Data Privacy in an Age of Digital Pollution
Kamloops Adult Learners Society
CBC Spark: "Your photos can be used in 'catfishing' romance scams"
Alec Couros, "Information for romance scam victims"
Tarleton Gillespie, Logic, "The Scale is Just Unfathomable"
Samanth Subramanian, "The Macedonian Teens Who Mastered Fake News"
"the obvious parodies and even the shadier knock-offs interact with the legions of algorithmic content producers until it is completely impossible to know what is going on. "
"What concerns me is that this is just one aspect of a kind of infrastructural violence being done to all of us, all of the time, and we’re still struggling to find a way to even talk about it, to describe its mechanisms and its actions and its effects."
James Bridle, "Something is wrong on the internet"
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"a recipe or a list of directions to a friend’s house can be understood as an algorithm...
...machine-learning algorithms are effectively programming themselves, meaning that they can sometimes be unpredictable"
Jacob Brogan, "What is an algorithm? An explainer."
"Like gods, these mathematical models were opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists."
Cathy O'Neil, Weapons of Math Destruction
"Here’s an exercise: The next time you hear someone talking about algorithms, replace the term with “God” and ask yourself if the meaning changes."
Ian Bogost, "The Cathedral of Computation"
"Stacks. In 2012 it made less and less sense to talk about "the Internet," "the PC business," "telephones," "Silicon Valley," or "the media," and much more sense to just study Google, Apple, Facebook, Amazon and Microsoft. These big five American vertically organized silos are re-making the world in their image."
Bruce Sterling, "State of the World, 2012"
"...the dominant logic of the web."
Associated Press, "Google records your location even when you tell it not to"
Kashmir Hill, "Goodbye Big Five"
Kaveh Waddell, "Your Phone Is Listening—Literally Listening—to Your TV"
Katarzyna Szymielewicz, "Your digital identity has three layers, and you can only protect one of them"
Leo Mirani and Max Nisen, "The nine companies that know
Bart van der Sloot and Sascha van Schendel, "Ten Questions for Future Regulation of Big Data: A Comparative and Empirical Legal Study"
University of Cambridge Research, “Computers using digital footprints are better judges of personality than friends and family”
Wall Street Journal: Facebook: Blue Feed – Red Feed
"I experimented with nonpolitical topics. The same basic pattern emerged. Videos about vegetarianism led to videos about veganism. Videos about jogging led to videos about running ultramarathons."
Zeynep Tufekci, "YouTube, the Great Radicalizer"
Robinson Meyer, "Could Facebook Have Caught Its 'Jew Hater' Ad Targeting?"
Sheera Frenkel, New York Times, "Facebook to End News Feed Experiment in 6 Countries That Magnified Fake News"
Astra Taylor and Jathan Sadowski, "How Companies Turn Your
Emily Glazer, Deepa Seetharaman, AnnaMaria Andriotis, "Facebook to Banks: Give Us Your Data, We’ll Give You Our Users"
Olivia Solon, The Guardian, "Facebook asks users for nude photos in project to combat 'revenge porn'"
Suzanne Barlyn, Reuters, "Strap on the Fitbit: John Hancock to sell only interactive life insurance"
Alex Hern, The Guardian, "Fitness tracking app Strava gives away location of secret US army bases"
The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues.
...the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.
Esther Kaplan, Harper's, "The Spy Who Fired Me:
Audrey Watters, "The Weaponization of Education Data"
...many schools are adopting analytics and surveillance technologies to monitor and predict student behavior: to identify cyberbullying and suicide threats; to recommend what students should be reading; to recommend what lessons students should be working on; to ascertain if teachers should be awarded tenure; to determine school bus routes; to identify learning disabilities; to identify college students who are struggling with classes; to identify K–12 students who are struggling with classes; to recommend students enroll in certain courses or pursue certain degrees; to help colleges decide who to admit in the first place. “Can you predict your students’ final grade at the start of the course?” Technológica de Monterrey asked on its website, “Yes, you can with Artificial Intelligence.” “Will You Graduate?” asked an article in The New York Times. “Ask Big Data.”
Mike Caulfield, Four Moves
