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Expectation #1

Unemployment should rise as machines replace work previously performed by humans.

Reality: Labour statistics do not bear this out. In the past 10 years, major global economies have all experienced record-low levels of unemployment: 4.1% in the US, 2.4% in Japan, 3.6% in Germany, 4.3% in the UK (Figure 1).

 

Graph depicting current unemployment rate versus 10 year average for Germany, Japan, the UK and the US

Explanation: There are two main influencing factors. First, there is a time lag between the introduction of a technological disruption and a measurable impact on the workforce. In the first decade after introduction, soft automation, where only parts of a job are automated, is more dominant than hard automation, where technology fully substitutes labour. Second, history indicates that new technologies do not necessarily reduce the number of available jobs. The advent of cars meant the loss of horse-related jobs, but the creation of many more roles in auto production, garages, etc.

Expectation #2

Record-low unemployment should lead to wage growth.

Reality: Wages have been suppressed since the turn of the millennium in every major economy, despite an increase in employment.

Graph depicting labour share of US national income by industry

Explanation: Following the financial crisis of 2008, workers might have been more reluctant to move jobs and less confident in their pricing power. But 10 years later, there are other factors at play. According to the IMF, technology is the biggest reason why the US labour share of national income has been declining, as shown in Figure 2, with automation playing a role in about 50% of that decline.1

 

For the first several years or decades, even the most path-breaking technologies end up automating specific tasks within a job, not the job itself. In doing so, technology frequently ends up lowering the skill-set needed to do a job, in turn expanding the pool of potential workers, which then acts as a drag on wage growth.

The trucking industry provides a good example. In 1980, the median trucker wage was about $38,000. Four decades on, median wages are still close to that level. We believe that soft automation is to blame. The introduction of technology such as power steering, cruise control and automatic braking has made the job of the truck driver easier and less specialized – and therefore less able to command high wages.

Expectation #3

Technological advances improve productivity.

Reality: Labour productivity growth has slowed sharply in OECD economies over the past several years, predating the 2008 financial crisis. From 2005 to 2015, the OECD estimates that aggregate productivity in 30 major economies was just over 1%, compared with 2.5% in the previous decade – a marked decline in productivity and global growth.2

Explanation: Most of the path-breaking leaps in technology – the generation and collection of big data, the collapse in data storage costs, the advent of machine learning – largely occurred after 2005, so why hasn’t productivity improved? The past offers an explanation: Most of the great technological leaps of the past 150 years – including the invention of the automobile and electrification – happened around the turn of the 20th century.

 

Yet productivity languished in the following decades, even as these game-changing inventions became mainstream. By contrast, productivity growth averaged 1.5% or more in every decade from 1940 to 1980, including a dizzying 3.3% between 1950 and 1960, a period not associated with economy-changing technological advances (Figure 3).

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Podcast: Goldilocks in developed economies: How long can it continue?

Unemployment is at record lows, yet wages are stagnant. What’s the holdup? Our Research analysts debate cyclical vs. structural explanations and the economic implications of both.

Infographic: Will robots take our jobs? 

Machines are learning to do increasingly complex tasks. Will people be replaced by technology in the workplace anytime soon?

Read 'Robots at the gate' (PDF, 3MB)

Download the latest report in Barclays' Impact Series

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