“Robots are going to take our jobs, worsen unemployment and consequently lower our standard of living. We should, therefore, do everything in our power to stop the automation of jobs.”
The hard truth is that robots and artificial intelligence (AI) are already starting to take jobs from humans, and it’s going to continue into the future. Some AI industry experts, such as Kai-Fu Lee, predict as much as 40% of existing jobs will be automated and eliminated within the next 15 years (Gallo, 2019). With such startling statistics staring us in the face, why don’t we do the obvious and stop the automation of jobs and protect employment and our subsequent standard of living? Does the above statement apply equally to both developed and developing economies?
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With real world concerns of growing inequality and the current lack of opportunity for many in the labor force we need to better understand the link between these two and the structural changes that need to take place within countries’ economies. As in most cases the answer to the above paradigm is not a straightforward one and I will explore this in detail throughout the body of this essay.
David Autor, an American economist, AI industry expert and professor of economics at the Massachusetts Institute of Technology (MIT) has developed two principles that analyze the question of: Will automation take away all our jobs? (Autor, 2016).
The first is called the O-ring principle and stems from the fact that the Challenger Spaceship failed on its mission into space because of a simple O-ring failure two minutes after takeoff. This simple O-ring froze prior to take-off and was the single determining factor in the failure of the operation as all the other tasks functioned without any issues. It essentially says that improving the reliability of any one link in the chain will increase the value of any of the other links. If we apply this principle to the labor market with an AI lens, what Autor is saying is that automating some subset of these tasks doesn’t make the other one unnecessary, in fact the opposite is true, and it increases their economic value. Technical expertise and intuition are often forgotten in the talk about robots and therefore jobs are still important. They can’t all be done by machines but they still need to be done (Autor, 2016).
The second principle is based on the premise that as our tools improve, technology magnifies our leverage and increases the importance of our expertise, judgment and creativity. Autor (2016) says we “Never Get Enough” and identifies a great example whereby in the late 1800’s and early 1900’s, farming and agriculture contributed 40% of the jobs in the US. This has now reduced to 2%, despite the increase in population and demand for food. Productivity and technology made this possible and subsequently jobs were created in other and new industries. Autor summarizes this well by stating: “Once we get sufficiently productive at something, we basically work our way out of a job” (Autor, 2016).
By looking at history and indulging these principles there is no denying that automation and technology can eliminate jobs but it is important to avoid looking at this in isolation.
Hal Varian, Google’s chief economist and founding dean of the School of Information at the University of California, Berkeley, said that when predicting future labor market outcomes it is important to consider both sides of the supply-and-demand equation (Snyder, 2019). Most of what is written and discussed about technology today focuses on factors that decrease demand for labor by replacing workers with robots or machines. Having said this, demographic trends point to a considerable decrease in the supply of labor, potentially larger in scale than the automation of jobs. To add to this, the prediction of demographic trends are easier and more accurate to predict, as we know how many 40 year olds will live in a country 20 years from now. Varian says that if one compares the most aggressive expert estimates about the impact of automation on labor supply with demographic trends that allude to a workforce reduction, he found the demographic effect on the labor market is 53% larger than the automation effect (Snyder, 2019). Therefore real wages are more likely to increase than to decrease when both factors are considered.
David Autor was the keynote speaker at this year’s MIT Initiative of the Digital Economy (IDE) annual conference in June and began his presentation with a conundrum. He said that one would normally expect the price of something plentiful to go down while the price of scarce things to rise (Aeppel, 2019). What has happened in the American job market in recent decades however, is the exact opposite. The share of the workforce that has college degrees has increased dramatically from 12% to 39% while the percent of workers who didn’t finish high school had dropped from 42% to just 6% (Aeppel, 2019). And yet salaries of tertiary educated workers have gone up progressively and strongly, while those with few skills have largely experienced unchanged wages. Autor said it is easier to explain the increase as rising demand for advanced cognitive skills has meant higher salaries for those with degrees, even as they became more abundant. It’s harder to explain what has happened to low skilled workers and this is where Autor has chosen to focus some of his research with surprising results, some of which he is still processing and examining.
The two main focuses of his research are the analysis of urban labor trends and the need for new career paths.
With urban labor trends one expected big developing cities to provide higher wages for both high and low skilled workers as higher productivity and growth would dictate. Prior to the 1970’s low skilled workers we at an advantage to those in rural areas and were able to hold middle-skilled jobs in offices and factories, while those outside the cities didn’t have those opportunities. In the 1990’s this mix changed dramatically and many of the low skilled workers that were able to have more secure and better paid middle skilled jobs and opportunities, or as Autor puts it, “climb the occupational escalator”, were no longer available (Aeppel, 2019). This makes sense as many of these jobs were easily automated, such as bank tellers who were replaced by the ATM machine. The low skilled workers became increasingly clustered into low level service jobs instead of middle-skilled jobs. By contrast Autor says “Cities have become much more educated, much more skill-intensive, much higher wage places” (Aeppel, 2019, June 7). Therefore the gap between low skilled workers and those of higher education is increasing, particularly in urban areas. The result is that many of these low skilled workers now work purely for the care, convenience and maintenance of the affluent, rather than working together to produce something.
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One used to safely say, to those without a university degree, that they could find better opportunities in urban areas however now this is not the case anymore. As the occupational structure has shifted there is hardly a difference between the work opportunities in both rural and urban areas, and as the cost of living is substantially more in cities, it is becoming less feasible.
So what are the kinds of jobs and careers that the economy needs to create in order to help those low skilled workers? In developing economies we have this exacerbated problem and we need the government and society as a whole, to facilitate the process. Autor mentions that we have plenty of great careers for the highly educated and plenty of jobs for the less educated (Aeppel, 2019). However we don’t have careers for the less educated and this is a problem. He mentions three main job categories namely; frontier jobs, ‘wealth work’ and last-mile jobs (Aeppel, 2019). Frontier jobs are often tied to technology, such as AI specialists, while ‘wealth work’ doesn’t necessarily have an obvious technical component, and are usually in service to the super affluent. Last-mile jobs are those that are worse affected by automation and used to be robust but are becoming increasingly scarce.
The challenge, according to Autor, is creating sustainable jobs in any of these three categories that can offer secure careers for low-skilled workers (2019). These will undoubtedly take time and resources from both public and private sectors but it is something that cannot be ignored. This is especially significant in developing economies where the equality gap continues to widen and should be made a priority for the future sustainability of the economy and improvement in the standard of living.
The last point I want to highlight is the advantage of leaders in the Age of AI. Robots can never be sufficient leaders as they don’t have emotion or empathy. Kai-Fu Lee, an AI industry pioneer says: “AI is incapable of building trust between two people (or between customers and a company). It cannot inspire teamwork, show passion or exhibit empathy because it has no imagination.”(Gallo, 2019). Lee says that the jobs of the future will require creative, compassionate and empathetic leaders who create trust, build teams, inspire service and communicate effectively. He states: “We will end up with the inevitable outcome that large numbers of routine jobs will be eliminated and large numbers of empathetic jobs will be created.” (Gallo, 2019, January).
As Dr. Helen Riess writes in her book, The Empathy Effect, that great leaders are exquisitely attuned to others’ emotions. She cites neurobiology studies which show that most people have a preference “for leaders who above all else express empathy and compassion.” Empathetic leaders recognize the feelings of other people and respond appropriately (Gallo, 2019, January).
Autor says that as automation frees our time, increases the scope of what is possible, we invent new products, ideas, services that command our attention, occupy our time and spur consumption. (Autor, 2019). What is critical is that the leaders of today use the wealth generated by their economies and industries in the right way. If the decision making and investment for the future is not made well then this will have a negative repercussion for the future of labor and the standard of living of each country respectively.
It is evident that robots and AI are not only reshaping jobs, they are deciding where the work gets done, who gets it, and at what wages. Therefore stopping the automation of jobs will not lead to job security and better standards of living. It is not always possible to know the type of jobs that will exist in the future, app developers and AI experts being prime examples, but if we do not embrace the change and challenge that it brings we will not only be doing humanity a disservice, but increasing the economic polarization that exists in both developed and developing economies.
- Aeppel, Tim. (2019, June 7). David Autor Tracks Shifting Job Trends. Retrieved from URL. http://ide.mit.edu/news-blog/blog/david-autor-tracks-shifting-job-trends.
- Hoban, Brennan. (2018, March 8). Robots aren’t taking the jobs, just the paychecks—and other new findings in economics. Retrieved from URL. https://www.brookings.edu/blog/brookings-now/2018/03/08/robots-arent-taking-the-jobs-just-the-paychecks-and-other-new-findings-in-economics/.
- Gallo, Carmine. (2019, January). An AI Expert Told ’60 Minutes’ That AI Could Replace 40 Percent of Jobs. Here’s the Part He Left Out. Artificial intelligence can replace repetitive tasks, but it doesn’t have the empathy to lead.
- Retrieved from URL. https://www.inc.com/carmine-gallo/an-ai-expert-told-60-minutes-that-ai-could-replace-40-percent-of-jobs-heres-part-he-left-out.html.
- Autor, David. (2016, September). Will Automation take away all our jobs? Retrieved from URL. https://www.ted.com/talks/david_autor_why_are_there_still_so_many_jobs?language=en#t-1103654
- Snyder, Bill. (2019, March). Fears of job-stealing robots are misplaced. Retrieved from URL. https://www.therobotreport.com/jobs-fears-robots-misplaced/.
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