Meta’s new AI deepfake playbook, More labels, fewer takedowns

Meta’s new AI deepfake playbook, More labels, fewer takedowns

Meta plans to implement a labeling strategy, provide context for manipulated media, and introduce a deepfake playbook to detect and mitigate AI-generated deceptive content on its platforms.

Implications for Misinformation and Elections

The initiative seeks to identify possibly deceptive material, which is important in a year marked by several international elections. However, only deepfake playbook that have disclosed their AI origin or have certain AI indicators will be labeled; this could result in some AI-generated content going unlabeled.

Shift towards Transparency

To give users more context, Meta places a higher priority on transparency than the removal of content. Instead of carrying out large-scale takedowns, the new strategy concentrates on contextualizing and labeling content to reduce risks while maintaining free speech.

In July, Meta intends to stop removing manipulated media based only on existing policies. This move is probably in response to legal demands brought on by impending elections and the EU’s Digital Services Act.

Oversight Board’s Influence

Meta’s policy was revised in response to the Oversight Board’s criticism, which recognized the need for a more comprehensive strategy regarding AI-generated and manipulated content. Less restrictive actions, such as labeling with context, are supported by the Board’s recommendations.

Expanding Labeling Standards

Meta works with the sector to create industry-wide guidelines for recognizing AI content. To give users additional context and information, the “Made with AI” label will apply to a variety of artificial intelligence-generated media, with an emphasis on high-risk content.

Content Moderation and Fact-Checking

About one hundred independent fact-checkers are employed by Meta to evaluate the possibility of manipulated content. False or modified content will be accompanied by informative labels and algorithmic adjustments to limit its reach.


As detailed in its deepfake playbook, Meta’s shift toward categorizing and contextualizing AI generated and manipulated media is a major step toward combating misinformation. By putting openness ahead of content removal, Meta hopes to provide users with the knowledge they need to determine the veracity of media.

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