Man vs. Machine: Article in “Der Spiegel”

Mensch gegen Maschine


Your fired!

Markus Dettmer, Martin Hesse, Alexander Jung, Martin U. Müller, Thomas Schulz; Der Spiegel, no. 36, Sept. 3, 2016, pp. 10-18.

This article in the German magazine “Der Spiegel” (a leading European news magazine) deals with the current and future impact of computing and robotics on the job market.

I summarize it in English here.

The attack of robots threatens the economic existence of the middle class. At risk are not only jobs in the factory hall. Now it is threatening qualified and skilled office employees. Which jobs will survive?

Robots are already working as bankruptcy lawyers.

Jurists speak with “Ross” him just as with any other experienced colleague. When asked a question on a point of law, the robot searches through a billion documents – law texts, commentaries and formulates an answer within seconds.

This law robot is already at work in a few US law firms and is one of the applications developed by IBM’s Watson program. Watson is a system that searches through gigantic databases, learns as it goes and never forgets anything – unlike people. It can

  • Help oncologists to identify tumors and suggest treatment
  • Help an investment consultant put together the right portfolio for a certain client
  • Analyze weather patterns to more accurately predict weather
  • Answer customer queries by analyzing email contents

Watson is the perfect assistant for physicians, bankers, weathermen and call center agents… and could soon become your stiffest job competitor.

Watson can do what many specialists do better and cheaper. He does not get tired, does not need vacation and does not go on strike.

In the past, robots threatened mainly jobs in manufacturing. Now they are threatening jobs in logistics, delivery services (drones), pharmacy, lab assistance, translation / interpretation services and various back office jobs.

In the meantime, robots are even capable of learning tasks from and collaborating with other robots. These are now named “cobots”. Soon, people will not have to tell robots what to do – robots; they will be able to observe what happens in their vicinity and be able to decide what is to be done. You might even have a robot as your boss.

Sabine Jeschke, professor of machine technology in Aachen knows that technical progress does benefit all people – many will lose their jobs as a result: “We have to ask ourselves whether people can have a reasonable existence when they are able to perform commercially productive work.” This is a critical issue for society in the future digital world.

One problem that those employing robots must consider is, despite the fact that robots can manufacture and perform services better and more cheaply than people, how will those made jobless afford to buy the same products and services?

Past revolutions in industry and employment – the industrial revolution of the 19th century, the production-line revolution of the early 20th century and the introduction of robots in heavy manufacturing (automobiles, etc.) in the 1950s cost jobs, but also created new industries that led to new jobs and more jobs than they destroyed.

The robotic / digital revolution could be the first that fails to create more jobs than it destroys. The difference with industrial robots up to now is that robots and computers served as tools that assisted workers to get their jobs done more efficiently.

This new generation of automating robots is, however, designed to replace human workers.

Professions at high risk (at least 70% probability that these professions will be automated in the next 20 years)

  • Office / secretarial jobs
  • Sales
  • Gastronomy services
  • Business management
  • Postal / delivery services
  • Kitchen jobs
  • Banking services
  • Warehouse management
  • Metalworking
  • Accounting

Professions at low risk Professions at high risk (less than 30% probability that these professions will be automated in the next 20 years)

  • Child care
  • Health services
  • Supervisory and business leadership
  • Mechanical and industrial engineering
  • Automobile technology
  • Purchasing, distribution and trade
  • Social work, social education
  • Geriatric care
  • University instruction and research
  • Construction electronics

(List composed by Carl Frey and Michael Osborne of Oxford University)

Applied to Germany, research would suggest that 42% of all employees would lose their work to automation.

Facebook employs 13,000 people globally. These employees create a profit of about a quarter million dollars per head. By contrast, Daimler employs 284,000 people globally and – in a good year – achieves a profit pro employee of only 30,000 dollars.

Enterprises in the Old Economy, automobile manufacturers for example, have the most difficulty in fully exploiting the new technologies. They have to question everything that was once certainty – especially the very concept whereby cars are manufactured. Mass production facilities – around since Henry Ford – may become a thing of the past.

Local Motors is a new company provides a contrast with companies like Daimler. Cars are not produced in large, centralized factories. Local Motors produces cars in small, so-called “micro factories” close to customers; no factory is larger than 4,600 square meters. Most components other than motors, cables and batteries are produced by 3-D printers and assembled mainly by robots. Its model “Strati” consists of only 49 components. At the moment, three micro factories exist in the USA. Local Motors plans to expand globally.

Local Motors employs only 116 people at its headquarters in Phoenix Arizona.

(Much of the article, pp 14-17, gives some indications that the effect of automation will be perhaps not quite so drastic and deals with the impact of automation on manufacturing companies as well as the nature of employment in the future.)

One idea towards preventing the impoverishment of employees replaced by automation would be to introduce a basic income for all national residents (the Swiss held a plebiscite on this idea in 2016; the proposal was defeated, but who knows what the result of such a plebiscite might be in 10-20 years?). Such an approach would obviously be expensive, and companies automating would need to contribute towards its financing – perhaps by means of a “machine tax” (yet if too many people have no / too little income, where will automated business find customer able to buy their products or services?)

One approach towards securing people’s future financial security has been suggested by American occupational scientist Richard Freeman of Harvard University. He proposes that employees should own the robots that will replace them. They would thereby finance the costs for acquiring such robots for the companies employing them and earn from these new “replacement” employees. This idea represents in interesting potential solution for workers whose source of income is under threat.

Researchers at the German Bertelsmann Foundation and the foundation Neue Verantwortung have developed 6 scenarios as to how German society and job market could change by 2030.  The scenarios range from the very optimistic “Engineering Nation with Heart” to the disastrous “Digital Failure” with mass unemployment, collapse of tax sources and political revolution. In five of the six scenarios, the researchers reckon with a cumulative loss of jobs for people. The battle for jobs will become harder and the danger of loss of income for many increased. This fate is however not inevitable.

People have the opportunity to protect themselves by continually supplying themselves with new knowledge and skills. Sebastian Thrun, a Silicon Valley visionary, employs about 200 people at Udacity, an online academy that enables people to update their knowledge and skills. He established the company four years ago near Google headquarters in Mountain View where he previously directed it secrete laboratory “Google X”.

The courses resemble skilled tradesman training as study. Participants in Udacity work with specialists on real projects and products. A course lasts 6 months and costs 200 dollars a month. The course participants receive a so-called “nano degree”.

“Artificial intelligence learns a lot more quickly than humans. We need to do something urgently so as to keep up.” Technology does have its limits. There are skills that people have and that machines have trouble copying: flange-mounting a motor onto a drive chain, pleading a law case in court, socially competent human resource planning, et al.

A robot could attend to the needs of a dying patient day and night, but cannot comfort him with the touch of a warm, human hand.


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