{"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":45,"pdf_page":55,"physical_index":55,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"c3bfb646e4946022ff3a759e91cb1789b1d2763e5eeede7019fe0d4fc56d1b93"},"chapter":"IF...THEN","content":"When algorithms are positioned as black boxes in current discourses, it is usually  to problematize the fact that many have harmful or discriminatory efects. Particularly within legal circles, repeated calls have been made for opening up the black box of algorithms. As Pasquale argues, “without knowing what Google actually does when it ranks sites, we cannot assess when it is acting in good faith to help users, and when it is biasing results to favor its own commercial interests” (2015: 9). For Pasquale, what is worrisome is the knowledge asymmetry inherent in the black box society or what he calls the “one-way mirror” of knowledge: “Important corporate actors have unprecedented knowledge of the minutiae of our daily lives, while we know litle to nothing about how they use this knowledge to influence the important decisions that we—and they—make” (2015: 9). This knowledge asymmetry impinges new power relations—not just between corporations knowing more and more about the people it monitors but also between corporations themselves, ultimately undermining robust competition (Pasquale, 2015: 83). Thus, legal scholars (especially, in the US context) are now intensifying calls for greater transparency, asking corporations to make their workings more transparent (see, for example, Balkin, 2016; Benjamin, 2013; Citron & Pasquale, 2014; Cohen, 2016; Mehra, 2015).6 As Pasquale provocatively puts it, “you can’t form a trusting relationship with a black box” (2015: 83).\n\nWhat, then, are some of the proposed solutions to the pervasive black boxing of technical details in the “algorithmic society” (Balkin, 2016)? For Pasquale, black boxes must be revealed in order to counteract any wrongdoings, discrimination, or bias these systems may contain: “algorithms should be open for inspection—if not by the public at large, at least by some trusted auditor” (2015: 141). Here, opening up may simply involve making source code accessible. As Citron and Pasquale argue in the context of detecting bias in credit-scoring systems, “To know for sure, we would need access to the source code, programmers’ notes and algorithms at the heart of credit-scoring systems to test for human bias, which of course we do not have” (2014: 14). Others are more skeptical about the demands for transparent source code, pointing out that such calls are not taking account of the many adequate reasons for not making every detail fully transparent (Kroll et al.,  2016). However, opening up the black box of algorithms may also imply opening up the conditions under which algorithms can be legally audited from the outside. As a recent lawsuit filed in US federal court by researchers Sandvig and colleagues atest, the law may constitute an additional barrier to access—in this case, “preventing researchers from collecting data to determine whether online algorithms result in discrimination” (Grauer, 2016). While the many calls for greater transparency certainly hold merit, what I want to argue in the following is that knowing algorithms need not necessitate opening the black box. In fact, the black box may not even be the most adequate notion to use when thinking about the ontology and epistemology of algorithms.\n\nNeither Black nor Box\n\n45","previous_page":44,"next_page":46}