Consider two hypothetical people.
The first is a thirty-year-old white-collar resident of Manhattan. She participates in modern life in all the ways typical of her demographic: smartphone, Google, Gmail, Netflix, Spotify, Amazon. She uses Facebook, with its default privacy settings, to keep in touch with friends. She dates through the website OkCupid. She travels frequently, tweeting and posting geotagged photos to Flickr and Instagram. Her wallet holds a debit card, credit cards, and a MetroCard for the subway and bus system. On her keychain are plastic barcoded cards for the “customer rewards” programs of her grocery and drugstore. In her car, a GPS sits on the dash, and an E‑ZPass transponder (for bridge, tunnel, and highway tolls) hangs from the windshield.
Now consider a second person. He lives two hours southwest of Manhattan, in Camden, New Jersey, America’s poorest city. He is underemployed, working part-time at a restaurant, paid under the table in cash. He has no cell phone, no computer, no cable. He rarely travels and has no passport, car, or GPS. He uses the Internet, but only at the local library on public terminals. When he rides the bus, he pays the fare in cash.
What differences are there between the types of data that the Manhattan resident generates and the types of data the resident of Camden generates?
Which individual has more privacy? (Feel free to argue both ways, taking into account differing forms of surveillance.)
How does the failure of corporate interests including social media companies to collect online information on the Camden resident affect his
(i) economic opportunities
(ii) social mobility
(iii) government services
(iii) democratic participation?
These are the readings for the week and the only ones to use when supporting ideas and giving examples:
READ the Module 14 materials in the Syllabus:
Hess (2017). How Privacy Became a Commodity for the Rich and Powerful, New York Times. https://www.nytimes.com/2017/05/09/magazine/how-privacy-became-a-commodity-for-the-rich-and-powerful.html
FTC Report: Big Data: A Tool for Inclusion or Exclusion? Understanding The Issues (2016), pp. 9-10. https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclusion-understanding-issues/160106big-data-rpt.pdf
Gellman & Adler-Bell (2017), The Disparate Impact of Surveillance, The Century Foundation.
Haimson, O. (2015). Marginalized Populations and Research Ethics Online, Conference Paper
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