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Lawmakers pressed European Commission officials on Wednesday on why existing rules protecting children online are not being enforced, even as the bloc moves toward new legislation setting a minimum age for social media.

The European Parliament’s Internal Market and Consumer Protection Committee 

 that brought together representatives from Meta, BEUC (the European Consumer Organization), the Center for Democracy and Technology Europe, European Digital Rights (EDRi), DOT Europe and Kids Unplugged Belgium.

The session came ahead of an expert panel report, 

, that will advise the Commission on minimum age thresholds and platform design requirements for minors.

A Commission official said nearly all EU member states called for a harmonized European approach to children's online safety at a 

, reflecting political pressure that has also driven France, Germany and Belgium to introduce national measures in recent months.

A Kids Unplugged Belgium representative, describing a coalition of tens of thousands of families across Europe and the United Kingdom, called for an EU-wide minimum age of 16 backed by effective age verification, with no parental consent exemptions. She argued commercial incentives always push platforms toward the lowest permissible threshold, making opt-out carve-outs self-defeating. She also called for social media to be treated as a product requiring safety testing before being marketed to children.

Civil society representatives took a different view. One said age verification is routinely circumvented, carries privacy risks and shifts responsibility away from platforms. On age limits specifically, EDRi argued that banning children from social media at 14 or 16 and then releasing them into the same unregulated environment at 18 — with no experience navigating it — risks leaving young people less equipped, not more. The advocacy group said the opportunity to learn should not be taken away, and that adults have a responsibility to empower minors to live in the digital world that has been built for them.

A Commission official told the committee that the EU is developing an age verification architecture intended to be privacy-preserving, acknowledging that guidelines issued a year ago "deliberately" left verification requirements vague because the technology and political readiness were not in place.

The official explicitly cited Australia's experience — including regular exchanges with the eSafety Commissioner — as the reference point for why verification now has to be resolved. "If you haven't had an effective age verification, you're missing an important tool to actually effectively enforce," the official said, describing it as something that now "has to be tackled."

But the official also flagged Australia's limits. An eSafety Commissioner 

, the official said, showed "yes, they have an effect — but it's also massive circumvention," adding that the EU needs to design its approach to avoid repeating that outcome.

Several MEPs questioned whether the Digital Services Act (DSA), which already imposes obligations on platforms to protect minors, is being adequately enforced.

MEP from Italy Brando Benifei said enforcement has been "far too slow," arguing that platforms have had years to bring their systems into compliance and have not done so. He called for stronger coordination between national regulators and the Commission and for binding timelines on enforcement outcomes.

 into addictive design features and account settings. But the official also acknowledged that regulators, despite last year’s 

, “do not see enough, and that is why we [regulators] have to enforce.”The Commission official added that enforcement action is expected following the expert panel's recommendations.

When an MEP asked whether any investigations specifically target the DSA's existing prohibition on targeted advertising to minors, the Commission did not point to any. A Commission official described the ban as "indeed a prohibition" and said the Commission is "looking at whether we should also extend it to other operators" not currently covered by the DSA.

A representative from DOT Europe, an industry coalition representing major online platforms, said its members are already deploying screen time limits, family pairing tools, age-appropriate content settings and wellbeing prompts — and argued that the EU already has "a substantial and sophisticated legal architecture" in the DSA, GDPR, AVMSD and Unfair Commercial Practices Directive that, if enforced, would go far.

Its central concern was fragmentation, given France, Germany, Belgium and other member states are introducing incompatible national age verification systems, block lists and parental consent models that they said amount to "the fragmentation engine," particularly where national regulators classify entire services as harmful to minors outside the DSA's harmonized risk framework.

DOT Europe called on the Commission to enforce existing rules first and ensure any new proposals — including the Digital Fairness Act — do not duplicate or conflict with the DSA.

They also raised a point that some member states are actively discussing how to prevent online providers from scanning private communications for child sexual abuse material, making it legally impossible for platforms to detect CSAM in messaging. "Protection of minors also includes enabling online providers to search for sexual abuse material," they said. "This is currently not possible."

The Commission is expected to propose amendments to consumer protection rules before the end of the year, targeting attention-maximizing features such as infinite scroll, non-personalized advertising defaults for minors, and influencer marketing disclosure obligations. A Commission official said the proposals would be "coherent and complementary" to the existing DSA framework.

The expert panel report due July 13 is expected to shape those proposals. Several MEPs and civil society speakers said children themselves are largely absent from the consultation process, and called for their meaningful participation in decisions that directly affect them.

In early March, the former French ambassador to Israel, Gérard Araud, 

 an extraordinary, but fake, video of missiles raining down on Tel Aviv. Buildings collapsed. Infrastructure burned. Coming days after the first Israeli and US strikes on Iran, the footage seemed to capture Tehran’s devastating reply. Hundreds of accounts shared it. Tens of thousands watched.

 of AI-generated videos that flooded X during the conflict, and it fooled an ambassador. Examples like this explain why policymakers are increasingly alarmed by visual misinformation. France’s President, Emmanuel Macron, drove the point home last year by 

 deepfakes of himself, including as a rapper and a beauty influencer, to promote the Paris AI Action Summit.

But the obsession with deepfakes misses the bigger threat. A 

 from the International Panel on the Information Environment (IPIE), a Swiss-based scientific consortium of more than 500 researchers across 75 countries, finds that the most immediate and persuasive risk from generative AI is not visual. It is textual. The conclusion draws on 60 effect estimates from 24 peer-reviewed randomized controlled trials involving more than 33,000 participants.

The trend is striking. People are becoming harder to fool with AI-generated images. The cruder fakes give themselves away: the 

 of seven-fingered hands and the viral “Shrimp Jesus” have become objects of ridicule rather than belief. Recent studies show deepfakes are now judged as less credible than they were just a few years ago. Public awareness has bred a useful skepticism towards what we see online.

The opposite is happening with text. As large language models like ChatGPT have grown more sophisticated, false machine-generated text is now often perceived as 

 accurate, credible and believable than truthful information. The very tools we have learned to rely on for everyday queries are the ones we struggle to distrust when they mislead us.

This matters because text is cheap, scalable and easy to customize at industrial volumes. It is also being woven into the fabric of search, messaging and conversational interfaces — a deliberate push to embed the technology into everyday institutions before its full effects are understood. Worse, the IPIE’s findings may understate the danger. Most existing studies tested static text passages, but the conversational chatbots people increasingly rely on appear substantially more persuasive than static messages. Current estimates are likely conservative.

The message for policymakers and platforms is clear: they have been right to worry about deepfakes, but they cannot afford to overlook the quieter, more pervasive influence of AI-generated text.

The IPIE’s review points to one intervention that holds up consistently across studies: preventive corrective information. The idea is simple. Give people the knowledge and context they need 

 they encounter misleading content, not after.

In practice, this means brief explanations of how AI systems generate content, reminders that those systems can produce errors, and short prompts that nudge users to think about accuracy and credibility. Across the studies reviewed, these approaches deliver a small-to-moderate but reliable reduction in the perceived credibility of misinformation. The effect sizes (0.17 to 0.43 standard deviations) may sound modest, but applied at the scale of platforms with hundreds of millions of users, the real-world impact is substantial.

Content labelling is trickier. Labels flagging content as AI-generated or potentially misleading can reduce credibility, but their effects swing widely depending on design, wording, timing and source. A poorly built label can have no effect, or even backfire.

Labelling should not be abandoned. It cannot be treated as a plug-and-play fix either. It is a design problem, demanding rigorous testing, refinement and adaptation across platforms and audiences.

That cautious framing reflects a broader limitation worth confronting head-on. For all the strengths of the underlying research, the evidence base has serious gaps. It is overwhelmingly concentrated in the United States and Western Europe, leaving most of the world’s information environments effectively unstudied. Most experiments are run in controlled conditions, which may not reflect how people behave while scrolling a chaotic social feed. And the science is chasing a moving target: research cycles run in years, generative AI cycles in months. By the time a study is published, the threat it describes has often evolved.

Closing these gaps is essential if policy is to keep pace. Independent researchers need better and more timely access to platform data. Cross-regional, properly funded research must become a prerequisite for any policy claiming to work globally. Without that, public policy will remain reactive and incomplete.

The stakes are not abstract. Generative AI is already shaping public discourse from elections to public health. As these systems embed themselves further into our information ecosystems, their influence will only grow.

The question is not whether misinformation can be eliminated. It cannot, and never has been. The question is whether we can reduce its impact and harden the resilience of our information environment.

The evidence says we can. But doing so will require shifting our focus, expanding our knowledge base and investing in interventions that actually work. Above all, it requires accepting that the most significant risks are not always the most visible ones.

If we keep watching only for what we can see, we will miss what is already persuading us.

At the dawn of the internet in 1996, Congress adopted 

 of the Communications Decency Act (CDA), which generally shields online platforms from liability for content posted by their users. Europe soon followed suit. This deregulatory exemption from normal legal liability is widely considered to have made the creation of the modern internet with its many positive attributes possible. But by immunizing internet platforms it also allowed them to function as sources of disinformation, hate speech, political extremism and mental health risks for the world’s children.

Thirty years later, the reaction has set in. Countries around the world are 

 social media companies from offering their services to children. The Court of Justice of the European Union recently 

 legal protections in Europe, ruling that exemption from liability did not apply where an internet service provider uses an algorithm in respect of the information it transmits. Recent US 

 involving addictive designs and child exploitation have begun to bypass Section 230’s immunity by relying on product liability rules that punish social media companies for defective designs that harm children rather than for the content of their users’ speech.

Lawmakers should not want to repeat this mistake when it comes to AI. Lina Khan, then head of the Federal Trade Commission, 

 years ago there is no AI exemption from current law, and a useful part of any AI legislation going forward would be a ringing affirmation that AI companies are responsible for the products they produce. It is generally 

 that Section 230 does not apply to companies providing generative AI services, since Section 230 protects only user speech, not the content produced in part by AI companies through the models they provide to the public. Despite Section 230, court cases holding AI companies liable for 

 are underway, and one has resulted in a 

But judicial activity and calls for executive branch and/or state AI regulation beg the question of Congress’s role. We posit that Congress is uniquely positioned to reassure the American people that AI will be developed in accordance with existing consumer protection law, as well as protecting the public from catastrophic harms. Therefore, we propose that the US should adopt new laws affirming consumer protection law, as well as ensuring that cybersecurity, bioweapons risk and catastrophic harm are avoided. Focusing these new AI laws narrowly on catastrophic and consumer harm could incentivize broad bipartisan support, leaving for another day or different legislative vehicles other important public policy issues raised by AI including energy usage and possible impact on jobs.

The time to act is now because opposition to AI is growing in the US and because there is a competition between the US, the EU, and China on how best to regulate AI. In fact, a Spring 

 found Americans most concerned about AI compared with 24 other countries, and almost half of them had little or no trust in the US government to regulate AI effectively. Moreover, those concerns are not related to political attachment, which is very rare today.

We suggest two separate but complementary paths forward for AI legislation—one narrowly focused on AI frontier models and catastrophic risks and another focused more broadly on algorithmic decision tools and a range of consumer harms.

For example, the approach of national security and catastrophic risk reduction for frontier AI models is embodied in the bipartisan 

 introduced by Congressman Jay Obernolte (R-Calif.) and Congresswoman Lori Trahan (D-Mass.). The proposal 

 the Center for AI Standards and Innovation (CAISI) in the Commerce Department to develop voluntary standards and guidelines for frontier AI systems and provides annual appropriations $100 million for testing these systems. It also requires frontier AI developers to write and implement plans addressing risks prior to releasing new models. Like some state bills, it focuses on ensuring that AI models have been developed with “acceptable levels of mitigation of catastrophic risks.”

Senator Ron Wyden (D-Ore.) and Congresswoman Yvette D. Clarke (D-NY) have also reintroduced their 

 AI model deployers to conduct impact assessments and to attempt to eliminate or mitigate any negative impacts on consumers. A negative impact is defined broadly to include any “likely material negative impact that has legal or similarly significant effects on a consumer’s life.” The bill empowers the Federal Trade Commission to enforce these requirements.

These approaches differ in the range of AI systems they regulate and the harms they seek to prevent, but they are complementary and reinforce each other. In light of the public backlash against AI, Congress should act immediately to move both of them. Congress should also consider tightening up US export control law to ensure that administrations do not act 

 against individual companies, as the administration recently 

 in an export control order against Anthropic. But the immediate priority should be in avoiding catastrophic harm and reaffirming the applicability of consumer protection law in the AI context.

Would all this be enough to reassure the American public? Probably not. But it would be a start, especially if combined with other measures such as 

 to protect ratepayers against increases in electricity rates caused by AI data centers, and comprehensive privacy legislation. And because these measures would be laws, not Executive Orders easily rescindable at any time, they should have a useful impact on the public’s willingness to give AI another look.

Congress should make it clear to Americans that AI is not exempt from American consumer protection law. Companies remain responsible for the products they release to the public. Congress should begin its path to AI legislation by saying so.

of student essays produced in collaboration with the Berkman Klein Center for Internet & Society at Harvard University.

As a student in Beijing, I enjoyed the mundane conveniences that facial recognition technology provided. When I went to watch the China Open, the country’s premier tennis tournament, a cursory scan of my face produced directions to my seat. At Daxing International Airport, a small 

 scanned my face and displayed my gate, seat, and boarding time. On street corners, my face unlocked refrigerated vending machines from which I drank cold jasmine tea while several yuan were deducted from my AliPay account. In China, more than in the United States, artificial intelligence is an ambient feature of the commercial ecosystem, a lubricant for the minor frictions of everyday transactions.

Whether or not you find these applications of AI benign or troubling, notice that none were implemented by institutions that the public could vote out. The United States is now drifting toward its own version of undemocratic AI governance: today, the most consequential limits on the American government’s AI use appear not in statutes or regulations, but in the contractual terms of a single private company. Such contractual provisions, however well-intentioned, are insufficient to protect the American people against AI harms. They are undemocratic in origin, brittle in practice, and, most dangerously, a de facto substitute for the more robust protections that only public law can provide.

Harmful technologies seldom announce themselves; they arrive first as benign conveniences. Browser cookies, introduced in 1994 to save items in users’ carts between shopping sessions, later enabled consumer surveillance and 

. Facebook’s Like button began in 2009 as a way to show appreciation for friends’ posts; later, its descendants became the engine of a teenage 

. Aza Raskin, who created the infinite scroll in 2006 to create a more seamless user experience, deeply regrets an invention that now wastes 

 daily. Convenient technology can embed itself in daily life, only revealing its darker applications after millions have come to depend on it.

Congress’s abject failure to remedy, much less anticipate, these technological harms has led to an unreliable regime of industry self-regulation. Anthropic’s 

, which governs when its models are deemed too dangerous to deploy, has been criticized on exactly this ground. OpenAI has received similar criticism for changes to its 

 its “mission alignment” team. In 2023, seven leading AI companies voluntarily 

 at the Biden White House to conduct safety testing before releasing powerful models. By 2025, most of the seven had quietly 

But we are now seeing a different type of industry regulation—not of itself, but of its government clients. Call it “reverse regulation”: private firms dictating the terms under which public institutions may wield a critical technology. Generally speaking, attaching such use restrictions is 

. But we should hesitate when private firms use their leverage to dictate restrictions concerning the most fundamental questions of privacy and national security.

The standoff between Anthropic and the Department of Defense (DoD) is the starkest example. Anthropic, whose Claude model has become deeply integrated into military and intelligence systems, refused to remove two contractual 

: that Claude not be used for mass domestic surveillance and that it not power autonomous lethal weapons. Secretary of Defense Pete Hegseth 

 by designating Anthropic a supply chain risk (a label previously reserved for foreign firms like Huawei) and 

The public reaction split predictably. On one hand, 

 concerned about AI safety and civil liberties felt that Anthropic was “absolutely heroic.” On the other hand, many national security 

 that it was “a master class in arrogance and betrayal” and “a cowardly act of corporate virtue-signaling.” Both camps are missing a deeper democratic problem.

Set aside, for a moment, whether you agree with Anthropic’s substantive positions. (I do.) The prospect of the Trump administration employing AI for domestic surveillance is harrowing, and this essay is not an endorsement of Hegseth’s response; designating Anthropic a “supply chain risk” is a brazen abuse of power that 

, denounced. The question is not whether Anthropic’s red lines are sensible, but rather whose role it is to set them. In a democratic republic, it must be the people and their elected representatives—not a private company’s boardroom, however wise or well-intentioned.

When Anthropic attaches policy conditions to defense contracts, it makes a public policy decision that Congress otherwise might: determining, on behalf of almost 350 million Americans, what the United States military may and may not do with a critical technology. It is, of course, within Anthropic’s legal rights to set terms for its services. But unlike Congress, Anthropic’s leadership is unelected; it holds no constitutional mandate; there is no guarantee that its normative views will align with the public’s; and the public has no mechanism to hold it accountable for its stipulations to DoD.

Even in the absence of congressional action, the executive branch could promulgate 

 preventing the use of AI in autonomous weapons. The DoD’s failure to do so is itself a piece of information on which voters might base electoral decisions. This particular standoff did not suppress public attention; to the contrary, it produced a spectacle. But had DoD accepted Anthropic’s stipulations, voters would have been deprived of information about the Trump administration’s approach to military AI.

The problem with governing by contract is not merely that it is undemocratic, but also that it produces dangerously brittle protections of fundamental civil liberties. If Anthropic’s CEO or board changes, its contractual language might be quietly revised, leaving the American public without recourse. Anyone under the illusion that the company’s voluntary commitments are durable need only look at its stripped-down 

, “We didn't really feel, with the rapid advance of AI, that it made sense for us to make unilateral commitments…if competitors are blazing ahead.” Americans who believe they are protected from AI-driven surveillance are, in reality, protected only by the Anthropic leadership’s policy preferences. Worse still, those preferences are about to answer to public shareholders: Anthropic’s June 2026 IPO 

, at a valuation near one trillion dollars, makes maintaining a costly red line precisely the kind of choice that fiduciary duty disfavors.

More insidiously, private red lines displace the political urgency for democratic action in the long run. When private red lines do the work of public law, the political pressure that might produce more robust legislation may abate. Had DoD accepted Anthropic’s terms, they would have taken effect quietly. Yet, when a contractual provision quietly limits what a federal agency may do with a critical system, no one protests, no legislator convenes a hearing, and no vote is taken. The constituency that might ordinarily demand legislative action has less to gain by doing so.

Setting aside democratic concerns, contractual enforcement may well fail in practice. Anthropic almost certainly cannot monitor how the DoD uses Claude in certain classified environments. And if the DoD breached the contract, federal courts would be deeply 

 to enjoin a sitting president’s use of AI in military operations. Although the red lines exist on paper, the enforcement mechanism may be only the government’s good faith, which is precisely what Anthropic does not trust.

It is worth distinguishing Anthropic’s actions from conventional corporate political activity. When Exxon, say, lobbies Congress to favor fracking over environmental regulation, it advocates its narrow interests above the public’s. But Anthropic is claiming to do the opposite: It is acting in the public good to its own financial detriment. Amodei has written of his willingness to incur costs that “cut into our margins” because it “is the right thing to do.” That may sound nobler, but precisely because Anthropic claims to act for everyone rather than for itself, it supplants the democratic process more completely than any lobbyist does.

Many dissenters are pragmatic: Amodei’s red lines, they contend, are a sensible response to a dysfunctional Congress, and waiting for that Congress is fanciful. But the illusion of protection is more dangerous than its visible absence. History bears this out. In the wake of the Watergate scandal, the Church Committee 

. The public reacted, and Congress introduced FISA in 1978, which was 

 in 2008 after yet more domestic surveillance by the NSA was uncovered. Durable protections of civil liberties require public exposure, public outrage, and public law, even if they are born of a slow and imperfect process. Anthropic’s red lines are a substitute for that process, not a step toward it. Anthropic itself seems to recognize this point: in June 2026, when the government 

 it to disable its newest models, the company 

 that such limits belong in “a statutory process that is transparent, fair, clear, and grounded in technical facts,” which is to say, in public law.

It is tempting, when facing an administration as reckless as the current one, to cheer any institution that stands in its way. But the right response to democratic dysfunction is not to cede governance to private corporations. The more consequential a question, the more deserving it is of a democratic answer. Correct though they are, these red lines are not Anthropic’s to draw.

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