"They said Ned Ludd was an idiot boy, that all he could do was wreck and destroy, and he turned to his workmates and said: Death to Machines, They tread on our future and they stamp on our dreams" - Lyrics of a song by Robert Calvert

Ned Ludd was a textile worker in the 18th century England. He was a regular fellow, just like you and I, who happened to like his job. In fact, he loved it. So, when the industrial revolution brought forth inventions like automated textile equipment, his job was threatened like never before. One day, in what was described as a "fit of passion", Ludd smashed two mechanical knitting machines to the ground, and thus began the rebellion of Luddites.

Luddites were British weavers and textile workers who objected to the increased use of automated looms and knitting frames. But today in our pop-culture, “Luddite” is a term with a rather infamous meaning - people who fear new technology.

Ned Ludd’s story perfectly sums up the viewpoint that as long as machines have existed, economists and workers alike have feared that they are making humans obsolete. Just as previous industrial revolutions threatened jobs and livelihood with technology, the “fourth industrial revolution” is making a case for replacing humans with more efficient algorithms and automation at the workplace.

The Future is Now

As technologies like Cloud, IOT, AI, and Big Data continue to grow, the role of machines as “tools” to increase productivity is fading. Instead, machines are becoming workers. Take, for instance, Amazon’s Kiva robots which can plan, control, and navigate to fill warehouse orders four times faster than their previous system. Or IBM’s Watson which processes up to 60 million pages of text per second and produces medical diagnoses and treatment recommendations. Or The Grid, an AI website design platform where ”AI websites design themselves.”

The future is here now and it’s uncertain. It’s even more disturbing when you think about what machines can take away from you. For instance, a blend of AI and big data analytics can help computers “learn” how to create and curate content that’s tailored for lakhs of individual customers - something a marketer can never do. If you think I’m wildly exaggerating here, this is what our esteemed ex-RBI Governor had to say about automation:

“The emerging threat is it’s not the guy in Bengaluru but the robot next door who’s going to take your job.” - Raghuram Rajan

And if your job requires repetitive work, more bad news for you. A study found, India's IT services industry will lose 6.4 lakh "low-skilled" jobs to automation in the next five years. It defined low skills as those that follow a set of process and are repetitive. Obviously, a bot can handle such work better than you without breaking a sweat.

To understand how industry and startup ecosystem view the upcoming era of automation, I asked Kevin Freitas, Head of People Operations at InMobi, for his opinion.

“The largest play for automation will be in manufacturing and heavy industries. In services industries, artificial intelligence is still progressing and has not yet reached the potential of perfect human interaction, though the success rate and error rate is improving.” - Kevin Freitas

To give you a glimpse of the future - ICICI has made a move to automation to handle 20% transactions by March next year and Raymond is set to replace 10,000 human workers with robots in next 3 years.

A Faulty Skill-Set

While automation may cast a scary shadow on jobs, we have more pressing issues at home. According to a report only 17.91% of Indian engineers were employable for the software services sector, 3.67% for software products and 40.57% for a non-functional role such as BPO.

Additionally, the skill gap in our young workforce was never clearer than when 19,000 graduates applied for 114 vacancies for sweepers in Amroha, UP this year. That’s as shocking as a statistic can get. And when you combine this skill-gap with automation, it’s not hard to imagine the blow on our workforce.

The Magic You Need

Not all is lost. In fact, history shows us that advances in tech don’t decrease jobs over an extended period. As the workforce adjusts their skills and entrepreneurs explore alternatives based on the new technologies, the number of jobs rise again.

Kevin shares similar sentiments about automation. “It's not an immediate threat to jobs, as the pace of automation will not outstrip the pace of employment generation opportunities in the short term (5-10 years). In the long run (by 2040), it is best for talent to move to higher value jobs that require discretion and judgement.”

Therefore, as long as the computational power grows, many jobs are going to be redefined rather than destroyed. Our best tools for future are going to be upskilling and reskilling.

So, what can we learn to thrive and secure our career insurance, say, in 2020?

Speaking from a tech perspective, skills that will see high demand and lucrative salaries in the future will be the likes of Big Data, Analytics, Mobility, Design, Machine Learning, IoT, and AI.

Why? Well, when everyone with a smartphone and an internet connection is bent on shooting infinite data into the web, it becomes almost impossible to make sense of it. Yes, your Instagram, Snapchat stories, and Youtube broadcasts count. And that’s the battle today’s tech communities are fighting. To make sense of this data. To learn from it. And finally, code that learning into machines (e.g. driverless cars).

Demand for data scientists and software engineers in machine learning, natural language processing and computer vision is already far exceeding the supply, both in India as well as abroad.

Meanwhile, the scale of adoption of these technologies is still in its nascent stage, but their impact is proving invaluable. To present a few examples:

Google’s Deepmind can now read lips better than humans. Machine learning is such a strong aspect of Deepmind that it can also play and beat different video games. If you think about it, it’s a machine that just woke up, had no knowledge of any particular game, learnt all of it on its own, and beat more than 30 different games.

Similarly, IBM watson can now read a physician’s notes just like any doctor and figure out, for instance, whether a patient has heart failure. It uses a machine learning algorithms to comb through physician’s free-form text notes and synthesize the text using NLP.

National Information Communications and Technology, Australia is working on the bionic eye. They're trying to help people who are losing their eyesight, using AI and computer vision algorithms.

Closer home, startups like niki.ai are building AI powered chat bots. Niki understands human language in the context of products/services the user would like to purchase, guides her along with recommendations based on her preferences and completes the purchase with in-chat payment.

Kevin, with his HR leadership experience at two of India’s top companies in InMobi and Flipkart, offers the following advice to young professionals.

“Employees and college students will also be well served by staying current by building their expertise in machine learning and NLP. If we learn and understand how machines are learning, we will always be a step ahead of 'machines', because our decision libraries are way too advanced currently for machines to catch up to within the decade. But, this will also help everyone benefit and be prepared for the tides of change that are gradually building strength in different industries.”

In a future where machines co-exist with us, it’s not hard to carve a place for ourselves. The world needs people who are capable of more big-picture thinking and a higher level of abstraction than computers. By combining human ingenuity with raw computing power, we can create a workforce more productive than ever.

And in this future, if you find yourself stuck in a lifeless job, remember - Learn, Relearn, Repeat.

Notes:

A version of this article was originally posted on Tech in Asia.

Thanks a lot to Kevin Freitas of InMobi for his valuable inputs!

I run Instahyre, a new age career platform where the top 2% of talent and companies meet each other. Our data-science algorithms match candidates with just the right jobs. So as a job-seeker you, no longer have to get spammed for irrelevant jobs, while companies get a curated list of talent. Check it out here!