just do your job like it’s with school. Do your
job, make good grades, ace your quizzes, ace your tests, and then you graduate with honors. But
it doesn’t really work like that.” She added that her manager, a White woman, had explained
what happens when managers seek promotions for their employees; the information enabled her
to understand, empowered her to act, and taught her a new way of communicating and
advocating for future promotions.
Tammy also reported having to learn how promotions work and expressed frustration
about being unfamiliar with a process that her coworkers already understood:
I’m thinking even of the process for promotion. It’s something that you usually bring up
to your manager proactively, and just how I spent a really long time not knowing that that
was something that was in my hands. I would wait for someone else to bring it up, and
then having had the experience of bringing it up, and in the aftermath learning that it’s a
conversation that could have been positioned differently....It’s just like I didn’t even
know, I didn’t even know how to go about it. And I had peers that somehow did.
Janeen also mentioned that in her opinion, Black women might not understand the
process for raises and promotions. Although she could not say how much others understood,
Black women assume that raises and promotions happen automatically: “I think maybe one of
the hindrances as a Black woman is just feeling that we should have that invite, or thinking we’ll
get the invite when that’s not really how it works.”
Learning the process and how to effectively seek promotions and raises is just one of the
challenges Black women must address to persist in technology. Three of the women mentioned
the lack of transparency and honest communication when a promotion or raise is sought or
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mentioned to leadership. Crystal, who is now a C-level executive, described the reactions she
received upon stating her desire to move from manager to director: “The responses I was getting
were like, ‘I just don’t really see it for you,’ or ‘I’ll know it when I see it.’ So, it was not
anything that I could do anything with.” Such vague feedback thickens the concrete wall
between Black women and the opportunity to develop and thrive in the technology industry.
Jennifer, also an executive at a technology company, related her experience of being on
the other side of the table, witnessing firsthand how the lack of transparency impedes career
progress: “I have the privilege of being in rooms that a lot of people are trying to get to, and they
have no idea what's holding them back as no one’s giving them that feedback.” Mary identified
this lack of transparency as the means that was used to control her (whether intentionally or not
is difficult to know) when a manager was pushing her into a role that she did not want. “This was
not what I wanted, and that’s when the dissension came because now you think you control me,
you don’t, and I believe they would not have been as domineering in that control if I had not
been Black.” After reflecting on her tenure in technology, Lauren said, “people underestimate
how much coaching and perseverance it takes to continue to do this,” especially for those who
are excluded from social circles and, consequently, communications about the inner workings of
career progression.
Networking
Networking was one of the strategies seven participants identified as key to their
longevity in technology. Mary said, “Networking is important. Find a way to partner. I always
have had someone that was not my color, and generally, a man in many cases, who will stand
behind me.” Now a 20-year veteran of the industry, Mary discovered early that to find new
opportunities, she needed to learn how to use the knowledge of others—which in technology
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meant men. “You may not even like the people, but you have to learn to network and use it to
your advantage,” she recommended. None of the other participants described receiving such
support from a man. In response to a question about how to persist in technology, Crystal
responded, “Find your tribe. Find your network of people.” Candace also endorsed networking as
key to longevity in the technology industry: “It’s all about not just connection, but networking
and nurturing those networked relationships.”
Jennifer explained the inner workings of in-person meetings and the communion of men.
“I can’t tell you the amount of conference rooms you walk into, and the men are shaking each
other’s hands, but ignore the females. So, you have this otherness that happens as the men are
connecting in the room.” This “otherness,” which superficially concerns only gender differences,
is also about communication norms and practices in the technology industry.
When recounting the offer of a new opportunity, Lauren said, “I have benefited from
people who have helped me with information that I didn’t know.” Janeen stated, “I was
fortunate. I learned early on how things work. I had one of the greatest managers [at] maybe the
second job out of school,” who was a White woman. Tammy also described her experience of
learning how to network: “That has been a real learning process for me; learning how to build—
just gain access—to build relationships, what that relationship would look like, should look like.”
She added that her colleagues, who are mostly male and White do not seem to struggle with the
same learning curve.
Three women reported that failing to understand networking had directly impacted their
careers. Janeen, who did not understand either the importance or process of networking
described her experience: “I didn’t go to the happy hours. I didn’t know how to. I’m not
mingling at the coffee machines. I’m not, you know, interacting and putting names to faces with
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people. I was working.” Meanwhile, a male colleague was “making the rounds, and so when his
name came up, oh, we know him, and he got the promotion.”
Summary
This section examined data about technology’s language and ways of communicating,
which Black women needed to learn but was already familiar to their male and White colleagues.
A lack of transparency was the first of two sub-themes explored. Seven women pinpointed that
lack of transparency as a barrier to gaining the information needed to develop and be promoted.
Networking was the second sub-theme. Seven women described having to learn how to network
and how networking is leveraged to find opportunities and developmental paths and obtain
promotions. Information about the promotion process and networking—including its importance
and how to do it well—sat on the other side of an opaque wall. Yet, as several participants noted,
obtaining that information was instrumental to persisting in the technology industry.
Theme 4: Black Women Persist in Technology Because They Love Their Work
All 11 participants stated that despite the field’s challenges, they persist in technology
because the work they do inspires and positively challenges them; in short, they love what they
do. As the research data indicated, each one of these Black women in technology consciously
chose to remain for reasons of self-actualization—which according to Maslow’s (1954)
hierarchy of needs is the highest level of psychological development. Arguably, then, they
persisted because almost nothing was going to keep them from fulfilling their purpose.
Eight of the women discussed their sense of agency, self-efficacy, or the gratification
they receive from working in technology. Lauren commented, “I owe it to myself to stick this out
for a number of reasons. I like the job, so I should continue doing it. And I seem pretty good at
it.” Mary remarked, “I can do just about anything in IT [information technology]. I try to drive
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myself with my own personal desires of where I want to be.” Opal explained that she never tires
of learning new things:
Technology is always changing, so nothing is ever boring for me. And that’s what drives
me. I get to learn something, and it’s like along the way you get to teach somebody
something new. Some women like rings. I like all kinds of tech.
Kassie cited similar reasons for remaining in technology: “[It is because of] my interest in how
everything works. I love finding ways to do things differently. I love the challenge of it.”
Janeen recounted that she loved computer science from the moment she was first
introduced to it at an academy for middle school students: “I was going to be a veterinarian. But
then I got introduced to computer programming, and I was like, forget about those animals.” She
then described her two decades’ worth of technology experience, including how she gained
various soft and technical skills each time she moved from one part of an organization to
another: “There are things that challenge me, but there aren’t a lot of things that intimidate me.”
For Tammy, seeking and building solutions to large, ambiguous problems was what she
loved most about the technology industry. Continuing, she remarked, “I would have never
proactively characterized myself in this way, but I do think it takes a very specific kind of
performance-driven quality to want to stay at some of these bigger tech firms for long periods of
time.” Crystal felt that her persistence was bolstered by “not letting [not getting a promotion]
dissuade me; in some ways, using that as encouragement to go forward.” She also mentioned
some advantages: “This career has allowed me to travel all over the world. It's given me the
flexibility, freedom, and independence from, you know, having to get that from a man.”
Four of the women cited the technology industry’s financial benefits. When asked, “What
are some of the things you really like about working in technology as a Black woman?” Sarah
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replied, “I love the money, and that has nothing to do with color.” Lauren also responded simply:
“Financially is a big one.” Crystal also mentioned the financial rewards: “Having a career in tech
is lucrative relative to other jobs.”
Thus, all of the participants have remained in the technology industry because of the
desire to realize their potential or other personal reasons, including the challenges of solving
problems, the unbounded opportunities for creativity and innovation, and also financial rewards.
Concerning the latter, the participants mentioned the industry’s higher-than-average
compensation, the retirement plan and healthcare benefits, and flexibility with work schedules.
Once again, however, love for their work was the primary motivation that all of the participants
cited for remaining in technology. The Black women in this study have endured the challenges
they described in order to realize their potential and fulfill their destiny. Therefore, it would not
be a stretch to describe the Black women interviewed for the study with this modification of
Maslow’s (1954) remark: “What a woman can be, she must be.”
Summary of Findings
This analysis identified four main themes. (1) Black women in technology feel they must
continually prove their competence. (2) Black women in technology perceive that their male and
White counterparts have easier inroads and more opportunities. (3) Black women in technology
must learn a language that their male and White counterparts apparently already know. (4) Black
women persist in technology because they love their work. Data analysis indicated that Black
women employed in technology fields experience more headwinds than their White and male
counterparts, who, as the dominant demographic that historically and currently wields most of
the industry’s executive power, primarily enjoy tailwinds. Despite the headwinds, Black women
forge their own paths in one of the most cutting-edge industries on earth. As described in their
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examples of agency and self-efficacy, they employ strategies they have had to discover largely
alone, notably self-advocacy, networking, and meticulous preparation. As the data show, they do
this in part because they are driven and inspired by their work and the industry; they refuse to
allow an oppositional culture or a broken system to deter them from their dreams. The final
chapter, which follows, will use these findings to present evidence-based recommendations for
change.

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Chapter Five: Discussion and Recommendations
The purpose of the study was to understand the experiences of Black women who have
persisted in the technology industry for five or more years. The underrepresentation of Black
women in the technology industry can hinder the creation and innovation of products and
services that could have benefitted a wider market, had Black women been given the opportunity
to contribute to their development (Solomon et al., 2018). The limited representation of this
group can also lead to greater income and wealth disparities for Black women across the United
States (Scott et al., 2018). Black women account for 3% of the technology workforce, which is
less than half of the total representation of Black women in the U.S. population (U.S. Bureau of
Labor Statistics, 2020). Technology is one of the most innovative industries (Maddikunta et al.,
2022) and one of the largest drivers of the U.S. economy, accounting for 9.3% of the U.S. gross
domestic product (Statista, 2022); however, the workforce has remained at 73% male and 90%
White or Asian for almost a decade (EEOC, 2016).
This chapter provides additional insight into the research findings related to the
experiences of Black women persisting in the field of technology through the lens of social
cognitive theory (SCT) and informed by intersectionality theory. It includes a discussion of
findings, three evidence-based recommendations for change specific to the culture and climate of
technology, study limitations and delimitations, future opportunities for research, and the final
concluding section. The next section covers a discussion of the findings as they relate to the
literature, other research studies, and recommendations for change.
Discussion of Findings
This research study focused on understanding the experiences of Black women in
technology who have persisted in the industry despite challenges. The study intended to address
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the problem of the underrepresentation of Black women in the technology sector. Leveraging
qualitative methods, I interviewed 11 Black women who had been employed in the technology
industry for five or more years. This research aimed to provide a better understanding of how
individual characteristics, including self-efficacy and agency; social observations; and the
technology culture and climate shaped their decisions to remain in the industry.
Chapter four included four themes that emerged from the research data analysis: (a)
Black women in technology feel they continually need to prove they are competent, (b) Black
women in technology perceive that their male and White counterparts experience easier inroads,
(c) Black women in technology describe having to learn a language that their male and White
counterparts seem to already know, and (d) Black women persist in technology because they
love their work. The first research finding on proving competency is discussed next.
Expectation to Continually Demonstrate Competency
Of the participants, 10 out of 11 Black women in technology reported that they had to
continually prove they are competent and able to do the job they are already performing. This
phenomenon was not explicitly discussed in chapter two, but was inferred through the research
on meritocracy primarily serving White men (Beckwith et al., 2016; Castilla, 2008) and the
biased perception that Black women are less qualified for jobs even though their qualifications
and education are the same as—if not higher than—other groups (Roberts et al., 2019; Smith &
Nkomo, 2021).
This finding has been validated by another recent study examining the perceptions of
Black women in technology. In 2022, Williams et al. published their findings on 216 completed
surveys and reported that women of color experience what they termed “prove-it-again bias.”
The authors explained that part of this phenomenon stems from in-group bias, where people in
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the dominant group typically favor others who are like them (Scheepers et al., 2006). Men make
up 73% of the tech industry (EEOC, 2016). Studies have shown that men are more likely to favor
other men; these men then benefit from casual information-sharing, mentorship, and resources
(Williams et al., 2022). One way to address this problem is by creating formal networking,
mentorship, and sponsorship programs for Black women (Burrow et al., 2019; Charleston et al.,
2014b; McCluney & Rabelo, 2019; Yamaguchi & Burge, 2019). Establishing recruitment efforts
focused on hiring more Black women is another (Blosser, 2019; Burrows et al., 2021; Carr et al.,
2019; Harrison, 2019; Sherbin & Rashid, 2017). Both recommendations, which relate directly to
culture and climate factors in technology organizations, will be discussed in greater detail in later
sections of this chapter.
Easier Inroads for Male and White Peers
All 11 women perceived that their male and White counterparts in technology
experienced easier inroads and better access to new opportunities, including access to new jobs,
social connections, promotional opportunities, and equitable compensation. This finding has
been validated by many other studies. Because few Black women occupy leadership roles, they
have limited opportunities for social connection, mentorship, sponsorship, or close referrals for
friends or social networks (Beal, 2008; Sims & Carter, 2019). Despite having equal or superior
qualifications, Black women are less likely to receive a callback for a job interview when their
resume includes a social identity indicator (Ceccarelli & Tedrick, 2023; Kang et al., 2016). In
addition, Black women are more likely to be offered less money than White men for the same
job (Hired, 2021; Steig, 2022).
To address this organizational deficit in the technology industry, companies should
revamp their recruiting efforts to hire more Black women (Blosser, 2019; Burrows et al., 2021;
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Carr et al., 2019; Harrison, 2019; Sherbin & Rashid, 2017), which would create more social
connection and mentorship opportunities for Black women (Beal, 2008; Sims & Carter, 2019;
Yazeed, 2020). In addition, Black women recruited into technology companies should be
compensated equitably in all cases (Ceccarelli & Tedrick, 2023; Woods et al., 2021). These
recommendations, which relate directly to culture and climate factors in technology
organizations, will be discussed in greater detail below.
Outside the Concrete Wall
Seven out of 11 Black women in technology described having to learn a language that
their male and White counterparts seemed to already know. This manifested in two ways: (a) a
lack of transparency in the process through which they obtain the information needed for career
growth and promotion and (b) a lack of understanding of how networking is used in the industry
to create opportunities, development paths, and promotions. These findings have been validated
by prior research. This is the crux of the concrete wall. The concrete wall is the social fabric
(McGee, 2018) woven into the organizational culture and climate of the technology industry that
keeps Black women outside the circle of knowledge (Yamaguchi & Burge, 2019).
There is strong scholarly evidence to suggest that both mentorship and sponsorship are
critical to providing Black women with safe career spaces to grow, develop, and experience
success and failures that are not attributed to their race or gender (Charleston et al., 2014a;
Ireland et al., 2018; Roberts & Mayo, 2019b). Recommendations for formal mentorship and
sponsorship programs for Black women in technology are covered in more detail later in this
chapter.
To address environmental factors in the culture and climate of technology organizations,
bias training (sometimes referred to as unconscious bias training) has the potential to initiate
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change if designed and implemented correctly (Chang et al., 2019; Devine et al., 2017; Dobbin
& Kalev, 2016). This type of training, if based on methodologies that have been proven to
change behaviors as well as attitudes, could serve to educate the industry and be a catalyst for
transformation (Carter et al., 2020; Schmader et al., 2022). This proposal is examined next in the
recommendations for practice.
Recommendations for Practice
This research study was framed by social cognitive theory (SCT) and informed by
intersectionality theory. SCT allowed for an examination of personal characteristics, social
experiences, and environmental factors (Bandura, 2001) that shape the unique experiences of
Black women in technology, and, ultimately, their decision to remain in a predominantly White
and male industry. Intersectionality theory, as an informing tool, provided a framework for
identifying complex social problems as they relate to power structures and their impact on
overlapping identities (Collins & Blige, 2020). In this study, participants self-identified as Black,
women, and technology employees.
Below are three proposed recommendations to address the key findings above.
Employing any one of them could help address the underrepresentation of Black women in
technology. However, these recommendations would be most effective if executed in concert
with one another. This problem of practice is systemic and, therefore, requires a holistic and
systemic approach to effect real and lasting change (Bolman & Deal, 207; Schein, 2017). The
first recommendation is to establish targeted recruitment efforts to attract Black women to
technology companies. The second recommendation is to build formal programs to develop,
mentor, and sponsor Black women in technology. The third and final recommendation is to drive
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awareness about bias and organizational cultural deficits in technology through education efforts.
The next section covers the recommendation to diversify recruitment efforts.
Recommendation 1: Target Recruitment Efforts to Attract Black Women to Technology
Companies
All 11 women perceived that their male and White counterparts in technology had easier
inroads and more access to new opportunities and promotions. The data indicated that these
inroads and new opportunities could apply to both new and existing employees. Black women
likely represent a small proportion of those new and existing employees, in part due to a leaky
pipeline that prevents Black women from getting hired or promoted due to social and structural
barriers related to systemic racism and sexism (Scott et al., 2018; Sherbin & Rashid, 2017;
Solomon, 2018; Yamaguchi & Burge, 2019).
Recruiting efforts targeted at underrepresented groups have been shown to drive diversity
(Llado-Farrulla et al., 2021; McGee, 2018; Xu, 2021). Hiring new and diverse talent begins with
revamping recruiting functions throughout the organization (Dobbin & Kalev, 2017; Roberts &
Mayo, 2019b). My recommendation is that technology companies invest in recruitment efforts to
attract Black women and conduct compensation audits to ensure fair and equitable pay for
current and future Black employees (Ceccarelli & Tedrick, 2023; Woods et al., 2021).
It is nearly impossible to measure the success of a change initiative if the baseline data
are unknown or unavailable (Kirkpatrick & Kirkpatrick, 2016). Therefore, to measure the
success of such efforts, companies should start by examining the baseline demographic data of
the current employee base through the lens of diversity (Dobbin & Kalev, 2017; Forscher et al.,
2019; Yamaguchi & Burge, 2019). Organizations that are transparent with their demographic
metrics and goals have the most success in creating diverse environments (Motel, 2016). As
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recommended by Lewis (2019) and Denning (2011), companies should communicate the new
goal effectively, explain the reason for it, and describe how the company will measure success.
Training should be provided to the recruiting team to support the change through a multifaceted
return on expectations program as described by Kirkpatrick and Kirkpatrick (2016). The
company should supply the team with resources, including a budget and access to candidate-
sourcing websites that include a large number of Black women. Finally, it should ensure there is
a multilayered sequence of accountability for the goal, from senior leadership down to frontline
recruiters. While accountability is binary, it is not a simple phenomenon of a single point of
failure, but rather a shifting web of ambiguity where actors play different parts at any given time
(Olsen, 2014). Ultimately, this recommendation is to ensure that the training, resources, data
measurement, and overarching goal are seamlessly integrated into the company culture to create
real change (Schneider et al., 1996).
A prominent component of SCT is modeling (or the social aspect of observing others),
which allows learning to take place vicariously (Bandura, 2001; Schunk, 1987; Schunk & Usher,
2019). As technology companies hire more Black women, it creates more models for other Black
women to learn from and aspire to. In addition, the more Black women in technology, the more
opportunities there will be for mentorship and sponsorship of less-experienced Black women
(McGee, 2018; Sherbin & Rashid, 2017). The next recommendation covers how to build formal
programs to develop, mentor, and sponsor Black women in technology.
Recommendation 2: Build Formal Programs to Develop, Mentor, and Sponsor Black
Women in Technology
Seven out of 11 Black women in technology described having to learn a language that
their male and White counterparts seemed to already know. This manifested in two ways: (a) a
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lack of transparency in the process through which they obtain the information needed for career
growth and promotion and (b) a lack of understanding of how networking is used in the industry
to create opportunities, development paths, and promotions. Research has shown that both
mentorship and sponsorship are critical to providing Black women with safe spaces in their
careers to grow, develop, and experience success and failures that are not attributed to their race
and gender (Charleston et al., 2014a; Ireland et al., 2018; Roberts & Mayo, 2019b). Effective
mentorship and sponsorship programs can help Black women, other women, and other people of
color break through the concrete wall by offering access to knowledge and networking
opportunities that can lead to career development, increased visibility, and promotion (Burrows
et al., 2021; Mahendran et al., 2022; Sherbin & Rashid, 2017).
Building a formal program focused on developing, mentoring, and sponsoring Black
women and others in technology requires support, budgeting, and resourcing from senior
company leadership (Elliot et al., 2017; Schein, 2018). To measure the success of such a
program, the company must look at the baseline data before initiating any change (Doerr, 2018).
The creation of and company commitment to the program should be communicated by
leadership. This information should include the goals of the program, the designation of a senior
leader or sponsor responsible for the program, and key performance indicators (KPIs) for how
the organization will measure success (Lewis, 2019). Few Black women occupy leadership roles,
thus limiting opportunities among Black women for social connection, mentorship, or
sponsorship (Beal, 2008; Sims & Carter, 2019; Yazeed, 2020). To ensure success, this program
must recruit a body of senior leaders, preferably Black women (Charleston et al., 2018; Nash &
Peters, 2020). It should be noted, however, that research has shown that non-Black women and
men can successfully mentor Black women, with similar results (Leitner et al., 2018).
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Organized programs like the one proposed are a key SCT component of environmental
factors. In the conceptual framework for this study, I defined this as the technology
organizational culture and climate. Mentorship programs that support Black women working
within the culture, climate, and environment of technology organizations can help advance their
careers (Burrows et al., 2021; Yamaguchi & Burge, 2019). Additional evidence has suggested
that an environment that supports underrepresented groups of technical professionals allows for
career development through both mentorship and sponsorship (Higgins & Kram, 2001; Mendez
et al., 2020; Xu, 2021). Mahendran et al. (2022) found that the lack of sponsorship for women
limited their ability to be promoted and, consequently, to sponsor other women themselves.
These are organizational culture and climate shortcomings in the technology industry. The next
section discusses additional cultural deficits of technology organizations that can be addressed
through education.
Recommendation 3: Drive Awareness Through Educational Efforts on Bias and
Organizational Cultural Deficits in Technology
Ten out of the 11 Black women in technology interviewed reported that they had to
continually prove they are competent and able to adequately fulfill the duties of the job they
currently hold. “Education is the most powerful weapon which you can use to change the world”
(Mandela, 1990, as cited in Kifner, 1990, p. 21). Researchers have not reached a consensus on
what constitutes effective DEI programming, but data have suggested that mandatory diversity
training could improve the awareness of both employees and leaders (Burrows et al., 2021;
Onyeader et al., 2021; Rabelo et al., 2020). Other scholars have argued that quotas are more
effective at increasing demographic diversity (Hamplová et al., 2022; Velkova, 2015). Still
others refute the effectiveness of mandatory training and quotas alike, and instead maintain that
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to effectively impact an organization’s diversity and inclusion, organizations must change their
culture (Dobbin & Kalev, 2017; Forscher et al., 2019; McCluney & Rabelo, 2019).
My recommendation for driving awareness on bias and organizational cultural deficits in
the technology industry through educational efforts is to mandate unconscious bias training. This
training should be framed through the research on the technology industry’s cultural deficits with
regard to Black women and all women of color. Introducing the concept and history of bias
through bias training can create shifts in both awareness and attitude (Gino & Coffman, 2021;
Kim & Roberson, 2022). Research criticizing bias training has suggested that the typical
unconscious bias training module reduces “all diverse forms of gendered and racialized violence
to a cognitive level … so that structural sexism and racism and barriers to change remain largely
absent” (Möller et al., 2023, p. 17). Building on this research, my recommendation is to ground
the training in the realities of systemic sexism and racism, White privilege, and historical
inequities so that it cannot be misinterpreted or misconstrued as anything but a legitimate tool for
organizational culture change (Schmader et al., 2022).
Effective bias training prioritizes the learning objectives—such as a common
understanding and shared history about organizational sexism, racism, White privilege, and the
fallacy of meritocracy—over positive reviews from its audience (Carter et al., 2020). Technology
leaders, most of whom are White men, must encourage open conversations about race and
gender (Roberts & Mayo, 2019b) and hold themselves and others accountable to established
standards and goals (Rabelo et al., 2020). If leadership supports such an effort and employees
embrace the realities of historical inequities, the learning experience can offer new perspectives
to help employees recognize bias and potentially mitigate or eliminate it (Chang et al., 2019;
Kim & Roberson, 2022), not only in the recruiting or interview process, but also during
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performance review cycles, compensation considerations, and promotion discussions. Finally, a
critical component of successful bias training is measuring meaningful outcomes (Cox, 2023)
and tracking its effectiveness (Carter et al., 2020).
Summary
Until there are more women—specifically, Black women—in technology leadership
roles, there will be limited access to sponsorship opportunities and, consequently, limited
opportunities for other Black women to act as sponsors themselves (McGee, 2018; Sherbin &
Rashid, 2017). These three recommendations are aimed at driving an increase in Black women in
technology through structured programs supported with data that measure their impact and
effectiveness: (a) targeted recruiting efforts, (b) formalized mentorship and sponsorship
programs, and (c) education on bias and the deficits in the culture and climate of technology
organizations. The next section covers the limitations and delimitations of the study.
Limitations and Delimitations
Limitations are possible flaws or weaknesses in the study that are beyond the researcher’s
control (Creswell, 2012). Potential limitations of my study included concerns about the
trustworthiness of the participants or the veracity of their self-reported experiences and their
feelings about them. Another potential limitation concerned the respondents’ potential
unwillingness to share uniquely Black female experiences with a White female researcher.
Delimitations are characteristics of the study that are bound by the researcher’s choices
and scope (Simon, 2011). The most significant delimitation of this study was its focus on a very
narrow demographic population and a specific set of questions. The scope of this study included
Black women who had persisted in the technology industry for five or more years. It was framed,
and consequently limited, by social cognitive theory and informed by intersectionality. Finally,
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individual interviews were the only source of study data; therefore, this limited the possibility of
data triangulation.
My participant sample was limited mostly by my extended professional social network.
The experiences of the Black women I interviewed cannot be representative of all Black women
in technology, nor do other Black women’s experiences necessarily align with those of the
participants of this study. Furthermore, I interviewed Black women with additional intersecting
social identities, including lesbian and immigrant. However, this study did not explore
experiences that related to these additional intersections. Finally, this research did not focus on
potentially relevant factors such as socioeconomic level, disability, or veteran status.
This study only looked at women who persisted for five or more years. Only two women
were in the industry for nine years or less, and five of the women were in the industry for 20
years or more. In addition, this study was conducted at the beginning of 2023, when an
unprecedented number of technology employees—at least 194,00 between January and June,
according to Forbes (Bushard, 2023)—were laid off. This inhibited my ability to recruit veterans
in the industry who had been part of those layoffs as they were no longer eligible for the study
once they became unemployed.
Recommendations for Future Research
This research study focused on improving the understanding of the experiences of Black
women in technology who persisted for years in the industry despite challenges. The study was
limited to Black women who remained in the industry for five or more years. It would be
compelling to study additional Black women who have remained in the industry for 20 years or
more to better understand the strategies they used to persist for two or more decades. In addition,
future research could include a narrower scope of technology employees, such as only computer
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science or data science engineers, as opposed to any position in the technology industry. This
would allow the focus of the research to improve understanding of the challenges of engineering-
specific roles, which are held by even fewer women, let alone Black women.
Additional opportunities for further research include gaining a more thorough
understanding the mechanism of exclusion from the language of technology, or, more plainly,
the inner workings of how tech companies utilize development, leverage networking, and
promote people. Another opportunity could be to create a technology survival guide for Black
women in technology. It is outside the scope of this dissertation to include a compilation of best
practices for Black women starting out in technology based on the experiences of tenured Black
women. However, a more focused and scientific qualitative exploration and collection of this
information could benefit Black women interested in getting into the industry or those just
starting their careers. Finally, it could be worthwhile to conduct a larger-scale quantitative study
examining the relationship between additional Black women in technology companies and the
levels of innovation, quality, and marketability of products or services at those companies.
Implications for Equity
It is my hope that this work contributes to the future fulfillment of the promise that
Crenshaw articulated in her 1989 Chicago Law Review article: “The goal of this activity should
be to facilitate the inclusion of marginalized groups for whom it can be said: ‘When they enter,
we all enter’” (p. 167). More than 30 years later, there is still much work to be done toward
creating equity for underrepresented groups. I hope this small contribution to the growing
research on Black women in technology will inspire technology leaders to take the beginning
steps outlined in the recommendations above to bring about positive and equitable change in
their respective organizations.
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Conclusion
This study explored the experiences of Black women who have persisted in technology
despite challenges. The organizational culture and climate of the technology industry contain
barriers, like the concrete wall, that exclude Black women from its social fabric and inner
workings. Through the lack of representation, discrimination masked as meritocracy,
microaggressions, bias, and the unwillingness to recognize all of the above, the technology
industry has alienated Black women. Yet, some Black women persist. Interviews with a small,
purposeful sample of 11 Black women who have remained in technology for five years or more
revealed insights into their experiences. Through the lens of SCT, the data indicated that these
women had high agency, high self-efficacy, and the determination to realize their highest
potential and self-actualization by persisting in technology.
Although some technology companies have DEI programs in place, the velocity and rigor
around these are not enough. Black women are still underpaid. They are sidelined and ignored.
Black women are still the victims of racism and sexism. There is little to no broader awareness of
bias and systemic, structural racism. This needs to change if we are to build environments that
are conducive to every employee doing their best work. This is how we create the most
innovative products and services for the future in the technology industry.
If we do not change the system, the system will not change. If the root of racism or
sexism—any -ism—is a system by which a phenomenon occurs, and White men, being the
dominant social identity in technology, created the system, then, as Audre Lorde (1984) so
eloquently described, “the master’s tools will never dismantle the master’s house” (p. 110). In
other words, the creators of these systems are neither the recipients of oppression nor the
architects of remedying the dysfunction. Together, in collaboration with Black women and
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women of color and through evidence-based recommendations, a greater commitment can be
made in leadership accountability to bring equity, transformation, and a level of innovation not
yet realized in the technology industry.

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111

Appendix A: Interview Protocol
The purpose of this study was to understand the experiences of Black women who have
persisted in technology for five or more years. The participant group for this study were
individuals who identified as Black women, were (at the time) employed in the technology
industry, and had worked in the technology industry for five or more years. The research
questions that guided this study included the following:
What are the experiences of Black women who have persisted in technology?
a. How has organizational culture and climate shaped Black women’s decisions to
persist in the technology industry?
b. How have individual characteristics shaped Black women’s decisions to persist in the
technology industry?
c. How have social factors shaped Black women’s decisions to persist in the technology
industry?
Introduction to the Interview
Hello. Thanks for being here. I am Sherry Keating, and the purpose of my study is to
understand the experiences of Black women who have persisted in the technology industry. Just
a reminder, this interview is completely voluntary and confidential. You can skip questions or
stop at any time. Before we begin, what pseudonym would you like to use?
Is it okay if I record this session? Only I have access to the recording along with the
Zoom Admin at the University of Southern California. I will use it for transcription purposes and
to ensure accuracy. After my research study is completed, I will delete it from the website. Is that
okay? [Turn on recording.]
Any questions before we proceed? Great, let’s get started.
112

1. Tell me a little bit about your career in technology. How did you get started to where
you are today? RQ: personal, social, or environmental experiences
2. What personal characteristics or strengths of yours have contributed to your staying in
the technology industry for so many years? RQb
3. What organizational culture challenges, if any, have you faced as a Black woman in
the technology industry? RQa
4. What types of relationships, both personal and professional, have helped or supported
you and your technology career? RQc
5. Tell me about the benefits, if any, you experience working as a Black woman in the
technology industry? RQa
6. Tell me about the drawbacks, if any, you experience as a Black woman working in the
technology industry? RQa
7. What are some of the things you really like about working in tech as a Black woman?
Probe: What makes you feel that way? [Probe for (self-efficacy) confidence related to
a specific task and/or (agency) ability to control one’s thoughts/emotions/behaviors.]
RQb
8. What are some of the things you dislike about working in the tech industry as a Black
woman? Probe: What makes you feel that way? [Probe for (self-efficacy) confidence
related to a specific task and/or (agency) ability to control one’s
thoughts/emotions/behaviors.] RQb
9. What has been your experience with promotion or advancement opportunities, if any?
Probe: How do you feel being a Black woman has helped or hindered these
opportunities? RQa
113

10. How do you feel being a Black woman has influenced your ability, if at all, to remain
in the technology industry for more than five years? RQb
11. What recommendations would you make for how to best support Black women who
remain in the technology industry? RQa
12. What advice, if any, would give other Black women who are early in their tech
careers about how to successfully persist in technology? RQc
13. In what ways, if any, have you observed your career path in technology has differed
or followed the same course as those of your non-Black female peers? RQc
14. What else do you think I should know or that you would like to share with me? RQ:
personal, social, or environmental experiences
Interview Conclusion
Thank you for your time, energy, and thoughts today. I really appreciate everything you
shared. If I have any questions to ensure I am representing your words and thoughts accurately,
can I follow up with you? Do you have any last questions for me?
[Turn off recording.]

114

Appendix B: Recruitment Questionnaire
The purpose of the recruitment questionnaire was to qualify prospective candidates for
the research study. Each participant must have identified as a Black woman, was currently
working in the technology industry, and had been employed in the technology sector for five or
more years. This recruitment questionnaire (Table B1) was collected from every participant
regardless of how she learned about the study, including a word-of-mouth referral, colleague of
mine, or social media.
Recruitment Questionnaire Introduction Text
Thank you for your interest in participating in a research study about the
underrepresentation of Black women in technology. Please complete this form to see if you
qualify. Contact me directly at sherryke@usc.edu with any questions.
Recruitment Questionnaire Closing
The closing text for the survey is standard to Qualtrics and not editable. It includes, “We
thank you for your time spent taking this survey. Your response has been recorded.” In the
lower, left-hand corner it also says, “Powered by Qualtrics” with an indicator that shows if you
click on it, it will take the user out of the questionnaire and into a Qualtrics website.

115

Table B1
Recruitment Questionnaire
Question Answers Logic
Are you currently employed? Yes. No. Prefer not to answer. Only answering yes
allows the candidate to
move forward.
Do you work in the technology
industry?
The technology industry
includes a group of
industries with the highest
concentration of technology
workers. Examples of roles
in the technology industry
include but are not limited to
software designers, coders,
engineers, technical project
managers, computer system
programmers, technical
support specialists, user
acceptance testers, and
quality assurance teams.
Yes. No. Prefer not to answer. Only answering yes
allows the candidate to
move forward.
How many years have you
worked in the technology
industry?
0-4. 5-9. 10-14. 15-19. 20 years or
more. Prefer not to answer.
0-4 or Prefer not to
answer ends the
questionnaire.
What is your current
occupation?
Text field.
What function(s) are you a part
of in the technology
industry? [Select all that
apply.]
Account Management / Sales /
Business Development.
Administrative Services.
Advertising / Marketing.
Engineering / Computer Science /
Data Science. Business
Operations. Design / UX. Project /
Program Management. Executive
Leadership. Accounting / Finance.
Other (text box). Prefer not to
answer.
All answers allow the
candidate to move
forward.
116

Question Answers Logic
How many years have you
been employed at your
current company?
0-4. 5-9. 10-14. 15-19. 20 years or
more. Prefer not to answer.
All answers allow the
candidate to move
forward.
Do you manage people in your
current role?
Yes. No. Prefer not to answer. All answers allow the
candidate to move
forward.
Have you managed people in
past roles?
Yes. No. Prefer not to answer. All answers allow the
candidate to move
forward.
What is your gender? Man. Woman. Nonbinary. Prefer
not to answer.
Only answering woman
allows the candidate to
move forward.
How do you identify your
ethnicity?
Black or African American.
Eastern Asian or Asian American.
Hispanic or Latinx. Native
American or Alaska Native.
Pacific Islander or Native
Hawaiian. White or Caucasian.
Other (text box). Prefer not to
answer.
Answering Black or
African American
allows the candidate to
move forward.
If you would like to be
contacted for potential
participation in this research
project, please include your
full name, phone number,
and email address below
N/A N/A

First and Last Name Text box. N/A
Phone Number Text box. N/A
Email Address Text box. N/A

Note. This questionnaire was facilitated by Qualtrics and published through my University of
Southern California student account.

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Asset Metadata

Creator Keating, Sherry (author)

Core Title Outside the concrete wall: a qualitative study of Black women persisting in technology

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2023-12

Publication Date 09/06/2023

Defense Date 08/31/2023

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag Black women in technology,intersectionality,OAI-PMH Harvest,social cognitive theory,technology culture and climate

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Phillips, Jennifer L. (committee chair), Carbone, Paula M. (committee member), Phillips, Stefanie P. (committee member)

Creator Email sherryk@me.com,sherryke@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113303093

Unique identifier UC113303093

Identifier etd-KeatingShe-12317.pdf (filename)

Legacy Identifier etd-KeatingShe-12317

Document Type Dissertation

Format theses (aat)

Rights Keating, Sherry

Internet Media Type application/pdf

Type texts

Source 20230906-usctheses-batch-1091 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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Repository Name University of Southern California Digital Library

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Repository Email cisadmin@lib.usc.edu