13 Matching Annotations
  1. Jan 2021
  2. Nov 2020
    1. other technologies

      particularly proctoring and "plagiarism detection" platforms that exacerbate the "patterns of systemic racism" mentioned above.

  3. Aug 2020
    1. Facebook has apologized to its users and advertisers for being forced to respect people’s privacy in an upcoming update to Apple’s mobile operating system – and promised it will do its best to invade their privacy on other platforms.

      Sometimes I forget how funny The Register can be. This is terrific.

    1. Facebook is warning developers that privacy changes in an upcoming iOS update will severely curtail its ability to track users' activity across the entire Internet and app ecosystem and prevent the social media platform from serving targeted ads to users inside other, non-Facebook apps on iPhones.

      I fail to see anything bad about this.

  4. Jun 2020
  5. May 2020
  6. Apr 2020
  7. Dec 2019
  • Nov 2019
  • Apr 2019
    1. We may share information as discussed below, but we won’t sell it to advertisers or other third parties.

      Notice Drop Box states up front that it does not sell your info to advertisers and third parties. This line is crucial to your data privacy.

    1. (iii) Information we collect from other sources: From time to time, we may obtain information about you or your Contacts from third-party sources, such as public databases, social media platforms, third-party data providers and our joint marketing partners. We take steps to ensure that such third parties are legally or contractually permitted to disclose such information to us.

      So while this is a free site, they can mine your data including your social media account. All of this in the name of providing you better service.

    1. Digital sociology needs more big theory as well as testable theory.

      I can't help but think here about the application of digital technology to large bodies of literature in the creation of the field of corpus linguistics.

      If traditional sociology means anything, then a digital incarnation of it should create physical and trackable means that can potentially be more easily studied as a result. Just the same way that Mark Dredze has been able to look at Twitter data to analyze public health data like influenza, we should be able to more easily quantify sociological phenomenon in aggregate by looking at larger and richer data sets of online interactions.

      There's also likely some value in studying the quantities of digital exhaust that companies like Google, Amazon, Facebook, etc. are using for surveillance capitalism.