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Women and Girls of Color in Computing

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Women and Girls of Color in Computing DATA BRIEF: Women and Girls of Color in Computing TECHNOLOGY AND THE GLOBAL DATA HIGHLIGHTS ECONOMY • Women of color currently constitute 39% of the female- identified population in the United States, and will Technology is a significant driver of economic growth and comprise the majority by 2060. development across the globe (Dutta, Geiger, & Lanvin, 2015). Technology plays a critical role in the United States • Just 4% of all high school students taking AP Computer economy and workforce, with nearly one-quarter of the Science in 2017 were Latinx girls, 2% were Black girls, country’s total economic output produced by high-tech and <1% were Native American/Alaskan Native girls. industries (Bureau of Labor Statistics [BLS], 2016, 2017) and • Women of color make up less than 10% of all Bachelor’s nearly 1 million job openings projected in computer and degrees earned in computing, and Latinx women information technology over the next 10 years (BLS, 2017). are most underrepresented in computing Bachelor’s In addition to being among the fastest-growing, computing degree completion rates relative to their population in postsecondary education. occupations are also among the most economically lucrative, with median salaries more than twice the median • Women earn 21% of all doctorates in computing, wage for all other occupations (BLS, 2015b) and significant however, less than 5% are awarded to Black, Latinx, wealth being generated by technology creators and Native American/Alaskan Native, or Native Hawaiian/ investors (CB Insights, 2017). Yet, the technology workforce Pacific Islander women. is not representative of the diversity of the United • Among all women employed in computer and States population, with the vast majority of individuals information science occupations, only 12% are Black employed in computer and mathematical occupations or Latinx women; In 177 Silicon Valley firms, less than being White (63%) and male (75%; BLS, 2015). To ensure 2% of all workers are Black, Latinx, or Native American/ Alaskan Native women. the future economic growth and prosperity of the United States, developing a robust, skilled, and diverse national • While White women and Asian women participate in workforce will be essential. Simultaneously, increasing roughly equal rates in the overall workforce, Asian equity in economic opportunity and decreasing inequality women are significantly less likely to be in leadership will be directly linked to the preparation of individuals positions. from marginalized and underrepresented communities to • Less than 1% of Silicon Valley tech leadership positions participate in the rapidly evolving technology economy. are held by Latinx women, and <0.5% are held by Black Thus, the current and pervasive lack of racial/ethnic and women. gender diversity in the technology ecosystem presents a • Women of color account for 80% of the new female-led significant national challenge. small businesses, but in tech, Black women account for less than 4% of female-led startups. WOMEN AND GIRLS OF COLOR IN THE vastly underrepresented across the technology pipeline and UNITED STATES many of the strategies, interventions and investments to diversify the technology ecosystem have focused on race or Women of color currently constitute 18% of the overall gender, overlooking the intersection of race and gender (and U.S. population and 39% of the roughly 163 million female- other marginalized sexual, cultural, economic, religious, and identified population in the United States (Census, 2014; linguistic identities). Figure 1). Nearly half of female students in K-12 education are girls of color (U.S. Department of Education, 2013) and by 2060, the census projects that women of color will INTERSECTIONALITY IN COMPUTING comprise the majority of the female population in the United Foundational scholarship on Intersectionality theory States (Census, 2014, Catalyst, 2017; Figure 2). articulates the ways in which racism and sexism affect educational, social and occupational outcomes of women FIGURE 1 of color in ways that FIGUREcannot 2be fully captured by examining US Female Population by Race, Ethnicity experiencesUS Female Populationby race or Growthgender byseparately Race, Ethnicity (Crenshaw, 1989, (2015-2060) .5% 1991). Intersectionality describes the complex interactions 1% 120 108% ■ White between multiple identities and120% dynamics of power, 6% ■ Latinx 100 ■ Black racism, sexism, and oppression (Hill Collins and Bilge 2016; 14% ■ Native American/ 80 Crenshaw, 1991). Intersectionality theory encompasses62% Alaskan Native not60 only the intersection between marginalized racial and ■ Asian 41% 40% 17% ■ Native Hawaiian/ gender40 identities, but also additional marginalized identities 61% Pacific Islander including20 sexual orientation, socioeconomic status, religion, age, ability,-9% and linguistic background, among others. Within 0 Latinx Black Asian Native Amer/ Native science, technology, engineering and math (STEM) fields, the -20 White Alaskan Hawaiian/ unique combined and cumulative challengesNative Pacific ofIslander racism and Source: U.S. Bureau of Census (2014) sexism experiencedSource: U.S. Bureauby women of Census of (2014)color has been described as the “double-bind” (Malcom et al., 1975; Ong et al., 2011; FIGURE 1 FIGURE 2 Williams et al., 2014), which leads to disparities throughout US Female Population by Race, Ethnicity US Female Population Growth by Race, Ethnicity (2015-2060) the STEM pipeline. In the technology pipeline, specifically, .5% 1% 120 the double-bind for women and girls of color begins early ■ White 108% FIGURE 3120% FIGURE 4 6% ■ Latinx 100AP CS Participation, by Gender and Race/Ethnicity inK access – 12 Female and participation Enrollment vs. in APcomputing CS Participation education, persists ■ Black throughout post-secondary education, and culminates in 14% ■ Native American/ 80.05% 1% 1% ■ Male (All Races)62% Alaskan Native disparities2% in participation at all levels■ White of the technology 60.05% ■ Black/African American ■ Asian 8% ■ Latinx 10% 41% Female40% workforce, technology entrepreneurship, and venture capital 17% ■ Native Hawaiian/ ■ Black 40 ■ Latinx/Hispanic Female 61% Pacific Islander 8% (Scott et12% al., 2018). ■ Asian 4%20 ■ Asian Female 0.50% ■ Native American/ -9% ■ Native American/ 2% 8% Alaskan Native 0 Latinx Black AsianAlaskan Native Amer/ Native Native ■ Native Hawaiian/ 2% White Alaskan Hawaiian/ 24% 4% -20 74% PacificNative Islander Pacific Female Islander ■ White Female 10% Source: U.S. Bureau of Census (2014) Source: U.S. Bureau of Census (2014) ■ Other Female US K – 12 EnrollmentIntersectionality AP CS Participation describes Further, recent data has also shown that women of color, (Female) (Female) the complex interactions between specificallySource: College Black Board and (2017); Latinx Includes women, AP CS Aare and the AP fastestCS Principles. growing Source: College Board (2017); U.S. Department of Education, Oce for group of entrepreneurs in the United States, creating over Civil Rights (2014);multiple Data for Pacific identities Islander and Nativeand Hawaiiandynamics student enrollment unavailable. FIGURE 3 80% of the new women-ledFIGURE small 4businesses and nearly of power, racism, sexism, AP CS Participation, by Gender and Race/Ethnicity doublingK – the 12 Femalenumber Enrollment of businesses vs. AP started CS Participation by women FIGURE 5 and oppression .05% 1% of color since1% 2007 (AMEX, 2016; MacBride, 2015). Both ■ Male (All Races) Female2% AP CS Participation, by Race/Ethnicity■ White .05% ■ Black/African American the rapidly increasing size and entrepreneurial■ Latinx activity of 10% 8%.10% Female .2% ■ Black this population indicates significant■ earningWhite and spending 8% ■ Latinx/Hispanic Female ■ Asian 12% 6% ■ Black/African American 4% ■ Asian Female potential. Yet despite the size0.50% and projected■ Native growth American/ of this ■ Native American/ ■ Latinx/Hispanic 2% important segment of the population,8% womenAlaskan of Nativecolor remain Alaskan Native ■ Asian ■ Native Hawaiian/ 2% ■ Native American/ 32%24% 38% 4% 74% Pacific Islander Female Alaskan Native Kapor Center/ASU CGEST | 2 ■ White Female 10% ■ Native Hawaiian/ ■ Other Female Pacific Islander US K – 12 Enrollment AP CS Participation■ Other (Female)16% 7% (Female) Source: College Board (2017); Includes AP CS A and AP CS Principles. Source: College Board (2017); U.S. Department of Education, Oce for Civil Rights (2014); Data for Pacific Islander and Native Hawaiian student enrollment unavailable. Source: College Board (2017); Includes AP CS A and AP CS Principles FIGURE 5 Female AP CS Participation, by Race/Ethnicity FIGURE 6 Bachelor’s Degree Completion in Computer Sciences, .2% .10% ■ White by Gender and Race/Ethnicity 6% ■ Black/African American 2% .1% ■ Latinx/Hispanic 2% ■ Male (All Races) ■ Asian 3% ■ White Female ■ Native American/ 3% ■ Black/African American 32% 38% Alaskan Native 8% Female ■ Native Hawaiian/ ■ Latinx/Hispanic Female Pacific Islander ■ Asian Female ■ Other ■ Native American/ 16% 7% Alaskan Native Female 82% ■ Native Hawaiian/ Pacific Islander Female ■ Other Source: College Board (2017); Includes AP CS A and AP CS Principles Source: National Science Foundation (2016a). FIGURE 6 Bachelor’s Degree Completion in Computer Sciences, by Gender and Race/Ethnicity .1% FIGURE 7 FIGURE 8 2% ■ Male (All Races) 2% Post-Secondary Enrollment vs. Bachelor’s Degree PhD Completion in Computer Sciences, by Gender ■ White Female Page 4, Figure 8: the 3% Completion in Computing
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