#FactCheck: Old Jerusalem Clash Video Falsely Shared as Chaos at Tel Aviv Airport

AI has grown manifold in the past decade and so has its reliance. A MarketsandMarkets study estimates the AI market to reach $1,339 billion by 2030. Further, Statista reports that ChatGPT amassed more than a million users within the first five days of its release, showcasing its rapid integration into our lives. This development and integration have their risks. Consider this response from Google’s AI chatbot, Gemini to a student’s homework inquiry: “You are not special, you are not important, and you are not needed…Please die.” In other instances, AI has suggested eating rocks for minerals or adding glue to pizza sauce. Such nonsensical outputs are not just absurd; they’re dangerous. They underscore the urgent need to address the risks of unrestrained AI reliance. 

AI’s Rise and Its Limitations

The swiftness of AI’s rise, fueled by OpenAI's GPT series, has revolutionised fields like natural language processing, computer vision, and robotics. Generative AI Models like GPT-3, GPT-4 and GPT-4o with their advanced language understanding, enable learning from data, recognising patterns, predicting outcomes and finally improving through trial and error. However, despite their efficiency, these AI models are not infallible. Some seemingly harmless outputs can spread toxic misinformation or cause harm in critical areas like healthcare or legal advice. These instances underscore the dangers of blindly trusting AI-generated content and highlight the importance and the need to understand its limitations.

Defining the Problem: What Constitutes “Nonsensical Answers”?

Harmless errors due to AI nonsensical responses can be in the form of a wrong answer for a trivia question, whereas, critical failures could be as damaging as wrong legal advice. 

AI algorithms sometimes produce outputs that are not based on training data, are incorrectly decoded by the transformer or do not follow any identifiable pattern. This response is known as a Nonsensical Answer and the situation is known as an “AI Hallucination”. It can be factual inaccuracies, irrelevant information or even contextually inappropriate responses. 

A significant source of hallucination in machine learning algorithms is the bias in input that it receives. If the inputs for the AI model are full of biased datasets or unrepresentative data, it may lead to the model hallucinating and producing results that reflect these biases. These models are also vulnerable to adversarial attacks, wherein bad actors manipulate the output of an AI model by tweaking the input data ina subtle manner.

The Need for Policy Intervention

Nonsensical AI responses risk eroding user trust and causing harm, highlighting the need for accountability despite AI’s opaque and probabilistic nature. Different jurisdictions address these challenges in varied ways. The EU’s AI Act enforces stringent reliability standards with a risk-based and transparent approach. The U.S. emphasises creating ethical guidelines and industry-driven standards. India’s DPDP Act indirectly tackles AI safety through data protection, focusing on the principles of accountability and consent. While the EU prioritises compliance, the U.S. and India balance innovation with safeguards. This reflects on the diverse approaches that nations have to AI regulation.

Where Do We Draw the Line?

The critical question is whether AI policies should demand perfection or accept a reasonable margin for error. Striving for flawless AI responses may be impractical, but a well-defined framework can balance innovation and accountability. Adopting these simple measures can lead to the creation of an ecosystem where AI develops responsibly while minimising the societal risks it can pose. Key measures to achieve this include:

• Ensure that users are informed about AI and its capabilities and limitations. Transparent communication is the key to this.  
• Implement regular audits and rigorous quality checks to maintain high standards. This will in turn prevent any form of lapses.
• Establishing robust liability mechanisms to address any harms caused by AI-generated material which is in the form of misinformation. This fosters trust and accountability.

CyberPeace Key Takeaways: Balancing Innovation with Responsibility

The rapid growth in AI development offers immense opportunities but this must be done responsibly. Overregulation of AI can stifle innovation, on the other hand, being lax could lead to unintended societal harm or disruptions. 

Maintaining a balanced approach to development is essential. Collaboration between stakeholders such as governments, academia, and the private sector is important. They can ensure the establishment of guidelines, promote transparency, and create liability mechanisms. Regular audits and promoting user education can build trust in AI systems. Furthermore, policymakers need to prioritise user safety and trust without hindering creativity while making regulatory policies. 

We can create a future that is AI-development-driven and benefits us all by fostering ethical AI development and enabling innovation. Striking this balance will ensure AI remains a tool for progress, underpinned by safety, reliability, and human values.

References

• https://timesofindia.indiatimes.com/technology/tech-news/googles-ai-chatbot-tells-student-you-are-not-needed-please-die/articleshow/115343886.cms
• https://www.forbes.com/advisor/business/ai-statistics/#2 
• https://www.reuters.com/legal/legalindustry/artificial-intelligence-trade-secrets-2023-12-11/ ‍
• https://www.indiatoday.in/technology/news/story/chatgpt-has-gone-mad-today-openai-says-it-is-investigating-reports-of-unexpected-responses-2505070-2024-02-21

Introduction

A Reuters investigation has uncovered an elephant in the room regarding Meta Platforms' internal measures to address online fraud and illicit advertising. The confidential documents that Reuters reviewed disclosed that Meta was planning to generate approximately 10% of its 2024 revenue, i.e., USD 16 billion, from ads related to scams and prohibited goods. The findings point out a disturbing paradox: on the one hand, Meta is a vocal advocate for digital safety and platform integrity, while on the other hand, the internal logs of the company indicate the existence of a very large area allowing the shunning of fraudulent advertisement activities that exploit users throughout the world. 

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The Scale of the Problem

Internal Meta projections show that its platforms, Facebook, Instagram, and WhatsApp, are displaying a staggering 15 billion scam ads per day combined. The advertisements include deceitful e-commerce promotions, fake investment schemes, counterfeit medical products, and unlicensed gambling platforms.

Meta has developed sophisticated detection tools, but even then, the system does not catch the advertisers until they are 95% certain to be fraudsters. By having at least that threshold for removing an ad, the company is unlikely to lose much money. As a result, instead of turning the fraud adjacent advertisers down, it charges them higher ad rates, which is the strategy they call “penalty bids” internally. 

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Internal Acknowledgements & Business Dependence

Internal documents that date between 2021 and 2025 reveal that the financial, safety, and lobbying divisions of Meta were cognizant of the enormity of revenues generated from scams. One of the 2025 strategic papers even describes this revenue source as "violating revenue," which implies that it includes ads that are against Meta's policies regarding scams, gambling, sexual services, and misleading healthcare products.

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The company's top executives consider the cost-benefit scenario of stricter enforcement. According to a 2024 internal projection, Meta's half-yearly earnings from high-risk scam ads were estimated at USD 3.5 billion, whereas regulatory fines for such violations would not exceed USD 1 billion, thus making it a tolerable trade-off from a commercial viewpoint. At the same time, the company intends to scale down scam ad revenue gradually, thus from 10.1% in 2024 to 7.3% by 2025, and 6% by 2026; however, the documents also reveal a planned slowdown in enforcement to avoid "abrupt reductions" that could affect business forecasts.

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Algorithmic Amplification of Scams

One of the most alarming situations is the fact that Meta's own advertising algorithms amplify scam content. It has been reported that users who click on fraudulent ads are more likely to see other similar ads, as the platform's personalisation engine assumes user "interest."

This scenario creates a self-reinforcing feedback loop where the user engagement with scam content dictates the amount of such content being displayed. Thus, a digital environment is created which encourages deceptive engagement and consequently, user trust is eroded and systemic risk is amplified.

An internal presentation in May 2025 was said to put a number on how deeply the platform's ad ecosystem was intertwined with the global fraud economy, estimating that one-third of the scams that succeeded in the U.S. were due to advertising on Meta's platforms.

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Regulatory & Legal Implications

The disclosures arrived at the same time as the US and UK governments started to closely check the company's activities more than ever before.

• The U.S. Securities and Exchange Commission (SEC) is said to be looking into whether Meta has had any part in the promotion of fraudulent financial ads.
• The UK’s Financial Conduct Authority (FCA) found that Meta’s platforms were the main sources of scams related to online payments and claimed that the amount of money lost was more than all the other social platforms combined in 2023.

Meta’s spokesperson, Andy Stone, at first denied the accusations, stating that the figures mentioned in the leak were “rough and overly-inclusive”; nevertheless, he conceded that the company’s consistent efforts toward enforcement had negatively impacted revenue and would continue to do so.

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Operational Challenges & Policy Gaps

The internal documents also reveal the weaknesses in Meta's day-to-day operations when it comes to the implementation of its own policies.

• Because of the large number of employees laid off in 2023, the whole department that dealt with advertiser-brand impersonation was said to have been dissolved.
• Scam ads were categorised as a "low severity" issue, which was more of a "bad user experience" than a critical security risk.
• At the end of 2023, users were submitting around 100,000 legitimate scam reports per week, of which Meta dismissed or rejected 96%.

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Human Impact: When Fraud Becomes Personal

The financial and ethical issues have tangible human consequences. The Reuters investigation documented multiple cases of individuals defrauded through hijacked Meta accounts.

One striking example involves a Canadian Air Force recruiter, whose hacked Facebook account was used to promote fake cryptocurrency schemes. Despite over a hundred user reports, Meta failed to act for weeks, during which several victims, including military colleagues, lost tens of thousands of dollars.

The case underscores not just platform negligence, but also the difficulty of law enforcement collaboration. Canadian authorities confirmed that funds traced to Nigerian accounts could not be recovered due to jurisdictional barriers, a recurring issue in transnational cyber fraud.

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Ethical and Cybersecurity Implications

The research has questioned extremely important things at least from the perspective of cyber policy:

1. Platform Accountability: Meta, by its practice, is giving more importance to the monetary aspect rather than the truth, and in this way, it is going against the principles of responsible digital governance.
2. Transparency in Ad Ecosystems: The lack of transparency in digital advertising systems makes it very easy for dishonest actors to use automated processes with very little supervision.
3. Algorithmic Responsibility: The use of algorithms that impact the visibility of misleading content and targeting can be considered the direct involvement of the algorithms in the fraud.
4. Regulatory Harmonisation: The presence of different and disconnected enforcement frameworks across jurisdictions is a drawback to the efforts in dealing with cross-border cybercrime.
5. Public Trust: Users’ trust in the digital world is mainly dependent on the safety level they see and the accountability of the companies.

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Conclusion

Meta’s records show a very unpleasant mix of profit, laxity, and failure in the policy area concerning scam-related ads. The platform’s readiness to accept and even profit from fraudulent players, though admitting the damage they cause, calls for an immediate global rethinking of advertising ethics, regulatory enforcement, and algorithmic transparency.

With the expansion of its AI-driven operations and advertising networks, protecting the users of Meta must evolve from being just a public relations goal to being a core business necessity, thus requiring verifiable accountability measures, independent audits, and regulatory oversight. It is an undeniable fact that there are billions of users who count on Meta’s platforms for their right to digital safety, which is why this right must be respected and enforced rather than becoming optional.

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References

• https://www.reuters.com/investigations/meta-is-earning-fortune-deluge-fraudulent-ads-documents-show-2025-11-06/?utm_source=chatgpt.com
• https://www.indiatoday.in/technology/news/story/leaked-docs-claim-meta-made-16-billion-from-scam-ads-even-after-deleting-134-million-of-them-2815183-2025-11-07

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Executive Summary:

A video online alleges that people are chanting "India India" as Ohio Senator J.D. Vance meets them at the Republican National Convention (RNC). This claim is not correct. The CyberPeace Research team’s investigation showed that the video was digitally changed to include the chanting. The unaltered video was shared by “The Wall Street Journal” and confirmed via the YouTube channel of “Forbes Breaking News”, which features different music performing while Mr. and Mrs. Usha Vance greeted those present in the gathering. So the claim that participants chanted "India India" is not real.

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Claims:

A video spreading on social media shows attendees chanting "India-India" as Ohio Senator J.D. Vance and his wife, Usha Vance greet them at the Republican National Convention (RNC).

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Post link

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Fact Check:

Upon receiving the posts, we did keyword search related to the context of the viral video. We found a video uploaded by The Wall Street Journal on July 16, titled "Watch: J.D. Vance Is Nominated as Vice Presidential Nominee at the RNC," at the time stamp 0:49. We couldn’t hear any India-India chants whereas in the viral video, we can clearly hear it. 

We also found the video on the YouTube channel of Forbes Breaking News. In the timestamp at 3:00:58, we can see the same clip as the viral video but no “India-India” chant could be heard.

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Hence, the claim made in the viral video is false and misleading.

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Conclusion:

The viral video claiming to show "India-India" chants during Ohio Senator J.D. Vance's greeting at the Republican National Convention is altered. The original video, confirmed by sources including “The Wall Street Journal” and “Forbes Breaking News” features different music without any such chants. Therefore, the claim is false and misleading.

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Claim: A video spreading on social media shows attendees chanting "India-India" as Ohio Senator J.D. Vance and his wife, Usha Vance greet them at the Republican National Convention (RNC).

Claimed on: X 

Fact Check: Fake & Misleading

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