#FactCheck -AI-Generated Video Falsely Shared as Leopard Dragging Passenger From Moving Train

Introduction

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‍"Artificial Intelligence may be the new charlatan in town"

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There is something almost wonderfully Indian about our current relationship with artificial intelligence. We are simultaneously afraid of it, fascinated by it, regulating it, funding it, using it and occasionally asking it to write the regulation meant to control it. In contrast, artificial intelligence seems to have figured out the oldest trick in the book: create an issue and then figure out how to solve it. Both the deepfake and the deepfake detector can be produced by it. It has the ability to  both generate and detect false information. It can both authenticate and mimic your voice. It can create a fake image and determine if it is fake. The machine ,in other words, is increasingly becoming both the burglar and the security system. We now refer to this as innovation.  Perhaps nothing better captures this peculiar moment than India’s most recent regulatory actions. The government has strengthened regulations pertaining to synthetic content such as requiring labelling and expediting the removal of illegal AI-generated information. After a legitimate government or court order, platforms are expected to take action within three hours, significantly reducing the removal window for some content. It took years for the internet to become ubiquitous. There are  now three hours for the law to become transitory. This is the first great paradox of AI governance. Technology operates at the speed of creation. Law operates at the speed of procedure. The citizen is seated between the two. 

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The Age of the Digital Double

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Indian courts are already dealing with this issue in more tangible ways. Cricket player Yuvraj Singh recently received relief from the Delhi High Court in a personality-rights case involving deepfakes created by AI and unlawful use of his identity. Courts have intervened against AI-generated and modified content in similar cases involving other public individuals. As a result, the law faces an odd dilemma: What exactly belongs to a person?  In the past, humans used comparatively stable identifiers to understand identity, such as a name, portrait, signature, or voice. That simplicity has been disrupted by AI. You can now detach your face from your body. You may separate your throat from your voice. It is possible to distinguish between your emotions and your expressions. It is possible to fabricate your political beliefs without engaging in politics. The legitimacy of a person's existence is being requested to be protected by the law, not just their property which is a far more difficult issue.

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When Artificial Intelligence Enters the Courtroom

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The irony becomes richer when AI enters the courtroom itself. Courts are creating guidelines for the use of  AI in the courtroom, just as they are being challenged to decide what happens when AI creates reality outside of it. Human primacy, accountability, transparency, data protection and judicial independence are highlighted in the Supreme Court’s proposed rules on the use of AI in courts. After all, there is one situation in which the justification that “the AI said so” should never be accepted. A hallucinated judgment is more than just a mistake in technology. It may turn into a mistake of authority in a legal system. A precedent can be confidently created by a machine. It can be cited with confidence by a lawyer and maybe then brought before a court for consideration.  All of a sudden, we have created a flawless little bureaucratic ecology where everyone has been duped despite no one's intention to do so. It's not inevitable that machines will turn malevolent, but rather that people will grow unduly reliant on machines that seem authoritative.

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The Great AI Contradiction

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We asked, "What can AI do?" for years.What can AI do for us, we then enquired? We are starting to wonder what AI might do to humans. The following query ought to be more challenging: When it does, who is at fault? Because AI systems don't cleanly fit into the legal frames we inherited, that question becomes very challenging. Developers, model providers, data providers, deployers, platforms, and end users are among them. There may occasionally be a middleman. There is a victim occasionally. Surprisingly, there can occasionally be multiple roles at once. This point is made in a recent working paper on AI and consumer rights in India: while current consumer protection laws may apply to AI harms, the conventional division of accountability among manufacturers, sellers, and service providers becomes challenging when AI systems involve a much more dispersed value chain.

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The Misunderstanding on AI’s Intelligence

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This is the point at which our sense for policy sometimes fails. We are concerned that AI will develop superintelligence. The more imminent threat can be much less dramatic. It is not necessary for AI to surpass human intelligence in order to wreak great harm. All it needs to do is become more convincing, quicker, and less expensive than human verification. Artificial general intelligence is not necessary for a fraudster to con an elderly person. A supercomputer is not necessary for a political manipulator to create a candidate's voice. A stalker can create an intimate deepfake without being conscious. A pupil can file a hallucinated case citation without the assistance of a robot attorney. Ordinary human wrongdoing magnified by incredible technical magnitude is what it is.

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The Real Test of AI Governance

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The number of standards we create, the number of committees we form, or the number of compliance boxes platforms check will not ultimately determine the success of AI regulation. Something considerably simpler will be used to measure it. Can the legal system advise a regular citizen where to go, what to do, and who will be held accountable when an AI system impersonates, defrauds, surveils, manipulates, or denies them a service?

The presence of accountability following failure, not the absence of failure.

Sometimes the most advanced piece of technology in the room is still an old-fashioned institution: a law that works, a regulator that responds, a court that understands the technology and a human being willing to take responsibility. Because if AI is going to be both the fire and the fire extinguisher, we should at least make sure that someone other than the machine owns the building.

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References

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• https://economictimes.indiatimes.com/news/india/government-tightens-deepfake-rules-mandates-ai-content-labels-and-three-hour-takedown-timeline/articleshow/133011656.cms?utm_source=chatgpt.com&from=mdr 
• https://theleaflet.in/law-and-technology/explained-the-supreme-court-of-indias-draft-regulations-for-use-of-artificial-intelligence-in-courts-2026 
• https://www.bananaip.com/intellepedia/yuvraj-singh-personality-rights-ai-deepfakes-delhi-high-court/

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‍Introduction 

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In September 2025, social media feeds were flooded with strikingly vintage saree-type portraits. These images were not taken by professional photographers, but AI-generated images. More than a million people turned to the "Nano Banana" AI tool of Google Gemini, uploading their ordinary selfies and watching them transform into Bollywood-style, cinematic, 1990s posters. The popularity of this trend is evident, as are the concerns of law enforcement agencies and cybersecurity experts regarding risks of infringement of privacy, unauthorised data sharing, and threats related to deepfake misuse.

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What is the Trend?

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This trend in AI sarees is created using Google Geminis' Nano Banana image-editing tool, editing and morphing uploaded selfies into glitzy vintage portraits in traditional Indian attire. A user would upload a clear photograph of a solo subject and enter prompts to generate images of cinematic backgrounds, flowing chiffon sarees, golden-hour ambience, and grainy film texture, reminiscent of classic Bollywood imagery. Since its launch, the tool has processed over 500 million images, with the saree trend marking one of its most popular uses. Photographs are uploaded to an AI system, which uses machine learning to alter the pictures according to the description specified. The transformed AI portraits are then shared by users on their Instagram, WhatsApp, and other social media platforms, thereby contributing to the viral nature of the trend.

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Law Enforcement Agency Warnings

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1. A few Indian police agencies have issued strong advisories against participation in such trends. IPS Officer VC Sajjanar warned the public: "The uploading of just one personal photograph can make greedy operators go from clicking their fingers to joining hands with criminals and emptying one's bank account." His advisory had further warned that sharing personal information through trending apps can lead to many scams and fraud.
2. Jalandhar Rural Police issued a comprehensive warning stating that such applications put the user at risk of identity theft and online fraud when personal pictures are uploaded. A senior police officer stated: "Once sensitive facial data is uploaded, it can be stored, analysed, and even potentially misused to open the way for cyber fraud, impersonation, and digital identity crimes.

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The Cyber Crime Police also put out warnings on social media platforms regarding how photo applications appear entertaining but can pose serious risks to user privacy. They specifically warned that selfies uploaded can lead to data misuse, deepfake creation, and the generation of fake profiles, which are punishable under Sections 66C and 66D of the IT Act 2000.

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Consequences of Such Trends

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The massification of AI photo trends has several severe effects on private users and society as a whole. Identity fraud and theft are the main issues, as uploaded biometric information can be used by hackers to generate imitated identities, evading security measures or committing financial fraud. The facial recognition information shared by means of these trends remains a digital asset that could be abused years after the trend has passed. ‘Deepfake’ production is another tremendous threat because personal images shared on AI platforms can be utilised to create non-consensual artificial media. Studies have found that more than 95,000 deepfake videos circulated online in 2023 alone, a 550% increase from 2019. The images uploaded can be leveraged to produce embarrassing or harmful content that can cause damage to personal reputation, relationships, and career prospects.

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Financial exploitation is also when fake applications in the guise of genuine AI tools strip users of their personal data and financial details. Such malicious platforms tend to look like well-known services so as to trick users into divulging sensitive information. Long-term privacy infringement also comes about due to the permanent retention and possible commercial exploitation of personal biometric information by AI firms, even when users close down their accounts.

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Privacy Risks

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A few months ago, the Ghibli trend went viral, and now this new trend has taken over. Such trends may subject users to several layers of privacy threats that go far beyond the instant gratification of taking pleasing images. Harvesting of biometric data is the most critical issue since facial recognition information posted on these sites becomes inextricably linked with user identities. Under Google's privacy policy for Gemini tools, uploaded images might be stored temporarily for processing and may be kept for longer periods if used for feedback purposes or feature development. 

Illegal data sharing happens when AI platforms provide user-uploaded content to third parties without user consent. A Mozilla Foundation study in 2023 discovered that 80% of popular AI apps had either non-transparent data policies or obscured the ability of users to opt out of data gathering. This opens up opportunities for personal photographs to be shared with anonymous entities for commercial use. Exploitation of training data includes the use of personal photos uploaded to enhance AI models without notifying or compensating users. Although Google provides users with options to turn off data sharing within privacy settings, most users are ignorant of these capabilities. Integration of cross-platform data increases privacy threats when AI applications use data from interlinked social media profiles, providing detailed user profiles that can be taken advantage of for purposeful manipulation or fraud. Inadequacy of informed consent continues to be a major problem, with users engaging in trends unaware of the entire context of sharing information. Studies show that 68% of individuals show concern regarding the misuse of AI app data, but 42% use these apps without going through the terms and conditions.

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CyberPeace Expert Recommendations

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While the Google Gemini image trend feature operates under its own terms and conditions, it is important to remember that many other tools and applications allow users to generate similar content. Not every platform can be trusted without scrutiny, so users who engage in such trends should do so only on trustworthy platforms and make reliable, informed choices. Above all, following cybersecurity best practices and digital security principles remains essential.

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Here are some best practices:-

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1.Immediate Protection Measures for User

In a nutshell, protection of personal information may begin by not uploading high-resolution personal photos into AI-based applications, especially those trained for facial recognition. Instead, a person can play with stock images or non-identifiable pictures to the degree that it satisfies the program's creative features without compromising biometric security. Strong privacy settings should exist on every social media platform and AI app by which a person can either limit access to their data, content, or anything else.

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2.Organisational Safeguards

AI governance frameworks within organisations should enumerate policies regarding the usage of AI tools by employees, particularly those concerning the upload of personal data. Companies should appropriately carry out due diligence before the adoption of an AI product made commercially available for their own use in order to ensure that such a product has its privacy and security levels as suitable as intended by the company. Training should instruct employees regarding deepfake technology.

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3.Technical Protection Strategies

Deepfake detection software should be used. These tools, which include Microsoft Video Authenticator, Intel FakeCatcher, and Sensity AI, allow real-time detection with an accuracy higher than 95%. Use blockchain-based concepts to verify content to create tamper-proof records of original digital assets so that the method of proposing deepfake content as original remains very difficult.

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4.Policy and Awareness Initiatives

For high-risk transactions, especially in banks and identity verification systems, authentication should include voice and face liveness checks to ensure the person is real and not using fake or manipulated media. Implement digital literacy programs to empower users with knowledge about AI threats, deepfake detection techniques, and safe digital practices. Companies should also liaise with law enforcement, reporting purported AI crimes, thus offering assistance in combating malicious applications of synthetic media technology.

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5.Addressing Data Transparency and Cross-Border AI Security

Regulatory systems need to be called for requiring the transparency of data policies in AI applications, along with providing the rights and choices to users regarding either Biometric data or any other data. Promotion must be given to the indigenous development of AI pertaining to India-centric privacy concerns, assuring the creation of AI models in a secure, transparent, and accountable manner. In respect of cross-border AI security concerns, there must be international cooperation for setting common standards of ethical design, production, and use of AI. With the virus-like contagiousness of AI phenomena such as saree editing trends, they portray the potential and hazards of the present-day generation of artificial intelligence. While such tools offer newer opportunities, they also pose grave privacy and security concerns, which should have been considered quite some time ago by users, organisations, and policy-makers. Through the setting up of all-around protection mechanisms and keeping an active eye on digital privacy, both individuals and institutions will reap the benefits of this AI innovation, and they shall not fall on the darker side of malicious exploitation. 

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References

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1. https://www.hindustantimes.com/trending/amid-google-gemini-nano-banana-ai-trend-ips-officer-warns-people-about-online-scams-101757980904282.html%202
2. https://www.moneycontrol.com/news/india/viral-banana-ai-saree-selfies-may-risk-fraud-warn-jalandhar-rural-police-13549443.html
3. https://www.parliament.nsw.gov.au/researchpapers/Documents/Sexually%20explicit%20deepfakes.pdf
4. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
5. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
6. https://socradar.io/top-10-ai-deepfake-detection-tools-2025/

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Introduction

The Telecom Regulatory Authority of India (TRAI) has directed all telcos to set up detection systems based on Artificial Intelligence and Machine Learning (AI/ML) technologies in order to identify and control spam calls and text messages from unregistered telemarketers (UTMs).

The TRAI Directed telcos

The telecom regulator, TRAI, has directed all Access Providers to detect Unsolicited commercial communication (UCC)by systems, which is based on Artificial Intelligence and Machine Learning to detect, identify, and act against senders of Commercial Communication who are not registered in accordance with the provisions of the Telecom Commercial Communication Customer Preference Regulations, 2018 (TCCCPR-2018). Unregistered Telemarketers (UTMs) are entities that do not register with Access Providers and use 10-digit mobile numbers to send commercial communications via SMS or calls.

TRAI steps to curb Unsolicited commercial communication

TRAI has taken several initiatives to reduce Unsolicited Commercial Communication (UCC), which is a major source of annoyance for the public. It has resulted in fewer complaints filed against Registered Telemarketers (RTMs). Despite the TSPs’ efforts, UCC from Unregistered Telemarketers (UTMs) continues. Sometimes, these UTMs use messages with bogus URLs and phone numbers to trick clients into revealing crucial information, leading to financial loss.

To detect, identify, and prosecute all Unregistered Telemarketers (UTMs), the TRAI has mandated that Access Service Providers implement the UCC.

Detect the System with the necessary functionalities within the TRAI’s Telecom Commercial Communication Customer Preference Regulations, 2018 framework.

Access service providers have implemented such detection systems based on their applicability and practicality. However, because UTMs are constantly creating new strategies for sending unwanted communications, the present UCC detection systems provided by Access Service providers cannot detect such UCC.

TRAI also Directs Telecom Providers to Set Up Digital Platform for Customer Consent to Curb Promotional Calls and Messages.

Unregistered Telemarketers (UTMs) sometimes use messages with fake URLs and phone numbers to trick customers into revealing essential information, resulting in financial loss.

TRAI has urged businesses like banks, insurance companies, financial institutions, and others to re-verify their SMS content templates with telcos within two weeks. It also directed telecom companies to stop misusing commercial messaging templates within the next 45 days.

The telecom regulator has also instructed operators to limit the number of variables in a content template to three. However, if any business intends to utilise more than three variables in a content template for communicating with their users, this should be permitted only after examining the example message, as well as adequate justifications and justification.

In order to ensure consistency in UCC Detect System implementations, TRAI has directed all Access Providers to deploy UCC and detect systems based on artificial intelligence and Machine Learning that are capable of constantly evolving to deal with new signatures, patterns, and techniques used by UTMs.

Access Providers have also been directed to use the DLT platform to share intelligence with others. Access Providers have also been asked to ensure that such UCC Detect System detects senders that send unsolicited commercial communications in bulk and do not comply with the requirements. All Access Providers are directed to follow the instructions and provide an update on actions done within thirty days.

The move by TRAI is to curb the menacing calls as due to this, the number of scam cases is increasing, and now a new trend of scams started as recently, a Twitter user reported receiving an automated call from +91 96681 9555 with the message “This call is from Delhi Police.” It then asked her to stay in the queue since some of her documents needed to be picked up. Then he said he works as a sub-inspector at the Kirti Nagar police station in New Delhi. He then inquired whether she had recently misplaced her Aadhaar card, PAN card, or ATM card, to which she replied ‘no’. The scammer then poses as a cop and requests that she authenticate the last four digits of her card because they have found a card with her name on it. And a lot of other people tweeted about it.

Conclusion

TRAI directed the telcos to check the calls and messages from Unregistered numbers. This step of TRAI will curb the pesky calls and messages and catch the Frauds who are not registered with the regulation. Sometimes the unregistered sender sends fraudulent links, and through these fraudulent calls and messages, the sender tries to take the personal information of the customers, which results in financial losses.