The important effects of automation on employment- good or bad?

The advancement of machinery in the working world has been commonplace for centuries, dating all the way back to the Industrial Revolution and the pioneering of automation such as steam engines and sewing machines, but it is in recent decades that a fierce debate has emerged about what automation means for the security of employment. The automation of manufacturing jobs has resulted in the loss of millions of jobs worldwide. In 2017, the economic forecaster Oxford Economics predicted that up to 20 million net jobs worldwide could be lost to automation by 2030. Even though the technology involved in automation creates many more jobs, with the World Economic Forum (WEF) concluding that up to 97 million new jobs could be created by automation, offsetting a vast predicted number of 85 million subsequent job losses in the same period, this has still done little to ease the worry felt by vast swathes of disenfranchised workers. 

Economists have issued a timely reminder to ensure that the risks to employment associated with a possible rush to automation are not made worse in the wake of the pandemic. The economist Klaus Schwab, who is also the founder and executive chairman of the World Economic Forum, has said that while COVID has brought the time of ‘The Fourth Industrial Revolution’ closer to us, this cannot be a reason to forget the concerns of automation, calling for the technological and digital environment to be ‘human-centred and serve society as a whole.’ Recent studies by the Economist have shown that despite ongoing automation in various fields, ranging from automated checkout tills in supermarkets to automated machinery doing most of the work in slaughterhouses, such fears may be somewhat exaggerated. Rockwell Automation, the largest automation delivery company in the world, saw its sales decline by 5.5% in 2020, while US imports of automated robots for industry fell by 3% last year. 

Research by US banks has found that automation numbers in industrial and service sectors of the economy are relatively consistent in their similarity to their pre-pandemic levels. Historically, when automation was predicted to take hold on a huge scale, it did not evolve to dominate working life in the way many feared it would. AI is being predicted to not experience the growth one would expect it to experience. In 2018, PWC published a study that predicted a 26% increase in global GDP by 23% as a result of AI. It also predicted for any jobs it eliminates will be offset by the jobs created by the technology involved in it. 

Automation processes can sometimes take significant amounts of time and training to implement and must be supplemented by a large amount of continuous investment to keep these processes efficient and minimise the likelihood of errors- whether the investment is in training, logistics or technical support. While one of the impacts of the pandemic will be that more work can be done digitally, the uncertain economic climate may make investors hesitant to put large sums of investment into automation, when it is not yet known how much of it will be needed as the world recovers from the economic downturn caused by Covid-19. Oxford Economics has found that global investment growth from 2019 to 2025 will be less than it would have been had the pandemic not occurred.

McKinsey has said that automation will continue to be more appropriate for jobs that are predictable in their nature, such as packaging, preparing food or carrying out tasks on an assembly line. It is not just these traditional functions that have been automated as well. The IDC has stated that 78% of global banks require the use of apps and other data sources to conduct business. These functions have a repetitive and predictable pattern of work involved and it is cheaper and more successful to automate these roles than roles involving empathy, communication skills, analytical thinking and dynamic decision making which tend to be less predictable in their process and outcomes. McKinsey uses the example of working with dangerous tools in businesses such as construction to illustrate the benefits of humans doing these tasks rather than automating them. They point out that humans would be best placed to deal with the unpredictability of these tasks as the machines have not yet been programmed to do so. 

And let’s not forget about the human factor. While both automation and a person can make the same product, many still feel the need for human contact when engaging in a service, in the hope that they will not just get the experience of the product itself but some insight and appreciation of the effort that goes into producing it. 

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