The Impact of Workplace Automation on the Relationship Between Unemployment and Economic Growth Rate How the relationship between unemployment and economic growth rate changed as the  workplace becomes increasingly automated?

The idea of an automated economy is not necessarily new, with the invention of the steam  engine came the industrial revolution. Work horses that once formed the backbone of many  industries were retired as new technology such as the combustion engine were brought in.  There was and still is widespread fear that robots will replace human workers, forcing  humans to exist on a subsistence wage, Some economists believe that the indeed during the  early 1800’s a group known as the Luddites destroyed machinery, fearing that it would come  to replace them and make them redundant. There are however some jobs that may always  require the human touch. Otekhile and Zeleny (2016)

With regard to the current state of the global market, the assumptions of Keynesian and  classical economic theories may not apply. Following the most recent global recession  unemployment has not reduced significantly, however economic growth appears to have  continued (Brynjolfsson & McAfee, 2012). Therefore, there is an anomaly that is not  explained by the two most prominent schools of economic thought. It is suggested that the  increase in growth seen without the assumed dropping in unemployment rate is the product of  new technology creating market growth but displacing workers from their jobs and therefore  failing to reduce unemployment. The interaction between economic growth and technology is  documented and its effect on unemployment is subject to much discussion.

Frey and Osborne (2017) conducted analysis across many different sectors of employment  and found that in the US 47% of jobs were at risk of being lost to automation. They also  found evidence that wages and level of education attainment strongly predicted the lack of a  computerization risk. Therefore, it could be assumed that automation of the workplace will  affect lower skilled and lower paid jobs, especially in areas like manufacture, quality  checking and information transfer and storage. Positions such as sales assistant and clerical  work were also high on the list for automation. On the other end of the scale positions such as  medical practice, therapy, hospitality and teaching were low risk. This again suggests that  automation will take over lower skilled roles and create space for investment in human  capital, effectively up-skilling workers in different or higher-level positions and sectors.  Otekhile and Zeleny (2016)

Aghion and Howitt (1990) Propose that technology exerts two factors on the rate of  unemployment with regards given to growth rate. They based their model on findings from

Pissarides’ (1999) employment growth theory that while found a link between higher  productivity and declining unemployment rates. This is a contentious link however, Layard,  Nickell and Jackman (1991) argue that unemployment rates do not consider rate of growth as  an explanatory variable, equally Phelps (1968) states that natural equilibrium employment  rates are independent of productivity growth. Regardless, Aghion and Howitt (1990) used  Pissarides’ (1990) model but adapted it as the original model failed to consider increases in  productivity can be within new job positions that replace old jobs. They found that with this  specifically applied to technological advancements that replace human workers with  automation, growth exhibited two contrasting processes on unemployment, the first they  termed capitalization, directly increased growth as a result of workplace automation, it raised  the returns of new job creation and reduced rates of unemployment. The second process,  creative discussion, describes how increased growth reduces the duration of job positions in  the labour market, this in turn has an increasing effect on unemployment rates as it indirectly  discourages the creation of new job vacancies and increases the rate at which jobs positions  are terminated. These two processes interact within the economy to create equilibrium of  unemployment that in turn influences and is influenced by growth. Thus, it suggests that the  introduction of new technology in the workplace creates stabilizing unemployment  equilibrium by creating jobs while some jobs are lost. Aghion and Howitt (1990), Otekhile  and Zeleny (2016) conclude that in the future the effect of new technologies on the workforce  is elusive, but that there is certainly an interaction that is worthy of studying as the world of  work becomes increasingly automated.

Otekhile and Zeleny (2016) discuss the impact of self-service technology on unemployment  rates and conclude that there may be an interaction between the lack of aggregate demand,

and the absence of a new sector