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Earlier this year, thousands of United States Immigration and Customs Enforcement (ICE) and Customs and Border Protection (CBP) agents were deployed across the Twin Cities and Minnesota in a massive federal immigration enforcement campaign launched by the Department of Homeland Security (DHS). The campaign, Operation Metro Surge, extended beyond borders and brought immigration enforcement directly into Minnesota’s communities, inciting widespread terror among communities and their families. According to 

, community members were so terrorized by ICE and CBP agents' excessive and unpredictable use of force, they restricted their movement and sheltered in their homes for weeks.

This siege disrupted nearly every aspect of daily life in Minneapolis, threatening residents’ ability to work, attend school, access health care, and seek legal protection. The City of Minneapolis 

 that the campaign resulted in 4,000 arrests and an estimated $700 million impact on the community and City government operations. Facial recognition technology played an integral role throughout this campaign, as federal immigration agents used 

, a smartphone facial-recognition tool that allows agents to scan the face of individuals they encounter and search it against multiple government databases. The use of this technology in this campaign reflects how facial recognition can be used to expand ICE’s reach, transforming immigration enforcement into a broader surveillance dragnet capable of reaching immigrants and citizens alike.

The expanded use of this technology is particularly concerning for Black migrants and other migrants of color, since facial recognition performs differently across racial groups. Black migrants are disproportionately exposed to the surveillance systems using facial recognition in the first place. Drawing on a 

 by the Black Alliance for Just Immigration (BAJI) and the Immigrant & Racial Justice Solidarity Clinic and International Justice Clinic at UC Irvine School of Law to the UN Special Rapporteur on contemporary forms of racism, this article examines how facial recognition has become embedded throughout US immigration enforcement, including ports of entry, ICE enforcement, and biometric databases; how its deployment reproduces and amplifies existing racial inequalities; and why that expansion raises concerns under international human rights law, particularly the International Convention on the Elimination of All Forms of Racial Discrimination (ICERD).

The use of facial recognition during Operation Metro Surge is not unique nor isolated; it is one example of a much larger system in which the government uses biometric technologies throughout immigration enforcement. Facial recognition is now used well beyond identity verification at airports and ports of entry. The government now uses it across immigration enforcement; from ICE agents scanning faces during street-level enforcement operations, to remote check-ins through apps like 

, to large-scale DHS databases that store biometric information. These uses of facial recognition do not necessarily operate separately. Biometric information collected in one encounter can be retained, combined with other personal information, and accessed or shared across government agencies, allowing information collected for one purpose to later be used in other immigration and enforcement contexts. This system continues to grow. In July 2025, a 

 toward CBP technology, including expanded border surveillance, accelerating the federal government’s investment in the technologies that make this system possible.

This expanded use of facial recognition is particularly significant because there are racial disparities in both its design and deployment. facial recognition has 

 for darker-skinned faces since it is trained on white data and relies on databases which are more likely to categorize darker skinned people as “risks” or “threats” because of increased enforcement and surveillance of black and Latinx neighborhoods in the US. These existing patterns of racialized surveillance persist in the deployment of facial recognition, since they continue to be disproportionately exposed to surveillance technologies that perform less reliably on them. As a result, expanded use of facial recognition can subject Black migrants and other migrants of color to heightened surveillance, misidentification, wrongful stops or detention, and the collection and retention of their biometric information for further use across multiple enforcement contexts.

Further, as seen during Metro Surge, these harms can extend beyond the individual migrant to their families and communities. During the operation, US citizens were recorded. As federal agents were deployed into Minneapolis and the Twin Cities, they would 

 residents, target individuals at protests or those observing enforcement activity, or go into public spaces they assumed to be immigrant spaces. When federal agents first encounter an individual in these operations, they do not immediately know their status, so they collect identifying information about them regardless of immigration or citizenship status. This expands immigration surveillance beyond those ICE initially sought. As a result, other people in the same spaces, such as family members and neighbors, can also be subjected to this surveillance. Therefore, facial recognition does not simply reflect existing racial inequalities; its use can reproduce and amplify them.

These racialized harms also implicate the US’s binding obligations under international law, which provides a framework for evaluating both the technologies themselves and state policies that authorize and expand their use. Under the International Convention on the Elimination of All Forms of Racial Discrimination (ICERD), the United States has a binding obligation to (1) prevent both direct and indirect racial discrimination, (2) refrain from engaging in and prevent acts of racial discrimination, and (3) mitigate structural racism by amending policies that perpetuate it. ICERD also requires states to regulate third-party vendors, ensure equal treatment before the law, and guarantee an effective remedy for people subjected to racial discrimination. Applied to facial recognition, this convention requires that the US look beyond whether the technology intends to discriminate along racial lines and examine how the government’s design and deployment of facial recognition impacts Black migrants and other migrants of colors in practice.

Racial bias is a design element of facial recognition

The racial bias inherent to facial recognition technology’s function starts before it is ever used at a border. Facial recognition systems are trained on datasets that are more than 80 percent light-skinned. Since there is not equal representation in the data the technology learns from as it develops, it becomes more accurate when it is deployed against those with lighter-skinned tones than darker skin tones. 

Further, the cameras used to capture new images are typically calibrated for lighter skin tones, so image quality for darker faces is degraded before an algorithm processes them. As a result of these design choices, the 

 for facial recognition is as low as 1 percent for lighter-skinned men and as high as 34.7 percent for darker-skinned women. So, facial recognition performs differently depending on race and gender. In the case of one private vendor, errors were attributable to darker-skinned subjects 93.6 percent of the time. For another vendor, the errors were attributable to women 95.9 percent of the time. Further, facial recognition systems compare a person’s face against large databases of stored images. 

Since Black communities are policed at higher rates, they are also 

 in those databases. Therefore, the databases that facial recognition draws from are already skewed against Black people as existing patterns of racialized surveillance are embedded within its design.

Surveillance at the border and ports of entry

Today, nearly every point of entry into the US has become a biometric checkpoint. Through its 

 CBP now uses facial recognition at all international airports on entry, at 66 airports on exit, across 39 seaports, and at multiple land crossings. 

The government’s use of biometric surveillance at such ports is only poised to expand. A proposed DHS rule would allow USCIS to require non-citizens of all ages to routinely submit biometric information throughout the immigration process until they become US citizens. This proposed policy would also expand the types of biometric information USCIS can collect, along with the circumstances in which this information can be reused.

Facial recognition does not stop at the border; it follows migrants into the interior of the United States. After entering the US, some migrants are placed in ICE's Intensive Supervision Appearance Program (ISAP) instead of being held in detention. Most recently, it has been 

 that the program consists of around 200,000 people. As part of the program, most participants are required to use the SmartLINK app, which uses facial recognition to verify migrants’ identities during ICE check-ins and confirms their location during the check-in. This app is used by 

 of the program’s participants. While ICE claims that location is only tracked and recorded during required check-ins, 

 by The Markup and Documented found that, for two SmartLINK users whose devices were examined, the app accessed location information when it was launched, as well as during required check-ins.

Glitches and malfunctions within the app can have severe consequences for migrants’ immigration processes and possibilities of re-detention: one user missed one check in because his phone died, and another because the app malfunctioned. Technological malfunctions like this can potentially lead to findings of non-compliance, that may ultimately result in increased reporting requirements, re-detention, and separation from family and community. Users are aware of these risks. Some users state that they feel “constantly exhausted and anxious” living under this app’s surveillance. In one law review account, a woman placed in the program—a composite of the author's clients—

 that she was scared that, should the app malfunction, she would be re-detained and separated from her siblings.

The facial recognition systems discussed above, such as CBP Home, airport scans, and SmartLINK, do not operate independently. They all feed into a larger DHS system for collecting, storing, and sharing biometric information. IDENT, DHS’s current biometric database, is 

 by the Homeland Advanced Recognition Technology System (HART). Instead of only storing fingerprints and faceprints, HART goes further, connecting those biometrics with other information, including political affiliation, religion, location, and known associations. The database is not just for CBP; it can be accessed by the Department of Defense, the Department of Justice, state and local police, and foreign governments.

The lack of transparency surrounding this database has led watchdogs to 

 a “black box,” since people are not notified before their information is collected, and they don’t know what information is stored within the database and who has access to it.

The expansion of facial recognition throughout immigration enforcement is also largely driven by private corporations, who develop and operate key parts of this surveillance structure. Clearview AI, which scrapes photos from social media and the open web, holds a 

 with Homeland Security Investigations (HSI) 

 for and was founded by a figure who has documented associations with white-nationalist and far-right figures. Palantir Technologies builds the data-integration infrastructure that lets ICE fuse biometric, location, and biographic data into a single profile. These companies consider key information about how their proprietary technology 

 as confidential business information that competitors should not be able to access, so they argue that they are 

 the systems relied on to produce particular results. This makes it very difficult to challenge or independently evaluate these systems, limiting the companies’ accountability.

Further, data-sharing extends beyond the US border. At the time our 

 was submitted to UN Special Rapporteur, the government had biometric-sharing agreements or letters of intent with five countries: 

. Since then, the government has expanded biometric data sharing throughout the region. Most recently, in July 2026, DHS 

 with the Caribbean Community’s Implementation Agency for Crime and Security (CARICOM IMPACS), creating a framework for sharing biometric and biographical information across the Caribbean. The agreement includes particular cooperation with Caribbean countries that operate 

 programs, including Antigua and Barbuda, Dominica, Grenada, Saint Kitts and Nevis, Saint Lucia, and Saint Vincent and the Grenadines. This means that US immigration enforcement no longer begins when someone physically reaches the US border. Instead, because biometric information is shared with other governments, US authorities may identify and monitor migrants while they are still traveling through Latin America, exposing migrants to profiling and refoulement long before they reach US soil.

From historic Black Codes to facial recognition Black codes

The racialized, uneven consequences of these technologies often go unscrutinized. This, in part, is because the government justifies facial recognition by arguing that it is preventative rather than punitive. More specifically, it argues that facial recognition is necessary for national security, prevention of fraud, management of borders, and minimization of crime. However, in doing so, these technologies make determinations about who is considered as a “risk” or “threat.” 

These determinations are not neutral; they often reflect older racialized assumptions about riskiness that predate facial recognition by centuries: lantern laws, which required Black, Indigenous, and mixed-race enslaved people in colonial New York to carry lanterns after dark so they could be more easily monitored; slave patrols, which monitored and controlled enslaved Black people; Black Codes, which criminalized Black life after emancipation; and COINTELPRO, which surveilled Black civil rights and liberation movements. In this reading, facial recognition does not simply police the border; it helps construct it, transforming it into a network of surveillance that digitizes colonial logic and sorts bodies into categories of belonging and threat along racial lines.

In their report to the United Nations Special Rapporteur, BAJI and the UCI Clinics propose that the solution to decolonizing this technology is embedding a collectivist rather than individualistic worldview into how it is designed and governed. An individualistic approach asks how a system may efficiently identify an individual. On the other hand, a collectivist approach asks how a system may affect relationships, communities, and human dignity.

2001 Durban Declaration and Programme of Action

, which identified colonialism as one of the historical roots of contemporary racism, the report argues that addressing discrimination in facial recognition technology requires confronting the historical structures that continue to shape its design, deployment, and use. This approach mirrors Jose Cossa’s contribution, 

, an approach derived from the African philosophy of Ubuntu, which is rooted in the idea that “a person is a person through persons.” In other words, Ubuntu understands personhood as fundamentally relational rather than individualistic. Applied to technology governance, that means evaluating systems not only by whether they function efficiently, but also by how they affect human dignity, communities, and relationships.

This decolonial praxis offers an alternative to the individualistic assumptions that often shape Western approaches to technology design, asking developers and agencies to examine not just what a system does, but why it was built that way, and to give the communities most affected by it, including the African Diaspora, a meaningful role in its future design and oversight.

The consequences of expanding immigration surveillance are already visible, as facial recognition technology has become an additional tool of oppression employed against our country’s most vulnerable communities. In Springfield, Ohio, in the aftermath of the 

 of hundreds of thousands of Haitian immigrants’ Temporary Protected Status (TPS), ICE agents 

 at least thirty local Haitians at the Butler County Jail. Haitian immigrants in Springfield have been shackled with ankle monitors, have had their biometric information collected through facial recognition technology without their consent, have been zip-tied in front of their children, pulled off of their job sites and out of their homes. They are now scared to leave their homes, go to grocery stores, or take their children to school. Through these methods of intimidation and oppression, it is evident how facial recognition technology has expanded the scope of the subjugation Black and Brown people can experience at borders, in their homes and communities, and as they move through the world.

While the racialized error rates associated with facial recognition technology are indeed concerning, facial recognition technology still causes real harm when it operates as intended, as it functions within existing systems of power. In these systems, it furthers existing patterns of over-policing communities of color that are disproportionately subjected to immigration enforcement. Therefore, the question is not simply whether the technology is accurate. Rather, we must examine who is subject to the increased surveillance it offers and what happens with the information it collects.

From pouring in billions of euros of public funds to build 

, Brussels wants to reduce its dependence on Washington and position the European Union as a legitimate force in the global Digital Great Game.

Yet just as EU officials flex their muscles — including the 

 in the bloc’s next seven-year budget for cloud computing, semiconductors and other strategic technologies — Europe has left itself exposed to outside forces.

Brussels’ growing stable of digital rules, including the recently announced 

, relies heavily on outside groups to provide the 

live fact-checking and election monitoring

defense of citizens’ fundamental rights

These groups, collectively, are Europe’s Democracy Stack.

They are the independent media outlets, disinformation research groups, regulatory compliance organizations and internet governance bodies that represent the strategic public infrastructure at the heart of the bloc’s digital and geopolitical ambitions.

At their core, they provide the democratic accountability layer to the EU’s digital sovereignty agenda. These groups hold both companies and governments to account in an increasingly digital age. They also connect European citizens to the bloc’s long-term plans to become more sovereign and more autonomous.

Yet Europe’s Democracy Stack is anything but sovereign.

 from the Atlantic Council’s Democracy + Tech Initiative and the Global Disinformation Index of almost 100 organizations at the center of this public-interest infrastructure quantified, for the first time, how much Europe relies on others — and the United States, in particular — to pay for the bloc’s digital aspirations.

Currently, only 12 percent of the annual budget for Europe’s Democracy Stack is funded by EU institutional funds, based on a review of groups’ statutory filings, the annual reports of philanthropic organizations and a tallying of EU and non-EU government grants.

In contrast, almost 60 percent of the capability’s annual 144 million euro operating budget for 2024, the latest full-year figures available, comes from either the US government or US philanthropic organizations. The remainder came from EU national governments or commercial and membership income.

That includes non-EU institutional funds to protect Europe’s elections from foreign interference; fund strategic litigation to defend the bloc’s fundamental rights; and support the regulatory compliance functions of groups that both the European Commission and EU member state governments routinely rely on to enforce Europe’s digital rulebook.

Such EU dependency on US funding did not appear overnight.

Until recently, Europe’s digital rights, election integrity and democratic resilience agenda went hand in glove with the priorities — and deep pockets — of both Washington and major US philanthropic organizations. This alignment allowed Brussels to 

 for Europe’s Democracy Stack with that of like-minded non-EU government agencies and foundations, which received a global halo effect of backing Europe’s 

Between 2021 and 2024, it helped to expand the collective funding for Europe’s Democracy Stack by 51 percent, cumulatively, at a time when Brussels was writing, implementing and enforcing the Digital Services Act, Digital Markets Act and Artificial Intelligence Act.

This expansion, however, was built on faulty ground. Between 2023 and 2024, for instance, almost 40 percent of groups reported a decline in their income, according to regulatory filings. In the wake of a changing of the guard in the White House, US government funding has dried up.

Washington has pivoted hard away from such digital rights work, and now even 

 that openly challenge aspects of Europe’s Democracy Stack. US philanthropic organizations have similarly cut back on supporting European groups. They 

 toward domestic concerns or doubled down on investments targeting artificial intelligence.

Confronted with this financial shortfall for groups central to the bloc’s digital sovereignty project, EU officials have failed to respond.

What current public funding exists for Europe’s Democracy Stack is overly bureaucratic, short-term in nature, and misaligned to the bloc’s digital needs, based on a 

 from the Atlantic Council’s Democracy + Tech Initiative that drew on a series of EU member state workshops.

In part, this failure is political. Just as US federal officials 

 Europe’s digital-focused groups for censoring Americans’ free speech, so too have some EU politicians, including those in Germany, 

 that Europe’s scarce public funding should not be earmarked for civil society groups.

At a time of sluggish European economic growth and belt-tightening 

 in Europe’s next seven-year budget, such reticence is understandable when many lawmakers believe supporting these outside groups is a luxury, not a necessity.

Yet this is a fundamental misreading of Europe’s Democracy Stack.

As part of the EU’s next budget cycle, officials have determined that reducing the bloc’s structural dependencies on other countries, most notably the US, is a political imperative. That includes a so-called 

 worth roughly 400 billion euros to fund research and deployment of strategic technologies, among other priorities.

Europe must apply that same logic — that reliance on outsiders for the bloc’s digital future is no longer acceptable — to the public-interest capabilities necessary to provide democratic accountability to the public money spent on artificial intelligence, semiconductors and the implementation of the EU’s digital sovereignty agenda.

Reducing that dependency is the missing layer of Brussels’ political ambitions. It can only be resolved through greater EU institutional support, via the next bloc-wide seven-year budget, for the public-interest infrastructure that defines Europe’s Democracy Stack.

That is where Brussels needs to act, and the fix isn’t complicated.

Currently, Europe only provides roughly 17 million euros a year for the fact-checkers, election-monitoring watchdogs and digital rights groups upon whose work the bloc’s digital rulebook — and global reputation — depends, based on the analysis of the finances of Europe’s Democracy Stack.

Matching what the US government and philanthropies have traditionally paid would mean Brussels providing closer to 85 million euros a year. Importantly, it must be committed for several years at a stretch instead of doled out grant by grant to ensure Europe’s Democracy Stack can be the public infrastructure it was designed to be.

Next to the 400 billion euros which Brussels wants to fork out for high-end semiconductors and AI infrastructure, such figures are mere rounding errors. When confronted with threats to its sovereignty, Europe found the money for glitzy AI gigafactories. It now also needs to find the money for its Democracy Stack that keeps its digital rules accountable to citizens.

Earlier this month, the United States was derided for being the only country to vote against the UN General Assembly’s “

” resolution, which encourages the global adoption of map projections that show Africa’s true size. It echoed the ridicule directed at the US Department of State on social media following a presentation at a global AIDS conference in Brazil in July showing an AI-watermarked map of Africa, with seven countries displayed 

That the US still hasn’t even worked out how to use 16th century 

 became a standing joke; that its hegemonic hold over the international order persists regardless, is not. Washington dismissed the UN’s resolution to switch to the 

 projection as a “radical ideological project,” linking it to 

 passed in March that condemns slavery as the gravest crime against humanity and calls for reparations.

Technically, officially, even scientifically, it is not: a cartographic correction of the distortions in Mercator maps corresponds to what the world already understands as fact — which is why, in the increasingly Alice-in-Wonderland world of US geopolitics, with its 

 of international waterways and lakes, Washington’s opposition to a scientifically supported correction is preposterous.

But the correction is certainly also political. The 

 highlights the non-neutrality of so-called ‘objective’ scientific instruments, contending that diminishing Africa geographically, “affects education, public understanding, culture, geopolitics, development narratives and perceptions of Africa’s scale and potential” — linking accurate mapping to cognitive justice, historical recognition and equitable representation. As Togo’s representative put it, “A fair map does not change the geography of the world; it changes how we see the world.”

This was evident not a month before in Washington’s glib acknowledgement of the entirely incorrect location of all seven African states in the presentation outlining its future HIV response. A State Department spokesperson 

 “an unfortunate error,” adding that the department takes “full responsibility for the confusion and misrepresentation it caused for attendees, including our African partners.” Whose responsibility could it otherwise have been — the AI’s?

Africans, inured to this kind of condescension as routine in international aid and trade relations, responded with disappointment officially, but with humorous derision online. Nonetheless, the error raises sharper questions about the integrity of the data behind much vaunted AI systems that UN agencies, sovereign donors and private 

 are pushing to the rest of the world — as well as the data behind Washington’s 

It also raises concerns about the integrity of the media — and the international media in particular — whose reporting on the map debacle in July amounted to little more than the State Department’s own apology.

 followed up — identifying the invisible OpenAI watermarks and getting African government and HIV organisations on record. The substantive story broke on Substack, where AIDS expert 

 revealed it as part of a much greater deception by the State Department’s Bureau of Global Health Security and Diplomacy. It was not just fabricating maps of Africa, but rewriting the history of 

, the imperfect but massively impactful US President’s Emergency Plan for AIDS Relief. Among the more striking omissions, Hess points out, was the reason for the failure of DATIM, the system tracking HIV data, in the Bureau’s rationale for new in-country data systems that, as Bass notes, already existed.

“DATIM went offline because of the stop-work order in 2025,” Bass writes — not a systems failure, but a system that “went offline during a lethal, haphazard and shocking termination of US foreign aid for global health.” The consequences were not abstract: “People died and will keep dying horrible, painful deaths from undiagnosed HIV, without being counted or, better yet, helped” — because Washington froze, then reinstated, data collection without the staff needed to capture and validate it, or allow for any public review.

“There is no chance of a constructive, productive future for an American global health strategy that has such a loose relationship to the facts,” Bass said.

Why does this matter for technology policy, media and democracy? What’s notable here is the inversion of traditionally authoritative sources of official information — accountable government and the Fourth Estate’s role in obtaining and scrutinising that information. More credible, fact-checked accounts increasingly come not from official or establishment media but from specialists, researchers, and independent journalists on platforms as far from Big Tech’s reach as they can manage.

The implications go beyond AI or social media, to the broader erosion of democracy. Social networks that once gave a multiplicity of voices direct access to global audiences, have been co-opted or bought out by Big Tech, or have become instrumental to the AI race to build unassailable leads on the back of unregulated data-extractive oligopolies. Dominant browsers, social media platforms, and now unavoidable AI chatbots, have hollowed out local media.

In Africa, barely a handful of independent, non-state outlets are left to cover increasingly weaponised trade and aid, which has tied reduced US funding for HIV healthcare 

to long-term data and pathogen-provisioning deals

 that several African countries have recently rejected. Establishment media has not fared much better internationally, as they are bought or sold out to tech oligarchs who declare, in public manifestos, the need to rid 

 or have techno-nationalist doctrines of firms building and deploying dual-use, defense AI — while nominally ‘public interest’ broadcasters report on genocide through the lens of its perpetrators, and the UN looks on.

The more authoritarian and anti-humanist the worldview, the more room the broligarchy seems to be given in establishment media it hasn’t yet bought or broken. In a July 

 with Elon Musk, The Economist’s editor-in-chief, Zanny Minton Beddoes, lobbed questions so weak she conceded almost as soon as they were asked. Musk was left free to construct his own fabrication of the record. To her 

that DOGE’s cuts to USAID food and health programs had caused hardship and loss of life, his response was categorical: “Zero people died. Zero died because of DOGE… Zero point zero.” Her reply: “Well, that’s what I would take issue with… the pace and the suddenness with which it happened will almost certainly have caused unnecessary suffering and deaths.”

A five-minute search would have given her an arsenal of facts and figures very far from “Zero point zero”. An 

 died unnecessarily from the DOGE cuts to USAID and other health and food programs before June, with the toll potentially reaching up to 14 million over five years if the trajectory holds. This is supported by a growing number of 

 from USAID’s 2023 $42.4 billion budget, alongside disruption to PEPFAR and reduced UK overseas aid. 

 suggests the USAID cuts alone will contribute to an additional 15.2 million AIDS deaths, 2.2 million tuberculosis deaths, 7.9 million child deaths and 40 million to 55 million unintended pregnancies between 2025 and 2040.

Rather than press the point, Beddoes let Musk pivot repeatedly — from the US accounting for humanitarian outcomes, to DOGE having saved the country from USAID fraud, to blaming the Gates and MacKenzie Scott foundations for failing to deploy the $50 billion they sit on to shore up the USAID deficit. “Fair point,” she offered.

Sitting in Tesla’s Texas Gigafactory, a Tesla parked behind them, she did try to push back, briefly: “Not everyone functions as fast as you do… if funding is cut off for antiretrovirals overnight, people will die” — before undercutting herself: “Let’s be practical… I don’t want to have an argument.” She noted many health programs across Africa had shut down, but still failed to counter Musk’s dismissal: “These claims are false. They’re nonsense. Absolute nonsense.”

That an outlet with The Economist’s resources could go into an interview this unprepared — common neoliberal ground notwithstanding, to which both parties are of course entitled — is an indictment of the publication but also symptomatic of the loss of integrity and credibility of establishment journalism.

Information integrity is one of seven critical issues in the 

 of the UN’s Independent Scientific Panel on AI released in July at the 

Global Dialogue on Artificial Intelligence

. It warns that AI can erode shared reality and civic participation through “epistemic erosion,” the gradual wearing away of society’s ability to distinguish truth from falsehood. Opening the Dialogue, the UN’s secretary-general, António Guterres, tied that erosion directly to the viral and exponential nature of advanced data driven technologies: “A machine-enabled lie can now persuade as effectively as the truth, and authentic evidence can be dismissed as fake.”“A society that cannot agree on what is real cannot defend itself,” Guterres said.

And yet he did not reference the threat of AI to amplify inequality, unless governed effectively. Instead, Guterres casts AI as “the great equaliser of the 21st century ” achievable by developing countries on the technology fast-track through safe systems that honor human rights, with real transparency about labor and planetary impacts. Getting this right, he said, is “at the heart of our common future.”

Yet the Panel’s Report, subtitled as an “evidence-based assessment of the opportunities, risks and impacts of AI” provides no evidence that AI will be a ‘great equaliser’. On the contrary, despite its curious ‘balancing’ of every claim with a counter claim, the heavily referenced report actually demonstrates far more evidence of the negative consequences of AI, while doing very little to support claims that AI will help in the achievement of the UN’s 

. Regardless, this did not stop the ‘great equaliser’ mantra from being repeated by numerous member states and heads of multilateral bodies who subsequently addressed the forum.

In fact the report highlights the lack of — and unevenness of — evidence, including on some of the big ticket items: productivity gains, labor market effects, value-chain impacts, and importantly, which governance arrangements might actually work best.

That absence of evidence should trouble anyone who is serious about AI governance. It should trouble Africa most of all. A continent whose true size still has to be legislated back onto the map, whose HIV data can be switched off and on again without explanation or accountability, and whose dead can be waved away on a public stage with an emphatic “Zero point zero,” has the most to lose from a world in which the loudest, best-resourced voice always gets to define reality.

Last week, the European Commission introduced the 

, a new legislative proposal aimed at strengthening the protection of children online.

While the initiative had long been anticipated, it remained unclear until the very end what instrument the Commission would use to complement its existing digital rulebook. By opting for a standalone regulation instead of revising existing ones, the EU executive has added another layer to an already dense regulatory landscape.

 (DSA) already contains extensive obligations to protect minors online, while the forthcoming 

 (DFA) is expected to address many of the problematic design practices targeted by the KIDS ACT.

So, the questions naturally follow: What exactly does the new proposal add? Where do these instruments overlap? And what does this growing regulatory stack mean for enforcement and the EU’s broader approach to online child safety?

Under Article 28 of the DSA, which applies since 2024, providers of online platforms accessible to minors — with the exception of micro or small enterprises — must already “put in place appropriate and proportionate measures to ensure a high level of privacy, safety, and security of minors, on their service.”

In July 2025, to give this broad obligation more concrete meaning, the European Commission published more than 60 pages of 

 detailing measures platforms may take to comply with Article 28. These range from setting minors’ accounts to private by default, to adapting recommender systems to reduce exposure to harmful content or disabling by default features that can contribute to excessive use.

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