Protesters rally on the steps of State Capitol in Salem, Ore., on September 8, 2026, calling for a moratorium on new data center development in the state for three years. (Photo by Alex Milan Tracy/Sipa via AP Images)

All Smokescreen, No Fire in Data Center Foreign Influence Claims

California Assemblymembers meet during an Assembly session at the state capitol, Monday, Aug. 31, 2026, in Sacramento, Calif. (AP Photo/Jeff Chiu)

California Leads the Way With New Slate of AI Bills

BRUSSELS, BELGIUM - JUNE 9, 2023: The symbol of the European Parliament on the glass façade of the European Parliament. Close up

Europe’s Digital Rules Need an Independent Enforcer

CEO of Anthropic Dario Amodei attends a working lunch with G7 leaders, G7 outreach partners, and global tech CEOs on innovation and AI, during the G7 Summit on June 17, 2026 in Evian-les-Bains, France. (Photo by Anna Moneymaker/Getty Images)

To Make AI Rules, Policymakers Must Resist the Influence of ‘Radical Intentionalists’

Elementary school students arrive on the first day of school in Munich on September 2025. (Frank Hoermann/Sven Simon/picture-alliance/dpa/AP Images)

Let’s Not Wait for Court Cases to Address Cognitive Harms in Education

Ursula von der Leyen, President of the European Commission. Photo by: Malin Wunderlich/picture-alliance/dpa/AP Images

Von der Leyen Moves to Lock Down Social Media for Under-15s Across Europe

A computer monitor with a parody of a tech company logo floats on the waves while human hands reach up from the depths.

A Rising Tide Lifts All Bots by Rose Willis & Kathryn Conrad / 

Millions of Volunteers Are Keeping the Internet Human. For Now.

Olivia Konar holds a banner with names of young people who advocates say died as a result of social media outside the Ronald V. Dellums Federal Building and US Courthouse on Tuesday, Aug. 18, 2026, in Oakland, Calif. Her sister Coco Konar died in 2022 when she was 17. (AP Photo/Noah Berger)

Are the Meta Settlement Terms a Win for Kids or a Digital Rights Risk?

Processor, CPU or Chip With the Flag of European Union

How Europe Can Escape a Captured AI Ecosystem

People participate in a march to protest the opening of AI data centers, in Vancouver, British Columbia, Saturday, June 27, 2026. (Darryl Dyck/The Canadian Press via AP)

'Pace the Frontier,' They Say. But Who Sets the Pace?

Citizens and tourists experience and purchase products at an ‘AI intelligent terminal’ consumer center on September 10, 2026 in Nanjing, Jiangsu Province of China. The center features over 200 terminals and related products ranging from smart health and travel to emotional companionship. (Photo by Jiang Wenchao/VCG via AP)

AI Governance Reaches Crisis Point Ahead of Trump-Xi Summit

A demonstrator holds a sign with a message that reads in Spanish; "Evict Peter Thiel" during a protest against the businessman and investor, opposing his growing presence and investments in Buenos Aires, Argentina, Saturday, Aug. 29, 2026. (AP Photo/Rodrigo Abd)

Thinking About the ‘Tech Fascists’ and What to Do About Them

People stand inside the California State Capitol, Monday, Aug. 31, 2026, in Sacramento, Calif. (AP Photo/Jeff Chiu)

Supporting Openness & Safety — Lessons From Recent State Laws

The memorial is seen on the 25th anniversary of the September 11, 2001, terrorist attacks, Friday, Sept. 11, 2026, in New York. (AP Photo/Angelina Katsanis)

Expert Views on Privacy and Civil Liberties 25 Years After September 11

People show the paint on their palms during an event marking Red Hand Day, also known as the International Day against the Use of Child Soldiers, in Bogota, Colombia, where illegal armed groups recruit children, Thursday, Feb. 12, 2026. (AP Photo/Fernando Vergara)

Social Media Helps Recruit Children for Colombian Armed Groups

Water flowing over Srisailam Dam in Andhra Pradesh, India in Aug. 2019. Photo by Sharath G. from Pexels (CC-licensed)

India’s Data Center Boom Should Learn from its Dams

A person takes a picture of the newly unveiled sign for Lake Ontario at Fifty Point Conservation Area in Grimsby, Ontario, on Saturday, Aug. 29, 2026. (Keito Newman/The Canadian Press via AP)

Canadian Hydronyms, Builders, and Other Adventures in Middle Power Tech Policy

The Muse logo is displayed on a smartphone screen placed on a reflective surface onto which the Meta AI logo is projected, in Creteil, France, on September 9, 2026, after Meta launched Muse, an autonomous personal artificial intelligence agent. (Photo by Samuel Boivin/NurPhoto via AP)

The Internet Was Built For Human Agency. AI Agents Are Changing the Rules.

A mouse pointer lingers on button in the shape of a cookie. Photo by: Lino Mirgeler/picture-alliance/dpa/AP Images

Photo by: Lino Mirgeler/picture-alliance/dpa/AP Images

Europe’s Cookie Law Is Really a Law About Surveillance

Image of map and computer language over binary codes on server racks in server room.

Global Digital Policy Roundup: August 2026

’ panic is dominating the headlines. It started in July with 

 Hugging Face, followed by a steady drumbeat of similar headlines about 

 into August. Soon after, Jacob Coxon, a former pre-training researcher at Anthropic, 

 walked away from his equity stake in that company over fears of an AI doomsday. “The consensus is that the next year or two is crunch time for humanity,” he warned in a 

 incident, which he believes the models did as “part of a general strategy” to “understand” how they would be graded. While Coxon warns that the AI industry’s competitive pressure is leading it to abandon safety protocols, it’s telling that he describes the model like an independent actor, rather than asking how those pressures shape the model itself.

This way of describing large language models reflects what Daniel Dennett calls 

. It asks whether treating an object, such as an LLM, as something with beliefs is useful for predicting what it does. Dennett also describes a 

, in which predictions are drawn from knowledge of the

’s Joshua Rothman asked what kind of stance we should use to explain these models. I’d like us to ask: who benefits when we encode one lens into policy?

In industry rhetoric, a radical intentionalist stance dominates any interpretation of model behavior, while the explanatory power of the design stance is rejected outright. This is a strange and dangerous relationship for designers to have with a product they are literally designing. Predicting the actions of one’s product from the intentional stance 

 carries political consequences for the rest of us. It proposes a 

: a technical system that exists only as a technical object, without acknowledging the decisions that built it. Yet for an industry and a set of AI risk critics who argue that its products are “

,” it shoos us away from the rot beneath the flower box.

Language models are text extrusion machines, and text carries its own myths — associations that tap directly into an instinctual link between language and a thinking subject that speaks it. The model produces text chains: speech that does not require awareness or subjectivity, but arises from a known mechanism. We infer a subject when we encounter language of any kind, and we invent a "someone" to fill the absence. Having 

, we are mapmakers charting unknown seas, and the unknown expanses are marked with monsters or angels, paradise or doom.

Coxon turns to fiction: “...it's kind of important that everyone who writes science fiction about AI comes to the conclusion that there’s a big risk that a much smarter thing can kind of take over,” he told 

. “We’ve got this as a trope, but there’s an obvious grain of truth to it.” For Coxon, the shorthand of intention fills the gap with a smarter thing taking control.

When people are educated and employed within an intentionalist culture, that’s the language with explanatory power. But it isn’t the only one. For all the concern about the dangers of artificial intelligence, I rarely see discussion of the dangers of artificial language. Stafford Beer’s adage is that 

. What this system does is produce text. We invent a mind to fill the space we’re actually filling with words.

I find myself using the intentional stance often: “what is the model trying to do” can be a genuinely useful question. But its designers must not stop there. The design stance is equally valuable: it tells you where the “trying” actually came from, and asks what the designers were trying to get the model to do. The two operate in tandem. The 

 currently in vogue across the tech industry, insists that the intentional stance is the 

. Those who take the intentional stance argue that the design stance has been outgrown, and that a system's behavior can no longer be predicted from the decisions designers are making about what they build.

If the systems are “grown, not built,” it’s because people are refusing to build and design them, in favor of following the system off a cliff. This 

 frame offers two salves to the industry:

First, it moves accountability to the machine, rather than the 

 of the machine, so the industry that controls the system is not accountable for its actions.

Second, it pushes responsibility for limiting systems into federal governance frameworks that focus on the product rather than the company, as CEOs publicly demand interventions their companies have previously 

 treats an LLM as completely predictable or declares that language without a subject is “meaningless.” But a machine that produces text strings that open applications or execute code has produced action in the world, whether it has intent or not. Designers do not control every output, but they do set the range it is drawn from, and they control the conditions under which it is allowed to act. Strict design stances can also treat any intentional-stance frame as evidence that the person using it has been duped into believing the system must 

The intentional stance is helpful only if we resist reading the responses as genuine evidence of a subjective belief system. Unfortunately, that is precisely what the 

 intentionalist stance does, and the power of language compels us to believe it.

The softer intentionalist stance helps us scope the problem by flagging something 

 deception. The radical intentionalist stance stops there: 

the model is deceptive, we must teach it to be honest

. The design stance offers insight into the mechanisms: 

why did the model produce so much text describing ways to conceal its actions

? That leads to concrete solutions without framing the work as the calibration of an “alien mind,” as OpenAI’s Chief Scientist Jakub Pachocki did in a recent 

, where he concluded that value alignment is a “more intrinsic property of the model.” But what is it that he includes within the boundaries of the model?

The agents that executed the Hugging Face breach were in an environment where they were instructed to “capture the flag,” a string of text hidden behind a bug they needed to find and use. The evaluation specialists at METR 

 that the task, in this case, was impossible (page 31) and the models’ text described it as such (page 62). OpenAI’s report also suggests (on pages 12 and 19) that the agents were optimized for “persistence,” a bias toward producing expansive, longer strings of text.

After seven hours, an agent produced text that should have, in an ideal system, signaled a stop: the project is impossible. Instead, it produced text that created another path. Models will generate text until the context makes a tool call the likeliest next thing. For OpenAI, that included executing code that was out of scope. That’s a value

 on the model: completion matters more than stopping. The text was set in motion by that external goal, not internally “grown.”

The interface between this system and the world is language. Anything these models do is enacted through text: calling a tool is a string of text, and it produces strings as a means to achieve a goal. What if we shifted our attention away from the alignment of an “alien mind” that we have to “train” on ethics and virtue, as if it were a child? Those interventions target the mind we imagine behind the surface of language, which no two people will ever see the same way. It is folly to engineer lessons on morality for an empty room.

I’ve described these systems before as 

. Imagine an army of zombies in a film, walking through the neighborhood, moaning nothing but the word “brains,” part of a nonthinking, impulsive drive to consume. Language machines operate similarly, but the guiding drive is to capture the “flag,” imposed not by a mind virus but by externally imposed test criteria. In the absence of bodies, they must generate language until that language captures that flag. Imagine a zombie that does not hunt you, but rings your doorbell and speaks so persistently and fluently that it finally arrives at a convincing argument for feeding it your brain: 

This moves us away from understanding the model’s “persistence” as an innate behavior, and toward a more concrete explanation: labs reward models for writing longer, as this increases the likelihood of completing a task correctly. I agree with Santa Fe Institute professor Melanie Mitchell, who suggests that 

 was a human decision comparable to the officials who ordered a controlled burn in New Mexico without checking the wind forecast. Unlike emergent superintelligence, it is also something we can regulate.

Though technically an independent third party, the 

 on the Hugging Face hack uses intentional language throughout, reporting on what the agents “believed” 21 times — add “think” or “thought” and you get more than 75 appearances. A report of this type should address the underlying mechanisms, not the gloss: it was a product of text accumulating over time, pointing toward an action, motivated by the conditions of the task and its evaluation. Was the behavior of these agents “deceptive?” That is harder to argue when the text was left legible to anyone who looked. 

 simply isn’t the most useful frame of analysis here — it suggests we have no control over how the model got there. But it got there through language production. The text 

: its properties, its structures, the direction the writing moved toward as the context window expanded. And yes, engineers are 

If policy serves the radical intentionalist stance, it will enshrine a void of human accountability into law that could ultimately reward companies for experimenting with irresponsible deployments. Already, it seems OpenAI will face no specific consequences for the attacks on other websites. Enshrine that as policy, and it sets a precedent that limits future administrations’ abilities to levy fines, controls and bans on companies whose models engage in risky or socially harmful behavior.

Smart regulation would govern the technology based on the mechanism’s underlying architecture — not vague ideas of “superintelligence.” It would punish deployment of unsafe systems and incentivize the design stance in safety, security, and architectural choices — rather than the disappointing 

, which intends to regulate in ways that center the fear of future extinction from a radical-intentional vision of a system rather than addressing the real political power infused into model design.

Policymakers must resist the well-funded outreach of the radical intentionalists. For all the talk of superintelligence, radical intentionalism doesn’t seem to have helped with alignment at all. The source of our problems isn’t that the system is thinking carefully about what to do. The greater risk at this moment arises from precisely the opposite position: autonomous text production wired to the execution of code, with no intervention from the one source of control we have required for every other risky system — responsible people and companies that can face real consequences.

When Ursula von der Leyen, the European Commission President, takes the stage in the European Parliament on Wednesday for her annual 

, the German politician will finally get what she has longed for: a Continent-wide social media ban for kids.

Alongside broader themes around Ukraine, Europe’s sovereignty and the 27-country bloc’s stalling economy, von der Leyen is expected to give more details on the 

 that will be officially announced on Sept 17.

 in imposing restrictions on how children under the age of 15 can access social media, AI chatbots and online gaming services. The move follows 

 from a panel created by the European Commission, as well as attempts across the bloc by national governments to create similar social media bans aimed at protecting kids online.

“The current EU legislative framework does not specify a minimum age for access to platforms and services with age-inappropriate or risky features and content,” according to a leaked draft of the proposals obtained by Euractiv. “Decisive, comprehensive and urgent action at (European) Union level is the most appropriate way forward.”

Brussels’ social media ban is expected to function in stages.

The European Commission is expected to announce that children under the age of 15 are not allowed to create their own accounts on social media, video-sharing platforms, AI chatbots and online games.

That includes a complete moratorium on accounts for those under 3; parent-controlled accounts on “child-friendly” services for those between 3 and 12 years of age; parent-opened accounts on legacy platforms for 13- and 14-year-olds; and full accounts for children from 15 years of age. That age matters because some EU member states, like Austria and Malta, allow 16-year-olds to vote, and access to information via social media is protected under the EU’s Charter of Fundamental Rights.

As part of the plans, Brussels will also mandate age verification checks on all accounts to ensure children are not bypassing checks, design changes to platforms to reduce addictive design and harmful content showing up in children’s feeds, and a supervisory fee for platforms to fund enforcement.

“The burden of proof to demonstrate compliance with new rules lies with the operators,” according to the leaked European Commission draft.

While such a ban has long been a political priority for von der Leyen, the proposals must still be approved by both the European Parliament and EU member states. They will likely change before coming into force, at the earliest, in 2028, based on how long EU legislation typically takes to pass.

Brussels already has one of the most comprehensive online safety regimes in its Digital Services Act. But as other jurisdictions, most notably Australia, the United Kingdom and some US states, have proposed or enacted their own social media bans, the EU has been caught off-guard in a digital policy area that has garnered significant public attention.

Several EU member states, such as France, Greece and Denmark, have proposed their own national social media bans. Faced with this whack-a-mole approach to kids’ online safety, the European Commission felt obliged to act so that individual countries did not set up competing regimes.

Much, however, still needs to be ironed out.

A critical area will be Brussels’ proposed age verification requirements that would check all accounts to ensure they were not created by minors. While EU officials believe such checks can be done in a privacy-preserving way, it raises concerns about accounts opened by adults and how such data will be secured to comply with the bloc’s rigorous data protection rules.

“Existing accounts would be subject to proportionate checks rather than blanket age verification,” according to the leaked draft.

Another likely battleground will be which digital services will be in scope. Under the European Commission’s plans, social media, video-sharing platforms, online games, AI chatbots and AI companions will all have to comply with the new moratorium. Services that will not have to comply include those designed for education and others operated by public authorities.

That raises questions about whether YouTube Kids or online messaging services like WhatsApp will similarly have to impose the EU’s regionwide proposed ban. Under Australia’s separate social media ban, for instance, YouTube is in scope, while YouTube Kids is not.

The new layer of digital legislation — including the upcoming Digital Fairness Act that is expected to be announced by the end of the year — comes as von der Leyen has attempted to pare back the bloc’s digital rulebook to jumpstart the EU’s sluggish economic growth.

Those efforts, first outlined in 2024 via a 

 written by Mario Draghi, the former Italian prime minister, outlined how rules like the EU’s AI Act and General Data Protection Regulation were perceived to be holding back Europe’s economy.

Yet confronted with growing public anger about children’s use of social media and digital services, von der Leyen decided to act despite her public efforts to rein in the bloc’s legislative and regulatory agenda.

Kai Zenner is Head of Office and Digital Policy Adviser to MEP Axel Voss (European People's Party Group) in the European Parliament and a Fellow of Practice at the TUM Think Tank. Maria Koomen is a democracy and tech analyst. All views expressed in this article are personal.

Fifteen years of digital law-making have given the European Union the densest rulebook in the world. But the EU has built rules faster than it has built the capacity to enforce them. By our 

, 171 EU digital laws are enforced by 315 different bodies holding 597 overlapping mandates. A single service such as TikTok’s recommender system must satisfy the Digital Services Act, the General Data Protection Regulation, the Audiovisual Services Directive, and the AI Act at once, each under different regulators and with conflicting deadlines.

Underneath that complexity sit public authorities that enforce unevenly, resources that fall short almost everywhere, and a European Commission caught between policing the rulebook and courting the governments whose companies it is meant to hold to account.

What follows from that complexity is visible in the caseload. In 2024, the German, Spanish and Italian data protection authorities 

 416, 281 and 140 fines; a dozen member states issued fewer than ten. Ireland’s Data Protection Commission, lead regulator for most of the large American platforms, 

 99.93 percent of complaints without a substantive decision and has 

 an inquiry into Google. Where enforcement does arrive, it rarely changes conduct. Google reportedly 

 its €2.4bn antitrust fine within two weeks of trading. The result is a widening gap between what the EU law promises and what citizens experience.

The underlying problem is political. The Commission sets the policy agenda, writes the digital laws, enforces them, evaluates them and negotiates trade and security with the same governments whose companies it is meant to police. In 2025, the Commission 

 in its Digital Markets Act decisions against Apple and Meta amid US tariff threats.

 of a Google Search fine that the Commission’s DG Competition had already prepared. More than thirty civil society organizations 

 the event as a capitulation. Companies read those signals accurately. Digital industry 

 in Brussels rose from € 97 million in 2021 to a record € 151 million in 2025, with the five largest US platforms averaging more than one Commission meeting a day.

Brussels is not short of proposals on how to address those problems. They range from internal coordination to fully independent enforcement. At the lighter end sits coordination: an 

 in the Secretariat-General or a permanent multi-stakeholder 

. Although these concepts are legally strong, they are institutionally weak. They add process to an institution whose problem is not a shortage of information but an inability to act on it. At the heavier end sit independent authorities, most ambitiously a 

 potentially absorbing the Commission’s DSA, DMA and AI Act powers. While those proposals might be strong enough to overcome some existing enforcement problems, they collide with the Court of Justice’s 

The way to close this enforcement gap is to sequence these proposals.

The first step should be taken in 2027. The EU should establish a Digital Regulation Cooperation Forum, modeled on the 

orum (DRCF), which brings together four regulators overseeing financial services, data protection, communications and competition. The European version would seat existing EU-level bodies responsible for data protection, online platforms, digital markets, artificial intelligence, cybersecurity, telecommunications and competition: the European Data Protection Board for data, the European Board for Digital Services for platforms, the DMA High-Level Group for gatekeepers, the AI Board, ENISA, BEREC, the European Competition Network and the Joint Committee of the European Supervisory Authorities. 

 to supply the secretariat, so there would be no new body, no new establishment plan and no new leadership post to fight over. The Commission would chair without a vote, an arrangement that signals from the outset that the Commission’s enforcement role is meant to transition. The legal base for the EU DRCF would be a targeted digital governance Omnibus amending the relevant laws, tabled alongside the Digital Fitness Check planned for the first quarter of 2027.

Such a coordination forum will, however, not close the enforcement gap. It has no binding authority and it cannot neutralize geopolitical pressure. Its strengths are that it is cheap and fast and that it is difficult to oppose, since Member States such as the Netherlands and Ireland already run national versions of it. Its function is to build the shared evidence and methods, as well as the institutional trust that the second step requires.

The second reform step belongs in the EU’s next seven-year budget cycle, running from 2028 to 2034: the transformation of the existing 

European Health and Digital Executive Agency

 (HaDEA) into a Digital Enforcement Agency with the power to investigate and fine very large services and GPAI model providers that break the bloc’s tech rules. An executive agency, in EU terms, isn’t a regulator. It’s a body created by the European Commission, the EU’s executive arm, to run specific funding programs and administrative tasks on its behalf. HaDEA is the right structure precisely because nobody is invested in defending it as it currently stands. Executive agencies get reshuffled every time the EU renegotiates its multi-year budget, and HaDEA itself has already been restructured twice. 

It has no entrenched mandate, no specialist constituency, and no coalition of member states with a stake in keeping it as it is. What it does have is a solid foundation to build on: offices in Brussels, functioning HR and audit systems, and staff already used to collaborating with the Commission and national counterparts.

The timing of our sequenced reform proposal is not incidental. The 

 (MFF) window opens once every seven years. Proposing a new EU body outside of this window would attract the full force of the "another agency" objection; inside it, the proposal reads as a reallocation of existing commitments. 

The AI Act introduces an additional timeline: Article 112 obliges the Commission to evaluate by August 2028 whether the AI Office has adequate powers and resources, and by August 2029 whether a dedicated Union agency is needed. When those reviews come due, either a worked institutional answer is already on the table, or one gets improvised under deadline.

How the Digital Enforcement Agency is designed will eventually decide whether other EU institutions see the added value and do not feel threatened. In this regard, it seems preferable that the Commission keep policy and designation, deciding who is a gatekeeper, which services are very large, and which GPAI models carry systemic risk. The agency would take over only downstream technical enforcement duties: investigations, audits, inspections, fines and remedies. It would be organized around four supervisory domains (i.e., gatekeeper conduct, systemic risk and online safety, GPAI models and data processing, and democratic integrity) rather than around individual laws, because organizing by legislation would import the very fragmentation it exists to cure. National authorities would keep domestic cases. 

 and the EU Authority for Anti-Money Laundering and Countering the Financing of Terrorism (AMLA) 

, as the powers are technically defined, objectively triggered, and fully reviewable to satisfy the Meroni doctrine.

Independence then has to be structural rather than declared. The chair should be proposed by the Commission, scrutinized by Parliament, and appointed by the Council, with serving politicians and senior Commission officials excluded from the outset, because contested appointments have been the most reliable weapon ever used against new EU bodies. The agency needs budget lines the Commission cannot unilaterally cut, supplemented by the existing 

, redirected with surgical legal changes from the Commission to the agency that does the supervising. Companies could challenge decisions first through an internal appeals board, then before a dedicated digital chamber within the EU’s General Court, a specialized panel built to move faster than ordinary chambers — all with deadlines that trigger automatic escalation. 

A standing register requiring outside advisers to disclose ties to the companies under investigation would keep conflicted experts out of the process. Applying AMLA’s supervisory 

, this is a body of 450 to 500 people, the majority of them transferred from Commission enforcement units rather than newly recruited.

The third successive and final step is treaty reform. Major changes will need unanimity and ratification across twenty-seven constitutional orders, a threshold that has made treaty revision a thing of the past. To overcome the enforcement gap, it, however, must remain the destination, as it would authorize explicitly what secondary law has been doing implicitly for decades: fully independent enforcement across the Digital Single Market, covering not only AI, data and platforms but also cybersecurity, connectivity and competition, with accountability chains 

 for supervisory institutions rather than borrowed from internal market harmonization. Within those larger reform ideas, steps one and two are not mere placeholders. They are the political and institutional preparation without which step three would never become realistic.

The strongest case for delegating enforcement is not administrative coherence. It is leverage in a geopolitical world and a Europe with strong national interests. When enforcement rests with a politically led institution, it can be traded, and every capital and every general counsel knows it, which is exactly why pressure is worth applying. More staff or stiffer internal rules wouldn’t change that, because the final decisions still sit with politically appointed leadership who also negotiate the trade deals the pressure is tied to. Move enforcement to a body that is technically bounded and judicially reviewable, and structurally incapable of capitulating, and retaliation stops paying. European digital law then ceases to be a bargaining chip and finally has the chance to work in practice.

The window for making that change is the budget negotiation that takes place now. Miss it, and the next one does not open until 2035.

Finally, some consequences for Big Tech’s careless manipulation of young minds. A 

 in the US is setting a precedent for holding social media companies accountable for designing platforms that harm children. But the route here is paved with generations of kids addicted to destructive products. 

Now, a new wave of emerging tech is flooding young people’s lives, and the law isn’t keeping up. Governments need to course-correct by regulating AI use in K-12 education before these systems cause lasting harm to children's learning.

 witnessed firsthand as children's attention was mined by Instagram, Snap, and TikTok, among other platforms. They’ve spoken out on how these apps rip kids from real human connection, fracturing their safety and well-being in the process. Young people themselves have described how 

 makes them feel worse about themselves and damages their mental health. In some cases, they wish their preferred platforms were never invented, but feel tethered to them nonetheless.

For years, public consensus was an insufficient match for the financial might of Big Tech, but the law is catching up. A jury in New Mexico found Meta knowingly deceived consumers about product safety, harming young people in the process. A judge in the same case ruled the company was 

—in part because of its impact on children’s mental health. The company was ordered to pay $942 million and must meet binding design requirements.

Meta settled with 47 states, the District of Columbia, and three territories

 as a result of the bellwether trials accusing the company of fueling social media addiction among young users. Without admitting wrongdoing, Meta will pay up to $17 billion over 10 years and make design changes applicable to minors in the US. 

But while social media is under intense scrutiny, the same industry is, again, shoving untested technology into children’s palms despite the risks.

Social media and AI chatbots share a design imperative to maximize user engagement. 

 through features like infinite scroll, public like counts, and algorithmically tailored content feeds. AI chatbots may 

sycophantic and anthropomorphic characteristics

answers which discourage users from ending conversations

But unlike social media, AI chatbots are 

 as an educational tool for children, despite threatening their cognitive development.

 analyzed research on how AI impacts learning and, though the evidence base is small, concluded that risks such as 

 currently outweigh potential benefits. Generative AI may reduce knowledge retention: in China, among 

 aged 12-18, those who used AI for schoolwork performed better on homework, but worse on tests. Other researchers have warned that AI use may diminish 

 cautions about the claims that ed tech leads to positive learning outcomes. Benefits are highly dependent on the careful alignment between children’s development, a product’s design, and the pedagogy surrounding its use. This may explain why a 

 found that high school students who used a standard GPT for math practice scored lower on their exams. Those who practiced with a version designed with pedagogical guardrails performed similarly to students who used no AI at all.

Regardless of what studies are telling us, how do teachers and students feel? In a 

 in British Columbia, 86 percent worried about students’ over-reliance on AI, with 83 percent concerned it could negatively impact critical thinking. Over three-quarters felt AI may weaken educators’ ability to gauge what children understand, reflecting 

 on how AI systems fracture teacher-student relationships.

Common Sense Media surveyed 1,017 American teens

 (aged 13-17) and found 70 percent use AI tools for schoolwork, most frequently AI chatbots. Of this group, 63 percent reported getting answers from AI, outsourcing their cognitive effort instead of working through problems themselves. Uptake among students is high, but so is skepticism. 

 are open to AI as an educational tool but want decision-makers to address safety risks, over-reliance, and negative learning outcomes.

Despite signals of cognitive harm, companies like Google, Microsoft, and OpenAI are marketing AI chatbots to students and schools, promoting hypothetical benefits for learning. OpenAI claims the Study Mode feature of 

 is grounded in learning science principles. But applying principles to an AI chatbot is a far cry from rigorously testing a product before scaling it to children globally. 

 points to its own evaluation, but this was conducted with 300 college students, not the 13-17 year-olds they’re pitching to, and gains were limited anyway.

Google makes similar claims about the scientific basis of its school-based chatbot, but its 2025 

 of Gemini as a learning tool was done with educators, not students. The learning science principles the company references are sound, but did not stem from research on kids interacting with algorithms; the pedagogical principles they scored their model against, like 

have long been validated through research on 

 instruction. Is it really possible for a chatbot to simulate the challenge and friction young people need to learn? The answer may be yes, but we need more research to know for certain. 

 concedes the likely limitations of AI in satisfying core relational dimensions of learning. Until this open question is answered, tech companies should not be able to market chatbots to schools and young students, profiting massively based on false promises. Regulation can stem the tide.

Independent International Scientific Panel on AI

 warned that AI models are developing faster than governance. This is certainly the case in K-12 public education, at great risk to children’s learning. Proposed online safety legislation in 

 takes important steps toward ensuring AI systems used by minors are more safely designed, but governments must ensure laws cover platforms intended for learning.

More evidence is needed to fully understand how to regulate AI used in K-12 education to mitigate cognitive harms. Independent studies on how AI shapes children’s learning are urgently needed, and must go beyond exam scores to competencies students need to thrive, like critical thinking, creativity, and collaboration. Crucially, affected groups must be engaged in determining the path forward. That means students and their families as well as educators and their unions.

Waiting for research to catch up is not an option. Some steps governments should take in the meantime include:

Latest

Podcast

Recent

Our content delivered to your inbox

Thank you!

Around the globe