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CHAPTER 2. RELATED WORK 5 ating worker-employer relationship [36, 46]. Algorithms manage work, decide on pay, and effectively redistribute uncertainty and risks from employers to workers with no means for re- course. In a media environment such as YouTube, where the boundaries between commerce, content and information are currently being drawn, content creators who situate between video consumers and video distributors, have rather limited potential to “wrest power from the few”, let alone to “change the way the world changes” [78]. Most of the YouTubers are invisible workers with little negotiation power in the technically mediated worker-employer relationship. 2.3 Algorithmic Folk theories and Imaginaries Studies of folk theories have looked into how users of social media form theories of the workings of the algorithms and how users’ folk theories of algorithms frame their behaviors [16, 24, 12]. Much of the research discuss folk theory formation process, which starts from information foraging, to sense-making (including social sense-making) to formulation of folk theories. Folk theories guide users’ behaviors from self-presentation to counteract and the theories are often in flux, where users iteratively form theories using the various information input they receive [24]. Bucher explores folk theories via the algorithmic imaginaries that are “the way in which people imagine, perceive and experience algorithms and what these imaginations make possible.” Algorithmic imaginaries not only influence users’ subsequent behaviors, but also affect their moods and feelings. [12] 2.4 Algorithm as culture A subset of research on algorithmic folk theories centers around cultural meanings and values of the algorithm. Seaver argues that algorithm should be considered as culture and not just as an object in culture. This angle views the algorithm as a mix of human decisions and mysterious inner working of the code [64]. With much research that focuses on the algorithmic folk theories crafted by people and the power that algorithms hold on people, little investigation has gone into personification to explain the relationship between human and algorithm despite algorithms’ constant and intimate roles in our lives. Willson briefly touches on the anthropomorphizing language in discussions of algorithms. She also highlights the lack of an appropriate language to describe complex processes of algorithmic decisions and human interactions with algorithms [82]. 2.5 Design as provocation The methodology of our research relies heavily on a body of previous work that leverages design not to simply provide a solution, but to provoke critical thinking of a socio-technical issue [25, 17, 86, 41, 85]. Wong and Mulligan outline the four purposes of design (in thePDF Image | How Content Creators Craft Algorithmic Personas and Perceive the Algorithm that Dictates their Work
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