- In Stanford ranking, hope for Indian science
- The rise of the AI economy
The government has plans to set up a National Research Foundation (NRF) with an aim to catalyse and energise research and innovation across all academic disciplines, particularly at the university and college levels.
GS Paper 3: Achievements of Indians in S&T; Indigenisation of technology & development of new technology.
- Discuss the features of the National Research Foundation. Also, Assess the role of National Research Foundation to catalyse research and innovation in India. 15 Marks
- Scientific research in Indian universities is declining, because a career in science is not as attractive as our business operations, engineering or administration, and the universities are becoming consumer oriented. Critically comment. 15 Marks
Dimensions of the Article
- Status of scientific research in India
- Issues related to scientific research in India
- Measures taken by the government
- Way forward
Status of scientific research in India
Scientists at Stanford University, led by John Ioannidis, have created a database of 1,59,683 (top 2%) scientists of the world , based on standard indicators such as information on citations, h-Index, co-authorship and a composite indicator.
- This database has largely depended on the citation index provided by resource databases such as Scopus and Web of Science.
- It is based on the number of research papers published, the number of times the author has been cited and the h-index, which is a measure of the impact of an author’s work and other people’s research.
- There is no other database that systematically ranks all the scientists across the world with such accuracy and depth. From India, 1,594 Indians have made it to the list of top 2% scientists in the world.
- India ranks 6th position for scientific publications and ranks at 10th for patents which included only resident applications.
- India has improved its innovation ranking from 29 spots in Global Innovation Index in last five years from 81th position in 2014 to 52th position in 2019.
- India is among the topmost countries in the world in the field of scientific research, positioned as one of the top five nations in the field of space exploration.
- According to WIPO, India is the seventh largest patent filing office in the World.
Issues related to scientific research in India
- Funding Issue: According to Economic Survey (2018), India’s R&D funding has been stagnant for two decades at around 0.7% of GDP. Developed countries spend more than 2% of GDP on R&D. Bulk of the spending, especially for basic research, comes from the government and a large section of the country’s public research is concentrated in national research centres.
- Participation of Private sector: India’s private sector spends less than 0.2% of GDP on R&D.
- Lack of Opportunity: India has employed only 40 researchers per lakh labour force for the last decade as compared to USA’s 790 per lakh of their labour force.
- A disconnect between labs and academia: There is limited coordination between colleges and research facilities. Apart from PhD students hardly anyone is seen in labs conducting research. The academic ambience in many universities does not encourage the research pursuits of faculties. Research management is another very serious problem.
- Less Attractive Option: Many Indian students prefer to major in engineering rather than science, because of the promise of lucrative industrial career opportunities. According to National Council of Applied Economic Research (NCAER), less than three per cent of school-going children want to pursue a career in science in India.
- No uniform policy: Government has not yet come up with a uniform and integrated policy for research and development which could aggregate the efforts of various institutes.
Measures taken by the government
- The National Research Foundation (NRF) will be set-up as autonomous body envisaged under the New Education Policy (NEP) 2020. Considered to be one of the biggest announcements under NEP, it will look after funding, mentoring, and building ‘quality of research’ in India. The NRF aims to fund researchers working across streams in India.
- Prime Minister Research Fellows (PMRF): It is a public-private partnership (PPP) between Science & Engineering Research Board (SERB) and Confederation of Indian Industry (CII) which aims to improve the quality of research by attracting the best talents across the country and reduce brain drain.
- Impactful Policy Research in Social Sciences (IMPRESS): It aims to identify and fund research proposals in social sciences with maximum impact on the governance and society.
- Scheme for Promotion of Academic and Research Collaboration (SPARC): It aims to boost joint research with global universities from 28 countries and get international expertise to solve major national problems, train Indian students in the best laboratories, deepen academic engagement and improve the international ranking of Indian Institutes.
- Impacting Research Innovation and Technology (IMPRINT): It is a national initiative of Ministry of Human Resource Development (MHRD) which aims to address engineering challenges in 10 technology domains relevant to India through an inclusive and sustainable mode.
- Atal Innovation Mission: It is a flagship initiative set up by the NITI Aayog to promote innovation and entrepreneurship across the length and breadth of the country, based on a detailed study and deliberations on innovation and entrepreneurial needs of India in the years ahead.
- STARS Scheme (Scheme for Translational and Advanced Research in Science): Under this, 500 science projects would be funded.
The National Research Foundation paves the way for a self-reliant India while advocating merit-based but equitable peer-reviewed research funding, an incentivisation of research, and to usher in a new culture of research and development in the country. Despite certain limitations, the announcement of the NEP and the Atma Nirbhar Bharat Abhiyan may enable the country to redraw the contours of research beyond the conventional disciplines. The report by Stanford University provides the impetus to Indian scientists to reach international standards.
The pandemic has taught us many lessons and opened our minds to new ways of doing things, including understanding the potential of technologies such as artificial intelligence (AI) and machine learning (ML).
GS Paper 3: S&T developments and everyday applications & effects; Awareness in fields of IT, Space, Computers, Robotics, Nanotech, Biotech, IPR issues.
- Artificial intelligence (AI) and machine learning (ML) models and algorithms have supplemented the work of healthcare professionals, medical researchers, public health authorities and local administrations in monitoring and predicting trends. Explain 15 marks
- The future for AI looks promising but to convert the potential into reality, India will need better strategies. Discuss. 15 marks
Dimensions of the Article
- What is the Artificial intelligence?
- Significance of Artificial Intelligence
- Issues related to Artificial Intelligence
- Measures taken by the government
- Way forward
What is the Artificial Intelligence?
Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Moreover
- It is simulation of human intelligence processes by machines, especially computers.
- It refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making and execute tasks in real time situations without constant supervision.
- Particular applications of AI includes expert systems, speech recognition and machine vision.
Significance of Artificial Intelligence:
- NITI Aayog’s national strategy for AI envisages ‘AI for all’ for inclusive growth, and identifies healthcare, agriculture, education, smart cities and infrastructure, and smart mobility and transportation as focus areas for AI-led solutions for social impact.
- Data and AI services are expected to help boost India’s economic growth in a big way. NASSCOM believes that data and AI will contribute $450 billion-$500 billion to India’s GDP by 2025, which is around 10% of the government’s aspiration of a $5 trillion economy.
- It has the potential to overcome the physical limitations of capital and labour and open up new sources of value and growth.
- The growing AI economy is estimated to create over 20 million technical roles alone.
- AI can create not just niche solutions to specific problems that banks and other service providers are deploying, such as speeding up loan application processing or improving customer service;
- it can also provide solutions for better governance and social impact. For example, during the lockdown, the Telangana police used AI-enabled automated number plate recognition software to catch violations.
- It has the potential to drive growth by enabling
- Intelligent automation i.e. ability to automate complex physical world tasks. o Innovation diffusion i.e. propelling innovations through the economy.
- Role in social development and inclusive growth: access to quality health facilities, addressing location barriers, providing real-time advisory to farmers and help in increasing productivity, building smart and efficient cities etc.
- The exponential growth of data is constantly feeding AI improvements.
- AI has varied applications in fields like Healthcare, Education, Smart Cities, Environment, Agriculture, smart Mobility etc.
Issues related to Artificial Intelligence:
- Ethical concerns- With popularization of a new technology, its virtues are not guaranteed. For instance, the internet made it possible to connect with anyone and get information from anywhere, but also easier for misinformation to spread.
- Data Management- as there is lack of clarity on data flow and data ownership which might result into data colonialism (data generated by developing countries yet not benefitting them).
- Biasedness: The algorithms used in artificial intelligence are discrete and, in most cases, trade secrets. They can be biased, for example, in the process of self-learning, they can absorb and adopt the stereotypes that exist in society or which are transferred to them by developers and make decisions based on them.
- Accountability: If an AI system fails at its assigned task, someone should be made responsible for it. e.g. an anti-terrorism facial recognition program revoked the driver’s license of an innocent man when it confused him for another driver.
Measures taken by the government:
- National Strategy for Artificial Intelligence- NITI Aayog has identified five areas where AI can be useful. It has noted the lack of regulation around AI as a major weakness for India.
- Center of Excellence in Artificial Intelligence by National Informatics Centre (NIC) which is a platform for innovative new solutions in AI space, a gateway to test and develop solutions for projects undertaken by NIC at central and state level.
- Global Partnership on Artificial Intelligence (GPAI): Recently, India joined GPAI as a founding member. GPAI is multi-stakeholder international partnership to promote responsible and human centric development and use of AI, grounded in human rights, inclusion, diversity, innovation, and economic growth.
The stakes are high for India. We need to speed up our readiness to seize the opportunities that the future presents. Three areas need our attention.
- The first is talent development. No meaningful conversation on AI preparedness can take place unless we are able to meet the rising demand with the right talent. In 2019, we nearly doubled our AI workforce to 72,000 from 40,000 the year before.
- The second area is policies around data usage, governance and security. Without data, there cannot be AI. However, we need a balanced approach in the way we harness and utilise data. We need a robust legal framework that governs data and serves as the base for the ethical use of AI.
- Third, though the use of digital technologies has gone up, the level of digitisation continues to be low. This poses a big challenge for organisations in finding the right amount of training data to run AI/ML algorithms, which in turn affects the accuracy of the results. Then there is the problem of availability of clean datasets. Organisations need to invest in data management frameworks that will clean their data before they are analysed, thus vastly improving the outcomes of AI models.
The future for AI looks promising but to convert the potential into reality, India will need better strategies around talent development, stronger policies for data usage and governance, and more investments in creating a technology infrastructure that can truly leverage AI.