标题：Cathy O'Neil (2016) Weapons of Math Destruction: How Big DataIncreases Inequality and Threatens Democracy, New York, St.Martin’s Press and Virginia Eubanks (2018) Automating Inequality:How High-Tech Tools Profile, Police, and Punish the Poor, NewYork, Broadway Books
期刊名称：Journal of Comparative Research in Anthropology and Sociology
电子版ISSN：2068-0317
出版年度：2018
卷号：9
期号：1
页码：89-94
出版社：University of Bucharest
摘要：Providing personal data is something that we do on a regular basis, from filling out governmental forms and documents to indicating preferences and habitual patterns on social media and consumer websites. However, there are many ways in which this data is used that are beyond our control or knowledge. For middle and upper-class individuals, this data collection can make certain things easier, like getting recommendations for different products on Amazon. Some are irritated or mildly fearful as new information comes to light about the erosion of privacy on social media, or shocked by advertisements related to things they may have spoken about on the phone or searched for, but had not explicitly shared on those platforms. However, this form of data mining, along with more traditional forms, such as filling out governmental forms, job applications, and request for public services, is also used for more pernicious and pervasive ends. Data collection, algorithms used to interpret that data, and the effects that these mathematical models have on all strata of American society are the topics of two different but related books Weapons of Math Destruction How Big Data Increases Inequality and Threatens Democracy (2016) by Cathy O'Neil and Automating Inequality How High-Tech Tools Profile, Police, and Punish the Poor (2018) by Virginia Eubanks. In both, the authors argue that data collection and automation increasingly flatten individuals into groups that drive the wedge between the rich and poor, white and people.
