The Meta Oversight Board finds the company's current methods for identifying and labeling AI-generated content are insufficient, especially during fast-moving conflicts where misinformation spreads rapidly. This conclusion follows a review of a fake AI video about the Israel war, with the Board warning the system relies too much on user self-disclosure and fails to address cross-platform content proliferation.
The Board calls for Meta to overhaul its approach by improving AI detection tools and establishing a clear, separate policy for AI-generated content. Key recommendations include scaling up the use of "High-Risk AI" labels and consistently implementing technical standards like C2PA to make content origins clear to users.
The main topics covered are the inadequacy of Meta's deepfake moderation, the specific risks during armed conflicts, and the recommended policy and labeling improvements.
Meta’s methods for identifying deepfakes are “not robust or comprehensive enough” to handle how quickly misinformation spreads during armed conflicts like the Iran war. That’s according to the Meta Oversight Board — a semi-independent body that guides the company’s content moderation practices — which is now calling on Meta to overhaul how it surfaces and labels AI-generated content across Facebook, Instagram, and Threads.
Meta’s deepfake moderation isn’t good enough, says Oversight Board
The board is calling on Meta to scale AI content labeling, including C2PA.
The board is calling on Meta to scale AI content labeling, including C2PA.
The call for action stems from an investigation into a fake AI video of alleged damage to buildings in Israel that was shared on Meta’s social platforms last year, but the Board says its recommendations are particularly relevant right now, given the “massive military escalations” throughout the Middle East this week. In its announcement, the Board says that access to accurate, reliable information is vital to people’s safety amid the heightened risk of AI tools being used to spread misinformation.
“The Board’s findings highlight that Meta’s current system to properly label AI content is overly dependent on self-disclosure of AI usage and escalated review and does not meet the realities of today’s online environment,” the Meta Oversight Board said. “The case also highlights the challenges with cross-platform proliferation of such content, with the content appearing to have originated on TikTok before appearing on Facebook, Instagram, and X.”
Recommended steps issued by the Board include pushing Meta to improve its existing rules on misinformation to address deceptive deepfakes, and establish a new, separate community standard for AI-generated content. Meta is also being asked to develop better AI detection tools, be transparent about penalties for AI policy violations, and scale AI content labeling efforts. The latter includes ensuring that “High-Risk AI” labels are added to synthetic images and videos more frequently, and improving C2PA (otherwise known as Content Credentials) adoption so that information on AI-generated content is “clearly visible and accessible to users.”
The Board says it’s concerned by reports that Meta is “inconsistently implementing” the C2PA standard “even on content generated by its own AI tools,” with only “a portion” of Meta AI outputs being properly labelled. Meta isn’t beholden to implement these recommendations, but they do align with concerns raised by Instagram head Adam Mosseri last year about the need to improve how authentic photographs and videos are identified on Meta’s platforms.
Meridiano
