#FactCheck - Viral Video Misleadingly Tied to Recent Taiwan Earthquake

Executive Summary:

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A viral social media message claims that the Indian government is offering a ₹5,000 gift to citizens in celebration of Prime Minister Narendra Modi’s birthday. However, this claim is false. The message is part of a deceptive scam that tricks users into transferring money via UPI, rather than receiving any benefit. Fact-checkers have confirmed that this is a fraud using misleading graphics and fake links to lure people into authorizing payments to scammers.

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Claim:

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The post circulating widely on platforms such as WhatsApp and Facebook states that every Indian citizen is eligible to receive ₹5,000 as a gift from the current Union Government on the Prime Minister’s birthday. The message post includes visuals of PM Modi, BJP party symbols, and UPI app interfaces such as PhonePe or Google Pay, and urges users to click on the BJP Election Symbol [Lotus] or on the provided link  to receive the gift directly into their bank account.

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Fact Check:

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Our research indicates that there is no official announcement or credible article supporting the claim that the government is offering ₹5,000 under the Pradhan Mantri Jan Dhan Yojana (PMJDY). This claim does not appear on any official government websites or verified scheme listings.

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While the message was crafted to appear legitimate, it was in fact misleading. The intent was to deceive users into initiating a UPI payment rather than receiving one, thereby putting them at financial risk.

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A screen popped up showing a request to pay ₹686 to an unfamiliar UPI ID. When the ‘Pay ₹686’ button was tapped, the app asked for the UPI PIN—clearly indicating that this would have authorised a payment straight from the user’s bank account to the scammer’s.

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We advise the public to verify such claims through official sources before taking any action.

Our research indicated that the claim in the viral post is false and part of a fraudulent UPI money scam. 

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Clicking the link that went with the viral Facebook post, it took us to a website

https://wh1449479[.]ispot[.]cc/with a somewhat odd domain name of 'ispot.cc', which is certainly not a government-related or commonly known domain name. On the website, we observed images that featured a number of unauthorized visuals, including a Prime Minister Narendra Modi image, a Union Minister and BJP President J.P. Nadda image, the national symbol, the BJP symbol, and the Pradhan Mantri Jan Dhan Yojana logo. It looked like they were using these visuals intentionally to convince users that the website was legitimate. 

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Conclusion:

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The assertion that the Indian government is handing out ₹5,000 to all citizens is totally false and should be reported as a scam. The message uses the trust related to government schemes, tricking users into sending money through UPI to criminals. They recommend that individuals do not click on links or respond to any such message about obtaining a government gift prior to verification. If you or a friend has fallen victim to this fraud, they are urged to report it immediately to your bank, and report it through the National Cyber Crime Reporting Portal (https://cybercrime.gov.in) or contact the cyber helpline at 1930. They also recommend always checking messages like this through their official government website first.

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• Claim: The Modi Government is distributing ₹5,000 to citizens through UPI apps
• Claimed On:  Social Media
• Fact Check: False and Misleading

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‍Brief Overview of the EU AI Act

The EU AI Act, Regulation (EU) 2024/1689, was officially published in the EU Official Journal on 12 July 2024. This landmark legislation on Artificial Intelligence (AI) will come into force just 20 days after publication, setting harmonized rules across the EU. It amends key regulations and directives to ensure a robust framework for AI technologies.  The AI Act, a set of EU rules governing AI, has been in development for two years and now, the EU AI Act enters into force across all 27 EU Member States on 1 August 2024, with certain future deadlines tied up and the enforcement of the majority of its provisions will commence on 2 August 2026. The law prohibits certain uses of AI tools, including those that threaten citizens' rights, such as biometric categorization, untargeted scraping of faces, and systems that try to read emotions are banned in the workplace and schools, as are social scoring systems. It also prohibits the use of predictive policing tools in some instances. The law takes a phased approach to implementing the EU's AI rulebook, meaning there are various deadlines between now and then as different legal provisions will start to apply.

The framework puts different obligations on AI developers, depending on use cases and perceived risk. The bulk of AI uses will not be regulated as they are considered low-risk, but a small number of potential AI  use cases are banned under the law. High-risk use cases, such as biometric uses of AI or AI used in law enforcement, employment, education, and critical infrastructure, are allowed under the law but developers of such apps face obligations in areas like data quality and anti-bias considerations. A third risk tier also applies some lighter transparency requirements for makers of tools like AI chatbots.

In case of failure to comply with the Act, the companies in the EU providing, distributing, importing, and using AI systems and GPAI models, are subject to fines of up to EUR 35 million or seven per cent of the total worldwide annual turnover, whichever is higher.

Key highlights of EU AI Act Provisions

• The AI Act classifies AI according to its risk. It prohibits Unacceptable risks such as social scoring systems and manipulative AI. The regulation mostly addresses high-risk AI systems.
• Limited-risk AI systems are subject to lighter transparency obligations and according to the act, the developers and deployers must ensure that the end-users are aware that the interaction they are having is with AI such as Chatbots and Deepfakes. The AI Act allows the free use of minimal-risk AI. This includes the majority of AI applications currently available in the EU single market like AI-enabled video games, and spam filters, but with the advancement of Gen AI changes with regards to this might be done. The majority of obligations fall on providers (developers) of high-risk AI systems that intend to place on the market or put into service high-risk AI systems in the EU, regardless of whether they are based in the EU or a third country. And also, a third-country provider where the high-risk AI system’s output is used in the EU.
• Users are natural or legal persons who deploy an AI system in a professional capacity, not affected end-users. Users (deployers) of high-risk AI systems have some obligations, though less than providers (developers). This applies to users located in the EU, and third-country users where the AI system’s output is used in the EU.
• General purpose AI or GPAI model providers must provide technical documentation, and instructions for use, comply with the Copyright Directive, and publish a summary of the content used for training. Free and open license GPAI model providers only need to comply with copyright and publish the training data summary, unless they present a systemic risk. All providers of GPAI models that present a systemic risk – open or closed – must also conduct model evaluations, and adversarial testing, and track and report serious incidents and ensure cybersecurity protections.
• The Codes of Practice will account for international approaches. It will cover but not necessarily be limited to the obligations, particularly the relevant information to include in technical documentation for authorities and downstream providers, identification of the type and nature of systemic risks and their sources, and the modalities of risk management accounting for specific challenges in addressing risks due to the way they may emerge and materialize throughout the value chain. The AI Office may invite GPAI model providers, and relevant national competent authorities to participate in drawing up the codes, while civil society, industry, academia, downstream providers and independent experts may support the process.

Application & Timeline of Act

The EU AI Act will be fully applicable 24 months after entry into force, but some parts will be applicable sooner, for instance the ban on AI systems posing unacceptable risks will apply six months after the entry into force. The Codes of Practice will apply nine months after entry into force. Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force. High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force. The expected timeline for the same is:

• August 1st, 2024: The AI Act will enter into force.
• February 2025: Prohibition of certain AI systems - Chapters I (general provisions) & II (prohibited AI systems) will apply; Prohibition of certain AI systems.
• August 2025: Chapter III Section 4 (notifying authorities), Chapter V (general purpose AI models), Chapter VII (governance), Chapter XII (confidentiality and penalties), and Article 78 (confidentiality) will apply, except for Article 101 (fines for General Purpose AI providers); Requirements for new GPAI models. 
• August 2026: The whole AI Act applies, except for Article 6(1) & corresponding obligations (one of the categories of high-risk AI systems);
•  August 2027: Article 6(1) & corresponding obligations apply.

The AI Act sets out clear definitions for the different actors involved in AI, such as the providers, deployers, importers, distributors, and product manufacturers. This means all parties involved in the development, usage, import, distribution, or manufacturing of AI systems will be held accountable. Along with this, the AI Act also applies to providers and deployers of AI systems located outside of the EU, e.g., in Switzerland, if output produced by the system is intended to be used in the EU. The Act applies to any AI system within the EU that is on the market, in service, or in use, covering both AI providers (the companies selling AI systems) and AI deployers (the organizations using those systems).

In short, the AI Act will apply to different companies across the AI distribution chain, including providers, deployers, importers, and distributors (collectively referred to as “Operators”). The EU AI Act also has extraterritorial application and can also apply to companies not established in the EU, or providers outside the EU if they -make an AI system or GPAI model available on the EU market. Even if only the output generated by the AI system is used in the EU, the Act still applies to such providers and deployers. 

CyberPeace Outlook 

The EU AI Act, approved by EU lawmakers in 2024, is a landmark legislation designed to protect citizens' health, safety, and fundamental rights from potential harm caused by AI systems. The AI Act will apply to AI systems and GPAI models. The Act creates a tiered risk categorization system with various regulations and stiff penalties for noncompliance. The Act adopts a risk-based approach to AI governance, categorizing potential risks into four tiers: unacceptable, high, limited, and low. Violations of banned systems carry the highest fine: €35 million, or 7 percent of global annual revenue. It establishes transparency requirements for general-purpose AI systems. The regulation also provides specific rules for general-purpose AI (GPAI) models and lays down more stringent requirements for GPAI models with 'high-impact capabilities' that could pose a systemic risk and have a significant impact on the internal market. For high-risk AI systems, the AI Act addresses the issues of fundamental rights impact assessment and data protection impact assessment.

The EU AI Act aims to enhance trust in AI technologies by establishing clear regulatory standards governing AI. We encourage regulatory frameworks that strive to balance the desire to foster innovation with the critical need to prevent unethical practices that may cause user harm. The legislation can be seen as strengthening the EU's position as a global leader in AI innovation and developing regulatory frameworks for emerging technologies. It sets a global benchmark for regulating AI. The companies to which the act applies will need to make sure their practices align with the same. The act may inspire other nations to develop their own legislation contributing to global AI governance. The world of AI is complex and challenging, the implementation of regulatory checks, and compliance by the concerned companies, all pose a conundrum. However, in the end, balancing innovation with ethical considerations is paramount. 

At the same hand, the tech sector welcomes regulatory progress but warns that overly-rigid regulations could stifle innovation. Hence flexibility and adaptability are key to effective AI governance. The journey towards robust AI regulation has begun in major countries, and it is important that we find the right balance between safety and innovation and also take into consideration the industry reactions.

References: 

1. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401689
2. https://www.theverge.com/2024/7/12/24197058/eu-ai-act-regulations-bans-deadline
3. https://techcrunch.com/2024/07/12/eus-ai-act-gets-published-in-blocs-official-journal-starting-clock-on-legal-deadlines/
4. https://www.wsgr.com/en/insights/eu-ai-act-to-enter-into-force-in-august.html
5. https://www.techtarget.com/searchenterpriseai/tip/Is-your-business-ready-for-the-EU-AI-Act
6. https://www.simmons-simmons.com/en/publications/clyimpowh000ouxgkw1oidakk/the-eu-ai-act-a-quick-guide

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Introduction
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The rapid rise of AI tools has reshaped how health content spreads on platforms like Instagram Reels and YouTube Shorts. These sub-minute videos promise quick fixes for weight loss, glowing skin, or reduced anxiety, often delivered through polished visuals and confident AI-generated voiceovers. The result feels highly personalised, as if the advice is tailored to each viewer, even though it is usually generic and widely recycled.

Short-form videos tend to compress complex health topics into “one tip” solutions, such as drinking a specific detox drink daily or following a single workout for rapid fat loss. While appealing, this oversimplification removes essential context, including individual health conditions, long-term risks, and scientific nuance. For example, viral diet trends or fitness hacks may work for some but can be ineffective or even harmful for others.

Algorithms play a major role in amplifying such content. Videos that promise dramatic transformations or instant results are more likely to gain engagement, which pushes them to wider audiences. Repeated exposure then builds familiarity, making the advice seem more credible over time. Audiences often trust this content due to its clean presentation, authoritative tone, and frequent repetition. However, the risks include misinformation, unrealistic expectations, and potential harm from unverified practices. To approach such content critically, viewers should cross-check claims with credible medical sources, avoid relying on single tip solutions, and remember that real health advice is rarely one size fits all.
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The Illusion of Personalisation
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AI-generated health content often mimics personalisation through:

• Synthetic voiceovers that designers created to match different age groups through their voice output, which speak specifically to people who are 20 years old and younger.
• The script development process uses data that tracks currently popular search terms.
• Viewers can interpret information through visual elements, which show changes between two different states.

The process of "personalisation" uses generalised data that does not match individual health profiles to create targeted results. The videos fail to provide a medical assessment because they do not consider:

• Existing medical conditions
• Hereditary differences
• Personal habits and the impact of surrounding conditions

The users will think that general medical advice applies to their personal health needs, which will lead them to use this advice inappropriately.

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Short-Form Content and Oversimplification
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Short-form videos have time limitations, which result in reduced complex medical information development into basic medical stories. The typical patterns of evaluation include these two patterns of evaluation include:

• “One-tip solutions” (e.g., “Drink this before bed to burn fat”)
• Binary framing (“good vs bad foods”)
• The process of eliminating all disclaimers and side effects information

For example, the three diet methods here the three diet methods here

• Viral detox drinks that make the claim to "flush toxins" from the body
• Extreme calorie-cutting diet hacks
• Fitness shortcuts that guarantee users will see results within days

The content demonstrates a pattern of disregarding essential human body operation rules that include both metabolic patterns and human body operation over extended periods of time.
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Algorithmic Amplification and Virality
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The recommendation algorithms used by Instagram and YouTube deliver their most important results through three main factors, which include:

• Engagement (likes, shares, watch time)
• Retention rates
• Emotional or aspirational triggers 

Health-related content that claims to deliver:

• Immediate body changes
• Needs minimal work from viewers
• Results in extreme physical changes

Attractive health-related content that displays extreme physical changes through quick transformations. The system produces a continuous cycle during which:

1. Misleading content gains traction
2. Algorithms amplify it further
3. More creators replicate similar formats using AI tools 

The system produces a secondary result that favours content that people share instead of content that has authentic credibility.
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Why Do Users Trust AI-Generated Health Content?
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Several psychological and technological factors contribute to trust:

1. Professional Aesthetics - AI tools generate high-quality visual content together with authentic voiceover performance and expert-level script documentation, which replicates professional communication methods.
2. Repetition and Familiarity - When people encounter identical recommendations multiple times, their belief in those recommendations increases through the illusory truth effect.
3. Authority Signals

• Medical terminology serves as a standard term
• Medical professionals appear in stock footage through lab coat visuals
• The narrator delivers information through an assertive speaking style

4. Perceived Personal Relevance - Algorithmic targeting makes users feel the content is "meant for them.

Real-World Examples of Viral Trends
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The typical types of health misinformation that artificial intelligence systems spread through their enhanced capabilities include:

• Diet Trends: Keto shortcuts, extreme intermittent fasting variants
• Fitness Hacks: Spot reduction exercises (scientifically unsupported)
• Supplement Advice: Unverified claims about vitamins or herbal products
• Mental Health Tips: Oversimplified coping strategies that lack clinical evidence

The statement that drinking warm lemon water will detox your liver continues to be popular despite the fact that the liver has natural self-detoxification abilities.

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Risks and Public Health Implications
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The widespread consumption of such content creates multiple dangers, which include:

1. Physical Health Risks

• Nutritional deficiencies from extreme diets
• Injury from improper exercise techniques
• Delayed medical consultation

2. Psychological Impact

• Unrealistic body image expectations
• Anxiety due to conflicting advice

3. Misinformation Ecosystem

• The public loses confidence in evidence-based medicine
• Unverified or pseudoscientific practices spread throughout society

Regulatory and Ethical Concerns

The increase of AI-generated health materials connects to more extensive problems, which include:

• Who is responsible for the content
• Who is responsible for the platform
• How AI systems show their inner workings to users

Most platforms today do not have strict systems that can:

• Verify medical claims
• Display which health advice comes from artificial intelligence
• Punish users who spread false information multiple times

The absence of regulations allows misleading information to spread without consequences.
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A CyberPeace Perspective: Building Digital Health Resilience
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The problem needs complete involvement from several parties to create effective solutions that protect both online security and data integrity. 
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For Users

• Users should confirm claims by using trustworthy medical resources, which include the WHO and peer-reviewed studies.
• People should avoid using "quick solutions" until they receive guidance from certified experts.
• Users should exercise caution when they encounter content that does not include necessary warning signs.

For Platforms

• Platforms should implement systems that enable users to identify AI-generated content.
• Platforms should decrease the visibility of health information that contains false statements.
• Platforms should support authentic health content producers who have been validated.

For Policymakers

• Policymakers should create standards that govern AI-produced medical content.
• Policymakers need to enhance initiatives that teach people about the health information available online.

For Content Creators

• Content creators must show how they implement AI technologies.
• They should stay away from making claims that either go beyond what is needed or state things as absolute truth.

Conclusion
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AI-generated health tips on short-form video platforms create complex research conditions that involve three scientific fields: technology, psychology and public health. The tools provide equal access to information, yet create higher risks for people to believe false information when they use the tools without responsible usage. 

The challenge requires organisations to maintain user safety through accurate information management while providing users with transparent digital health services. The growing dependence of users on algorithm-based content requires educational institutions to develop students' critical thinking abilities and digital skills to minimise negative effects from AI-driven communication methods.
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References
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• https://pmc.ncbi.nlm.nih.gov/articles/PMC12924558/
• https://academic.oup.com/heapro/article/40/2/daaf023/8100645
• https://pmc.ncbi.nlm.nih.gov/articles/PMC12673052/
• https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1713794/full
• https://www.who.int/teams/digital-health-and-innovation/digital-channels/combatting-misinformation-online
• https://link.springer.com/article/10.1186/s12982-025-00777-2
• https://www.washingtonpost.com/health/2026/04/21/chatbot-medical-advice-accurate/

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