Starting August 2, the European Union will require companies to disclose when images, audio and text have been artificially generated or manipulated to look authentic, as the Guardian reports. The rules are part of the EU’s AI Act, and they could have a particular impact on publishers and other organizations that are increasingly using AI to produce content.

Under the new requirements, people must be told when they are interacting with an AI chatbot or viewing manipulated media. Synthetic content must carry a visible label as well as a digital watermark identifying it as AI-generated.

The rules apply to new AI systems entering the European market beginning August 2. Existing systems will have an additional four months to comply. And for publishers, there is another important provision: Text about matters of public interest must be labeled as AI-generated when there has been no human editorial oversight.

Companies that fail to comply could face penalties of up to €15 million.

There are some exceptions. Personal content is exempt, as are works that are clearly artistic, satirical or fictional. Labeling AI-generated content created before the rules took effect is encouraged, but not required.

The European Union says the goal is to make it easier for people to distinguish authentic material from synthetic content. The rules follow the June 10 publication of a voluntary Code of Practice on Transparency of AI-Generated Content, which lays out how AI providers and deployers can comply with the AI Act’s labeling requirements.

Sergey Lagodinsky, a Green member of the European Parliament, told the Guardian that the rules are about more than protecting the public.

“It is a matter not only of customer protection, it’s also a matter of democracy protection,” he said. “Making transparent this information is something which we need to preserve our democracy and the authenticity of facts online.”

But some technology companies and industry groups say the rules have become too broad.

The Computer and Communications Industry Association argues that guidelines issued in July expanded the definition of a deepfake beyond what lawmakers intended when they passed the AI Act in 2024.

“The label was meant to flag deceptive content,” said Boniface de Champris, CCIA Europe’s AI policy lead. “That distinction has been removed, so now almost everything gets labeled — a landscape in an advert is the same as a manipulated political speech… That doesn’t protect anyone, it just burdens commercial activity across the board.”

De Champris says the biggest changes may not be obvious on social media, where platforms already label much AI-generated material. He expects the rules to have more consequences for advertising, film and publishing — industries that are using AI at scale but do not always tell audiences when they do.

That could put news organizations and other content producers in the EU in a new position. AI-generated images, synthetic voiceovers and machine-written text about matters of public interest may now require disclosure under the rules. What was once a question of editorial policy could become a matter of compliance.

Some major technology companies have already taken steps in that direction. TikTok says it requires creators to label realistic AI-generated media and has labeled more than 3 billion pieces of content. Google says its SynthID watermarking system has been used on more than 100 billion images. And more than 180 organizations, including Google and Meta, have signed a voluntary code of practice supporting the EU’s transparency requirements.

Henna Virkkunen, the European Commission’s executive vice president for tech policy, says the broader rules are meant to strike a balance. She described AI as a “transformative technology” capable of bringing “extraordinary benefits,” while warning that the most advanced systems could create risks “on an entirely new scale.”

For publishers and other content producers, the next phase will be figuring out exactly where those lines fall — and what AI disclosure looks like when it becomes a legal requirement rather than an editorial choice.

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Thirty-seven hosts for home shopping network QVC voted Thursday to unionize with SAG-AFTRA, turning concerns over generative AI and the use of their voices and likenesses into a new front in the media industry’s growing labor battles. Only nine voted against the move, giving SAG-AFTRA roughly 80% support in a National Labor Relations Board election covering full-time and part-time presenters at the company’s West Chester, Pennsylvania, headquarters, according to The Hollywood Reporter.

The vote covers hosts who appear across linear television, livestream and shortform programming. While the bargaining unit is small, the fight behind it reflects a broader industry battle over a question becoming harder to ignore: who controls a performer’s image when companies can create synthetic versions of it.

SAG-AFTRA President Sean Astin framed the vote around that concern. “QVC, HSN and Omni Channel employees deserve fair compensation, AI protections and a stronger voice in decisions that affect their work,” he said in a statement, adding that the union’s 160,000 members are proud of the hosts for organizing.

QVC said it has historically preferred a direct relationship with employees but will “respect the outcome of the election” and begin working with SAG-AFTRA toward a first contract.

The organizing effort was driven in large part by concerns over generative AI. The Hollywood Reporter reported earlier this summer that hosts feared their images, voices and likenesses could be used without consent or compensation. In a petition delivered to management, the hosts said they “should have meaningful input into [their] role in the network’s future, and that this is best accomplished through a formal collective-bargaining process.” They also sought clearer standards around pay, promotions and job protections.

Those demands mirror the fight SAG-AFTRA already waged with Hollywood studios in 2023, when AI consent and compensation protections became central issues in the film and television contract that ended a monthslong strike. QVC hosts do not have the same bargaining power as scripted actors, but the underlying concern is similar: companies gaining the ability to create digital versions of a person’s face or voice without their permission.

The timing adds another layer of complexity. Qurate Retail Group, QVC’s parent company, filed for Chapter 11 bankruptcy protection in April after cutting 900 jobs earlier this year. The company is also shifting its business model toward live shopping on social platforms and streaming services as traditional linear television declines. SAG-AFTRA will enter negotiations with a company restructuring both its finances and its distribution strategy.

For other newsrooms and media companies leaning on on-camera talent, hosts, anchors, livestream personalities, the QVC case is a preview. As publishers experiment with AI-generated avatars and voice clones to expand content across platforms, the people whose likenesses power those systems are seeking contract protections before the technology gets ahead of them. The Media Copilot has tracked similar consent and compensation disputes emerging wherever generative tools touch a recognizable face or voice.

What QVC’s first contract with SAG-AFTRA ultimately includes on AI rights, consent and compensation could become a reference point for other retail media and livestream operations facing similar questions.

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The European Commission has published a voluntary Code of Practice on Transparency of AI-Generated Content, giving AI providers and deployers a concrete path to compliance with the AI Act’s labeling requirements—and a clear reason to sign up.

The code, released June 10, 2026, covers two broad categories of obligations. Section 1 targets providers of generative AI systems, requiring them to mark outputs—audio, image, video, and text—in machine-readable formats and ensure their detection as artificially generated or manipulated. The technical solutions must be effective, interoperable, and reliable “as far as technically feasible,” factoring in content type, implementation costs, and the state of the art. Section 2 targets deployers, requiring them to label deepfakes (audio, image, or video that falsely appears authentic) and disclose AI-generated or manipulated text publications on matters of public interest.

The Commission also released a set of standard icons that deployers can use to label AI-generated content. Nicholas Diakopoulos, a professor at Northwestern University, shared them on LinkedIn:

The code is currently under adequacy assessment by the Commission and the AI Board. Once it clears that review, signatories can rely on its measures to demonstrate compliance with Article 50 of the AI Act, reducing administrative burden and gaining legal predictability across all EU member states. Non-signatories will have to demonstrate adequate compliance individually, assessed case-by-case by national market surveillance authorities.

Signatories also gain access to Signatory Taskforces: working groups set up to share implementation practices and advance marking and detection techniques across the value chain.

The code is described as a “consistent, practical and proportionate” implementation framework, not a replacement for the AI Act or the Commission’s forthcoming guidelines on Article 50’s scope.

The code was developed over three drafting rounds between September 2025 and June 2026, led by an independent chair and vice-chair. Participants included AI system providers, detection developers, industry associations, civil society organizations, academic experts, and organizations with expertise in transparency and very large online platforms. International and European observers also contributed without voting rights. Two dedicated working groups handled the providers and deployers tracks separately.

Key milestones included a first drafting round starting November 5, 2025, a second round in January 2026, a third round in March 2026, and a closing plenary on June 10, 2026—the same day the code was published.

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Fake AI-generated videos of Venezuelans celebrating President Nicolás Maduro’s capture flooded social media this week. The clips looked real enough. But the more troubling part wasn’t how convincing they were.

It was who was sharing them.

As John Herrman writes in New York Magazine’s Intelligencer, Elon Musk widely shared and reposted the fabricated celebration videos to his massive following. That’s notable because Musk is “perhaps the best equipped in the entire world to know that they weren’t real.” He runs an AI company connected to a social network with a fact-checking system.

The old hypothesis about AI disinformation assumed bad actors would trick unsuspecting masses with realistic fake videos. The reality is stranger.

“They were passed around by a powerful person with a large following…for an audience of people who do not care whether they are” real, Herrman writes.

Even X’s own chatbot Grok got duped. Reuters reports the bot initially told users the video “shows real footage of celebrations in Venezuela.” It later acknowledged the video “appears to be manipulated” only after being challenged.

The clips served as what Herrman calls “ambient ideological slop for backfilling a desired political reality.” They weren’t meant to persuade skeptics. They gave true believers something satisfying to share.

This creates a new challenge for newsrooms. Traditional fact-checking assumes people want the truth but lack access to it. What happens when the audience treats reality as optional?

The answer may be sobering. AI disinformation isn’t primarily causing chaos or confusion. Instead, Herrman writes, it’s creating “a perverse form of order in which persuasion is unimportant, disinformation is primarily directed at ideological allies, and everyone gets to see exactly what they want.”

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Within hours of Nicolás Maduro’s arrest by U.S. forces, fake AI-generated images of Venezuela’s ousted president spread across social media faster than newsrooms could verify them.

The incident marks one of the first times synthetic imagery has depicted a major figure during a rapidly unfolding news event, according to a New York Times report by Stuart A. Thompson and Tiffany Hsu.

“This was the first time I’d personally seen so many A.I.-generated images of what was supposed to be a real moment in time,” Roberta Braga, executive director of the Digital Democracy Institute of the Americas, told the Times.

Some fake images made it into Latin American news outlets before being quietly replaced with an official photo shared by President Trump. NewsGuard, which monitors the reliability of online information, tracked five fabricated images and two misrepresented videos that collectively drew more than 14.1 million views on X in under two days.

The Times tested a dozen AI generators and found most tools, including Google’s Gemini, OpenAI’s ChatGPT, and X’s Grok, quickly created fake arrest images despite stated policies against misleading content.

Jeanfreddy Gutiérrez, who runs a fact-checking operation covering Venezuela, said the fakes spread through “almost every Facebook and WhatsApp contact” he has before official images were available.

“It just took a lot of work, because we always lose the battle to convince people of the truth,” Gutiérrez told the Times.

A pattern of failures

That battle is getting harder. The Maduro deepfakes emerged just days after Grok became the center of a global regulatory firestorm. Governments in the EU, UK, France, India, Malaysia, and Australia have all launched investigations after the chatbot began generating non-consensual sexualized images of women and minors at scale.

Bloomberg reported that Grok was generating thousands of “undressed” images per hour earlier this week. The official Grok account posted an apology on X, writing that it “deeply regret[s]” generating sexualized images of girls “estimated ages 12-16.”

If a major image generator can’t prevent the creation of child sexual abuse material, its safeguards against political deepfakes are likely just as porous.

Gutiérrez said many people refused to believe the official image of Maduro posted by Trump was real.

“It’s funny, but very common,” he told the Times. “Doubt the truth and believe the lie.”

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UK regulators are scrambling to contain a deepfake disaster unfolding on Elon Musk’s X platform. Ofcom, the UK’s independent regulator for communications services, made “urgent contact” with xAI this week after reports that Grok, the platform’s AI chatbot, has been generating explicit images of women and children without consent.

The tool reportedly put images of Princess Catherine, celebrities and ordinary women into sexualized contexts. Users discovered they could digitally undress anyone by simply tagging Grok in a post.

Journalist Samantha Smith told the BBC she felt “dehumanised and reduced into a sexual stereotype” after discovering Grok users had targeted her photos. When she posted about the experience, others asked Grok to generate more.

Technology Secretary Liz Kendall called the situation “absolutely appalling” and called on xAI to to “urgently deal” with its chatbot. She has also backed Ofcom to take enforcement action. The European Commission labeled the outputs “illegal” and “disgusting.”

xAI’s response to journalists has been an auto-reply. Many media organizations seeking comment from the company reported receiving auto replies that said only, “Legacy Media Lies.” But under pressure from regulators in the UK, EU, India, France and Malaysia, the company has issued reactive statements. X’s Safety account said it removes illegal content and works with law enforcement. Musk posted that users who prompt illegal content will face consequences. The Washington Post reported he also responded to one complaint with a laughing emoji.

Call it “breaking verification” instead of breaking news.

This crisis illustrates why the Reuters Institute’s 2026 predictions matter for newsrooms. Harvard Shorenstein Fellow Shuwei Fang told the Institute that news organizations will discover their next product isn’t content but process: answering “Is this real?” at speed.

When fake images spread instantly and AI tools generate convincing forgeries on command, audiences need trusted sources who can quickly establish what’s authentic. News organizations with verification expertise have a product the market desperately needs.

Law professor Clare McGlynn of Durham University told the BBC that X “could prevent these forms of abuse if they wanted to” but “appear to enjoy impunity.”

In a landscape where platform owners dismiss press inquiries as lies, journalism’s verification function becomes essential infrastructure.

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