“National Strategy For Artificial Intelligence (AI)”
For successful adoption of AI in public forum, concerns regarding ethical management of data and the digital divide prevalent in Indian society needs to be addressed. Technology disruptions like AI are once-in-a generation phenomenon, and hence large-scale national strategies, need to be taken to strike a balance between narrow definitions of financial impact and the greater good.Amitabh Kant summarized it best when he commented-” Democratizing AI” is essential for India’s Inclusive growth.
With the aim to adopt this transformative technology and to pursue India’s unique needs and aspirations, NITIAayog released a paper defining “National Strategy for Artificial Intelligence(AI)”, calling for #AI for All.
Focus Areas
- Healthcare: increased access and affordability of quality healthcare
- Agriculture: enhanced farmers’ income, increased farm productivity and reduction of wastage,
- Education: improved access and quality of education,
- Smart Cities and Infrastructure: efficient and connectivity for the burgeoning urban population
- Smart Mobility and Transportation: smarter and safer modes of transportation and better traffic and congestion problems.
Barriers in adoption of Artificial Intelligence
- Lack of broad based expertise in research and application of AI
- Absence of enabling data ecosystems – access to intelligent data
- High resource cost and low awareness for adoption of AI
- Privacy and security, including a lack of formal regulations around anonymization of data
- Absence of collaborative approach to adoption and application of AI
How to address India’s AI Research Aspirations
- To address India’s leadership aspirations in Artificial Intelligence, NITI Aayog paper proposes a two-tiered structure namely:
- Centre of Research Excellence (CORE), focusing mainly on understanding existing core research and pushing technology frontiers through creation of new knowledge.
- International Centers of Transformational AI (ICTAI), with the mandate of developing and deploying application-based research.
Way Forward
- Skilling and reskilling of the existing workforce to shift the benchmarks of technological aptitude.
- Developing future talent in accordance with the changing needs of the job market through the adoption of decentralised teaching mechanisms working in collaboration with the private sector and educational institutions.
- New Areas of job creation like data annotation needs to be identified and promoted
- Adoption of AI across the value chain viz. start-ups, private sector, PSUs and government entities, will unlock the potential by creating a virtuous cycle of supply and demand.
- A formal marketplace needs to be created focusing on data collection and aggregation, data annotation and deployable models.
- Establish a common platform called the National AI Marketplace (NAIM) that provides a gateway for accelerated adoption of highly collaborative technology like AI in the government sector.
- A consortium of Ethics Councils at each Centre of Research Excellence (CORE) needs to be set up to discuss questions on ethics, privacy and security regarding AI.
- A robust intellectual property framework is required to strengthen IP regime especially patent laws related to AI applications.
- Establishment of IP facilitation centers to help bridge the gap between practitioners and AI developers,
- Adequate training of IP granting authorities, judiciary and tribunals is suggested.
- Pursuing “moon shot research projects” through specialized teams
- Development of a dedicated supranational agency to channel research in AI.
