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How Our Days Became Numbered: Risk and the Rise of the Statistical Individual

3.88 (32 ratings by Goodreads)

English

By (author): Dan Bouk

Long before the age of Big Data or the rise of today's self-quantifiers, American capitalism embraced risk--and proceeded to number our days. Life insurers led the way, developing numerical practices for measuring individuals and groups, predicting their fates, and intervening in their futures. Emanating from the gilded boardrooms of Lower Manhattan and making their way into drawing rooms and tenement apartments across the nation, these practices soon came to change the futures they purported to divine. How Our Days Became Numbered tells a story of corporate culture remaking American culture--a story of intellectuals and professionals in and around insurance companies who reimagined Americans' lives through numbers and taught ordinary Americans to do the same. Making individuals statistical did not happen easily. Legislative battles raged over the propriety of discriminating by race or of smoothing away the effects of capitalism's fluctuations on individuals. Meanwhile, debates within companies set doctors against actuaries and agents, resulting in elaborate, secretive systems of surveillance and calculation. Dan Bouk reveals how, in a little over half a century, insurers laid the groundwork for the much-quantified, risk-infused world that we live in today. To understand how the financial world shapes modern bodies, how risk assessments can perpetuate inequalities of race or sex, and how the quantification and claims of risk on each of us continue to grow, we must take seriously the history of those who view our lives as a series of probabilities to be managed. See more
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Product Details
  • Dimensions: 152 x 229mm
  • Publication Date: 06 Feb 2018
  • Publisher: The University of Chicago Press
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9780226564869

About Dan Bouk

Dan Bouk is assistant professor of history at Colgate University and a member of the Historicizing Big Data working group at the Max Planck Institute for History of Science.

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