{"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":146,"pdf_page":156,"physical_index":156,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"10d2839c2244175048512fa828d152774dbbff5d987210e7052495fd05d2aa3b"},"chapter":"IF...THEN","content":"Second, as I have already alluded to, algorithms problematize existing boundaries of what journalism is and ought to be. The interviews reveal how the inclusion of algorithms in journalistic practices and products fuel important discussions about the nature of news. A central theme in Gillinger’s discussion of developing an algorithm to curate and rank socially engaging content at Sveriges Radio is the way in which the process itself brought about important reflections and discussions on the significance of journalism today. As he says, “In my 20 years of working in various editorial teams, I have witnessed a lot of implicit ideas about what constitutes news values.” Talking about what an algorithm is supposed to reflect and how it ought to work has forced people to reflect on these implicit and often unspoken believes and ideas about news, Gillinger says (Interview 17, May 2016).\n\nMoreover, algorithms problematize journalism through “boundary-drawing practices—specific material (re)configurings of the world—which come to mater” (Barad, 2007: 206). As a contested mater, algorithms have become the focus of much public discussion surrounding journalism, making important marks upon the journalistic institution itself. As “pharmacological” objects of sorts, algorithms make themselves known as both remedy and harm.16 The question, however, is not so much whether algorithms are poison or cure but what is at stake in their diferen tial configuration as one or the other. As Suchman writes, “Objects achieve recognition within a matrix of historically and culturally constituted familiar, intelligible possibilities [in which] we might understand ‘things’ or objects as materializations of more and less contested, normative identifications of mater” (2007: 10). As the interviews and various controversies surrounding algorithms suggest, the news media are by no means a neutral component in the diferential mobilization of algorithms. In line with the broader argument of the book, this chapter reveals how algorithms do not always mater (as much), but are rather made to mater in certain ways. We can think of this form of diferential matering as a form of ontological politics, insofar as algorithms are carved out as entities with specific features and “normative variability” (Marres, 2013). That is, algorithms do not always carry the same moral or normative capacities. Sometimes they are rendered bad or inferior, do the wrong things, as indicated in the discussions over filter bubbles. At other times, algorithms do the right thing, for example, by helping journalists do a beter and more efective job. What the algorithm does and how it is made meaningful is not set in stone. This variability suggests that the power and politics of algorithms cannot necessarily be found in the algorithm, but rather, as it was also suggested in chapter 3, is more a question of when the agency of algorithms is mobilized and on whose behalf.\n\n146\n\nI F . . . T H E N","previous_page":145,"next_page":147}