India’s AI Regulation Journey: Key Insights and Policy Pathways

Описание: In this episode of #CarnegieIndiaInsights, join Shatakratu Sahu, Senior Research Analyst and Senior Program Manager at Carnegie India's Technology and Society Research Program, as he unpacks his working paper, “India’s Advance on AI Regulation.” https://carnegieindia.org/research/20...

Shatakratu, along with his co-author Amlan Mohanty, explores India's evolving approach to AI regulation, analyzing stakeholder perspectives, existing legal frameworks, and potential policy pathways. This episode delves into the key takeaways from their research, including:

Stakeholder Consensus and Debates: The broad agreement that India does not need a new AI-specific law but should strengthen existing legal frameworks, encourage self-regulation, and consider targeted regulations where necessary. Key disagreements remain around AI risks, gaps in existing laws, and the sufficiency of self-regulation.

AI Risk Classification: The paper identifies five key AI risk categories—malicious use, algorithmic discrimination, transparency failures, systemic risks, and loss of control—and proposes a structured framework for Indian policymakers.

Regulatory Approaches: The discussion explores different regulatory models, including self-regulation, co-regulation, and binding regulation, evaluating their feasibility in the Indian context. The paper highlights global precedents from the U.S., UK, Japan, and the EU to inform India's policy choices.

Legal and Policy Implications: A structured gap analysis of existing Indian laws in addressing AI-related harms, with recommendations for amendments, judicial interpretations, and potential new regulations for high-risk AI applications.

Learn more about India's regulatory landscape, its alignment with global AI governance trends, and the challenges in balancing innovation with oversight.

Read the full paper here: https://carnegieindia.org/research/20...