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.