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VOL. I · EST. 11.2025 
SatyaDheesh
सत्याधीश
India's Ground Truth Record
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India to release consultation paper on AI law to regulate "frontier models"

GS3Economy · S&T · Environment · Security· IT, AI, semiconductors & computing· Prelims + Mains·

AI governance and risk mitigation: a relevant GS3 Science & Technology and Ethics case study.

Why in news

Union Minister Ashwini Vaishnaw announced the upcoming release of a consultation paper on a new AI law to regulate 'frontier models' and mitigate risks like deepfakes and financial fraud.

Background

The proposed framework focuses on 'frontier models' using mechanisms like pre-release sandbox testing, human oversight, and liability frameworks. It seeks to balance the growth of startups with the risks identified by companies like Anthropic and OpenAI.

Facts for Prelims

  • S&TSandbox testing: A regulatory environment where AI models can be tested under controlled conditions before public release.
  • FactThe proposed AI law aims to address specific harms including deepfakes, financial fraud, and psychological harm.

Prelims practice question

With reference to the proposed AI law in India, consider the following statements:

  1. The proposed law seeks to prioritize the risks identified by Anthropic over the growth of startups.
  2. The framework proposes a pre-release sandbox testing mechanism for AI models.
  3. The law aims to regulate frontier models to mitigate risks such as deepfakes and financial fraud.

Which of the statements given above is/are correct?

  1. (a)3 only
  2. (b)1 and 3 only
  3. (c)2 and 3 only
  4. (d)1, 2 and 3
Show answer

Answer: (c) 2 and 3 only — Statements 2 and 3 are correct. Statement 1 is incorrect: The framework seeks to balance the growth of startups with the risks identified by companies.

For Mains

Q. Discuss the necessity of a regulatory framework for frontier AI models in India, balancing the promotion of technological innovation with the mitigation of socio-economic risks.

Dimensions to cover in your answer

  • Regulatory friction: Balancing rapid startup innovation with stringent safety protocols for high-risk frontier models
  • Liability ambiguity: Determining legal accountability for harms caused by autonomous AI-generated content and deepfakes
  • Safety-innovation trade-off: Ensuring sandbox testing does not stifle the development of indigenous AI capabilities

Keywords: Frontier models · Regulatory sandbox · Algorithmic accountability · Deepfakes · Technological sovereignty

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