Los Angeles Times owner Patrick Soon-Shiong, who blocked the newspaper’s endorsement of Kamala Harris and plans to overhaul its editorial board, says he will implement an artificial intelligence-powered “bias meter” on the paper’s news articles to provide readers with “both sides” of a story.

Soon-Shiong, the biotech billionaire who acquired the Times in 2018, told CNN political commentator Scott Jennings — who will join the Times’ editorial board — that he’s been “quietly building” an AI meter “behind the scenes.” The meter, slated to be released in January, is powered by the same augmented intelligence technology that he’s been building since 2010 for health care purposes, Soon-Shiong said.

“Somebody could understand as they read it that the source of the article has some level of bias,” he said on Jennings’ “Flyover Country,” podcast. “And what we need to do is not have what we call confirmation bias and then that story automatically, the reader can press a button and get both sides of that exact same story based on that story and then give comments.”

  • Alexstarfire@lemmy.world
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    6 天前

    he will implement an artificial intelligence-powered “bias meter” on the paper’s news articles to provide readers with “both sides” of a story.

    Or, publish both sides of the story? You’re a publisher. Maybe I’m overcomplicating it.

    A media bias meter is more useful as a third party tool to rate various media outlets. Assuming it works. Which it’s “AI” so… hopefully at least better than a coin flip.

      • Nougat@fedia.io
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        5 天前

        “And what we need to do is not have what we call confirmation bias and then that story automatically, the reader can press a button and get both sides of that exact same story based on that story and then give comments.”

        Dude literally says “bOtH sIdEs”.

  • BougieBirdie
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    5 天前

    What tool are we going to use to measure the bias of the bias meter?

  • Steve@communick.news
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    5 天前

    I don’t think you really need AI for that.
    You can manually curate a list of phrases, and create a score for how often/many appear in a given story.