Bowdoin: Data Driven Societies: Remix
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Bowdoin: Data Driven Societies: Remix



Data Driven Societies

Data Driven Societies
Digital & Computational Studies
Bowdoin College
April 21, 2014
Professor Gieseking

Lecture Slides "Remix"



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Bowdoin: Data Driven Societies: Remix Bowdoin: Data Driven Societies: Remix Presentation Transcript

  • Data Driven Societies: On Algorithms & Remix Professors Gieseking & Gaze
  • Reminder: Matt Wilson on 4/28
  • Recap: Visualizing Social Life • Coleman: Determining respect in Anonymous via language and activist intervention hacking efforts ! • Coleman’s “code as speech” = ethical, legal, cultural ramifications of language of code, exceeds code as law and much broader
  • Recap: Visualizing Social Life ✦ Katz & Donovan confront anxiety around children’s and youth’s use of computers ✦ Hacking - play, curious exploration, or as a puzzle solution that helps young people to better understand and control their environments (technological and otherwise)
  • On algorithms and trending.
  • ✦ Who determine Twitter “Trends”? Feedback determines further feedback loop but claims to represent the will of the people ✦ Algorithms are closely guarded (Amazon, Fb, YouTube, Digg, etc.) ✦ Sales pitch of Twitter is its free and open qualities Can the Algorithm be Wrong?
  • ✦ But Twitter is a corporation — one that supports anti-terrorist efforts but encrypts against NSA ✦ See also: Weibo ✦ Algorithms are not only socially constructed, the social construction is always political ✦ a la filter bubble ✦ Facebook “Friends” networks do not represent actual social networks Can the Algorithm be Wrong?
  • These algorithms produce not barometric readings but hieroglyphs. At once so clear and so opaque, they beg to be read as reliable measures of the public mind, as signs of “us.” But the shape of the “us” on offer is by no means transparent. -Gillespie
  • All is not lost. Ever.
  • Then there is remix.
  • ✦ R/O (Read/Only) Culture: a culture of consumption rather than amateur performance ✦ R/W (Read/Write) Culture: mixing, matching, merging traditions, ideas, and media to create new or derivative work, whether as satire, sample, etc. ✦ Remix - “critical expression of creative freedom” Lessig’s Remix Culture
  • ✦ Napster created P2P (peer-to- peer) music and other file sharing - note: not yet bandwidth for movies ✦ Steve Job’s intervention in piracy: Digital Rights Management (DRM), i.e. encoding music files to not be shared Napster v. iTunes Napster, Apple
  • ✦ What changed was affordability not interest (ex. record —> tape —> CD —> Mp3) ✦ see Sterne’s Mp3 ✦ Amateur creativity and copyright equally important ✦ “YouTube is a picture of unmet demands.” (46) ✦ Free access pays more in data than advertiser fees Remix Culture Beyonce Knowles
  • As these businesses grow, they not only change business. They also change us. They change how we think about access to culture. They change what we take for granted. -Lessig (43)
  • ✦ Benkler’s “writable web” of blogging —> comments —> tags and ranking systems —> other forms of “creating” exceed writing because we make more use of them ✦ RW internet as “ecosystem” vs. Donovan’s “proprietary ecologies” Remixed Ecosystems
  • ✦ Two good remix creates for now: ✦ community ✦ education ✦ Note: remix is not new Lessig on the Good of Remix
  • Next Class: Apr. 23 ✦ Today: algorithms & remix ! ✦ Readings: Hagy & Anderson ! ✦ Lab: 4/23 ggplot2, part trois ! ✦ Last blog assignment due 5/1 ! ✦ Hackathon 4/23(!) ! ✦ DCSI lectures: David Stork on 4/21 (tonight), Matt Wilson on 4/28 (req’d)