The Hindu Editorial Analysis
13 November 2025
Fine-tune the AI Labelling Regulations Framework
(Source – The Hindu, International Edition – Page No. – 8)
Topic : GS Paper III: Science & Technology | GS Paper II: Governance
Context
With the rapid proliferation of AI-generated content, deepfakes, and misinformation, India has begun tightening its digital regulation framework.
The government has proposed amendments to the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, mandating large social media intermediaries (SSMIs) to clearly label synthetic or AI-generated content.
However, the editorial argues that the proposed AI labelling framework, though timely, remains ambiguous, technologically complex, and hard to enforce without multi-stakeholder collaboration.
Key Issues in the Current Framework
- Vague Definition of Synthetic Media:
The rules broadly define “synthetic content” as any computer-generated modification of authentic content. But since AI tools are used in almost 50% of all content creation today, this definition risks overreach. - Ambiguity in Implementation:
- Mandating “clear labels” sounds simple but lacks clarity on placement, duration, and form — e.g., should it be a visual watermark, an audio disclaimer, or a metadata tag?
- A uniform “30-second disclaimer” or “AI label” could either overwhelm viewers or be ignored entirely.
- Verification Challenges:
- Current tools to verify authenticity (C2PA standards, AI detectors) are inconsistent and error-prone.
- Platforms like YouTube, Instagram, and X have low success rates (only 30–55%) in flagging AI-generated content correctly.
- Need for Categorisation:
The editorial calls for a graded labelling system distinguishing:- “Fully AI-generated” content
- “AI-assisted” or partially altered content
Regulatory and Ethical Concerns
- Freedom and Privacy Risks: Over-regulation may curb innovation or lead to state overreach in digital surveillance.
- Platform Responsibility: Tech platforms should be jointly accountable with third-party auditors to ensure transparency.
- User Trust: AI disclaimers are not merely compliance tools but essential to maintaining public trust and online integrity.
Way Forward
- Precision and Clarity:
Define where, how long, and in what format AI labels should appear across different media (text, image, video, audio). - Collaborative Enforcement:
Involve AI researchers, media regulators, civil society, and platform representatives in designing dynamic verification systems. - Technological Investment:
Encourage Indian start-ups and public institutions to develop indigenous AI detection tools. - Graded Regulation:
Establish a flexible framework based on risk level, content type, and audience reach, rather than blanket labelling.
Conclusion
The AI labelling amendments mark India’s first step towards addressing the deepfake menace, but precision, proportionality, and enforceability are key.
“The line between creation and deception is blurring fast — regulation must walk that line with both technological agility and democratic restraint.”