#FactCheck:AI-Generated Footage Misleadingly Shared as Rawalakot Protest Video

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

The fast-paced development of technology and the wider use of social media platforms have led to the rapid dissemination of misinformation with characteristics such as diffusion, fast propagation speed, wide influence, and deep impact through these platforms. Social Media Algorithms and their decisions are often perceived as a black box introduction that makes it impossible for users to understand and recognise how the decision-making process works. 

Social media algorithms may unintentionally promote false narratives that garner more interactions, further reinforcing the misinformation cycle and making it harder to control its spread within vast, interconnected networks. Algorithms judge the content based on the metrics, which is user engagement. It is the prerequisite for algorithms to serve you the best. Hence, algorithms or search engines enlist relevant items you are more likely to enjoy. This process, initially, was created to cut the clutter and provide you with the best information. However, sometimes it results in unknowingly widespread misinformation due to the viral nature of information and user interactions. 

Analysing the Algorithmic Architecture of Misinformation

Social media algorithms, designed to maximize user engagement, can inadvertently promote misinformation due to their tendency to trigger strong emotions, creating echo chambers and filter bubbles. These algorithms prioritize content based on user behaviour, leading to the promotion of emotionally charged misinformation. Additionally, the algorithms prioritize content that has the potential to go viral, which can lead to the spread of false or misleading content faster than corrections or factual content.

Additionally, popular content is amplified by platforms, which spreads it faster by presenting it to more users. Limited fact-checking efforts are particularly difficult since, by the time they are reported or corrected, erroneous claims may have gained widespread acceptance due to delayed responses. Social media algorithms find it difficult to distinguish between real people and organized networks of troll farms or bots that propagate false information. This creates a vicious loop where users are constantly exposed to inaccurate or misleading material, which strengthens their convictions and disseminates erroneous information through networks.

Though algorithms, primarily, aim to enhance user engagement by curating content that aligns with the user's previous behaviour and preferences. Sometimes this process leads to "echo chambers," where individuals are exposed mainly to information that reaffirms their beliefs which existed prior, effectively silencing dissenting voices and opposing viewpoints. This curated experience reduces exposure to diverse opinions and amplifies biased and polarising content, making it arduous for users to discern credible information from misinformation. Algorithms feed into a feedback loop that continuously gathers data from users' activities across digital platforms, including websites, social media, and apps. This data is analysed to optimise user experiences, making platforms more attractive. While this process drives innovation and improves user satisfaction from a business standpoint, it also poses a danger in the context of misinformation. The repetitive reinforcement of user preferences leads to the entrenchment of false beliefs, as users are less likely to encounter fact-checks or corrective information.

Moreover, social networks and their sheer size and complexity today exacerbate the issue. With billions of users participating in online spaces, misinformation spreads rapidly, and attempting to contain it—such as by inspecting messages or URLs for false information—can be computationally challenging and inefficient. The extensive amount of content that is shared daily means that misinformation can be propagated far quicker than it can get fact-checked or debunked.

Understanding how algorithms influence user behaviour is important to tackling misinformation. The personalisation of content, feedback loops, the complexity of network structures, and the role of superspreaders all work together to create a challenging environment where misinformation thrives. Hence, highlighting the importance of countering misinformation through robust measures. 

The Role of Regulations in Curbing Algorithmic Misinformation

The EU's Digital Services Act (DSA) applicable in the EU is one of the regulations that aims to increase the responsibilities of tech companies and ensure that their algorithms do not promote harmful content. These regulatory frameworks play an important role they can be used to establish mechanisms for users to appeal against the algorithmic decisions and ensure that these systems do not disproportionately suppress legitimate voices. Independent oversight and periodic audits can ensure that algorithms are not biased or used maliciously. Self-regulation and Platform regulation are the first steps that can be taken to regulate misinformation. By fostering a more transparent and accountable ecosystem, regulations help mitigate the negative effects of algorithmic misinformation, thereby protecting the integrity of information that is shared online. In the Indian context, the Intermediary Guidelines, 2023, Rule 3(1)(b)(v) explicitly prohibits the dissemination of misinformation on digital platforms. The ‘Intermediaries’ are obliged to ensure reasonable efforts to prevent users from hosting, displaying, uploading, modifying, publishing, transmitting, storing, updating, or sharing any information related to the 11 listed user harms or prohibited content. This rule aims to ensure platforms identify and swiftly remove misinformation, and false or misleading content.

Cyberpeace Outlook

Understanding how algorithms prioritise content will enable users to critically evaluate the information they encounter and recognise potential biases. Such cognitive defenses can empower individuals to question the sources of the information and report misleading content effectively. In the future of algorithms in information moderation, platforms should evolve toward more transparent, user-driven systems where algorithms are optimised not just for engagement but for accuracy and fairness. Incorporating advanced AI moderation tools, coupled with human oversight can improve the detection and reduction of harmful and misleading content. Collaboration between regulatory bodies, tech companies, and users will help shape the algorithms landscape to promote a healthier, more informed digital environment.

References:

• https://www.advancedsciencenews.com/misformation-spreads-like-a-nuclear-reaction-on-the-internet/
• https://www.niemanlab.org/2024/09/want-to-fight-misinformation-teach-people-how-algorithms-work/ 
• Press Release: Press Information Bureau (pib.gov.in) 

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Executive Summary

A video is being widely shared on social media with the claim that Baloch people celebrated by dancing after Pakistan’s crushing defeat to India in the T20 World Cup. However, research by the CyberPeace found the claim to be misleading. The video is actually from a Lohri celebration held on January 23 at Government College University in Lahore, and is unrelated to any cricket match. India defeated Pakistan by 61 runs in the T20 World Cup 2026 match held in Colombo last Sunday. India scored 175 runs for the loss of seven wickets in 20 overs, while Pakistan were bowled out for 114 runs in 18 overs.

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Claim

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The 30-second video was shared on X with the caption, “Baloch people celebrate India’s victory.” The footage shows a group of men dressed in traditional attire dancing around a fire, while a large crowd gathers around and applauds.

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• https://x.com/IPSinghSp/status/2023307632103350315 

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Fact Check

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To verify the authenticity of the viral claim, key frames from the video were extracted and subjected to reverse image search. The search led to an Instagram post uploaded on January 26, 2026, by an account associated with Government College University Lahore. The caption described the performance as a Balochistan cultural dance held at the university’s amphitheatre.

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• https://www.instagram.com/p/DT9sZg5iCXB/

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Further research  also uncovered another video of the same event, recorded from a different angle and uploaded on January 24, 2026, on Instagram. The caption again confirmed that the event took place at Government College University Lahore.

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• https://www.instagram.com/p/DT3vcXHiIwB/

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Conclusion

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The evidence confirms that the viral video does not show Baloch people celebrating Pakistan’s defeat in the T20 World Cup. Instead, it depicts a cultural dance performance during a Lohri celebration at Government College University Lahore, and has been shared with a misleading claim.

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