#FactCheck- 2019 Fighter Jet Escort Video Falsely Linked to Iran Delegation

Introduction

Misinformation regarding health is sensitive and can have far-reaching consequences. These include its effect on personal medical decisions taken by individuals, lack of trust in conventional medicine, delay in seeking treatments, and even loss of life. The fast-paced nature and influx of information on social media can aggravate the situation further. Recently, a report titled Health Misinformation Vectors in India was presented at the Health of India Summit, 2024. It provided certain key insights into health-related misinformation circulating online.

The Health Misinformation Vectors in India Report

The analysis was conducted by the doctors at First Check, a global health fact-checking initiative alongside DataLEADS, a Delhi-based digital media and technology company. The report covers health-related social media content that was posted online from October 2023 to November 2024. It mentions that among all the health scares, misinformation regarding reproductive health, cancer, vaccines, and lifestyle diseases such as diabetes and obesity is the most prominent type that is spread through social media. Misinformation regarding reproductive health includes illegal abortion methods that often go unchecked and even tips on conceiving a male child, among other things. 

In order to combat this misinformation, the report encourages stricter regulations regarding health-related content on digital media, inculcating technology for health literacy and misinformation management in public health curricula and recommending tech platforms to work on algorithms that prioritise credible information and fact-checks. Doctors state that people affected by life-threatening diseases are particularly vulnerable to such misinformation, as they are desperate to seek options for treatment for themselves and their family members to have a chance at life. In a diverse society, with the lack of clear and credible information, limited access to or awareness about tools that cross-check content, and low digital literacy, people gravitate towards alternate sources of information which also fosters a sense of disengagement among the public overall. The diseases mentioned in the report, which are prone to misinformation, are life-altering and require attention from healthcare professionals. 

CyberPeace Outlook

Globally, there are cases of medically-unqualified social media influencers who disperse false/mis- information regarding various health matters. The topics covered are mostly associated with stigma and are still undergoing research. This gap allows for misinformation to be fostered. An example is misinformation regarding PCOS( Polycystic Ovary Syndrome) which is circulating online.

In the midst of all of this, YouTube has released a new feature that aligns with combating health misinformation, trying to bridge the gap between healthcare professionals and Indians who look for trustworthy health-related information online. The initiative includes a feature that allows doctors, nurses, and other healthcare professionals to sign up for a health information source license. This would help by labeling all their informative videos, as addressed- from a healthcare professional. Earlier, this feature was available only for health organisations including a health source information panel and health content shelves, but this step broadens the scope for verification of licenses of individual healthcare professionals. 

As digital literacy continues to grow, methods of seeking credible information, especially regarding sensitive topics such as health, require a combined effort on the part of all the stakeholders involved. We need a robust strategy for battling health-related misinformation online, including more awareness programmes and proactive participation from the consumers as well as medical professionals regarding such content.

References

1. https://timesofindia.indiatimes.com/india/misinformation-about-cancer-reproductive-health-is-widespread-in-india-impacting-medical-decisions-says-report/articleshow/115931612.cms
2. https://www.ndtv.com/india-news/cancer-misinformation-prevalent-in-india-trust-in-medicine-crucial-report-7165458
3. https://www.newindian.in/ai-driven-health-misinformation-poses-threat-to-indias-public-health-report/
4. https://www.etvbharat.com/en/!health/youtube-latest-initiative-combat-health-misinformation-india-enn24121002361
5. https://blog.google/intl/en-in/products/platforms/new-ways-for-registered-healthcare-professionals-in-india-to-reach-people-on-youtube/
6. https://www.bbc.com/news/articles/ckgz2p0999yo

Introduction

The ongoing debate on whether AI scaling has hit a wall has been rehashed by the underwhelming response to OpenAI’s ChatGPT v5. AI scaling laws, which describe that machine learning models perform better with increased training data, model parameters and computational resources, have guided the rapid progress of Large Language Models (LLMs) so far. But many AI researchers suggest that further improvements in LLMs will have to be effected through large computational costs by orders of magnitude, which does not justify the returns.  The question, then, is whether scaling remains a viable path or whether the field must explore new approaches. This is not just a tech issue but a profound innovation challenge for countries like India, charting their own AI course. 

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The Scaling Wall: Gaps and Innovation Opportunities

Escalating costs, data scarcity, and diminishing gains mean that simply building larger AI models may no longer guarantee breakthroughs. In such a scenario, LLM developers will have to refine new approaches to training these models, for example, by diversifying data types and redefining training techniques.  

This global challenge has a bearing on India’s AI ambitions. For India, where compute and data resources are relatively scarce, this scaling slowdown poses both a challenge and an opportunity. While the India AI Mission embodies smart priorities such as democratising compute resources and developing local datasets, looming scaling challenges could prove a roadblock.  Realising these ambitions requires strong input from research and academia, and improved coordination between policymakers and startups. The scaling wall highlights systemic innovation gaps where sustained support is needed, not only in hardware but also in talent development, safety research, and efficient model design.

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Way Forward

To truly harness AI’s transformative power, India must prioritise policy actions and ecosystem shifts that support smarter, safer, and context-rich research through the following measures: 

• Driving Efficiency and Compute Innovation: Instead of relying on brute-force scaling, India should invest in research and startups working on efficient architectures, energy-conscious training methods, and compute optimisation.
• Investing in Multimodal and Diverse Data: While indigenous datasets are being developed under the India AI Mission through AI Kosha, they must be ethically sourced from speech, images, video, sensor data, and regional content, apart from text, to enable context-rich AI models truly tailored to Indian needs. 
• Addressing Core Problems for Trustworthy AI:  LLMs offered by all major companies, like OpenAI, Grok, and Deepseek, have the problem of unreliability, hallucinations, and biases, since they are primarily built on scaling large datasets and parameters, which have inherent limitations. India should invest in capabilities to solve these issues and design more trustworthy LLMs.
• Supporting Talent Development and Training: Despite its substantial AI talent pool, India faces an impending demand-supply gap. It will need to launch national programs and incentives to upskill engineers, researchers, and students in advanced AI skills such as model efficiency, safety, interpretability, and new training paradigms

Conclusion

The AI scaling wall debate is a reminder that the future of LLMs will depend not on ever-larger models but on smarter, safer, and more sustainable innovation. A new generation of AI is approaching us, and India can help shape its future. The country’s AI Mission and startup ecosystem are well-positioned to lead this shift by focusing on localised needs, efficient technologies, and inclusive growth, if implemented effectively. How India approaches this new set of challenges and translates its ambitions into action, however, remains to be seen.

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References

• https://blogs.nvidia.com/blog/ai-scaling-laws/
• https://www.marketingaiinstitute.com/blog/scaling-laws-ai-wall 
• https://fortune.com/2025/02/19/generative-ai-scaling-agi-deep-learning/ 
• https://indiaai.gov.in/ 
• https://www.deloitte.com/in/en/about/press-room/bridging-the-ai-talent-gap-to-boost-indias-tech-and-economic-impact-deloitte-nasscom-report.html 

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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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