[Hamsini - Non-core post 3] The Manosphere

Not to keep harping on influencers, but this BuzzFeed piece is interesting (and horrible): https://www.buzzfeednews.com/article/adeonibada/andrew-tate-fresh-fit-podcast-kevin-samuels-toxic-male

The "manosphere" and the ways misogyny (and misogynoir) seems ever-present in digital culture: to what extent have misogyny and responses to it structured platforms, in terms of design, moderation, entanglement with practice? From the early days of the internet (e.g., Dibbell's "A Rape in Cyberspace" article from 1993) to Gamergate to incels to whatever is going on here with Andrew Tate. The Anable piece reminds us to connect the materiality of technologies with the materiality of bodies; the stories in this article are all as much stories of race, gender, and class as they are of platforms, influence, and deplatforming. I think it also shows the need to study phenomena across platforms: the way actors who cause harm (often in the pursuit of profit as much as ideology) move opportunistically and fluidly across Reddit, YouTube, IG, TikTok, podcasting, the chans, etc... I suppose the manosphere could be thought of as ecosystemic (though I think that metaphor runs the risk of "naturalizing" deliberate and opportunistic behavior...). 

Julia Rose Camus - Additional Post 3

As a follow-up to my presentation today, I just wanted to share some additional resources about the Dark Web that I encountered in my research. While thinking of the Dark Web as a platform is a bit out of the box, I do think it serves an important role in creating space for resistance, beyond its more notorious uses.

Broad overview of The Dark Web:

https://www.youtube.com/watch?v=ngT2Aq1VBFc

Useful papers on the way in which the dark web has aided community organising and activism:

https://uosc.primo.exlibrisgroup.com/discovery/fulldisplay?docid=cdi_crossref_primary_10_1177_1461444814554900&context=PC&vid=01USC_INST:01USC&lang=en&search_scope=MyInst_and_CI&adaptor=Primo%20Central&tab=Everything&mode=Basic

https://uosc.primo.exlibrisgroup.com/discovery/fulldisplay?docid=cdi_proquest_miscellaneous_1771459506&context=PC&vid=01USC_INST:01USC&lang=en&search_scope=MyInst_and_CI&adaptor=Primo%20Central&tab=Everything&mode=Basic

"Toxic" feat. AO3

Here are the artists of our age telling us that no good culture is left un-recycled. PLEASE sing along. 

Original post: 

https://homo-sex-shoe-whale.tumblr.com/post/655107456535560192/ive-done-something-a-little-weird

Dalia Hatalova Blog Post #3/15

Google Photos is a popular form of cloud storage that draws users by offering to store and retrieve personal photos as desired. When Google launched the platform, it was originally free to use because Google needed more data on which to train its algorithms, making it a particularly interesting interaction between platform and user, which raises questions about digital consent. When users signed on, they gave up ownership of their images by clicking off 'accept' on a contract, which allowed Google to utilize them as data cannon fodder. As Victor Luckerson describes in an article, "Google already has plenty of pictures of objects that it's indexed across the web with its search engine, but it still doesn't know that much about what individual people look like." Having a vast database of images allowed Google to sell information about their users to advertisers, as some new articles raised concerns as early as 2015 when the platform launched. This desire for information on users is a similar motivation to Google's acquisition of Youtube, where "Google was predominantly interested in YouTube's (meta-)data revealing patterns of user's interests and behavior, in order to connect these patterns to other Google databases and sell relevant information and space to advertisers" (van Dijck 149). 

This very data allowed Google's algorithm to function effectively, which is a crucial aspect of data acquisition that is often less mentioned. This training of algorithms is expanded upon in Nick Srnicek's analysis, however, where he states that "Cloud platforms ultimately enable the outsourcing of much of a company's information technology (IT) department" (Srnicek 33). Hence, companies not only gather their own data but are able to gain additional data by renting their capacities to other companies: something Google Photos does on a personal level with users. The aspect of the Google Photos cloud storage being free served to draw as many users as possible. Similar to the search algorithm,  "the more numerous the users who search on Google, the better their search algorithms become, and the more useful Google becomes to users" (26). An early article discussed a concern regarding Google storage – in this case, Google Drive – owning material that is uploaded there dating back from 2012, but a lot of the discussion centers around privacy rather than the labor that this data provided by users contributes. 

While providing free storage and training algorithms may appear to be a fair exchange, the lack of transparency is nevertheless concerning. Tarleton Gillespie describes Google's strategy as appearing to be but a neutral procurer of services through self-labeling itself as a platform. He writes, "calling their service a 'platform' can be a way not to trumpet their [Google's and YouTube's] role, but to downplay it" (Gillespie 357). The last development in the saga of Google Photos that I identified from my searches about the service, which adds to the downplaying of the company's role in monetizing user data, occurred in 2020 when Google requested users to actively participate in training algorithms for better performance (Young Won, Vincent). Crowdsourcing algorithmic training in this way presents an interesting collaborative twist. While consensual, the publicity does make one question how users' relationship with Google has evolved through the years, resulting in an acceptance of how algorithms use our data. This acceptance is particularly surprising considering that Google did not explicitly foreground Google Photo's exchange of free storage in return for data at the launch of the service for fear of alienating its users. 

Dalia Hatalova Blog Post # 2/15

I was interested in this article that dates back to 2015 and concerns itself with Google's algorithmic mislabeling of Black people as gorillas at the time. It is an interesting illustration of the possible biases of algorithms, so I'm retracing steps to last week's texts. For Taina Bucher, "algorithms, understood as forms of organizational logic, some with specific affordances that both enable and constrain" (Bucher 23). These constraints are apparent in Google's mislabeling, which was a result of the algorithm's inability to adhere to an organizational structure. The author of the Wall Street Journal article shared here (though there were many other publications covering it at the time), Alistair Barr, writes, "machine-learning systems don't understand the difference between mistaking a chimp for a gorilla, which may be OK, and mislabeling a human as a gorilla, which is offensive" (Barr). As such, in addition to failing to categorize correctly, the algorithm may also fail on account of not realizing the emotional impact of certain mislabeling. Barr's conclusion points toward the fact that "machine-learning systems often reflect biases in the real world. Some systems struggle to recognize non-white people because they were trained on Internet images which are overwhelmingly white" (Barr). Similarly, Ed Finn warns that "algorithms and their human collaborators enact new roles as culture machines that untie ideology and practice, pure mathematics and impure humanity, logic and desire" (Finn 47). However, the additional component is that while more substantial data could have prevented this algorithmic failing, it was not necessarily reproducing an existing mislabeling due to cultural prejudice but creating a new one through a failed algorithmic organization. Tarleton Gillespie writes, "when we turn over the provision of knowledge to others, we are left vulnerable to their choices, methods, and subjectivities" (Gillespie). Google's mislabeling highlights the potential perils that lie in trusting our imperfect machines to create meaning. José van Dijck writes, "non-human elements, like algorithms, affect how people act and how they are controlled" (van Dijck 151). While their organizational abilities will grow, errors will nevertheless make mistakes and errors that will be harder to spot but nonetheless continually extant, making it essential to view machine algorithms as other than perfect and objective organizational structures.

CATS!!!!!!!!!!!

 

Platform Week

 The example of YouTube:  

 https://www.omnicoreagency.com/youtube-statistics/ 

https://blog.hootsuite.com/youtube-stats-marketers/ 

Influencer revenues:  

https://www.forbes.com/sites/abrambrown/2022/01/14/the-highest-paid-youtube-stars-mrbeast-jake-paul-and-markiplier-score-massive-paydays/?sh=3a89f4581aa7 

Hate on Platforms:

https://counterhate.com/research/hidden-hate/ 

Gillespie:

https://www.youtube.com/watch?v=O9UifQLRXRw   3 minutes in 

Van Dijck:

The Book: https://www.amazon.com/Platform-Society-Public-Values-Connective/dp/0190889772 

 

https://www.youtube.com/watch?v=g2rVuDQeAeg  (first couple of minutes; then go to 8 min.    13m: hate speech as issue) 

 

Catfish trailer:  https://www.youtube.com/watch?v=BuE98oeL-e0 

 

On ANT:    https://www.youtube.com/watch?v=1iw0BDeYdgI&list=RDLVApmtxIO1GvM&index=5 

Thomas Apperly and Jussi Parrika:

https://www.linkedin.com/in/thomas-apperley-28357628/ 

https://jussiparikka.net/ 

Bogost and Montfort: http://platformstudies.com/ 

Garnet Hertz: http://www.conceptlab.com/ 

The Out Run Game:   https://www.youtube.com/watch?v=TaTB5Q11Dzc 

Nick Srnicek 

https://www.kcl.ac.uk/people/nick-srnicek

https://www.ge.com/digital/iiot-platform 

https://siemens.mindsphere.io/en 

Aubrey Anable 

https://carleton.ca/filmstudies/people/aubrey-anable/ 

The Platform Multiple - Will Core Post 1

This weeks readings on platforms look at the social, cultural, political and technological entanglements of these artifacts. Particularly, these readings problematise the multiplicity of platforms, as the promises of tech corporations, as the definitions of the term, as the actors enrolled in their social production and as the varied and distributed experiences of their use.

To begin with, Van Dijck's highlights how platforms bring human and non-human actors into relation. I appreciated the clear distinction between 'users' and usage to recognise the shaping power of both the social and the technical in creating the eventual use cases of technologies: "Human and technical agents, rather than being hierarchically ordered entities, are mutually intertwined in determining a platform’s usage." While of course being a clear application of ANT, I thought that this may have been strengthened by looking at the affordances of the platforms themselves. Usages may be encouraged or discouraged by platforms materiality, but workarounds exist (such as Angela's fake persona). I also wonder how these usages and perceptions of platforms are temporally situated. Today, we are aware that people may not be as they appear on platforms (thanks, Catfish), even with policies such as Facebook's real name/real id policy.

By looking at the multiple implications of the term, Gillespie notes how corporations are able to deploy the term to safeguard their own political and economic strategy. The term 'platform' benefits certain stakeholders and constructs the visage of corporations as neutral facilitators rather than actors in their own right: "These are efforts not only to sell, convince, persuade, protect, triumph or condemn, but to make claims about what these technologies are and are not, and what should and should not be expected of them." More than a decade later, corporations still attempt to find this balance between claims of neutrality and condemnation of egregious harms or disinformation.   

The multiplicity of platforms was also evident though Srnicek's platform capitalism. I found this piece useful for thinking though platforms primarily as profit generating machines: "The simple wager of the book is that we can learn a lot about major tech companies by taking them to be economic actors within a capitalist mode of production." This piece was particularly useful for thinking though multiple kinds of platforms, the distinctions between which are flattened through the use of the term. This is particularly useful giving the increasing dominance of platforms, beyond just social media interactions, to highlight the multiple actors the platforms can bring into relation. I appreciated how Srnicek problematised what is actually novel about platforms, and moreover, how these claims of novelty can obscure traditional forms of power or well established dynamics between human and non-human actors.

The ambiguity of platforms continued with Anable, who notes the variegated experiences with platforms. "Rather than being discrete objects, platforms, and the ways they connect us technologically and socially to others, are porous, penetrating, and penetrable."  Rather than a homogenising lens on platforms, Anable calls for increased scrutiny as to *who* is affected by platforms and whose lives they claim to improve. For instance, 'lean' labour platforms facilitate the domination of a precarious labour force, often intersecting with racial, class and gender fault lines. Regulation of these spaces cannot come a purely social or technical perspective. Rather than bracketing off the social this is to recognise the role that difference plays in the establishment of platform power.

[Hamsini - Non-core post 2] Virtual Influencers

 

Sharing a recent episode of the Overthink philosophy podcast on Influencers -- which ties into our discussions last week and this week about the relationship between algorithms, platforms, and users. The hosts talk about the case of Lil Miquela, an Instagram influencer who "came out" as virtual, discussing the company that runs the account and the ways it draws on popular (read: both of the people and trending) social movements and evolving gender tropes. They explore to what extent Miquela influences vs. is influenced by algorithms, bringing to mind Gillespie's discussion of calculated publics and entanglement with practice, as well as van Dijck's distinction between users and usage. 

[Ray Kyooyung Ra, Blog #5/15] Just some 19C programmer vs. engineer feud

Sharing a funny image Twitter recommended me the other day, (which is unsettling to experience -- how does social media know I am reading about codes and platforms?) posted by user @ninabegus with the caption: "Ada Lovelace, the first programmer, begging her collaborator Charles Babbage, the inventor of the first general computer, not to mess with her math."

Hilarious, the way Lovelace is reading Babbage to filth: "I wish you were as accurate, & as much to be relied on, as I am myself." The pettiness is aspirational.

[Ray Kyooyung Ra, Core #2/5, Blog #4/15] Platforms and abstractions

For another course I am taking this semester, the class discussed a book titled The Digitally Disposed: Racial Capitalism and the Informatics of Value by Seb Franklin that I highly recommend (the first chapter might be a bit much, but once you get through the introductions, the rest is a breeze). Franklin’s project elucidated the level of abstraction in which digitality functions at, much like racial capitalism that found itself on exploitations of gendered and racialized surplus labor, where the “digitally disposed” are pushed to the margins by de-valuation but at the same time, become vital part of the very system that produces their oppressed status. 

Franklin’s mission to make legible what is abstracted, what is obscured in digitality with its promise of the digitally-liberal subject resonated with the readings this week, particularly for me in bringing together works by Anable, Gilllespie, van Dijck, and Srnicek. As human labor is coagulated to capitalist value in objective product form to be exchanged, and this process of production and exchange is further fetishized as social relationships, (Marx) the abstraction of materiality into fluid data form and mere “surface effects” (Anable) obscures the users from seeing platforms beyond its self-serving representation and their supposed neutral role in facilitating communication. 

Something else that intrigued me with this week’s discussion of ‘platforms’ was that the object of analysis itself had such far-reaching scope of definition. The ‘platform’ that this week’s writers were discussing wasn’t just social media, it wasn’t just located at the level of codes, but rather presented as a complex entanglement of software, hardware, capital, culture, legal structures, and more. Different writers found different points of entry to interrogate the trope of the platform: Anable in the “the thing-ness” behind the bachelor apparatus as well as the reservoir of data beneath interface; Gillespie in etymology; van Djick in the complexly engineered sociality, user agency, and cultural contents of Web 2.0; and Srnicek in the material consequences of exploitative capitalism and its employment of data as resource. 

How far-reaching, then, is the workings of abstraction which obscures the nature of the digital to us users? When we “open the black box” (Apperly, Parikka) and are able to see platforms as not stable, closed entities but as its multiple manifestations, how do we deal with the worms inside? As Hyejoo’s presentation from last week illustrated, what is hidden beneath the surface that promises minimalistic modernity, universal communications, or liberal subject-hood? Platforms studies seem to direct us to look beyond screen-deep representation.

Max Berwald Non-Core Post #2

https://arstechnica.com/information-technology/2022/09/we-interviewed-linux-os-through-an-ai-bot-to-discover-its-secrets/

This is very, very stupid, but speaks well to how eager we still are to disavow human agency and point frantically at code, algorithms or platforms. One interesting thing about the rhetorical framing of the article is the contrast it seems to establish between the old (Linux) and the new (the cutting-edge chat bot that will finally allow Linux to speak for itself). 

"Wouldn't it be nice to know what Linux really thinks about open source...?" 

Max Berwald - Core Post #2

In Platform Capitalism, Srnicek argues that, in the context of the growing affordability of recording, managing and processing enormous amounts of data, the platform is the key capitalist innovation of the 21st century (22–25). He describes their tendency towards monopolization (the product of network effects) as well as their tendency to offer systematized architectures for developers to produce software within. This too has the process of generating ever greater quantities of legible data. It’s very American and appropriate that false optimism of Web 2.0 rhetoric all got crushed by Google and Facebook deciding to just become new spaces for advertising. Like from the perspective of the 1980s, this extremely powerful new communications technology has been invented and people are sure it’s going to somehow generate peace and democracy, but it turns out the biggest internet companies will have reinvented themselves as data-optimized billboards by 2000. 

To Srnicek’s point on 30, it’s perfectly true that not all of our social interactions are captured and monetized by platforms, but the scale of the capture that does go on changes how we behave both on and off platforms. In this sense, platforms are socializing us. This is different from the way the factory floor, the subway train, or even the movie theater socialized people in the past, because those were all places for certain kinds of social interaction, whereas email, SMS, Twitter, Slack, and the full gamut of digital communications platforms subsume increasingly broad swathes of human “social” activity. You leave the factory floor, the subway train and the movie theater, but you always have your phone ready to hand. You have to use it to work, and also to get ahold of your mom.

I thought the Gillespie was much more incisive in terms of what is really new about platforms (relative to legacy structures for disseminating large volumes of media). Gillespie centers his analysis with the etymology and history of the word “platform,” and then quickly moves into a discussion of how the largest internet companies cannily use different definitions of the word to appeal to different stakeholders, from users to investors to politicians. For prospective users and content creators, YouTube is a platform in the sense of being radically open and level playing field where anyone can share video content with the world. For would be regulators, it is a platform in the sense of being only a platform: what media appear on any given user’s screen is not something YouTube can be held accountable for. Of course, as Gillespie notes, platforms have to be built, and what content appears on any given user’s screen is the result of decisions made by developers at YouTube (even if a mountain of algorithms mediates those decisions), as well as a result of their content policies (359–60). 

The Apperley and Parikka article on “Platform Studies’ Epistemic Threshold” gets into possibilities for shared concern, methodology and research between platform studies and media archaeology. While Gillespie and, to an extent, Srnicek are concerned with tracking the positions of various platform types with regard to culture and the state in the contemporary moment, Apperley and Parikka are, in media archaeological fashion, arguing for more concerted study of what’s “inside the black box of the platform.” (362) That is to say, moving beyond what is on the screen, even if what is on the screen is recognized as important and included alongside study of the platform itself. They also make a call for a greater attention to user practices and developer practices, creativity outside of the model of a single, agential genius, etc. Writing from 2018, Anable notes that platform studies (1) is already devoted to looking inside the box (probing the materiality of platforms) but that (2) this aligns platform studies with the longer STS trajectory. This doesn’t seem contradictory to me, since I think Parikka would agree that media archaeology is already broadly aligned with and drawing from STS, but Anable also points out that the very metaphor of hardware ensconced in a black box, a deep “layer” of hidden meaning, has been destabilized by feminist scholarship. Using the example of Facebook’s construction of gender, Anable points out that there is no layer of the platform that does not exist in extension of, tension with, negotiation of larger cultural forces.   

Core Post #2 - Mahnoor

This week, though I’ll touch on all of the readings, I want to start with the epistemological (and methodological) arguments made by Parikka and Apperley. I am specifically interested in their claim that “it is necessary to have a more critical appreciation of ‘failure’”(359), emphasizing that it is important to analyze platforms that have failed in one way or another in addition to those which have succeeded. This emphasis is tied to their goal of using media archaeology (as well as media anarchaeology) to form “an explicitly articulated critical methodology” to study platforms (351). Media anarchaeology does not look “to the past or future” but seeks out multiple paths and possibilities, “evoking the speculative, alternative, minor, and even imaginary perspectives of media history” (360). This notion of anarchaeology, as well as Parikka and Apperly’s focus on failure, echo in aspects of theorist and visual artist Svetlana Boym’s articulation of “Off-Modern” thinking. I think bringing Boym into conversation with this week’s texts could be fruitful. Boym argues that a form of “lateral” looking across time, genre, and discipline is necessary to understand a world of shifting paradigms, cultural patterns, and new technologies:

“We need to interrupt the new cultural myths that naturalize the homepage and Facebook and that uncannily remind us of the dystopias of the early twentieth century. [...] A new pedagogy is needed to embarrass the digital totality. Off-moderns insist on thinking with error, play, ambiguity, human memory, crisscrossing digital and public space—just for a rainy day. Off-modern new media combines new digital platforms as well as critical reflection on the new forms of digital mediation that have been domesticated to the point of destroying our intimacies. Off-modern new media is about networking across different genres and mediums, reawakening senses and refining sensibilities, exploring diagonal and zigzag thinking and working on a new public architecture.” (Boym 23)

There is also something in Boym’s “lateral” looking that functions similarly to Gillespie’s crafting of a definitional constellation in order to both dissect individual meanings of the word "platform" and to explicate the ways in which these meanings are linked. Like Gillespie, Srnicek too analyzes the platform in its multiple forms. He does so within the category of “business model” (25). In order to grasp what roles platforms – as entities, corporations, websites – and "platforms" – as discursive and rhetorical tools – play in society, it is important to account and allow for ambiguity, multiplicity, and interchangeability, to define terms and then be okay with muddling those definitions in accordance with new circumstances. It is important to look beyond single definitions or ways of looking limited to one vector, to either “past or future”. 

The Parrika and Apperley reading, as well as the Boym text, tie into Anable’s advocacy for an approach to platform studies that recognizes platforms as “porous, queerly promiscuous, and radically leaky” (139). This porosity is also connected to the blurred boundaries between different conceptions of “the platform” in Gillespie’s analysis, though Anable perhaps articulates a more radical iteration of these boundaries. Van Dijck too speaks about the ways in which the relationship to technology is not a straightforward one: “Technology shapes sociality as much as sociality shapes technology”(146). She adds that this is a “process in which humans and machines have their own distinctive but mutually shaping roles”(146). I think using the word “distinctive” is interesting. As the boundaries between platforms are leaky and porous – as argued in Anable and implied in Gillespie’s intersecting definitional permutations of platform – and as those platforms themselves are subject to multiple creative vectors of analysis – as argued by Parikka – are the roles that humans and platforms play in relation to one another truly distinctive? That is, are the roles themselves more rigidly defined and delimited than the spaces in which these roles are meant to play out? Anable argues that imagining platforms as sealed black boxes leads to imagining “subjectivity, agency, race, and sexuality” as similarly sealed categories (137), which is why porosity becomes an important characteristic to assign to platforms and platform studies. Would imagining the roles of humans and machines as similarly porous help or hinder the scholarly confrontation of platform power dynamics related to race, gender, and sexuality? Though opening up the categories of digital platforms to ambiguity and leakiness can enable challenging structural power, reducing the "distinctiveness" between human and machine roles feels to me like verging into a realm of dystopic imaginings, perhaps exacerbating existing power struggles.

Boym, Svetlana. The Off-Modern. Bloomsbury Academic, 2017.

Platform studies and its methods [Rohan - core post #2]

This week’s readings featured different methodologies and epistemologies in pursuit of refining the emergent field of “platform studies”. Overall, I found many of the readings compelling and urgent because they demonstrate analytic strength without fetishizing either users or interfaces.

Anable builds on Apperly & Parikka’s critique that “platform studies” produces uniformity by prescribing a feminist intervention: tackling the presumed discreteness of platforms. For example, she draws on Chun’s and Friedland’s provocative assessments of “promiscuity” and “sluttiness” in how platforms treat data to illustrate how marketing rhetoric (e.g., “sharing economy”) produced by companies can be dangerous because it can obscure their sociocultural implications, as Gillespie discusses in detail. Thus, I agree with Anable, and by extension Apperly & Parikka and Gillespie, that platform studies’ material-discursive methods risk reinforcing a presentist stability by presupposing the object of study and relying on readymade empirical sites, such as interfaces and marketing material.

I found it peculiar, then, that van Dijck was not cited by those later works, because I found her use of actor-network theory compelling for analyzing platforms as techno-socio-cultural artifacts. She argues—with a more specific empirical focus than Anable or Apperly & Parikka, focusing on social media platforms—that the engineering of connectivity illustrates how platforms are not just intermediaries but rather actors that mediate sociocultural dynamics. (Perhaps as a response, Anable cites Nooney who seems to describe this approach as “simply rearranging actor-network deck chairs, envisioning histories and theories without corporeal or discursive bodies, histories or theories lost in their own love for the mechanism’s indifference to the body”; p. 136). However, different analysts apply ANT in different ways, and I thought van Dijck’s approach was fairly grounded.

Finally, I was most excited by Srnicek’s turn to the economics of platforms. While his particular approach is certainly subject to Anable’s critiques, I also found that his general conceptualization of platforms as economic actors lays bare the sociocultural stakes—for example, implications for labor and work. What I found most compelling is his typology of platforms—a level of both comprehensiveness and specificity that I found lacking in the other texts—that demonstrate the central role of data. This zooms out from the all too common focus on social media networks to include other platforms such as Amazon and GE (while excluding Apple as a consumer products company). This is an important intervention because a narrow discursive focus on Facebook and Google forecloses analytic opportunities by excluding empirical sites that don’t feature prominent interfaces and users—such as Amazon Web Services or non-tech-industry platforms that Srnicek discusses. Thus, I find platform capitalism compelling not necessarily for its methodological intervention in platform studies, but rather for its epistemic consequences for what constitutes a platform in the first place.

Creativity, Play, and Fissuring the Blackbox through Media Archaeology (just a regular post), (Marisol Vasquez Non-Core Post 1 / 10)

At first, in Thomas Apperley and Jussi Parikka’s “Platform Studies’ Epistemic Threshhold,” the argument towards applying a media archaeological approach to platform studies did not become clear for me until I breached its end when the authors discussed Corey Arcangel’s piece Super Mario Clouds (363). I have been familiar with this artist previously, but Apperley and Parikka’s pointing towards the work’s significance as an artistic practice “inspired by media archaeology” was highly effective, as I had only encountered discussions on his work as “Post-Internet Art,” a nondescript attribution once compared to Apperley and Parikka’s interpretation. Mostly, I felt the insight and clarity upon interpreting these media archaeological inspired artistic practices “illustrate this drive to search for the seams and the cracks that contradict the orderliness of the black box and test the platform’s limits” (363). 

Moreover, Apperley and Parikka’s work also call into question the nature of “creativity” and “play” as they figure throughout dominant methodological interpretations of “platform studies.” Creativity also figures in Audrey Anable’s writing as well, in which platforms become the "'underlying computing systems' of culture and creativity" (136). I was wondering if it was possible in class to parse out and unpack a bit more how each author approaches the notion of creativity and play with platforms, as it has not only recurred in this week but also in the recommended Parikka reading from a couple weeks ago.  

https://coryarcangel.com/

Julia Rose Camus - Additional Post 2

Thinking back to our class discussions surrounding Code/Software/Algorithms, I've been trying to dig up this project I encountered a few years back based on Gayatri Spivak's seminal essay: Can The Subaltern Speak? which feels directly in conversation with Allucquère Rosanne Stone's “Will the Real Body Please Stand Up?"

This digital art piece designed and created by Behnaz Farahi engages with the politics of the veil in Iran, by fully automating a set of veil-like masks that have functional electronic eyes that communicate with each other in order to create their own language based on their interaction with each other routed through code. 

https://behnazfarahi.com/can-the-subaltern-speak/

Julia Rose Camus - Additional Post 1

Thinking broadly through the idea of algorithms and platforms, I frequently return to my primary object of study, TikTok. I often concern myself with the ways in which censorship operate on platforms, which Srniceck alludes to in Platform Capitalism, and I wanted to share a community-created list of words that are throttled on TikTok, which allows us to draw certain parallels between the ways in which different identifies are moderated on this particular platform: 

https://docs.google.com/document/u/0/d/116Brr96uD08PX0MtLVIfgca1VJGOVX35XCpzwC2DD_Q/mobilebasic

"Data trusts" - Blog 2/10 (Hyejoo)

I've seen talks of "data trusts" emerging online, which I find somewhat relevant to Srnicek's last few pages on keeping platforms in check. 

Here's a definition according to the Ada Lovelace Institute: "Data trusts create a vehicle for individuals to state their aspirations for data use and mandate a trustee to pursue these aspirations... data trusts might work better in contexts where individuals and groups wish to define the terms of data use by creating a new institution (a trust) to steward data on their behalf, by representing them in negotiations about data use."

And here's a brief MIT Technology Review article on data trusts more broadly: https://www.technologyreview.com/2021/02/24/1017801/data-trust-cybersecurity-big-tech-privacy/ 

But if the raw material of our current state of capitalism is data, what will a data trust ultimately be if not just another mode of managing capital, especially if they are private institutions? Like any other legal trust, some data trusts, no matter how collective, would be more valuable than others, both by quantity and the information the data provide. So I would assume these "more valuable" trusts to be better managed and represented than others, just like legal counsel. Who assigns the trustees? Who are the beneficiaries? Who qualifies to be a beneficiary? 

Just as legal counsel is a privilege, I personally find this idea of data trusts to be a noble attempt, but perhaps ultimately exclusive as well. And while data trusts are envisioned after unions and the idea of ethical data stewardship––data trusts "could allow us to exercise our rights as producers of data in much the same way trade unions allow workers to exercise their rights," says the MIT Technology Review––we have to remember that unions have long been quelled in many parts of the world already. Not to be too pessimistic, but wouldn't this inevitably be the same fate for any noble idea of public or private data trusts?

School District Bans "Girls Who Code" books - Pratik

It is no surprise to anyone that the U.S. and many other countries have emphasized a STEM-oriented educational system, particularly in the past few decades. With that have come a lot of complicated narratives around humanities, arts, and social science education. Many educational programs in the arts and humanities have faced substantial budget cuts, for that STEM emphasis.

Regardless of how emphasized and well-resourced/funded programs in engineering/computer science have been, the gender disparity among these fields is still astronomical (still an understatement). I completed my undergraduate degree in Informatics (a CS-adjacent field) and I still remember being in programming classes of 200+ people with only a dozen or so individuals who identified as women or non-binary. Obviously, when these students go into the workforce, this disparity is exacerbated. While there may be an myth of the idea of access when it comes to education, these social, political, and economic complexities further the notion of an embedded patriarchial layer into software, technologies, and the digital world at large. 

 https://www.theguardian.com/us-news/2022/sep/26/pennsylvania-book-ban-girls-who-code

Joy Buolamwini - "AI, Ain't I A Woman?"

The poetry incorporated into the Transborder Immigrant Tool we looked at on Thursday reminded me of Joy Buolamwini's work as a "Poet of Code." She does interesting and urgent research on racial biases embedded in AI facial recognition technology, often communicating her findings in creative modes of expression. The poem below demonstrates the way this tech often fails Black women by misgendering them or mischaracterizing their identities. 

"Face by face the answers seem uncertain

Young and old, proud icons are dismissed

Can machines ever see my queens as I view them?

Can machines ever see our grandmothers as we knew them?"

Here are a few additional links if you're interested in exploring more of her work: 

Her personal website: https://poetofcode.com/?home 

The Algorithmic Justice League, which she founded in order to combat discrimination in AI tech: https://www.ajl.org/

Video essay about platforms (Sebastian)

https://www.youtube.com/watch?v=r3snVCRo_bI 

    In light of the readings on “Platform,” I thought it might be interesting to share this video essay, “VidMe or Why Platforms Aren’t Your Friends,” from Dan Olson. In the essay, Olson reflects on his own experiences as a YouTube “content creator” to explore the tensions that invariably arise between creators and platforms like YouTube. He ultimately concludes that VidMe – at the time, an aspiring YouTube competitor – is destined to fail because it does not address the actual complaints about YouTube that prospective VidMe users and content creators have. Indeed, VidMe did officially close mere months after Olson posted this essay in 2017. 

    I find Olson’s remarks about YouTube’s shortcomings especially compelling in relation to Tarleton Gillespie’s article, “The Politics of ‘Platforms.’” Gillespie is interested in the ideological work done by the term “platform” when it is mobilized by companies like YouTube and its owner, Google. For instance, he explores the architectural connotations of the word “platform,” arguing that it implies that a site like YouTube is an “open-armed, egalitarian facilitation of expression, not an elitist gatekeeper with normative and technical restrictions” (Gillespie 352). YouTube relies extensively on this connotation when it attempts to justify its supposed neutrality vis-à-vis the content it hosts. But, as Gillespie observes, this is a fiction. He writes, “YouTube and Google have pursued a specific business model that, while it does not force them to emulate the traditional gatekeeper role of broadcasters and publishers, nevertheless does have consequences for what they host, how they present it, and what they need from it” (Gillespie 358). YouTube favors the terminology of the “platform” precisely because it effectively disguises its incentives and penchant for intervention.

    Olson’s essay acknowledges these interventions but does not call for a video hosting service that resurrects the ideal of neutrality. Instead, he criticizes the lack of transparency surrounding these interventions and the subsequent injustices they produce. He demands that YouTube do a better job of moderating comments and equitably applying community standards so as to combat the site’s current toxicity. In other words, Olson wants YouTube to drop the veneer of neutrality implied by the term “platform” and take a more active – and, arguably, more politically considerate – role in shaping the culture of the site. Although certainly not a content creator myself, I suspect that Olson’s arguments probably make a great deal of sense for that community. Per his critique of VidMe’s lack of moderation, I have no doubt that a truly “neutral” platform would quickly become a cesspool of far-right bigotry. Regardless, I can’t help but wonder if the ideal of neutrality is functionally impossible in the way that platforms are currently conceived. Is it possible to build a platform that is neutral in the most optimistic/idealistic sense of that word? Or, in keeping with Gillespie, will the very concept of a “platform” always hide interventions? Moreover, is the notion of neutrality that the term “platform” evokes truly worth aspiring to in the first place?

Links for Week 5: Algorithms

 Short Doc on Algorithms:
https://www.youtube.com/watch?v=NFF_wj5jmiQ 

T. Gillespie
https://www.microsoft.com/en-us/research/people/tarleton/ 
https://www.youtube.com/watch?v=Oty60JVYis8   

Ed Finn:
https://edfinn.net/  
https://www.youtube.com/watch?v=28JfaslqABY&t=90s

Taina Bucher: 
http://tainabucher.com/

Juan De Lara

https://www.juandelara.com/ 

https://www.ucpress.edu/book.php?isbn=9780520297395 

Transborder Immigrant Tool:  https://anthology.rhizome.org/transborder-immigrant-tool 

https://vimeo.com/6109723 

https://www.arte-util.org/projects/transborder-immigrant-tool/

Safiya Noble

https://safiyaunoble.com/   

Re:Compute at Notre Dame and Online, 9/23

 You might want to check out this upcoming event asking if we can re:compute our computational world.

Non-Core Blog Post #1

    Just watched Kimi (2022) for another class. The film offers an ambivalent commentary on virtual assistant and home surveillance technology, valorizing the “human element” in the operation of algorithmic machine intelligence as redemptive. The film's story, which explores the pervasive digital surveillance of private, corporate and public spaces, is set in motion Blow Up (1966) style, when our hero overhears a murder in recordings from a virtual assistant product. Angela Childs works for Amygdala, the corporation behind the product, and her job is to train language processing algorithms to interpret questions that they failed to properly account for in the first place. Her job involves moving through an endless stream of clipped recordings of Kimi, the titular product, failing to work. This intervention at the site of error leads her to uncover a violent crime. Her responsible attempts to pursue justice, via the FBI, are thwarted by the company she works for, which is eager to cover up the crime to protect its IPO. On the one hand, this locates the algorithm in a socio-technical system similar to that in the de Lara and the Gillespie. On the other, the film produces the problem of algorithmic surveillance as one to be solved by proper human oversight (obscuring the development of the product itself within power relations and the production of certain bodies– say, racialized bodies– as threats).

    The decision to make the drama one of seeking out law enforcement (the FBI) in order to expose the guilt and negligence of a tech company is also interesting, given the penchant of the operators of adjacent products (like Amazon Ring) to proactively share data with law enforcement. The film also ends with the hero’s removal of Kimi from her own home, despite the fact that her own responsible stewardship of this technology has just saved the day.

Border Cams - Tania

Juan De Lara's essay packed a punch...not least because while it purports to study only two specific border technologies, it gestures to a whole sprawling range of others throughout. His passing reference to Camilla Fojas' Border Optics (via her concept of "borderveillant media) snagged me. In place of formed thoughts, here are some live border cams compiled by Border Report, a news outlet devoted to the US-Mexico border. 

No longer linked to the explicit surveillance functions such cameras once had (De Lara, 158), it's unclear to me what work these public-facing border cams are supposed to now do.

How AI sees LA - Will Orr

AI generated art has been a bit of a re-occuring theme within class. I just want to share this LA times piece that I came across that uses depictions of LA within literature, poetry and mythology as prompts for Midjourney creations.

Some of the descriptions are really beautiful, and I find the conceptual distance between the literary descriptions and the images fascinating. Despite knowing how these systems work and why the images look the way they do, I still feel this sense of enchantment watching the images being rendered before my eyes.
 

https://www.latimes.com/projects/los-angeles-poetry-midjourney-artifical-intelligence-literature/

Core Post #1 - Pratik Nyaupane

This week, we read a collection of texts that outlined the relationship between algorithms and power. Tania Bucher summed it up well, "Algorithms do not work on their own but need to be understood as part of a much wider network of relations and practices" (p.20).

Tarleton Gillespie did an excellent job of helping us understand why algorithms are significant in terms of publics, their epistemology, and algorithmic ubiquity. Algorithms are not merely commands, but they are mathematical procedures that "produce and certify knowledge" (p. 2). We can see how in the age of digital misinformation and disinformation, this can lead to dangerous outcomes. Sarah Noble's work on search algorithms solidifies this idea. Stereotypes, biases, and discriminative norms are certified and reproduced as knowledge. Search engines like Google maintain a divine-like trust from the public that often believes that Google or the internet can tell no lies, as the computer must know everything. The opaqueness of the black box allows people to have this sort of blind trust. This reminded me of Guillermo Gómez-Peña's article on The Virtual Barrio, where they actually did not want to know how this all works. One could draw parallels between this and some followers or religious and spiritual communities, in that it is best not to question the inner workings because it is too complex and why ruin the mystery or magic of it all.

Gillespie also points out that we often fail to give credit to the complexity of these algorithms. As users, we refer to interfaces as algorithms, but they go much beyond that. We only see google searches, Facebook feeds, and TikTok feeds as an algorithm, but they are multiple algorithms at work with constant changes that are not always noticeable visually/through UX.

With my fascination in surveillance technologies, I thoroughly enjoyed Juan de Lara's Race, "Algorithms, and the Work of Border Enforcement." De Lara's piece on algorithms and border enforcement was an excellent reminder that the digitization and datafication of traditional colonial infrastructure is a frightening and violent process. Similarly to scholars like Lisa Nakamura, de Lara contextualizes technological tools within labor, race, and coloniality. In a refreshing way, he uses Richard Edward's theory that "technology can only be fully understood by taking into account the role it plays in specific societal processes" (p. 152).

De Lara does a great job reminding us also that while technology has propelled discourses and critical analyses regarding surveillance, it is integral to understand that the logics of anti-Blackness, anti-Indigenousness, xenophobia, and racism are what truly maintain and uphold surveillance through technological and digital means.

Marisol Vasquez Core Response 2 / 5

"From the beginning, then, algorithms have encoded a particular kind of abstraction, the abstraction of the desire for an answer" (Finn 25). 

I open with this quote from Finn's "What is an Algorithm" to raise a question regarding data collection and the archive. First, to unpack Finn's statement, I want to examine what is implicated by the desire for an answer. As Finn claims, desire is encoded into a pursuit of effectiveness that obscures within computational regimes. (Finn 26) If we were to define this "desire" in the algorithm, according to Finn and the evidence the author lays forth, it might have its origins in what N. Katherine Hayles refers to as the 'hard claim' for computationalism, in which the cultural processes "are themselves computational machines that can be mathematically duplicated" (22). As Finn elegantly points to, algorithms might be built, produced, and constructed around this desire for accuracy, which manifests as simulations of “election outcomes,” “future price stocks,” or—as exemplified in Juan De Lara’s “Race, Algorithms, and the Work of Border Enforcement” and Sofiya Umoja Noble’s Algorithms of Oppression—a desire for accuracy can also figure through the production and reproduction of racialized bodies. 

As the production and reproduction of racialized bodies implicates, this desire for accuracy is laced with ideological drawbacks, such as the reproduction of the US racial state, as De Lara elucidates. Computational processes—their seductive allure of accuracy and effectiveness—obscure the consequences of blinded algorithmic production. As Finn claims, “universal computation” and computational models for cultural problems lay forth serious risks and downfalls in which computational models can “compress or shorthand reality” (23). This ostensible eclipse of “reality” might be considered in their national contexts, as exemplified by De Lara specifically, who dismantles the classification of a ‘risky body’ as it tethers to an imaginary of the US racial state. As De Lara exemplifies, the case of the U.S. racial state and the genealogies of America’s nativist politics (154) or epistemologies of anti-immigration (154) constitute the desire embedded within the production of the algorithm and its accompanying border control technologies. I found it curious how academic research and Silicon Valley partook in developing earlier technologies of the virtual border, which led me to question who is ultimately the arbiter of the production of desire within algorithms? This is a similar question to Stone’s essay and her case study of VR engineers. However, with algorithmic production, De Lara’s and Noble’s work seeks to dismantle the ideological underpinnings that inform such a reproduction of desire through the computation of a racialized body.   

In the work of cultural studies, however, I would also like to ‘imagine otherwise,’ while De Lara and Noble deployed race to disassemble the power imbalances and racial hierarchy assumed within computational processes, what other forms of cultural production via computation have people produced that seek to imagine otherwise? Coming from a film studies background, I raise this question frequently, and I also believe it ties into Kara Keeling’s work and the concept of “Queer OS” to queer or reshape computation’s dominant logic of desire, and the reproduction of race, gender, class, citizenship, and ability within a nation-state. To offer another concluding point, this work led me to think about the colonial archive and the racial taxonomies produced upon “the emergence of European liberalism, settler colonialism in the Americas, the transatlantic African slave trade, and the East Indies and China trades in the late eighteenth and early nineteenth centuries” (Lowe, 1). In other words, I point to the colonial archive to think about how computation, algorithms, data collection, and archive theory hearken back to and index the construction of racial taxonomies and share a relation under the dominant logic of ‘Western science’ that seem to suffuse through many of these critiques on algorithmic production. 

Week 4 - "Negative weighting" and "shadow bodies." - Blog 1/10 (Hyejoo)

I recently learned of another algorithmic technique with AI art called "negative weighting." Essentially this finds the opposite of an input. For example, you input "dog" and the AI will find everything it understands to be the opposite of a dog. 

An AI illustrator (who goes by the moniker "Supercomposite"), using negative weighting, came across a grotesque, creepy, ghostly figure that emerged as the output of a string of certain prompts. The illustrator named it "Loab." Here's the article on it by Max Read (disclaimer: potentially scary/gory pics!––you can see Supercomposite's whole Twitter thread, with even scarier images, as well).

"Loab" reminded me of the concept of "shadow bodies" (mentioned in Gillespie). Even though shadow bodies refer to an actual human user, it's kind of like the negative weighting of a user: "these shadow bodies persist and proliferate through information systems..." They remain unseen in the deep ocean of machine learning datasets. 

This was an alluring, intriguing concept for me. Though, the macabre fantasy of "Loab," along with our dystopian imaginations of AI overpowering humans, etc. may all be the flip side of the same coin as fetishizing computers as all powerful, occupying a "higher plane of thought" (Finn 24) etc. As Max Read writes: "Loab's not a ghost––it's an embedding somewhere in the multi-dimensional latent space, strongly associated with gore, darkness, and dread." It's just strong associations... but it sparks our fantasies nonetheless.

Julia Rose Camus - Core Response 3

On the topic of Queer OS, I feel there is further I’d like to expand upon. As we have mentioned in class, a number of graduate students have produced a response to Keeling’s work in the form of QueerOS: A User’s Manual penned by Fiona Barnett, Zach Blas, Micha Cárdenas, Jacob Gaboury, Jessica Marie Johnson, and Margaret Rhee. In this piece, these theorists expand beyond the speculative nature of Keeling’s work to consider the practical applications of a Queer OS. They posit: “A more productive interface would be expansive, proliferating the relationality allowed for by the inter-face, its inter-activity, its nature as that which is between or among, that which binds together, mutually or reciprocally. Far from the extractive impulse of contemporary systems that mine and surveil, it is an act of consent and mutual transformation. It is that which allows us to enter one another and be in-formed—that is, to be shaped from within.”

As someone working in academia, I do find it incredibly helpful when speculative works are expanded upon in concrete thinking, and this has fueled much of my own thinking surrounding my dissertation. What comes after critique? is the key question at play. In this piece, Barnett et al. propose some of the ways in which we can practically understand the radical potential of a Queer OS, wherein hegemonic structures of interactives, dialogue, and interface are disrupted. This leaves us to question what this platform might actually look in practical execution. How does moderation affect this modality? Does this redefine the concept of a digital citizenship overall? Can a platform like this exist on the current Internet access that we know, or must we also radically tear down and rebuild the ways in which servers operate?