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Access to an online social networking service provided by an online platform is prohibited for children under the age of fifteen.” By enacting those words into law on Tuesday, July 21, the French Parliament became the first legislative body in the European Union (EU) to adopt a 

 forbidding children under a certain age from accessing social media platforms. Since then, reactions have abounded, some praising the French initiative, others condemning it.

But going beyond the political fanfare, what does the ban entail exactly? Who will enforce it? And above all, how will it fit with a much-expected EU-level initiative?

What France has actually adopted and how it changed

France’s adopted bill is the result of multiple wrestling matches between the country’s two legislative houses on the one hand, and between the French legislators and the European Commission on the other hand.

Tabled by Member of the National Assembly Laure Miller in November 2025, the 

“[p]roviders of online social networking services operating in France shall refuse to register minors under the age of fifteen.”

 It also required these service providers to block access for all under-18s between 10.00 pm and 8.00 am, and to use age verification methods that would be in line with the 

 elaborated by Arcom, France’s regulatory authority for audiovisual and digital communication. Financial penalties in case of non-compliance could reach up to 3% of the given platform’s global turnover.

 – France’s highest administrative court – warned lawmakers that requiring social media platforms to deny access to minors under 15 could be seen as conflicting with the EU Digital Services Act (DSA), since Member States may not impose obligations on online platforms that go beyond the ones the DSA already foresees. In an attempt to circumvent that hurdle, MP Miller changed the wording of her bill so that the obligations would fall on minors themselves instead of platforms.

 also noted that the bill didn’t strike a fair balance between the best interests of the child and children’s fundamental rights, since neither the blanket ban nor the night-time curfew appeared necessary or proportionate. The National Assembly only partially took this observation into account, by getting rid of the curfew provisions but keeping the blanket ban for all social media platforms. The Senate, however, addressed the 

’s feedback more thoroughly. The version of the bill it 

 to the European Commission – let go of the blanket ban and introduced a blacklist of services that may not be accessed under 15. As for accessing non-blacklisted services, minors below that age would need parental consent.

of July 6, the European Commission did not expressly conclude that the under-15 restriction, the blacklist or age verification requirements are inherently incompatible with EU law. However, it objected to the bill’s enforcement architecture, noting that it would create a parallel national supervision and cooperation regime that overlaps with – and therefore breaches – the DSA’s harmonized enforcement framework. In its comments, the Commission also observed that although framed as a prohibition applying to minors, the bill could effectively require platforms to verify age and collect and authenticate parental consent, which may collide with parts of the DSA.

Following this blow from Brussels, and in a complete U-turn, French legislators stripped their bill of the blacklist approach to come back to the original blanket ban. They also removed the provisions entrusting Arcom with enforcement powers. This is the bill that became law on July 21.

In the end, the bill was so stripped of its substance that its final form resembles a shadow of its original. Crucially, it is especially defined by grey areas and uncertainty.

What we know is the law contains a ban that 

 to rest on children themselves. The list of what we don’t know is much longer. The law may – or may not – indirectly require social media platforms to put in place age verification solutions and guardrails to prevent underage users from accessing their services. It mentions neither a specific enforcement mechanism nor sanctions in case of non-compliance.

What happens if targeted platforms don’t comply? It’s difficult to say. By putting an obligation on users, French lawmakers aim to reconcile their main objective (forcing social media platforms to verify their users’ age) with the DSA – which prevents national regulators from enforcing that obligation on them. Still, the European Commission might consider that, since the bill indirectly implies that platforms must prevent access to children under 15, it clashes with the DSA. For now, EU officials have 

 from commenting on whether the French initiative is compatible with the existing European framework.

The bill’s relationship with the EU’s competencies and structures is still less clear. Some observers 

 it as “entrusting the European Commission with overseeing its implementation.” Still, it is hard to imagine a world in which the European Commission would let Member States adopt their own age limits to access social media platforms, then take on the responsibility of potentially overseeing the implementation of these virtually 27 different regimes.

Another, more plausible, interpretation would be that French authorities report any breach of its law to the European Commission, which then may use these notified breaches as part of its own investigations. This could perfectly fit, for instance, into the investigations currently under way concerning 

’s platforms, Facebook and Instagram, and 

. However, this doesn’t sound like a major improvement from the current cooperation framework the DSA provides.

More importantly, it seems like French lawmakers have learned little from the Australian experience. 

 indeed shows that in Australia, where a social media ban for under-16s is in place since December 2025, more than 85% of underage users are circumventing that measure.

One can legitimately expect the same to happen in France. The likelihood is high that France’s age restriction law ends up, in large part, ignored. Add to this the fact that the legislation does not address platforms’ harmful features, and France risks ending up with a largely symbolic law that shifts responsibility onto children and parents, while allowing platforms – and their harmful designs – to continue operating unchanged.

There is, however, one thing the French initiative achieved: putting political pressure on the EU to take action. By taking on this legislative process and convincing 

 to do the same, French decision-makers pushed European Commission President Ursula von der Leyen herself to take the matter into her own hands. 

On July 13, the Co-chairs of the Special Panel advising her on online child safety delivered their 

. Besides recommending a ban under 13 – which, notably, is already what should be in place if platforms actually implemented their own terms and conditions –, the report gives center stage to safety by design. That is, addressing the digital services’ designs and features by imposing limits on infinite scroll, autoplay, push notifications, and problematic recommender systems. Interestingly, it also proposes to shift the burden of proof to online services providers: until they demonstrate that their services are safe for minors, age restrictions should apply. Which is exactly what the French bill fails to achieve.

, will the Commission go for this “product safety approach,” which is slowly but surely gaining traction in Brussels? It remains unclear But the coming months will definitely show whether Europe has learned from the French experience – or whether the political appeal of a headline-grabbing ban will once again prevail over evidence, enforceability and meaningful platform accountability.

Back in March, the National Medical Products Administration (NMPA) of China 

 a brain implant for people with spinal cord injuries for commercial sale. Shanghai-based 

 that sits on the dura mater – the outermost layer of the brain. It has eight sensors that decode neural signals in real time. 

 is paired with a pneumatic robotic glove, allowing patients with C2-C6 cervical spinal cord injuries to regain some hand motor function. This is the first invasive motor brain-computer interface in the world approved for routine clinical use outside a clinical trial.

What happened next is arguably more significant than the approval itself. 

, China's National Healthcare Security Administration (NHSA) assigned the device a reimbursement billing code. That speed highlights something broader than regulatory efficiency: China has been building the administrative infrastructure needed to commercialize neurotechnology long before the first product reached the market.

China's investment in neurotechnology reflects 

 to move up the value chain: from a manufacturing-led economy toward one driven by high-value innovation. BCIs align with several national priorities: improving care for an aging population, strengthening China's domestic medical device industry, and building capabilities in adjacent sectors such as AI, robotics, and advanced semiconductors. Against that backdrop, it is less surprising that China has also invested in the regulatory and reimbursement infrastructure needed to bring these technologies to market quickly.

NMPA's approval mechanism for speed comes from its 

Innovative Medical Device Special Review Procedure.

 To qualify, an applicant must hold a Chinese patent over the device's core mechanism and demonstrate that the product's primary working principle is first-in-China. Eligible devices get priority testing and evaluation. In 2024, innovative devices were approved through the procedure in an average of 180 days, roughly half the standard review timeline. That's faster than the equivalent US FDA mechanism even in its best case, which would average 

On the reimbursement side, NHSA didn’t just happen to develop billing codes a couple of days after NEO was approved; the agency built the pricing infrastructure before there was any commercial BCI product in the market (and a year before the NEO device was approved). Chinese medical service pricing is organized around technology and procedure categories rather than named products, and NHSA has a 

for defining those categories through expert consultation even before any specific device exists to fill them. Once NMPA clears a product, it just needs to be slotted into an already-defined pricing category, which is why NEO could be assigned a billing code within 48 hours of approval. In other words, the approval was the final step in a reimbursement framework that had already been designed.

In the United States, the Food and Drug Administration (FDA) regulates medical devices, including BCIs. While there is no BCI-specific pathway, developers may receive expedited interaction with regulators through programs such as the Breakthrough Devices designation, which is intended for technologies addressing serious or life-threatening conditions. This grants more frequent, structured engagement with agency reviewers for technologies treating life-threatening or irreversibly debilitating conditions, resulting in shorter BCI approval timelines.

CorTec received Breakthrough Device Designation

 for its Brain Interchange System, a closed-loop implant that reads and stimulates the brain to support motor recovery in chronic stroke patients. Breakthrough Device Designation isn't an approval nor is it a shortcut around the FDA's evidence standards. Devices still have to go through the same full 

review as anything else. What changes is the process around that review: designated devices get priority placement in the review queue, dedicated senior reviewers, and more frequent structured meetings with FDA staff throughout development, rather than the more limited, scheduled touchpoints companies get by default. Closer and earlier FDA engagement lets a small team catch a flawed trial design or an insufficient evidence package months before a rejection would otherwise surface those issues.

However, this only speeds up the device approval process. The US, unlike China, does not have a cohesive or efficient pathway to determine coverage for BCI medical devices. However, soon after the approval of and billing code assignment for NEO, the US Centers for Medicare and Medicaid Services and the FDA jointly announced something called 

. It aims to synchronize FDA market authorization with Medicare national coverage determinations for Class II and Class III Breakthrough Devices.

Both countries have demonstrated that they can accelerate regulatory review for promising BCIs. The difference is that China also built much of the reimbursement infrastructure before the first commercial product existed. The US is now reactively building that infrastructure. Regulatory approval allows a device to be sold. Reimbursement determines whether hospitals adopt it and whether patients can realistically access it.

Beyond approvals – the governance questions that remain

Both approval processes answer one question: is this device safe and effective for its intended medical use? Neither touch on what distinguishes BCIs from most medical devices: their ability to collect and increasingly interpret neural activity.

As decoding algorithms improve, those signals may reveal increasingly rich information about movement intentions, emotional states, cognitive impairment or other aspects of mental activity. While today's clinical BCIs remain task-specific and cannot "read thoughts" in the science fiction sense, 

 that neural data deserves special treatment because it is both biologically intimate and increasingly valuable as artificial intelligence models improve.

Neither approval process is designed to determine who controls neural data after collection; whether it may be reused to train AI systems; how long it may be retained; whether inferences derived from neural activity deserve protections beyond ordinary health information; or whether individuals should have distinct legal rights over their brain-derived data. Those questions largely fall outside the scope of traditional medical device approval and remain only partially addressed by existing privacy, data protection and health laws.

 that focuses not only on device safety, but also on frameworks that protect mental privacy. 

 has argued that existing regulatory systems were built to evaluate medical devices rather than govern the broader societal implications of brain-computer interfaces, recommending a combination of standards, corporate governance, and international coordination while more comprehensive legal frameworks develop. Right now, there is 

 that protects neural data. Otherwise, neurotechnology continues to be governed through a patchwork of medical device law, privacy law, cybersecurity requirements, research ethics, and general data protection legislation.

Closing that gap doesn't require waiting for a comprehensive federal neurorights statute, though. It needs infrastructure and coordination models regulators have already built for other purposes, earlier in the process than they've been willing to so far.

NHSA's approach to NEO worked because the pricing categories already existed before the device did. CMS could take the same posture toward neural-data-generating devices generally: defining technology and procedure categories in advance of specific product approvals, rather than building coverage pathways reactively once a device has already cleared FDA.

The harder gap is that FDA's device approval was never designed to touch data governance in the first place. However, there is precedent in place: FDA and CISA have coordinated on medical device cybersecurity 

 since 2018. That model could be widened rather than reinvented by bringing the FTC and HHS into the existing FDA-CISA structure, so that neural data reuse, retention, and AI training rights are governed by the same kind of standing coordination that already exists for device cybersecurity.

Consent is the piece closest to patients directly. Right now, a single signature at implantation typically covers clinical use, research use, and any downstream commercial or AI-training use of a patient's data; three decisions collapsed into one moment. Separating them would let patients consent to each independently. And because BCIs collect data continuously over months or years, unlike a single scan or blood draw, consent arguably shouldn't be a one-time event either; patients need some mechanism to revisit or revoke it as collection continues.

None of this requires Congress to first agree on what neural data is in a legal sense. Speed is not the part of this story the US (or other jurisdictions) need to copy. Rather, it’s foresight. China built reimbursement infrastructure before a product existed to use it. Regulators can do the same for the reimbursement and data questions, if they start now instead of after the next approval.

Elise Silva, PhD is the Director of Policy Research at Pitt Cyber; Beth Schwanke, JD is the Executive Director of Pitt Cyber; and Joy Ruff, AICP is the Executive Director of Local Government Academy.

Downtown Dormont Borough, PA. (Photo credit: Local Government Academy)

Local government is the layer of government Americans encounter most often, running everything from public safety to parks to permitting. Yet the vast majority of research and policy action on artificial intelligence targets federal, state, or large city governments. Consider the 

, for example: of its 2,555 municipalities, nearly 90 percent have fewer than 10,000 residents. These are the boroughs, townships, and small cities where a handful of employees manage everything from procurement to payroll. Small governments touch millions of Americans' daily lives but are far harder to study than their larger counterparts.

This gap matters. The policy frameworks and guidance now taking shape assume staff and budgets that these small governments just don’t have. For the past year, the 

Institute for Cyber Law, Policy, and Security

 (Pitt Cyber) at the University of Pittsburgh has partnered with the 

, a nonprofit that provides nonpartisan education to local governments in Pennsylvania, to find out 

The 35 respondents to our recent survey, mostly senior staff from townships and boroughs serving 5,000 to 20,000 residents in Pennsylvania, offer a small, self-selected sample. Their responses do not present a national picture but do provide meaningful ground-level data on a population few studies are reaching, offering clear direction for how policy researchers can help smaller local governments implement AI responsibly.

Among our respondents, AI use is already common, but basic governance hasn't caught up. Two-thirds said they use generative AI tools at least monthly for work. More than half reported their workplace had rolled out enterprise tools like Microsoft Copilot, yet more than a quarter said they were also using personal, free accounts like OpenAI’s ChatGPT for work tasks (a detail that should concern anyone thinking about data security in government settings). Despite that level of use, the majority of respondents have no genAI policy at all, yet more than half of those without a policy said it would be valuable to have one. As these responses show, the demand for guardrails is real.

Leadership attitudes may help explain the lag. About one fifth of the respondents said their leadership was actively encouraging AI exploration and adoption and another quarter said their leadership was supportive but not actively promoting AI use. Around two-fifths–the largest group–described their leadership’s position as neutral or unclear, and only two respondents to this question said leadership actively discouraged use. A similar number reported conflicting signals from their leadership. As in other sectors like education, AI 

. It is often slipping in through the cracks and is being used alongside already-established workflows, rather than being put in place to intentionally disrupt those workflows or being directly procured. While using AI may be as simple as opening a browser, governing it responsibly requires substantially greater organizational capacity. That reality, compounded by the absence of policy resources, may be why leadership sits in neutral. AI has spread differently from earlier technologies, most often arriving through individual use rather than institutional decision.

So, what are people doing with these tools? As of the summer of 2026, mostly writing, summarizing, and taking meeting notes. Well over half cited these productivity tasks as their primary use. Notably, a handful of the respondents mentioned surveillance and identification. While a minority, with the possibility of no policies in place and personal accounts in place, their concern is worth noting.

Asked what excites them about AI, respondents pointed to efficiency gains, data analysis, and accessibility improvements. But they were equally vocal about what worries them: data privacy, loss of human connection, confidentiality, bias, and legal exposure all came up in open-ended responses. The trade-offs between the gains and the risks associated with these tools were well recognized by local government employees.

And what do these employees need given these realities? One finding was unambiguous: they want training and support to use and govern these tools. Half of the respondents cited a lack of staff expertise as the biggest barrier to responsible adoption, ahead of budget constraints at thirty-eight percent. Training, policy guidance, and data security concerns followed closely behind. When asked directly what kind of support would be most useful, respondents were clear: they wanted to see how peer governments in their own region are using AI and basic training on using these tools for everyday office work. A formal report or written guidance ranked well below live peer-to-peer learning. Local governments do not want another framework. Instead, they want to talk more to each other about what worked, what didn't, and why.

This does not contradict the case for policy research and artifacts; rather, it clarifies what would be most useful for smaller governments. Much of the current conversation about public-sector AI—procurement standards, model evaluations, pilot programs in major cities—assumes a level of staffing and budget that smaller governments simply do not have. Our survey suggests that what these governments want is more basic and more local. They would like help writing a use policy, straightforward training, and examples from governments that look like their own. One way to meet this need is activating networks that are already positioned within civil and public society, including state municipal associations, councils of governments, universities, and regional nonprofits like the 

. These organizations are positioned to translate best practices into locally applicable guidance, and to convene the peer networking and collaborative learning that respondents asked for.

Small jurisdictions like those represented in our survey make up the overwhelming majority of American governments, yet they get the least attention in AI policy and governance. Our data—while limited—shows use running ahead of rules to guide it. We worry that if adoption keeps outpacing governance, the potential costs from compromised resident data to biased outputs to eroded public trust, will land on the governments least equipped to absorb them.

Amber Sinha is a contributing editor at Tech Policy Press.

In early 2020, as demonstrations against the Citizenship Amendment Act (CAA) 

, I was on a Delhi Metro train heading toward Central Delhi to join the sit-in. What began as a routine commute quickly devolved into an eerie experience of the Indian state’s spatial control. As the train moved closer to central Delhi, station after station began shuttering in real time. The transit shutdown radiated outward in deliberate, concentric circles from Jantar Mantar, the heart of protest gatherings in the nation’s capital. My companion and I managed to disembark at Paharganj, a few miles away, slipping through the station gates just moments before security personnel pulled down the shutters, sealing off the entrance behind us. This physical enclosure created by the law enforcement controlled India’s Home Ministry was mirrored in the digital, with mobile internet connectivity cut off in large parts of central Delhi.

Over the past week, as I follow the student protests led by the satirically named 

) in New Delhi from afar, I see a more sophisticated version of this infrastructure of control and surveillance play out. When citizens assemble at Jantar Mantar or march through Central Delhi, their physical presence is intrinsically mediated by mobile connectivity, real-time broadcasts, and online coordination. The Indian state’s response to public dissent has evolved into a sophisticated strategy defined by two mutually reinforcing tactics: preemptive network blackouts and automated biometric surveillance.

The procedural minimalism of network shutdowns

Protestors in Delhi, currently raising their voices against the litany of incompetence in the Indian state’s management of key competitive examinations, are experiencing the outcomes of the routine deployment of mobile internet suspensions and signal jammers around protest sites. Framed by law enforcement as precautionary measures to maintain public order, these disruptions cut off the vital flow of live updates, citizen journalism, and emergency communication.

 judgment, India’s Supreme Court held that internet access is constitutionally protected, establishing that any suspension must satisfy strict tests of necessity and proportionality accompanied by publicly reasoned, published orders. In practice, telecom suspensions frequently lapse into procedural minimalism. Orders are either withheld from the public domain or published retroactively, shielding administrative decision-making from timely judicial review. By severing connectivity, the state does not merely manage public order; it actively limits demonstrators' capacity to document and in real time share state conduct.

 (notified under Section 20(2)(b) of the Telecommunications Act, 2023) replaced the older 2017 regime (

Temporary Suspension of Telecom Services Rules, 2017

. They grant Union or State Home Secretaries, or a designated Joint Secretary in urgent cases, the authority to suspend telecom services. Where the state previously relied on indiscriminate, district-wide blackouts under the 2017 Rules, the 2024 framework's emphasis on "defined geographic areas” has been operationalized during the current CJP protests as tactical micro-geofencing.

These protests, much like those in the last few years, highlight a crucial evolution in civic resistance. Recognizing that cellular networks and centralized platforms are vulnerable to administrative kill-switches, student demonstrators have pivoted toward offline, Bluetooth-aided mesh messaging protocols (such as Briar and Bitchat).

Deployment of automated facial recognition systems (AFRS) in New Delhi, highlighted by a Public Interest Litigation (PIL) currently before the Delhi High Court, illustrate the use of facial recognition technology with chilling clarity, particularly concerning the ongoing CJP protests.

At the center of this judicial scrutiny is the Delhi Police’s sprawling AI-powered surveillance network. 

 filed by former Jawaharlal Nehru University Students’ Union (JNUSU) president Aishe Ghosh paints a disturbing picture of how this network is operationalized at Jantar Mantar, where demonstrators are subjected to relentless, indiscriminate filming from permanent surveillance towers capturing not just political speech, but mundane actions like eating or resting. The petition also highlights coercive intimidation, claiming police personnel threatened to disseminate footage of young protesters to their parents and educational institutions.

During court hearings, the Solicitor General appearing for the state dismissed the PIL as "

," equating state-operated biometric logging with the routine filming done by protesters on their cellphones. This defense reflects a profound and deliberate mischaracterization. When a citizen records a protest, it is a localized act of documentation. When the state deploys AFRS, it exercises structural power.

Crucially, the composition of these underlying databases remains dangerously opaque. In a recent story, 

 that official accounts have fluctuated wildly, citing anywhere from 20,000 to over 350,000 criminal records. However, 

 have revealed a far more concerning dataset: an unregulated category described as "rabble-rousers and miscreants," populated by harvesting images from previous public demonstrations. This arbitrary cataloging effectively criminalizes the constitutional right to assemble, treating every protester as a prospective security threat.

The state’s strategy to render citizen dissent invisible to the outside world while hyper-legible to the state has so far failed miserably on the first front as the movement appears to be rapidly assuming a national character. Yet it is on the second front that I fear the data collected by the state may prove to have lasting damage on select demonstrators targeted in the months to come.

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