How Countries Are Weaponizing AI (and Why It Matters)

Introduction

Facial recognition technology (FRT) is rapidly entering everyday life, from unlocking smartphones and boarding airplanes to helping police identify suspects. Proponents tout its security benefits: faster identity checks, improved safety, and crime prevention. For example, the U.S. Transportation Security Administration (TSA) reports that automated face scans at airports provide a “significant security enhancement” by confirming travelers match their ID. 

Many governments and businesses now rely on FRT for access control and surveillance. Yet this powerful tool also raises serious ethical questions about surveillance, consent, bias, and data protection. Critics warn that constant face-scanning undermines personal privacy and civil liberties. In practice, striking a balance between security advantages and privacy rights is complex. Weighing the promise of crime prevention against risks like wrongful identification, unequal treatment, and intrusive tracking is at the heart of the facial recognition ethics debate.

A brick wall covered with rows of CCTV surveillance cameras illustrates pervasive monitoring in public spaces.

Public safety agencies and private organizations deploy FRT in more ways than ever before. Law enforcement uses FRT to scan crowds and videos for known suspects. in 2021, about half of U.S. federal agencies and 25% of local police forces had access to facial recognition​. Border patrols and airports use face scans to verify travelers’ identities, streamlining security checks. Even mobile devices now use Face ID to unlock phones. In the retail and corporate world, FRT aids security: stores use cameras to flag shoplifters or identify VIP customers​, and companies use it for building access. 

These facial recognition security benefits can be significant. For instance, biometrics speed up screenings and reduce fraud – the TSA notes their system matches travelers to passport photos without storing images afterwards​. In casinos and banks, one-to-many facial matches help spot barred individuals or verify high-value clients. In short, FRT can enhance security and convenience by automatically verifying identities and detecting threats (e.g., catching criminals or locating missing persons) faster than manual methods.

However, the same capabilities that help catch bad actors can also invade ordinary people’s privacy. Critically, most facial recognition deployments happen without explicit consent. A person walking down the street or into a store usually cannot opt out of being scanned. Privacy advocates point out that FRT in public spaces is effectively indiscriminate surveillance – it tracks individuals everywhere, whether they have done anything wrong or not. 

As one expert notes, ubiquitous face scanning is “like walking around with your [driver’s] license stuck to your forehead,” leaving no anonymity​. Indeed, ordinary citizens generally don’t agree to (nor often even know about) FRT usage by governments and companies. This lack of consent and transparency is ethically troubling. Without consent, people lose the basic choice of whether or not to be identified. Research highlights this issue: the Center for Democracy & Technology found that most people expect only their immediate acquaintances to recognize them, not government or corporations linking their face to detailed personal profiles​.

Two security cameras mounted on a wall, representing the constant surveillance enabled by facial recognition systems.

Beyond consent, FRT raises concerns about bias and fairness. Multiple studies show that face scanners are not equally accurate for everyone. For example, a landmark MIT study found error rates as high as 20–35% for dark-skinned women, compared to below 1% for light-skinned men. In practical terms, this means people of color (especially women) are far more likely to be misidentified by the software. The U.S. National Institute of Standards and Technology (NIST) likewise found that many commercial FR algorithms return false matches for Black, Asian, and Native American faces much more often than for white faces. 

These biases arise partly because training datasets overwhelmingly contain lighter-skinned faces​. The impact of such bias can be severe. In one case reported by The New York Times, several Black men were wrongfully arrested after police used facial recognition that mismatched their images​. Civil liberties groups warn that FRT “automates discrimination”​; if the technology flags the wrong people, it can fuel racial profiling, unjust detentions, or harassment of marginalized groups. 

These inequities exacerbate existing social biases in law enforcement and marketing. (By contrast, errors remain very low for white men, meaning the technology may work “great for some and terrible for others”​.) Without careful safeguards, bias in FR systems can lead to unfair treatment – for example, black and brown communities may be surveilled and arrested at disproportionate rates due to flawed matches.

Data protection is another major ethical issue. Facial images and biometric templates are highly sensitive personal data. If a FR database is breached, the fallout can be more damaging than a password leak, because, unlike a password, one cannot change one’s face. Experts note that breaches involving face data “increase the potential for identity theft, stalking, and harassment”​. 

The permanence of face data means individuals could be tracked indefinitely. Unlike credit card numbers, which can be canceled after a theft, stolen biometric data can’t be “reset.” Moreover, FRT often aggregates data from many sources: companies like Clearview AI have scraped billions of images from the web without consent​, building databases that can be used to identify people later. 

The idea that firms or governments could compile faceloads from social media or CCTV and link them to your identity raises deep privacy alarms. Regulations like Europe’s GDPR treat biometric identifiers (including facial images) as “sensitive data,” banning their processing without explicit consent or compelling justification​. But in practice, enforcement lags, and many FR deployments still operate in a legal gray zone.

All these concerns force us to weigh the security gains against privacy costs. On one hand, facial recognition can accelerate law enforcement and border control, potentially preventing crimes or terrorism more efficiently. On the other hand, widespread FR can erode anonymity and civil liberties.

 Critics point out that the security benefits are not guaranteed to outweigh the risks: surveillance does not always reduce crime, and false positives can lead to harmful outcomes. For example, even as police adopt FRT, studies question its effectiveness: the NYPD’s counterterrorism data program in the 2010s was found to be “inaccurate and ineffective,” targeting Muslim neighborhoods. 

In general, if facial recognition is so good, why worry? Because in many scenarios, the perceived safety it brings may not compensate for the real loss of privacy and freedom. Citizens may self-censor or avoid public places if they feel watched​.

Real-world examples illustrate these trade-offs. Retailers have quietly installed facial scanners to flag suspected shoplifters, sometimes without customers’ knowledge​. While this may reduce theft (retailers report rising violent theft rates and see FRT as a deterrent​), shoppers worry about constant monitoring and profiling. 

In policing, cities like Detroit have used FRT in investigations, but concerns over misidentification have led some US departments to pause or limit use. Worldwide, governments like China have deployed facial recognition for social control, fueling fears of abuse (although detailed discussion of non-Western uses is outside our scope, it underscores the technology’s potential). 

At home, major tech companies took notice: in 2020, in Amazon, IBM, and Microsoft either halted or threatened to suspend police use of their FR tools amid protests over racial justice​​. Amazon’s one-year moratorium (initially announced June 2020) was extended, with ACLU and others urging outright bans​. These corporate actions implicitly acknowledge that unchecked FRT raises enough risk that even profit-driven firms felt compelled to pause and call for regulation.

Weighing Security Benefits Against Privacy Risks

Facial recognition presents a true dilemma of security versus privacy. Its proponents highlight many concrete advantages:

• Enhanced threat detection: Rapid identification of suspects in crowds or investigations can help law enforcement act quickly. For instance, automated face matching can locate wanted fugitives or missing persons faster than manual photo reviews.
• Convenience and efficiency: Verifying identities via a quick face scan (for example, at airports or building entrances) can streamline processes and reduce human error​.
• Loss prevention: In retail and other businesses, FRT can automatically flag known offenders or detect suspicious behavior, potentially reducing crime without confronting employees with dangerous situations.
• Access control: Using one’s face to unlock phones or enter secure facilities adds a user-friendly layer of security that is (often) harder to spoof than a password.

At the same time, these gains come with serious privacy costs:

• Pervasive surveillance: Continuous face-scanning in public means being tracked everywhere. Even law-abiding citizens can have their movements recorded without consent, which many find unacceptable​.
• Chilling effects: Knowing that every action could be recorded by a face scanner may deter people from freely exercising rights like peaceful assembly or protest.
• Errors and bias: The more accurate an FR system becomes (often through larger datasets), the broader its surveillance reach. Yet if it is not equally accurate for everyone, innocent individuals will suffer the consequences of errors​.
• Data security: Centralizing millions of biometric records creates an attractive target for hackers. A single breach of face data could endanger many lives.

Ultimately, whether FRT is justified depends on safeguards. Security agencies argue that benefits like preventing terrorism or violent crime can outweigh privacy intrusions, especially if face scans are done with oversight. Critics counter that without strict controls, the threats (e.g. false arrests, racial profiling, identity theft) are too high. Context matters: limited, accountable use (e.g. only scanning for a specific wanted person in a one-time operation) may be more acceptable than mass, indiscriminate scanning of all citizens. But in practice, many deployments blur these lines.

Regulatory and Policy Solutions

Given the tensions, lawmakers are beginning to step in with regulations. In North America and Europe, policy responses are emerging to protect privacy while permitting some security uses. Notable examples include:

• United States: Several states and cities have enacted restrictions. San Francisco (2019) was the first city to ban all municipal FRT use​. Massachusetts, Florida, and others require law enforcement to obtain warrants or meet probable cause before using facial recognition​. On the consent front, Illinois’s Biometric Information Privacy Act (BIPA) – already famous for classifying face scans as private – inspired others. As of 2023, states like Colorado have passed biometric privacy laws: Colorado’s law explicitly requires businesses to obtain opt-in consent before processing facial recognition data​. Oregon and New Hampshire prohibit using FRT on police body camera footage​. A national bill (Facial Recognition and Biometric Technology Moratorium Act) has been proposed to limit government use of FRT and require courts’ oversight, though it has not yet passed Congress.

• European Union: The EU is drafting the world’s first comprehensive AI regulation, which includes strict rules on biometric surveillance. The proposed EU AI Act would ban real-time face recognition in public spaces by law enforcement, except in narrowly defined cases (e.g., searching for a missing child, preventing an imminent threat), and only with court approval and transparency reports​. Biometric identification is classified as “high risk,” imposing rigorous requirements on data use and impact assessments​. In addition, the GDPR already treats biometric data as “special category” personal data; processing it for identity must be justified (for example, explicit consent is required)​

• Corporate Accountability: In the absence of or alongside laws, some companies have adopted their own policies. Amazon and Microsoft instituted voluntary moratoriums on sales of facial recognition technology to police, citing the need for federal regulations​. Other firms have committed to independent testing and bias mitigation or pledged not to build FR systems for unrestricted government use.

These regulatory efforts illustrate the direction of the debate. There is a growing consensus that transparency, oversight, and limits are needed. Potential solutions include: requiring audits and bias testing of FR algorithms; mandating data minimization (not storing images longer than necessary); ensuring public notice (signage where FR is in use, so people know they’re being scanned); and creating clear redress mechanisms for those harmed by misidentification. 

Some have proposed a “biometric warrant,” analogous to search warrants, to control when governments can tap facial databases. Others advocate for a tiered approach: for example, allowing one-to-one verification (matching you to your own ID) more freely, while strictly controlling one-to-many searches of crowds. Whatever the path, experts stress that public trust hinges on robust privacy guarantees.

In sum, the regulation of facial recognition technology is rapidly evolving. Europe’s AI Act and GDPR will set a high bar globally, while North American jurisdictions take varied approaches from bans to privacy laws. Advocacy groups continue pressing for outright bans on certain uses (especially mass, unconsented surveillance), whereas law enforcement and security interests push back for measured allowances. The final balance will likely require ongoing dialogue: policymakers must listen to privacy advocates, technologists, law enforcement, and the public to craft rules that ensure FRT’s security benefits do not override fundamental rights.

Conclusion

Facial recognition is a quintessential double-edged sword in modern tech ethics. It can boost security, helping guard borders, track criminals, and streamline services, yet it simultaneously erodes privacy, risks abusing power, and perpetuates bias. The debate is not one-sided: both camps have valid points. What matters is finding a responsible way forward. 

That means demanding transparency (who’s being scanned, for what purpose, and with what safeguards), enforcing strict data protection, and continually evaluating the technology’s impact on society. It also means lawmakers must catch up: clear laws and oversight are essential so that facial recognition, when used, is fair, consensual, and truly serves the public good. Only then can we harness the security advantages of face-scanning while preserving the privacy and dignity of individuals.