Select Page

The workforce crisis of 2030 is already here

The idea that someone or something will come along and “steal our jobs” is nothing new. It seems to be a cyclical symptom that is deeply rooted in our fast changing society and it’s evolving technology. However the concept that change leads to lost jobs is perhaps too simplistic a view to take.

Rainer Strack gave an absolutely fascinating TED talk back in 2014. He predicted many of the world’s largest economies will have more jobs than adult citizens to do those jobs. He explains this shortage by delving into plummeting birth rates as well as discussing the rise of A.I. and automation. He argued that although some jobs will become redundant through technological progress, this will lead to the creation of new jobs in new fields that we can not yet imagine:

So does Rainer’s vision hold water? In my opinion, it most certainly does. Having worked in both recruitment and HR for over a decade, I can attest to the fast changing global employment landscape. In my line of work, it is all too common for veterans to notice the comings and goings of employment trends, largely dictated by technological progress, social and geopolitical trends. Having worked in smaller countries such as Switzerland and the UK, I am all too familiar with labor market skills not catching up to labor demand. A timely example is the current imbalance in the UK’s Cyber Security labor market. Following a recent report by the Department for Digital, Culture, Media and Sport (DCMS) Rahul Powar comments:

While he regards the increase in cyber security employment found by the governmental report as “a vital boost for the seemingly impossible task of plugging the current 4 million shortfall in cybersec professionals”, Red Sift CEO Rahul Powar says that research should delve deeper into movement between specific industries.”

Rahul Powar, 2020

Not only would I say Rainer Strack is correct about the impending workforce crisis in 2030, I would argue that it has already started.

Artificial Intelligence vs Machine Learning

There is a lot of confusion around some of the technological buzzwords we hear floating around these days. For instance, people often use the words “Artificial Intelligence” and “Machine Learning” interchangeably. But do they really mean the same thing? Let’s define them:

When a machine performs tasks using a set of defined rules to solve problems (algorithms), we call this “intelligent” behaviour artificial intelligence or “AI”. Machine or “ML” is a subset of artificial intelligence. It is a technique for realizing AI or, to put it another way, training algorithms such that they can learn how to make decisions autonomously. This is achieved by giving lots of data (think “Big Data”) to the algorithm and allowing it to learn more about the processed information.

According to the latest forecasts and market estimates from Forbes:

Open jobs requiring TensorFlow experience is a useful way to quantify how prevalent machine learning is becoming in business today. There are 4,134 open positions in the U.S. on LinkedIn that require TensorFlow expertise and 12,172 open positions worldwide as of today. Open jobs on LinkedIn requesting machine learning expertise in the U.S. further reflect its growing dominance in all businesses. There are 44,864 jobs in the U.S. today according to LinkedIn that list machine learning as a required skill, and 98,371 worldwide.   

Roundup Of Machine Learning Forecasts And Market Estimates, 2020 – Forbes.com

No matter what industry you are in, chances are the use of artificial intelligence leveraged by machine learning is going to dramatically change not only your sector, but your work environment as well. This revolution will not only require technically skilled people to implement it but will necessitate leadership and management to understand why they need it, how to leverage it and finally, what deploying it entails.

So no matter what your job title, understanding what artificial intelligence and machine learning are will be critical in the coming years. A great place to start is a short online course provided free by the University of Helsinki (no affiliation):

In spring 2018, Reaktor and the University of Helsinki came together to help people to be empowered, not threatened, by artificial intelligence (AI). Together they built the Elements of AI course to teach the basics of AI to people from a wide range of backgrounds.

You can sign up for the course on the “Elements of AI” website absolutely free. You even get a certificat upon completion.