With the myriad of potential benefits to the global economy that automation possesses, it also comes with notable challenges which are difficult to manage. One of the most widely recognized hurdles is surely on addressing the effect of automation to workers whose jobs will be displaced by technology. While measures of companies’ production efficiency are soaring, so is the number of potential job destruction throughout the world.
As a quick illustration, back in 2015 the Bank of England estimated that about 15 million UK labors were at risk from automations while another finding from Brookings Institution stated that one-quarter of total American jobs belong to this category. Moreover, the latter study outlined that the trait of those jobs which are at high-risk from automation involves “monotonous and routine” tasks which are naturally attached to lower-wage workers. Consequently, it would affect income inequality more severely. While there is a growing school of thought stating that eventually new types of jobs (i.e. programming, data analysis, etc) would emerge and thus constructing a firm novel demand for workers, it often requires a remarkably high standards for competency. Hence, we can say that to ‘equalize the opportunity’ is something which could not be achieved overnight since the skill gap among workers is already wide.
In addition to the aforementioned direct effect, one more lurking, yet not less harmful, implication derived from automation is actually its impact on the process of intergenerational mobility of the displaced workers. Straightforwardly speaking, if you are a worker whose job is located in a sector highly exposed to automation, be aware that this condition will not just harm yourself and the current well-being of your family but also to your child’s future economic status. Put on a vivid concern that your today’s circumstance is directly linked to their education attainment which will be their tomorrow’s human capital stock. As we would later elaborate, this interlinkage provides an empirical ground to safely say that the repercussion induced from automation to affected workers will span for generations.
The Future is (Somewhat) Predetermined…
The term ‘intergenerational mobility’ refers to ‘the ability for a family group to move up or down the socio-economic ladder across the span of one or more generations.’ If your son is wealthier than you, then your family is having an upward intergenerational mobility, and vice versa. However, most society around the globe does not feature a high-level of intergenerational mobility, as reported by the World Economic Forum’s Global Social Mobility Index 2020. In other words, in almost every economy, a person’s background, which resulted from the family where they came from, will most likely predetermine their future economic well-being. Some channels through which this hypothesis materialize are the expected level of education they will attain, the expected type of job they will have, and the expected income level they will earn.
As intuitive as it may sound, the impediment for this socio-economic movement to emerge is the persistent level of income inequality globally. As recent study has found that greater inequality has been robustly linked to lower levels of intergenerational mobility through the so-called “The Great Gatsby Curve” as shown below, there is a plausible rationale behind the mentioned relationship. The Theory of Intergenerational Mobility stated that wealthy parents in general invest more in their offspring than poorer ones and thus making their children’s respective future economic status more persistent. This difference in human capital endowment will magnify the skill gaps between the ‘rich-and-smart’ youngsters and the rest, enlarging the discrepancy between their future earning potential as well, as ILO predicts. Furthermore, low-income parents tend to give birth to less-healthy children with primarily less nutrition intake which is important for their cognition skills due to several socio-economic factors. Noting that the opposite is the reality for higher-income parents, this circumstance will also contribute to the widening gap of human capital development. In conclusion, as the rich get richer (the top 1% of earners in 2018 earn 158% more than in 1979, in comparison to 24% of those belonging in the bottom 90%) the poor will stay poor.
…And Automation Across Industries Will Amplify it…
There is a plain logic behind the above statement. Automation at the end of the day does destroy jobs, at least for some certain types. This disfigurement of affected laborers’ income stream erodes their ability to invest in their descendants’ health and human capital since it is even becoming hard to bring bread to the table. A 2018 study from University of Oxford provided an empirical estimation highlighting the significant intergenerational impact of automation-induced job destruction to the affected families’ economic welfare. The researchers found that a standard deviation higher of automation exposure is associated with a 0.9–1.2-point reduction in upward mobility. Their ‘exposure to automation’ variable is calculated by obtaining the data from International Federation of Robotics (IFR) which provides industry-level data on the use of industrial robots and then comparing the shares of robot and human workers in a specific industry, successively. Generally, according to the stated statistical inference above, this study concludes that a childhood spent in an area more exposed to automation will generate substantially lower income in adulthood. However, all the reasons behind this specific finding is actually more far-reaching than only their parent’s job loss per se. There are also developmental consequences of community job loss that manifest earlier in children’s life which lessen their ability and motivation to economically mobilize upward. In other words, longer time-spent in areas affected by automation means longer time-spent with a community which lacks all the optimum resources to pursue an upward intergenerational mobilization.
Another frame of reference to comprehend this phenomenon is the very recent study published around May 2020 by MIT’s Daren Acemoglu. He found a strong, semi-causal, link between automation and income gap which has taken place since the late 1980s. Be noted that it is commonplace for higher income inequality to dampen the progress of intergenerational mobility, as we already examine. From 1987–2016, average displacement (job losses due to automation) was 16% while average reinstatement (new job opportunities due to automation) was 10%. In short, the figure of job losses exceeds opportunity. Furthermore, this computation is even more hurting for low-skill workers since starting from the early 1990s, the newly available tasks are only benefitting high-skill workers (i.e. those with relatively higher education). In sum, automation per se is one of the most prominent engines for a broader income inequality and its following widespread intergenerational immobility.
…As Long as We Opt for “Do Nothing” Scenario
At times, the status quo is already enough, but it is not the case with this problem. Policy reforms to better promote an equal share of next generation’s human capital in the society through more accessible education and early-age public health services are alarmingly needed. Taken from OECD’s report on intergenerational mobility, some programs which could enhance the equality of future opportunities through school-based tools include encouraging a more inclusive social mix between students and circulating a government-supported grant system for schoolers’ schooling purposes. The former one aims to increase the overall representation of the disadvantaged students, making them having the opportunity to intellectually catch-up with their fellow smarter friends, while the latter refers to the condition in which the government ease up students’ financial dependence on their families regarding their educational goals. The same report also signifies the significance of progressive taxation systems and education-oriented social transfer programs which could assist parents in investing in their child’s knowledge.
Besides poor children’s inclusion, increasing their performance is just as necessary. One prominent example of this is Banerjee et al’s Balsakhi Remedial-Based Schooling Program. The experiment concluded that a remedial program aimed to teach specific students which are lagging behind in basic literary and numerical skills will increase the average test score of overall students by 0.28 standard deviation. This rise of score stems from large gains of the students in the bottom of previous test scores distribution which are typically a member of the remedial program. Other than studying arrangement, we must reckon that this is largely a health-based issue as well in which poorer students come to school after eating a diet with comparatively less nutrition. Therefore, to bolster public investment on poor people’s health should be added to government’s to-do-list for tackling the issue, as a study indicates a strong relationship between spending on health with more equal child test scores at school. All-in-all, boosting the ability of unlucky students to follow the progress of their luckier counterpart is of utmost importance.
Finally, in the information technology era, it should be taken into account that a huge shift in types of skill demanded by companies is currently taking place, as McKinsey analyzes. Coupling aforesaid Acemoglu’s statement on high-skills-requiring novel tasks which will harm low-skill workers with fact, this paper finds that the demand for technologically high-cognitive skills will rise by 55% up until 2030 whereas the demand for basic cognitive skills and physical-manual skills will fall by 15 and 14 percent, respectively. Henceforth, all of the above education programs should be intended to not only prepare future workforce to have a commensurate level of human capital but also to prepare them to be adaptive to the changing global demand of more digitized and more intellectually-demanding skills. From mixing digital literacy awareness to school curriculum to encouraging the learning in online platforms, several steps could be opted for to reach said objective, as modern problems need modern solutions as a remedy. Most of the time, we need to be context-specific to solve the world’s most pressing issues, including this one. Summarily, as the welfare pie of humanity is already unfairly distributed, we should not let machines exacerbate it.
Written by Fadli Jihad Dahana Setiawan
Reviewed by Sendy Jasmine & Mervin Goklas
Illustrated by Gayatri Wulansari
Reference
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