What AI owes the people who make content, and how to make sure they get paid. Each issue breaks down the deals, lawsuits and pricing moves shaping content’s value to AI, so publishers, labels and rights holders can protect what their work is worth.
YouTube Music now labels AI songs from partner declarations, but won’t say if labels affect payouts. Why rights holders should test the label, not trust it.
Read the issue →Meta’s new terms let it scrape and train on news sites tied to any business account, with no opt-out. Why publishers must map their exposure before October 30.
Read the issue →DOJ and Google agree AdX must open to Prebid but split on six months versus twelve. Why publishers should log their own bids before the monitor arrives.
Read the issue →SPUR reaches 80 members as the New York Times signs on and Google pays Reach on undisclosed terms. Why publishers should count AI use by one shared standard.
Read the issue →Disney bids $20 million for Character.ai’s IP and $180 million for its staff, but not its training data. Why rights holders should ask what that data was worth.
Read the issue →OpenAI lets DoubleVerify and IAS test ChatGPT ads but keeps pricing and reporting private. Why buyers and rights holders need their own record of where ads run.
Read the issue →USA Today Co. seeks more than $250 million from OpenAI over AI training. Why publishers need their own record of what was copied before the next lawsuit.
Read the issue →The US Copyright Office wants to size music streaming fraud. Why the industry needs one shared evidence standard by November 23, not a set of competing counts.
Read the issue →Publishers call AI licensing deals secret and lumpy as Google’s referral share falls. Why mid-size publishers need their own record of use to price deals.
Read the issue →The Third Circuit says training AI on Westlaw headnotes is not fair use and counts AI licensing as a market publishers can lose. What that means for deals.
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