#FactCheck - AI-Generated Image of Abhishek Bachchan and Aishwarya Rai Falsely Linked to Kedarnath Visit

Introduction

In the era of digitalisation, social media has become an essential part of our lives, with people spending a lot of time updating every moment of their lives on these platforms. Social media networks such as WhatsApp, Facebook, and YouTube have emerged as significant sources of Information. However, the proliferation of misinformation is alarming since misinformation can have grave consequences for individuals, organisations, and society as a whole. Misinformation can spread rapidly via social media, leaving a higher impact on larger audiences. Bad actors can exploit algorithms for their benefit or some other agenda, using tactics such as clickbait headlines, emotionally charged language, and manipulated algorithms to increase false information.

Impact 

The impact of misinformation on our lives is devastating, affecting individuals, communities, and society as a whole. False or misleading health information can have serious consequences, such as believing in unproven remedies or misinformation about some vaccines can cause serious illness, disability, or even death. Any misinformation related to any financial scheme or investment can lead to false or poor financial decisions that could lead to bankruptcy and loss of long-term savings.

In a democratic nation, misinformation plays a vital role in forming a political opinion, and the misinformation spread on social media during elections can affect voter behaviour, damage trust, and may cause political instability.

Mitigating strategies

The best way to minimise or stop the spreading of misinformation requires a multi-faceted approach. These strategies include promoting media literacy with critical thinking, verifying information before sharing, holding social media platforms accountable, regulating misinformation, supporting critical research, and fostering healthy means of communication to build a resilient society.

To put an end to the cycle of misinformation and move towards a better future, we must create plans to combat the spread of false information. This will require coordinated actions from individuals, communities, tech companies, and institutions to promote a culture of information accuracy and responsible behaviour.

The widespread spread of false information on social media platforms presents serious problems for people, groups, and society as a whole. It becomes clear that battling false information necessitates a thorough and multifaceted strategy as we go deeper into comprehending the nuances of this problem.

Encouraging consumers to develop media literacy and critical thinking abilities is essential to preventing the spread of false information. Being educated is essential for equipping people to distinguish between reliable sources and false information. Giving individuals the skills to assess information critically will enable them to choose the content they share and consume with knowledge. Public awareness campaigns should be used to promote and include initiatives that aim to improve media literacy in school curriculum.

Ways to Stop Misinformation

As we have seen, misinformation can cause serious implications; the best way to minimise or stop the spreading of misinformation requires a multifaceted approach; here are some strategies to combat misinformation.

• Promote Media Literacy with Critical Thinking: Educate individuals about how to critically evaluate information, fact check, and recognise common tactics used to spread misinformation, the users must use their critical thinking before forming any opinion or perspective and sharing the content.
• Verify Information: we must encourage people to verify the information before sharing, especially if it seems sensational or controversial, and encourage the consumption of news or any information from a reputable source of news that follows ethical journalistic standards.
• Accountability: Advocate for social media networks' openness and responsibility in the fight against misinformation. Encourage platforms to put in place procedures to detect and delete fraudulent content while boosting credible sources.
• Regulate Misinformation: Looking at the current situation, it is important to advocate for policies and regulations that address the spread of misinformation while safeguarding freedom of expression. Transparency in online communication by identifying the source of information and disclosing any conflict of interest.
• Support Critical Research: Invest in research and study on the sources, impacts, and remedies to misinformation. Support collaborative initiatives by social scientists, psychologists, journalists, and technology to create evidence-based techniques for countering misinformation. 

Conclusion

To prevent the cycle of misinformation and move towards responsible use of the Internet, we must create strategies to combat the spread of false information. This will require coordinated actions from individuals, communities, tech companies, and institutions to promote a culture of information accuracy and responsible behaviour.

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Introduction

India's broadcasting sector has undergone significant changes in recent years with technological advancements such as the introduction of new platforms like Direct-to-Home (DTH), Internet Protocol television (IPTV), Over-The-Top (OTT), and integrated models. Platform changes, emerging technologies and advancements in the advertising space have all necessitated the need for new governing laws that take these developments into account. 

The Union Government and concerned ministry have realised there is a pressing need to develop a robust regulatory framework for the Indian broadcasting sector in the country and consequently, a draft Broadcasting Services (Regulation) Bill, 2023, was released in November 2023 and the Union Ministry of Information and Broadcasting (MIB) had invited feedback and comments from different stakeholders. The draft Bill aims to establish a unified framework for regulating broadcasting services in the country, replacing the current Cable Television Networks (Regulation) Act, 1995 and other policy guidelines governing broadcasting.

Recently a new draft of an updated ‘Broadcasting Services (Regulation) Bill, 2024,’ was shared with selected broadcasters, associations, streaming services, and tech firms, each marked with their identifier to prevent leaks. 

Key Highlights of the Updated Broadcasting Bill 

As per the recent draft of the Broadcasting Services (Regulation) Bill, 2024, social media accounts could be identified as ‘Digital News Broadcasters’ and can be classified within the ambit of the regulation. Some of the major aspects of the new bill were first reported by Hindustan Times. 

The new draft of the Broadcasting Services (Regulation) Bill, 2024, proposes that individuals who regularly upload videos to social media, make podcasts, or write about current affairs online could be classified as Digital News Broadcasters. This entails that YouTubers and Instagrammers who receive a share of advertising revenue or monetize their social media presence through affiliate activities will be regulated as Digital News Broadcasters. This includes channels, podcasts, and blogs that cover news and utilise Google AdSense. They must comply with a Programme Code and Advertising Code.

Online content creators who do not provide news or current affairs but provide programming and curated programs beyond a certain threshold will be treated as OTT broadcasters in case they provide content licensed or live through a website or social media platform.

The new version also introduces new obligations for intermediaries and social media intermediaries related to streaming services and digital news broadcasters, and, in contrast to the last version circulated in 2023, the latest also carries provisions targeting online advertising. In the context of streaming services, OTT broadcasting services are no longer a part of the definition of "internet broadcasting services." The definition of OTT broadcasting service has also been revised, allowing content creators who regularly upload their content to social media to be considered as OTT broadcasting services.

The new definition of an 'intermediary' includes social media intermediaries, advertisement intermediaries, internet service providers, online search engines, and online marketplaces. 

The new Bill allows the government to prescribe different due diligence guidelines for social media platforms and online advertisement intermediaries and requires all intermediaries to provide appropriate information, including information pertaining to the OTT broadcasters and Digital News Broadcasters on their platform, to the central government to ensure compliance with the act. This entails the liability provisions for social media intermediaries which do not provide information “pertaining to OTT Broadcasters and Digital News Broadcasters” on its platforms for compliance. This suggests that when information is sought about a YouTube, Instagram or X/Twitter user, the platform will need to provide this information to the Indian government.

A new draft bill contains specific provisions governing ‘Online Advertising’ and to do so it creates the category of 'advertising intermediaries'. These intermediaries enable the buying or selling of advertisement space on the internet or placing advertisements on online platforms without endorsing the advertisement. 

Final Words

The Indian Ministry of Information and Broadcasting (MIB) is making efforts to propose robust regulatory changes to the country's new-age broadcast sector, which would cover the specific provisions for Digital News Broadcasters, OTT Broadcasters and Intermediaries. The proposed bill defining the scope and obligation of each. 

However, these changes will have significant implications for press and creative freedom. The changes in the new version of the updated bill from its previous draft expanded the applicability of the bill to a larger number of key actors, this move brought ‘content creators’ under the definition of OTT or digital news broadcasters, which raises concerns about overly rigid provisions and might face criticism from media representative perspectives. 

According to recent media reports, the Broadcasting Services (Regulation) Bill, 2024 version has been withdrawn by the I&B ministry facing criticism from relevant stakeholders.

The ministry must take due consideration and feedback from concerned stakeholders and place reliance on balancing individual rights while promoting a healthy regulated landscape considering the needs of the new-age broadcasting sector.

References:

1. https://www.medianama.com/2024/07/223-india-broadcast-bill-online-creators/#:~:text=Online%20content%20creators%20that%20do,or%20a%20social%20media%20platform.
2. https://www.hindustantimes.com/india-news/new-draft-of-broadcasting-bill-news-influencers-may-be-classified-as-broadcasters-101721961764666.html
3. https://www.hindustantimes.com/india-news/broadcasting-bill-still-in-drafting-stage-mib-tells-rs-101722058753083.html
4. https://www.newslaundry.com/2024/07/29/indias-new-broadcast-bill-now-has-compliance-requirements-for-youtubers-and-instagrammers
5. https://m.thewire.in/article/media/social-media-videos-text-digital-news-broadcasting-bill
6. https://mib.gov.in/sites/default/files/Public%20Notice_07.12.2023.pdf
7. https://news.abplive.com/news/india/centre-withdraws-draft-of-broadcasting-services-regulation-bill-1709770

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As AI language models become more powerful, they are also becoming more prone to errors. One increasingly prominent issue is AI hallucinations, instances where models generate outputs that are factually incorrect, nonsensical, or entirely fabricated, yet present them with complete confidence. Recently, ChatGPT released two new models—o3 and o4-mini, which differ from earlier versions as they focus more on step-by-step reasoning rather than simple text prediction. With the growing reliance on chatbots and generative models for everything from news summaries to legal advice, this phenomenon poses a serious threat to public trust, information accuracy, and decision-making.

What Are AI Hallucinations?

AI hallucinations occur when a model invents facts, misattributes quotes, or cites nonexistent sources. This is not a bug but a side effect of how Large Language Models (LLMs) work, and it is only the probability that can be reduced, not their occurrence altogether. Trained on vast internet data, these models predict what word is likely to come next in a sequence. They have no true understanding of the world or facts, they simulate reasoning based on statistical patterns in text. What is alarming is that the newer and more advanced models are producing more hallucinations, not fewer. seemingly counterintuitive. This has been prevalent reasoning-based models, which generate answers step-by-step in a chain-of-thought style. While this can improve performance on complex tasks, it also opens more room for errors at each step, especially when no factual retrieval or grounding is involved.

As per reports shared on TechCrunch, it mentioned that when users asked AI models for short answers, hallucinations increased by up to 30%. And a study published in eWeek found that ChatGPT hallucinated in 40% of tests involving domain-specific queries, such as medical and legal questions. This was not, however, limited to this particular Large Language Model, but also similar ones like DeepSeek. Even more concerning are hallucinations in multimodal models like those used for deepfakes. Forbes reports that some of these models produce synthetic media that not only look real but are also capable of contributing to fabricated narratives, raising the stakes for the spread of misinformation during elections, crises, and other instances.

It is also notable that AI models are continually improving with each version, focusing on reducing hallucinations and enhancing accuracy. New features, such as providing source links and citations, are being implemented to increase transparency and reliability in responses.

The Misinformation Dilemma

The rise of AI-generated hallucinations exacerbates the already severe problem of online misinformation. Hallucinated content can quickly spread across social platforms, get scraped into training datasets, and re-emerge in new generations of models, creating a dangerous feedback loop. However, it helps that the developers are already aware of such instances and are actively charting out ways in which we can reduce the probability of this error. Some of them are:

1. Retrieval-Augmented Generation (RAG): Instead of relying purely on a model’s internal knowledge, RAG allows the model to “look up” information from external databases or trusted sources during the generation process. This can significantly reduce hallucination rates by anchoring responses in verifiable data.
2. Use of smaller, more specialised language models: Lightweight models fine-tuned on specific domains, such as medical records or legal texts. They tend to hallucinate less because their scope is limited and better curated.

Furthermore, transparency mechanisms such as source citation, model disclaimers, and user feedback loops can help mitigate the impact of hallucinations. For instance, when a model generates a response, linking back to its source allows users to verify the claims made.

Conclusion

AI hallucinations are an intrinsic part of how generative models function today, and such a side-effect would continue to occur until foundational changes are made in how models are trained and deployed. For the time being, developers, companies, and users must approach AI-generated content with caution. LLMs are, fundamentally, word predictors, brilliant but fallible. Recognising their limitations is the first step in navigating the misinformation dilemma they pose.

References

• https://www.eweek.com/news/ai-hallucinations-increase/
• https://www.resilience.org/stories/2025-05-11/better-ai-has-more-hallucinations/ 
• https://www.ekathimerini.com/nytimes/1269076/ai-is-getting-more-powerful-but-its-hallucinations-are-getting-worse/ 
• https://techcrunch.com/2025/05/08/asking-chatbots-for-short-answers-can-increase-hallucinations-study-finds/ 
• https://en.as.com/latest_news/is-chatgpt-having-robot-dreams-ai-is-hallucinating-and-producing-incorrect-information-and-experts-dont-know-why-n/
• https://www.newscientist.com/article/2479545-ai-hallucinations-are-getting-worse-and-theyre-here-to-stay/
• https://www.forbes.com/sites/conormurray/2025/05/06/why-ai-hallucinations-are-worse-than-ever/ 
• https://towardsdatascience.com/how-i-deal-with-hallucinations-at-an-ai-startup-9fc4121295cc/ 
• https://www.informationweek.com/machine-learning-ai/getting-a-handle-on-ai-hallucinations 

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