{"title":"数据资本主义和人工智能伦理的反未来","authors":"Ezekiel Dixon-Román, L. Parisi","doi":"10.1177/2057047320972029","DOIUrl":null,"url":null,"abstract":"Ethics in data science and artificial intelligence have gained broader prominence in both scholarly and public discourse. Much of the scholarly engagements have often been based on perspectives of transparency, politics of representation, moral ethical norms, and refusal. In this article, while the authors agree that there is a problem with the universal model of technology, they argue that what these perspectives do not address is the postcolonial epistemology of the machine. Drawing from Mark Fisher’s science fiction capital, it is posited that data capitalism doesn’t rely on data as a given, but on what data can become; it operates in the future as much as the calculation of probabilities coincides with the predictive extraction of surplus value. The authors argue that in order to address ethical and sociopolitical concerns in artificial intelligence, technosocial systems must be understood in data capitalism. After discussing what they characterize as the three paradigms of prediction, the authors point toward the transformative potential of temporal structures and indeterminacies in automated self-regulating systems. They argue therefore that assumptions of technological determinism that are found in debates about the reproduction of biases in systems of predictive intelligence has nothing to do with the technical machine, but is rather the result of a continuous re-territorialization of the technosocial possibilities of re-inventing epistemological paradigms outside the framework of colonial capital.","PeriodicalId":44233,"journal":{"name":"Communication and the Public","volume":"5 1","pages":"116 - 121"},"PeriodicalIF":1.2000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/2057047320972029","citationCount":"2","resultStr":"{\"title\":\"Data capitalism and the counter futures of ethics in artificial intelligence\",\"authors\":\"Ezekiel Dixon-Román, L. Parisi\",\"doi\":\"10.1177/2057047320972029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ethics in data science and artificial intelligence have gained broader prominence in both scholarly and public discourse. Much of the scholarly engagements have often been based on perspectives of transparency, politics of representation, moral ethical norms, and refusal. In this article, while the authors agree that there is a problem with the universal model of technology, they argue that what these perspectives do not address is the postcolonial epistemology of the machine. Drawing from Mark Fisher’s science fiction capital, it is posited that data capitalism doesn’t rely on data as a given, but on what data can become; it operates in the future as much as the calculation of probabilities coincides with the predictive extraction of surplus value. The authors argue that in order to address ethical and sociopolitical concerns in artificial intelligence, technosocial systems must be understood in data capitalism. After discussing what they characterize as the three paradigms of prediction, the authors point toward the transformative potential of temporal structures and indeterminacies in automated self-regulating systems. They argue therefore that assumptions of technological determinism that are found in debates about the reproduction of biases in systems of predictive intelligence has nothing to do with the technical machine, but is rather the result of a continuous re-territorialization of the technosocial possibilities of re-inventing epistemological paradigms outside the framework of colonial capital.\",\"PeriodicalId\":44233,\"journal\":{\"name\":\"Communication and the Public\",\"volume\":\"5 1\",\"pages\":\"116 - 121\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/2057047320972029\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communication and the Public\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/2057047320972029\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communication and the Public","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/2057047320972029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
Data capitalism and the counter futures of ethics in artificial intelligence
Ethics in data science and artificial intelligence have gained broader prominence in both scholarly and public discourse. Much of the scholarly engagements have often been based on perspectives of transparency, politics of representation, moral ethical norms, and refusal. In this article, while the authors agree that there is a problem with the universal model of technology, they argue that what these perspectives do not address is the postcolonial epistemology of the machine. Drawing from Mark Fisher’s science fiction capital, it is posited that data capitalism doesn’t rely on data as a given, but on what data can become; it operates in the future as much as the calculation of probabilities coincides with the predictive extraction of surplus value. The authors argue that in order to address ethical and sociopolitical concerns in artificial intelligence, technosocial systems must be understood in data capitalism. After discussing what they characterize as the three paradigms of prediction, the authors point toward the transformative potential of temporal structures and indeterminacies in automated self-regulating systems. They argue therefore that assumptions of technological determinism that are found in debates about the reproduction of biases in systems of predictive intelligence has nothing to do with the technical machine, but is rather the result of a continuous re-territorialization of the technosocial possibilities of re-inventing epistemological paradigms outside the framework of colonial capital.