Let’s talk about future
Mr. Krzywdzinski, at the moment, the debate in the media vacillates between paradisiacal ideas à la “The need to work will end!” and horrific scenarios like “Machines will take control of humans!” What are your personal views of the future world of work?
The debate about this is imbued with way too much drama. I personally do not believe that in the future we’re all going to be lying in hammocks or that we’ll be seeing a major wave of unemployment in industrialized countries. Technological change has always existed, just like the discussions about it. Productivity gains due to machines primarily mean progress. It started with the industrial revolution in the 18th century. Then there was Henry Ford, and now we’ve been experiencing the digital revolution for a few decades. Naturally, this has the effect of machines being able to handle more and more of the things that humans do. At the same time, employment has continually increased because the economy has kept growing, too. Especially in the industrial environment, the level of automation is high – even so, we’ve been seeing record employment rates across the value chain in this country in recent years.
About Dr. Martin Krzywdzinski
PD Dr. Martin Krzywdzinski is one of seven directors of the Weizenbaum Institute in Berlin and head of the Globalization, Work and Production research group at the Berlin Social Science Center (WZB). He holds a PhD from FU Berlin and obtained his habilitation in sociology there. He is co-director of the “Good Work” doctoral program at the WZB and member of the international automotive research network GERPISA steering committee. He’s also a board member of the industrial and labor sociology section of the German Sociological Association.
A frequently cited study by Oxford University analyzed the probability of automation for a range of different jobs. What’s your assessment of such predictions?
You always have to interpret such studies with caution. This particular one was primarily focused on the fraction of routine activities in occupations that were evaluated based on job descriptions. This resulted in the conclusion that the higher the routine fraction of a job, the higher the alleged risk of substitution by automation. Whether or not companies will actually opt for such substitution is a different question. For instance, it depends on how much an automation project would cost. Forecasts like this one do not consider this aspect at all. Obviously, some job profiles are going to disappear. But so far the past has always shown that major technical game changers resulted in all-new job profiles – including new skill requirements. Consequently, there’s a shortage of specialists in many sectors today. At the same time, such periods of change obviously raise the question about who will tend to be disadvantaged. The modern logistics centers of online stores are such a negative example: Warehouse workers often perform standardized jobs there that require no skills and are poorly paid. Nobody can bear up to that for a long time.
What technologies are changing the way we’ll be working in the future?
There are many examples. Technology is coming into closer touch with humans, for instance in the form of wearables such as data glasses. Enhanced models make this technology viable in areas like remote maintenance and logistics. At the same time, some pilot projects fail simply due to lack of employee acceptance – whether in terms of operability, wearing comfort, display resolution, or battery runtimes. In any event, there’s still plenty of potential here and questions of data security have to be resolved. 3D printing is another field. In this case, the optimism of companies varies, depending on the markets they serve. Although large-volume production by 3D printing is not feasible yet, the technology can replace and optimize manual routines in activities like rapid prototyping, so that concepts and ideas can be realized faster.
Lifelong learning has long ceased to be a buzzwordMartin Krzywdzinski
How can the workforce across all hierarchies keep pace with technological change?
It’s not enough for companies to just recruit top talent and to buy skills externally. They also have to tap into internal resources and offer their employees opportunities and room for dealing with data-based technologies and gathering experience. Anyone working with artificial intelligence should be able to judge according to which principles it works. HR departments have to bring together diverse skills for this purpose. The learning architecture should pay attention to an interdisciplinary alignment of skill profiles. For instance, the combination of classic engineering knowledge in the field of automation with modern approaches to software development is becoming increasingly relevant. Moreover, it makes sense to think about alternative development paths that may subsequently lead from maintenance or tooling functions to software development in order to contribute appropriate know-how. In this area, I’m still seeing a lot of room for improvement with the majority of German companies. Plus, young employees in particular will have to be prepared for the fact that “lifelong learning” has long ceased to be merely a buzzword.
How can companies promote acceptance of change among their employees?
If everything in the wake of digitalization just revolves around speed, efficiency and the intensification of work, this automatically results in resistance and the previously praised efficiency gains are lost. Let’s face it, digital transformation hinges on acceptance by the entire workforce – not only by young, digitally savvy employees. After having worked as a machine operator at a factory for forty years, it’s only natural that I’ll initially perceive digitalization as a threat. On the other hand, new tools can broaden one’s own horizon and replace tedious routines. It’s necessary to embrace change and, in the best case, be involved in shaping it. But that’s easier said than done.
Digital transformation hinges on acceptance by the entire workforceMartin Krzywdzinski
As a result of digitalization, many things can be done at locations other than one’s regular place of work. Jobs are being flexibilized. Will the importance of the office tower decrease?
The organization as the social connecting link is still in vogue. There’s nothing more important in daily working life than personal exchange. The fact that the workplace and its design are receiving a different quality with short business channels, less silo thinking, and optimal means of communication for cross-functional and cross-location exchange is a positive development. The reason for Silicon Valley’s success for instance lies in the fact that people seek to be in close touch with and talk to each other. We’re seeing this in the new work methodology in software development, experiencing it in small start-ups, as well as in small and medium-size companies, but not yet in all large corporations.
In day-to-day work, algorithms and machines are increasingly taking over decision-making processes. Are we progressively moving down the chain of command?
I’d caution anyone to have too much faith in technology – most machines and algorithms are not as intelligent yet as we always assume them to be. Most of the things we delegate to them are routine tasks. However, algorithmic assistance systems are gradually beginning to play a part in more complex decision-making processes, for instance in HR recruiting using diagnostic tools. Plus, in the future, there’ll be fewer checking and control processes by humans. Systems in industry such as predictive maintenance and condition monitoring automatically detect problems and reduce defects. However, the higher-level tasks of process control, communications, coordination and improvisation cannot be delegated to machines. In aviation, for example, many systems today are already running autonomously but especially the most recent air disasters have shown that it will continue to be necessary for pilots and air traffic controllers to keep an eye on everything and be able to intervene in critical situations. We should therefore look at algorithms and machines as tool, but not believe that they can make entire decisions and ultimately even think for us.
40 % of all new jobs
created between 2005 and 2016 were in areas with high levels of digitalization. The problem: 6 in 10 workers worldwide do not even have basic computer skills. This is another divide showing that continuous education is an increasingly important admission ticket to the labor market.
Will the day come when humans are able to view robots and AI as equivalent colleagues – or even accept them as bosses?
We tend to ascribe human traits to machines and programs in order to humanize them, but robots and cobots only execute what they’ve previously been taught. They can neither think nor autonomously solve problems or develop emotions. That’s why I think that’s nonsense.
What do you think of the idea of classifying robots or computers as “electronic persons” and to require their owners or operators to pay separate taxes for them?
We shouldn’t discuss additional taxation of capital expenditures because that’s actually what taxation of robots would amount to. When we’re discussing tax reforms it would be better to think about raising taxes for specific corporations – especially the major internet companies – and closing tax loopholes.