CMNS_488_ALGORITHMS_IN_THE_ARCHIVES

I presented this research at the Faculty of Communication, Art, and Technology Undegraduate Research Conference at SFU on April 14, 2024. Directly below are the slides I created for that presentation, followed by the actual paper.

In an age of rapid artificial intelligence (AI) development and critical issues regarding privacy, it’s easy to forget that the human value of community has always been a target in machine learning & technology. Even when 21st century tech companies are more invested in profit, the selling point has always been focused on community, which branches into desirability, transparency, and at its core, what makes someone human. Just like any other community, these virtues are important in queer communities, as they consequently grow in importance as a result of European settler colonialism hegemonic structures —white supremacy and capitalism.  Alan Turing’s work in exploring gender in machine learning as a gay man, pre-internet BBSes serving as underground hubs for queer communities, and Safiya Noble’s work on oppressive algorithms are examples of how machine learning has evolved to uplift or damage marginalized communities. In this paper, I will specifically explore how queer communities have sold or sell intimacy as a form of community, and how this calls into question the larger issues of desirability politics and where that comes from and a continued need for intersectionality in digital spaces.

I think that positionality is important to note, especially when talking about issues regarding marginalized communities such as the LGBTQI+ community, which I will be referring to using the umbrella term queer community, unless archival sources are limited to a certain or certain groups. I am writing this paper from the perspective of a second generation Filipino-Canadian settler, using archival sources that are limited to a western framework, specifically the UK and North America. Although I will be analyzing the culture, experiences, and perspectives of early digital queer communities, they do not speak for everyone in these communities, nor do they reflect the same for societies elsewhere in the world regardless of time. 

Machine Learning & Selling Intimacy

Alan Turing’s Imitation Game

Alan Turing was a British mathematician and an openly gay icon at a time when it was illegal to be homosexual. He is best known for his work called the “Imitation Game” which stemmed from a parlour game in British society that involved “swapping genders” between a man and a woman (Turing, 1950). Another person of either gender played the role of “interrogator” and had to guess which one was a man or woman. In Turing’s (1950) iteration, a computer played the role of the woman and the goal was to see if the computer was intelligent enough to present itself as a human woman. Turing’s goal was to find a way to measure intelligence that didn’t have anything to do with the body and gender (personal communication, November 14, 2023). On a socio-political level, it can be understood as exploring the theory that gender is a construct and how it’s mutually exclusive with sexuality. 

Introduction of Notable Queer BBSes: GLIB & Multicom-4

According to The Queer Digital History Project (n.d), the Bulletin Board System (or BBS) served as a precursor to social media by the way it provided hubs for anyone, including members of queer and other marginalized communities to connect, as long as they had the means. BBSes worked via a modem that an individual would have to call to gain access to the board’s functions, such as games, chat rooms, and files (Al’s Geek Corner, 2020). Two notable BBSes were GLIB (1986-2001) and Multicom-4 (1989-2000). GLIB, also known as the Gay & Lesbian Information Bureau was “a free computer-based information and international communications resource proudly and continuously serving the greater gay, lesbian, bisexual, and transgendered community since 1986” (GLIB, 2000). Within this well-known BBS, members were able to share opinions, questions, and information about things they might be interested in. One of the co-founder’s expressed that, despite the death threats he received early on almost every day - his “most treasured messages are those from men and women positively stunned to discover anything like GLIB …” for example, closeted men and women living in seemingly heterosexual married lives (GLIB, 2000). On the other hand, Multicom-4 was a New York state-based BBS that became a gay and lesbian BBS when sysop, slang for system operator (Al’s Geek Lab, 2020), Chaz Antonelli, came out in the 1980s (The Queer Digital History Project, n.d.). Whereas GLIB took the form of a traditional bulletin board that users could visit, the Multicom-4 BBS held regular in-person gatherings and maintained free terminals in Rochester and Buffalo, NY in which people who didn’t have access to a computer and modem could become members (as opposed to users of GLIB) of the community (The Queer Digital History Project, n.d; Al’s Geek Lab, 2020)

The two BBS systems are examples of how human beings have explicitly delved into using technology to create digital hubs for queer communities. They are reminiscent of Christopher Strachey’s work on early computer music and games, and arguably, the first piece of computational art that took the form of a love letter generator compiled via random number generation (Gaboury, 2013). Strachey was a student at the time Alan Turing was a faculty member at King’s College; the notable difference between them being that Strachey was a closeted  gay man (Gaboury, 2013).  Still his work at the time is groundbreaking in that we can see its influence in BBS culture for the queer community. 

Machine Learning & Desirability Politics

BBSes were popular as a counter culture for two significant reasons; 1) they allowed marginalized groups of people to connect in a way that allowed them privacy in a pre-internet era and 2) it still felt human-centric. As a former BBS user said in the documentary “Back to the BBS,” the former was especially significant in that individuals knew that there was a human behind a BBS — the sysop; therefore, if a problem occurred, such as they couldn’t connect to the BBS, they knew there was probably an issue with the human itself, something as mundane as the sysop’s parents cutting off the modem connection or there was someone else using the only phone line in the household (Al’s Geek Corner, 2020). However, although BBS was a popular counter culture in the late 80s to 90s, accessibility is an issue as the archives on this technology and the people who grew up with them are mostly white. What is not available in the archives of the BBS era are voices from queer people who were racialized minorities, disabled, and/or fat. To this day, beauty standards that align with white supremacy, such as a fit body, chiseled face, symmetrical face, light skin, and a pointy nose are markers for how beauty is defined for people in the queer community. Additionally, because western society is patriarchal and dominantly heterosexual and Christian, many queer people feel pressured to become “conventionally attractive” to make up for not meeting society’s standards. If they cannot play into gender roles, they can at least attempt to transcend the roles laid out for them in hopes they are exempt. Of course, the pressure reigns much more for people of colour who are more likely to stray away from the dominant beauty standard. For example, Filipinos in the diaspora grow up with beauty standards that align with those of our colonizers —Spain, the United States, and Japan. Although Japan is an Asian country, east Asian features, such as light skin and small noses are still in proximity to white supremacist beauty ideals. 

Intersectionality As A Continued Call to Action

This cause for concern stems from a term called “desirability politics.” While there is not an official definition for it, I connect it to the significance of white supremacy and how European settler colonialism in North America brought upon their beauty standards. So even if there exists a deep nostalgia for computers before the world wide web and BBSes for the queer community, how did queer people who were also part of other marginalized groups feel about openness to their gender and sexuality? If it were anything like technology in the 21st century, in which wearable tech like apple watches profit off of people not meeting the dominant beauty standards (Schüll, 2016), marginalized people’s data are exploited, such as Indigenous peoples data just for data/research sake (Radin, 2017), or harmful stereotypes create oppressive computer algorithms (Noble, 2018), it is safe to assume that not much has changed. When dealing with any system, in this case, digital systems, it is also safe to assume that the data and algorithms not only reflect the biases of the humans who work on technology (Seaver, 2019), but that they are largely reflective of the dominant systems of oppression brought by settlers hundreds of years ago, sometimes into the history of our own Indigenous lands, who established societies through violence, genocide, and abuse. More than ever, collective power and voices from queer people who are also people of colour, fat, and/or disabled are needed to mend data injustices in digital spaces, because everyone deserves safe community spaces.

Conclusion

In this paper, we explored how queer communities have sold or sell intimacy as a form of community through looking at the early work of British mathematician Alan Turing and BBSes GLIB and Multicom-4, and how this calls into question the larger issues of desirability politics and where that comes from and a continued need for intersectionality in digital spaces.

To accompany these examples of empowerment for equitable justice,  research on tech companies associated with policymakers and their role in censorship, hate speech, discrimination towards queer community can help contextualize the politics involved. Additionally, the technical differences between BBSes and social media and how they differ in selling community values can help contextualize the role data plays in contemporary issues. 

Reference List

Al’s Geek Lab. (December, 2020). Back to the BBS - Part one: The Return to Being Online. [Video]. Youtube. https://www.youtube.com/watch?v=n0OwGSX2IiQ&list=PLop3s1hMlSJKXqmuFjK7gbJh2WAyllTTY&index=1&t=1719s 

Antonneli, C. (2015, November 7). The BBS Documentary and Multicom-4. Queer Digital History Project. https://mc4bbs.livejournal.com/246094.html 

Duarte, N., Llanso, E., & Loup, A. (2017). Mixed messages? The limits of automated social media content analysis.

Gaboury, J. (2013), ‘Darling sweetheart: Queer objects in early computer art’, Metaverse Creativity, 3: 1+2, pp. 23–27, doi: 10.1386/mecr.3.1-2.23_1 https://queerdigital.com/items/show/55.

Queer Digital History Project. (n.d). Bulletin Board Systems. https://queerdigital.com/exhibits/show/platforms/bulletin-board-systems

Schüll, N. D. (2016). Data for life: Wearable technology and the design of self-care. BioSocieties, 11(3), 317–333. https://doi.org/10.1057/biosoc.2015.47

Radin, J. (2017). Digital Natives. Osiris (Bruges), 32(1), 43–64. https://doi.org/10.1086/693853

Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press.

Seaver, N. (2019). Captivating algorithms: Recommender systems as traps. Journal of Material Culture, 24(4), 421–436. https://doi.org/10.1177/1359183518820366

Seaver, N. (2019). Knowing Algorithms. In digitalSTS (pp. 412–422). Princeton University Press. 

https://doi.org/10.1515/9780691190600-028

Turing, A. M. (1950). Mind. Mind, 59(236), 433-460.