#techbias

[live-infographic]

Multi Linear Regression in Machine learning via @ http://www.liveinfographic.com/ Techbiason, November 27, 2020 at 08:16AM

[kristynguyen7]

Blog Post #3 - Week 4 (due 2/13)

Racial Bias and Technology

How does Anna Everett’s idea of “black technophilia” challenge common beliefs about the digital divide, and how does Black history with technology add complexity to this view? 

Everett challenges the common idea of the “digital divide” by showing that African Americans have often been early users of new technology, rather than being left behind. She highlights Black “technolust,” stating that “the swelled ranks of black people throughout the African diaspora connecting to the Internet, particularly to the World Wide Web, have forced a new reckoning with the rapidly changing configuration of the new electronic frontier” (Everett, 2002, p.133). This shifts the view of Black digital participation from being behind to being actively involved in tech progress. She also compares this to past technologies like the printing press, radio, and film, showing that Black communities have embraced and shaped technological advancements despite facing barriers. This challenges the idea that technology gaps exist only because of lack of access and instead highlights the creativity and adaptability of Black communities in using new media. 

How does Everett’s view of the digital public sphere challenge traditional ideas of the Habermasian public sphere, and how does the Internet create new spaces for Black communities to share their voices? 

Everett challenges the Habermasian idea of the public sphere by showing how Black communities have been excluded from mainstream discussions but have still created their own spaces for expression. She references Houston A. Baker Jr., who says Black Americans “are drawn to the possibilities of structurally and affectively transforming the founding notion of the bourgeois public sphere into an expressive and empowering self-fashioning” (Everett, 2002, p. 141). The Internet helps Black counterpublics form, as seen with the Million Woman March, where “working and so-called ‘under-class’ black women made ingenious uses of the new technology to further their own community uplift agendas” (Everett, 2002, p. 131). This shows how the Internet can empower marginalized voices beyond traditional media limitations. 

How does Ruha Benjamin define the “New Jim Code,” and how does it continue systemic racial inequalities in technology? 

Benjamin defines the “New Jim Code” as “the employment of new technologies that reflect and reproduce existing inequities but that are promoted and perceived as more objective or progressive than the discriminatory systems of a previous era” (Benjamin, 2019, p. 23). This concept highlights how racism is not eradicated by technological advancement but is instead embedded within algorithms and automated systems. For example, predictive policing and biased AI hiring tools reflect historical inequalities under the guise of neutrality. These systems  entrench racial hierarchies while appearing race-neutral, making discrimination harder to challenge. Thus, the New Jim Code is a continuation of systemic oppression through digital means. 

How does Benjamin challenge the idea that technology is neutral, and what are the risks of ignoring its racial biases? 

Benjamin challenges the assumption of technological neutrality by arguing that “encompasses a range or discriminatory designs - some that explicitly work to amplify hierarchies, many that ignore and thus replicate social divisions” (Benjamin, 2019, p. 26). She emphasizes that technology does not simply reflect society but actively shapes and reinforces systemic biases. Ignoring the racialized design of technology allows injustices to be obscured under claims of efficiency and objectively. For example, algorithmic hiring systems often replicate historical patterns of exclusion, disproportionately disadvantaging Black applicants. By assuming technology is impartial, society enables these systems to operate unchecked, making discrimination even more difficult to detect and challenge. 

How does Safiya Umoja Noble show that search engines reinforce racial and gender biases, and why does this matter for society? 

Noble argues that search engine algorithms reinforce racial and gender biases by privileging crucial events over the concerns of human rights. She critiques the notion that search engines are neutral, showing how Google’s algorithm prioritizes content based on profit rather than ethical considerations. For example, early Google searches for “Black girls” returned hypersexualized content, revealing how “we need a full-on reevaluation of the implications of our information resources being governed by corporate-controlled advertising companies” (Noble, 2018, p. 34). This bias shapes public perception and access to knowledge, reinforcing systemic inequalities. Without accountability, these technologies continue to reproduce harmful stereotypes that disproportionately affect marginalized communities. 

Word Count: 576

Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Polity.

Everett, A. (2002). The revolution will be digitized: Afrocentricity and the digital public sphere. Social Text, 71(20.2), 125-146.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.

[classicinfj]

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[unabashedlytremendousphilosopher]

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