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Journal: AI Facial Recognition, Troll Shock Troops, and Online Polarization

July 26, 2017 - 02:09 -- Admin

Some items of interest:

  • Singapore: "Changi (airport) will be using facial recognition technology to offer self-service options at check-in, bag drop, immigration and boarding" What happens over the long term? Automated systems like this will seek to partner with companies like Facebook.  Why?  Facebook will have, if they don't have already, the best facial recognition AIs available.  Why?  They simply have the biggest and best dataset available to build it with, by a wide margin.  They also can do it on a global scale (sans China/Russia) and they have strong vectors for expansion/growth into more robust methods of identity verification. 
  • Oxford University:  Where are the social media trolls and bots?  A new working paper from Oxford (Troops, Trolls and Troublemakers: A Global Inventory of Organized Social Media Manipulation) assembled a global inventory of cyber shock troops used by governments, militaries, and political parties to manipulate social media.  Unsurprisingly, given that the US pioneered this technology and excels at all things marketing and media, the US leads the world in this new arms race:

Cyber Troops
Cyber Shock Troops

  • Princeton University:  What led to the US political factionalization?   One of the big reasons is that the US news media lost its ability to set the context for the news (the facts).   Traditionally, this context was set through the emotional and moral conjugation of the facts.  For example, "the President's statement" is transformed through emotional conjugation into "the President's outrageous statement".  The advent of social networking formally ended the media's monopoly on setting the emotional context for the news (although the division began earlier with Fox, Drudge, etc.). The US emotional context is now deeply divided.  Here's a Princeton study that mapped the use of emotional/moral words online (pic below).  It showed the US is deeply divided, by the emotional and moral context that frames the news (a far more interesting finding that blaming "fake news").   It also shows there is little crossover between the two groups, likely due to the way social networking self-reinforces the context and controls the people within it.  What?  People don't just read/hear the news anymore -- they retweet it, like it, add emotionally conjugated commentary to it, and pressure their friends with it now.  

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The use of moral words