Automation Threatens 73 Million American Jobs by 2030 | Pt. 1
The next decade will see an increasing amount of Americans become displaced in the economy.
Technology has always posed a threat to jobs it can eventually replace. It seems that throughout history, the changes have always been recoverable. Human nature requires our ability to adapt. Our ability to adapt as individuals and as a collective society has been proven over our species existence.
Even within my own lifetime, technological advancements have been happening rather quickly. Amazingly, technology has managed to already replace 90% of jobs that humans used to do. All indications point towards the fact that automation will increasingly replace more and more jobs. American college graduates have increasingly become enslaved to their debts. 44.7 million borrowers owe $1.56 trillion in student loans. This fact is problematic in and of itself.
Noam Chomsky articulates the real problem to be found in regards to the insane levels of debt that college graduates now are faced with.
“Students who acquire large debts putting themselves through school are unlikely to think about changing society. When you trap people in a system of debt, they can’t afford the time to think. Tuition fee increases are a “disciplinary technique,” and, by the time students graduate, they are not only loaded with debt, but have also internalized the “disciplinarian culture.” This makes them efficient components of the consumer economy.” — Noam Chomsky
The growing student loan debt problem is a crisis in and of itself.
- 1 million borrowers default on their student loans every year.
- Nearly 40% of borrowers are expected to default on their student loans by 2023.
- Data shows that 44% of college graduates are underemployed.
- Most college students are being prepared for entry level jobs that are going to be replaced by automation.
A study conducted by McKinsey, reported that more than a fifth of the world’s labor force will lose their jobs to automation by 2030. Quite an alarming conclusion.
One fifth of the world’s labor force would equate to around 800 million people. McKinsey reviewed 800 job types across 46 nations. More specifically, McKinsey stated that we can expect one-third of American workers to lose their jobs to automation by 2030.
Upon reading this study, my first instinct was that various industries and countries would be hit harder than others. That seems to be true from what I can deduct. The one aspect that remains consistent is that both developed and emerging economies will be affected. It presents difficulties for both types of economies in highly different ways. Like any economic revolution, it can also present opportunities in emerging and developed economies. But this will only happen, if these economies are to react fast enough.
Most Americans are aware of the fact that automation is coming down the pipeline. However, most Americans do not realize that we are already in the thick of it, to a certain extent. America’s labor participation rate is only 62.7%. The U.S. labor participation rate is more comparable to nations like El Salvador (61.9%) and Colombia (62.4%) then countries like the United Kingdom (79.3%), France (72.4%), Netherlands (69.7%), and Switzerland (67.8%).
While the low labor participation rate can partly be explained by the Baby Boomers retiring or children in school, this does not fully encapsulate the true picture. As of 2016, the United States had lost 5 million manufacturing jobs not to bad trade deals and outsourcing, but rather technology. A study from Ball State University found that 13% of manufacturing jobs have been lost to trade while 88% have been lost to robots and other technological advancements.
One would expect to see a decrease in manufacturing output correlate with this, right? Actually, the opposite has occurred. The study found that from 2006 to 2013, “manufacturing grew by 17.6%, or at roughly 2.2% per year.”
While the output increased, 5 million American workers became displaced in the process. This is the trend we increasingly see. McKinsey expects the United States to lose another 73 million jobs in a similar fashion. From 2003 to 2013, white, middle-aged suicide increased 40%. A rapidly changing and displacing economy is at the forefront of the blame. The Center for Disease Control and Prevention claims suicide rates now top the number of deaths due to automobile accidents. The problem has become so severe that life expectancy in the United States has now decreased for three consecutive years.
One has to wonder just how bad things will become as increasingly more workers become displaced throughout the economy. Those who understand the problems associated with low labor participation rates would expect to see higher toxic drug use, increased crime rates, increased suicide rates, the rise of extremist and hate groups, xenophobia and a host of other issues. Arguably, a lot of these factors are already showing face.
Automation is now going beyond just the realms of manufacturing. McKinsey points out that there is high potential for automation to transform sectors such as healthcare and finance. Robots are already assisting doctors in performing surgeries.
The Mayo Clinic states the many advantages to be found by robots performing surgeries include:
- Fewer complications, such as surgical site infection
- Less pain and blood loss
- Quicker recovery
- Smaller, less noticeable scars
Both the healthcare and finance sectors involve highly knowledge based application. It was once thought that these industries were safe from automation due to the amount of knowledge that is required. We can now see that is the precise reason why automation now poses such a large threat to them. Machine learning and robotics has an extremely large capability to impact any job that is largely based upon knowledge and use thereof.
The McKinsey study points out that one-third of tasks could be automated in 60% of jobs. Given this statistic, we can expect massive changes would need to take place for both employers and workers. This statistic that McKinsey references is using only technologies that are available as of July 2016. It is easy to see how that number will drastically change as new technologies are brought forward.
Who is most at risk to be replaced by automation? McKinsey looked at occupations and activities and classified whether or not there is technically feasible for automation. And as they point out, each occupation is made up of various activities. Each of these activities have varying levels of technical feasibility.
To paint this example, I will use retailing. In retailing there are various activities like collecting and processing data, interacting with customers, and setting up merchandise displays. Each of these activities are going to have various levels of automation potential. Due to that, McKinsey arrives at an overall estimate based on scores for the whole.
In addition to technical feasibility, McKinsey states four other factors that will impact automation.
- Costs to automate: Simply, how much will it cost companies to automate?
- Relative Scarcity of Skills: paired with the cost of workers who might do the activity otherwise. This really depends on the supply of workers available to carry out these activities. If there are a higher supply of workers available, this will drive wages down and workers will cost less to carry out the job.
- Benefits of Automation Beyond Labor-Cost Replacement: Are there superior benefits of automation that would justify spending more on automating? Some of these benefits could be: higher productivity, lack of error, and overall better quality.
- Regulatory and Social-Acceptance Considerations: What are the social consequences to be found by changing to automation? What regulations are in place or will be put in place to halt or encourage automation?
If we review the graph above, we see that McKinsey has broken down activities into several categories. They then ranked these based upon the amount of time being spent on activities that can be automated by adapting current technologies. By studying all occupations in the US, we can see patterns of where time is being spent in all US occupations.
It seems that those that have the largest percentages of time being spent on them, are many times those that are most susceptible to being replaced by automation. Data collection, data processing, and predictable physical work account for 51% of all time being spent in US occupations.
Over half of the time being spent in all US occupations is highly susceptible to being replaced by automation, as classified by McKinsey.
Highest Potential For Automation
To which sectors does automation pose the biggest threat? This is naturally a very important question. McKinsey slates manufacturing, food service and accommodations, and retailing as the top of the most susceptible list. In the food service and accommodations sector, 73% of the activities performed by workers have potential for automation replacement. In the manufacturing sector, the number is 59%. In the retailing sector, 53% of all activities are automatable. Of course, across all of these sectors, specific occupations will differ as to how susceptible they are.
As I just mentioned, even within these sectors, there are other considerations to be had. Bookkeepers, accountants, auditing clerks, all require specific sets of skills and levels of training. These occupations have greater scarcity than basic cooks or dishwashers, for example. But on the other hand, the activities that accountants perform cost less to automate. A company would need to invest in mostly software and computers to replace that job.
As it stands currently, McKinsey is able to show that automation for activities within middle-skill jobs (for example data collection or data processing) have led to an “observed tendency for higher rates of automation.”
You may be breathing easier after reading that if you have a higher skill job, but consider this. McKinsey is using data as it currently stands for automation. Automation is only going to advance in its capabilities. Because of this, they state, “jobs involving higher skills will probably be automated at increasingly high rates.”
Where does your occupation fit in? View the graph below:
Largely, I have been discussing job activities that you may believe to not require high levels of education. With the exception of auditing and accounting, that is correct. However, consider the fact that one third of all time spent in occupations in the US economy involves the collection and processing of data. These activities are not done just by entry-level workers or low-wage receiving workers. Those who have an annual income of higher than $200,000 spend 31% of their time performing these tasks. This just continues to paint the ever broad picture of how disruptive automation will become at all levels of occupations.
McKinsey uses an example I really like within the financial services and insurance sectors. The finance world relies on professional expertise. In order for stock traders and investment bankers to be successful, they must have a certain level of expertise and skill. Regardless, it is true that half the time spent in the fields of finance and insurance is spent collecting and processing data. We already know that the potential for automation in those activities is very high.
For example, insurance sales agents are responsible for gathering customer or product information. That information is then passed to underwriters where they verify the accuracy of the information the sales agent collected. As for the financial world, bank tellers verify the accuracy of financial data. 43% of the financials sectors worker’s time spent could be potentially automated. And once again, it is going to vary depending upon specific occupation.
Least Potential For Automation
I have detailed many sectors that have a high or middle range potential for automation. While this is certainly important, it would be rather pointless if we don’t identify which sectors or occupations have the least potential for automation.
McKinsey states that the hardest activities to currently automate are those that involve: managing and developing people (9% automation potential) and applying expertise to decision making, planning, or creative work (18% potential for automation).
The activities can be extremely varied. They can include: coding software, creating menus, or designing promotional materials. Computers are able to perform excellent work when they have well defined parameters. But they do not do well at creating goals, and specific works of art as it currently stands. Sectors where human interaction is highly needed tends to have low potential for automation. Two sectors that McKinsey cites as such are: education and healthcare.
McKinsey also points out that within these sectors, there is still high potential for automation. Take for example, nursing assistants, who spend about two-thirds of their time collecting health information. What about doctors? Some of the more complex functions that doctors performed could become automated. Two of these examples include reading radiological scans or administering anesthesia. Keep in mind, the list is going to continue to grow as automation increasingly becomes more capable.
McKinsey believes that the technical feasibility of automation is actually lowest in the in the education sector. While digital technology is changing the field, it still requires expertise on the part of teachers. But where McKinsey does see the potential for automation within the sector happens largely outside of the classroom. Administration, janitors and cleaners, and cooks in cafeterias are all places where automation could cause disruption and displacement. The automation of administration processes could help to reduce the cost of education.
As with all important issues, it is first important to come to understand the facts and data. That is what I desired to do with part one of this article mini series. Once we come to face the facts, then we can better make decisions about how to proceed forward. Part two will focus on possible ways of how to move forward into the automation age.
