Careers in the age of Machine Learning, or What do I tell my 15 year old?

In the age of machine learning and robotics, it is not only the future of work that is in the balance. The very meaning of a career must be reimagined.

I have been amazed by the number and variety of people concerned with this issue. Old friends discuss it over dinner, it’s one of the first topics broached with strangers on planes, and executives raise it in the context of both their workforce and their family.

Two groups feel most affected: those in the middle of their career whose work will be made redundant and for whom retraining and finding new work will be difficult. And people not yet in the workforce wondering how best to prepare for the future. A future that no one can sufficiently describe to make them feel confident about their choices.

First the good news.

A career should take many paths — and platforms

Those of us who have been working for many years thought of our careers as a vector. For me, it was a fairly simple linear process in the academic world from PhD to Professor to Dean.

Yet my two most interesting roles were not on that vector. Neither being Founder and CEO of Duke Corporate Education, nor my current role as PwC’s Global Leader of Strategy and Leadership were natural steps on the ladder. Yet it’s those roles in which I’ve learned the most and had the most fun.

This non-linear, platform approach to a career is becoming the norm. A platform in this context is a collection of problems that require a specific set of capabilities to solve. So, rather than being responsible for a larger team and bigger budget every few years, people will take their unique set of skills and apply them to new domains in creative ways. Thus, careers will be made of moves from platform to platform, rather than steps on a ladder. The goal is to find a good platform; one that is rewarding, where you are stretched and develop, and which opens up a host of new possibilities for when the time comes to make the next move.

Some people skills will always be in demand

What will people always want from people, as opposed to machines? Empathy, connectedness, experience, imagination, integrated advice and clear values. Or, more simply said, humanity. In the future, performance reviews, compensation models, and job markets will need to adjust to emphasize these points, rather than the technocratic elements. This is similar to the mental adjustment that was required at the time of industrialization — except that we have much less time because these changes are coming at us at an increasing pace.

Now the caution: the ability to maximize the upside will depend on where in the world you are and how far into the future you are looking.

First, the pace of innovation and the sophistication of the existing technological infrastructure varies around the world. This can’t simply be divided into “developed” and “developing” nations: think of South Korea or Singapore as examples of countries traditionally classified by the UN as developing, but doing an outstanding job building a sophisticated technological base for their growth. Countries also vary in terms of their maturity of technology use, in quality of education, money to invest, and support for new business. Nations in which technology is still behind the world average will need a large number of engineers and computer scientists to aid in the catchup, but the nature of innovation means that this catchup process will be accelerated.

Second, in countries with aging populations — such as Germany which has a median age of 46.8 — the biggest opportunities will be different than countries where the age is much younger, such as Nigeria at 18.3 years. In aging countries, the proliferation of breakthrough technologies is additionally incentivized by the decline in working age population. This means work in AI and robotics will be on the rise as well as healthcare and leisure. At the same time young countries will face the need to address massive youth unemployment in an environment where cheap labor slows down the pursuit of automation.

When these two factors are combined, it might be that countries like China will benefit the most: their population is aging at the same time that it is migrating to value-added businesses, with supporting capital, a great school system and an evolving new business ethos. Yet even China will have to deal with the global phenomena that will cause thousands, if not millions, of people in low skilled manufacturing jobs to be replaced by robots.

Finally, we need to admit that we don’t know enough to be able to focus our response long term. So, while we can assume STEM roles will be very important for the next decade, they will become less so as computers write their own code, run experiments, do primary analytics and adapt as they learn.

So what should you tell yourself and your children? Focus on your ability to continuously adapt, engage with others in that process, and retain your core sense of identity and values. For students, that argues for studying a broad array of disciplines so they develop the skill of learning, as much as they retain the specific content. And for the rest of us, it suggests that intellectual complacency is not our friend and that learning — not just new things but new ways of thinking — should be a life-long endeavor.

For more insights into forces radically reshaping the world of work and into skills needed in the future, please see PwC’s new report “Workforce of the Future: the Competing Forces Shaping 2030.”