It’s a view that’s not supported by the Deputy Director of the Centre for Labour Market Studies at the Higher School of Economics in a recent paper.
The paper highlights how between 1990 and 2007 some 670,000 workers were replaced by automated technology in the United States, with typical installations replacing anything up to six workers at a time. Whilst on the surface this sounds a lot, in reality it is a drop in the ocean.
“In the U.S., the annual employee turnover, i.e. the sum total of all hiring and firing, exceeds 120 million. For new technology to affect the overall unemployment level, it would have to cause a one-off loss of at least 500,000 to one million jobs,” the author says.
What’s more, when the analysis is performed on a more granular level, either at firm, industry or economy levels, the same relative lack of impact is noted. Indeed, the impact of technology is often positive rather than negative. This phenomenon is noted not only in the US, but in Germany, France and Israel too.
The author contends that whilst there is unemployment caused by technology, these are usually short-term in nature until the market adapts to the new technology. For instance, during an analysis conducted between 1985-2009 across 21 developed countries, this lag lasted for around three years on average before employment recovered.
Indeed, none of the professions Oxford economists Carl Frey and Michael Osborne predicted would be automated back in 2013 have come even close to being so as yet. Whether it’s bank tellers, cashiers or paralegals, the numbers employed have increased even as technology has become more potent.
The reality tends to be that certain tasks within jobs can be automated but it’s much harder to automate everything contained within a job. When this relatively simple nuance is added to equations, it tends to reduce the jobless predictions six-fold, and even these might be overestimations as just one (of 300) occupations was fully automated between 1950 and 2010 (elevator operator).
The paper outlines a number of fundamental flaws in the kind of radical predictions that have become commonplace recently:
- An assumption that all jobs are either low or high skilled – “In reality,” the author says, “skills levels tend to form a much wider range depending on the workforce quality. It is quite possible that under certain conditions, workers at the lowest level of their professional hierarchy could move a step upward, taking the place of someone else who has also moved up, and so on to the top of the ladder. This type of job replacement can dramatically lower the risk of a sudden surge in technological unemployment.”
- They fail to account for the limits of technological spread – There are numerous social, ethical and legal factors that limit or slow the spread of technology. Autonomous vehicles, for instance, are likely to require fundamental revisions of legislation that may significantly slow the roll-out of the technology.
- Stalling productivity figures – If we assume productivity growth is a reflection of technological progress, then the decline in annual productivity growth between 2005-2015 doesn’t paint a great picture of technological adoption.
Indeed, the paper argues that the biggest impact technology has had on the economy is the increase in value of leisure time over the last decade or so. It contends that it has had a significant adverse affect on our motivation to work. The author believes that this has contributed to a 10% fall in employment for American men aged 21-30. This has coincided with a rise in zero hour work, and the average number of hours worked per person per year fell by 300 hours. Despite this, the overall tone is a positive one.
“New technologies contribute to people’s wellbeing and usually lead to higher demand for labour, despite what some techno-alarmists may be saying. This is confirmed by extensive theoretical, empirical and historical evidence. Rather than fear the speed of technological progress, societies should be wary of it slowing down, which may result in economic and social stagnation,” the paper concludes.