Authored by – Gaurav Aggrawal (2014 IAS Topper)
They say Napoleon couldn’t have happened without the French Revolution. They also say that the rise of Napoleon was inevitable in the aftermath of the French Revolution. People and events are mere cogs in the wheel of history. Once there is a necessity, and the conditions are ripe, the idea takes fruition.
Artificial Intelligence (AI) in governance is an idea whose time has come. The necessity is there – our people are growing ever more exasperated and demanding efficiency in public services delivery while the traditional systems seem to be unable to cater to these changing times.
Also, the conditions are ripe – thanks to the use of IT there is a lot of data in the government today in machine-readable form, and the technologies have reached a level where they can rival any human on a real-time and cost-effective way.All that is needed now is that leap.
AI would fundamentally transform methods of governance in this country. We often hear complaints that the implementation of government schemes remain confined only to papers. Now, what if there is a way to check if things are happening on the ground? Take, for example, the Swacch Bharat Mission (SBM). To make sure that the toilets are built, the government has developed a mobile app where the government functionary will have to go to the toilet site, click a photo of the toilet along with the beneficiary, and then upload it to the central server. Connectivity issues are taken care of by giving offline photo-clicking mode and uploading the photos when the person comes back on a 2G network. This curbs malpractice to a great extent.
However, there are ten crore toilets that are needed to be built and hence ten crore photographs. Is it manually possible to check these photos? Or if the toilet is in use or is stashed with hay? And is the same beneficiary appearing on multiple photos? What if 100 photos have been uploaded from sitting in an office? Clearly no.
The present system relies on people to do random checks to create a deterrence effect but so has the system that we have relied upon for past 70 years and the outcome is for us to see. It does not work because of people either not having enough time or lacking the inclination to do petty things.
Now what if you actually get a way to process each of these 10 crore photos and generate an alert whenever the photograph is not that of an entirely built toilet which is actually in use (not stashed with hay or other stuff) and same beneficiary doesn’t appear in multiple photos or multiple photographs don’t get uploaded sitting in the office? Won’t cheating and malpractices go down by order of magnitude as people realise that each photo would be scrutinised and not just some small sample? Wouldn’t it be awesome to know we have ten crore functional toilets on the ground and not just paper? That, my friends, AI can achieve – and in a very cost efficient manner.
But then the sceptics argue that in rural and remote India, the penetration of internet is very low and as a result, AI will have limited or no applicability there and will create a digital divide. However, contrary to this, the need and applicability for AI are more in the remotest areas of the country than in the heart of the capital. That is because it is in these most secluded areas that the traditional governance systems are entirely broken. Physical infrastructure is inefficient, and the people are poor and unaware.
Generally, no one wants a posting there – most people there would be on punishment postings, and as soon as they come, they would start spending their energies in getting a transfer back to the mainstream areas. As a result, there are problems of severe under-staffing, lack of morale, poor quality in the government workforce and weak monitoring of government schemes and implementation. In Delhi and state capitals, there would be a lot of people to check if toilets are built, we won’t need AI. But who will check in the tribal areas of Rajasthan or Chattisgarh? Imagine if in these regions, the government schemes start functioning as they were supposed to do, AI will bridge the development and digital divide, not accentuate it.
Likewise, again contrary to what the sceptics say, the scope of AI is immense in traditional sectors such as agriculture. For example, take the government run crop insurance scheme; in this crop insurance scheme, if the yield is below a threshold, it would trigger an insurance payout to the farmer. To determine the actual yield, millions of crop cutting experiments would be carried out – much more than what are mandated today. As per the scheme guidelines only, even the ones done today “lack reliability, accuracy and speed”.
So mobile app solutions could be developed where geo-tagged photographs of the crop cutting experiment would be uploaded like SBM. Would it not be amazing if we have a solution to check these millions of photos to see whether an actual crop cutting experiment has been carried out by the same person who was supposed to carry it out or has the crop cutting experiment work been sub-contracted to unskilled individuals who went there and clicked selfies?
Similarly, the government runs Kisan Call Centres which receive lakhs of calls every month. Wouldn’t it be priceless if we can get a timely warning from the call centre data that say in Maharashtra, this year the distress level among farmers is unusually high due to this particular factor? Perhaps then the administrative machinery can be activated timely on a war scale to prevent farmer suicides? Or say based on soil and environmental condition reports from our satellites and based on what crop is sown in a particular area, we can predict that this year vulnerability of this crop to this pest is higher, and perhaps we can supply additional required pesticide there and send targeted SMS / agronometric advisories to the farmers in that region?
All these things have not been taken from some science fiction movie but are very much available, proven and economic technologies. Similarly, there is a Kisan suvidha app – the flagship app of the agriculture department – where among other things, a person can upload three photos of some pest infected crops and our scientists would tell what the problem is and what the remedies are.
However, as with the case with almost anything in our country, the rush is huge, there are thousands of queries and there isn’t enough capacity to answer all the queries manually. As a result, many questions go unanswered, and people’s faith suffers due to which they would stop using it in future. Again, AI can help here. Even if the farmer himself doesn’t have a smartphone, even in remotest areas of the country, today someone will be having a smart-phone and there would be a 2G connectivity nearby if not within the village. So these are solutions which can work given the enormous social capital in our rural society.
Finally a word on another common misconception – that AI will lead to loss of jobs. One bane of our country is systems don’t work here. AI can make them work. It can leapfrog us regarding development to the level of Singapore or Western nations. It can bring immense prosperity to the country. The government today is over-burdened, and there is a lack of capacity to do the multitude of tasks it has taken upon itself.
AI is our answer to capacity building. Human beings are not like horses – that after the mass production of cars, horses were suddenly rendered jobless. When machines started spinning cotton, we started to build machines. Productivity gains always create more and better jobs than the ones which are lost due to them. We are still far away from a Terminator kind of scenario where machines may be able to replace humans. That might happen 50 years from now, not today – and if it has to happen, will happen regardless of whether the government uses AI or not. But the massive productivity gains cannot be ignored.
Apart from the examples mentioned above, there is a huge scope of AI in fields such as grievance redressal, law and order, health, education, etc. Today the West is using driverless cars and flying drones. 300 years ago, the West was similarly inventing and using new technologies like the steam engine and cotton gin. We chose to shut our eyes then, and we all know what happened afterwards. Can we afford to make the same mistake again?
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Steve Ovett, the famous British middle-distance athlete, won the 800-metres gold medal at the Moscow Olympics of 1980. Just a few days later, he was about to win a 5,000-metres race at London’s Crystal Palace. Known for his burst of acceleration on the home stretch, he had supreme confidence in his ability to out-sprint rivals. With the final 100 metres remaining,
[wptelegram-join-channel link=”https://t.me/s/upsctree” text=”Join @upsctree on Telegram”]Ovett waved to the crowd and raised a hand in triumph. But he had celebrated a bit too early. At the finishing line, Ireland’s John Treacy edged past Ovett. For those few moments, Ovett had lost his sense of reality and ignored the possibility of a negative event.
This analogy works well for the India story and our policy failures , including during the ongoing covid pandemic. While we have never been as well prepared or had significant successes in terms of growth stability as Ovett did in his illustrious running career, we tend to celebrate too early. Indeed, we have done so many times before.
It is as if we’re convinced that India is destined for greater heights, come what may, and so we never run through the finish line. Do we and our policymakers suffer from a collective optimism bias, which, as the Nobel Prize winner Daniel Kahneman once wrote, “may well be the most significant of the cognitive biases”? The optimism bias arises from mistaken beliefs which form expectations that are better than the reality. It makes us underestimate chances of a negative outcome and ignore warnings repeatedly.
The Indian economy had a dream run for five years from 2003-04 to 2007-08, with an average annual growth rate of around 9%. Many believed that India was on its way to clocking consistent double-digit growth and comparisons with China were rife. It was conveniently overlooked that this output expansion had come mainly came from a few sectors: automobiles, telecom and business services.
Indians were made to believe that we could sprint without high-quality education, healthcare, infrastructure or banking sectors, which form the backbone of any stable economy. The plan was to build them as we went along, but then in the euphoria of short-term success, it got lost.
India’s exports of goods grew from $20 billion in 1990-91 to over $310 billion in 2019-20. Looking at these absolute figures it would seem as if India has arrived on the world stage. However, India’s share of global trade has moved up only marginally. Even now, the country accounts for less than 2% of the world’s goods exports.
More importantly, hidden behind this performance was the role played by one sector that should have never made it to India’s list of exports—refined petroleum. The share of refined petroleum exports in India’s goods exports increased from 1.4% in 1996-97 to over 18% in 2011-12.
An import-intensive sector with low labour intensity, exports of refined petroleum zoomed because of the then policy regime of a retail price ceiling on petroleum products in the domestic market. While we have done well in the export of services, our share is still less than 4% of world exports.
India seemed to emerge from the 2008 global financial crisis relatively unscathed. But, a temporary demand push had played a role in the revival—the incomes of many households, both rural and urban, had shot up. Fiscal stimulus to the rural economy and implementation of the Sixth Pay Commission scales had led to the salaries of around 20% of organized-sector employees jumping up. We celebrated, but once again, neither did we resolve the crisis brewing elsewhere in India’s banking sector, nor did we improve our capacity for healthcare or quality education.
Employment saw little economy-wide growth in our boom years. Manufacturing jobs, if anything, shrank. But we continued to celebrate. Youth flocked to low-productivity service-sector jobs, such as those in hotels and restaurants, security and other services. The dependence on such jobs on one hand and high-skilled services on the other was bound to make Indian society more unequal.
And then, there is agriculture, an elephant in the room. If and when farm-sector reforms get implemented, celebrations would once again be premature. The vast majority of India’s farmers have small plots of land, and though these farms are at least as productive as larger ones, net absolute incomes from small plots can only be meagre.
A further rise in farm productivity and consequent increase in supply, if not matched by a demand rise, especially with access to export markets, would result in downward pressure on market prices for farm produce and a further decline in the net incomes of small farmers.
We should learn from what John Treacy did right. He didn’t give up, and pushed for the finish line like it was his only chance at winning. Treacy had years of long-distance practice. The same goes for our economy. A long grind is required to build up its base before we can win and celebrate. And Ovett did not blame anyone for his loss. We play the blame game. Everyone else, right from China and the US to ‘greedy corporates’, seems to be responsible for our failures.
We have lowered absolute poverty levels and had technology-based successes like Aadhaar and digital access to public services. But there are no short cuts to good quality and adequate healthcare and education services. We must remain optimistic but stay firmly away from the optimism bias.
In the end, it is not about how we start, but how we finish. The disastrous second wave of covid and our inability to manage it is a ghastly reminder of this fact.