Since it was formally founded in the early 1940s, computer science has made extraordinary progress and contributed positively to society. It has, in many cases, lowered the barrier for access to information, transactions, education, and healthcare. It has enabled us to put man on the moon and perhaps even beyond. It fuels the most modern progress in science. It has rendered distance immaterial. It may even help by driving cars for us, delivering packages in cities and flying aircraft. And, in some cases, it even appears that ‘intelligent’ software systems may entirely take over from human beings. In fact, the birth, genesis and vision of computer science has always been to build a machine that can ‘accurately’ emulate human ‘intelligence’.
Despite all these strides, computer science still has a fair bit of distance left to cover before it can produce a software system that is functionally capable the same way a human is. The understanding of ‘intelligence’ in computer science, though defined in academic circles, has been fairly misused (and/or 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.
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 on the basis of whatever data we train it with. Though, in some cases, given large amounts of data and human input, we are able to get software to discover some rules on its own.
But at the core of it is the fact that we have not invented any new magic wand to make software ‘think’ on its own or have any sense of ‘consciousness’, in the way humans do. Instead, the most important 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, yielding what some may consider as 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, car driving, playing games, etc. In these cases, software can emulate human behaviour and perhaps even exceed human capabilities.
These gaps help deflate claims that artificial intelligence (AI) and automation are ready to take over people’s jobs and potentially spark mass unemployment, particularly in the Indian IT industry. This industry employs a couple of million people, largely comprising our Indian middle class, and recently has been called out by commentators as under threat from automation.
But automating away this labour force is not an easy task. Even though, as a computer scientist, I am bred to believe in the superiority of silicon (computers) over carbon (humans), my work and study over the past few years in this industry has given me reason 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 is to emulate the same value that humans bring to the table.
In the case of the Indian IT industry, for example, professionals perform a range of activities spanning understanding customers’ business requirements, writing code, maintaining software systems and processing transactions. Working in teams, they perform a variety of 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, that are inherent to each one of us, and ultimately create trust and confidence in our colleagues. This trust and confidence are the fuel all businesses run on. Therefore, it has always been more than just following ‘simple’ rules.
So 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.
Consider, for example, questions that managers could ask their teams today. ‘Why did you do that?’, ‘Why did you choose X over Y?’, or ‘Are you sure?’. Or more simply put, ‘explain yourself’. For all the reasons articulated earlier, these questions, though straightforward for humans, are very difficult for machines to answer. Therefore, the next stage of innovation in computer science will be not just to make software run faster, but also about how we get software to emulate more human-like traits and ultimately become truly trustworthy (like humans).
All this said, we should not be naive to think that technology won’t eventually succeed in recreating some-if not many-layers of human cognition and range of activities. And given this eventuality, it is important to think about and begin planning how India can excel in this new normal. Much of this, it appears, will depend on our preparedness for upskilling opportunities.
The IT industry is no stranger to upskilling. In fact, companies like Infosys and a few others have made unprecedented efforts in training campuses as a way to augment the engineering education imparted to the country’s young people. For example, Infosys has the capacity to train anywhere between 40,000-60,000 people each year at its Mysore campus. Such investments in training, perhaps more than anything else, give such companies an insurance policy against a future of automation. But one may say, isn’t an idea of ‘training’ a copout? In the software world, learning has been a constant feature. Consider this: in the 1980s, a FORTRAN/C programmer was in vogue, C++/Java in the 1990s, perhaps Python/Go/Ruby today, and so on. Hence, constantly learning and re-training has been a way of life in this industry.
But even if the promises of automation are only half as true as the hype, it suggests that just a fraction of India’s IT industry professionals, even with all that company-led training, will be required. Those who are needed will have to learn areas of computation that are far more advanced than what the IT industry presently offers. So, do we again look to the IT industry to lead the upskill charge, or is a broader public-private coalition required?
India is not alone in this conundrum. Many countries, including the United States, have been grappling with the question of who owns the responsibility of upskilling, especially in the face of challenges from offshoring or automation. And, as recently evidenced, even notional attitudes of a community being overlooked by a changing economy can have significant implications on political outcomes.
Despite these struggles, and those of many other countries, it’s unclear if a paradigm for upskilling populations has emerged. Which brings us back to my original point: the remarkable capability of the human mind. In an ideal world, this push toward automation would be a catalyst for upskilling, which would unlock remarkable human potential and usher in a new, more technologically advanced economy for India. In the real world, however, this will take a shared mission, careful planning and genuine cooperation.