{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","title":"If...Then Algorithmic Power and Politics","author":null,"edition":null,"publisher":null,"year":null,"isbn":"2017054909","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","id":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","uuid":"1d3bd28e-c1ba-4af2-8580-60b32ef26053","title":"If...Then Algorithmic Power and Politics","normalized_title":"ifthenalgorithmicpowerandpolitics","author":null,"edition":null,"publisher":null,"year":null,"isbn":"2017054909","isbns":["2017054909","9780190493042","9780190493059"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":211,"navigation_url":"https://workshop.closeclaw.top/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053","title_url":"https://workshop.closeclaw.top/ai/title/If...Then%20Algorithmic%20Power%20and%20Politics","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/1d3bd28e-c1ba-4af2-8580-60b32ef26053","page_url":"https://workshop.closeclaw.top/api/ai/books/1d3bd28e-c1ba-4af2-8580-60b32ef26053/page","search_url":"https://workshop.closeclaw.top/api/ai/books/1d3bd28e-c1ba-4af2-8580-60b32ef26053/search"},"page":{"printed_page":96,"pdf_page":106,"physical_index":106,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"e9ed15dd85359c6c6c369fd25280bc9f5e05c5df2b05ac4dd8e6f79784146ac9"},"chapter":"IF...THEN","content":"More than simply describing the strange feelings of media users, these scenes describe some of the many mundane moments in which people variously encounter the algorithmic realities and principles underlying contemporary media platforms. For 21-year-old Michael, the Facebook algorithm has become an important part of his everyday life. As a musician, he depends on the Facebook platform to promote his music, connect with fans and followers, and engage in a community of likeminded artists in L.A., where he lives. Michael describes his encounters with the algorithm as a game of popularity that hinges on the number of likes and comments his updates are able to atract. In many ways, Michael’s story is reminiscent of the “threat of invisibility” described in the previous chapter. To counteract this threat, Michael has developed strategies and tactics that he thinks will guarantee him a beter chance at retaining atention and geting noticed. Based on previous experience and videos about the underlying logic of the news feed, Michael has developed theories about how the algorithm works. What is frustrating, he says, is when it turns out not to be true. For Rachel, the Facebook algorithm is not subject to the same kind of frustration as it is for Michael. Rachel, a 24-year-old journalist based in New York City, does not “depend” on the algorithm for her own livelihood in the way that Michael does. As a journalist, however, she has noticed that there seems to be an increasing number of news reports on algorithms lately. An article in the Washington Post dealt with the Facebook algorithm; and, ever since, Rachel has been trying to find signs of it in her own news feed. When an old friend from high school appeared in her feed seemingly from nowhere and even “liked” one of Rachel’s posts, she finally sensed the algorithm at work. With respect to forgeting people, Rachel says, it feels like the algorithm is trying to make decisions on her behalf, ultimately influencing the way in which she conducts her friendships. The question going forward is how we might want to think about such everyday encounters with algorithms and what, if anything, they might tell about the ways in which algorithms shape our experiences?\n\nAsking about people’s encounters with algorithms seems to suggest a conscious meeting of some sort or that people are already aware of and have a grasp of what algorithms are. As existing research has shown this is far from always the case (Eslami et al. 2015; Rader & Gray, 2015). In many ways, the question of how people atend to algorithms is akin to the question of how people start to make sense of that which is not readily available to the senses, which has always been an important area of research in the history of science.9 Many scientific and technological innovations are not visible as such. Just think of nanotechnology, RFID, or sensor technologies of various kinds. Like algorithms, they are embedded in computers, pieces of clothing, and other more visible interfaces. Dealing with uncertainties and unknowns is part of what it means to be a human; it is part of what it means to live toward a future, what it means to be in love, or what it means to understand things such as physics and climate change. When people are faced with the hidden and uncertain aspects of life, they tend to construct what has variously been described as “mental models” (Schutz, 1970; Kempton, 1986), “interpretive frames” (Bartunek & Moch, 1987), or simply “folk theories” (Hirschfeld, 2001; Johnson-Laird & Oatley, 1992; Johnson, 1993). To interact with technologies, people have to make sense of them, and they do so in a variety of ways—for example, through visualizations, analogies to more familiar domains, or by the use of metaphors. Media discourses, cultural artefacts, stories, anecdotes, and shared cultural beliefs can “provide people with explanatory power and guide behavior surrounding use of a particular technology” (Poole et al., 2008). The increased ubiquity and popularity of depicting unfamiliar phenomena such as artificial intelligence and robotics in films and popular imagery have arguably made these phenomena more available to public reasoning and debate (see Suchman, 2007).10 This is no diferent when it comes to the algorithm, which is rarely encountered in its mathematical or technical form. When people encounter or “see” the algorithm, it is typically in the form of simplified images of a formula (e.g., EdgeRank formula) or a newspaper story about a recent controversy as evident, for example, in the recent censorship accusations against Facebook and their “algorithm” removing the iconic “Terror of War” image or through other means of cultural mediation such as films and artworks of various kinds.\n\n96\n\nI F . . . T H E N","previous_page":95,"next_page":97}