Much as has been written about the role of artificial intelligence and machine learning in shaping the economy of a country and how the technology has the potential to better governance.
Due to the high rate of efficiency in bringing about the desired change at a large scale, governments across the world is mulling its application at a macro-level within its various subsidiaries.
The Indian government too has taken considerable steps for better the adoption of the technology and has partnered with various AI-solution providers for improving their working.
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Unlike the western governments, which took to digital transformation years back and have the benefit of owning vast swath of digital data, in India, the availability of strong data set is still a problem as many public offices still follow the traditional mode of documentation.
India’s unstructured data is the key
However, over the last couple of years, the government has been working round the clock to improve the situation and the government has been taking slow but steady steps to improve the situation.
The amount of unstructured data that the public offices currently hold coupled with data from social media conversations, comments from public portals would itself table to a strong data that the AI solutions providers have been hungry for.
Realising how public data sets can be a boon and addressing the issue of non-availability of in its draft AI Policy, the NITI Aayog highlighted that it would set a National AI Marketplace where unused public data will be made available through the platform. The proposed three-pronged platform will comprise of an exclusive data marketplace to make AI training data sets and services available at a reasonable price.
Further, the government added that it will make data from institutes like ISRO (India Space Research Organisation), ICAR (Indian Council of Agricultural Research), All India Radio (AIR) and NIC available at the marketplace.
NL for unstructured data
One of the biggest challenges that unstructured data pose is that often it becomes a challenge to identify patterns and to draw insight from it. Hence, the applicability of NLP in this vast pool of unstructured government data can be highly beneficial and can aid the process better policy-making and even to improve public services across sectors.
We look at how NLP can help with improved governance through its application in unstructured data.
To tackle crime: By applying NLP to data collected from social media platforms and other public domain, the system can tame possible criminal activities that are likely to occur in the future. Also, by leveraging NLP in existing criminal records, law enforcement agencies can identify patterns, the interrelation between criminal activities and identify criminal pockets.
In India, presently the AI-systems like facial recognition have used beforehand and crowd monitoring is another area where AI has found a sound ground. But by expanding and looking beyond the existing use cases, the law and enforcement can ensure further protection for people.
Analysis of public feedback: India’s diversity and the uniqueness of each state is the right fodder for NLP to thrive and provide better service to its users. With the central and state governments pushing for governance, currently almost every public services are available online and the number of people who are availing this service has gone up considerably.
Though chatbots are highly in use among private players in the country, the adoption in it in public portals is still not looked into.
By leveraging technologies like chatbots in public portals, the government can guide the users to the right services and also answer their queries thus improving public service.
Improving healthcare: Though the application of AI for medical research purpose is making considerable advancement in India, it hasn’t made considerable progress to other aspects of the field. Medical data from across the country would compound a large pool and public hospitals institutions haven’t made considerable use of it.
In a recent study by Indian researchers who looked into the application of big data in medical receipts, the researchers found that many a time several patients are sent to wrong medical departments. Hence, by augmenting health records and by applying text analytics along with NLP, the researchers were able to direct the patients to the right medical department.
