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    From shrimp Jesus to fake self-portraits, AI-generated images have become the latest form of social media spam
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    Aug. 9, 2010, 6 p.m.

    Links on Twitter: TBD launches its local news site, Ushahidi launches Crowdmap, Forbes launches HuffPo-style blogging initiative

    Journal Register Company finishes Q2 ahead of its $12M earnings goal, on track to share profits with its employees http://j.mp/d1Rmq9 »

    Exciting: @Ushahidi launches Crowdmap, a free, quick-to-install, easy-to-use version of the platform http://j.mp/bJJiNz »

    More Google news, via @jilliancyork: the company is beginning an extensive recruitment campaign in China http://j.mp/cjgKtZ »

    Here it is, from @googlepubpolicy: "A Joint Policy for an Open Internet" http://j.mp/9gB5UF »

    Forbes to enlist HuffPo-style unpaid bloggers. Others will be paid based on traffic stats http://j.mp/9EE0Rf »

    Working on a journalism project in Philly? Apply for one of 10 $5K grants http://j.mp/dpAeG7 »

    How @TBD got its name: "We were just cursed." http://j.mp/97UpzO »

    Betting against the atom: Dorchester Publishing goes all-digital http://j.mp/9oKxJ4 »

     
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    The latest from Nieman Lab
    From shrimp Jesus to fake self-portraits, AI-generated images have become the latest form of social media spam
    Renee DiResta, Abhiram Reddy, and Josh A. Goldstein
    What journalists and independent creators can learn from each other
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    Deepfake detection improves when using algorithms that are more aware of demographic diversity
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    Join the 60,000 who get the freshest future-of-journalism news in our daily email.
    From shrimp Jesus to fake self-portraits, AI-generated images have become the latest form of social media spam
    Within days of visiting the pages — and without commenting on, liking, or following any of the material — Facebook’s algorithm recommended reams of other AI-generated content.
    What journalists and independent creators can learn from each other
    “The question is not about the topics but how you approach the topics.”
    Deepfake detection improves when using algorithms that are more aware of demographic diversity
    “Our research addresses deepfake detection algorithms’ fairness, rather than just attempting to balance the data. It offers a new approach to algorithm design that considers demographic fairness as a core aspect.”
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