Post Session Report on Universal Acceptance and Multilingual Internet at BIT University under CyberPeace Center of Excellence (CCoE)

Introduction

In a world where Artificial Intelligence (AI) is already changing the creation and consumption of content at a breathtaking pace, distinguishing between genuine media and false or doctored content is a serious issue of international concern. AI-generated content in the form of deepfakes, synthetic text and photorealistic images is being used to disseminate misinformation, shape public opinion and commit fraud. As a response, governments, tech companies and regulatory bodies are exploring ‘watermarking’ as a key mechanism to promote transparency and accountability in AI-generated media. Watermarking embeds identifiable information into content to indicate its artificial origin. 

Government Strategies Worldwide

Governments worldwide have pursued different strategies to address AI-generated media through watermarking standards. In the US, President Biden's 2023 Executive Order on AI directed the Department of Commerce and the National Institute of Standards and Technology (NIST) to establish clear guidelines for digital watermarking of AI-generated content. This action puts a big responsibility on large technology firms to put identifiers in media produced by generative models. These identifiers should help fight misinformation and address digital trust.

The European Union, in its Artificial Intelligence Act of 2024, requires AI-generated content to be labelled. Article 50 of the Act specifically demands that developers indicate whenever users engage with synthetic content. In addition, the EU is a proponent of the Coalition for Content Provenance and Authenticity (C2PA), an organisation that produces secure metadata standards to track the origin and changes of digital content.

India is currently in the process of developing policy frameworks to address AI and synthetic content, guided by judicial decisions that are helping shape the approach. In 2024, the Delhi High Court directed the central government to appoint members for a committee responsible for regulating deepfakes. Such moves indicate the government's willingness to regulate AI-generated content. 

China, has already implemented mandatory watermarking on all deep synthesis content. Digital identifiers must be embedded in AI media by service providers, and China is one of the first countries to adopt stern watermarking legislation.

Understanding the Technical Feasibility

Watermarking AI media means inserting recognisable markers into digital material. They can be perceptible, such as logos or overlays or imperceptible, such as cryptographic tags or metadata. Sophisticated methods such as Google's SynthID apply imperceptible pixel-level changes that remain intact against standard image manipulation such as resizing or compression. Likewise, C2PA metadata standards enable the user to track the source and provenance of an item of content.

Nonetheless, watermarking is not an infallible process. Most watermarking methods are susceptible to tampering. Aforementioned adversaries with expertise, for instance, can use cropping editing or AI software to delete visible watermarks or remove metadata. Further, the absence of interoperability between different watermarking systems and platforms hampers their effectiveness. Scalability is also an issue enacting and authenticating watermarks for billions of units of online content necessitates huge computational efforts and routine policy enforcement across platforms. Scientists are currently working on solutions such as blockchain-based content authentication and zero-knowledge watermarking, which maintain authenticity without sacrificing privacy. These new techniques have potential for overcoming technical deficiencies and making watermarking more secure.

Challenges in Enforcement

Though increasing agreement exists for watermarking, implementation of such policies is still a major issue. Jurisdictional constraints prevent enforceability globally. A watermarking policy within one nation might not extend to content created or stored in another, particularly across decentralised or anonymous domains. This creates an exigency for international coordination and the development of worldwide digital trust standards. While it is a welcome step that platforms like Meta, YouTube, and TikTok have begun flagging AI-generated content, there remains a pressing need for a standardised policy that ensures consistency and accountability across all platforms. Voluntary compliance alone is insufficient without clear global mandates.

User literacy is also a significant hurdle. Even when content is properly watermarked, users might not see or comprehend its meaning. This aligns with issues of dealing with misinformation, wherein it's not sufficient just to mark off fake content, users need to be taught how to think critically about the information they're using. Public education campaigns, digital media literacy and embedding watermarking labels within user-friendly UI elements are necessary to ensure this technology is actually effective.

Balancing Privacy and Transparency

While watermarking serves to achieve digital transparency, it also presents privacy issues. In certain instances, watermarking might necessitate the embedding of metadata that will disclose the source or identity of the content producer. This threatens journalists, whistleblowers, activists, and artists utilising AI tools for creative or informative reasons. Governments have a responsibility to ensure that watermarking norms do not violate freedom of expression or facilitate surveillance. The solution is to achieve a balance by employing privacy-protection watermarking strategies that verify the origin of the content without revealing personally identifiable data. "Zero-knowledge proofs" in cryptography may assist in creating watermarking systems that guarantee authentication without undermining user anonymity.

On the transparency side, watermarking can be an effective antidote to misinformation and manipulation. For example, during the COVID-19 crisis, misinformation spread by AI on vaccines, treatments and public health interventions caused widespread impact on public behaviour and policy uptake. Watermarked content would have helped distinguish between authentic sources and manipulated media and protected public health efforts accordingly.

Best Practices and Emerging Solutions

Several programs and frameworks are at the forefront of watermarking norms. Adobe, Microsoft and others' collaborative C2PA framework puts tamper-proof metadata into images and videos, enabling complete traceability of content origin. SynthID from Google is already implemented on its Imagen text-to-image model and secretly watermarks images generated by AI without any susceptibility to tampering. The Partnership on AI (PAI) is also taking a leadership role by building out ethical standards for synthetic content, including standards around provenance and watermarking. These frameworks become guides for governments seeking to introduce equitable, effective policies. In addition, India's new legal mechanisms on misinformation and deepfake regulation present a timely point to integrate watermarking standards consistent with global practices while safeguarding civil liberties.

Conclusion

Watermarking regulations for synthetic media content are an essential step toward creating a safer and more credible digital world. As artificial media becomes increasingly indistinguishable from authentic content, the demand for transparency, origin, and responsibility increases. Governments, platforms, and civil society organisations will have to collaborate to deploy watermarking mechanisms that are technically feasible, compliant and privacy-friendly. India is especially at a turning point, with courts calling for action and regulatory agencies starting to take on the challenge. Empowering themselves with global lessons, applying best-in-class watermarking platforms and promoting public awareness can enable the nation to acquire a level of resilience against digital deception. 

References

1. https://artificialintelligenceact.eu/
2. https://www.cyberpeace.org/resources/blogs/delhi-high-court-directs-centre-to-nominate-members-for-deepfake-committee
3.  https://c2pa.org
4. https://www.cyberpeace.org/resources/blogs/misinformations-impact-on-public-health-policy-decisions
5.  https://deepmind.google/technologies/synthid/
6. https://www.imatag.com/blog/china-regulates-ai-generated-content-towards-a-new-global-standard-for-transparency

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A video circulating widely on social media shows a child throwing stones at a moving train, while a few other children can also be seen climbing onto the engine. The video is being shared with a communal narrative, with claims that the incident took place in India.

Cyber Peace Foundation’s research found the viral claim to be misleading. Our research revealed that the video is not from India, but from Bangladesh, and is being falsely linked to India on social media.

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Claim:

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On January 15, 2026, a Facebook user shared the viral video claiming it depicted an incident from India. The post carried a provocative caption stating, “We are not afraid of Pakistan outside our borders. We are afraid of the thousands of mini-Pakistans within India.” The post has been widely circulated, amplifying communal sentiments.

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• https://www.facebook.com/watch/?v=2717701495242496 
• https://archive.ph/g6Dsq 

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Fact Check:

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To verify the authenticity of the video, we conducted a reverse image search using Google Lens by extracting keyframes from the viral clip. During this process, we found the same video uploaded on a Bangladeshi Facebook account named AL Amin Babukhali on December 28, 2025. The caption of the original post mentions Kamalapur, which is a well-known railway station in Bangladesh. This strongly indicates that the incident did not occur in India.

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• https://www.facebook.com/reel/1455086036178843 

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Further analysis of the video shows that the train engine carries the marking “BR”, along with text written in the Bengali language. “BR” stands for Bangladesh Railways, confirming the origin of the train. To corroborate this further, we searched for images related to Bangladesh Railways using Google’s open tools. We found multiple images on Getty Images showing train engines with the same design and markings as seen in the viral video. The visual match clearly establishes that the train belongs to Bangladesh Railways.

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Conclusion

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Our research confirms that the viral video is from Bangladesh, not India. It is being shared on social media with a false and misleading claim to give it a communal angle and link it to India.

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Introduction

The term ‘super spreader’ is used to refer to social media and digital platform accounts that are able to quickly transmit information to a significantly large audience base in a short duration. The analogy references the medical term, where a small group of individuals is able to rapidly amplify the spread of an infection across a huge population. The fact that a few handful accounts are able to impact and influence many is attributed to a number of factors like large follower bases, high engagement rates, content attractiveness or virality and perceived credibility.

Super spreader accounts have become a considerable threat on social media because they are responsible for generating a large amount of low-credibility material online. These individuals or groups may create or disseminate low-credibility content for a number of reasons, running from social media fame to garnering political influence, from intentionally spreading propaganda to seeking financial gains. Given the exponential reach of these accounts, identifying, tracing and categorising such accounts as the sources of misinformation can be tricky. It can be equally difficult to actually recognise the content they spread for the misinformation that it actually is. 

How Do A Few Accounts Spark Widespread Misinformation? 

Recent research suggests that misinformation superspreaders, who consistently distribute low-credibility content, may be the primary cause of the issue of widespread misinformation about different topics. A study[1] by a team of social media analysts at Indiana University has found that a significant portion of tweets spreading misinformation are sent by a small percentage of a given user base. The researchers conducted a review of 2,397,388 tweets posted on Twitter (now X) that were flagged as having low credibility and details on who was sending them. The study found that it does not take a lot of influencers to sway the beliefs and opinions of large numbers. This is attributed to the impact of what they describe as superspreaders. The researchers collected 10 months of data, which added up to 2,397,388 tweets sent by 448,103 users, and then reviewed it, looking for tweets that were flagged as containing low-credibility information. They found that approximately a third of the low-credibility tweets had been posted by people using just 10 accounts, and that just 1,000 accounts were responsible for posting approximately 70% of such tweets.[2]

Case Study

1. How Misinformation ‘Superspreaders’ Seed False Election Theories

During the 2020 U.S. presidential election, a small group of "repeat spreaders" aggressively pushed false election claims across various social media platforms for political gain, and this even led to rallies and radicalisation in the U.S.[3] Superspreaders accounts were responsible for disseminating a disproportionately large amount of misinformation related to the election, influencing public opinion and potentially undermining the electoral process.

In the domestic context, India was ranked highest for the risk of misinformation and disinformation according to experts surveyed for the World Economic Forum’s 2024 Global Risk Report. In today's digital age, misinformation, deep fakes, and AI-generated fakes pose a significant threat to the integrity of elections and democratic processes worldwide. With 64 countries conducting elections in 2024, the dissemination of false information carries grave implications that could influence outcomes and shape long-term socio-political landscapes. During the 2024 Indian elections, we witnessed a notable surge in deepfake videos of political personalities, raising concerns about the influence of misinformation on election outcomes.

2. Role of Superspreaders During Covid-19

Clarity in public health communication is important when any grey areas or gaps in information can be manipulated so quickly. During the COVID-19 pandemic, misinformation related to the virus, vaccines, and public health measures spread rapidly on social media platforms, including Twitter (Now X). Some prominent accounts or popular pages on platforms like Facebook and Twitter(now X) were identified as superspreaders of COVID-19 misinformation, contributing to public confusion and potentially hindering efforts to combat the pandemic.

As per the Center for Countering Digital Hate Inc (US), The "disinformation dozen," a group of 12 prominent anti-vaccine accounts[4], were found to be responsible for a large amount of anti-vaccine content circulating on social media platforms, highlighting the significant role of superspreaders in influencing public perceptions and behaviours during a health crisis.

There are also incidents where users are unknowingly engaged in spreading misinformation by forwarding information or content which are not always shared by the original source but often just propagated by amplifiers, using other sources, websites, or YouTube videos that help in dissemination. The intermediary sharers amplify these messages on their pages, which is where it takes off. Hence such users do not always have to be the ones creating or deliberately popularising the misinformation, but they are the ones who expose more people to it because of their broad reach. This was observed during the pandemic when a handful of people were able to create a heavy digital impact sharing vaccine/virus-related misinformation. 

3. Role of Superspreaders in Influencing Investments and Finance

Misinformation and rumours in finance may have a considerable influence on stock markets, investor behaviour, and national financial stability. Individuals or accounts with huge followings or influence in the financial niche can operate as superspreaders of erroneous information, potentially leading to market manipulation, panic selling, or incorrect impressions about individual firms or investments.

Superspreaders in the finance domain can cause volatility in markets, affect investor confidence, and even trigger regulatory responses to address the spread of false information that may harm market integrity. In fact, there has been a rise in deepfake videos, and fake endorsements, with multiple social media profiles providing unsanctioned investing advice and directing followers to particular channels. This leads investors into dangerous financial decisions. The issue intensifies when scammers employ deepfake videos of notable personalities to boost their reputation and can actually shape people’s financial decisions. 

Bots and Misinformation Spread on Social Media

Bots are automated accounts that are designed to execute certain activities, such as liking, sharing, or retweeting material, and they can broaden the reach of misinformation by swiftly spreading false narratives and adding to the virality of a certain piece of content. They can also artificially boost the popularity of disinformation by posting phony likes, shares, and comments, making it look more genuine and trustworthy to unsuspecting users. Bots can exploit social network algorithms by establishing false identities that interact with one another and with real users, increasing the spread of disinformation and pushing it to the top of users' feeds and search results.

Bots can use current topics or hashtags to introduce misinformation into popular conversations, allowing misleading information to acquire traction and reach a broader audience. They can lead to the construction of echo chambers, in which users are exposed to a narrow variety of perspectives and information, exacerbating the spread of disinformation inside restricted online groups. There are incidents reported where bot's were found as the sharers of content from low-credibility sources.

Bots are frequently employed as part of planned misinformation campaigns designed to propagate false information for political, ideological, or commercial gain. Bots, by automating the distribution of misleading information, can make it impossible to trace the misinformation back to its source. Understanding how bots work and their influence on information ecosystems is critical for combatting disinformation and increasing digital literacy among social media users.

CyberPeace Policy Recommendations

1. Recommendations/Advisory for Netizens:

1. Educating oneself: Netizens need to stay informed about current events, reliable fact-checking sources, misinformation counter-strategies, and common misinformation tactics, so that they can verify potentially problematic content before sharing.
2. Recognising the threats and vulnerabilities: It is important for netizens to understand the consequences of spreading or consuming inaccurate information, fake news, or misinformation. Netizens must be cautious of sensationalised content spreading on social media as it might attempt to provoke strong reactions or to mold public opinions. Netizens must consider questioning the credibility of information, verifying its sources, and developing cognitive skills to identify low-credibility content and counter misinformation.
3. Practice caution and skepticism: Netizens are advised to develop a healthy skepticism towards online information, and critically analyse the veracity of all information sources. Before spreading any strong opinions or claims, one must seek supporting evidence,  factual data, and expert opinions, and verify and validate claims with reliable sources or fact-checking entities.
4. Good netiquette on the Internet, thinking before forwarding any information: It is important for netizens to practice good netiquette in the online information landscape. One must exercise caution while sharing any information, especially if the information seems incorrect, unverified or controversial. It's important to critically examine facts and recognise and understand the implications of sharing false, manipulative, misleading or fake information/content. Netizens must also promote critical thinking and encourage their loved ones to think critically, verify information, seek reliable sources and counter misinformation.
5. Adopting and promoting Prebunking and Debunking strategies: Prebunking and debunking are two effective strategies to counter misinformation. Netizens are advised to engage in sharing only accurate information and do fact-checking to debunk any misinformation. They can rely on reputable fact-checking experts/entities who are regularly engaged in producing prebunking and debunking reports and material. Netizens are further advised to familiarise themselves with fact-checking websites, and resources and verify the information.

2. Recommendations for tech/social media platforms 

1. Detect, report and block malicious accounts: Tech/social media platforms must implement strict user authentication mechanisms to verify account holders' identities to minimise the formation of fraudulent or malicious accounts. This is imperative to weed out suspicious social media accounts, misinformation superspreader accounts and bots accounts. Platforms must be capable of analysing public content, especially viral or suspicious content to ascertain whether it is misleading, AI-generated, fake or deliberately misleading. Upon detection, platform operators must block malicious/ superspreader accounts. The same approach must apply to other community guidelines’ violations as well. 
2. Algorithm Improvements: Tech/social media platform operators must develop and deploy advanced algorithm mechanisms to detect suspicious accounts and recognise repetitive posting of misinformation. They can utilise advanced algorithms to identify such patterns and flag any misleading, inaccurate, or fake information.
3. Dedicated Reporting Tools: It is important for the tech/social media platforms to adopt robust policies to take action against social media accounts engaged in malicious activities such as spreading misinformation, disinformation, and propaganda. They must empower users on the platforms to flag/report suspicious accounts, and misleading content or misinformation through user-friendly reporting tools.
4. Holistic Approach: The battle against online mis/disinformation necessitates a thorough examination of the processes through which it spreads. This involves investing in information literacy education, modifying algorithms to provide exposure to varied viewpoints, and working on detecting malevolent bots that spread misleading information. Social media sites can employ similar algorithms internally to eliminate accounts that appear to be bots. All stakeholders must encourage digital literacy efforts that enable consumers to critically analyse information, verify sources, and report suspect content. Implementing prebunking and debunking strategies. These efforts can be further supported by collaboration with relevant entities such as cybersecurity experts, fact-checking entities, researchers, policy analysts and the government to combat the misinformation warfare on the Internet.  

References:

1. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201 {1}
2. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {2}
3. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {3}
4. https://counterhate.com/research/the-disinformation-dozen/ {4}
5. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette
6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201
7. https://www.nytimes.com/2020/11/23/technology/election-misinformation-facebook-twitter.html
8. https://www.wbur.org/onpoint/2021/08/06/vaccine-misinformation-and-a-look-inside-the-disinformation-dozen
9. https://healthfeedback.org/misinformation-superspreaders-thriving-on-musk-owned-twitter/
10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139392/
11. https://www.jmir.org/2021/5/e26933/
12. https://www.yahoo.com/news/7-ways-avoid-becoming-misinformation-121939834.html

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