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Should we all become computer programmers?

LiveMint logoLiveMint 20-03-2017 Siddharth Pai

Workers in the information technology (IT) industry worry about the decline in computer programming jobs due to the rise of automation and artificial intelligence (AI). Many former stalwarts are predicting doom for the industry. One of them has claimed that up to 200 million Indians will become jobless over the next decade. Consulting firm McKinsey and Co. makes a prediction that is even more dire, and which encompasses more than just the computer programming profession. It says that 51% of today’s jobs can already be made obsolete—not by technology that is over the horizon, but by technology that is available today, thereby saving the world’s capitalists almost $15 trillion in wages.

As an aside, I can see almost every CEO begin to salivate. This is an opportune moment for consultants to birth a new buzzword, since Six Sigma, Transformation and Digital Disruption are all passé. I am going to christen it Technology Efficiency Engineering (TEE). Long may TEE live, and line the consulting fraternity’s pockets.

Some governments such as Finland’s are already experimenting with macroeconomic moves such as establishing a universal basic income (UBI), which is a flat dole paid out to every citizen, in the expectation that automation will make the population jobless. Others, like former US president Barack Obama, are stressing the need for retraining millions of workers. Robert Reich, former US secretary of labour, suggested in a recent speech at Google’s offices that people should find fulfilment outside of work instead, since the level of unemployment will soar while median incomes stagnate or decline due to technology.

This prediction of the “end of work” is difficult to swallow when one concurrently hears that the world economy is healthy; last week’s The Economist says the global economy is experiencing a “surprising” upturn, despite the rise of economic nationalism. Moreover, the IT industry is also expected to grow at speed over the next few years—some estimates place the growth at over 12% compounded annually.

Where, then, is the disconnect?

Reich provided a part of the answer, when after plugging UBI, he went on to say that the reduction in median incomes in the counties that overwhelmingly voted for President Donald Trump was caused not by “globalization” but by the inexorable rise of technology, and its almost insidious spread into every field of human endeavour.

So, the inescapable fact is that computer programming is not going to go away any time soon; all that is going to happen is that the need to program a computer is going to become a mainstream part of any worker’s job, whether blue collar or white, much like familiarity with basic word processing or spreadsheets is today indispensable to many.

Computer programming requires different skills than today’s blue-collar work, which often lies at the intersection of man and “unintelligent” machine. Interestingly, it also requires different skills than those needed for top-drawer jobs, which one pursues only after a long, strenuous period of education and apprenticeship—such as advanced biological science or medicine. According to Wired, many employers are responding to the needs of the evolving job market by attempting to make it more accessible for their employees to learn to code.

Google, where Reich delivered his speech, has initiatives designed to engage and teach programming to anyone who may be interested. Schools the world over have been working to introduce coding early during a child’s schooling. We have seen institutions in India such as NIIT offer intensive programming courses to aspiring professionals. Fifteen years ago, NIIT’s headquarters outside Delhi even had computer consoles placed in cubbyholes on its perimeter walls, so that the indigent children playing in the fields outside its facility could familiarize themselves with the machines. The hope of that generation was that a decent level of education in coding would be enough to qualify NIIT’s students for a reliable job in the IT sector. Evidently, this may now be better focused on the population at large.

Once coding is demystified and people realize that it is but a simple, learnable skill of the expression of logical commands, coding has the potential to open more doors to employment in the age of automation. Simple coding may not be enough to make you an AI expert, but it can certainly help you do your own job better.

Wired cites the example of an Indian origin postdoctoral researcher in biology who has realized that she needs to code to run her laboratory. She had reams of data that came out of her lab experiments but found it limiting that she needed to go to someone with coding skills each time she needed to array and make sense of the data. The lady has now enrolled in an introductory programming class so that she can now do her job without being limited by her lack of ability to massage and manipulate her lab data as needed, since, as she says, she can’t manually look through 15,000 datapoints any longer.

The US National Institutes of Health has also caught on, reportedly, and has been pushing to add coding skills to biomedical postgraduate training, since apart from specialized computational biology and bioinformatics programmes, most other fields of biology research don’t require coding classes. Meanwhile, working scientists who need to know this skill now turn to other means.

One can see the need to be able to write code in almost any profession. McKinsey’s analysis has looked at the intersection of certain routine tasks such as real-time optimization or the discovery of new trends—with various industry sectors such as healthcare and telecom (think triage in a hospital emergency room or self-healing telecom networks) in an attempt to lay out areas where the potential of machine learning can have great impact. TEE, anyone?

I’m off to the nearest academy to brush up my coding skills. And to TEE up a client!

Siddharth Pai is a world-renowned technology consultant who has led over $20 billion in complex, first-of-a-kind outsourcing transactions.

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