{"title":"Front and Back Matter","authors":"","doi":"10.1086/726662","DOIUrl":"https://doi.org/10.1086/726662","url":null,"abstract":"","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44422361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Previous articleNext article FreeNotes on the ContributorsPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmailPrint SectionsMoreMike Ananny is associate professor of communication and journalism, and affiliated faculty of science, technology, and society, at the University of Southern California’s Annenberg School for Communication and Journalism. He studies the public significance of sociotechnical infrastructures, including digital news systems, machine learning algorithms, and social media platforms. He is the author of Networked Press Freedom (MIT, 2018) and coeditor (with Laura Forlano and Molly Wright Steenson) of Bauhaus Futures (MIT, 2019), and frequently writes for popular press publications including the Atlantic, Wired, Harvard’s Nieman Lab, and the Columbia Journalism Review.Michael J. Barany is senior lecturer in the history of science at the University of Edinburgh, specializing in the history and culture of modern mathematics. He is principal investigator of the project Situating International and Global Mathematics and coedited with Kirsti Niskanen the volume Gender, Embodiment, and the History of the Scholarly Persona: Incarnations and Contestations (Palgrave, 2021).Alex Csiszar is a professor at the Department of the History of Science, Harvard University. He is the author of The Scientific Journal: Authorship and the Politics of Knowledge in the Nineteenth Century (Chicago, 2018) and is currently completing a book titled “Rank and File: From the Literature Search to Algorithmic Judgment.”Stephanie Dick is an assistant professor in the School of Communication at Simon Fraser University. Her research explores entanglements of mathematics and computing in the postwar United States. She is coeditor of Abstractions and Embodiments: New Histories of Computing and Society (Johns Hopkins, 2022).Theodora Dryer, PhD, is a writer, historian, and critical policy analyst. Her research centers on data and technology in the climate crisis and the political functions of algorithms and digital data systems in water and natural resource management. She teaches on technology and environmental justice at New York University.Salem Elzway is a PhD candidate in history at the University of Michigan and a national fellow with the Jefferson Scholars Foundation. His research explores the political and socioeconomic history of automation, security policy, and welfare in the postwar United States. The dissertation emerging from this, titled “Arms of the State: A History of the Industrial Robot in Postwar America,” provides the first scholarly history of the industrial robot and demonstrates how the American state’s socialization of the technology underwrote a political economy that exacerbated economic insecurity and reproduced social inequality.James Evans is Max Palevsky Professor of History and Civilization in Sociology and director of Knowledge Lab at the University of Chic
{"title":"Notes on the Contributors","authors":"","doi":"10.1086/725149","DOIUrl":"https://doi.org/10.1086/725149","url":null,"abstract":"Previous articleNext article FreeNotes on the ContributorsPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmailPrint SectionsMoreMike Ananny is associate professor of communication and journalism, and affiliated faculty of science, technology, and society, at the University of Southern California’s Annenberg School for Communication and Journalism. He studies the public significance of sociotechnical infrastructures, including digital news systems, machine learning algorithms, and social media platforms. He is the author of Networked Press Freedom (MIT, 2018) and coeditor (with Laura Forlano and Molly Wright Steenson) of Bauhaus Futures (MIT, 2019), and frequently writes for popular press publications including the Atlantic, Wired, Harvard’s Nieman Lab, and the Columbia Journalism Review.Michael J. Barany is senior lecturer in the history of science at the University of Edinburgh, specializing in the history and culture of modern mathematics. He is principal investigator of the project Situating International and Global Mathematics and coedited with Kirsti Niskanen the volume Gender, Embodiment, and the History of the Scholarly Persona: Incarnations and Contestations (Palgrave, 2021).Alex Csiszar is a professor at the Department of the History of Science, Harvard University. He is the author of The Scientific Journal: Authorship and the Politics of Knowledge in the Nineteenth Century (Chicago, 2018) and is currently completing a book titled “Rank and File: From the Literature Search to Algorithmic Judgment.”Stephanie Dick is an assistant professor in the School of Communication at Simon Fraser University. Her research explores entanglements of mathematics and computing in the postwar United States. She is coeditor of Abstractions and Embodiments: New Histories of Computing and Society (Johns Hopkins, 2022).Theodora Dryer, PhD, is a writer, historian, and critical policy analyst. Her research centers on data and technology in the climate crisis and the political functions of algorithms and digital data systems in water and natural resource management. She teaches on technology and environmental justice at New York University.Salem Elzway is a PhD candidate in history at the University of Michigan and a national fellow with the Jefferson Scholars Foundation. His research explores the political and socioeconomic history of automation, security policy, and welfare in the postwar United States. The dissertation emerging from this, titled “Arms of the State: A History of the Industrial Robot in Postwar America,” provides the first scholarly history of the industrial robot and demonstrates how the American state’s socialization of the technology underwrote a political economy that exacerbated economic insecurity and reproduced social inequality.James Evans is Max Palevsky Professor of History and Civilization in Sociology and director of Knowledge Lab at the University of Chic","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135452755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter investigates the origin narratives and commemoration practices that came hand in hand with the growing cultural authority of the algorithm after World War II, culminating in celebrations in honor of the 1,200th anniversary of the medieval scholar Abu ʿAdallah Muhammad Ibn Musa al-Khwarizmi. I first show how al-Khwarizmi’s legacy was claimed by Soviet historians of mathematics aiming to construct a history inspired by dialectical materialism, a goal that eventually led to arguments about the distinct, algorithmic character of mathematics in the East. Next, I study how these ideas were appropriated by the international community of computer scientists in search of the origins for their discipline. The late-Soviet coupling of commemoration rituals with programming literacy campaigns evolved into an enduring cultural reference shared across post-Soviet spaces. Such alternative symbolic lives of the algorithm suggest a need to suspend assumptions of universality in historicizing the global modalities of algorithmic culture.
{"title":"Algorithm’s Cradle","authors":"Ksenia Tatarchenko","doi":"10.1086/725145","DOIUrl":"https://doi.org/10.1086/725145","url":null,"abstract":"This chapter investigates the origin narratives and commemoration practices that came hand in hand with the growing cultural authority of the algorithm after World War II, culminating in celebrations in honor of the 1,200th anniversary of the medieval scholar Abu ʿAdallah Muhammad Ibn Musa al-Khwarizmi. I first show how al-Khwarizmi’s legacy was claimed by Soviet historians of mathematics aiming to construct a history inspired by dialectical materialism, a goal that eventually led to arguments about the distinct, algorithmic character of mathematics in the East. Next, I study how these ideas were appropriated by the international community of computer scientists in search of the origins for their discipline. The late-Soviet coupling of commemoration rituals with programming literacy campaigns evolved into an enduring cultural reference shared across post-Soviet spaces. Such alternative symbolic lives of the algorithm suggest a need to suspend assumptions of universality in historicizing the global modalities of algorithmic culture.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"286 - 304"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43501980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The history of hypertext has been dominated by the history of the World Wide Web. However, the inventor of hypertext, Theodor Nelson, has long viewed the web as a deeply problematic implementation of his ideas and advocated for his own hypertext system known as Project Xanadu. This essay situates Xanadu against a background of changing ideas about media and text in the 1960s and 1970s. Based on close reading of Nelson’s work, this essay shows how Xanadu was an instance of the kind of media structure that Nelson saw as most liberating and empowering.
{"title":"Code and Critique","authors":"Hallam Stevens","doi":"10.1086/725144","DOIUrl":"https://doi.org/10.1086/725144","url":null,"abstract":"The history of hypertext has been dominated by the history of the World Wide Web. However, the inventor of hypertext, Theodor Nelson, has long viewed the web as a deeply problematic implementation of his ideas and advocated for his own hypertext system known as Project Xanadu. This essay situates Xanadu against a background of changing ideas about media and text in the 1960s and 1970s. Based on close reading of Nelson’s work, this essay shows how Xanadu was an instance of the kind of media structure that Nelson saw as most liberating and empowering.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"245 - 264"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60729542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article examines artists’ and designers’ engagements with US legal culture and its pronouncements on the status of code-driven creations as intellectual property. Focusing on a copyright dispute between a computational origami designer and a conceptual artist, it describes the historical circumstances that recast mathematical and computational origami as a creative art form rather than a traditional craft not usually given authorial attribution. Showing how artists’ practices and legal disputes over copyright employed historic and contemporary understandings of code and craft to delineate art, I argue that their resulting interpretations of mathematical and computational origami depended upon reaffirming origami as an Asian subject. Consequently, this article cautions against an ahistorical reliance on code and craft as analytics. It encourages critical engagement with the scalar contexts and racial and historical contingencies from which such analytics operate.
{"title":"The Art and Craft of Mathematical Expression","authors":"Clare S. Kim","doi":"10.1086/725130","DOIUrl":"https://doi.org/10.1086/725130","url":null,"abstract":"This article examines artists’ and designers’ engagements with US legal culture and its pronouncements on the status of code-driven creations as intellectual property. Focusing on a copyright dispute between a computational origami designer and a conceptual artist, it describes the historical circumstances that recast mathematical and computational origami as a creative art form rather than a traditional craft not usually given authorial attribution. Showing how artists’ practices and legal disputes over copyright employed historic and contemporary understandings of code and craft to delineate art, I argue that their resulting interpretations of mathematical and computational origami depended upon reaffirming origami as an Asian subject. Consequently, this article cautions against an ahistorical reliance on code and craft as analytics. It encourages critical engagement with the scalar contexts and racial and historical contingencies from which such analytics operate.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"82 - 102"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48575637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nobel laureate Wassily Leontief crafted a computer metaphor to describe the workings of an economy through his development of interindustry input-output analysis. He came to argue that economic activities of a national economy behaved as if they were equations arranged, stored, and manipulated in computers. The computer metaphor, however, has two limitations. First, economists’ careful crafting of codelike economic activities was a more heuristic process than it appeared. Second, economists often deemed the economic structure of developing economies too irregular, and that of less developed economies too simple, for the analysis to work. Leontief’s computer metaphor showcases the quest for automating information processing, computing, and human decision making in Cold War science and technology, leaving many legacies in the contemporary algorithmic culture.
{"title":"Between “Magnificent Machine” and “Elusive Device”","authors":"Honghong Tinn","doi":"10.1086/725091","DOIUrl":"https://doi.org/10.1086/725091","url":null,"abstract":"Nobel laureate Wassily Leontief crafted a computer metaphor to describe the workings of an economy through his development of interindustry input-output analysis. He came to argue that economic activities of a national economy behaved as if they were equations arranged, stored, and manipulated in computers. The computer metaphor, however, has two limitations. First, economists’ careful crafting of codelike economic activities was a more heuristic process than it appeared. Second, economists often deemed the economic structure of developing economies too irregular, and that of less developed economies too simple, for the analysis to work. Leontief’s computer metaphor showcases the quest for automating information processing, computing, and human decision making in Cold War science and technology, leaving many legacies in the contemporary algorithmic culture.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"129 - 146"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49272628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article links optimization algorithms in US southwestern water management to equitable apportionment and prior appropriation water policies in the 1950–1990 period. I argue that quantitative water law and algorithmic water management are coconstitutive historical processes, as they derive from the same formulation of settler colonial space and time—a practice I call settler computing. Settler computing clarifies how the settler theft of Indigenous natural resources is formalized within projects of data-driven resource management. I engage this history by reflecting on a major water planning project led by the Bureau of Reclamation called the Central Utah Project (CUP), which was formally enacted in 1956. When tech developers appropriated the Ute Indian Tribe of the Uintah and Ouray Reservation’s water and land during the development of CUP, this appropriation was simultaneously encoded in linear optimization frameworks.
{"title":"Settler Computing","authors":"Theodora Dryer","doi":"10.1086/725187","DOIUrl":"https://doi.org/10.1086/725187","url":null,"abstract":"This article links optimization algorithms in US southwestern water management to equitable apportionment and prior appropriation water policies in the 1950–1990 period. I argue that quantitative water law and algorithmic water management are coconstitutive historical processes, as they derive from the same formulation of settler colonial space and time—a practice I call settler computing. Settler computing clarifies how the settler theft of Indigenous natural resources is formalized within projects of data-driven resource management. I engage this history by reflecting on a major water planning project led by the Bureau of Reclamation called the Central Utah Project (CUP), which was formally enacted in 1956. When tech developers appropriated the Ute Indian Tribe of the Uintah and Ouray Reservation’s water and land during the development of CUP, this appropriation was simultaneously encoded in linear optimization frameworks.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"265 - 285"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49187465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article examines the role of automatic speech recognition research in the rise of data-driven machine learning as a privileged and pervasive form of computational knowledge. It focuses on IBM’s Continuous Speech Recognition group between 1972 and 1993 as they fueled speech recognition’s “statistical turn,” uprooting the field from the simulation of human reason and language understanding and redirecting it toward the acquisition of data for large-scale pattern recognition. This shift, I argue, was instrumental in the remaking of artificial intelligence and computational modeling into radically data-centric pursuits that underpin algorithmic culture today. In doing so, this history offers a critical piece in the story of how we became data-driven, highlighting how efforts to turn language into data consequently turned data into an imperative, preparing the way for the widespread incursion of algorithmic authority across everyday life.
{"title":"“There’s No Data Like More Data”","authors":"Xiaochang Li","doi":"10.1086/725132","DOIUrl":"https://doi.org/10.1086/725132","url":null,"abstract":"This article examines the role of automatic speech recognition research in the rise of data-driven machine learning as a privileged and pervasive form of computational knowledge. It focuses on IBM’s Continuous Speech Recognition group between 1972 and 1993 as they fueled speech recognition’s “statistical turn,” uprooting the field from the simulation of human reason and language understanding and redirecting it toward the acquisition of data for large-scale pattern recognition. This shift, I argue, was instrumental in the remaking of artificial intelligence and computational modeling into radically data-centric pursuits that underpin algorithmic culture today. In doing so, this history offers a critical piece in the story of how we became data-driven, highlighting how efforts to turn language into data consequently turned data into an imperative, preparing the way for the widespread incursion of algorithmic authority across everyday life.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"165 - 182"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45034104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From law and politics to commerce and art, algorithms are powerful sociotechnical forces. But what does it mean when algorithms “fail”? What do we learn about sociotechnical dynamics when algorithms are seen to have erred or made a mistake? Seeing algorithms as culture, I argue that algorithmic errors are constructs of intertwined computational, psychological, organizational, infrastructural, discursive, and normative forces. Through three stories of error, I show algorithmic failures as illustrations not only of algorithmic power but also of normative forces that define success, rationalize iteration, and distribute harm. Instead of seeing algorithmic errors as unavoidable parts of technological innovation or self-evident transgressions, I instead see them as evidence of how people think systems should work, and the power to declare failures, trigger fixes, and envision futures by discovering and repairing mistakes. This power to “make mistakes” is a crucial and largely understudied form of sociotechnical control.
{"title":"Making Mistakes","authors":"Mike Ananny","doi":"10.1086/725146","DOIUrl":"https://doi.org/10.1086/725146","url":null,"abstract":"From law and politics to commerce and art, algorithms are powerful sociotechnical forces. But what does it mean when algorithms “fail”? What do we learn about sociotechnical dynamics when algorithms are seen to have erred or made a mistake? Seeing algorithms as culture, I argue that algorithmic errors are constructs of intertwined computational, psychological, organizational, infrastructural, discursive, and normative forces. Through three stories of error, I show algorithmic failures as illustrations not only of algorithmic power but also of normative forces that define success, rationalize iteration, and distribute harm. Instead of seeing algorithmic errors as unavoidable parts of technological innovation or self-evident transgressions, I instead see them as evidence of how people think systems should work, and the power to declare failures, trigger fixes, and envision futures by discovering and repairing mistakes. This power to “make mistakes” is a crucial and largely understudied form of sociotechnical control.","PeriodicalId":54659,"journal":{"name":"Osiris","volume":"38 1","pages":"223 - 241"},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46361481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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