#FactCheck! Viral Image Claiming Virat Kohli and Rohit Sharma Visited Kedarnath Is AI-Generated
A photo featuring Indian cricketers Virat Kohli and Rohit Sharma is being widely shared on social media. In the image, both players are seen holding a Shivling, with the Kedarnath temple visible in the background. Users sharing the image claim that Virat Kohli and Rohit Sharma recently visited Kedarnath.
However, CyberPeace Foundation’s investigation found the claim to be false. Our verification established that the viral image is not real but has been created using Artificial Intelligence (AI) and is being circulated with a misleading narrative.
The Claim
An Instagram user shared the viral image on December 22, 2025, with the caption stating that Rohit Sharma and Virat Kohli are in Kedarnath. The post has since been widely reshared by other users, who assumed the image to be authentic. Link, archive link, screenshot:
Fact Check
On closely examining the viral image, the Desk noticed visual inconsistencies suggesting that it may be AI-generated. To verify this, the image was scanned using the AI detection tool HIVE Moderation. According to the results, the image was found to be 99 per cent AI-generated.
Further verification was conducted using another AI detection tool, Sightengine. The analysis revealed that the image was 93 per cent likely to be AI-generated, reinforcing the findings from the previous tool.
Conclusion
CyberPeace Foundation’s research confirms that the viral image claiming Virat Kohli and Rohit Sharma visited Kedarnath is fabricated. The image has been generated using AI technology and is being falsely shared on social media as a real photograph.
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AI and other technologies are advancing rapidly. This has ensured the rapid spread of information, and even misinformation. LLMs have their advantages, but they also come with drawbacks, such as confident but inaccurate responses due to limitations in their training data. The evidence-driven retrieval systems aim to address this issue by using and incorporating factual information during response generation to prevent hallucination and retrieve accurate responses.
What is Retrieval-Augmented Response Generation?
Evidence-driven Retrieval Augmented Generation (or RAG) is an AI framework that improves the accuracy and reliability of large language models (LLMs) by grounding them in external knowledge bases. RAG systems combine the generative power of LLMs with a dynamic information retrieval mechanism. The standard AI models rely solely on pre-trained knowledge and pattern recognition to generate text. RAG pulls in credible, up-to-date information from various sources during the response generation process. RAG integrates real-time evidence retrieval with AI-based responses, combining large-scale data with reliable sources to combat misinformation. It follows the pattern of:
- Query Identification: When misinformation is detected or a query is raised.
- Evidence Retrieval: The AI searches databases for relevant, credible evidence to support or refute the claim.
- Response Generation: Using the evidence, the system generates a fact-based response that addresses the claim.
How is Evidence-Driven RAG the key to Fighting Misinformation?
- RAG systems can integrate the latest data, providing information on recent scientific discoveries.
- The retrieval mechanism allows RAG systems to pull specific, relevant information for each query, tailoring the response to a particular user’s needs.
- RAG systems can provide sources for their information, enhancing accountability and allowing users to verify claims.
- Especially for those requiring specific or specialised knowledge, RAG systems can excel where traditional models might struggle.
- By accessing a diverse range of up-to-date sources, RAG systems may offer more balanced viewpoints, unlike traditional LLMs.
Policy Implications and the Role of Regulation
With its potential to enhance content accuracy, RAG also intersects with important regulatory considerations. India has one of the largest internet user bases globally, and the challenges of managing misinformation are particularly pronounced.
- Indian regulators, such as MeitY, play a key role in guiding technology regulation. Similar to the EU's Digital Services Act, the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, mandate platforms to publish compliance reports detailing actions against misinformation. Integrating RAG systems can help ensure accurate, legally accountable content moderation.
- Collaboration among companies, policymakers, and academia is crucial for RAG adaptation, addressing local languages and cultural nuances while safeguarding free expression.
- Ethical considerations are vital to prevent social unrest, requiring transparency in RAG operations, including evidence retrieval and content classification. This balance can create a safer online environment while curbing misinformation.
Challenges and Limitations of RAG
While RAG holds significant promise, it has its challenges and limitations.
- Ensuring that RAG systems retrieve evidence only from trusted and credible sources is a key challenge.
- For RAG to be effective, users must trust the system. Sceptics of content moderation may show resistance to accepting the system’s responses.
- Generating a response too quickly may compromise the quality of the evidence while taking too long can allow misinformation to spread unchecked.
Conclusion
Evidence-driven retrieval systems, such as Retrieval-Augmented Generation, represent a pivotal advancement in the ongoing battle against misinformation. By integrating real-time data and credible sources into AI-generated responses, RAG enhances the reliability and transparency of online content moderation. It addresses the limitations of traditional AI models and aligns with regulatory frameworks aimed at maintaining digital accountability, as seen in India and globally. However, the successful deployment of RAG requires overcoming challenges related to source credibility, user trust, and response efficiency. Collaboration between technology providers, policymakers, and academic experts can foster the navigation of these to create a safer and more accurate online environment. As digital landscapes evolve, RAG systems offer a promising path forward, ensuring that technological progress is matched by a commitment to truth and informed discourse.
References
- https://experts.illinois.edu/en/publications/evidence-driven-retrieval-augmented-response-generation-for-onlin
- https://research.ibm.com/blog/retrieval-augmented-generation-RAG
- https://medium.com/@mpuig/rag-systems-vs-traditional-language-models-a-new-era-of-ai-powered-information-retrieval-887ec31c15a0
- https://www.researchgate.net/publication/383701402_Web_Retrieval_Agents_for_Evidence-Based_Misinformation_Detection
Artificial intelligence tends to attract extreme opinions. Some commentators argue it is eroding our capacity to think. Others believe it is freeing our minds for more valuable work. Both views miss the more important point: the effect of AI depends on how a person chooses to use it. Whether a chatbot supports someone's thinking or replaces it altogether comes down to that choice, and that choice is what separates an assistant from a substitute. Not long ago, generative AI was a novelty. Now it shows up daily in classrooms, newsrooms and offices - almost everywhere people write, plan or make decisions. That kind of shift is exactly why researchers have started looking closely at something harder to see: what happens inside the brain once thinking gets outsourced to a machine. The findings are worth knowing.
What the Brain Scans Actually Showed
One of the clearest pieces of evidence comes out of MIT's Media Lab. The study by Nataliya Kosmyna was carried out for 4 months in 2025 with the participation of all in all, there were 54 participants The fifty four participants were divided into three groups and assigned each group one unique but identical writing task. Group one wrote with ChatGPT open in front of them. The second used a standard search engine. The third had access to nothing but their own knowledge. Throughout, an Electroencephalogram (EEG device) sat on every participant's head, feeding the research team a live picture of brain activity as the essays took shape. It did not take long for the ChatGPT group's readings to pull away from the other two. Activity in regions linked to memory and analytical reasoning dropped noticeably. Several participants struggled later to recall, or even accurately quote, essays they had written only minutes before. Kosmyna's team gave this effect a name: cognitive debt, borrowed from the language of personal finance. The convenience arrives immediately; the cost turns up afterwards, in this case as weakened memory and independent reasoning.
A less-reported result from the same study points the other way. Participants who started the task unaided, then moved on to using ChatGPT, showed higher brain activity than before, not lower. That detail matters. It indicates the tool itself is not the problem. What seems to matter more is the mental effort a person has already put in before turning to AI for help.
Assistant or Substitute? The Line Is Thinner Than You Think
A study published in Frontiers in Psychology in July 2026 offers a useful distinction that extends the MIT findings. The researchers differentiate between dependent offloading, where a task is handed over because a person doubts their own ability to complete it, and autonomous offloading, where a person chooses to delegate part of a task while remaining in control of the overall process.
Dependent offloading, according to the study, gradually undermines a person's sense of competence, since it signals, even quietly, that they cannot manage without help. Autonomous offloading works differently. Here, too, the scientists are relieved to discover that giving a wide birth to any 'hardest' decisions-just taking AI's assistance where it can make an honest contribution-boosts rather than damages the confidence. The same holds for creative output too. The tool does not change between these two scenarios. What changes is who remains in charge of the process.
The Cost Nobody Is Measuring at Work
This pattern is not confined to academic settings. Earlier, in August 2026 the Conversation collated workplace data which brings up similar issues. Around six out of 10 workers don’t receive formal training on using AI and the same number say they have used artificial intelligence irresponsibly (or covertly) as part of their work.
A separate finding, from a July 2026 study by the Centre for AI Safety, adds further weight to this concern. Even the most capable AI agents tested were unable to complete around 85 per cent of assigned projects to a standard fit for paid, professional work. Put next to the workplace training gap, these numbers point to something organisations cannot really ignore. Many employees are trusting output from tools they were never taught to question, built by systems that make more mistakes than most people give them credit for. That is not a case for banning AI at work. It does mean employees need a clearer sense of where these tools are likely to fail, and the training to recognise it when they do.
Building the Habit of Human-Centred AI Use
Translating this research into practice requires a few deliberate habits.
Think before you prompt:Structuring an argument or outline before opening an AI tool matters more than it might seem. Even five minutes of this kind of preparation involves exactly the mental effort that the MIT study found missing in its heaviest AI users.
Treat AI output as a starting point:Whatever output an AI tool provides should be treated as a rough sketch to work on and not a finished product. Facts need checking. Awkward sentences need rewriting in your own words. At the end of the day, the person whose name goes on the piece is the one who answers for what is in it — which by itself is enough reason to go through it carefully before it is sent out.
Preserve AI-free time:A few hours each week, kept free of AI tools entirely, gives planning and brainstorming room to happen without shortcuts. Teams that build this into their schedule, rather than compressing every stage of a project with AI, generally produce stronger work as a result.
Examine the motivation:Using AI to move through an idea faster is one thing. Using it to dodge thinking about a problem altogether is something else. The second habit tends to catch up with people later, often without their noticing at first.
Conclusion
Whether AI functions as a cognitive assistant or a cognitive substitute depends less on the technology itself and more upon the way it is used. Used to support one's own thinking, AI appears to strengthen cognitive engagement. Used as a substitute for effort, it appears to accumulate a quiet cost, one that eventually surfaces in memory, confidence and the overall quality of work produced. The relevant question, each time AI is used, is a straightforward one: is it being used to assist thinking, or to replace it?
References
2. Chow, A. (2025) 'ChatGPT's Impact On Our Brains According to an MIT Study', TIME
Executive Summary
A news graphic is being widely shared on social media claiming that Union Education Minister Dharmendra Pradhan will resign on July 22. The graphic quotes him as saying, "Respecting the sentiments of the country's youth, I have taken this decision." CyberPeace Research Wing ’s research found the claim to be false. The probe revealed that no official announcement has been made regarding Dharmendra Pradhan’s resignation as Union Education Minister. However, demands for his resignation have intensified from opposition parties and student groups over alleged irregularities in NEET and other examinations, leading to protests in Delhi and other places. The research also found that the viral news graphic circulating on social media was likely created using Artificial Intelligence (AI).
Claim:
A social media user on Instagram shared the viral news graphic on July 21, 2026, claiming that Union Education Minister Dharmendra Pradhan is set to resign on July 22. The post also claimed that Pradhan said during a press conference, "Respecting the sentiments of the country's youth, I have taken this decision."
https://www.instagram.com/reel/DbEMoRtgLfT/?igsh=c3g3dzZxZ2U3YW01
Fact Check:
To verify the authenticity of the viral claim, we conducted a Google search using relevant keywords. However, we did not find any credible media reports confirming that Union Education Minister Dharmendra Pradhan is resigning on July 22.Further, we examined the official X (formerly Twitter) account of Union Education Minister Dharmendra Pradhan. No official announcement or post related to his resignation was found on his account.
https://x.com/dpradhanbjp?lang=en
Upon examining the viral news graphic, we noticed several indicators suggesting that it could be AI-generated. To verify this, we analysed the graphic using the AI detection tool AI or Not. The tool’s analysis indicated a 94% probability that the graphic was generated using AI.
We also scanned the viral graphic through another AI detection tool, WasIt AI. According to the tool’s results, the probability of the graphic being AI-generated was found to be 87%.
Conclusion:
CyberPeace Research Wing ’s fact check found the viral claim to be false. No official announcement has been made regarding Union Education Minister Dharmendra Pradhan’s resignation, and reports claiming that he will resign on July 22 are incorrect. The research further revealed that the viral news graphic circulating on social media was created using Artificial Intelligence (AI).
