The pandemic situation has not been able to prevent the scientific developments and discoveries. One such instance is the brain-machine interface, recently demonstrated by scientists at Elon Musk-backed Neuralink. According to a report by venturebeat.com, “Readings from a pig’s brain were shown onscreen in a live demo. When the pig touched an object with its snout, neurons captured by Neuralink’s technology (which had been embedded in the pig’s brain two months prior) fired in a visualisation on a television monitor.” This can be a landmark development in the field of science and technology.
AI during pandemic
Technology has proved to be efficient than ever in this pandemic situation. Artificial Intelligence has helped in the functioning of various sectors in a more versatile and customised way. Prasoon Nigam, CTO & Co-Founder of Stratbeans, while talking to BE about the development by Neuralink said, “As of now introducing this kind of technology into the e-learning can be exceptionally valuable and opens up better approaches for instructing and for students to learn as technology unfolds into the reality, we will encounter the development being brought into the education sector.”
Undoubtedly, with online classes, examinations, evaluation, online laboratories and other facilities, education sector has been quite efficiently utilising the AI technology throughout this pandemic period. Nigam informed, “The AI in the education market is supposed to reach $2 billion by 2023 developing at 38% CAGR in the estimated time frame 2018-2023.” He further stated that all students are different with different learning approaches. The educators cannot manage to personalise their teaching methods for an entire class keeping that in mind. In such a scenario, AI can be of great help by making content easily digestible.
AI has also been used in the other sectors and it has played an important role in the battle against the Covid-19 pandemic.
· Banking and financial services – AI-based chatbots are being sent in the insurance area to improve the customer experience. Another significant application of AI in the finance sector is fraud detection which is taking a shape in today’s world.
· Logistics and transportation – The utilisation of machine learning and predictive analytics has already transformed supply chain management, making it a consistent process. Moreover, AI algorithms can also be progressively used to locate the fastest shipment course and backing the last-mile conveyance.
· e- Commerce- These companies are progressively incorporating AI in different applications to increase an upper hand in the market. The adoption of AI-fuelled tools encourages companies to analyse the list progressively to serve customers with comparable and pertinent items.
· Mobility industry - AI applications are integrated into each new vehicle manufactured these days.
· Health sector - AI has a critical influence in the health sector in technological advancements - from autonomous surgical robots, virtual nursing assistants to automated image diagnosis.
A report by codingelements.com suggested that throughout the pandemic period, AI has helped in restricting the spread of fake news. The report stated, “Fake news does nothing but spreads fear in the minds of people. WHO has collaborated with Praekelt.Org to deliver precise and helpful information directly to people. They have used AI to help with this initiative.” Analysing the large chunks of data and providing useful insights, predicting the progress of diseases, robotics, data visualisation, etc., AI can help researchers tremendously not only to combat this pandemic but also to assist in future research.
Problems and prospects in India
In India, the finance ministry allotted the expenditure of `7,000 crore ($1 billion) for the proposed NITI Aayog’s AI programme. The billion-dollar AI financial plan declared by the Indian government is likely to be used by the NITI Aayog in the time span of next five years. However, there are certain challenges in development of AI programme in India.
However, India is still miles away from opening the true value of the huge repository of data collected from different sources using AI and Machine Learning (ML) techniques, in both the government and the private sector. There are two wide requirements for dispersion – ‘policy push’ for spread of AI adoption and ‘policy pull’ (trust of consumers or users). The policy push has been inadequate. The other key element of diffusion is to gain the trust of consumers and residents by protecting their privacy and data, which is again absent because of the absence of privacy law in India.
The quality of connectivity is also a fundamental challenge for AI development in India. Nigam pointed out, “There must be expanded long-term investment in Artificial Intelligence in both the public and private sectors. India lingers behind the main five topographies for private area interest in AI.” He also feels that in order to support AI infrastructure in India, there is an earnest requirement for government departments both at the central and the state levels to embrace AI-based solutions to solve the legacy and intractable problems being faced by them – from expanding agricultural productivity to climate change, from air pollution to disaster management.
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