Twitter shares draft of its new deepfakes policy for public input through Nov. 27, says it won't ban deepfakes but will label them and warn users before sharing
but won't remove them Paul Sawers / VentureBeat : Twitter proposes flagging deepfakes, but would only remove content that threatens harm Kate Cox / Ars Technica : Twitter wants your feedback on its proposed deepfakes policy Adrian Potoroaca / TechSpot : Twitter is working on a policy to flag deepfakes Ryan Daws / AI News : Deepfake has Johnson and Corbyn advocating each other for Britain's next PM Makena Kelly / The Verge : Twitter proposes draft deepfake policies Ivan Mehta / The Next Web : Twitter wants your help to figure out its half-baked deepfakes policy Andrew Hutchinson / Social Media Today : Twitter Outlines Policy Plan for Identifying Deepfakes in Tweets Kritti Bhalla / Inc42 Media : Twitter Seeks Public Opinion For Draft Policy To Curb Fake News Duncan Riley / SiliconANGLE : Twitter releases draft policy on how it will handle deepfakes Kris Holt / Engadget : Twitter reveals how it plans to address deepfakes Maya Shwayder / Digital Trends : Is Twitter good now? Only if it can enforce its new rules Fabrizio Bulleri / Reclaim The Net : Twitter wants to know when it's right to take action against people who share “manipulated media” Chris White / The Daily Caller : Twitter Addresses Deepfakes Months After Media Pundits Melted Down Over Doctored Pelosi Video Elizabeth Culliford / Reuters : Twitter wants your feedback on its deepfake policy plans Victoria Song / Gizmodo : Twitter Wants the Hive Mind to Weigh In on Its Deepfake Policy David Cohen / Adweek : Twitter Releases Its Draft of Potential Rules Covering Deepfakes Matt Binder / Mashable : Twitter wants your help figuring out how to deal with deepfakes Shelby Brown / CNET : Twitter is trying to figure out how to handle deepfakes Shereesa Moodley / Memeburn : This is Twitter's new stance on ‘deep fakes’ Jason Aycock / Seeking Alpha : Twitter adding Topics, taking on ‘deepfakes’ Tweets: Fabio Chiusi / @fabiochiusi : “What isn't clear, however, is how Twitter will be able to detect the deepfakes published on its platform, given that detection techniques aren't perfect and often lag behind the newer and more advanced creation methods” https://techcrunch.com/... Alexios / @mantzarlis : Some of the questions @Twitter is asking of its users in this survey on deepfakes. (On the fourth set of questions, would love a “I don't have enough evidence to answer this") https://blog.twitter.com/... https://twitter.com/... Donie O'Sullivan / @donie : New this AM: Twitter is asking for public feedback on its proposed deepfake policy. Here's what the company is considering. Notably, but not surprisingly for Twitter, no suggestion they'll remove something just because it's false. https://blog.twitter.com/... https://twitter.com/... Greg Jenner / @greg_jenner : Twitter running a short 2 minute questionnaire on its potential new policy regarding how to handle misleading imagery & video content. Should they ignore, add a warning, or delete such content? Take the survey and let them know your thoughts https://twitter.com/... Thaddeus E. Grugq / @thegrugq : Answer the survey and tell them that false/misleading context is more common than false content. https://twitter.com/... Yoel Roth / @yoyoel : Today we're sharing our draft policy on synthetic and manipulated media — and want your feedback. Check the blog for more details, and tweet your questions and ideas using #TwitterPolicyFeedback. https://twitter.com/... Vijaya Gadde / @vijaya : Help us shape Twitter's policy on synthetic and manipulated media. Feedback due by 11/27. Details in the blog! https://blog.twitter.com/... See also Mediagazer
Context & Ripple Effects
This draft is Twitter opening the door on synthetic-media moderation before writing the rules: instead of a unilateral ban, it publishes the draft deepfakes policy for public input through Nov. 27, proposing labels, pre-share warnings, and removal only where content threatens harm.
It lands just ahead of a crowded field — weeks later Facebook took a harder line with a ban that critics flagged as riddled with loopholes around satire and simpler manipulations like the distorted Pelosi video, and Twitter finalized its approach in February with a harm-based rule. TikTok followed years later by expanding its Community Guidelines to cover synthetic and manipulated media.
First-order effects
- Users posting or resharing synthetic media will start seeing labels and pre-share warnings, with removal reserved only for content Twitter deems likely to threaten harm — a narrower enforcement scope than outright deletion.
- The Nov. 27 comment window gives researchers, civil society groups, and heavy platform users direct leverage over the final rule text before enforcement begins.
Second-order effects
- Facebook's competing deepfake ban turns the two platforms' choices into an A/B test of governance models — removal-first versus label-first — with each side's loopholes (satire exemptions, AI-only definitions) becoming the benchmark critics apply to the other.
- A label-based standard lowers the bar for other platforms to adopt synthetic-media policies without building full takedown operations, accelerating copycat drafts across social networks.
Third-order effects
- If the label-and-warn template holds across platforms — as TikTok's later guidelines expansion suggests — synthetic-media moderation consolidates into a shared harm-threshold framework rather than per-platform bans, shifting the battleground from whether to allow deepfakes to who decides what counts as 'deceptive'.
- Public-comment policymaking, if repeated, normalizes platforms drafting moderation rules in the open, inviting sustained regulatory attention to how consistently those rules get enforced.
The trend: Platform governance of synthetic media is converging from ad hoc bans toward harm-thresholded labeling frameworks, with Twitter's draft, Facebook's flawed ban, and TikTok's guideline expansion marking successive data points.