WikiCon Brasil 2025 group photo. Donatas Dabravolskas, CC BY-SA 4.0, via Wikimedia Commons

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Wikipedia Isn't Big Tech, and Brazil's Platform Rules Should Say So

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Francine Berman’s ‘Better Tech’ is a Call to Arms for Those Who Care About Tech’s Role in 21st Century Life

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

Global Digital Policy Roundup: September 2026

Composite graphic design image with a surveillance camera and three sets of feminine hands holding mobile phones, including one with the logo of MitID on the screen. 

How Denmark's National Digital ID Fuels Economic Violence Against Women

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Russia’s AI Law Puts Control Ahead of Capability

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Cloud Needs More than Fee Waivers to Be Competitive

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September 2026 US Tech Policy Roundup

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When AI Agents Break In, Governments Shouldn't Be Stuck With the Cleanup

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A Safer Internet Should Not Come with Democratic Shortcuts

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A collage of images of hands with index fingers in pointing position and squiggly lines.

AI Transparency Starts With the Audience

In early September, Facebook groups for drivers with ride-hailing and food delivery platform Grab in Vietnam were flooded with calls to boycott the app over excessive commissions and a lack of fare transparency.

“Let's turn off the app for two days—for the sake of our own future!” said the post by anonymous user 

 that was reposted in many groups, setting the date for September 12-13. “Attitude: Civilized, peaceful, and law-abiding — no to aggression and no to disrupting public order or security.”

“Please spend the 12th and 13th resting with your family or servicing your vehicle.”

This is not the first time drivers in Vietnam have called for a mass boycott in protest of platform policies. 

 but did not attract much public attention, nor result in any regulatory change.

“How the (boycott) is organized hasn’t changed much, but drivers have been more cautious in how they show their discontent,” Do Hai Ha, a researcher at the University of Melbourne who has studied Vietnam’s gig economy since 2017, told Tech Policy Press. What’s changed is “now the people sympathize with the workers more, the press is speaking up more, creating internal pressure” for regulatory change, he said.

 under the Ministry of Industry and Trade announced it had requested Grab and its competitors to explain their fare breakdown, while encouraging users and drivers to submit their own evidence. If the commission finds sufficient evidence of unfair competition, this could lead to legal proceedings, though it remains to be seen how far this will be taken.

Platform work remains unregulated in Vietnam, where workers for ride-hailing and delivery apps are considered driver-partners. The fact that the Competition Commission, rather than a labor authority, stepped in suggests that while the government is paying attention to the issue, drivers are still seen as users of platform services, rather than its employees, Ha said. 

Last June, the Ministry of Home Affairs said they would 

 platform workers in the compulsory social insurance scheme that applies to formally employed workers, saying they can choose to participate in the voluntary scheme.

For this to become a labor issue, Ha said, it must be shown that drivers don’t have sufficient bargaining power over the platform, warranting state intervention such as allowing unionization, setting minimum wages, providing social insurance, and other rights and benefits under the country’s Labor Code.

The recent call to boycott shows the tide is changing, even as the actual boycott appeared muted.

Past boycotts were more vocal and visible, with 

 on social media and gathering outside their platforms’ offices.

This time, on the first morning of the boycott, it was quiet outside Grab’s office in Hanoi, with no driver in sight. An anonymous account led the call for the boycott over what they said were excessive commission rates, ranging from 40 to 50%, while in Indonesia, Grab is 

Pham Mi Sen, deputy head of the Ho Chi Minh City App-based Drivers Association, confirmed that platform drivers’ pay has fallen significantly over the years. In 2015, a motorcycle delivery driver for Grab got paid 3,000 dong per km. By 2026, it had fallen to just 2,500 dong. “To shoulder the (rising) cost of living, drivers have only one option: they have to increase their working hours,” he said. But “the initiative (call to boycott) was sporadic, spontaneous, and lacked any real direction; it certainly didn't reflect the stance of the vast majority of drivers.”

Ahead of the boycott weekend, Le Tan Luu, the chair of Binh Tan App-based Drivers Association in Ho Chi Minh City, 

. “You have the right to raise concerns or make proposals if you find a policy unsuitable,” he added. “However, if you approach the matter calmly—backed by information, data, and adherence to regulations—your voice will carry much more weight and be far more persuasive.”

While it is hard to ascertain the actual size of the boycott, Van, who drives full-time for Grab in Ho Chi Minh City, noticed a spike in the number of rides he got assigned over the boycott weekend. “I’m still working, otherwise I’d go hungry,” Van, who requested to be identified by a pseudonym for fear of retaliation by the platform, told Tech Policy Press.

Duy Nam, 24, who’s been driving for Grab in Hanoi for just three months, decided to turn off the app over the weekend and try out rival Tada who 

. “This is not some revolution or a protest, but an expression of the drivers' outrage as they demand their rights,” Duy Nam, who didn’t give his surname, said. “It also raises a major question as to why the company takes such a high cut.”

To illustrate his point, Duy Nam showed an example of a Grab ride where the customer paid 17,000 dong ($0.65), and he was paid 9,000 dong. After a recent 78,000 dong Tada ride, he pocketed 72,000 dong after the platform deducted VAT and income tax.

The individual drivers’ choice to quietly turn off the app without taking to the streets with protest banners and the association’s choice to call for restraint are both indicative of how thin the line they’re threading between their right to voice their concerns and disturbance of public order, which in Vietnam is a criminal offense often used against protesters.

Indeed, while there have been no reports of protesting drivers getting fined or arrested, on September 14, the police 

 for spreading unverified news that “Grab drivers are turning off the app en masse.” The police warned the public against engaging with accounts that spread misinformation about the boycott, singling out accounts that used words like “protest” and “Grab is paralyzed” without citing a clear source.

The police also quoted Grab as saying that during the weekend of September 12-13, the app continued to operate as normal. Grab did not respond to Tech Policy Press’ request for comment.

The loudest voices through this campaign were actually the media and Grab users, notably on Threads, which in the past year has become a 

 covered the boycott before it even started, leading with stories on how drivers’ earnings have been falling over the past several years.

On Threads, users expressed solidarity with the drivers, pledging to boycott the app too. On the first day of the boycott campaign, Grab was trending on Threads with a million posts. Users shared example letters to Grab and government agencies to demand better pay for the workers, and mobilized free meals for drivers going offline that weekend. By Sunday, the Nasdaq-listed company’s stock f

This solidarity is not an isolated event. Last year, users from Malaysia, Singapore, Thailand and Vietnam used Grab and another popular app, Gojek, to 

for drivers in Indonesia who were at the forefront of anti-government protests.

This reflects the quasi-intimate relationship users in Southeast Asia have developed with ride-hailing and delivery drivers. “Since the pandemic, they have become essential to the daily lives of the people,” Mi Sen, the deputy chair of the drivers’ association, said. Users rely on them for everything, from the daily commute through the region’s crowded mega-cities, to deliveries of groceries, food and other essentials whenever the roads are flooded, or it’s too hot, or one is simply just too busy to go outside.

Over time, the public has come to understand drivers’ struggles, from chats during the commute and protests across the region to media reports on how platforms use algorithms to control drivers' pay and pressure them to work longer hours.

Regulation is catching up, just as the number of ride-hailing and delivery drivers has risen to hundreds of thousands, or even more than a million in some countries, and with that, the power to paralyze traffic and logistics.

 came into effect, the first legislation in the region to recognize this form of work with rights to social security. Malaysia followed with its 

 mandated the 8% cap on commissions in July.

In June, the ILO adopted the Decent Work in the Platform Economy 

, which states employment classification should be “guided mainly by facts relating to the performance of work, the remuneration or payment of the digital platform worker, among other elements, and considering the specificities of work via digital labor platforms.”

These regulations act as reference points for the Vietnamese government, but for meaningful change to happen, “the motivation has to come from within,” Ha said.

On Sept. 29, National Assembly member Tran Thi Dieu Thuy proposed that ride-hailing and delivery platforms 

contribute to their drivers’ social insurance

 during a meeting discussing amendments to the Law on Social Insurance.

On Sept.15, the Laborer Counseling and Support Center under the Ho Chi Minh City Federation of Labor organized 

 entitled Social Protection for Ride-Hailing Drivers: Current Situation and Solutions. Among the invitees were Grab drivers and platform work researchers who said the job's flexibility is an illusion; instead, the app forces them to work dangerously long hours just to make ends meet.

Mi Sen was present there too. And in an interview with Tech Policy Press, he reiterated his message to the government: “We drivers want to have a clear classification of where we stand in this society (…) we want equality with other workers.”

“If (the platform) insists we are partners, then we must have the right to negotiate rates, working hours, and policies regarding incentives and penalties.”

comprehensive law governing large foundation AI models

 took effect this month on Sept.1. The law was signed on July 26 after a substantially broader draft went through 

 in the spring and was replaced in June by a narrower bill focused on large foundation models and state support for their development.

The law does less to manage the risks of AI than to establish a framework for supporting and controlling developers of large foundation models. The framework offers qualifying developers state support, a role in shaping AI policy and potentially protected markets in exchange for meeting requirements on Russian ownership, data localization and conformity with Russian law and what the statute calls “traditional Russian spiritual and moral values.”

Russia has spent decades extending state control over its digital space: data storage, communications, network infrastructure. Developers were bound by personal data and content rules, but AI largely fell outside that framework. Direction came from the 

, but no law addressed the industry itself. The new law closes that gap at the layer that matters most: foundation models, the "brains" other AI systems are built on.

Development is led by Sber, T-Bank, Yandex and MTS. None is a startup, and all four depend on state licenses, contracts and goodwill. Sber is the state-controlled savings bank that 

 itself as a technology group; Yandex was the country's largest private tech company until 

 to government-approved investors — the fate 

The layer's foundations are largely foreign, and mostly Chinese. Sber says it 

, but on an architecture its own engineers describe as 

, with Qwen-style attention in the latest version.

The hardware is foreign too. Export controls bar Russia from advanced Western accelerators; 

, and the compute behind these models mixes Chinese accelerators with Western GPUs bought before the controls or 

 was built using Qwen-2.5-32B weights, while T-Bank's 

 are built on top of successive Qwen generations. Absent from international leaderboards, they appear on Russian-language ones such as 

From regulation to support for model development

 was published for public comment in March 2026. It was a different document, which tried to cover the whole field: the rights of individuals, governance structure, the allocation of obligations from model providers to system and service deployers, and intellectual property.

Russian lawyers, businesses and even government-related organizations heavily 

 it for poor drafting and controversial content. It appeared that several interest groups had drafted separate parts independently. Furthermore, it did not resolve any of the sector's legal issues, yet it granted government bodies a wide range of additional powers.

By June, both the concept and the title had changed. The comprehensive approach was dropped. Instead, the legislature passed the 

On Support for the Development of AI Technologies in the Russian Federation

 law. Its subject is narrower: large foundation models and measures supporting their development. The State Duma 

 in July, the Federation Council approved it later that month, and President Vladimir Putin signed it on July 26.

The adopted law no longer regulates AI systems in general. Instead, it applies to "large foundation models,” defined as models with at least “1 billion parameters,” general enough to serve as a basis for software development and a wide range of tasks.

The parameter count is a relatively crude threshold. By comparison, the 

 uses training compute — the amount of computing power used to train a model —alongside other criteria to identify general-purpose AI models and models with systemic risk. The European 

 use 10²³ FLOPs (floating-point operations) as an indicative criterion for identifying GPAI models, while models trained using more than 10²⁵ FLOPs are presumed to have systemic risk, subject to rebuttal.

A 1-billion-parameter threshold can encompass both relatively small open models that run on local hardware and models far larger than the threshold; it therefore does not map neatly onto the frontier of commercial AI. The final text also covers large foundation models made available to users in Russia, meaning that foreign developers serving the Russian market may fall within its scope.

The law is built around two models’ statuses: "sovereign" and "national". The requirements for both largely overlap: the developer must be a Russian legal entity; responses to user queries must be generated and stored in Russian-owned data centers in Russia; the model must be assessed for conformity with Russian legislation and "traditional Russian spiritual and moral values," although the law sets no procedure and the rules for this assessment await a decree.

The law does not name the bodies that will conduct the assessment: the procedure, like the rules for granting the statuses, 

, the Ministry of Digital Development is drafting it with the FSB and the FSTEC, the export-control and technical-security service. Under the proposed scheme, developers would disclose the model's architecture and filtering mechanisms, accredited laboratories would test its answers and try to bypass its safeguards, and the ministry would make the final decision. 

Since the values are already listed in a presidential decree, the plan is to turn them into a dedicated benchmark, developed together with industry, against which models will be tested. The resolution has not yet been adopted. 

 as "patriotism, service to the Fatherland, high moral ideals, a strong family, the priority of the spiritual over the material, humanism, collectivism," etc.

Russian models already appear to apply content moderation in that direction. A 

 of 14 models found that the two Russian models tested, Sber's GigaChat and YandexGPT, refused most often when prompted in Russian and about Russian-born figures. Its authors argue the moderation is tailored to a domestic audience. The law formalizes for the AI industry what general legislation already requires.

The difference between the two statuses is provenance. A sovereign model must be developed end-to-end by the Russian developer and technically reproducible by it. A national model may be built on a foreign model under an open license, provided the Russian developer determines and changes its essential characteristics.

Given the distance between Russian developers and the frontier, we read the national status as a legal pathway for Russian developers to build on open foreign models, including Chinese models such as Qwen, especially since prominent Western 

The obligations are written in general terms: security measures, rules of use, safety documentation. The privileges are specific. Under provision 5 of Article 5 of the new law, status holders receive state support, a role in shaping state policy and access to state datasets, subject to FSB agreement. The government will also designate cases in which only sovereign or national models may be used, making the status a condition of market access.

The most valuable concession is in copyright. Under provisions that take effect in March 2027, the law provides that certain computational uses of copyrighted and related-rights material do not constitute infringement. It specifically permits short-term reproduction in computer memory solely to train a sovereign or national large foundation model, provided the developer uses a lawfully obtained copy of the work or the work has been made publicly available and is accessible for analysis without technical restrictions.

The unusual feature is that the training provision is tied to the model's legal status. The same type of copying can therefore fall within the statutory exception when it is used to train a sovereign or national model but not necessarily when it is used to train a model outside those categories.

The treatment of AI training data differs sharply across jurisdictions. In the EU, 

 certain text-and-data-mining uses, including exceptions for scientific research and broader training data unless rightsholders reserve their rights. The 

AI Act requires providers of general-purpose AI models

, including respecting such reservation. In the United States, 

 has separately examined licensing and other policy questions.

Russia has chosen a more explicit statutory approach for sovereign and national models, without establishing remuneration for rightsholders in the training provision. However, the exemption may still be narrowed before it applies; it is being actively 

In terms of transparency, the law does not require every piece of AI-generated audio or visual material to carry a notice. Instead, beginning March 1, 2027, a person using a large foundation model to create audio or visual material must be given the ability to attach an AI notice, which they might not use in practice. The format, content and placement of the notice are to be agreed between the user and the provider of access to the model.

The law is short — 13 articles — and leaves important implementation details to subsequent government rules. These include the criteria and procedures for sovereign and national status, the conformity assessment against Russian law and the procedure for access to data held in federal and other state information systems.

Federal laws and presidential acts may establish rules for the use of large foundation models in national defense and state security, operational-search activity, public order, counterterrorism and public administration. The list covers many of the areas where AI poses the greatest human rights risks: biometric identification, predictive policing, social media monitoring and movement tracking.

The law says nothing about how these uses should be regulated: no prohibitions, no human rights impact assessment, no independent oversight, no notification of affected persons, no route to challenge a decision. That leaves unresolved some of the procedural concerns the European Court of Human Rights identified in 

. Nikolay Glukhin was identified by Moscow's cameras after riding the metro with a cardboard cut-out of a political prisoner. The Court held that facial recognition against a peaceful protester violated his rights to private life and free expression.

One clause goes further than the carve-out. It grants the president broad authority over AI technologies as a whole, not merely large foundation models, including an open-ended power to exercise "other powers." The law nowhere specifies which questions must be settled by statute and which by decree. A policy domain has been handed to executive rulemaking with no boundary drawn around it.

Surveillance obligations apply to AI services as well. They are subject to the 

, meaning services that let users exchange messages with each other or with the service. This includes chatbots, AI assistants and other interfaces that accept user input, regardless of audience size. They must store interaction data, including message content, in Russia and give the FSB access.

The individual elements are recognizable from elsewhere: a risk-based approach, transparency requirements, a distinct regime for foundation model developers, and technological sovereignty. But the EU AI Act attaches them to a different regulatory structure. It imposes 

obligations on general-purpose AI providers

 and additional requirements on models with systemic risk, while the broader AI Act uses risk tiers for AI systems and includes provisions intended to support innovation, including regulatory sandboxes.

But the EU AI Act arranges them on two levels. AI systems, the applications people actually use, are regulated by risk tier, from prohibited practices to high-risk uses such as hiring or credit scoring, with duties for both providers and deployers. For general-purpose AI models, the Act sets separate baseline obligations on general-purpose AI providers and additional ones on providers of models with systemic risk.

The categories also do different work. In the EU, the 

 primarily allocates obligations: providers must maintain technical documentation, follow a copyright policy and publish a summary of training content, while providers of models with systemic risk face additional requirements for risk assessment, incident reporting and cybersecurity.

In Russia, the sovereign and national status also determines eligibility for specified state-support measures and can determine which models may be used in areas reserved for those categories.

Russia has adopted some of the vocabulary of contemporary AI regulation but uses the categories to combine regulation with industrial policy and technological sovereignty. The result is a system in which legal status can affect both the obligations imposed on a model developer and the benefits or markets available to it.

Several major provisions take effect March 1, 2027, including the rules governing sovereign and national models, developer obligations, AI-content notices and the copyright provisions. The government may also designate areas in which only sovereign or national models can be used. Until Sept. 1, 2032, that restriction does not apply to information systems using large foundation models that were created or operated as of March 1, 2027, provided the data is processed and stored in Russia.

Russia’s answer to the AI race is to build at the frontier but to own the checkpoint. Foundation models are where the stack narrows to a few companies, and a state that hands out the statuses they need to reach protected markets governs everything built on top of them without regulating a single application.

Sovereignty here means jurisdiction rather than capability: models that operate with data in Russia, under Russian legal requirements and, in some important cases, on foreign — particularly Chinese — model weights and hardware.

For countries that cannot afford to train a frontier model, the model offers a different proposition: domestic hosting and developers, foreign open weights where permitted, a domestic approval regime and preferential access to selected markets.

proposed a BRICS platform for AI sovereignty

, and says it is targeting states in Africa, Asia, Latin America and Oceania that want their own AI but cannot afford to build it. What travels with the models is the legal design around them: statuses, domestic registration and reserved markets. The exportable product is therefore not just AI capability, but a model of technological control.

This story was produced in partnership with 

Composite graphic design image with a surveillance camera and three sets of feminine hands holding mobile phones, including one with the logo of MitID on the screen.

 It was after Mary gave birth to her first child that she noticed a stark shift in the behavior of her husband. As part of a prenuptial agreement the couple signed when they got married in Denmark in 2011, they had agreed to pool their finances.

But that never materialized. Instead, Mary remained reliant on pocket money her husband, the sole breadwinner, would transfer to her personal bank account while Mary pursued a Master’s degree.

When she would ask about the shared bank account they had planned to open, “every conversation turned into an argument,” said Mary, who declined to give her real name for fear of consequences in her ongoing legal case with her now ex-husband. He also began interrogating her about what she had bought and paid for. “I felt a bit like he was an investigator,” she said.

While her ex-husband earned up to 4 million kroner a year (about $610,000 in 2015), he would usually only give her 6,000 kroner ($915) per month, she said. This was meant to cover all expenses for her and their two children.

In practice, this became an unsettling form of control. Mary claimed he actively discouraged her from working and refused to help with childcare. As a result, she was totally reliant on her husband’s allowance. “It was very unstable because if he thought he'd already paid for petrol, for example, or if I didn't deserve the money, he could deduct it. So I could never quite count on what I'd get,” she said.

The control over her finances got worse. In early 2015, her bank advisor got in touch and mentioned, offhandedly, that she had logged into her online banking many times. She told him he was mistaken. “And suddenly, the penny dropped. I said – ‘It wasn't me. It's my husband who has logged in,’” she recalled.

Her husband had used NemID – Denmark's first version of its digital ID with a username, password and one-use codes on a physical card – to access her account around 21 times. The bank advisor offered to report it. Mary waved him off. “Looking back, I think I should have just had it reported... because it could have been used as evidence of a pattern today.”

Mary does not know how often her ex-husband abused her digital ID during their 11-year relationship to spy on her. But the pattern she refers to is economic violence: a form of domestic abuse in which a partner controls or coerces a victim through finances. From bank account monitoring to pocket money control and pressure to sign over shared assets under threat of divorce, these were moments that may have seemed disparate alone, but together, amounted to abuse.

“I often had this image in my head – that he was a cat, and I was a mouse,” she said.

Until recently, economic violence has been largely invisible – and is still often misunderstood or ignored. It is only in the past few years that researchers have begun to investigate how digital banking apps and national IDs can play a role in enabling it.

Denmark has no national data on how digital ID has an impact on economic abuse. But

 to a 2026 report published by Danner, a non-profit that supports domestic violence survivors in Denmark, almost half of the women in its counseling program have 

 economic violence. Of those, 17% had their partner incur debt or apply for public funds in their name – often using digital ID as the instrument.

 countries in Europe, and the country rolled out its first national digital identity system, NemID, in 2010. More than a decade later, in 2021, this wasreplaced with MitID: a smartphone-based digital master key to virtually every aspect of a resident’s life, from banking to medical prescription history.

Although not mandatory by law, it is very hard to live without it. Danish residents are 

 to use MitID to open bank accounts, pay their taxes and access most essential services.

 and differs from the previous ID in a key way as it relies on biometric authentication. Usually, users have to scan their face through the smartphone MitID app to log into their account. According to Malte Bundgaard Kolze, a criminologist and researcher at Copenhagen-based legal think tank Justitia, this makes MitID “very secure against all kinds of misuse” as someone can’t just “go into the system and use a code”, he said.

But there’s a blind spot. “Against strangers, it’s very effective. But against intimate partners, it’s not because they’re close to you,” Kolze said. An abusive partner can use “whatever means are at their disposal” to convince, coerce, or manipulate their victim into scanning their face to unlock the app, Kolze adds. “[MitID] is a good system, but it has this oversight that has a very negative impact on specifically this group,” said Kolze, referring to women in abusive relationships.

When victims try to prove economic abuse took place, MitID’s biometric authentication makes coercion 

 to establish and therefore get justice for. Maja Wallmeier Wolfgang, a criminologist who works as a consultant for the region of Nordjylland’s police department, said economic violence cases are particularly difficult to investigate because of “the whole consent part”, which makes proving abuse more challenging.

“If someone has logged in with MitID, it can be hard to know whether it's her who did it, or someone else who gained unauthorized access, or whether she was misled in certain ways,” she said.

Finance Denmark, an umbrella organization representing banks in the country that co-developed MitID with the Danish state agency for digital government, said it “feels deeply for the women who are subjected to economic violence.”

“That is why we also work together with Danner and LOKK [the national organization of women’s shelters] to help combat it,” said Kjeld Gosvig-Jensen, Finans Denmark's deputy director of law.

When asked what Finans Danmark can do to stop MitID from being weaponized to abuse women, Gosvig-Jensen said that “with respect to the actual use of MitID, Finans Danmark has no independent opportunity to react.”

The state agency for digital government declined Fuller's request for comment.

 women experiences some form of economic violence, yet 

 European countries specifically criminalize it. Denmark is not one of them. However, the country 

 psychological violence in 2019, including “taking control over a person's finances”.

This is “a very slim definition” of the abuse, according to Clara Kort Illeborg, a project consultant at LOKK.

Abusers, for example, can exploit the digital ID system to incur debt or apply for public funds in their partners’ names. “You can take out really big loans, change where welfare cheques go, move money around,” said Illeborg. “And do a lot of things with MitID without having to talk to a real human being.”

In Denmark, perpetrators can also abuse digital IDs to take out “quick loans” in a victim's name without their knowledge, according to 

. After all, it is easy: loans can be approved

 for victims of digital signature fraud. But researchers saythat economic abuse victims are often left out by design. The scheme 

 where an abuser takes out a loan in their victim’s name via digital ID and directs the funds to themselves versus the victim’s account first.

 that a woman’s boyfriend had abused her NemID to take out a quick loan of 40,000 DKK ($6,200) in her name in 2017. Even though the man was subsequently convicted for fraud, the woman was taken to court by one of the banks involved, which wanted her to pay back the loan as well as any interest incurred.

It is one of the waysdigital ID abuse can become a “chain around the ankle” that outlasts the relationship, according to Kolze. “Maybe you accrue a huge debt that you can never get rid of,” he said. “The problem with [economic violence] is that its consequences can be potentially life-spanning.”

In another case, a few years after leaving her abusive ex-partner, a woman named Tahmina received a letter from Denmark’s tax authority. She owed them almost half a million kroner ($78,120) for a company she had never even heard of. “I was shocked,” she 

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