The gap in computer literacy between whites and blacks suffuses even income distribution. The United States of America has been surrounded by the issue of race and racial profiling especially to people of color. Blacks, for instance, have undergone racial discrimination since the Middle Passage. Although the United States Constitution protects its citizens from racial discrimination, the practice has continued to exist even in the contemporary society. Nowadays, there are new racial practices that exist in the U.S. The issue of race is now built into the tech industry. Issues of racial inequality now corrupt the sector. The tech industry boosts itself of diversity; however, the reality is much different on the inside. The essay will provide an overview of racial incidences experienced in tech industries.
Benjamin argues if race is a technology then it requires routine maintenance and upgrades. According to the author, todays generation racism comprises of practices that exacerbate the issue of racial inequality. Such methods include replacement of violent voter tactics with voter ID laws, redlining of government sanctions through predatory lending, and top-down eugenic policies to reproductive technologies that allow consumers to use socially desirable traits (2). In 2015, the author attended the International Summit on Human Gene Editing. The Summit displayed gene-editing techniques that are cheaper and easier to use than previous approaches to genetic engineering. A major tension arose from the Summit because the same gene-editing technology could be used to eradicate debilitating genetic diseases and character traits that are deemed socially undesirable; thus, putting racial fitness in the hands of the medical consumers (Benjamin 6). The analogy behind these techniques illustrates not only cosmetic surgery, but also propagates core notions of beauty and fitness that are racist and misogynistic. Analogizing genetic modification to cosmetic surgery invigorates hegemonic forms of whiteness (6).
Equally important, biometric security has long been connected to processes of racialization (Maguire 593). Researchers argue that biometric systems are coded with processes of racialization that enable those programs to sort, categorize, and grant or exclude an individual (594). More so, cases of racism in biometrics are evident in fingerprinting and face recognition. The new security technologies require the categorization of various suspicious populations to races. Biometric security involves the use of personal information to verify individual identity by using multiple characters such as fingerprints, face, or iris. The primary focus of the technology was criminal policing. However, since 2001, biometric technologies have received phenomenal public and private investment. Lately, biometric technology is used in international and migration management as a necessary weapon for homeland security. Biometric technologies are unable to distinguish individual bodies of people of color (Maguire 601). The failure to record the rates of dark-skinned users illustrates technological privileging of whiteness. Joy Buolamwini, the founder of Artificial Justice League, noticed that her face recognition software project did not process her face because she was very dark (Kleinman). When she tried a white mask, the face recognition software would work perfectly. Buolamwini was forced to use her lighter-skinned roommate to help her during the verification process. From the example, it is evident that biometric softwares and companies are not diverse in the creation of data sets to be used in the programs. Whiteness is common in facial recognition softwares making it seem like a dominant language over the others. The technology industry in the U.S. relies on a workforce where majorities of these individuals work in software and information technology companies. In this profitable industry, color-blind racism infuses in the business and theory of the popular internet. Daniels argues that the specificity and the structure of the internet is ignored by many. Race is implicated in the formation of the general user interface (2). For instance, DOS-commands utilize words such as Master Disk and Slave Disk, which are a representation of racial meanings coded into the lines of commands. Moreover, drop-down menus and clickable boxes are used to categorize race. The clickable boxes and the drop down menus utilize race as a critical marketing strategy. The use of the white hand-pointer acts as a depiction of white people in advertisements and web greeting cards. If one tries to search images of hands and babies on the internet, the results are white hands and babies (Kleinman). Individuals from racial and ethnic communities are rarely depicted as innovators or leaders in tech industry despite a long history of innovation in technology (3). The ethnic minority groups are represented as consumers of the technological products created by the whites.
Race is built into the tech industry. White men and women lead a majority of the tech firms in Silicon Valley, yet immigrants do the hard labor in the organizations. The lack of diversity in the tech industries is a critical issue. According to research conducted by CNN Money, a majority of the most influential tech industries in the U.S. underrepresent women in top positions such as management roles (Daniels 4). According to the report from the nonprofit Open MIC, existing data indicate that Native Americans, blacks, and Latinos are underrepresented in tech companies by 16 to 18 percent despite their overall presence in the U.S. labor force (Florentine). Another survey from Indeed revealed that about 52 percent of currently employed technology professionals who are nonwhite experienced non-inclusive behavior that made them uncomfortable in their organizations (Florentine). The respondents stated that the feeling of isolation in the workplaces arose due to their race, gender, age, and religious affiliations. The studies indicate that racism is part of the power structure and cultural norms of the tech companies that is why it is difficult for the organizations to recruit and retain employees from races other than white. Qichen Zhang, a technical specialist at Google, narrates how a male employee once made a racist joke about her, and it significantly affected her emotions. The male employee stated that it was easy for Zhang to get a job at Google because she is Asian and people assume that Asians are good at math. Zhang indicates that she experienced many instances of discrimination that made her feel isolated as a woman of color. The non-inclusive environment at the tech giant company prompted Zhang resign from her position a few months later (Levin). Former and current employees spoke in different interviews narrating how they think the company undermines women of color in assigning roles and pay. The workers stated that Googles culture tolerates sexism and racism. The male managers frequently support workers who look like them (Levin). One black woman who worked at Google for several years told The Guardian that discrimination and prejudice in the organization influenced her productivity on a daily basis. The woman continued to state that employees would frequently ask to see her identification throughout the Google campus while white workers were rarely questioned (Levin). Zhang told The Guardian that the daily aggressions that she experienced in Google led up to her resignation because the culture at the organization promoted meritocracy (Levin). For this case, Daniels argues that the move by Zuckerberg and other elites such as Bill Gates to claim that they are proponents of immigration reform is a plan to benefit their industries and eschew charges of bias in hiring and promotion (4).
The tech company is one of the largest in the U.S. and according to the numerous accounts of racial discrimination; it is evident that the industry has a deep culture of racism in its structure. The use of gene editing as a cosmetic remedy to eradicate socially undesirable traits is a direct counterattack against people of color. The technology seems to illustrate that ethnic minorities are inferior and should take the surgery to emulate white people. Researchers have also found that there are algorithms of race in biometric software. Dark people such as Boulamwini had difficulty to use her face for verification and instead opted to use a white mask, which worked perfectly. The use of white hand-pointer, terms such as Master Disk and Slave Disk, and white babies on the internet is an illustration of white dominance in the tech world. Additionally, the underrepresentation of women in tech companies such as Google depicts the seriousness of the issue of racism in the technology companies. People of color and minority groups have been sidelined from the limelight, an issue that raises many questions regarding the diversity of the tech companies, and the policies that the government has set aside towards mitigating this problem.
Works cited
Benjamin, Ruha. Innovating inequity: If Race is a Technology, Post racialism is the Genius Bar. Ethnic and Racial Studies, 2016, pp. 1-8. DOI:10.1080/01419870.2016.1202423.
Daniels, Jessie. My Brain Database Doesnt See Skin Color: Color-Blind Racism in the Technology Industry and in Theorizing the Web. American Behavioral Scientist, Vol.59, No. 11, 2015, pp. 1-17.
Florentine, Sharon. Racism in tech Runs Deep. CIO, 9 Mar 2017.
Kleinman, Zoe. Artificial intelligence: How to Avoid Racist Algorithms. BBC, 14 Apr 2017.
Levin, Sam. Women say they Quit Google because of Racial Discrimination: 'I was Invisible'. The Guardian, 18 Aug 2017.
Maguire, Mark. Biopower, Racialization and new Security Technology. Social Identities, Vol. 18, No. 5, 2012, pp. 593-607.
Request Removal
If you are the original author of this essay and no longer wish to have it published on the customtermpaperwriting.org website, please click below to request its removal:
