Troll Food Presents:
“All This Shit is Ours”, Crypto-labor,
and YouTube view currency
Crypto-labor — labor that is both ubiquitous and hidden by the massive filtration schemes controlling access and content in network environments such as YouTube.
“All this Shit is Ours”, a curated video program, employs a simple proprietary algorithm to boost the visibility of unseen, transgressive and excommunicated knowledge communities. These videos are simultaneously the site of unwillingly obscured, concealed work, as well as work that withdraws, hides and camouflages itself.
Crypto-labor is not just a common form of labor on the internet; it also embodies complex relations to labor that are pervasive in late capital. One of the profound elements of crypto-labor is the labor of the search. Google eats our questions and sells its digestion to advertisers where the contents can be parsed and user interests adequately indexed. YouTube’s data scientists consider the view as the base unit of currency in this system. Value and visibility are treated as the same thing. Although the formula for what constitutes a view is a secret, more than just view count goes into search rank results. The individual parameters are called signals.
YouTube rigorously protects these signals for fear of their potential to be gamed. To do this, it posits an ideal sincere viewer who is actually looking for things. The search rank algorithm runs at over one million lines of code. A better image of it is complex weighted counting. It determines which search results and recommendations show after a query is entered and undergoes 50–100 modifications a year over staggered launch schedules of analysis and evaluation. The algorithm is constantly trying to determine which videos will satisfy user queries but also allows for newer, less viewed results to show as well.
If the system were only ranked by view counts, there would be no way to inject novelty into the system. Organic search results are determined by signals that include view-count, previous search history, watch time, subscribers, likes, comments, location in competitive markets, reputability of link hosting site, use of annotations, thumbnails etc. Value on YouTube is fundamentally linked to this search function. Searching erases the discontinuity between the machinery of user subjectivity and the machinery that retrieves and curates, opening a dynamic circuit where inhuman algorithmic logics mesh and alloy to human desires.
Value in the digital economy also resides in relation to traditional labor, instruments of production, and instruments of communication. As a site of radical disintermediation, the internet is replete with the ghosts of dead middle men — travel agents, bank tellers, librarians, translators . Their corpses have been exhumed and made available as costumes for ASMR creators, digital fetish archivists and synthetic intelligences.
The filtration schemes that structure YouTube aim to crystallize the planetary feedback system — rather than incubating the seeds of disruptive planets. They tend to reinforce the borders of familiar image territories, constantly re-constructing the perceptual regime that lubricates, maintains, and mends the emotional machinery of laborers as they burn psychological resources in the struggle to maintain parity with the planetary economy.
In response to the monopoly on algorithmic visibility, communities with fragile identity formations have developed various strategies to sustain their images. Deviants, contraband traffickers, and counterfeiters tap into existing veins of attention and siphon them into parallel channels. These workers occupy the ghost zone of the database, using mainstream codes to pass internal message, accelerate transgressive behavior and innovate solutions to mine planetary infrastructure.
Each video in the Crypto-labor playlist is under 301 views. 301 views is the baseline for YouTube’s video authenticity verification. Before 301 views it cannot be said with any confidence if the video represents organic activity or automated activities such as view count inflators, malware, or the reverse engineering of YouTube’s algorithms by collective synthetic intelligences.
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