Pratik Nyaupane core post #4

"The sign of a good CCM worker is invisibility-- a worker who leaves no trace" (p .2).

Sarah Roberts emphasizes the invisibility of low-wage outsourced workers who singlehandedly keep so many of these platforms afloat. As I read this piece, I thought about automation and objectivity. In cases of policing, teaching, sports, or literally anything else, we see artificial intelligence and machine learning tools "attempt" to create objective truth. This utopian dream is evidently not a reality, and in order for companies to moderate content with outsourced human labor, workers of color from the Global South have been the victims of this system. 

I think we tend to think of content either as good or bad, but as Roberts' text alludes to, it’s a mess. The examples of content that is created for comedy are simply complicated. And while some content may be easily identified as hate speech or harmful activity, oftentimes there are cultural and social contexts where it matters. For example, words that are slurs, but used prevalently by the group that the slur targets. Additionally, words that are deemed insensitive in one language or country, but used in different regions and languages with no malicious intent. Therefore, a tool cannot just ban certain words, because other factors matter. This makes the content moderator's job only more complicated and stressful.

D'Ignazio and Klein touch upon similar notions of invisibility and labor that Roberts wrote about but also the role of gender, which we were introduced to with Lisa Nakamura's piece earlier this semester on Indigenous women. "In our capitalist society, we tend to value the work we can see" (p. 178) and this idea sadly holds true when Elon Musk is given so much credit for electric vehicles, Bill Gates for computers, and Steve Jobs for computers and iPhones. The material labor, the intellectual process, the coding work, and hundreds of other roles that are required for the development of these technologies is merely forgotten because in this capitalist society we also love to attribute accolades and accomplishments to simply one person, one name, one face. Often times artists don't write their own songs or produce their own music, and while there is a level of extraordinary vocal talent, so much of the required labor in producing a record is forgotten and just associated with the big name of the star. This holds true for almost any industry. 

While many of the issues addressed in this week's texts covered laborers in relation to digital technology, I think they continue similar concerns around labor that we have seen prior to the introduction of digital mediums. I want to call attention to how digital technologies have brought forth and affectec the gig economy, which affects such a significant portion of the population. The gig economy has essentially allowed companies to formalize themselves as a broker where they are not necessarily providing any service or product, but simply connecting consumers to providers. To a large portion of the labor force, these notions of flexibility, independence, and freedom, gave an advantage to individuals who were not able to or did not want to follow traditional practices of labor, such as the 9-5 office job.  However, for the functionality of the gig economy, digital tools such as mobile applications have been pivotal. Companies like doordash, instacart, lyft, uber, and others rely on a model of surveillance that is the application itself to exploit these marginalized laborers. Within this capitalist economy, and increasingly materialistic, and the datafied world, I believe we will see that more and more companies rely on gig workers because it can seem attractive to both workers and employers. That being said, the labor exploited on the basis of datafied performance tracking will increase and be detrimental to the rights and bodies of gig workers.