Social media regulation and safe AI among India committee’s 2026–27 review subjects

Parliament’s Standing Committee on Information Technology is set to examine 17 topics during 2026-27. An official bulletin issued on Wednesday listed social media regulation, safe AI, deepfakes, cybersecurity and India’s semiconductor ecosystem among the planned reviews. The work comes amid wider public concern over online harms and disputed platform actions.

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The bulletin followed recent reports of age-inappropriate posts, the spread of child sexual abuse material CSAM, and alleged censorship on social media. These incidents have drawn attention to gaps in oversight and enforcement. Against this backdrop, the committee’s programme places digital platforms and AI-related risks among its priority areas for 2026-27.

Social media regulation and deepfakes in 2026-27 review

The bulletin stated: "The Standing Committee on Communications and Information Technology have selected the following subjects for examination during the year 2026-27...Social and digital platforms and their regulation... Cybersecurity, Data Protection and Digital Trusts, Regulation of Synthetically Generated Information SGI involving AI, deepfakes and automated identity fraud etc... Safety controls, ethical standards and need for guardrails around the development and deployment of AI, the bulletin said.\"

Debate over AI use and misuse has increased in recent months. Governments in many countries have begun discussing how to ensure AI is used safely. The committee’s focus on synthetically generated information, including deepfakes and identity fraud, aligns with these discussions and reflects growing scrutiny of how such content can mislead users.

Cybersecurity regulation and CERT-In warnings on AI agents

India’s cybersecurity agency CERT-In, in the middle of October, issued a critical advisory. CERT-In warned that autonomous Artificial Intelligence AI agents accessed live systems and confidential data of Indian organisations without authorisation. The advisory also said threat actors were weaponising open-source agentic AI tools to carry out rapid cyberattacks.

CERT-In also issued a note for stakeholders on other risks. The note highlighted breaches in some critical infrastructure assets. It also flagged vulnerabilities linked to the widely used programming language PHP. These developments add urgency to planned parliamentary scrutiny of cybersecurity, data protection and digital trust frameworks.

Cybersecurity regulation for digital infrastructure across government and banks

During 2026-27, the panel plans to assess digital infrastructure across central and state governments. The review also covers banks, public sector units and other organisations. This work is expected to look at how systems are protected, how data is managed, and how preparedness is maintained against new forms of cyber threats.

Semiconductor ecosystem regulation and cloud, data centres, and computing milestones

The committee will review India’s Semiconductor Ecosystem - Growth, Opportunities and Challenges. It will also examine the development of India’s Cloud and Data Centre Infrastructure. Other areas include High-Performance Computing HPC and Quantum Computing QC milestones, along with indigenous AI/Machine Learning models and Regulatory Standards.

Additional subjects include India’s power sector resilience to support IT Revolution 2.0 and data Centres. The bulletin also listed advanced R&D, emerging tech and electronics manufacturing for review. These topics connect infrastructure capacity, supply chains and technology development, which are central to expanding digital services securely.

AI regulation, biometric data use, algorithmic bias, and e-waste management

The panel is also set to review biometric data and technologies for current and future uses. It will scrutinise the regulatory framework to tackle algorithmic bias and consumer protection. E-waste management in green computing in India is another listed topic, linking technology growth with environmental and public safety concerns.

With inputs from PTI