By Angeline Lee

In this moment, when we are reimagining our systems during calls to end racial structural violence and during a devastating pandemic, it’s important that we start with reforming language, replacing terms that exclude and reinforce oppression in our systems. Translating technical terms from English to other languages includes running the risk of unintentionally and unconsciously imposing Western values and constructs of gender, race, and individualism through technology. Terms like “whitelist/blacklist” and the “master/slave” programming command carry the weight of systemic issues deeply rooted in society. When these terms are localized into other communities, the values associated with them could be transferred into other cultures with different ideas of race and gender¹. Though the intent may not be to reinforce existing stereotypes and inequality, the effect is proven in the lack of inclusive language for a spectrum of users.

Translating terms with sexual innuendos perpetuate ideas of sex and gender, often in a binary bias. Sexist terms “preserve the ways in which casual use of English serves to uphold maleness as the norm and femaleness as the exception.”² Male domination, especially in decision making roles within the tech industry is evident by the exclusionary language used. By reinforcing sexist terminology, “gendered language performs some of the work of exclusion by reinforcing the message that female programmers are exceptions.”³ In order to systematically change tech culture and reach true inclusivity, language must also shift and reflect equitable values.

As we work in partnerships with marginalized groups, it is crucial that we are transparent about the problematic and at times violent histories of these terms; that we do not unconsciously pass on and perpetuate harmful ideology. For example, during our Localization Sprint in Thailand, participants collaboratively pushed back on existing constructs, intentionally careful in their methodology of language adoption. When technical terms are localized and translated, ideas are consequently transferred over, preserving or even promoting ideals of race, class, and gender onto other cultures without a clear understanding of possible harm. Language has the power to manipulate and change rhetoric, and it is our responsibility to acknowledge these problematic terms, change the narrative, and combat digital colonialism.

The tech industry is notoriously known as a heteronormative, white, male-dominated space; a bubble of intergenerational wealth, patriarchy, and privilege. The language and technical terms used in the tech industry are a reflection of those who are represented, hold the power, and control discourse. This exclusive fortress of power can create a hostile and uninviting environment for those who do not subscribe to, or identify with the norm; denying entry for diversity and inclusion based on colonial lines.

This article examines the technical terms used in cybersecurity, programming, and platforms with a gendered and racial lens, critiquing outdated and biased words used in the industry.

Racial & Ethnic Bias in Tech Terminology

Master-Slave command (Programming)

The term “Master-Slave” is a common computer programming phrase that refers to the idea that “components have total control over other components, or are controlled by a component, respectively,” ⁴ a one-way direction of control and power. By continuing to directly connect its association with slavery, this term normalizes inhumane practices, perpetuating the 465 years of institutionalized systemic oppression of Black Americans ⁵ . In addition, modern slavery in the form of the prison industrial complex, domestic servitude, and child soldiers still exist today.

By reducing “master” and “slave” to computer parts, the term desensitizes and softens the painful, historical dehumanization of enslaved peoples. This terminology, which has already been removed by Django, Twitter, Python, and Github contributes to the “power dynamic that’s the blood in the heart of racism.” ⁶ The term “reflects the bigotry of those that dominated the field when much of the conventions for technology were formed.” ⁷ The Master-Slave command is easily replaceable with more appropriate terminology like “database credentials” and “main” instead of “master”.

Blacklist, Whitelist, Black hat hacker, White hat hacker

In the most simplest terms, the racist ideology of “white is good, black is bad” ⁸ is unfortunately echoed into the racist biases of society, which has then translated into the exclusionary binary of technical language. The dichotomy of the colors - white and black, which respectively equates to good and evil, desirable and undesirable, not only reflect racist and colorist sentiments, but mirrors the problematic racist stereotypes of people in society.

The terms “whitelist” and “blacklist” are used in digital security to differentiate approval and denial. Whitelisting has a “trust-centric approach, allowing access for approved entities” ⁹ . While “blacklisting” is “threat-centric and involves blocking access to suspicious or malicious entities ¹⁰ . The implications of good and bad associated with these terms have a historically racist past, accompanied by the hierarchical direct relationship between race, class, and power. Additionally, the term “white/black hat hackers” have similar connotations of good and evil, oftentimes compared to ethical and criminal hacking, respectively. Subconsciously, the implications of the colors white/black bleed into the problematic biases for people of color. Mallory Knodel, the former Chief Technology Officer at Article 19 addresses that “this trope has significant impact on how people are seen and treated. As we’ve seen with metaphors, its use is pervasive and, though not necessarily conscious, perceptions do get promulgated through culture and repetition.” ¹¹ There is no technical need to use “white/black” in describing these mechanisms. In addition to reinforcing structural racism, the choice to continue this type of language reinforces overt prejudice and unconscious biases against a community that is already underrepresented in the field of technology.

Grandfathering

Though not exclusively used in the tech industry, phrases like “that product was grandfathered in” are directly related to the grandfather clause used to discriminate against African Americans in the nineteenth century. This phrase is usually used to describe “individuals or companies who get to keep operating under an existing set of expectations when new rules are put in place.” ¹² Racialized in its origins, the grandfather clause was created to discriminate and institutionally disenfranchise black voters and “their descendants from voting, while allowing poor and illiterate whites to vote.” ¹³

Though the usage of grandfathering is now part of mainstream vernacular, its origins are rooted in oppressive policies enacted to institutionally disenfranchise African Americans. The term’s historical connections to slavery and casual reference to White supremacy does not reflect the ideals of an inclusive, safe, and equitable environment.

Mechanical Turk

Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace that allows for businesses to outsource their jobs to a distributed virtual workforce. ¹⁵ The original Mechanical Turk is a fake chess-playing device, created in the 18th Century by a Hungarian engineer. ¹⁶ The device was an automated machine that acted as a mechanical illusion, while a real person hidden inside the device played chess.

The name and use of the Turkish culture embodied in these two automated mechanisms is rooted in the idea of oriental, mysticism from the East; a stereotype pinned on those originating from Asia. Ayhan Aytes, a researcher on cultural history of Artificial Intelligence and Cognitive Labor, connects the way the West views the East as “performers of technological and cultural alterity, satiating the anxieties caused by the unfamiliar notion of mechanized cognition, by projecting them onto all-familiar ethnic and religious differences.” ¹⁷ The parallels of Amazon’s platform and the Mechanical Turk encompasses the idea of a mystic, hidden labor force; fulfilled by others, unbeknownst to the mainstream audience. Heavily criticized for its low-pay and lack of labor regulations, Amazon’s platform exploits those who are in desperate need of employment, yet have adept technical skills.

Through Amazon’s platform, the word “turk” has additional dimensions. Employees are called “turkers”, and the verb form is known as “turking”. The term “turk” has a derogatory history, a blanketed label used to describe anyone with ethnic origins from the Middle East. Racialized in nature, Amazon’s use of the name “Mechanical Turk” highlights how the West is “overlooking examples from Islamicate cultures as an extension of colonialist desires to exclude non-western cultures from the Western-centric histories of science and technology.” ¹⁸ Not only is it problematic as a platform, but the name reinforces the idea that “Orientalist undercurrents were exploited by Enlightenment discourse in order to configure the docile subject on the image of the Turk.” ¹⁹ Usually performed by marginalized communities, the hidden labor of automated work is portrayed in both of these machines.

Sexist, Classist, and Cishet-normative Terminology

Fingering, Penetration and Pentest (Digital Security)

Digital security has several problematic terms rooted in sexism, including but not limited to fingering, penetration, and pentesting.

The term “fingering” has had various meanings in tech throughout the years. The original and most common use comes from a computer science term; an old Unix command called “finger.”²⁰ Created in 1971, it is used to find information on a particular user in a computer or a network.²¹ Though the origins of the term was not intended to be sexual, the meaning of the word has evolved to become so. “Fingering” as a computer command may be uncomfortable for a group of people, specifically women, who represent a minority in the tech industry.

The word penetration has many different meanings and has taken a definition of its own in the tech world. Phrases such as “internet penetration” and “penetration of products” insinuates a forceful entry and hints at a sexual innuendo. Though this term has entered mainstream vocabulary, it is important to address how it could conjure up past traumas or unpleasant imagery; especially for survivors of sexual assault.²²

In addition, penetration testing or pen test is an “attempt to evaluate the security of an IT infrastructure by safely trying to exploit vulnerabilities.”²³ Also known as ethical hacking, pen testing is a common method used in assessing security. While acknowledging this word can be used in nonsexual contexts, the mere use of penetration as technical terminology implies a sexual act and a masculine endeavor, a reflection of dominance in a majority male industry.

Male/Female Connectors

Female and male connectors are terms used in electrical and mechanical trades. A male connector is usually a “plug and has a solid pin for a center conductor.”²⁴ A female connector is “a jack and has a center conductor with a hole in it to accept the male pin.”²⁵ This mechanism is a direct analogy to sexual intercourse and the assumed binary nature of gender. By strictly promoting this cis normativity, we indirectly push this notion that gender and sex are binary, excluding and delegitmalizing those who identify as gender non-conforming or trans. In lieu of assigning a gendered relationship, using +/- could adequately represent this binary relationship.

John the Ripper

John the Ripper is a free, open source, “fast password cracker” used to detect weak Unix passwords.²⁶ The name is a play on the infamous “Jack the Ripper”, a serial killer who preyed on low-income women and mutilated the bodies of five sex workers in 19th century London.²⁷ The commemoration of a sadistic killer whose “crimes seemed to portray an abhorrence for the entire female gender”²⁸ feeds into the solicitous headlines that disregard the real fear of sexual assault. If diversity in the tech community increased, tools like John the Ripper might instead have titles that describe their actual function, without conjuring violent imagery.

Evil Maid Attack

An evil maid attack is an “attack in which bad actors gain physical access to unattended computing devices for malicious activities.”²⁹ This term originated from the idea that devices are left unattended in hotel rooms, where a maid has unsupervised access.³⁰ Assigning this type of attack to a typically female, service profession can be seen as playing into the demonization and distrust of those in the lower income bracket and could perpetuate harmful and false stereotypes of stealing and dishonesty. From a translation perspective, the analogy supporting "evil maid attack" is also complex and the relationship is difficult to explain, making it a particular challenge to translate in addition to the term being problematic in nature.

SuCKIT

A rootkit is a “stealthy type of malicious software designed to hide the existence of certain processes or programs from normal methods of detection.”³¹ A type of rootkit created to detect this compromise is named “sucKIT.”³² The name is a play on the vulgar expression “suck it,” which is oftentimes used as an insult, insinuating phallic action. Frequently used colloquially, it is a condescending phrase often indicating gendered power and dominance.

Man-in-the-Middle Attack (MitM)

A man-in-the-middle attack is when “an attacker intercepts communications between two parties either to secretly eavesdrop or modify traffic traveling between the two.”³³ Known as one of the oldest cyber attacks, this term does not translate well into other cultures nor does it accurately represent its description. Instead, the term “on-path attackers” is more accurate, as “attackers can then collect information as well as impersonate either of the two agents.”³⁴ Assigning this position of power to a man again highlights the male dominance in this industry. Because this type of attack was assigned a binary gender, it further reinforces that cybersecurity, hacking, and tech are for men, excluding other identities and representation.

Moving Towards Inclusive Terminology

Inequitable terms can easily be replaced to create change without compromising the value of the technical work itself. Instead, a plethora of alternative, appropriate, and inclusive terms should be used and mainstreamed, creating a new norm.

Language and culture are intrinsically connected, reflecting societal norms and its values. ³⁵ In a Western-centric industry, it is important to address and reconfigure the racist and sexist technical terms, even if unintentionally so, that are still used today. Knodel notes, “subtle configurations of sexist, racist, or ethnocentric language use[d] in technical documents can derail or interfere with readers’ ability and desire to comprehend and follow important information.” ³⁶ When language serves to reinforce a dominant group’s values and power, marginalized groups are forced to work within these imbalanced power dynamics, stifling abilities of consent and inclusion.

Merely hiring people of color is not enough, and changing the problematic language used within the industry is one step towards shifting the culture. Although language sounds innocent and a relatively minute detail, its influence becomes exponentially elevated when translated and localized to adapt to other cultures. For example, languages that use a masculine/feminine form risk mainstreaming the male form and erasing female presence. ³⁷ Practitioners must lead by refusing to use terminology that reinforces oppressive, exclusionary structures. These terms, which are embedded in the technical infrastructure of society, must represent an inclusive environment, as we work to reimagine and reconstruct societal foundations.

These expressions used in technology are a reflection of the historical biases within society. As we aim to create a diverse and inclusive industry, terminology matters. As we work to dismantle white supremacy and cultural bias, we must explore how Western binary definitions of race, gender, sexuality, class, and power affect those who rely on technologies developed in the West. When technology is localized to other cultures, especially adopted for minority groups, it is important that individuals feel safe and comfortable with the tools and language they are using. We need to replace terms that support casual racism, sexism, and cisheteronormativity with inclusive language, and ensure that dangerous ideologies are not perpetuated in other cultures, preventing harm in communities that rely on this technology. The tech industry has the power to change and shift its narrative, and it starts with inclusive language.

At Localization Lab, we hold localization sprints to discuss tech terminology and how to responsibly localize to different communities. This practice could be adopted for an English language sprint, bringing together diverse contributors in the tech space to tackle the complex and nuanced challenge of creating inclusive language and building a guide towards best practices.

Citations

¹ Taha, L., & McConnell, E. (2020, April 14). On Absenting Women from Arabic Public Discourse. Retrieved July 29, 2020, from https://www.localizationlab.org/blog

² Chevalier, T. (2014, February 24). Gendered Language: Feature or Bug in Software Documentation? Retrieved from https://modelviewculture.com/pieces/gendered-language-feature-or-bug-in-software-documentation

³ Ibid

⁴ Oberhaus, D. (2018, September 13). 'Master/Slave' Terminology Was Removed from Python Programming Language. Retrieved from https://www.vice.com/en_us/article/8x7akv/masterslave-terminology-was-removed-from-python-programming-language

⁵ Worland, J. (2020, June 11). America's Long Overdue Awakening on Systemic Racism. Retrieved from https://time.com/5851855/systemic-racism-america/ , Solomon, D., Hanks, A., & Weller, C. E. (2018, February 21). Systematic Inequality. Retrieved from https://www.americanprogress.org/issues/race/reports/2018/02/21/447051/systematic-inequality/

⁶ S. (2018, September 9). Even in Tech, Words Matter. Retrieved from https://deninet.com/blog/2018/09/09/even-tech-words-matter

⁷ Ibid

⁸ The New York Times, T. (2017, April 02). Readers Respond: Which Racial Terms Make You Cringe? Retrieved from https://www.nytimes.com/2017/04/02/us/racial-terms-that-make-you-cringe.html

⁹ Blacklisting vs. Whitelisting. (2019, August 12). Retrieved from https://consoltech.com/blog/blacklisting-vs-whitelisting/

¹⁰ Ibid

¹¹ Knodel, M. (2019, September 12). Terminology, Power, and Offensive Language [Scholarly project]. In Network Working Group. Retrieved 2020, from [https://tools.ietf.org/html/draft-knodel-terminology-01][0]

¹² Greenblatt, A. (2013, October 22). The Racial History Of The 'Grandfather Clause'. Retrieved from https://www.npr.org/sections/codeswitch/2013/10/21/239081586/the-racial-history-of-the-grandfather-clause

¹³ Riley, N. (2019, May 31). Words Matter: Why We Should Put an End to "Grandfathering". Retrieved from https://medium.com/@nriley/words-matter-why-we-should-put-an-end-to-grandfathering-8b19efe08b6a

¹⁴ Mechanical Turk. Digital Image. Untold History of AI: When Charles Babbage Played Chess With the Original Mechanical Turk. 18, March 2019. https://spectrum.ieee.org/tech-talk/tech-history/dawn-of-electronics/untold-history-of-ai-charles-babbage-and-the-turk

¹⁵ Amazon Mechanical Turk. (n.d.). Retrieved July 02, 2020, from https://www.mturk.com/

¹⁶ What is Mechanical Turk? (2016, July 11). Retrieved from https://www.pewresearch.org/internet/2016/07/11/what-is-mechanical-turk/

¹⁷ Aytes, A. (n.d.). Media Archaeology, Cultures of Automata, and Mechanized Cognition. Lecture presented at Cornell University. Retrieved 202, from http://complit.cornell.edu/sites/complit/files/Aytes_Talk.pdf

¹⁸ Ibid

¹⁹ Ibid

²⁰ Finger protocol. (2020, May 16). Retrieved July 24, 2020, from https://en.wikipedia.org/wiki/Finger_protocol

²¹ Colbath, Sean. “Origins of the Finger Command .” Google Groups, Google, 1990, groups.google.com/forum/#!msg/alt.folklore.computers/IdFAN6HPw3k/Ci5BfN8i26AJ.

²² New, J. (2015, May 27). Asking Too Much, or Not Enough? Retrieved August 17, 2020, from https://www.insidehighered.com/news/2015/05/27/language-sexual-assault-surveys-criticized-students-triggering

²³ Penetration Testing. (n.d.). Retrieved July 02, 2020, from https://www.coresecurity.com/penetration-testing

²⁴ What is the difference between male and female connectors? (n.d.). Retrieved July 02, 2020, from https://www.l-com.com/frequently-asked-questions/what-is-the-difference-between-male-and-female-connectors

²⁵ Ibid

²⁶ John the Ripper Password Cracker. (n.d.). Retrieved July 02, 2020, from https://www.openwall.com/john/

²⁷ Dickson, E. (2019, March 18). Jack the Ripper May Finally Have Been Identified, Says New Study. Retrieved from https://www.rollingstone.com/culture/culture-news/jack-the-ripper-identity-study-aaron-kominski-809808/

²⁸ History.com Editors. (2010, November 08). Jack the Ripper. Retrieved July 02, 2020, from https://www.history.com/topics/british-history/jack-the-ripper

²⁹ Yedakula, K. (2019, April 14). What is an Evil Maid attack and how is it different from Evil Twin attack?: Cyware Hacker News. Retrieved from https://cyware.com/news/what-is-an-evil-maid-attack-and-how-is-it-different-from-evil-twin-attack-8a73a96

³⁰ Evil maid attack. (2020, June 07). Retrieved from https://en.wikipedia.org/wiki/Evil_maid_attack

³¹ Checking for Known Rootkits. (n.d.). Retrieved July 02, 2020, from https://security.web.cern.ch/recommendations/en/rootkits.shtml

³² Ibid

³³ Swinhoe, D. (2019, February 13). What is a man-in-the-middle attack? How MitM attacks work and how to prevent them. Retrieved from https://www.csoonline.com/article/3340117/what-is-a-man-in-the-middle-attack-how-mitm-attacks-work-and-how-to-prevent-them.html

³⁴ “What Is an on-Path Attacker? .” Cloudflare, www.cloudflare.com/learning/security/threats/on-path-attack/.

³⁵ Birner, B. (n.d.). Does the language I speak influence the way I think? Retrieved July 02, 2020, from https://www.linguisticsociety.org/content/does-language-i-speak-influence-way-i-think

³⁶ Knodel, M. (2019, September 12). Terminology, Power, and Offensive Language [Scholarly project]. In Network Working Group. Retrieved 2020, from [https://tools.ietf.org/html/draft-knodel-terminology-01][0]

³⁷ McConnell, E., & Taha, L. (2020, April 14). On Absenting Women from Arabic Public Discourse. Retrieved July 29, 2020, from https://www.localizationlab.org/blog