Chapter 9: Unemployment Tomorrow

We will analyse the US workforce layer by layer. I chose the US mainly for three reasons: 1) it represents one of the biggest economies on the planet, 2) it has very good public data available, and 3) many of the industrialised countries are in a very similar situation.

In the United States, as of 2010, there were about 139 million workers, with a population of 308 million.1 The unemployment rate has fluctuated over time, but the cycles of ups and downs have started to look more like a trend. That trend represents a global rise in unemployment.

In 2010 unemployment was 9.6%,2 one of the highest in US history, second only to the 1982 value of 9.7%.3 An even more interesting statistic is the number of working people, against the total number of people. In 2000 the US had a population of 281,421,000, with a working force of 136,891,000. By 2010, the population had increased to 308,745,000, but the working force was only 139,064,000 (see Table 1.1).

Year Total Population Employed
2000 281,421,000 136,891,000 (48.6%)
2010 308,745,000 139,064,000 (45.0%)

Table 1.1: Total US workforce in between 2000 and 2010.

There are far more jobless people in the United States, and in the rest of the world, than you might think. While the reports say that unemployment in the past two years has been falling, the reality is different. As recent as March 2012, Eurozone unemployment hit the record high level 10.9%.4 But there is more.


Figure 1.1: Americans not in the labour force, by age, as of 2011. Image courtesy of CNN, data comes from the US Bureau Labor of Statistics.

In 2011, in addition to the millions of unemployed, another 86 million Americans were not counted in the labour force, because they did not keep up a regular job search. Most of them were either under age 25 or over age 65.5 It is easy for politicians and economists to minimise the fear of unemployment, just change the way you measure and you are suddenly much better off!

This is the present situation, and it is not looking good. But what does the future have in store for us? Let us take a look at the number of jobs per occupation, with at least 1 million workers.


Number of workers

Percentage of workers%

Driver/sales workers, bus and truck drivers



Retail salespersons



First-line supervisors/managers of retail sales workers






Secretaries and administrative assistants



Managers, all other



Sales representatives, wholesale, manufacturing, real estate, insurance, advertising



Registered nurses



Elementary and middle school teachers



Janitors and building cleaners



Waiters and waitresses






 Nursing, psychiatric, and home health aides



Customer service representatives



Laborers and freight, stock, and material movers, hand



Accountants and auditors



First-line supervisors/managers of office and administrative support workers



Chief executives



Stock clerks and order fillers



Maids and housekeeping cleaners



Postsecondary teachers



Bookkeeping, accounting, and auditing clerks



Receptionists and information clerks



Construction laborers



Child care workers






Secondary school teachers



Grounds maintenance workers



Financial managers



First-line supervisors/managers of non-retail sales workers



Construction managers






Computer software engineers



General and operations managers



Total of Occupations Listed Above



All Other Occupations



Total Employment



Take a good look at the table above. Now answer this: how many occupations were created in the last 50 years? The 34 occupations listed above make up 45.58% of the US Workforce. How many new jobs were introduced because of the advances in technology? The answer is only one: computer and software engineers. This profession barely makes it into the list at all. In fact, if we were to exclude the bottom two, we would still have 44.12% of the economy represented, and not a single type job was created in the last 50 to 60 years.

The reality is that the new jobs created by technology employ a very small fraction of people, and even those jobs tend to disappear soon after they are created. Think of the jobs created in the IT industry in the 1980s, and how many of them survive to this day in 2012. If you were a programmer back then, or a system administrator, and you did not study and learn the latest developments, it would be very hard to find a job for you today. How many occupations were created because of the introduction of a new technology, only to disappear because an even newer technology came along? New jobs require a high level of education, flexibility, intelligence, entrepreneurship – most people have not been trained to be like that. In fact, our entire educational system was created just after the industrial revolution, with the idea of creating factory workers. The needed manual jobs, repetitive jobs, and our educational system has not been sufficiently upgraded since then.

The economy has been in need of a different breed of people for a long time. The process of changing that is very slow, and hard, however. One reason is because the teachers themselves have been taught to be like that by their generation of teachers. Standardised tests, standardised courses, standardises exams, can only result in standardised minds. Students are not encouraged to challenge the textbook, or the teacher. They are not encouraged to work in groups, to collaborate, or to find different solutions.6 They have been taught that there is always a solution. There is only one, and it is on the back of the book. But do not look, because that is cheating.7

The reality is that there are many solutions to an infinite number of problems. Some are better than others. Sometimes, there are no solutions at all. Sometimes the solution can only be found in interdisciplinary thinking, by collaborating with people from different areas of speciality.

There have been attempts to reform the educational system, and some great experiments are being performed (we shall explore this in more details in Part 3: Solutions). But the educational system is an even bigger and slower elephant than companies are, and it will take a long time before it adjusts itself. The question is, can it be quick enough to adapt at the same speed of technological advancement? I do not think it can. A few people will be smart enough to adapt to this new paradigm (if you are reading this book it means you are already thinking about this problem, and you have a good chance of being in that tiny slot), but I fear the population at large will be in trouble.

Just to see what the trend is, let us examine some of the biggest and most successful companies, listed in chronological order. You can see the year they were founded, the number of employees in 2012, and the average revenue per employee.

Company Employees Revenue per employee
McDonald’s (1940) 400,000 $60,000
Walmart (1962) 2,100,000 $200,000
Intel (1968) 100,000 $540,000
Microsoft (1975) 90,000 $767,000
Google (1998) 32,000 $1,170,000
Facebook (2004) 3,000 $1,423,000

Table 1.3: List of multi billion-dollar companies over time and their revenue per employee.

I think you get where this is going. Newly created multi-billion dollar companies do not have strings attached, such as old workers from previous generations, so they can focus on efficiency from the start. Big companies with more than 20 years of age are like old elephants, trying to move through a very crowded place. They are heavy, and slow. They have lots of “excess baggage”8 (bear with me), which they would like to get rid of, but they cannot.

New companies do not have these problems. They are agile. They can hire the best, and only the best from the start. They encourage automation, rather than resist it. They deploy all possible strategies to increase productivity; that is, the revenue per employee. Look at Table 1.3 again. McDonald’s was founded in 1940, and the revenue per employee is $60,000. As we move towards present times, we see a progressive decrease in the numbers of workers (except for Walmart, but we saw before how that is likely to change pretty soon), and an increase in the amount of wealth that each employee creates. The last and most striking values are represented by Facebook, with a mere 3,000 workers, where each one is creating more than $1.4 million of wealth for the company. One could dismiss Facebook as just vapourware, a fashion that will soon be phased out. But consider this. In today’s economy, one of the most valuable assets is not represented in physical goods. It is information. Personal information about us, our habits, our wishes. Who our friends are, who we date, what we think. We have become the product. Facebook has the most extensive database of personal information ever created in history, approaching 1 billion users worldwide, and growing. Governments, companies, and intelligence services long for that information. In fact, there is a significant amount of speculation that Facebook may be selling our personal information to such institutions for profit,9 even though Facebook has rejected such claims.10 Regardless of the veracity of these accusations, it is without a doubt that Facebook has an intrinsic value much greater than its total revenue. A number that is already impressive on its own, considering how little time it took to reach $4.27 billion, with just 3,000 employees.

So if new industries only need highly educated, smart, and dynamic people; and old industries are replacing human workers in favour of automation; what will you do with the millions of those who have no formal education and do not have the means to even start learning sophisticated skills?

I noticed two types of reactions from economists when confronted with this very simple question. The first type does not see the problem to begin with. They do not believe technology is displacing human labour, so they do not even begin the discussion. The second type claims that people who make such arguments should spend less time talking about what they do not know, and more time doing what they are good at instead. They say that people like Martin Ford or myself are simply ignorant of economics, and that if we were economists we would know better. That may be true. After all, we are not economists. And we might be wrong. But that is not an argument, it is circular thinking, a self-reinforcing tautology with no substance. If you think you have a better argument, and you stand by it, then please present it and enlighten us. I asked many economists, and I am still waiting for such arguments to be brought up to me.

The refusal to explain is probably because they feel like this is basic economic theory, things that I should have learned in academia, and there is no point in wasting time explaining it. But whenever I hear this kind of reasoning, I am reminded of what the great Albert Einstein said11 :

“If you can’t explain it simply, you don’t understand it well enough.”

With years of experience in spreading scientific education and debunking climate change deniers, creationists, and all sorts of nonsense, I can see how Einstein’s quote could not be truer. If mainstream economists see me as I see proponents of “intelligent design”, it should be pretty easy to refute what I say. In fact, it should be quick to dismiss my claims with a few simple examples. After a year of research and discussion, I am still waiting for them.

Marshall Brain, author of Robotic Nation, gave a talk about job displacement due to automation at the Singularity Summit 2008. At the end of his presentation, he was ridiculed by one of the other speakers: “Have you ever heard of this discipline called history? We’ve gone through the same crap 150 years ago, and none of what you say has happened!”. This is the sort of easy criticism that uneducated people make very lightly: it did not happen in the past, why should it happen now?

First of all, there simply is no historical precedent for what we are about to experience. While it is true that we found ways to change occupation by inventing new jobs and new sectors altogether, there are two crucial aspects to consider.

One. There is a physical limit to what the human brain is capable of. Sure, our brains are very plastic12 and with training can greatly improve over time. But just as our physical strength, however much we may train, has been greatly surpassed by that of machines, so will our mental faculties. Biological evolution is simply too slow compared to the speed of growth of artificial and machine intelligence. Eventually this might change, but only if we allow ourselves to be “enhanced” by machines by merging with them. But I do not want to get into that discussion, which would require a book of its own just for the technical aspects, let alone the ethical implications. Let us stay focused and grounded: we know that the second technology-enabled species (intelligent machines) is coming, and unless we prepare ourselves, we are going to be in trouble.

Two. Have we ever considered the possibility that finding a job replacement, no matter what, might be the wrong choice to begin with? I’m sure that potentially we can come up with millions of all sorts of useless jobs in the future. Just a glance at what we have accomplished in the last 50 years should be enough make that argument very credible indeed. We have long since decoupled the usefulness of a job with its purpose. Historically, the purpose of jobs has been to make what we need to live better: food, clothing, houses, roads, cars, et cetera. But as productivity increased exponentially, we could have easily got those things by working less. Please note that this is not an ideology, nor it is wishful thinking. It is mathematics. Suppose you require x amount of labour to produce y level of wealth. Then, after 50 years, you only need 1/10 of x to produce the same y. It is a logical inference that you can work less to produce the same as before. Obviously the workload cannot be reduced at exactly the same proportion because advancing technologies also increased our expectations as standard of living rises. But the necessities of life have barely changed at all. We do not need 100 times the amount of food, water, and housing that we did 50 years ago. We could have easily reduced the work week. Instead, we work more than ever before, on average. This is pure madness: the purpose of technology was to free our time so that we could dedicated it to higher purposes. Instead, our jobs have become the purpose.

In the past, jobs have been outsourced to China, India, Vietnam, and other places where people compete for jobs that in the US and in Europe would be considered slavery. We are talking about jobs that pay $200 a month for a 12 hour per day, 6 to 7 days per week. And people there aspire to get these jobs. They have little to no insurance, benefits, vacation, no safety rules, no right to complain. Sure, if you work there and you do not like it you can always leave the job, but somebody else will gladly take your place. It should be clear that we cannot think to outcompete them with a race to the bottom, by bringing manufacturing jobs back here at lower prices. It simply is not going to happen, nor should it. The days when a high school education, a lot of good will, and hard work got you a decent middle-class lifestyle are long gone. Those jobs that have been outsourced are not coming back, period. And even those overseas jobs are now threatened by the rapid advances in automation and robotics. The more companies automate, because of the need to increase their productivity, the more jobs will be lost, forever.

More than ever, the future of work and innovation is unfamiliar territory. New and exciting fields are emerging every day. Synthetic biology, neurocomputation, 3D printing, contour crafting, molecular engineering, bioinformatics, life extension, robotics, quantum computing, artificial intelligence, machine learning, these new frontiers that are rapidly evolving and are just the beginning of a new, amazing era of our species that will bring about the greatest transformation of all time. A transformation that will make the industrial revolution look like an event of minor importance. This new era will create new opportunities, new frontiers for research and innovation that we cannot even begin to comprehend now. I have no doubt about that.

The problem is this: will we be able to keep up with such rapid changes and educate the millions of workers with no formal education for these new types of jobs? I think the answer is a big and loud NO.

There are millions of workers with a high school education at best, and sometimes not even that, who are over 40 years old who only know how to do either manual labour or jobs easy to automate. Any new job that we can come up with will employ a fraction of those people, at best. And these jobs will require a highly receptive, flexible mind, with profound knowledge of highly sophisticated subjects related mostly to the fields of biology, chemistry, computer science, and engineering. It can take 5 to 10 years to educate a young mind in these fields, and we are talking about a mind that is not only willing to learn, but that is also enthusiastic about the learning experience. How many of the millions of middle-aged, unemployed people are willing to reinvent themselves and start anew? And how many of those is the educational system able to accommodate? At what price? Even assuming that most of them do find the intrinsic motivation, how many can afford the time and the money required to upgrade their knowledge and skills? Most countries can barely manage to educate their children, and even so in most cases with disastrous results. I find it hard to believe that the government will magically find a way to make university-level education free for all, including the millions of new students that will suddenly have to go back to school at 50 years old.

The idea that society can keep up the number of jobs given the exponential expansion of technology, the rise of automation, and the widespread development of cheap personalised home manufacturing, is simply unrealistic. I have read several books, watched hundreds of debates and interviews on this subject, and I have not so far heard a single argument to support the idea that we can make this work, or how.

Technological marvels like Watson are now starting to make even the hardcore skeptics suspicious.

The old jobs are not coming back. The new jobs will be highly sophisticated, technically and creatively challenging jobs, and only a handful of them will be needed. The question is simple: what will the unskilled workers of today do? So far, nobody has been able to answer that question. The reason for this, I think, is because there is no answer. Not in this system, not in the way it is designed to work.

I think that if we want to solve this most challenging problem of our time, we will have to rethink our whole economic and social structure. Rethink our lives, our roles, our purposes, our priorities, and our motivations. It is time for a paradigm shift, one that will radically revolutionise our social system. In this universe, change is the only constant. Learn to love it, embrace it, and you will succeed. Fail to predict it, resist it, and you will be swept away by the torrent of change that is about to crush our civilisation as we know it.

At this point you might be wondering, will not these highly sophisticated and technically challenging jobs be automated, eventually? Given what we have learned about exponential expansion of technologies, the logical answer would be: yes, most of them. Surely we will create new fields of research, and new jobs will follow accordingly. But these new jobs will be even more difficult, and the percentage of population apt to those will be narrower and narrower every time, given that the ability for technology to self-innovate is greater and faster than our ability to keep up with it. So this is a dog chasing tail argument, the total number of jobs required by industry will be gradually reduced over time, and each time we will have to reinvent ourselves, finding new occupations for the newly displaced people by automation.

This becomes very tiring after some time. It is a game you cannot win. It is unfair, and there is no way out. One begins to wonder if this is the only way, or if there might be another solution. In the next part, we will explore many candidates in solving this problem of utmost importance. We do not know yet which will be the correct one. Maybe none, maybe it will be a combination of all of them. Nobody knows for sure.

What we know is that we will strive to find the best solutions, using our reason and our imagination. We may not succeed, we may even fail miserably in the process. But we could also prevail, facing any obstacle with courage and strength, looking into the future, advancing and evolving, and I feel that we can only achieve that if we share a common goal.

To paraphrase Martin Luther King Jr. and Carl Sagan:

“We are one planet, we must learn to live together as a family or perish alone as fools.”


1 Employed persons by detailed occupation, sex, race, and Hispanic or Latino ethnicity. Bureau of Labor Statistics.

2 Employment Situation Summary. Bureau of Labor Statistics.

3 Employment status of the civilian noninstitutional population, 1940 to date. Bureau of Labor Statistics.

4 Eurozone Unemployment Hits 10.9%, A Record High, 2012. Huffington post.

5 The 86 million invisible unemployed, Annalyn Censky, 2012. CNNMoney.

6 Ken Robinson says schools kill creativity. Ken Robinson, 2006. TED Global.

7 Sir Ken Robinson: Bring on the learning revolution!, Ken Robinson, 2010. TED Global.

8 I obviously do not think people are “excess baggage”, quite the opposite. But in the eyes of a multinational corporation inefficient workers mean loss of profit, and this is what they ultimately mean to them. Very few enlightened companies value people over profits.

9 Facebook faces EU curbs on selling users’ interests to advertisers, Jason Lewis, 2011. The Telegraph.

10 Does Facebook sell my information?. Facebook.

11 Albert Einstein quotes. ThinkExist.

12 Neuroplasticity refers to the susceptibility to physiological changes of the nervous system, due to changes in behaviour, environment, neural processes, or parts of the body other than the nervous system. It occurs on a variety of levels, ranging from cellular changes due to learning, to large-scale changes involved in cortical remapping in response to injury. The role of neuroplasticity is widely recognised in healthy development, learning, memory, and recovery from brain damage. Recent findings revealing that many aspects of the brain remain plastic even into adulthood.


  • Pascual-Leone, A., Freitas, C., Oberman, L., Horvath, J. C., Halko, M., Eldaief, M. et al. (2011). Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI. Brain Topography, 24, 302-315.
  • Pascual-Leone, A., Amedi, A., Fregni, F., & Merabet, L. B. (2005). The plastic human brain cortex. Annual Review of Neuroscience, 28, 377-401.
  • Rakic, P. (January 2002). Neurogenesis in adult primate neocortex: an evaluation of the evidence. Nature Reviews Neuroscience.

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