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- W3124013575 abstract "Predictive analytics use a method known as data mining to identify trends, patterns, or relationships among data, which can then be used to develop a predictive model. Data mining itself relies upon big data, which is “big” not solely because of its size but also because its analytical potential is qualitatively different. “Big data” analysis allows organizations, including government and businesses, to combine diverse digital datasets and then use statistics and other data mining techniques to extract from them both hidden information and surprising correlations. These data are not necessarily tracking transactional records of atomized behavior, such as the purchasing history of customers, but keeping track of communication dynamics and social interactions.Employers have long used various tools to monitor workers, whether to track productivity or guard against improper behavior in the workplace. But as individuals communicate and socialize more and more online, a whole new array of data is becoming available to employers to evaluate job candidates and monitor workers through predictive analytics. Current U.S. privacy law provides almost no protection from the type of “profile” that can be generated through predictive analytics, no matter how personal. It considers any information that is potentially publicly available to not be private — regardless of how that “public” information is collected and used. There is, however, one developing privacy theory that could potentially provide privacy protection from predictive analytics: the “mosaic” theory recognizes that continuous monitoring of publicly available information can reveal an intimate picture of an individual’s life.Predictive analytics have existed for some time, but have only recently “come of age” in employment situations. This article examines the use of predictive analytics in the workplace, threats to worker privacy arising from predictive analytics, and whether the mosaic theory offers a viable and needed method of privacy protection. This article concludes, however, that unless a new theory of privacy protection is adopted — and soon — everyone faces serious threats to their privacy." @default.
- W3124013575 created "2021-02-01" @default.
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- W3124013575 date "2015-12-31" @default.
- W3124013575 modified "2023-09-26" @default.
- W3124013575 title "Welcome to the Machine: Privacy and Workplace Implications of Predictive Analytics" @default.
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