The Future Of Jobs: Are We On The Verge Of A Fourth Industrial Revolution?
The staggering pace at which technology has been evolving in the last decade or so has generated as much enthusiasm as it has generated fear and while some of us have chosen to embrace it, others have chosen to perceive it as a threat. Nevertheless, beyond the futurists with their almost divine-like powers and their claims to know how the future is going to look like and the pessimists with their dystopian and dark, bleak and almost apocalyptic-like predictions, there is a harsh reality that we have to deal with and some pressing questions that are calling for urging and almost desperate answers and they all boil down to one simple question:
Are we likely to find ourselves unemployed in the future?
While some experts claim that we are slowly being replaced by machines, others have already declared that we are on the verge of a 4th Industrial Revolution. The situation is, however, much more complicated than it appears to be and, while there is truth in both claims, it is important not to jump into alarmist conclusions. In times such as these, it is important to remain vigilant, forward-thinking and always ahead of the curb. A thorough understanding of this technological revolution and of the technological breakthroughs that are currently taking place are an important step towards gaining a better understanding of what is happening around us and keeping an edge that would allow us to adapt rather than be caught by surprise and left behind. It is therefore ever so crucial to look at the facts first rather than speculate.
Recent developments in advanced machine learning, artificial intelligence (AI), 3D printing, robotics, nanotechnology and biotechnology, among others, and the unprecedented speed at which they have taken place, meant that the reality of thousands, if not millions, of job functions being replaced by machines is becoming more and more imminent. While less than a decade ago it was only straight forward blue-collar, mechanical jobs that were being replaced by machines, we now see more and more white-collar, middle-management, jobs that are being replaced.
Nevertheless, it is important to remember at this stage that despite the fast and the furious recent advancements, the technology has not yet reached the level where machines are likely to outright replace us. What we are likely to see in the near future, however, is a slow and steady stream of technological breakthroughs being accompanied by a slow and steady stream of job losses in various sectors across the board.
An important player in the transitioning of labour dynamics is artificial intelligence. AI, however, has not yet reached the level of total autonomy required for it to no longer require human assistance. Advanced machine learning which ultimately leads to AI means that computers automate data processing by learning and adapting. Handling complex data sets requires deep neural nets (DNNs). DNNS learn by allowing computers to act autonomously and perceive the world on their own. Major advances in deep learning neural networks meant that AI systems are now able to perform tasks that only humans were able to perform in the past.
Machines still need human input but for how much longer?
Advanced machine learning still requires the need to be supervised. Supervised machine learning is by far the most prevalent type of artificial intelligence that is being currently used in business. Algorithms learn from training data that is being fed into the system. However, algorithms do not learn anywhere near as efficiently as human beings and although they have the capacity to process far more data than us; the process of collecting data used to be a laboriously long and costly process where not only the quantity but also the quality being processed played a major part in ensuring the efficiency of a machine learning algorithm.
In every domain that involves machine learning, it so happens that there are situations in which algorithms find it extremely difficult to perform well and that’s where the human contribution is required as we get passed on the processes and decisions that the machines can’t make which means that, as it stands, AI is currently replacing only parts of a job function as opposed to an entire job function. This may lead to jobs being lost in some cases but also to the creation of other job functions in some other cases which seems to suggest that we are at least safe in the short term. In the long term however things are likely to be much more different.
In fact, the only reason why most knowledge-based work was spared from the effects of AI in the past is the cost of building a machine learning algorithm which were extremely high. However, as companies no longer need huge budgets to use machine learning internally, things are about to take a radical turn.
In 2015 alone, IBM, Microsoft, Amazon, google and Alibaba, among others, all launched general purpose cloud machine learning which meant that many smaller scale businesses which couldn’t afford machine learning technology in the past are now in a position to. What this also means is that over time the vast majority of companies will have their big data processing needs met simply by finding the right tool or product on the market which in turn will lower the cost of producing application programming interfaces (APIs) and make it much easier for data scientists and developers to make fully machine learning APIs in the cloud.
AI-based face recognition technology is today almost as good as human capability. Watson, IBM’s AI system, learned everything from cooking to finance, medicine and even Facebook and can diagnose certain types of cancers better than any human doctor can do. In journalism, for instance, some business and sports news are already being written by automated systems and more and more journalistic tasks will be done by machines as algorithmic journalism is getting better and better.
According to The World Economic Forum (WEF) which took place in Davos from the 20th to the 23rd of January of this year and the ensuing report published in the same month, artificial Intelligence and machine learning are expected to have a negative employment impact on Education and Training, Legal and Business and Financial Operations. The timeframe provided by the report estimates that the impact of AI and advanced machine learning will be mostly felt between 2018 and 2020, reason being is that these technologies will not have advanced significantly enough by the year 2020 to have a more widespread impact on global employment levels. This, however, does not exclude that their impact will be felt even further and across most sectors beyond the year 2020.
It is estimated that a total loss of up to 7.1 million jobs will occur over the 5 year period between 2015 and 2020 and that only 2 million jobs will be created over that same period, leading to a net total of over 5.1 million job losses between 2015 and 2020. A strong employment growth is expected across Architecture and Engineering as well as Computer and Mathematical jobs versus an average decline in Manufacturing and production jobs twinned with a significant major decline in Office and Administrative jobs.
A staggering 5.1 million job losses predicted over the period 2015-2020.
The sectors that are likely to be mostly impacted by this transition are The Energy, Infrastructure and Mobility sectors due to new energy supplies and emerging new technologies. The Financial and Professional Services sector and the Information and Communications sector will be mostly hit by big data and power processing and while forecasts vary widely between industries and regions, it is largely accepted that imminent changes are on their way. The most significant impact is, however, at the level of job families or job types as it is becoming more and more obvious that where the impact will be mostly felt is at the level of certain job categories such as office and administrative jobs; manufacturing and production; construction and extraction; arts, design, entertainment, sports and media; legal and installation and maintenance jobs.
In fact, computing power and Big Data analytics are expected to be the biggest driver for change and will constitute a major driver of employment growth in the next few years. Computer and mathematical jobs are expected to experience a very high growth mostly around data analysts and software and applications developers not only in the Information and Communication industry but across a wide range of industries including financial services media, entertainment as well as mobility and professional services among others.
Notwithstanding the industry and/or drivers for change, it is pretty obvious that the overall pace of industry transformation is not only staggering, to say the least, but also wholly unprecedented and these changes are not only disrupting the various industry sectors but also re-configuring business models and overall skill sets as a whole. Such changes are not only set to continue but also to carry on evolving at an even more accelerated rate over the next 4 years and appear to be a major driver for concern among HR professionals, scholars, academics, business leaders and policymakers alike. This unprecedented transformation has been described as a “Fourth Industrial Revolution”.
Are we truly on the verge of a 4th Industrial Revolution?
The WEF report which is an attempt at identifying these drivers for change and getting to grips with their current and future impacts on employment levels, skill sets and recruitment patterns across industries around the world, not only validates the impact of technology on global employment trends but also highlights that the world is, in fact, “on the cusp of a Fourth Industrial Revolution”.
A major point of contention here is that even though previous industrial revolutions have improved living standards for the masses of ordinary people in the long term, the majority of the consensus is that the bulk of the population that was at the bottom of the social scale suffered severe reductions in the quality of their life. In fact, it is today an established historical fact that, in the short term, for the majority of the overall population, living standards did not grow meaningfully until the late 19th and 20th century and that in many cases, workers’ living standards even declined under early capitalism.
It is therefore imperative to start taking action now if we want to ensure that the transitioning period does not bring further mayhem and disruption and while there is currently a call for action for industries and businesses to start making the necessary adjustments to the new and emerging business models and skill sets, it is also our responsibility to start taking the necessary actions, at a personal and professional level, that would enable us to adapt and transition safely.
A total rethink of industries, business models and hiring procedures is not only required, but probably already under way for, in fact, the companies, businesses and organisations that will know how to use this technological revolution to their advantage will get a huge competitive edge and are, as such, quite incentivised to take whatever actions necessary to better manage the transformative impact of this fourth Industrial Revolution on both skills as well employment, not to mention education.
As such, as individuals, we need to gain a thorough understanding of these changes, their drivers as well as disruptive impacts on business and economic models, evaluate our current and future options in the current as well as forthcoming labour market and try as best as we can to anticipate skills needs, recruitment patterns and occupational requirements which, I appreciate, may be a bit of wild guess at times. Predicting future needs and understanding current changes or drivers for change will allow us to make informed decisions about our future options rather than merely speculate on what, when and how the axe is going to fall. The next crucial steps, depending on the actual context, would to up – skills and/or re – skill or merely opt to choose a new career path.
Given the way things are heading, there is a real call for us to keep learning and developing. Keeping ahead of the curve, means being one step ahead of the technology and given how fast it is developing, well… we’re in for a ride! A personal observation, if I may, is that, often enough, quite a lot of middle-management and at times even senior management professionals get so complacent and do stop making efforts at reading, learning and keeping themselves up to speed with all the developments around them, especially when it comes to technology, a pet hate of a lot of managerial professionals, well… those times are over! No one is safe and they can no longer hide because change is coming and it is coming fast.