#FactCheck - Old Video Misleadingly Claimed as Footage of Iranian President Before Crash

Introduction 

The link between social media and misinformation is undeniable. Misinformation, particularly the kind that evokes emotion, spreads like wildfire on social media and has serious consequences, like undermining democratic processes, discrediting science, and promulgating hateful discourses which may incite physical violence. If left unchecked, misinformation propagated through social media has the potential to incite social disorder, as seen in countless ethnic clashes worldwide.  This is why social media platforms have been under growing pressure to combat misinformation and have been developing models such as fact-checking services and community notes to check its spread. This article explores the pros and cons of the models and evaluates their broader implications for online information integrity.

How the Models Work 

1. Third-Party Fact-Checking Model (formerly used by Meta) Meta initiated this program in 2016 after claims of extraterritorial election tampering through dis/misinformation on its platforms. It entered partnerships with third-party organizations like AFP and specialist sites like Lead Stories and PolitiFact, which are certified by the International Fact-Checking Network (IFCN) for meeting neutrality, independence, and editorial quality standards. These fact-checkers identify misleading claims that go viral on platforms and publish verified articles on their websites, providing correct information. They also submit this to Meta through an interface, which may link the fact-checked article to the social media post that contains factually incorrect claims. The post then gets flagged for false or misleading content, and a link to the article appears under the post for users to refer to. This content will be demoted in the platform algorithm, though not removed entirely unless it violates Community Standards. However, in January 2025, Meta announced it was scrapping this program and beginning to test X’s Community Notes Model in the USA, before rolling it out in the rest of the world. It alleges that the independent fact-checking model is riddled with personal biases, lacks transparency in decision-making, and has evolved into a censoring tool. 
2. Community Notes Model ( Used by X and being tested by Meta): This model relies on crowdsourced contributors who can sign up for the program, write contextual notes on posts and rate the notes made by other users on X. The platform uses a bridging algorithm to display those notes publicly, which receive cross-ideological consensus from voters across the political spectrum. It does this by boosting those notes that receive support despite the political leaning of the voters, which it measures through their engagements with previous notes. The benefit of this system is that it is less likely for biases to creep into the flagging mechanism. Further, the process is relatively more transparent than an independent fact-checking mechanism since all Community Notes contributions are publicly available for inspection, and the ranking algorithm can be accessed by anyone, allowing for external evaluation of the system by anyone. 

CyberPeace Insights

Meta’s uptake of a crowdsourced model signals social media’s shift toward decentralized content moderation, giving users more influence in what gets flagged and why. However, the model’s reliance on diverse agreements can be a time-consuming process. A study (by Wirtschafter & Majumder, 2023) shows that only about 12.5 per cent of all submitted notes are seen by the public, making most misleading content go unchecked. Further, many notes on divisive issues like politics and elections may not see the light of day since reaching a consensus on such topics is hard. This means that many misleading posts may not be publicly flagged at all, thereby hindering risk mitigation efforts. This casts aspersions on the model’s ability to check the virality of posts which can have adverse societal impacts, especially on vulnerable communities. On the other hand, the fact-checking model suffers from a lack of transparency, which has damaged user trust and led to allegations of bias. 

Since both models have their advantages and disadvantages, the future of misinformation control will require a hybrid approach. Data accuracy and polarization through social media are issues bigger than an exclusive tool or model can effectively handle. Thus, platforms can combine expert validation with crowdsourced input to allow for accuracy, transparency, and scalability. 

Conclusion 

Meta’s shift to a crowdsourced model of fact-checking is likely to have bigger implications on public discourse since social media platforms hold immense power in terms of how their policies affect politics, the economy, and societal relations at large.  This change comes against the background of sweeping cost-cutting in the tech industry, political changes in the USA and abroad, and increasing attempts to make Big Tech platforms more accountable in jurisdictions like the EU and Australia, which are known for their welfare-oriented policies. These co-occurring contestations are likely to inform the direction the development of misinformation-countering tactics will take.  Until then, the crowdsourcing model is still in development, and its efficacy is yet to be seen, especially regarding polarizing topics. 

References 

• https://www.cyberpeace.org/resources/blogs/new-youtube-notes-feature-to-help-users-add-context-to-videos
• https://en-gb.facebook.com/business/help/315131736305613?id=673052479947730
• http://techxplore.com/news/2025-01-meta-fact.html 
• https://about.fb.com/news/2025/01/meta-more-speech-fewer-mistakes/ 
• https://communitynotes.x.com/guide/en/about/introduction 
• https://blogs.lse.ac.uk/impactofsocialsciences/2025/01/14/do-community-notes-work/?utm_source=chatgpt.com 
• https://www.techpolicy.press/community-notes-and-its-narrow-understanding-of-disinformation/ 
• https://www.rstreet.org/commentary/metas-shift-to-community-notes-model-proves-that-we-can-fix-big-problems-without-big-government/ 
• https://tsjournal.org/index.php/jots/article/view/139/57 

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Introduction
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India’s data centre sector is rapidly emerging as strategic national infrastructure at the centre of the country’s AI ambitions, fuelled by a combination of technological advancements and the global political economy. Estimates suggest that national data centre capacity is expected to rise from 1.2 GW in 2025 to almost 8 GW by 2030. With a funding of ₹10,372 crore, the IndiaAI Mission aims to establish domestic compute power and expand GPU infrastructure throughout the nation. Simultaneously, the Digital Personal Data Protection (DPDP) Act, 2023 has introduced a form of “soft localisation,” empowering the government to mandate domestic storage for sensitive categories of data.

Together, this push for infrastructure aims to transform India from a passive data market into an active shaper of global data flows. Yet India’s current policy model differs significantly from the approaches being adopted in other major digital economies. A comparison with Singapore and the European Union reveals that while India is focused on aggressive data centre expansion, other jurisdictions are increasingly prioritising sustainability, efficiency, and digital sovereignty.

This raises a critical policy question: can India scale its AI infrastructure ambitions while accounting for the governance and resource challenges that other markets are now attempting to correct?
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India’s Incentive-Led AI Infrastructure Push
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India’s current approach to data centre expansion is fundamentally facilitative. The state is acting as an enabler of rapid private investment through fiscal incentives and infrastructure prioritisation.

The Union Budget 2022 had classified data centres as “infrastructure,” which enables developers to access cheaper institutional financing and long-term capital. The Union Budget 2026 further introduced tax holidays for foreign cloud providers using Indian facilities for global operations. At the state level, governments such as Maharashtra and Uttar Pradesh are aggressively competing to attract hyperscale investments through electricity duty exemptions, expedited approvals, and “essential service” status designed to guarantee uninterrupted operations.

This approach reflects India’s broader strategic positioning. As global demand for AI compute accelerates, India seeks to establish itself not only as a major digital market, but as a sovereign compute hub for the Global South.

The IndiaAI Mission demonstrates this ambition clearly. By seeking to scale domestic GPU capacity to 100,000 units, the government is recognising that compute infrastructure is increasingly becoming geopolitically strategic. AI leadership will now depend on the ability to control and secure the physical infrastructure powering advanced AI systems.

However, while India’s policy framework strongly incentivises capacity creation, it remains relatively underdeveloped in areas such as sustainability benchmarks, resource management, and operational accountability.
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Singapore and the European Union: Governance After Scale
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Singapore and the European Union offer models of digital infrastructure governance as rapid infrastructure growth starts to raise resource and sovereignty issues.

With the limited energy resources and land at its disposal, Singapore has shifted from unrestricted data centre growth to a tightly managed sustainability-first model. Through the Data Centre Call for Application (DC-CFA) framework, only projects meeting strict efficiency and economic value criteria are approved. For instance, new facilities are expected to maintain Power Usage Effectiveness (PUE) levels of 1.3 or lower and submit detailed water efficiency plans to comply with advanced environmental standards. The country has also developed tropical cooling standards that allow facilities to run at higher ambient temperatures, reducing cooling energy consumption significantly. Rather than uninhibited growth, Singapore is now geared towards growth efficiency.

The European Union, on the other hand, is pursuing a sovereignty-oriented governance model in response to geopolitical pressures. However, it is still introducing energy reporting requirements and waste heat recovery rules into digital infrastructure rules through the revised Energy Efficiency Directive and proposed EU Cloud and AI Development Act. Simultaneously, the Digital Markets Act (DMA) is being used to investigate hyperscale cloud providers for potential “gatekeeper” behaviour, reflecting concerns about excessive concentration of digital infrastructure power in the hands of a few non-European firms. This approach shows that sovereignty and energy efficiency can go hand-in-hand.

These models illustrate an important trend: digital infrastructure governance is shifting from the promotion of investment to sustainability, competition regulation and strategic autonomy.
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India’s Emerging Governance Challenge
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India’s current trajectory and global geopolitical tensions suggest that pressures regarding sustainability and sovereignty are set to intensify over the next decade.

AI infrastructure is resource-intensive by design. For example, a single modern AI server rack can consume up to 250 kilowatts (kW) of power, compared to a traditional enterprise server rack which typically requires only 15 kW. Despite the use of water use effectiveness (WUE) technologies, the sheer volume of heat transfer means that AI data centres can still put immense pressure on local water resources, especially in warmer climates. These figures juxtaposed against hyperscale clusters mean the volumes of electricity, cooling systems, land, water, and high-density compute rise by significant orders of magnitude.  Yet most Indian policies remain overwhelmingly focused on fiscal incentives rather than long-term resource governance.

This creates the risk of a reactive policy cycle in which sustainability standards are introduced only after resource pressures become acute. Urban concentration, grid stress, water scarcity, and energy reliability may eventually force abrupt regulatory interventions which can lead to higher compliance costs and uncertainty in operations.

At the same time, India’s push for sovereign AI infrastructure also raises broader questions around digital sovereignty and institutional capacity. Procuring GPUs alone does not create an AI ecosystem. Secure hosting environments, skilled infrastructure personnel, cybersecurity preparedness, and interoperable governance mechanisms are equally essential.

This makes workforce development a strategic human resource development issue rather than simply an industrial challenge. Without sufficient thermal engineers, cybersecurity professionals, and digital infrastructure specialists, India’s infrastructure ambitions may struggle to translate into long-term resilience.
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Building Governance into the Expansion Phase
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India’s current “pre-regulatory” moment also presents a significant opportunity. Because the sector is still evolving, both policymakers and infrastructure actors have the ability to shape governance standards before constraints become restrictive.

It is vital to establishing national sustainability benchmarks through public-private technical partnerships, possibly under the aegis of of NITI Aayog, the Bureau of Energy Efficiency (BEE) and MeitY, before the next resource pressures dictate reactive regulation. Pilot “sustainability sandboxes” focused on liquid immersion cooling, renewable integration, battery energy storage systems, and water-efficient operations could help create evidence-based policy frameworks tailored to Indian conditions. Similarly, Likewise, collaborations with skilling institutions like NSDC and NIELIT can contribute to the development of dedicated digital infrastructure academies for thermal engineering, cybersecurity, and AI infrastructure management.

This would support India to progress towards a sovereign AI infrastructure stack, bringing together compute capacity, sustainability, capacity building and governance resilience into a seamless ecosystem.
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Conclusion
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With AI systems become increasingly utilised in finance, healthcare, governance, and public services, the infrastructure ecosystem supporting them will become equally politically and strategically significant. The choices India makes today to operationalise sustainability, skilling, competition, and sovereign compute capacity will shape the foundations of its future AI economy.

The central challenge is no longer whether India can become a major AI infrastructure hub. It is whether the country can transition from an incentive-led expansion model toward a governance framework that balances scale with sustainability, sovereignty, democratic accountability, and long-term resilience.

That transition may ultimately define the success of India’s AI century.
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References
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https://www.thehindubusinessline.com/info-tech/economic-survey-indias-data-centre-capacity-to-reach-about-8-gw-by-2030/article70566326.ece

https://indiaai.gov.in/news/cabinet-approves-india-ai-mission-at-an-outlay-of-rs-10-372-crore

https://vidhilegalpolicy.in/blog/cross-border-data-transfers-and-data-localization-mandate-under-the-data-protection-regime/

https://www.sttelemediagdc.com/in-en/resources/what-does-infrastructure-status-mean-data-centre-industry

https://www.midcindia.org/wp-content/uploads/2021/09/IT-ITES_Policy_2015.pdf

https://uplc.up.gov.in/en/page/uttar-pradesh-data-center-policy

https://www.imda.gov.sg/resources/press-releases-factsheets-and-speeches/press-releases/2025/sg-it-energy-efficiency-standard-for-data-centres-launched

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Executive Summary

The IT giant Apple has alerted customers to the impending threat of "mercenary spyware" assaults in 92 countries, including India. These highly skilled attacks, which are frequently linked to both private and state actors  (such as the NSO Group’s Pegasus spyware), target specific individuals, including politicians, journalists, activists and diplomats. In sharp contrast to consumer-grade malware, these attacks are in a league unto themselves: highly-customized to fit the individual target and involving significant resources to create and use.

As the incidence of such attacks rises, it is important that all persons, businesses, and officials equip themselves with information about how such mercenary spyware programs work, what are the most-used methods, how these attacks can be prevented and what one must do if targeted. Individuals and organizations can begin protecting themselves against these attacks by enabling "Lockdown Mode" to provide an extra layer of security to their devices and by frequently changing passwords and by not visiting the suspicious URLs or attachments. 

Introduction: Understanding Mercenary Spyware

Mercenary spyware is a special kind of spyware that is developed exclusively for law enforcement and government organizations. These kinds of spywares are not available in app stores, and are developed for attacking a particular individual and require a significant investment of resources and advanced technologies. Mercenary spyware hackers infiltrate systems by means of techniques such as phishing (by sending malicious links or attachments), pretexting (by manipulating the individuals to share personal information) or baiting (using tempting offers). They often intend to use Advanced Persistent Threats (APT)  where the hackers remain undetected for a prolonged period of time to steal data by continuous stealthy infiltration of the target’s network. The other method to gain access is through zero-day vulnerabilities, which is the process of gaining access to mobile devices using vulnerabilities existing in software. A well-known example of mercenary spyware includes the infamous Pegasus by the NSO Group.

Actions:  By Apple against Mercenary Spyware

Apple has introduced an advanced, optional protection feature in its newer product versions (including iOS 16, iPadOS 16, and macOS Ventura) to combat mercenary spyware attacks. These features have been provided to the users who are at risk of targeted cyber attacks.

Apple released a statement on the matter, sharing, “mercenary spyware attackers apply exceptional resources to target a very small number of specific individuals and their devices. Mercenary spyware attacks cost millions of dollars and often have a short shelf life, making them much harder to detect and prevent.”

When Apple's internal threat intelligence and investigations detect these highly-targeted attacks, they take immediate action to notify the affected users. The notification process involves:

• Displaying a "Threat Notification" at the top of the user's Apple ID page after they sign in.

• Sending an email and iMessage alert to the addresses and phone numbers associated with the user's Apple ID.
• Providing clear instructions on steps the user should take to protect their devices, including enabling "Lockdown Mode" for the strongest available security.
• Apple stresses that these threat notifications are "high-confidence alerts" - meaning they have strong evidence that the user has been deliberately targeted by mercenary spyware. As such, these alerts should be taken extremely seriously by recipients.

Modus Operandi of Mercenary Spyware

1. Installing advanced surveillance equipment remotely and covertly.

2. Using zero-click or one-click attacks to take advantage of device vulnerabilities.

3. Gain access to a variety of data on the device, including location tracking, call logs, text messages, passwords, microphone, camera, and app information.

4. Installation by utilizing many system vulnerabilities on devices running particular iOS and Android versions.

5. Defense by patching vulnerabilities with security updates (e.g., CVE-2023-41991, CVE-2023-41992, CVE-2023-41993).

6. Utilizing defensive DNS services, non-signature-based endpoint technologies, and frequent device reboots as mitigation techniques.

Prevention Measures: Safeguarding Your Devices

1. Turn on security measures: Make use of the security features that the device maker has supplied, such as Apple's Lockdown Mode, which is intended to prevent viruses of all types from infecting Apple products, such as iPhones.

2. Frequent software upgrades: Make sure the newest security and software updates are installed on your devices. This aids in patching holes that mercenary malware could exploit.

3. Steer clear of misleading connections: Exercise caution while opening attachments or accessing links from unidentified sources. Installing mercenary spyware is possible via phishing links or attachments.

4. Limit app permissions: Reassess and restrict app permissions to avoid unwanted access to private information.

5. Use secure networks: To reduce the chance of data interception, connect to secure Wi-Fi networks and stay away from public or unprotected connections.

6. Install security applications: To identify and stop any spyware attacks, think about installing reliable security programs from reliable sources.

7. Be alert: If Apple or other device makers send you a threat notice, consider it carefully and take the advised security precautions.

8. Two-factor authentication: To provide an extra degree of protection against unwanted access, enable two-factor authentication (2FA) on your Apple ID and other significant accounts.

9. Consider additional security measures: For high-risk individuals, consider using additional security measures, such as encrypted communication apps and secure file storage services

Way Forward: Strengthening Digital Defenses, Strengthening Democracy

People, businesses and administrations must prioritize cyber security measures and keep up with emerging dangers as mercenary spyware attacks continue to develop and spread. To effectively address the growing threat of digital espionage, cooperation between government agencies, cybersecurity specialists, and technology businesses is essential.

In the Indian context, the update carries significant policy implications and must inspire a discussion on legal frameworks for government surveillance practices and cyber security protocols in the nation. As the public becomes more informed about such sophisticated cyber threats, we can expect a greater push for oversight mechanisms and regulatory protocols. The misuse of surveillance technology poses a significant threat to individuals and institutions alike. Policy reforms concerning surveillance tech must be tailored to address the specific concerns of the use of such methods by state actors vs. private players. 

There is a pressing need for electoral reforms that help safeguard democratic processes in the current digital age. There has been a paradigm shift in how political activities are conducted in current times: the advent of the digital domain has seen parties and leaders pivot their campaigning efforts to favor the online audience as enthusiastically as they campaign offline. Given that this is an election year, quite possibly the most significant one in modern Indian history, digital outreach and online public engagement are expected to be at an all-time high. And so, it is imperative to protect the electoral process against cyber threats so that public trust in the legitimacy of India’s democratic is rewarded and the digital domain is an asset, and not a threat, to good governance.

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