The Machine That Started the Fire Is Now Selling Us the Fire Extinguisher
Introduction
"Artificial Intelligence may be the new charkatan in town"
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.
The Age of the Digital Double
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.
When Artificial Intelligence Enters the Courtroom
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.
The Great AI Contradiction
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.
The Misunderstanding on AI’s Intelligence
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.
The Real Test of AI Governance
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.
References
- 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/
Related Blogs
Executive Summary
A graphic widely circulating on social media claims that Union Home Minister Amit Shah has warned, “A major crisis is coming; if possible, skip one meal a day.” The claim has been found to be false in a fact-check conducted by CyberPeace Research Wing. The research revealed that Amit Shah has not made any such statement.
Claim
A Facebook user shared the viral graphic on May 17, 2026, claiming that BJP leader and Home Minister Amit Shah issued a “warning” to the public, allegedly saying people should be prepared for a major crisis and consider skipping one meal a day. The post has been widely circulated on social media, drawing significant attention and discussion.
- https://www.facebook.com/photo.php?fbid=1509406197622070&set=pb.100056581115590.-2207520000&type=3
- https://archive.ph/Z9Tle
Factcheck
A keyword-based search on Google did not return any credible news reports supporting the claim. Further scrutiny of the official account of the Ministry of Home Affairs on X also found no mention or statement matching the viral claim.
A separate review of the official X account of Home Minister Amit Shah also did not show any such statement or post confirming the viral claim.
Conclusion
The viral claim is false. Union Home Minister Amit Shah has not made any such statement.
Introduction
In a setback to the Centre, the Bombay High Court on Friday 20th September 2024, struck down the provisions under IT Amendment Rules 2023, which empowered the Central Government to establish Fact Check Units (FCUs) to identify ‘fake and misleading’ information about its business on social media platforms.
Chronological Overview
- On 6th April 2023, the Ministry of Electronics and Information Technology (MeitY) notified the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules, 2023 (IT Amendment Rules, 2023). These rules introduced new provisions to establish a fact-checking unit with respect to “any business of the central government”. This amendment was done In exercise of the powers conferred by section 87 of the Information Technology Act, 2000. (IT Act).
- On 20 March 2024, the Central Government notified the Press Information Bureau (PIB) as FCU under rule 3(1)(b)(v) of the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Amendment Rules 2023 (IT Amendment Rules 2023).
- The next day on 21st March 2024, the Supreme Court stayed the Centre's decision on notifying PIB -FCU, considering the pendency of the proceedings before the High Court of Judicature at Bombay. A detailed analysis covered by CyberPeace on the Supreme Court Stay decision can be accessed here.
- In the latest development, the Bombay High Court on 20th September 2024, struck down the provisions under IT Amendment Rules 2023, which empowered the Central Government to establish Fact Check Units (FCUs) to identify ‘fake and misleading’ information about its business on social media platforms.
Brief Overview of Bombay High Court decision dated 20th September 2024
Justice AS Chandurkar was appointed as the third judge after a split verdict in January 2023 by a division bench consisting of Justices Gautam Patel and Neela Gokhal. As a Tie-breaker judge' Justice AS Chandurkar delivered the decision striking down provisions for setting up a Fact Check Unit under IT amendment 2023 rules. Striking down the Centre's proposed fact check unit provision, Justice A S Chandurkar of Bombay High Court also opined that there was no rationale to undertake an exercise in determining whether information related to the business of the Central govt was fake or false or misleading when in digital form but not doing the same when such information was in print. It was also contended that there is no justification to introduce an FCU only in relation to the business of the Central Government. Rule 3(1)(b)(v) has a serious chilling effect on the exercise of the freedom of speech and expression under Article 19(1)(a) of the Constitution since the communication of the view of the FCU will result in the intermediary simply pulling down the content for fear of consequences or losing the safe harbour provision given under IT Act.
Justice Chandurkar held that the expressions ‘fake, false or misleading’ are ‘vague and overbroad’, and that the ‘test of proportionality’ is not satisfied. Rule 3(1)(b)(v), was violative of Articles 14 and 19 (1) (a) and 19 (1) (g) of the Constitution and it is “ultra vires”, or beyond the powers, of the IT Act.
Role of Expert Organisations in Curbing Mis/Disinformation and Fake News
In light of the recent developments, and the rising incidents of Mis/Disinformation and Fake News it becomes significantly important that we all stand together in the fight against these challenges. The actions against Mis/Disinformation and fake news should be strengthened by collective efforts, the expert organisations like CyberPeace Foundation plays an key role in enabling and encouraging netizens to exercise caution and rely on authenticated sources, rather than solely rely on govt FCU to block the content.
Mis/Disinformation and Fake News should be stopped, identified and countered by netizens at the very first stage of its spread. In light of the Bombay High Court's decision to stuck down the provision related to setting up the FCU by the Central Government, it entails that the government's intention to address misinformation related solely to its business/operations may not have been effectively communicated in the eyes of the judiciary.
It is high time to exercise collective efforts against Mis/Disinformation and Fake News and support expert organizations who are actively engaged in conducting proactive measures, and campaigns to target these challenges, specifically in the online information landscape. CyberPeace actively publishes fact-checking reports and insights on Prebunking and Debunking, conducts expert sessions and takes various key steps aimed at empowering netizens to build cognitive defences to recognise the susceptible information, disregard misleading claims and prevent further spreads to ensure the true online information landscape.
References:
- https://www.scconline.com/blog/post/2024/09/20/bombay-high-court-it-rules-amendment-2023-fact-check-units-article14-article19-legal-news/#:~:text=Bombay%20High%20Court%3A%20A%20case,grounds%20that%20it%20violated%20constitutional
- https://indianexpress.com/article/cities/mumbai/bombay-hc-strikes-down-it-act-amendment-fact-check-unit-9579044/
- https://www.cyberpeace.org/resources/blogs/supreme-court-stay-on-centres-notification-of-pibs-fact-check-unit-under-it-amendment-rules-2023
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
