Amazon's Deep Learning Service Rekognition Mistakes Congress Members For Criminals

Discussion in 'Industry News' started by Calliers, Jul 27, 2018.

  1. Calliers

    Calliers HH's MC Staff Member

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    Amazon's Rekognition service has been making a considerable amount of mistakes, it seems, and its latest set may be some of the most egregious. Recently, the American Civil Liberties Union reported that during a recent test, the service mistakenly identified 28 members of Congress as criminals.

    Previously, the ACLU took a collection of a whopping 25,000 mugshots from an unnamed "public source" and had the service compare them all the photos from Congress. There were various photos simply misidentified, including civil rights activist Rep. John Lewis (D-Goergia). In fact, many of the false matches, around 38 percent of them to be exact, were actually people of color.

    An Amazon spokesperson told VentureBeat that the test likely made these egregious mistakes because of some "poor calibration" due to the low "confidence threshold" utilized by the system.
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  2. IvanV

    IvanV HH Assassin Guild Member

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    That AI seems more advanced than its human operators anticipated. Face recognition algorithms aren't perfect and they may make one or two mistakes, but 28? I don't think so.
     
  3. Judas

    Judas Obvious Closet Brony Pony

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    Seems like it's properly doing it's job, considering.

    Honestly if you watch Eagle Eye (movie)... The A.I. in it was actually doing it's job properly, but it was spun up as doing the wrong thing. Granted it's process of basically doing the wrong thing to ensure it could do the correct thing is very much in question, had it not been prevented from doing the right thing to begin with, which was to hold the people in power accountable for atrocities it committed.
     

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