#FactCheck:AI-Created Video Falsely Shows Car Catching Fire During Celebration

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 

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Introduction

In July 2025, the Digital Trust & Safety Partnership (DTSP) achieved a significant milestone with the formal acceptance of its Safe Framework Specification as an international standard, ISO/IEC 25389. This is the first globally recognised standard that is exclusively concerned with guaranteeing a secure online experience for the general public's use of digital goods and services.

Significance of the New Framework

Fundamentally, ISO/IEC 25389 provides organisations with an organised framework for recognising, controlling, and reducing risks associated with conduct or content. This standard, which was created under the direction of ISO/IEC's Joint Technical Committee 1 (JTC 1), integrates the best practices of DTSP and offers a precise way to evaluate organisational maturity in terms of safety and trust.  Crucially, it offers the first unified international benchmark, allowing organisations globally to coordinate on common safety pledges and regularly assess progress.

Other Noteworthy Standards and Frameworks

While ISO/IEC 25389 is pioneering, it’s not the only framework shaping digital trust and safety:

• One of the main outcomes of the United Nations’ 2024 Summit for the Future was the UN's Global Digital Compact, which describes cross-border cooperation on secure and reliable digital environments with an emphasis on countering harmful content, upholding online human rights, and creating accountability standards. 
• The World Economic Forum’s Digital Trust Framework defines the goals and values, such as cybersecurity, privacy, transparency, redressability, auditability, fairness, interoperability and safety, implicit to the concept of digital trust. It also provides a roadmap to digital trustworthiness that imbibes these dimensions. 
• The Framework for Integrity, Security and Trust (FIST) launched at the Cybereace Summit 2023 at USI of India in New Delhi, calls for a multistakeholder approach to co-create solutions and best practices for digital trust and safety.
• While still in the finalisation stage for implementation rollout, India's Digital Personal Data Protection Act, 2023 (DPDP Act) and its Rules (2025) aim to strike a balance between individual rights and data processing needs by establishing a groundwork for data security and privacy.
• India is developing frameworks in cutting-edge technologies like artificial intelligence. Using a hub-and-spoke model under the IndiaAI Mission, the AI Safety Institute was established in early 2025 with the goal of creating standards for trustworthy, moral, and safe AI systems. Furthermore, AI standards with an emphasis on safety and dependability are being drafted by the Bureau of Indian Standards (BIS). 
• Google's DigiKavach program (2023) and Google Safety Engineering Centre (GSEC) in Hyderabad are concrete efforts to support digital safety and fraud prevention in India's tech sector.

What It Means for India

India is already claiming its place in discussions about safety and trust around the world. Google's June 2025 safety charter for India, for example, highlights how India's distinct digital scale, diversity, and vast threat landscape provide insights that inform global cybersecurity strategies. 

For India's digital ecosystem, ISO/IEC 25389 comes at a critical juncture. Global best practices in safety and trust are desperately needed as a result of the rapid adoption of digital technologies, including the growth of digital payments, e-governance, and artificial intelligence and a concomitant rise in instances of digital harms. Through its guidelines, ISO/IEC 25389 provides a reference benchmark that Indian startups, government agencies, and tech companies can use to improve their safety standards.

Conclusion 

A global trust-and-safety standard like ISO/IEC 25389 is essential for making technology safer for people, even as we discuss the broader adoption of security and safety-by-design principles integrated into the processes of technological product development. India can improve user protection, build its reputation globally, and solidify its position as a key player in the creation of a safer, more resilient digital future by implementing this framework in tandem with its growing domestic regulatory framework (such as the DPDP Act and AI Safety policies).

References 

• https://dtspartnership.org/the-safe-framework-specification/
• https://dtspartnership.org/press-releases/dtsps-safe-framework-published-as-an-international-standard/?
• https://www.weforum.org/stories/2024/04/united-nations-global-digital-compact-trust-security/?
• https://economictimes.indiatimes.com/tech/technology/google-releases-safety-charter-for-india-senior-exec-details-top-cyber-threat-actors-in-the-country/articleshow/121903651.cms? 
• https://initiatives.weforum.org/digital-trust/framework 
• https://government.economictimes.indiatimes.com/news/secure-india/the-launch-of-fist-framework-for-integrity-security-and-trust/103302090 

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India is the world's largest democracy, and conducting free and fair elections is a mammoth task shouldered by the Election Commission of India. But technology is transforming every aspect of the electoral process in the digital age, with Artificial Intelligence (AI) being integrated into campaigns, voter engagement, and election monitoring. In the upcoming Bihar elections of 2025, all eyes are on how the use of AI will influence the state polls and the precedent it will set for future elections.

Opportunities: Harnessing AI for Better Elections

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Breaking Language Barriers with AI: 

AI is reshaping political outreach by making speeches accessible in multiple languages. At the Kashi Tamil Sangamam in 2024, the PM’s Hindi address was AI-dubbed in Tamil in real time. Since then, several speeches have been rolled out in eight languages, ensuring inclusivity and connecting with voters beyond Hindi-speaking regions more effectively.

Monitoring and Transparency 

During Bihar’s Panchayat polls, the State Election Commission used Staqu’s JARVIS, an AI-powered system that connects with CCTV cameras to monitor EVM screens in real time. By reducing human error, JARVIS brought greater accuracy, speed, and trust to the counting process.

AI for Information Access on Public Service Delivery

NaMo AI is a multilingual chatbot that citizens can use to inquire about the details of public services. The feature aims to make government schemes easy to understand, transparent, and help voters connect directly with the policies of the government. 

Personalised Campaigning   

AI is transforming how campaigns connect with voters. By analysing demographics and social media activity, AI builds detailed voter profiles. This helps craft messages that feel personal, whether on WhatsApp, a robocall, or a social media post, ensuring each group hears what matters most to them. This aims to make political outreach sharper and more effective.

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Challenges: The Dark Side of AI in Elections

Deepfakes and Disinformation

AI-powered deepfakes create hyper-realistic videos and audio that are nearly impossible to distinguish from the real. In elections, they can distort public perception, damage reputations, or fuel disharmony on social media. There is a need for mandatory disclaimers stating when content is AI-generated, to ensure transparency and protect voters from manipulative misinformation.

Data Privacy and Behavioural Manipulation

Cambridge Analytica’s consulting services, provided by harvesting the data of millions of users from Facebook without their consent,  revealed how personal data can be weaponised in politics. This data was allegedly used to “microtarget” users through ads, which could influence their political opinions. Data mining of this nature can be supercharged through AI models, jeopardising user privacy, trust, safety, and casting a shadow on democratic processes worldwide. 

Algorithmic Bias

AI systems are trained on datasets.  If the datasets contain biases, AI-driven tools could unintentionally reinforce stereotypes or favor certain groups, leading to unfair outcomes in campaigning or voter engagement.

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The Road Ahead: Striking a Balance

The adoption of AI in elections opens a Pandora's box of uncertainties.  On the one hand, it offers solutions for breaking language barriers and promoting inclusivity. On the other hand, it opens the door to manipulation and privacy violations. 

To counter risks from deepfakes and synthetic content, political parties are now advised to clearly label AI-generated materials and add disclaimers in their campaign messaging. In Delhi, a nodal officer has even been appointed to monitor social media misuse, including the circulation of deepfake videos during elections. The Election Commission of India constantly has to keep up with trends and tactics used by political parties to ensure that elections remain free and fair.  

Conclusion

With Bihar’s pioneering experiments with JARVIS in Panchayat elections to give vote counting more accuracy and speed,  India is witnessing both sides of this technological revolution. The challenge lies in ensuring that AI strengthens democracy rather than undermining it. Deepfakes algorithms, bias, and data misuse remind us of the risk of when technology oversteps. The real challenge is to strike the right balance in embracing AI for elections to enhance inclusivity and transparency,  while safeguarding trust, privacy, and the integrity of democratic processes. 

References

• https://timesofindia.indiatimes.com/india/how-ai-is-rewriting-the-rules-of-election-campaign-in-india/articleshow/120848499.cms#
• https://m.economictimes.com/news/elections/lok-sabha/india/2024-polls-stand-out-for-use-of-ai-to-bridge-language-barriers/articleshow/108737700.cms
• https://www.ndtv.com/india-news/namo-ai-on-namo-app-a-unique-chatbot-that-will-answer-everything-on-pm-modi-govt-schemes-achievements-5426028 
• https://timesofindia.indiatimes.com/gadgets-news/staqu-deploys-jarvis-to-facilitate-automated-vote-counting-for-bihar-panchayat-polls/articleshow/87307475.cms 
• https://www.drishtiias.com/daily-updates/daily-news-editorials/deepfakes-in-elections-challenges-and-mitigation 
• https://internetpolicy.mit.edu/blog-2018-fb-cambridgeanalytica/ ‍
• https://www.deccanherald.com/elections/delhi/delhi-assembly-elections-2025-use-ai-transparently-eci-issues-guidelines-for-political-parties-3357978#