View from India: Data annotation gains traction
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As 2021 comes to an end, we are still reeling under the impact of the pandemic. Yet Covid-19 has been an enabler and accelerator of digital health. It has also reinforced the digital economy, as companies both big and small have imbibed digitisation and digitalisation.
Dial D for Digital Health
India is gearing up to occupy a prominent place as a digital health leader in the global scenario. The stage has already been set with national public health initiatives such as Ayushman Bharat, a Government of India flagship scheme that aims to achieve the vision of Universal Health Coverage. Prime Minister Narendra Modi has launched the Ayushman Bharat Digital Mission, which aims to bring the healthcare records of citizens on to a national digital platform where every citizen will be issued with a unique 14-digit health identification number, which will also double up as their health account and contain details of every test, every disease, doctors visited, the medicines taken and the diagnosis. It will be portable, enabling patients to access it even if they shift to another city.
The adoption of digital health scaled-up in 2020 as Covid-19 spread rapidly. There was a rush for digital health platforms such as the government-initiated Arogya Setu app. As an official source of Covid-19 information, the app aims to connect citizens to essential health services. Technology is being leveraged in the national vaccine drive and the app supports Indian vernaculars. The Covid-tracking app warns users if they have come into close contact with people infected with the virus.
Going ahead, healthcare issues will continue to be addressed through digital technology. We are probably moving towards an era where digital and automated robots will perform many medical services. Manual efforts may be streamlined as pathology will be digitised.
The general consensus is that with new entities, it can be a make or break experience. But, considering the pandemic kept spreading and taking away lives, people had little choice but to make a scramble for telemedicine portals. Tele consultation and online clinical support have suddenly become a mission-critical option. Intelligent diagnosis along with healthcare devices is on the rise as much as online medical assistance, remote or contactless healthcare monitoring, portable diagnosis system and home testing kits. AI-IoT-powered algorithms form the core solutions of many of these devices. Venture capitalists are expected to capitalise on this emerging market by investing in digital healthcare deep-tech startups; hopefully this could bridge the demand-supply gap.
Along with healthcare, empowerment of rural women is also a concern. This led to the Nav Tejaswini programme, initiated by the UN’s International Fund for Agricultural Development and the Government of Maharashtra with the vision to empower rural women across Maharashtra’s 34 rural districts. Livelihood opportunities will be created along with access to finance and markets, and household food and nutrition security. Gender inequalities will be addressed and women-friendly technologies will be made available to reduce workloads. Let’s hope these women get the know-how of technology and many of them spread the word and teach others.
Chip – Core to the Digital Devices
Organisations have gleaned the various facets of artificial intelligence (AI), whose tools are integrated into stock trading, search engines and news feeds. Since AI understands its surroundings and their purpose, it will focus on actions to fulfil this.
This decade, AI-data will continue to determine decisions across industries while playing a pivotal role in satellite imagery and climate change. Agricultural crop patterns will continue to be mapped.
The frontiers of AI are expected to extend to a new dimension: R&D professionals could pursue AI algorithms to create machines through which people connect with the medical fraternity. Seen realistically, it will take care of the last-mile individual as well.
Data annotation is gaining traction and may become a must-have for pre-processing data for machine learning (ML) due to the automated applications-services and smart devices that may require training data sets. Data annotation is the process of adding metadata such as text, images and video on to the dataset. Simply put, data annotation categorises and labels data that find specific usage in AI-ML applications. When text data is annotated, it helps in streamlining workflows, increases customer experience and eliminates manual errors; this is particularly handy while dealing with medical data. Along with text data, voice-annotated data may open up newer digital services in the voice assistant realm of Alexa and the likes.
IT organisations can conceptualise data annotation tools in-house or outsource it to third parties, which itself can generate jobs. ML is being leveraged for financial decisions and real-estate evaluations. ML, combined with computer vision and extensive use of drones, could be the way forward.
There have been reports about job losses in the Indian IT/BPM industry. NASSCOM has put things in perspective around hiring and job creation in the sector: with the evolution of technology and increasing automation, the nature of traditional IT jobs and roles will evolve, leading to creation of new jobs. In a statement, the apex body clarified that the industry continues to be a net hirer of skilled talent, adding 138,000 people in FY2021, and has robust hiring plans for FY22 with the top five Indian IT companies planning to add over 96,000 employees. The industry is upskilling more than 250,000 employees in digital skills and has hired more than 40,000 fresh digitally trained talent, indicating its commitment and investment towards rapid enhancement of workforce capabilities.
The increased thrust on digital skills is because the pandemic has accelerated the pace of the digital growth. Digital preparedness is also required as the country is putting steps in place to scale-up the electronics manufacturing processes. The country is ramping up its domestic production of Internet-led equipment, smartphones, computers, electronics and connected devices. The design-functionality of the products aims to be of international standard so that they can be retailed in the global market. The semiconductor chip is the core of the electronics manufacturing; the country probably needs to build a robust community of chip players that have the technical know-how of the segment. In December 2020, the government called for Expression of Interest from companies that plan to set up semiconductor fabrication units or expand the existing ones – the vision is to strengthen the domestic supply chain of the semiconductor ecosystem, including front-end manufacturing and back-end assembly. This will lower the dependence on imported supplies. Microprocessor chips, required for hi-tech electronics devices, are produced in semiconductor fabrication units.
As the months went by, India received $64bn in foreign direct investment (FDI) in 2020. With this, the country notched up to fifth place in FDI globally as per the World Investment Report 2021, released by the UN Conference on Trade and Development. Various media reports indicate that the FDI increased to $64bn in 2020 from $51bn in 2019; this is a 27 per cent increase in inflows, largely driven by acquisitions in the software-hardware segments of the information and communication technology industry. Verticals like health, infrastructure, and energy are also boosters. In a pandemic-stricken year pulled down by economic fluctuations, this comes as a surprise. While FDIs have witnessed an uptick, it would be nice if smaller firms also attract big-ticket investments. For this, small firms may have to equip themselves with up-to-date skill sets.
The pandemic has catapulted Cloud into top slot. Enterprises, both big and small, prefer to save their data on the cloud as it assures cost efficiency and operational smoothness. Public-cloud, multi-cloud and hybrid-cloud environments are among the popular choices. Along with IT companies, insurance and retail companies have migrated to the cloud, which could be attributed to the fact that the volume of online transactions has multiplied in these industries since last year. Cloud practitioners with expertise in PaaS (Platform as a Service) and SaaS (Software as a Service) are on the rise. The future points to job scenarios where cloud engineers could be in demand.
Fintech is expected to be more inclusive in nature. Serving the un-served customers in the market, offering flexi loans and creating a level of readiness for the last-mile customers are among the key takeaways of the fintech system. There may be agile lending models, wherein lending happens at one click.
Innovation is anticipated to happen in the payment space. As per the Reserve Bank of India (RBI) mandate, the voluntary pre-paid instruments are to be interoperable; this includes mobile wallets and pre-paid cards. With this, customers can transfer money from a wallet to a bank account and also from one company’s wallet to another, besides using mobile wallets at ATMs to withdraw cash. All this happens without a bank account. Enabling factors come in the form of RTGS (real-time gross settlement) and NEFT (national electronic funds transfer), RBI-operated centralised payment systems open to PPIs for membership. The national finance-digital inclusion is expected to bring in first-timers from tier cities.
The Government of India has recognised 50,000 startups in the country, and over 10,000 have received approvals to go ahead. Registered with the Department for Promotion of Industry and Internal Trade, the startups represent verticals including IT, healthcare/life sciences, education, professional/commercial services, agriculture, and food and beverages. These startups are expected to generate jobs and enrich the R&D ecosystem of the country.
Startups have shown resilience in the pandemic-hit year. India is home to several 'Unicorns', a startup company valued at over $1bn. As the lockdown was gradually lifted in the second half of 2020, investors came forward with their deals. The second wave of the pandemic was devastating and many organisations were jolted out of their comfort zone to integrate digitised and digitalised solutions. Ironically this was an opportunity waiting to be tapped. Though the startups are not legacy brands, investors nurture them and back them with capital. Investments continue to pour in because the startups have a pulse on the market and specialise in software services and digital education, or ed-tech. Many of these startups specialise in healthcare and customise enterprise software solutions.
The ed-tech space has grown phenomenally during the pandemic. India is home to a few thousand ed-tech startups that have chalked out a variety of app-based modules for learners of different age groups. Live courses are beamed through videos, besides whiteboard and audio alternatives; SaaS platforms provide learning solutions including early childhood learning and STEM courses, while there are customised online courses and management systems, and apps based on augmented reality and virtual reality for the coding lot. Hour-based packages as well as monthly schemes are available, depending on the requirement.
Ed-tech startup BYJU’s is India’s most valuable startup, valued at $16.5bn. Ever since the pandemic brought the spotlight on online education, BYJU’s was quick to react and raised funds from various sources. The company has consolidated its position in the ed-tech space by acquiring tutorial chains and niche businesses. Co-founded by couple Byju Raveendran and Divya Gokulnath in 2015, Byju’s is the world’s 11th most valuable startup. It has emerged as the country’s most valuable unicorn startup, surpassing fintech company Paytm's $16bn valuation.
Technology gives scope for bringing in a personal layer of requirements. A case in point is an individual’s preferences for watching a film on Netflix. Likewise, other aspects such as key performance indicators, customer acquisitions and average revenue per user will all result in new business models.
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