learning to learn

Learning to learn

NIIT Editorial Thu, 24/11/2016 - 18:30

New jobs require the ability to adopt technology, adapt to generating ideas, and derive innovation

Schools in Delhi will now teach “happiness” as a subject, and an upcoming private school built around that concept believes that the traditional academic systems are too structured to consider human values such as happiness. Nothing could seem more paradoxical. In an age where data and algorithms are said to be changing the paradigm of the workplace, machines may be bringing back true human values into our professional systems.

This new thinking is symbolic of the requirement of a human element in the midst of the precision that machines have been designed to bring into traditionally human-run systems. Is it time, then, to nurture the human mind for bigger and better things? As entrepreneurship, innovation and technology take the driver’s seat, the emerging jobs have a human, creative and technological touch, many of them demanding all three of those skills.

Replacement versus redeployment. If there are any doubts in your mind about whether or not automation poses a clear and present danger to the job market, it is because geographic and developmental indexes may have different answers. However, as automation is around the corner in countries with a high technological growth track (including India), here is the confusion-buster: While conventional jobs may indeed continue to exist, just as the bullock cart will co-exist with Bullet Trains, the size of conventional job markets will shrink substantially. But replacing those conventional jobs are newer ones that demand skills required to enable automation.

A look at the “jobs that have the highest possibility of being replaced”, according to an Oxford University report, tells us that many of the highly replaceable jobs involve the degree of precision that machines can bring better than humans. Many of those jobs already seem redundant: data entry operators, photographic processors, and so on. But some may surprise us: Telemarketers, for example, will find themselves bot-ted out, as digital and social media intervention will replace the pesty, persistent calls. A word of caution is warranted, though, as the report itself mentions. Rather than fading out, jobs facing automation may face “redeployment”.

Predictably, digitization and automation are responsible for the bulk of this shift: Cyber security, data science, digital marketing, business analytics and machine learning offer roles with hitherto unknown skills or those that need “redeployment”. Machine learning makes virtual assistants now learn continuously using artificial intelligence. With the introduction of robots and artificial intelligence (AI), machine learning is a reality. Yet, if the history of technology adoption is any evidence, the shift will be gradual enough for us to cope: Natural linguistic processing (NLP)-based inventions in the 1990s led to the modern virtual assistant, but look how long that took.

Human relevance through technology-ideas-innovation. We are familiar with education systems’ investment in technology and even in entrepreneurship in recent years. In March this year, China has pledged “more” investment in innovation-driven development strategies. A World Economic Forum report says that more than 35% of today’s skills will have changed five years from now. A KPMG- CEO Outlook survey gathers that 50% CEOs say their organization will be completely transformed within three years. Yet this transformation is not all about automation. It is about people!

If there is one requirement that is changing the very concept of human capital, it is innovation. This is a skill that requires exposure to technology, openness of mind, and ideas. Yet, education systems can provide platforms for innovation, but learning innovation remains a personal system because it entails the ability to learn rather than traditional subject learning.

I will use ‘innovation’, that much-used term, to mean the ability to adopt and adapt to. In the last few years alone, a few functions have emerged on top of the pile of skill sets required in a fast digitizing and technology-driven world. Around the world, these functions are enveloping many industries from the technology industries themselves to manufacturing, and sure enough, the threefold set of competencies—ideas, technology and innovation—is at a heart of many of these new roles:

  • Digital and social media marketing
  • Business analytics and data sciences
  • Storytelling using technology such as gamification

 

In addition, there is a heavy technology application to many of the other new jobs that have rapidly taken centrestage, including:

  • Cyber security
  • Big data
  • Machine learning

 

Skilling to learn. Re-skilling has become a buzzword for professionals these days, and several commentators have rightly emphasized the role of skilling for learning. In February, Nasscomm launched a platform to re-skill two million IT employees, focusing on the new-paradigm competencies that include focus on a variety of new technologies including artificial intelligence, virtual reality, robotic process automation, internet of things, big data analytics, 3D printing, cloud computing and social and mobile. Learnability and adaptability will be key to how we morph our skills into the future, and perhaps this is what India’s IT Minister Ravi Shankar Prasad meant when he told the Nasscomm gathering, “Even if a technology destroys ten jobs, it will create 100 jobs.”

So there is more than merely learning skills that matters. For example, how can a marketing professional put conventional wisdom while using technology and reaching new and old markets through digital media? What new skills may be required? The good part for professionals in conventional roles, of course, is that while digitization has brought a new communication paradigm, requiring tools and technologies that may be different, the old experience may come in very handy while re-skilling for new paradigms. For example, the automated use of big data and their bots-enabled mining triggers the very human skill of storytelling. Storytelling has not been on top of any school’s curricular agenda so far. Yet it reflects the kind of re-skilling that is needed in the market.

As a recent McKinsey report states, data size, qualitative decision-making, generalizability of specific solutions, and other human bugs such as bias will remain sticking points in automation based on deep learning.  That is why the three-pronged skill formula will remain at the heart of new roles in our world of tomorrow.

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