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Surveillance technology, heavily regulated in Europe, is freely deployed across India. Spanish firm Herta Security is among the top suppliers behind facial recognition technology solutions for Indian systems, according to Investigate Europe.

At Howrah station in Kolkata, the trains never really stop, and neither do the cameras. One of India's busiest railway terminals, around a million people pour through it every day, with crowds so dense that following a single face can be near impossible, at least with the human eye.

Yet mounted high above the entrance and exit gates, platforms, food courts and waiting rooms, around 100 live facial recognition cameras silently keep track. The system, installed in the past year, lifts faces from the live feed and cross-checks them against a database of photos: wanted offenders, criminal suspects, missing people. A match alerts the railway police to the exact spot where a person was seen and authorizes them to approach the person.

Some commuters seem unaware that they are being surveilled in this way. Barnali Biswas, a private sector employee who passes through six days a week, was unbothered when questioned by a reporter, saying she thought it was probably good for safety. "People with nothing to do with crime had nothing to fear," she said. This kind of camera, enabled with facial recognition software, is increasingly familiar across India. And in eastern India, one supplier of that software is the Spanish firm Herta Security.

According to local partners and company documents, Herta supplies hundreds of railway stations across the region, Delhi's largest prison complex, a pilgrimage site in Ayodhya, and the city control rooms of Ahmedabad.

Herta confirmed the use of its technology in India but in a written statement said that it would "not disclose confidential customer information". Its software may also be deployed at Howrah station itself, though local railway officials would not confirm this when asked.

A source at one of Herta's Indian partners told Investigate Europe that they estimated that more than 4,000 cameras across the world’s largest democracy are now powered by the Spanish firm’s technology.

At least part of that rollout is linked to the Nirbhaya Fund, a pot of public money created to tackle sexual violence after a shocking 2012 Delhi bus gang rape. Women’s rights groups in India argue that the millions of euros earmarked for the fund have been spent on mass surveillance rather than on more direct victim protection and support.

According to four leading legal scholars who specialize in EU artificial intelligence and biometrics law, two of these deployments would be deemed unlawful if they operated inside the European Union: the system on Indian Railways' Eastern Region and a city-wide surveillance program in Ahmedabad.

Herta said it took such concerns seriously, adding that its products are “developed in line with European data-protection principles, regardless of the market in which they are deployed.” However, the company said that it could not "control how public authorities or system integrators implement the technology in specific environments".

Italian Member of the European Parliament Brando Benifei, however, said the findings raised troubling questions for the European lawmakers. "The fact that surveillance technologies banned in Europe are being exported and deployed elsewhere, such as in India's railway stations, exposes a dangerous double standard."

While the European Union has heavily restricted similar surveillance on its own citizens, Investigate Europe has found that it funded the Spanish company to develop its technology. Since 2020, Herta has received more than €3.3 million in EU research funding for projects involving "crowd behavior analysis" and facial recognition.

Herta Security was founded in Barcelona in 2009 by former Bosch employee Javier Rodríguez Saeta, a specialist in biometrics – automated identification based on people’s physical features or behavior. "Back in 2005," Rodríguez would later recall 

, "I already thought that in the future it would be necessary to identify people who did not want to be identified."

Today, the company's flagship product, BioSurveillance NEXT, is designed for what its own 

marketing materials describe as crowd-scale deployment

. Rodríguez has spoken of using it for "demonstrations, sports races, religious gatherings and airports.” The data sheet advertises real-time searches against databases of up to 100 million subjects.

The technology is underpinned by graphics-processing units, the same chips that power most current artificial intelligence and accelerate facial recognition so it can be performed in real time. In 2015, AI chipmaker Nvidia recognized Herta as 

. By 2019, Herta claimed to have amassed more than 200 clients across 50 countries.

The market Herta serves has expanded rapidly in recent years. Such tech is now used at sports stadiums in the United States, by police forces in the United Kingdom and has also been trialed by police forces across the EU.

However, the technology is heavily restricted in Europe. Since 2025, the EU AI Act has 

largely prohibited the use of real-time remote biometric identification systems

, above all facial recognition, in public spaces for law enforcement purposes. Those drafting the law identified this as one of the few uses of AI they considered unacceptable.

The ban allows three narrow exceptions: targeted searches for victims of trafficking, sexual exploitation or kidnapping, or missing persons; the prevention of a specific, imminent terrorist threat; and the identification of suspects of a closed list of serious crimes including terrorism, murder and rape. Even then, each individual use must be authorized by a judge in advance and logged in an EU database.

Herta has a track record of working with clients beyond EU borders. In a marketing presentation from 2021 and seen by Investigate Europe, Herta lists several projects.

These include city-wide surveillance schemes known as "safe-city projects" in Jamaica, Thailand and Mumbai in India. Other uses of its surveillance software include police forces in Colombia and Indonesia; football stadiums in Belarus and Russia and airports in Mexico, Nicaragua and Nigeria. It is not clear whether these partnerships are still active today.

Herta’s software has also been used in Europe. Notably, the company’s technology was trialled by the German Federal Police in 2017 and 2018 

asked about the risk that Herta’s products might be misused

. "In Europe," he said, "we are very well protected, we have very clear legislation that sets out the uses of this technology. There's nothing to fear." At that time, the EU-wide ban on real-time facial recognition in public spaces was not in place. The AI Act’s prohibition only took effect in February 2025. He did not address the protections available to citizens in his other markets such as India, where similar strict legislation is absent.

The Indian portfolio: Railways, prisons and temples

Herta's expansion into India has unfolded over a decade. Around 2014, the company supplied four or five cameras for the Mumbai Safe City project, according to a local business partner.

A former senior researcher at Herta, who asked to remain anonymous, said that the data Herta acquired through its early Indian deployments was central to overcoming problems with the algorithm's poor performance on non-white faces.

Herta told Investigate Europe that it "does not use customer operational data from deployments as a default mechanism to train or improve its algorithms". Any use of personal or biometric data for algorithmic training "would require a clear legal basis.”

The real breakthrough came eight years later. In 2022, a Delhi-based company 

won an €11.5 million tender contract for a video surveillance system

 covering hundreds of stations in eastern India. The facial recognition layer of the system runs on Herta software.

 that 540 facial recognition systems were operational at 143 stations. The full plan covers 392 stations, among them some of the largest stations in the region. Herta’s local partners said this could be fitted to more than 1,500 cameras in the near future.

Authorities regularly cross-reference faces against a watchlist of people of interest. It is not clear what criteria are used to list people, but one of Herta’s local business partners said there were around one million subjects on the watchlist.

The scale of the system is unlike anything available in Europe, they added. "On the busiest station, if I just implement one camera, you run 10,000 people in five minutes." If the system returns a match, an alert is sent to an armed police force authorized to stop them, they claimed.

treated facial recognition matches at 80 percent similarity as positive identifications

. With millions of travelers, even a small error rate is not insignificant. Significantly, the watchlist data is not public, nor are the criteria for inclusion, and there is no route to contest a false match.

Herta’s presence on the Indian rail network is not confined to the Eastern Region. Under a program run by the Railway Land Development Authority, which modernizes stations nationwide, Herta’s software has reached terminals as far as Jaipur and Secunderabad, according to Herta’s local partner.

Its software also runs facial recognition systems across three of Delhi's prison complexes, Tihar, Mandoli and Rohini, the local partner claimed. The government contract for the deployment is reportedly worth 352 million rupees (€3.2 million).

The system is not confined to public or state infrastructure. It also runs at the Ram Mandir temple in Ayodhya, where the local partner claims that the surveillance system alerts local police when individuals on a watchlist are identified. Similar deployments at two other temples are in progress, they added.

Herta also operates in the context of safe-city programs: in a marketing presentation obtained by Investigate Europe, the company claimed to have deployed 140 facial recognition cameras in Ahmedabad, and lists further deployments in several other cities.

Investigate Europe sought comments regarding the deployments by Eastern Railway, the authority implementing the Safe City Ahmedabad project, and the authorities responsible for managing Delhi’s prisons. All inquiries went unanswered.

Herta’s software is running on around 4,000 cameras across the country, according to one of its local partners.

Herta’s expansion in India is apparently linked to a policy shift triggered by an infamous rape case. In December 2012, a young physiotherapy student boarded a private bus in Delhi with a male friend after watching a film in the local cinema. Unknown to them, the bus was off-duty. The driver and five other men had stopped to pick the two of them up under the pretense of carrying passengers.

Over an hour, the six men beat her friend, gang-raped her, and threw both of them, seriously injured, from the bus. She died of her injuries two weeks later. The case triggered widespread protests across India and forced a national debate about gender violence, public safety and the state’s failure to protect women.

. Civil society groups that campaigned in the wake of the case had asked for victim support, legal aid and shelter networks, recalled a human rights lawyer involved in the discussion at the time.

The initial commitment of 10 billion rupees (€92 million) was for "the empowerment, safety and security of women and girl children". The fund came to be known by the same unofficial name the Indian press had given the young woman: Nirbhaya, meaning fearless.

Over the years, the Indian government allocated more money to the fund. By March 2025, around 58 billion rupees (€532 million) had been disbursed. Indian government data shared in February 2024 showed that roughly 50 percent went to surveillance and policing functions, versus 31 percent for direct victim support services and emergency helplines.

Some argue these new surveillance systems have not made women significantly safer. In 2014, the year after the Nirbhaya Fund was established, 340,000 crimes against Indian women were reported by 

. By 2023, the most recent year for which data is available, that figure had risen by roughly a third to 450,000.

Flavia Agnes, a Mumbai-based lawyer who estimates she has worked on around 100,000 cases of violence against women over a 40-year career, said the design of the response to the national outcry was wrong from the start.

"I have not come across cases where this kind of surveillance has helped to identify the accused," she said. Most violence against women in India does not happen in the places the cameras can see like train stations, she explains, but in the home. "About 95 percent of the rape cases take place by known people."

Audrey D'Mello, who directs a center providing legal aid to survivors of violence in Mumbai, has not seen evidence of the surveillance working in her field. The infrastructure built in the name of women's safety, she said, has rarely been about women's safety. She is more cynical about the government’s project. "They also realized," she said, "that it's easier to push in the name of women."

There is no direct evidence suggesting that the use of surveillance cameras in public spaces has not increased women’s safety in the country.

The Indian Ministry of Women and Child Development, which oversees the Nirbhaya Fund, did not respond to requests for comment.

Four scholars who work on EU artificial intelligence and biometrics law said the deployments in the Indian Railways Eastern Region and the Safe City Ahmedabad program would be unlawful in the EU.

"Such a deployment in an EU member state would quite clearly violate" the EU’s AI Act, said Rita Matulionyte from Macquarie Law School in Sydney.

Catherine Jasserand, of KU Leuven in Belgium, reached the same conclusion. "I don't think these two cases constitute good examples of the live use of facial recognition technology by police in public spaces."

"The two deployments are too broad to fall under one of the exceptions," she said, referring to the carve-outs for searches for vulnerable people, terror threats and suspects of serious crimes. Even under those exceptions, EU law requires it first to pass a national statute authorizing the practice, with detailed rules on supervision, reporting and judicial control. Spain, where Herta is based, has passed no such law, meaning the company could not legally run the system at home as in India.

India's own legal framework offers no comparable protection. India has no comprehensive data-protection law in force, and what it has passed 

exempts policing and law enforcement so broadly

 that deployments like these remain effectively unregulated.

"India is definitely one of the leading adopters of facial recognition technology in the world without any safeguards," said Apar Gupta, a Delhi-based digital rights lawyer and founder of the Internet Freedom Foundation.

Herta has received EU public money to develop the kind of technology that it sells in India. According to an analysis by Investigate Europe, the company has received at least €3 million in EU research funding over the past five years, with further support from Spanish national programs. The largest single grant, worth €2.36 million between 2022 and 2024, supported a Herta project called FUTURE.

The technology developed under the project was, according to Herta, designed to perform "crowd behavior analysis to identify abnormal activities and potential threats in large gatherings, public events, and high-traffic areas".

on the project's website, since taken down but preserved in web archives

, described its facial recognition layer as a tool for law enforcement agencies "to swiftly and accurately identify suspects and terrorists".

The use case described by Herta – real-time identification of suspects in crowded public spaces – is precisely the scenario the EU largely prohibited on its own soil soon after the FUTURE project ended. However, it is a blueprint that appears to be adopted in India.

"As with many technology companies, knowledge gained through research projects may contribute to the general evolution of our expertise, methodologies and product roadmap," a Herta spokesperson said.

"However, EU research funding is not used to finance, operate or subsidize specific commercial deployments in India or elsewhere."

The European Commission did not respond to requests for comment by the time of publication.

Italian MEP Brando Benifei led negotiations for the European Parliament in finalizing the AI Act. While the use of such facial recognition technology is now largely banned at home, Benifei believes the law must go further and prevent exports outside the EU altogether.

"The European Union cannot claim to be a global champion of digital rights if we allow our companies to profit abroad from tools deemed too dangerous for European citizens," he said. "We should find arrangements to not allow the export and use abroad of systems we would not permit at home."

Pulitzer Center’s AI Accountability Network

 are highly prominent digital policy issues. Yet like many concepts propelled by political debates and turbocharged by geopolitical change, these terms risk being stretched beyond analytical usefulness. Definitions vary, evidence for policy suggestions is often thin, and debates are frequently driven more by opinions and rhetoric than by evidence-based analyses.

This article draws on multiple years of research conducted within the 

 and multistakeholder debates on data governance within the 

, the Center for Technology and Society at FGV Law School in Rio de Janeiro. Rather than focusing narrowly on legislative developments, our work has analyzed how emerging economies may translate sovereignty claims into concrete digital, industrial and developmental policies. This perspective reveals a more operational understanding of data sovereignty, rooted less in formal legal prescriptions than in the capacity to shape and benefit from 

Indeed, across leading emerging economies, data is increasingly treated as a strategic resource that warrants protection but, crucially, must also be mobilized for development. From this standpoint, 

 is not synonymous with autarky or isolationism. It is better understood as the capacity to know how and why data are processed, by whom; to develop the technical means to process and extract value fairly from data; and to regulate these processes effectively. In short, it entails retaining and upgrading what has been defined as “informational self-determination” over the past four decades.

Digital sovereignty can be seen as an extension of the longstanding 

 of the UN Charter and reaffirmed in the 

International Covenant on Civil and Political Rights

International Covenant on Economic, Social and Cultural Rights

 (ICESCR), this principle stipulates the peoples’ fundamental right to “pursue their economic, social and cultural development.” Within a digital context, this right acquires a technological dimension: control over data and digital infrastructures becomes integral to the ability to chart an autonomous developmental path.

This conception aligns with what I defined as “

,” which rejects authoritarian and protectionist conceptions of digital sovereignty and embraces the use of technology to foster development, innovation and competition, in accordance with constitutional values. Sovereignty, in this view, can be exercised by a plurality of actors—public, 

—provided they possess the capacity to understand, use and develop digital technologies. Sovereignty thus depends as much on 

operational capability as on regulatory authority

The legal dimension is nonetheless foundational. Informational self-determination was first recognized by the German Constitutional Court in its landmark 1983 

 and reaffirmed more recently by the Inter-American Court of Human Rights in the 

. It constitutes a standalone fundamental right requiring active state protection.

Traditionally associated with personal data protection, this right must now be interpreted more broadly. Indeed, it seems increasingly evident it has 

both individual and collective dimensions

: individuals should control their personal data, but administrations, corporations and entire societies, too, should be able to exercise control and derive value from the data they generate.

The link to digital sovereignty is direct. Autonomy, whether individual or collective, presupposes not only formal rights, but also effective control over the technological systems that produce, process and monetize data.

 as “the new oil.” Yet the analogy is misleading if taken at face value. Unlike oil, data is often extracted without meaningful compensation or control. Vast quantities of valuable information—generated by individuals, public institutions, researchers and businesses—are effectively ceded to a small number of global technology firms that subsequently refine them, reselling the refined product extracting enormous value, and selectively sharing insight with national intelligence agencies.

Data is remarkably different from oil. Oil is largely fungible regardless of whether it is extracted in Brazil, Norway or Texas, and is depleted once consumed. Data is inherently contextual and non-rival. Information generated by Brazilian courts and administrations, Norwegian researchers or Texan consumers is unique, cannot be replicated elsewhere, reveals unique insights and—potentially—can be reused to fuel large-scale analytics and train proprietary AI systems indefinitely.

The rise of generative AI intensifies this dynamic. Users are not merely consumers: they actively work to contribute high-value data that plays an essential role in training AI systems. A few global firms extract local data to commercialize AI worldwide, capturing value away from its source.

Breaking this pattern requires more than rhetorical recognition of data as “

.” It demands the capacity to understand how data-processing technologies function, to develop alternative technologies domestically, and to regulate them effectively. Absent these capabilities, countries—especially 

—risk reproducing and exacerbating historical patterns of dependency, becoming suppliers of informational raw materials without sharing in the economic and technological gains.

Crucially, simplistic policy responses are inadequate. 

, which consists of storing data within national borders, is often presented as a solution. In practice, it is no panacea. Data may remain subject to foreign jurisdiction through extraterritorial laws; they may be replicated across global infrastructures on which neither individuals nor national regulators exercise any control or oversight; and may be accessed by foreign governments and processed by foreign-controlled platforms irrespective of where they are stored.

Without broader strategies connecting stringent cybersecurity requirements—including robust controls over access to cryptographic keys—to the development of local infrastructure and technological capabilities, localization, per se, risks being largely symbolic.

The limits of regulation and the untapped potential of fiscal policy

The proliferation of data protection laws over the past decades reflects an important normative shift. Yet the assumption that legal frameworks alone can secure data sovereignty is flawed. Sovereignty depends not only on the existence of rules but on the capacity to enforce them and to shape the environment in which they operate.

Adopting data protection legislation is necessary, but the mere existence of a law does not guarantee effective control 

. Enforcement agencies typically lack resources, technical expertise, and political support necessary to regulate effectively.

Without an industrial policy that actively promotes investment in technological capabilities, well-intentioned laws risk becoming either empty aspirations or an excessive burden on small and medium enterprises. This gap between formal regulation and practical reality is particularly pronounced in developing economies. There, the challenge is not merely to import regulatory models but to build the underlying ecosystem, including human capital, research infrastructure, and industrial capabilities, required to make those models effective.

In this perspective, if data is a source of economic value, then questions of 

 of such value become unavoidable in order to support the aforementioned policies. Who captures the value generated by data, and on what terms? Here, taxation should be understood not only as a revenue-generating tool but as a regulatory instrument. Properly designed, tax policies can incentivize responsible data governance, encourage investment in local ecosystems, and discourage business models based on the massive extraction and concentration of data.

At present, in most jurisdictions such policies are largely absent. A telling illustration is the principle of data minimization, also framed as the 

, which requires that only personal data strictly needed for a specific purpose be collected and processed. While normatively appealing, its practical application is frequently undermined by prevailing economic incentives. In the context of AI development in particular, the dominant logic is one of data maximization: market advantage accrues to actors capable of amassing and processing the largest possible datasets, often through 

 that sit uneasily with both data protection and copyright frameworks.

In the absence of fiscal or regulatory mechanisms that reward data minimization and put a price on uncontrolled data maximization, there is little incentive to adhere to normative principles. This situation undermines both data protection and fiscal sovereignty. It creates an asymmetry in which both data and value are extracted from one jurisdiction but realized in another, exacerbating global inequalities.

Brussels Effect or Dunning–Kruger Effect?

” is often cited as evidence of the European Union’s ability to shape global regulatory standards, notably through the diffusion of GDPR-inspired data protection regimes. This influence is real and has contributed to a degree of legislative convergence. Yet it may also have fostered a misleading sense of sufficiency.

The prominence of data protection law as the primary tool of digital governance risks encouraging regulatory overconfidence. In this sense, the comparison with another phenomenon, the 

, is apt: the existence of sophisticated legal frameworks can create the illusion of control, masking deeper structural limitations.

Adopting a law does not equate to technological autonomy. Nor does it, by itself, ensure effective control over data flows, infrastructures or enforcement contexts. Extraterritorial legal regimes, the operational practices of global service providers, the concentration of digital infrastructure, and the limited capacity of regulators all constrain the ability of both individuals and states to meaningfully exercise informational self-determination.

Addressing these challenges requires a more integrated approach, coordinating policies spanning education, research, industrial development, tax reform, digital infrastructure, cybersecurity and data governance. Absent such coordination, countries remain vulnerable, dependent on foreign technologies and subject to external control over critical digital resources.

Data sovereignty, therefore, is a composite condition, requiring the alignment of legal authority, developmental capabilities and governance capacity. This will be the focus of the 

, dedicated to “Data Governance for Digital Sovereignty, Cooperation, and Interoperability.” Considering these dimensions as quintessentially intertwined is instrumental to move beyond symbolic assertions and achieve genuine control over one’s digital future.

Noam Chomsky once observed that most people spend much of their lives in totalitarian systems. That system, 

In most workplaces, individuals exercise little meaningful democratic control over the conditions governing their existence: salary, working hours, surveillance, behavior. People are normally free to leave, but generally only on the condition that they subordinate themselves elsewhere. The alternative is starvation. In practice, most people spend the greater part of their lives inside institutions they don’t control. Trade unions and labor protections have mitigated some of these conditions through long political struggle, but the underlying structure of top-down authority in the majority of workplaces has remained largely intact.

For decades, the dominant education policy in most of the world rested on a relatively simple promise rooted in so-called human capital theory: accumulate qualifications, acquire technical skills, adapt continuously to the economy, and security through professional work would follow.

Yet the promised outcomes are becoming harder to see. Across wealthy economies, university participation has reached 

 while the labor-market advantage associated with higher education has eroded. Young graduates face one of the weakest entry-level labor markets in decades. Unemployment among Americans aged 22-27 reached 

 of US graduates work in jobs that don’t need degrees. In Britain, only 60.4% of graduates aged 21-30 are employed in high-skilled occupations while 

 outside London work in jobs that don’t require a degree, up from 31% in 1993.

AI now bypasses the original logic of the educational bargain altogether.

The industries that spent years encouraging young people towards technical and professional careers are shedding workers at remarkable speed. Meta 

 thousands of layoffs while redirecting resources towards AI infrastructure and automation. Amazon, after years of promoting engineering and computer science through initiatives such as 

 tens of thousands of corporate jobs as AI expands across its operations. Oracle workers recently described mass layoffs in 

: “Everyone’s a line on a spreadsheet.” A 

 report also documents sharp reductions in entry-level hiring, raising obvious questions about how younger workers are expected to acquire experience in the first place. Previous waves of technological change largely complemented human labor while creating new industries and occupations. AI today is increasingly being deployed to substitute for human work itself – 

 tasks and eroding the professional pathways 

 to prepare people for. Yet much of the policy response continues to assume that the central challenge is simply preparing more people for the labor market.

Two recent policy reports in the UK captured the scale of the problem. One, a major 

 by the Skills Commission on young people not in education, employment or training, warned that Britain now faces a “generational challenge”, with close to one million young people outside both work and education, rising levels of mental ill health, collapsing youth services and deepening insecurity around transitions into adult life. The 

, former chair of Social Mobility Foundation Alan Milburn’s government-commissioned 

, points to a “rising tide of mental ill-health, anxiety, depression and neurodiversity” as a major factor behind growing economic inactivity.

Yet both frame the solution largely through employability, skills pipelines, apprenticeships and labor-market participation, as though the central task were simply integrating people more efficiently into an economic model that is already producing widespread precarity.

Moreover, education policy still treats economic participation as the central purpose of the entire education system, while continuing to 

 digitization ever further across schools and universities and presenting digital participation and AI integration as 

What rarely gets discussed, however, is that this insecurity has long served the interests of those who benefit most from the existing economic order. In the late 1990s, the late Alan Greenspan, former chair of the US Federal Reserve, 

 that worker insecurity was helping contain inflation in the United States. Workers, he observed, had become too fearful of job loss and technological obsolescence to demand higher wages even during periods of economic growth. Job insecurity, Greenspan 

, had become more important than wage gains.

Anxiety and weakened bargaining power function as sustaining features of the economic system itself. As the labor historian Norman Ware argued nearly a century ago in 

, this subordination of labor was not an accidental by-product of industrialization but one of its organizing principles. A “healthy” economy, in this view, depends to a significant degree on workers feeling too insecure to resist deteriorating conditions. Put otherwise, much of what young generations experience is not accidental, but part of an economic model whose beneficiaries depend on precisely that insecurity.

The logic of insecurity now extends deeply into education itself. Universities mirror many of these same dynamics. Students accumulate extraordinary levels of debt in exchange for no clear guarantee of stability or professional security. In the United States, federal student debt has 

. In England, graduates leave university with some of the highest 

 levels in the world: the average borrower entering repayment in 2024 owed around £53,000, while total outstanding student debt has reached £267 billion. 

The question, then, is what kind of education would make sense now?

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