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AI Regulations in India

National Strategy for Artificial Intelligence #AIFORALL: NITI Aayog

India's first national strategy for AI

In 2018, India introduced its first national strategy for artificial intelligence (AI), which is an inclusive approach known as #AIFORALL. Niti Aayog published the Responsible AI approach documents in collaboration with the World Economic Forum Centre for the Fourth Industrial Revolution. In the paper's foreword, Dr. Rajiv Kumar, Vice Chairman of NITI Aayog, stated that the Approach Document aims to establish comprehensive ethical principles for the design, development, and deployment of AI in India.

The paper proposes a two-tiered structure to address India’s AI research aspirations:

a) Centre of Research Excellence (CORE) focused on developing a better understanding of existing core research and pushing technology frontiers through the creation of new knowledge;

b) International Centers of Transformational AI (ICTAI) with a mandate of developing and deploying application-based research. Private sector collaboration is envisioned to be a key aspect of ICTAIs.

NITI Aayog decided to focus on five sectors that are envisioned to benefit the most from AI in solving societal needs: Healthcare, Agriculture, Education, Smart Cities and Infrastructure, and Smart Mobility and Transportation. 

The paper addresses ethical, privacy, and security concerns related to the integration of AI. The FAT framework (Fairness, Accountability, and Transparency) is often discussed. 

Challenges related to data handling, such as data usage without consent, risk of identification of individuals through data, data selection bias and the resulting discrimination of AI models, and asymmetry in data aggregation are highlighted. To address these issues, the paper recommends the establishment of data protection frameworks, sector-specific regulatory frameworks, and promoting the adoption of international standards.

The paper also highlights the need for a robust intellectual property (IP) framework in India to support the growing AI innovation wave. The unique nature of AI solutions development makes it challenging to apply patent laws to AI applications. The paper suggests establishing IP facilitation centers to connect practitioners and AI developers and comprehensive training for IP granting authorities, judiciary, and tribunals to address these challenges.

The strategy has proven successful in implementing various recommendations, including the creation of high-quality datasets to bolster research and innovation. Additionally, it has led to the establishment of regulatory frameworks for data protection and cybersecurity.


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