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X is developing new AI transparency labels for posts, which will not only indicate whether AI was used to generate an update, but also how it was applied in each instance.
Michael O’Herlihy, X’s head of brand safety, shared some examples of these new labels during a presentation at the Brand & AI Safety Summit in New York on Tuesday.
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X is developing new AI transparency labels for posts, which will not only indicate whether AI was used to generate an update, but also how it was applied in each instance.
Michael O’Herlihy, X’s head of brand safety, shared some examples of these new labels during a presentation at the Brand & AI Safety Summit in New York on Tuesday.
As shown on these example screens, posted by Adweek senior tech reporter Kendra Barnett on X, X’s new AI content labels will include more detailed information on why a post was flagged for AI content. This will better explain the rationale X’s automated enforcement system is using, while also giving creators more opportunities to refute these labels by offering them a more detailed understanding of any potential concerns.
The hope is that these expanded notes will help X refine its AI detection process by prompting more creators to provide feedback on the specifics. This information can then be used to train the system.
At the same time, the tags will add more transparency for users, who may be less likely to re-share a post that’s been flagged for AI content.
O’Herlihy added that X increased its reliance on automated tagging of AI violations because it’s much faster. The automation should also ensure that more harmful content is refuted in-stream.
It could be a good way to enhance transparency in the AI era. However, false positives could also be problematic for creators, who could get annoyed if their content is unfairly tagged.
