What do experts have to say about the potential effects of robotisation and automation on the Hungarian labour market? Urgent reforms of the education system would be crucial for adapting to rapid technological change.
“You are very ambitious, Mr Lee, but just imagine the impact your invention would have on my subjects. It would certainly ruin them by taking their jobs and making them beggars,” allegedly is what Queen Elizabeth I told William Lee, the inventor of the knitting machine in 1589 when he applied for a patent. As this anecdote demonstrates, the fear of job losses in times of technological change is far from being a new phenomenon.
Prior to the First Industrial Revolution, no one could imagine the economic benefits the knitting machine would bring to people’s lives, as it was easier to predict how many jobs would be lost than how many new occupations would be created.
Today we are again witnessing such a transformation, the Fourth Industrial Revolution, and just as few hundred years ago, no day goes by without a new alarming prediction about how machines will take our jobs and how people will become redundant.
Last year, a World Economic Forum report asked executives around the world how will automation change their companies. What they found was startling: though in 2018 working hours were divided 71 to 29 per cent between people and machines respectively in existing jobs, this ratio will decrease to 58 per cent for people and will grow to 42 per cent for machines by 2022.
Harder, better, faster, cheaper
In one of the most frequently cited studies, two scientists from Oxford University examined the likelihood of people being replaced by robots or algorithms in 702 professions. Carl Benedikt Frey and Michael A. Osborne analysed the American labour market and concluded that machines will likely replace 47 per cent of these jobs.
The Oxford researchers divided occupations into four categories: routine, non-routine, manual and cognitive. Manual (for example assembly line work) and cognitive routine jobs (such as routine office work) can be replaced with machines, as workers in these occupations follow clearly defined basic rules and perform repetitive tasks, exactly the type of work that can be easily programmed.
Not too many years ago researchers believed that non-manual routine and non-routine cognitive tasks will be very difficult to replace with algorithms. Driving or handwriting recognition, for example, just seemed to be too complex tasks for machines.
Fast forward to the present day and you find that every major car manufacturer is working on its version of the self-driving car, and algorithms can recognise handwriting with nearly a hundred per cent accuracy.
This means that not only assembly line jobs are susceptible to automation, but also jobs that require complex skills and knowledge. Ever-cheaper and better sensors, exponentially growing computing power and big data empower machines to recognise patterns and to solve complex tasks more accurately, way faster, and in the long run, much cheaper than humans.
For example, British researchers recently have concluded that machine learning can analyze cardiac MRI scans in four seconds, whereas it takes an average of 13 minutes for specialists. Another example is JPMorgan. The New York-based investment bank has been using machine learning to sort legal documents for years since the algorithm does the job in seconds that would take 360,000 hours for legal assistants.
I interviewed several experts on whether the Hungarian labour market was ready for the fourth industrial revolution. Szilárd Molnár, President of the Zoltán Magyary Association of E-administration Sciences, warns that “49 per cent of the working hours of Hungarian workers can be automated. In other words, automation will have a significant impact on one million jobs in Hungary by 2030. According to PwC, automation can reduce factory jobs by up to 25 per cent, transport and warehouse jobs by up to 22 per cent, and administration jobs by 18 per cent.”
Júlia Varga, a Senior Research Fellow at the Institute of Economics of the Hungarian Academy of Sciences (MTA) thinks that eventually, robotisation will be a question of price for German car manufacturers that have production plants in Hungary.
When robots become cheaper than Hungarian workers, these companies will make the step to robotise their production to stay competitive – she told Visegrad Insight.
According to Annamária Artner, Senior Research Fellow at the Institute of World Economy of the Hungarian Academy of Sciences, low labour costs can provide some protection against automation in Hungary. But as they say “low wages support workers like the gallows supports the man to be hanged” – the MTA researcher added.
It all starts in the schools
In the long term, a lot depends on the education system’s ability to teach students skills that robots and algorithms cannot compete with. According to experts we talked to, these include creative and social intelligence, collaboration, problem-solving, analytical thinking, experimentation and initiative.
We know from the international PISA surveys that Hungarian students are lagging behind in these areas, and they only perform well in tests that measure lexical knowledge. This is alarming since it doesn’t matter how much data students can memorise, they just can’t compete against machines that process huge amounts of information at the speed of light.
Adult education will also have a crucial role to play since a large number of people are expected to look for a new profession.
According to a report by the World Economic Forum, 54 per cent of workers will need retraining due to digitalisation and automation by 2022, but companies will only be willing to pay for retraining costs for employees who are already doing well. That is, those who are less capable of creative, critical thinking and complex problem solving will likely be fired. Based on this, Hungarian workers are in a particularly vulnerable position.
According to Miklós Illéssy, Research Fellow at the Center for Social Sciences (MTA) there has been a significant decline in the creativity of work tasks in Hungary between 2005 and 2010, and the situation has not improved since 2010 either. This means that it is less and less necessary for an employee to solve a complex task, to learn new things, and to assign his or her own tasks.
Illéssy trusts that common sense and wisdom will help to mitigate the negative social impact that technological change may have. It may be encouraging to know that during previous industrial revolutions the number of jobs created outweighed those that were destroyed. But how long will it take for Hungary to adjust, and how painful will it be? If education policy continues on the current track, it is difficult to be optimistic.