An anonymous reader writes “Winston Smith, the protagonist of George Orwell’s novel 1984, resorted to hiding the bushes with his lover in a failed attempt to escape the government’s ubiquitous surveillance. Orwell was concerned with totalitarianism and explicit thought control enforced by police action. While that is still very much an issue for many of the world’s residents, here in the West there is an unsettling feeling about a more subtle form of thought manipulation, as more and more of our activities are watched, cataloged, and analyzed by more and more institutions — governments, businesses, non-profits, political parties, mostly for predictive purposes. At least we have a name for it now: ‘Dataland’, a term suggested by Kate Crawford of Microsoft Research, who studies the sociological effects of networking technologies. Crawford has been written up in Slashdot before. She’s criticized the indiscriminate adoption of Big Data analytics on several grounds, including the loss of anonymity, erroneous conclusions from skewed datasets, and the prospect of secret discrimination.”… An anonymous reader writes “Winston Smith, the protagonist of George Orwell’s novel 1984, resorted to hiding the bushes with his lover in a failed attempt to escape the government’s ubiquitous surveillance. Orwell was concerned with totalitarianism and explicit thought control enforced by police action. While that is still very much an issue for many of the world’s residents, here in the West there is an unsettling feeling about a more subtle form of thought manipulation, as more and more of our activities are watched, cataloged, and analyzed by more and more institutions — governments, businesses, non-profits, political parties, mostly for predictive purposes. At least we have a name for it now: ‘Dataland’, a term suggested by Kate Crawford of Microsoft Research, who studies the sociological effects of networking technologies. Crawford has been written up in Slashdot before. She’s criticized the indiscriminate adoption of Big Data analytics on several grounds, including the loss of anonymity, erroneous conclusions from skewed datasets, and the prospect of secret discrimination.”

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