In an age of rapid technological advancement, is a single career for life realistic? (A-level GP exam 2018)

Picture: The University of New Orleans

By Steven W.S. Ooi
Former GP tutor

Even as United States president Donald Trump blames illegal immigrants and unfair trade deals for causing Americans to lose their jobs, a new presidential candidate, Andrew Yang, has offered a very different narrative. It is robots and artificial intelligence (AI), he argues, that have robbed Americans of their jobs, and will continue to do so in the future. Mr Yang is not alone in his view. In 2013, an influential report by Oxford University claimed that 47 percent of US jobs are at risk from AI and automation over the next 15 or 20 years. While predicting the future is a notoriously tricky enterprise, it is safe to say that a substantial amount of human capabilities will be made redundant by the exponential rate of advancement in technology in the Fourth Industrial Revolution now taking place before our eyes. We need to be prepared to learn new skills constantly throughout our working lives and, for many of us, to lose our jobs and reinvent ourselves several times. For the purposes of this essay, a career shall be defined as an occupation undertaken for a significant period of a person’s life and with opportunities for progress. It is this writer’s position that a single career for life remains a reasonable possibility in some professions and circumstances, provided an individual is willing and able to learn continuously and adapt to changes brought by technology.

Technological innovations will make some human skills less relevant, and others more relevant, by 2030. In the first category, many jobs will be taken over totally or partially by technology. A study by McKinsey has projected that physical and manual skills will see a fall in hours worked in the US and Europe from 203 billion hours in 2016 to 174 billion by 2030. Lower-order cognitive skills such as basic data input or basic data processing, too, will see a decline in employability. On the other hand, the demand for social and emotional skills, together with technological skills and higher cognitive skills, will grow. Hours worked in the US and Europe using technological skills will burgeon from 73 billion to 113 billion, also by 2030. This data suggests that numerous workers will need to cast aside their old job descriptions to perform very different tasks, in many cases taking on a totally different role. For instance, an administrative clerk performing rostering for airline pilots may find his work taken over by AI, necessitating a shift into the work of operating the AI program, thinking of ways to make it work better and applying insights derived from the data collected by the AI – in other words, acquiring higher-order cognitive skills such as creativity, problem solving and complex information processing. Jobs that revolve around skills that are easily automated will be readily destroyed by AI. If workers insist on a career for life in these professions, they have an excellent chance of finding themselves in the unemployment line.

Be that as it may, those skills that are difficult to automate will likely remain in demand for the foreseeable future and jobs that revolve around such skills will in all probability remain intact or even grow in demand. AI may exhibit superhuman performance at tasks relating to a specific problem or application such as playing Go or poker or recognising images after being trained on a specific, diverse, massive dataset. However, it is very weak at interpreting data that differs from its dataset. For instance, Google Translate works on neural networks that are trained on billions of lines of parallel texts in different languages, translated by humans. When one keys in text that corresponds to those prelearned lines, it performs extremely well. But if you try feeding it something other than that, for instance a creative turn of phrase, it produces hilarious results. AI is also not noted for its higher-order cognitive skills such as inventing something new or empathizing with people; invention is likely to remain beyond the ability of a machine that can only perform based on processing what it is told, while human experience is so complex and diverse, with so many variables interacting with one another, that it would require an almost infinite amount of data to teach a computer to reliably produce accurate empathic responses. Hence higher order cognitive skills are, and will probably remain difficult for technology to replicate. Professions that are centred on such skills will be resilient and it is quite realistic to have a career for life in such fields, for instance counsellors, teachers, nurses and interpreters.

Granted that technological adoption may add to the requirements and demands of such jobs, and many of those who hold them will need to acquire these technological skills to remain employable. For instance nurses may need to master various computer programs and medical machinery installed by their hospital. If, however, these practitioners can stay abreast of technological applications in their field of work, they should be able to remain in their careers for life. A solid grounding in science, technology, engineering and mathematics (STEM) will be essential for most working people in the era of Industry 4.0 – especially if they hope to achieve longevity and upward mobility in their chosen careers.

It also needs to be acknowledged that a powerful trend catalysed by technology – outsourcing – is profoundly altering many industrial corporate structures in such a way that have destroyed or decimated traditional career paths. Many established industrial companies such as those in steel, automotive, energy, IT and manufacturing have outsourced many of their business processes and large parts of their value chain. An example in manufacturing would be Philips – which engages contract manufacturers in places like Mexico and China to produce many of their products – and one in IT would be IBM, which outsources tech support, research and development (R & D), and more to India. Gone are the days when these firms would offer a 30-year “lifelong career” to fresh university graduates. In fact, Deloitte has found that only 19 percent of companies still offer traditional, multi-decade functional career models. Many, such as AT&T and IBM, are devoting themselves instead to helping employees continuously reskill and move horizontally within the organisation. New kinds of hybrid jobs are constantly emerging, such as data scientist and user experience designer, as technical skills become commoditised and easily outsourced.

However, if the only constant is greater rapidity of change, then those who excel in keeping up with, driving or managing change will always be relevant. Top-notch R & D engineers will always be valued by an organisation. Outstanding managers who understand how to motivate people and strategize for a team in a dynamic environment will always be crucial to a company. And as corporate structures are adjusted, dismantled and reassembled in the Age of Acceleration, management consultants will only be increasingly needed to help companies to make optimal changes and make transitions successfully with guidance from research into the experience of other organisations. In an age of change, a career for life is still very much viable for those whose forte is change itself.

All said, I maintain my view that in the era of jet-heeled technological development, a single career for one’s entire working life, while elusive for many, remains a realistic aspiration for a good number of people in professions that are difficult to automate or which specialise in the process of technology-driven change itself. Amidst the constant hype about transformational technology replacing humans, I still believe that the human being is the greatest machine. Yes, a robot can beat us in some single, narrowly focused tasks like chess but it cannot yet handle a multifaceted job like doing all the housework, raising a child, running a government, managing a team, writing a screenplay – or for that matter, scoring an A for a General Paper exam. The complexity of programming for it to handle any of these things is mind-boggling and the evidence after many years of IT and AI research does little to suggest that man-made technology will ever be able to catch up to man in these multidimensional capabilities.

©Steven W.S. Ooi 2019. All rights reserved. No part of this publication is to be reproduced in any form without the prior written consent of the author.


Steven Ooi, a First Class Honours grad from NUS, retired from a 14-year career as a GP and English tutor in 2016. He continues to blog on issues of concern to General Paper and student life.

To view tutors recommended by him, click here.

More GP model essays here.

About gptuitionsg

A dedicated English and GP tutor with First Class Honours from the National University of Singapore, Steven Ooi retired from the profession after a 14-year career during which he was one of the most sought-after private tutors in Singapore. He is the recipient of the Minerva Prize from NUS, which is awarded to the top English Language honours student of each cohort. This website, which has consistently ranked among the top 10 on Google and has received over 530,000 hits, has now been converted into a GP resource site cum listing of recommended tutors. If you are a GP or English tutor who wishes to be listed here, please email Steven Ooi at stevenooi18 @ (remove the spaces). Interested parties will be assessed and interviewed by him, and qualifications will be checked. These procedures are necessary to uphold quality standards. DISCLAIMER: While every reasonable effort has been made to assess the competence and verify the qualifications of recommended tutors here, no guarantees are made and you engage them at your own risk. By using this website, you agree that you will not hold the webmaster Steven Ooi responsible for any consequences — direct or otherwise — that occur in relation with your use of this website.
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