Key takeaways from the ‘National strategy for Artificial Intelligence’: #AIforall

Pursuant to the mandate from the Finance Minister of India in his budget speech for 2018-19 to establish the National Program on Artificial Intelligence (“AI”), the NITI Aayog published a discussion paper on a “National Strategy for Artificial Intelligence” (“Paper”) on 4^th June, 2018. Some highlights of the Paper are as follows:

1. The Paper proposes the creation of a National Artificial Intelligence Marketplace (“NAIM”) to address challenges surrounding the adoption of AI in India. Per the Paper, the proposed marketplace model would enable the discovery of optimal AI solutions by the market. NAIM will be structured into three segments in the initial stage: data collection and aggregation marketplace, data annotation market place and solutions (or deployable model) market place.
2. The Paper envisages the application of AI in specific sectors to address important socio-economic and community concerns of the state. These include healthcare, agriculture, education, smart cities and infrastructure, and smart mobility and transportation. Other sectors with the potential to derive significant value from the application of AI include retail, manufacturing, energy, and education and skilling.
3. The Paper identifies certain challenges against large-scale adoption of AI including research and development for application of AI, a facilitating ecosystem to enable access to ‘intelligent data’, cost-intensive nature of AI, low awareness, absence of a formal regulatory structure involving anonymization of data that leads to privacy and security concerns, and the need for collaborations for application of AI.
4. The Paper proposes setting up Centre of Research Excellence and International Centers of Transformational AI to promote research and development in AI in India.
5. The Paper also proposes implementing an annual ‘AI Readiness’ Index, initially considered in the Task Force Report on AI by the Department of Industrial Policy and Promotion, along with promoting best practices among stakeholders across states to spread awareness about the various applications of AI.
6. In particular, the Paper identifies data as “a primary driver of AI solutions.” The challenges to the use of data include impermissible identification of individuals, prohibited collection, processing and sharing of data without consent, and impermissible discrimination against individuals due to biased data processing.
7. Lack of access to data is characterized as an entry barrier towards effective adoption of AI. In addition, large-scale collection of data by few market players may result in an oligopolistic market.
8. The Paper also recognizes the significance of dynamic intellectual property model laws to promote AI-based innovation. In particular, the patent laws require effective enforcement frameworks tailored to AI applications.
9. The Fairness, Accountability and Transparency framework is identified as the core paradigm to frame and view ethical considerations flowing from the large- scale adoption of AI. In conjunction, privacy, data protection and security of data were highlighted as key concerns. The Paper proposes setting up of Ethics Councils at every Centre of Research Excellence to address ethical considerations.

[This post is authored by Pushan Dwivedi, Associate, TRA.]