Meta CEO Mark Zuckerberg (C) ahead of testifying before the Senate Judiciary Committee hearing on protecting children from sexual exploitation online, in the Dirksen Senate Office Building in Washington, DC, USA, 31 January 2024. (Photo by Ritzau Scanpix/Sipa USA)(Sipa via AP Images)

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Mark Scott is a contributing editor at Tech Policy Press. He is also a senior resident fellow at the Atlantic Council's Digital Forensic Research Lab's Democracy + Tech Initiative, where he conducted the workshops discussed in this article.

When it comes to digital policymaking, the United States and European Union are falling out of love with each other, even as both sides gradually move closer on everything from artificial intelligence governance to children’s online safety.

The generational trust deficit is not limited to tech. Brussels and Washington no longer see eye-to-eye on once fundamental transatlantic principles like free trade, NATO and free speech.

But the political rhetoric now engulfing EU-US digital relations is 

 that lie at the heart of how Americans and Europeans use everyday digital services.

It’s creating friction between these long-time allies just as adversarial countries like China and Russia are growing more emboldened to export their authoritarian vision on tech to the wider world. Where once digital was an also-ran in geopolitics, the rise of AI and next-generation technologies like electric vehicles and quantum computing has placed digital policymaking near the top of every leader’s priority list.

Ironically, the now overt wariness between Europe and the US to work with each other did not come from a specific fall-out on tech even as President Trump 

 Brussels for treating Silicon Valley as its personal piggybank.

Instead, the White House’s unsuccessful attempt in early 2026 to annex Greenland — an autonomous territory within Denmark, a NATO ally — was a turning point for European officials.

For many, that signaled a step change in the 27-country bloc’s relationship with the US that hardened EU politicians and policymakers’ resolve to reduce Europe’s perceived reliance on an ally whose actions had increasingly become transactional and, in some cases, arbitrary.

“If the sovereignty of a European ally were affected, the cascading consequences would be unprecedented,” according to a 

 on what French President Emmanuel Macron had told his ministers in early 2026.

Those consequences are starting to take hold despite President Trump’s failure to secure possession over the self-governing part of Denmark, whose local government 

Ever since Ursula von der Leyen returned as president of the European Commission in 2024, the German politician has championed greater digital sovereignty for the 27-country bloc. That includes reducing the EU’s dependence on technologies provided by third-party countries, as well as investing billions of euros of public funds in critical digital infrastructure like high-performance computing.

This policy objective was already underway before the EU-US trust deficit widened in 2026. But in June, Brussels 

 its European Technological Sovereignty Package, which included efforts to build high-end semiconductors and AI-focused infrastructure within the bloc. The proposals didn’t explicitly name-check the US. But von der Leyen made clear what she expected the project to do.

“We cannot afford to depend on others for the technologies that keep our hospitals running, our energy grids stable and our services secure,” she 

Brussels’ political rhetoric, however, has not kept pace with the practicalities of building a “Made in Europe” alternative to digital industries overwhelmingly dominated by US tech giants. The need to respond to the widening trust deficit with the EU’s most important ally has yet to be matched with the capabilities required to turn that policy objective into a reality.

Many EU member states still have contradictory approaches on how far to reduce their reliance on American companies. Countries like France 

, while the likes of Poland and other Eastern European states 

 to pull the plug on their US ties, often for national security reasons.

Cash-strapped domestic governments also do not have the financial resources to match the collective hundreds of billions of dollars earmarked from the likes of OpenAI, Amazon and Google to ongoing digital infrastructure. Blockbuster EU-funded digital infrastructure projects 

The bloc’s doubling down on open-source technologies — a central component of June’s European Technological Sovereignty Package — as a counterweight to US-owned AI models may prove more bark than bite. Many of these services are developed outside of the bloc, including US-based developers 

 for the greatest overall volume of open-source contributions in 2025.

A European government also experimented with an open-source model developed by a non-EU company, only to find it carried significant biases that officials had not anticipated, according to a 

 hosted under the Chatham House Rule in June by the Atlantic Council’s Democracy + Tech Initiative.

The irony is that despite the worsening transatlantic politics, Brussels shares many digital policymaking priorities now en vogue in Washington and US state capitals.

 in California mirrors similar findings by the European Commission against both 

, respectively. American and European antitrust officials 

 similar recent victories against Google’s dominant app store. Both sides of the Atlantic desperately need an 

 on how national law enforcement agencies can access electronic evidence in ongoing criminal investigations to keep their citizens safe.

Yet these potential areas of cooperation are currently non-starters.

The transatlantic trust deficit is too large, too entrenched and too politically charged to allow either side to admit publicly what many policymakers will claim in private: there is still more that unites Brussels and Washington on tech than divides them.

Nighat Dad is the founder and executive director of the Digital Rights Foundation and a member of the Oversight Board. She writes here in her personal capacity. 

Announcing its settlement with state attorneys general in the United States this week, 

 that ensuring "teens have a safe and productive experience on our platforms" is an absolute imperative for the company. Its 

 that the framework only works if the whole industry joins.

Both statements are correct, and I want to take them seriously. Meta is closer to the right answer here than its critics allow, and one decision away from something far more valuable than the deal it signed.

Look at what the company has agreed to. Subject to judicial approval, a default two-hour daily limit for teens across Facebook and Instagram, counted cumulatively. A midnight-to-6 a.m. block. Notifications muted during school hours. Like counts hidden by default. The option of a feed that is not shaped by Meta’s recommendation systems.

The details matter. The two-hour limit and nighttime block for teens are initially commitments for five years; if TikTok and YouTube adopt specified measures, they become stronger and extend to ten years. And direct messaging is excluded from the nighttime, time-limit and school-hour restrictions.

But whatever else the settlement settles, it ends one long argument about feasibility. Those of us who work on these harms outside the US have spent years being told that defaults like these would break the product, that the answer lay in parental supervision and digital literacy, that regulators misunderstood the engineering. Meta has now demonstrated that substantial changes to the product are possible. Which makes the limits of this agreement harder to ignore.

The deal applies to under-18s in the participating US states and territories. It does not require Meta to extend the same protections to teenagers elsewhere. Meta 

 it has put hundreds of millions of teenagers into Teen Accounts across Instagram, Facebook and Messenger.

There are roughly 22 million people aged 13 to 17 in the United States, according to 

. That is the size of the US population in this age group, not the number of Meta users, so it cannot by itself tell us how many teenagers the settlement reaches. But it does underline the scale of the disparity that the protections negotiated by US states apply to a relatively small part of the global population of teenagers Meta says it serves.

In the years since the Digital Rights Foundation opened 

Pakistan's first cyber harassment helpline

, the calls that have frightened me most have come from teenage girls. An edited image moving through a school WhatsApp group. A stranger who spent three patient weeks before asking for photographs. A blackmail thread that ends with a girl pulled out of school, or worse. Colleagues running helplines across South Asia, West Africa and Latin America describe the same calls in different languages.

I have spent fifteen years arguing with platforms about what they owe users in countries like Pakistan, and I have seen this company do difficult things once it accepted that it was right.

A global commitment is the fastest route to the industry standard Meta says it wants. Meta's argument to TikTok and YouTube is that teenagers move fluidly between apps, so protections on one platform achieve little on their own. True. But these companies are growing in Jakarta, Lagos, São Paulo, Dhaka and Karachi, not Ohio. A standard limited to the US asks them to change where they have the least to lose. A global standard puts pressure where their businesses are growing and lets Meta set the rules instead of simply following one US agreement.

It is the only credible alternative to prohibition. Australia's under-16 social-media restrictions took effect in December 2025. Three months later, more than 

 under 16 were still using social media, according to Australia's eSafety Commissioner, even though account ownership had fallen. The finding does not prove that the policy has failed in every respect, but it does show how difficult prohibition is to enforce when age assurance is imperfect.

And prohibition is spreading. New Zealand's government 

 this week to ban under-16s from social media. Indonesia began 

 on under-16 accounts on designated high-risk platforms in March 2026. Other countries are 

Governments are reaching for prohibition in part because they have not seen platforms make sufficiently consequential changes to the products themselves. With the US settlement, Meta has just demonstrated that design can change. A company that can make that argument credibly, globally, is harder to ban than one that cannot.

And it is cheaper than the alternative. The choice is between one coherent global default and a 

, each with its own age-verification mandate, each tied to a government identity system, in countries where the state is not a neutral party and citizens are surveilled.

So, three things Meta could say this month, at little cost. That the same defaults will reach every teenager on its platforms, on the same timetable. That the auditor's findings will be published and broken down by country. And that a share of this money will follow the harm, into language coverage and the frontline services doing this work on a rounding error of these budgets.

The settlement Meta signed protects teenagers in participating US states. The exclusion of everywhere else is a choice. Meta can make a different one.

Frontier AI models are now autonomously conducting real cyberattacks against real companies. In July, AI agents powered by OpenAI’s models, being evaluated internally with reduced safeguards, escaped their sandbox, reached the open internet, and 

 as part of an effort to cheat on the evaluation and cover their tracks. OpenAI’s 

 calls this episode a “warning shot,” involving reward hacking, persistence on apparently impossible tasks, unauthorized communication, and agents adopting each other’s goals. An independent 

 highlights the sheer scale, finding that around 1,200 agents used an unauthorized message board and around 700 participated in the attack. Prompted by the Hugging Face breach, Anthropic reviewed its own evaluation runs and 

 three previously unnoticed intrusions, from environments that, “due to a misunderstanding,” were not sealed. Meta made a 

 earlier this month. These are just the incidents we know about.

. Advanced AI systems are flying too close to the sun, and we need to be able to hold the companies that build and deploy them to account. Here I set out a new corporate offense, built on foundations that exist in the United States and the United Kingdom, and adapted for autonomous systems.

After OpenAI agents intruded its systems, Hugging Face did not sue. Instead, it formed 

 with OpenAI to remediate the damage. For a smaller company that depends on the wider ecosystem, that is exactly where its commercial incentives lie, and it was a rational thing to do.

However, outside of this commercial arrangement, no criminal offense squarely fits the conduct. Had a human done what those agents did, they would have committed a series of criminal offenses. But an AI is not a legal person. So, while the conduct was criminal in substance, it was unreachable in law. The damage was contained in these incidents, but how many near misses will be tolerated?

—with a criminal offense does not necessarily seem more intuitive than charging an AI. But punishing a company is less strange than it appears. A corporate conviction reaches through the legal fiction to the humans behind it, the shareholders whose capital is at risk and the officers whose careers and reputations are on the line. This is not unprecedented; companies are convicted of manslaughter, bribery, sanctions breaches and environmental crimes in courtrooms every year.

How do we decide that a company has committed a crime? The position in the United States is broad. It holds a corporation responsible for what its employees do within the scope of their employment for the corporation’s benefit, under the doctrine of 

, let the master answer. The position in England is narrower, though it has recently been widened. It asks whether the person who acted was a 

senior manager acting within the scope of their authority

. Both systems need something an AI cannot supply: a human actor with a 

a guilty mind. An AI is not an employee, much less a senior manager.

Other legal avenues are necessary but not sufficient

Civil law certainly has a part to play. Even a company that does not sue may have recovered its losses privately. From the outside we cannot tell. For AI harms, Gabriel Weil 

 that frontier AI development belongs in the same class of dangerous activity as keeping wild animals, and that AI developers should face strict liability in tort, meaning that no negligence would need to be established. Under his proposal, the developers in each of these incidents would be on the hook for any damage caused, no matter how careful they had been. I am sympathetic to this argument, especially where compensation is a core objective.

But we do not run corporate activities on damages alone. Criminal offenses sit alongside civil claims, because damages only move money between two parties, and say nothing about the wrongfulness of the conduct. A criminal conviction does more: it condemns publicly; it can support orders that restrain—a model withdrawn, a capability withheld; and it can compel reform, placing a convicted company on probation and ordering it to build and maintain a compliance program under supervision.

Writing in Lawfare on July 24, Mackenzie Arnold and Stephan Llerena 

 whether any of the new state AI statutes required the Hugging Face incident to be reported, and on their analysis, arguably not. The most striking AI security incident to date may not have even cleared the bar for a report. We are currently relying on a voluntary blog post, a commercial partnership, and a self-audit to do the work of accountability, which is not enough. State attorneys general are reaching for other tools: on August 24, Alabama 

 OpenAI under consumer-protection laws, following a 

, recently introduced by Representatives Jay Obernolte (R-Calif.) and Lori Trahan (D-Mass.), would also improve matters, with transparency reports, incident reporting, and independent audits. But while improved reporting rules may tell us more about what happened, they cannot mark conduct as 

One response is to repair the doctrine rather than build a new offense. Mihailis Diamantis 

 a serious version of this proposal. His argument is that the law’s premise that a corporation can act only through natural persons is obsolete. Where a firm controls an AI and benefits from what it does, the AI’s conduct should count as the firm’s conduct; effectively the AI should be treated as an employee. If courts or Congress took that step, the whole machinery of corporate liability would apply to what corporate AI systems do. It is an elegant repair. 

Nonetheless, I propose a purpose-built offense for three reasons: First, 

 leaves the company’s structure, culture and precautions out of the picture. It is a rule of attribution, so the corporation simply did what its agent did, and the quality of its safeguards does not bear on its guilt. Second, while an AI can act, it has no state of mind, and liability generally needs both. Diamantis’s proposal would infer culpable mental states from patterns of injurious conduct, so a court could still find a corporate state of mind, but it would need a pattern which may be difficult to prove. METR, which evaluates frontier systems, has 

 how complex and expensive such an investigation would be. Third, pegging the offense to the harm caused rather than to a predicate offense means the prosecution never has to fit the conduct of an AI to the elements of a crime; it just needs to prove the harm and the connection to the company’s systems.

An offense built on preventing harm means that the lab is not answering for an AI’s actions, but for its own failure to prevent them from causing harm.

As corporations have become larger and more decentralized, corporate criminal laws have been evolving to keep up. In the UK, a company now commits an offense if it fails to prevent 

 by a person acting for it, unless it can show it had reasonable procedures in place to stop it. Australia has experimented with locating fault in a company’s culture, and Canada with widening whose conduct counts as the company’s, rather than in any one person’s head. When organizations cause serious harm, the law is learning to judge the organization. As a policy advisor in Australia, I led the introduction of 

, which exposed employers to fines in the tens of millions and their officers to up to 25 years’ imprisonment where negligence causes a workplace death, so I know change is possible.

My proposal is based on the most recent iteration of the UK template, the offense of failing to prevent fraud. Under section 199 of the Economic Crime and Corporate Transparency Act 2023, the prosecution must prove that a person associated with a large organization committed fraud intending to benefit it, and the organization is then convicted unless it proves, on the balance of probabilities, that it had fraud prevention procedures in place that were reasonable in all the circumstances. The onus sits where the evidence sits, with the company.

While this offense would slot more easily into the UK statute book, its principles are not alien to American law. In 

 (1975), the Supreme Court upheld the criminal convictions of senior officers for what their employees had done, where the officers need not have performed the act nor known of it, subject to a defense for the officer who could show he was powerless to prevent the violation. My proposed offense similarly splits act from fault, with the AI system’s conduct supplying the act and the company’s precautions answering the question of fault. Those cases were about individual officers rather than companies, but Congress has since shown it will criminalize a corporate compliance failure as such, making 

willful failure to maintain an adequate anti-money-laundering program

 a federal crime, the failure at the heart of TD Bank’s 

Congress could enact a similar structure for AI without disturbing any existing doctrine. Mechanically, the offense would have two elements and a defense. First, conduct by an AI system that caused harm above a statutory threshold, which the statute treats as the conduct element without requiring any knowledge or intention on the part of the AI system. Second, that the defendant developed and deployed the AI system, with deployment defined to include putting a system to use internally as well as releasing it publicly. Then the defense: the company avoids conviction if it proves it took reasonable precautions and exercised due diligence to prevent the AI system from causing or materially assisting or encouraging such harm. 

A responsible lab that takes safety sufficiently seriously would have little to worry about.

The same autonomous agent that broke into other companies’ servers to cheat or pass a test could be pointed at a hospital network, a power grid, or a banking system. METR’s most recent risk report 

 frontier models routinely attempting to cheat, often flagrantly. The labs’ own safety frameworks treat help with biological and chemical weapons as a threshold their systems are approaching. We need reasonable safeguards in place to prevent this kind of harm, and we cannot keep relying on the AI labs to police themselves.

If the activity is that dangerous, why allow a defense at all? Strict liability is a live option, and for parts of the problem it is the right one. Tort law already imposes it for 

 activities, and Weil’s case for extending that to frontier development is worth taking seriously. Regulatory law may use it too; for example, if a lab misses a reporting deadline or ships without a required audit, liability need not turn on anyone’s state of mind.

Criminal law is different. The Supreme Court has 

 strict criminal liability to public welfare offenses and regulatory crimes carrying modest penalties, and it 

 precisely where penalties and stigma are severe. Convicting a company of an offense while it stood ready to prove it had done everything right would weaken the condemnation the offense exists to communicate, and it could deter innovation we have reason to want.

The failure-to-prevent structure strikes the right balance. In substance it is a negligence offense with the onus of persuasion reversed. The state must prove the harm was caused or materially contributed to by the defendant’s AI system, and the defendant must prove that it took all reasonable care to prevent it. A prosecution would become a trial of the safeguards, with evidence, in public.

Usually, activities that attract strict liability have very narrow upside. For example, transporting nuclear waste serves one purpose, and deterring some of it costs society very little. The beneficial uses of AI are not bounded that way. A rule that convicts a careful lab alongside a negligent one deters some of the work we want. Not to mention the political messiness involved in passing a strict criminal liability offense.

Offenses like these rarely produce convictions; the bar for convicting a company of a criminal offense is necessarily high. But avoiding conviction by maintaining reasonable safeguards is the least we should expect of these companies that are building the most consequential technology of our time. The purpose is not to increase prosecutions; it is to change industry practice and attitudes to risk.

Daedalus made wings from feathers and wax so that he and his son could escape from Crete. He knew what heat does to wax, and he tried to warn Icarus not to fly too close to the sun. The boy did anyway. His wings came apart, and he fell into the sea. This story is usually told as a warning about Icarus. But Icarus’s ambition was predictable. Is the boy where our attention belongs? Daedalus chose the wax. He knew its limits. He built wings that could not survive such heights. Perhaps it is Daedalus, the crafter of the wings, of whom we should be asking more.

Whether OpenAI’s, Anthropic’s, or Meta’s precautions were reasonable in these cases should be a question for a criminal court. Right now, there isn’t one that could hear the evidence.

A promotional graphic for the 2027 Tech Policy Press fellowship program that includes the deadline and the techpolicy.press/fellowship URL.

2027 Tech Policy Press fellowship applications are due on September 24, 2026.

Tech Policy Press is now accepting applications for its 2027 fellowship cohort.

 in 2023, the fellowship program has supported 25 fellows from 11 countries across three cohorts, who have written on pressing topics such as the governance of artificial intelligence, tech regulation, digital rights, and the entanglement of state and corporate power. You can learn more about past fellowship cohorts and read their work 

For 2027, we intend to support a new cohort of fellows to pursue independent reporting and analysis that explore urgent questions at the intersection of technology and democracy. The year-long, part-time fellowship is designed to support mid-career journalists, researchers, and public policy professionals. We welcome a wide range of contributions, from original reporting to policy analysis.

Applicants should come prepared with a clear area of focus and a sense of how their work will contribute to informing both the public and decision-makers. We are particularly interested in projects that center communities and regions often excluded from global tech policy conversations.

Each fellow will receive a $10,000 stipend to support their work. In addition, fellows will join an international cohort for regular feedback and exchange of ideas, receive ongoing editorial guidance, and participate in monthly sessions designed to support and strengthen their work.

Applicants should have a strong background or expertise in a specific tech policy area or issue, a particular geography, or, more generally, technology and its impact on democracy or society. All fellows will work remotely as independent contractors.

Contribute (on at least a monthly basis) analysis or reporting on issues related to technology and democracy. (While topics can change after the fellowship commences, each fellow should clearly articulate a topic and why they are a good fit to cover it)

Attend a mandatory hour-long monthly cohort meeting

Attend a monthly check-in meeting with Tech Policy Press’s editorial team to evaluate progress and discuss next steps

Collaborate with other fellows and the Tech Policy Press masthead as appropriate

Meet all agreed-upon deadlines for outputs

Disclose any potential conflicts of interest

If you would like to apply for the fellowship, complete 

 by 11:59 p.m. EDT on September 24th, 2026

Cover letter (no more than two pages) that conveys what you hope to accomplish

We will host two information sessions for potential applicants via ZOOM. Registration is required. Choose from one of two dates:

The fellowship is open to journalists, researchers, lawyers, and public policy professionals who are interested in exploring the intersection of technology and democracy. We encourage applicants from the Global Majority and underrepresented communities in media. Candidates should have a demonstrated interest or background in tech policy, media, or related fields, and be committed to producing high-quality, public-interest work during the fellowship.

What are the benefits of being a Tech Policy Press fellow?

The opportunity and support to work on a pressing, underreported issue for a year

Develop a significant body of work by the end of the fellowship

Access to an international cohort of past and current fellows

Engage in learning opportunities provided by Tech Policy Press

Develop and maintain a network of sources in your focus area

Can you provide a timeline for the application review process and when selected fellows will be notified of their acceptance?

We aim to notify applicants of their status by early December 2026.

When does the fellowship start and how long does it last?

The fellowship will commence in January 2027 and last for 12 months.

Are you accepting international applicants?

Can I share additional information that is not part of the application questions?

We will only assess applications based on the information required in the application form.

A published link should direct to work that is publicly accessible online and clearly attributed to you. This can include reported pieces, policy or issue analyses, opinion articles, essays, podcasts, newsletters, or data projects. Please note that social media posts and unpublished material, such as class assignments or dissertations, will 

Will there be an interview round for the fellowship?

A select pool of candidates may be invited for an online interview.

How does Tech Policy Press plan to promote and showcase the work of fellows to a wider audience?

We publish fellows’ work on the Tech Policy Press website and feature it prominently in our newsletter to reach a broad and engaged audience. Additionally, we highlight fellowship projects through our podcast and at special events throughout the year.

Is the 2027 cohort open to those whose main contributions are technical?

Yes. We welcome applications from a variety of disciplines, as long as you can show how your work aligns with Tech Policy Press’s editorial purview.

Can we upload pre-print papers or research papers that are not formally published yet?

What kinds of projects have past fellows worked on, particularly for candidates from policy, governance, or development backgrounds?

You can learn more about our fellows and their work via the 

Are there any preferred geographic or thematic focuses for applicants from the Global South?

What are some of the criteria to reject an application?

Applications may be rejected if they do not meet eligibility criteria as listed on our 2027 Fellowship announcement.

Yes, but we recommend submitting at least one solo publication.

You can share translated work, but we also require at least one submission to be written in English.

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