AI, MACHINE LEARNING & BIG DATA 2020
Computing devices are able to mimic human behaviour, to an extent, through ‘artificial intelligence’. ‘Artificial intelligence’ is the decision-making ability of a machine, which often involves the processing of large amounts of data, literally ‘big data’, by the use of algorithms. This ‘big data’ can be used to develop ‘intuitive learning’ or ‘thinking’ in a machine i.e., ‘machine learning’. Evidently, the relationship between ‘artificial intelligence’ (AI), ‘machine learning’ (ML) and ‘big data’ (BD) is inescapable. India has a natural advantage in this field, coupled with an obvious requirement given the population – India has readily collectible large and diverse data, and also the technical ability to utilise such data. Fast-paced advancements in technology, excessive consumerism, and technological agility have contributed to the dynamic situation that we have today. In this chapter the authors have analysed the current trends in India relating to ‘artificial intelligence’, ‘machine learning’ and ‘big data’, and have examined attendant legal aspects with respect to ownership, antitrust, data protection, governance and regulatory matters.
1.1. Artificial Intelligence, Machine Learning and Big Data trends in India Why was involvement in AI made necessary?
AI is predicted to contribute $15.7 trillion to the global economy in 2030.1 We stand on the brink of a technological revolution led by AI which will fundamentally alter the way we live, work and relate to one another.2 AI has affected our lives more than we realize. From waking up to Siri’s news updates to falling asleep to a movie suggested by Netflix’s recommendation engine, the technology underlying the Fourth Industrial Revolution has penetrated our daily lives.
Since other countries are making rapid progress in the field of AI, and globalisation being inevitable, it is imperative that India begins to see AI as a critical element of national security strategy, focuses on AI-based innovation and establishes AI-ready infrastructure to prepare India’s jobs and skills market for an AI-based future to secure its strategic interests.
AI, ML and Big Data Trends
In the absence of any official big data repository and disclosure requirements regarding the manner of use of big data, it is difficult, at this juncture, to make an accurate assessment of any trend in India in this regard. However, analysing the flow of investments in the public and private sector, the following trends may be deduced:
I. Government thrust towards innovation and development of AI
The framework for regulating AI and its applications is in its embryonic stages and there is much to traverse. It is evident from the following that the Government is working towards creating an AI-friendly technological ecosystem in India:
a. In 2017, The Ministry of Commerce and Industry set up an AI Taskforce which highlighted various sectors of importance5 for the AI regime and the challenges in adopting AI in India.
b. In 2018, NITI Aayog,6 was directed to initiate programs on AI and its applications. The Ministry of Electronics & Information Technology (‘MeitY’) constituted four committees to develop a policy framework and analyse issues like leveraging AI, key policy enablers required across various sectors, and legal and ethical issues to AI.
c. In January 2020, NITI Aayog recommended that an AI-explicit computer framework ‘AIRAWAT’8 be set up to satisfy the processing needs of innovation hubs, start-ups, AI researchers and students.
II. Pioneering efforts of the private entities in the AI sector
Private initiatives in India have been far ahead in the development and use of AI than the Government. From utilising various applications powered by AI to providing various online services like MakeMyTrip, Firstcry and Flipkart, which learn from consumers’ online behaviour for making intelligent goods and services suggestions, corporates have been engaging in the use of AI for a long time. Big conglomerates are infusing AI to automate day-to-day operations. The insistence on automation of daily tasks is further necessitated by the fast growth of business. Indulgence of the private entities in AI is evident from the investments being made by them, specifically in the areas of e-commerce, anomaly detection, banking and finance, and retail. Flipkart uses AI-powered robots at sortation centres to process 4,500 shipments an hour with twice the speed and 99.99% accuracy. Swiggy uses AI-powered chatbots for customer support and an AI-ML model for search result optimisation. In India, many large corporations like Google and Walmart Labs are acquiring small start-ups for their AI innovations. Investments by private entities in AI-specific start-ups and the facilitation of an AI-friendly ecosystem by Government initiatives has resulted in blossoming of AI start-ups. In 2019, Indian AI start-ups received a global investment of $762.5 million dollars. It is noteworthy that the developments pursued by the Government in AI are primarily in collaboration with private entities. For instance, NITI Aayog’s collaboration with IBM for developing precision agriculture using AI for doubling farmers’ income by 2020, by using a machine learning process along with different computer lgorithms for crop classification and area estimation.12 Additionally, the Government of Andhra Pradesh collected information from a range of databases, and processed the information through Microsoft’s Machine Learning Platform to monitor children and devote student-focussed attention on identifying and curbing school drop-outs.