#FactCheck - Assam Video Falsely Shared as BJP Government Deporting Bangladeshis From West Bengal

Introduction

In the age of digital technology, the concept of net neutrality has become more crucial for preserving the equity and openness of the internet. Thanks to net neutrality, all internet traffic is treated equally, without difference or preferential treatment. Thanks to this concept, users can freely access and distribute content, which promotes innovation, competition, and the democratisation of knowledge. India has seen controversy over net neutrality, which has led to a legal battle to protect an open internet. In this blog post, we’ll look at the challenges of the law and the efforts made to safeguard net neutrality in India.

Background on Net Neutrality in India

Net neutrality became a hot topic in India after a major telecom service provider suggested charging various fees for accessing different parts of the internet. Internet users, activists, and organisations in favour of an open internet raised concern over this. Millions of comments were made on the consultation document by the Telecom Regulatory Authority of India (TRAI) published in 2015, highlighting the significance of net neutrality for the country’s internet users.

Legal Battle and Regulatory Interventions

The battle for net neutrality in India acquired notoriety when TRAI released the “Prohibition of Discriminatory Tariffs for Data Services Regulations” in 2016. These laws, often known as the “Free Basics” prohibition, were created to put an end to the usage of zero-rating platforms, which exempt specific websites or services from data expenses. The regulations ensured that all data on the internet would be handled uniformly, regardless of where it originated.

But the legal conflict didn’t end there. The telecom industry challenged TRAI’s regulations, resulting in a flurry of legal conflicts in numerous courts around the country. The Telecom Regulatory Authority of India Act and its provisions of it that control TRAI’s ability to regulate internet services were at the heart of the legal dispute.

The Indian judicial system greatly helped the protection of net neutrality. The importance of non-discriminatory internet access was highlighted in 2018 when the Telecom Disputes Settlement and Appellate Tribunal (TDSAT) upheld the TRAI regulations and ruled in favour of net neutrality. The TDSAT ruling created a crucial precedent for net neutrality in India. In 2019, after several rounds of litigation, the Supreme Court of India backed the principles of net neutrality, declaring that it is a fundamental idea that must be protected. The nation’s legislative framework for preserving a free and open internet was bolstered by the ruling by the top court.

Ongoing Challenges and the Way Forward

Even though India has made great strides towards upholding net neutrality, challenges persist. Because of the rapid advancement of technology and the emergence of new services and platforms, net neutrality must always be safeguarded. Some practices, such as “zero-rating” schemes and service-specific data plans, continue to raise questions about potential violations of net neutrality principles. Regulatory efforts must be proactive and under constant watch to allay these worries. The regulatory organisation, TRAI, is responsible for monitoring for and responding to breaches of the net neutrality principles. It’s crucial to strike a balance between promoting innovation and competition and maintaining a free and open internet.

Additionally, public awareness and education on the issue are crucial for the continuation of net neutrality. By informing users of their rights and promoting involvement in the conversation, a more inclusive and democratic decision-making process is assured. Civil society organisations and advocacy groups may successfully educate the public about net neutrality and gain their support.

Conclusion

The legal battle for net neutrality in India has been a significant turning point in the campaign to preserve an open and neutral internet. A robust framework for net neutrality in the country has been established thanks to legislative initiatives and judicial decisions. However, due to ongoing challenges and the dynamic nature of technology, maintaining net neutrality calls for vigilant oversight and strong actions. An open and impartial internet is crucial for fostering innovation, increasing free speech, and providing equal access to information. India’s attempts to uphold net neutrality should motivate other nations dealing with similar issues. All parties, including politicians, must work together to protect the principles of net neutrality and ensure that the Internet is accessible to everyone.

Introduction

Meta's bet that smart glasses will succeed the smartphone as the dominant personal computing device is, commercially, already paying off. EssilorLuxottica, the eyewear manufacturer that builds the Ray-Ban and Oakley Meta product lines, reported selling more than seven million pairs of AI-enabled glasses in 2025 alone, more than tripling the previous year's sales. Chief Executive Mark Zuckerberg has framed the shift as inevitable, comparing it in a recent interview to the transition from flip phones to smartphones and predicting that within a few years, eyewear without embedded AI will put its wearer at a disadvantage.

Yet as adoption accelerates, two features in various stages of internal testing have pulled Meta back into a familiar and uncomfortable position: at the centre of a privacy controversy over exactly how much a camera- and microphone-equipped wearable can quietly learn about the people around it.

NameTag and the return of facial recognition

In June 2026, the technology publication Wired reported that it had found dormant code for a facial-recognition system, internally called NameTag, embedded inside the Meta AI companion app that pairs with the company's smart glasses – an app that had by then been downloaded more than 50 million times. According to that reporting, the system relies on a pipeline of on-device AI models that detect a face, store it locally on the wearer's phone, and match it against previously saved "faceprints", alerting the wearer when it recognises someone they met before. Meta's Chief Technology Officer, Andrew Bosworth, has described the intended design as privacy-conscious: identification data would be encrypted locally, accessible only while the glasses are being worn, and would not populate a centralised company database. He has pitched the feature as a solution to the everyday difficulty of recalling names and past conversations.

Privacy researchers and advocacy groups have been considerably less reassured. One technologist with the Electronic Frontier Foundation’s Threat Lab who analysed the code concluded that despite having been deactivated, it appeared to be near-complete, and more recent reporting connected a portion of Meta’s facial recognition software licensing to Rank One Computing, a vendor that has also licensed similar tech to both U.S. law enforcement and military groups. Meta took the code down immediately after the story’s publication and claims no decision has been made regarding a public rollout.

"Super sensing" and always-on capture

A second, less publicised effort has drawn similar concern. The Financial Times reported in July 2026 that Meta is internally prototyping glasses, under the working concept "super-sensing", designed to capture ambient audio continuously and take still images every few seconds throughout the day, building a searchable log that a wearer's AI assistant could later query to recall where an item was left or what was discussed earlier. Notably, that reporting indicated Meta had discussed shipping the feature without activating the small LED indicator that currently signals when the glasses' camera is capturing photos or video the very light Meta had just reinforced against tampering on its existing hardware. Critics point out that the indicator is already a limited safeguard, since it is easily missed and unfamiliar to most bystanders; removing it during continuous, always-on capture would eliminate the one visible cue currently available to people nearby.

A pattern regulators are watching closely

Both features have emerged against a backdrop of substantial legal exposure. Meta has previously paid roughly two billion dollars combined in biometric-privacy settlements tied to earlier facial-recognition systems on Facebook, including $650 million under Illinois's Biometric Information Privacy Act and $1.4 billion to the state of Texas. 

A separate class action filed in early 2026 alleges that footage captured by smart-glasses users, including intimate recordings from inside private homes, was reviewed by outside contractors in Kenya for AI-training purposes, a claim that prompted an inquiry from the United Kingdom's Information Commissioner's Office. The Texas Attorney General has opened its own civil investigation into the glasses' data practices. Because U.S. federal privacy law remains fragmented, enforcement of claims like these is likely to continue playing out state by state through statutes such as BIPA, which allow individuals to sue directly, even as the European Union's AI Act imposes separate restrictions on biometric processing within Europe.

Why this matters beyond Meta

For readers focused on cybersecurity and digital privacy, the common thread running through NameTag and super sensing is consent architecture. The smart glasses take in not just what you’re up to but also the location, face, clothes and conversation patterns of anyone within the glasses’ field of vision – all without their consent. Where raising a smartphone to take a photo leaves no ambiguity to nearby observers, glasses made to look like normal eyewear leaves fewer visual and verbal tells of what is actually occurring behind a set of seemingly average lenses. According to security experts and law professors, wiretap laws and the patchwork of existing statutes addressing biometric data aren't prepared for the kind of invisible monitoring that AI-enabled eyeglasses from Meta, and eventually others, are capable of. It's that imbalance between a technology’s unseen power and the limitations of the average person’s awareness that is sure to be the main source of conflict.

CyberPeace Insights

Wearable AI holds real promise for accessibility and everyday convenience, and Meta's continued investment reflects where personal computing is headed. At the same time, features like NameTag and "super-sensing" show why privacy-by-design must stay foundational, not incidental, as this space matures. The core issue isn't innovation itself but consent — ensuring bystanders retain visible, reliable cues when a device is active. Meta's stated moves toward on-device processing and encryption are worth acknowledging as steps in the right direction. CyberPeace believes continued dialogue between industry, regulators, and researchers, rather than adversarial scrutiny alone, is the surest path to public trust.

Conclusion

Meta maintains that both NameTag and Super Sensing remain unreleased and unconfirmed for commercial launch and are subject to further internal review. Executives have publicly disputed characterisations suggesting either feature is further along than the company has described. Even so, the recurring pattern of infrastructure for sensitive capabilities surfacing through independent reporting rather than company disclosure is what has kept privacy advocates, journalists, and regulators paying close attention. It suggests that as smart glasses move from novelty item to mass-market device, the terms of that transition will be shaped as much by courts, regulators, and public pressure as by Meta's own product roadmap.

References

1. https://www.magzter.com/stories/newspaper/Mint-Mumbai/METAS-FLOOD-OF-SMARTGLASSES-HAS-PRIVACY-ADVOCATES-UP-IN-ARMS 
2. Engadget — Wired found code for an unreleased facial recognition feature in Meta's AI app
3. Malwarebytes Labs — Meta's face-recognition code raises new concerns about smart glasses
4. Kaspersky Daily — What's wrong with Meta's NameTag feature and why you should be wary of it
5. Biometric Update — AI glasses reveal widening gap between Meta's privacy safeguards and AI ambitions
6. Fortune — Meta added a privacy-safety feature to its AI glasses but is reportedly testing a 'super-sensing' prototype
7. MacRumors — Meta's 'Super Sensing' Prototype Glasses Quietly Record Everything
8. TechCrunch — Meta sued over AI smart glasses' privacy concerns, after workers reviewed nudity, sex, and other footage

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Introduction
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In April 2026, there was a fascinating example of the risks of generative artificial intelligence (AI). An Indian medical student, aged 22, developed a fake AI-driven influencer "Emily Hart" and leveraged the persona to amass a substantial social media following, engagement and revenue. 

It isn't just a case of online fraud. It is a turning point in the nature of influence, veracity, and profitability in the digital world. Ultimately, it poses a troubling question. If users can't tell the difference between real and fake people, then what is online trust?
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The Making of a Synthetic Influencer

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“Emily Hart” was a young, conservative American nurse. The identity was completely made-up, created with the help of AI programs that produced eerily realistic images, captions and engagement techniques.

The creator did not work with random content. They crafted the influencer to cater to a particular audience. With this in mind, the account was able to target conservatives in the United States who are politically active. It is reported that some of its posts have achieved millions of views, and within a few months, the influencer had thousands of followers.

Monetisation followed naturally. The account owner monetised through subscriptions and the sale of merchandise, reportedly earning thousands of dollars a month with fewer than an hour a day of "work" on the account.

The disproportionate effort and reward is what is interesting about this case. This is a unique example of how people can now use very little capital to create digital personas that attract value.

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Why It Worked: Engagement, Identity, and Algorithmic Incentives

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The "Emily Hart" case was no accident. It was enabled by three complementary factors.

First, identity targeting was crucial. The persona was constructed to fit a particular worldview and culture, making it more relevant and resonating with the target audience. AI platforms were even deployed to better target and position the persona, and it is suggested that micro-targeting would increase engagement.

Second, it was amplified by algorithms. Social media algorithms favour engagement, sometimes favouring emotional and divisive content. The account exploited this by producing visually appealing content with a strong political message, what the creator called "engageable" content.

Third, the authenticity of the AI content minimised distrust. Generative models have become so realistic that it is hard to tell if images are real or not. Specialists point out that AI increases the credibility and scalability of fake profiles, increasing their influence and reach.

All of this combined to make deception profitable. 

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The Blurring of Authenticity in Digital Spaces
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The "Emily Hart" phenomenon is emblematic of a broader shift in authenticity. Historically, influence was correlated with human personalities who establish trust over time. But AI upends this paradigm by allowing the creation of entirely fabricated personalities capable of mimicking, and even surpassing, human influencers.

This has two immediate consequences.

First, the truth is harder to discern. While platforms might require that AI-generated content be disclosed, there are inconsistencies in how this is policed. Here, the account apparently didn't disclose until it was banned for fraud.

Second, authenticity may not be as important to consumers. Consumers may view content for ideological or emotional reasons, rather than for its accuracy. This indicates that the rise of synthetic influencers is not just a technical problem but also a behavioural one.

The implication is stark. The internet is evolving into a place where authenticity is more important than truth.
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Economic Incentives and the Rise of Synthetic Monetisation
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The key difference between this fraud and previous ones is the business model. This creator didn't break into a computer or steal personal information. He cultivated an audience and sold attention.

This is an example of how the internet economy works. Attention is a commodity and platforms aim to generate it. AI reduces the cost of creating attention-generating artefacts, enabling people to amplify their reach.

This gives rise to synthetic monetisation. Online characters can be developed, fine-tuned and leveraged as money-spinning assets. In this case, identity is a product.

This raises regulatory challenges. Current laws on fraud, advertising and consumer protection may not be sufficient to cover cases of deceptive content sourced from an identity.
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Platform Responsibility and Enforcement Gaps
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The role of platforms in enabling such scenarios cannot be overlooked. Although platforms have policy guidelines on disclosure of AI-generated content, these are inconsistently applied.

In the case of "Emily Hart", the account apparently existed for some time before being shut down for scamming. This implies that either the ability to detect such accounts is weak or the tools used are reactive.

The challenge is structural. Companies are rewarded for engagement, and fake accounts can help to achieve this. But they must also promote authenticity and protect against fraud.

This presents a challenge between commercial interests and user safety. Without enforcement, synthetic influencers will become more prevalent. 
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Policy Implications: Rethinking Trust and Verification
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^{The "Emi}ly Hart" incident highlights a number of policy issues.

First, disclosure policies must be improved and harmonised. Consumers need to be clear when content is generated by AI, and platforms need to police this.

Second, identity verification needs to be updated. Classic forms of verification may not hold up in an era of imaginary characters amassing legions of fans. Alternative digital verification may be needed.

Third, new regulations should apply to synthetic identities. This means clarifying distinctions between art, commerce and fraud.

Finally, digital literacy becomes critical. Consumers need to be equipped to operate in a space where virtual personas aren't always human.

Conclusion
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The rise of "Emily Hart" is not just an example of one person using AI to make money. It is a glimpse of a digital revolution.

AI is redefining how influence can be generated, trust can be established and value can be monetized. As digital personas become more realistic, the distinction between human and machine will remain unclear.

The challenge will not be to stop AI being used to generate content. It is to ensure that the systems that mediate our online interactions are able to tell the difference, and that we are not left on our own to sort it all out.

When anyone can make a convincing identity for themselves, trust will no longer be a given. It will need to be engineered, policed and protected. 

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