The most fundamental progress that technology has made over the past few decades is a dramatic increase in computing power coupled with a reduction in the cost of storage. Such progress has enabled us to run algorithms and code over swathes of data and at a fraction of the cost, thus yielding what some may consider more insights. Consequently, we are able to find patterns in large amounts of data. This, by some limited definition, is construed as intelligence and has been demonstrated in specific classes of activities such as detecting diabetes from retinal scans, driving cars, playing games, etc. In these cases, software can emulate human behaviour and perhaps even exceed human capabilities. But the fact is that we have not yet invented any new magic wand to make software “think” on its own or have any sense of “consciousness”, in the way humans do.
The limitation is grounded in the fact that software still operates, for the most part, on the paradigm of Gigo (garbage in garbage out), meaning it mostly only does whatever we tell it to and is biased based on whatever data we train it with. Give it incorrect data and it will pick up incorrect patterns.
But the vision and aspiration of computer science has always been to build a machine that can “accurately” emulate human “intelligence”. However, we still have a long way to go before we can build a software system that is functionally capable the same way a human is. Software “intelligence”, though defined in academic circles, has been fairly misused (and misunderstood) in popular reporting, giving people the impression that software can do just about anything a human being can. This notion is fundamentally misguided. We are not there. Or at least not yet. The gap between software and the human mind is still massive.
These gaps help to deflate claims that artificial intelligence (AI) and automation are ready to take over people’s jobs, and about the potential for mass unemployment, particularly in the Indian IT industry. This industry employs a couple of million people, largely consisting of our middle class, and recently it has been called out by commentators as being under threat from automation.
But automating away this labour force is not an easy task. Computer scientist believe in the superiority of silicon (computers) over carbon (humans), the work and study over the past few years in this industry have given reasons to pause and consider the unique contributions and value that humans bring to the table in enabling businesses the world over. Automating these unique attributes requires emulating the same human value.
In the case of the IT industry, for example, professionals perform a range of activities, from understanding customers’ business requirements to writing code, maintaining software systems and processing transactions. Working in teams, they perform a variety of different actions touching several information systems, coordinate with each other, navigate uncertain or changing scenarios, report to their managers, take bottom- line responsibilities for their respective systems, are accountable and serve customers across the globe. All these activities engender a deep sense of trust and confidence among their customers the world over.
At an individual level, each has traits such as intuition, experience, common sense, and an ability to identify and fix the unusual. These are fundamental traits that all humans share, though, admittedly, some more than others. Even in the most seemingly “robotic” of tasks, each human has the potential and ability to apply these traits without necessarily being told to do so a priori, traits that are inherent to each one of us, and ultimately create trust and confidence in our colleagues. This trust and confidence are the fuel that all businesses run on. Therefore, it has always been about more than just following “simple” rules.
Hence, any attempt by “intelligent” software at automating all that work done by a single individual or an entire team of humans must involve recreating the same trust and confidence. This necessarily requires addressing the whole gamut of these activities that humans perform on a regular basis and with similar human traits, but in software. This is no longer about small piecemeal tasks that are easy to automate. It must involve emulating the same traits of common sense, intuition, teamwork, communication, and an ability to deal with the unexpected.
Therefore, the next stage of innovation in computer science will be not just to make software run faster but also about how to get software to emulate more human-like traits and ultimately become truly trustworthy (like humans).
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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.