Leverage artificial intelligence for better governance

Though the level of fraud in social welfare schemes as well as various subsidy programmes run by the government has reduced enormously ever since the use of Aadhaar biometrics increased, but as the scholarship scam in Jharkhand showed, there is enough scope for corruption even now; in the case of Rajasthan, this newspaper detailed the massive leakages in the health insurance scheme that was a precursor to the all-India Ayushman Bharat scheme.

One reason, of course, is that though the Aadhaar rollout is nearly universal, there are enough schemes that do not insist on this being used mandatorily even today. While the government needs to ensure that Aadhaar authentication is mandatory for all schemes at the earliest, according to a report in The Indian Express, the IT ministry is planning to conduct trial runs for the use of artificial intelligence (AI)—data analytics, to begin with—in various welfare schemes.

The ministry plans to use the service in some welfare and scholarships schemes initially and shall unveil a national implementation plan later. The development also comes on the back of Niti Aayog wanting to create a cloud infrastructure, AIRAWAT, replete with high-level AI applications which can be leveraged by government agencies to run data analysis.

While it is early days, in the case of Ayushman Bharat, a pilot exercise, for instance, helped detect 111 hospitals where fraud was being committed. Using analytics, companies hired by the government were able to detect persons who were trying to game the system by getting the same procedure done from the different hospitals; even Aadhaar authentication will not help detect this.

Given how fast Ayushman Bharat is growing—from 67 lakh in November 2019, Ayushman Bharat had 1.49 crore hospitalisations on December 25 this year. Using data analytics and artificial intelligence can help detect fraud to a large extent. Similarly, had AI been used in the case of Jharkhand, the information on scholarships would have been verified with not just the Aadhaar database but several others as well and then flagged the issue.

In agriculture, many start-ups are already using predictive analytics and sensors to determine irrigation and cropping techniques; governments can also leverage the system to detect soil degradation and water table depletion so that it can help with crop diversification, and the benefits of analytics for agricultural insurance is obvious. New research by Icrier along with Nasscom and Google shows that even a marginal increase in artificial intelligence adoption may add 2.5% to GDP in the immediate term. Given this, the sooner the government firms up, and activates, its plan to use AI in its services, the better.


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