#FactCheck: Misleading Clip of Nepal Crash Shared as Air India’s AI-171 Ahmedabad Accident

Introduction

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AI is transforming the way work is done and redefining the nature of jobs over the next decade. In the case of India, it is not just what duties will be taken over by machines, but how millions of employees will move to other sectors, which skills will become more sought-after, and how policy will have to change in response. This article relies on recent labour data of India's Periodic Labour Force Survey (PLFS, 2023-24) and discusses the vulnerabilities to disruption by location and social groups. It recommends viable actions that can be taken to ensure that risks are minimised and economic benefits maximised.

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India’s Labour Market and Its Automation Readiness

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According to India’s Periodic Labour Force Survey (PLFS), the labour market is changing and growing. Participation in the labour force improved to 60.1 per percent in 2023-24 versus 57.9 per cent the year before, and the ratio of the worker population also improved, signifying the increased employment uptake both in the rural and urban geographies (PLFS, 2023-24). There has also been an upsurge of female involvement. However,  a big portion of the job market has been low-wage and informal, with most of the jobs being routine and thus most vulnerable to automation. The statistics indicate a two-tiered reality of the Indian labour market: an increased number of working individuals and a structural weakness.

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AI-Driven Automation’s Impact on Tasks and Emerging Opportunities 

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AI-driven automation, for the most part,  affects the task components of jobs rather than wiping out whole jobs. The most automatable tasks are routine and manual, and more recent developments in AI have extended to non-routine cognitive tasks like document review, customer query handling, basic coding and first-level decision-making. There are two concurrent findings of global studies. To start with, part of the ongoing tasks will be automated or expedited. Second, there will be completely new tasks and work positions around data annotation, the operation of AI systems, prompt engineering, algorithmic supervision and AI adherence (World Bank, 2025; McKinsey, 2017).

In the case of India, this change will be skewed by sector. The manufacturing, back-office IT services, retail and parts of financial services will see the highest rate of disruption due to the concentration of routine processes with the ease of technology adoption. In comparison, healthcare, education, high-tech manufacturing and AI safety auditing are placed to create new skilled jobs. NITI Aayog estimates huge returns in GDP with the adoption of AI but emphasises that India has to invest simultaneously in job creation and reskilling to achieve the returns (NITI Aayog, 2025).

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Groups with Highest Vulnerability in the Transition to Automation

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The PLFS emphasises that a large portion of the Indian population does not have any formal employment and that the social protection is minimal and formal training is not available to them. The risk of displacement is likely to be the greatest for informal employees, making up almost 90% of India’s labour force, who carry out low-skilled, repetitive jobs in the manufacturing and retail industry (PLFS, 2023-24). Women and young people in low-level service jobs also face a greater challenge of transition pressure unless the reskilling and placement efforts can be tailored to them. Meanwhile, major cities and urban centres are likely to have openings for most of the new skilled opportunities at the expense of an increasing geographic and social divide. 

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The Skills and Supply Challenge

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While India’s education and research ecosystem is expanding, there remain significant gaps in preparing the workforce for AI-driven change. Given the vulnerabilities highlighted earlier, AI-focused reskilling must be a priority to equip workers with practical skills that meet industry needs. Short modular programs in areas such as cloud technologies, AI operations, data annotation, human-AI interaction, and cybersecurity can provide workers with employable skills. Particular attention should be given to routine-intensive sectors like manufacturing, retail, and back-office services, as well as to regions with high informal employment or lower access to formal training. Public-private partnerships and localised training initiatives can help ensure that reskilling translates into concrete job opportunities rather than purely theoretical knowledge (NITI Aayog, 2025)

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The Way Forward

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To facilitate the change process, the policy should focus on three interconnected goals: safeguarding the vulnerable, developing competencies on a large-scale level, and directing innovation towards the widespread ability to benefit.

1. Protect the vulnerable through social buffers. Provide informal workers with social protection in the form of portable benefits, temporary income insurance based on reskilling, and earned training leave. While the new labour codes provide essential protections such as unemployment allowances and minimum wage standards, they could be strengthened by incorporating explicit provisions for reskilling. This would better support informal workers during job transitions and enhance workforce adaptability.
2. Short modular courses on cloud computing, cybersecurity, data annotation, AI operations, and human-AI interaction should be planned through collaboration between public and private training providers. Special preference should be given to industry-certified certifications and apprenticeship-based placements. These apprenticeships should be made accessible in multiple languages to ensure inclusivity. Existing government initiatives, such as NASSCOM’s Future Skills Prime, need better outreach and marketing to reach the workforce effectively.
3. Enhance local labour market mediators. Close the disparity between local demand and the supply of labour in the industry by enhancing placement services and government-subsidised internship programmes for displaced employees and encouraging firms to hire and train locally.
4. Invest in AI literacy, AI ethics, and basic education. Democratise access to research and learning by introducing AI literacy in schools, increasing STEM seats in universities, and creating AI labs in the region (NITI Aayog, 2025).
5. Encourage AI adoption that creates jobs rather than replaces them. Fiscal and regulatory incentives should prioritise AI tools that augment worker productivity in routine roles instead of eliminating positions. Public procurement can support firms that demonstrate responsible and inclusive deployment of AI, ensuring technology benefits both business and workforce.
6. Supervise and oversee the transition. Use PLFS and real-time administrative data to monitor shrinking and expanding occupations. High-frequency labour market dashboards will allow making specific interventions in those regions in which the acceleration of displacement occurs.

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Conclusion

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The integration of AI will significantly impact the future of the Indian workforce, but policy will determine its effect on the labour market.  The PLFS indicates increased employment but a structural weakness of informal and routine employment. Evidence from the Indian market and international research points to the fact that the appropriate combination of social protection, skills building and responsible technology implementation can change disruption into a path of upward mobility. There is a very limited window of action. The extent to which India will realise the productivity and GDP benefits predicted by national research, alongside the investments made in labour market infrastructure, remains uncertain. It is crucial that these efforts lead to the capture of gains and facilitate a fair and inclusive transition for workers.

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References

• Annual Report Periodic Labour Force Survey (PLFS) JULY 2022 - JUNE 2023. 
• Future Jobs: Robots, Artificial Intelligence, and Digital Platforms in East Asia and Pacific, World Bank. 
• Jobs Lost, Jobs Gained: What the Future of Work Will Mean for Jobs, Skills, and Wages, McKinsey Global Institute 
• Roadmap for Job Creation in the AI Economy, NITI Aayog
• India central bank chief warns of financial stability risks from growing use of AI, Reuters 
• AI Cyber Attacks Statistics 2025, SQ Magazine. 

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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

A photo circulating on social media depicting modified tractors is being misrepresented as part of the 'Delhi Chalo' farmers' protest narrative. In the recent swirl of misinformation surrounding the 'Delhi Chalo' farmers' protest. A photo, ostensibly showing a phalanx of modified tractors, has been making the rounds on social media platforms, falsely tethered to the ongoing protests. This image, accompanied by a headline suggesting a mechanical metamorphosis to resist police barricades, was allegedly published by a news agency. However, beneath the surface of this viral phenomenon lies a more complex and fabricated reality.

The Movement 

The 'Delhi Chalo' movement, a clarion call that resonated with thousands of farmers from the fertile plains of Punjab, the verdant fields of Haryana, and the sprawling expanses of Uttar Pradesh, has been a testament to the agrarian community's demand for assured crop prices and legal guarantees for the Minimum Support Price (MSP). The protest, which has seen the fortification of borders and the chaos at the Punjab-Haryana border on February 13, 2024, has become a crucible for the farmers' unyielding spirit.

Yet, amidst this backdrop of civil demonstration and discourse, a nefarious narrative of misinformation has taken root. The viral image, which has been shared with the fervour of wildfire, was accompanied by a screenshot of an article allegedly published by the news agency. This article, dated February 11, 2024, quoted an anonymous official who claimed that intelligence agencies had alerted the police to the protesters' plans to outfit tractors with hydraulic tools. The implication was clear: these machines had been transformed into battering rams against the bulwark of law enforcement.

The Pursuit of Truth

However, the India TV Fact Check team, in their relentless pursuit of truth, unearthed that the viral photo of these so-called modified tractors is nothing but a chimerical creation, a figment of artificial intelligence. Visual discrepancies betrayed its AI-generated nature. 

This is not the first time that the misinformation has loomed over the farmers' protest. Previous instances, including a viral video of a modified tractor, have been debunked by the same fact-checking team. These efforts are a bulwark against the tide of false narratives that seek to muddy the waters of public understanding.

The claim that the photo depicted modified tractors intended for use in the ‘Delhi Chalo’ farmers' protest rally in Delhi on February 13, 2024, was a mirage. 

The Fact Check

OpIndia, in their article, clarified that the photo used was a representative image created by AI and not a real photograph. To further scrutinize this viral photo, the HIVE AI detector tool was employed, indicating a 99.4% likelihood of the image being AI-generated. Thus, the claim made in the post was misleading.

The viral photo claiming that farmers had modified their tractors to avoid tear gas shells and remove barricades put up by the police during the rally was a digital illusion. The internet has become a fertile ground for the rapid spread of misinformation, reaching millions in an instant. Social media, with its complex algorithms, amplifies this spread, as any interaction, even those intended to debunk false information, inadvertently increases its reach. This phenomenon is exacerbated by 'echo chambers,' where users are exposed to a homogenous stream of content that reinforces their pre-existing beliefs, making it difficult to encounter and consider alternative perspectives.

Conclusion 

The viral image depicting modified tractors for the ‘Delhi Chalo’ farmers' protest rally was a digital fabrication, a testament to the power of AI in creating convincing yet false narratives. As we navigate the labyrinth of information in the digital era, it is imperative to remain vigilant, to question the veracity of what we see and hear, and to rely on the diligent work of fact-checkers in discerning the truth. The mirage of modified machines serves as a stark reminder of the potency of misinformation and the importance of critical thinking in the age of artificial intelligence.

References

• https://www.indiatvnews.com/fact-check/fact-check-ai-generated-tractor-photo-misrepresented-delhi-chalo-farmers-protest-narrative-msp-police-barricades-punjab-haryana-uttar-pradesh-2024-02-15-917010
• https://factly.in/this-viral-image-depicting-modified-tractors-for-the-delhi-chalo-farmers-protest-rally-is-created-using-ai/

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