DO ROBOTS CREATE JOBS?
A deeper look, and why it matters to you.
One of the biggest disagreements about the future of employment comes down to a tired and frustrating comparison, one that is almost willfully unconsidered.
It goes like this: we don’t have to worry about robots, because every time new technology replaces jobs it also creates new ones. This is an opinion widely held, even by government officials.
It reeks of the unimaginative and anti alarmist mentality of old people unwilling to take a serious look at the future. But The McKinsey Global Institute, the most secretive, expensive and prestigious of consultant think tanks, came out with a study in December 2017. The consulting firm has been researching what the Public and Private sector should expect from the effects of tech on employment from now until 2030, and it turns out it’s a little more complicated than that.
There are a ton of factors contributing to what the future of employment entails for an individual, and it depends heavily on three main factors:
Which Jobs?
Do you do a repetitive task inside? You are screwed. Actually.
It is called “Predictable Work in Predictable Environments” and it’s the first thing to go. Factory jobs. I’m looking at you, Ingersoll, On. As advancements in robotics and AI progress it is this low hanging fruit that will quickly be chewed up by the machine. But it doesn’t stop there, other jobs that include simply connecting a frequent problem with a frequent solution is also up for grabs. Paralegals, IT workers, office support staff, administrative assistants, financial workers including procurement and payroll, these are all threatened with replacement in developed countries.
One glaring example panning out right now is at McDonalds, where self serve kiosks have replaced cashiers in most locations. McDonalds has stated that this has allowed their cashiers to be redeployed in back of house operations, but since these jobs land directly in the “Predictable Work in Predictable Environments” category, and with demands for a 15$ minimum wage across the US and Canada, how long will that “redeployment” last? As companies start looking at places to cut costs, what we consider “living wages” will look too expensive, and as economists are predicting, force wages down to compete with machines.
What happens when those employees are pushed into other lines of work?
Where?
One major component of the 2016 US election was the issue of manufacturing jobs in the rust belt region. Once juggernauts of American economic muscle, employment in these areas has been gutted in favour of globalized manufacturing and technological advancements. So what happened when people no longer had any job prospects? They stayed put. It is a relatively new feature of the job economy that people stay embedded in their communities even when there is no work. Given the precarious nature of work these days, most people aren’t willing to risk uprooting themselves for that level of uncertainty.
A drastic comparison between the old economy and the new economy, someone could compare the rust belt with silicon valley, with the rust belt decaying and silicon valley thriving. People are not uprooting from one and moving to the other because that requires financial security, skills retooling, and capability/willingness to learn those new skills. Instead people commonly give up looking for work, take unemployment benefits, and leave the work force.
This has led to political upheaval in many manufacturing centres, demanding the return of times long past.
When?
This is the biggest issue that confuses how people think about the problem. It is time that bridges both the “robots kill jobs” and “robots make jobs” arguments.
To be fair, there are somethings that robots do better than people and some things they do worse. There are also somethings that they do worse—that, in time, they will do better.
The McKinsey Global Institute places a premium on how long it takes for people to adapt to the demands of the changing economy. Their low estimates for a slow transition to automation puts 75 million jobs at risk globally between now and 2030 (Many other studies put jobs at risk of automation at much higher levels, but remember, the scope of this research covers only to 2030).
To counter balance this risk of job loss, three main areas of job growth in Canada and USA predicted by the study are as follows:
Care Providers - Doctors, nurses, physicians assistants, pharmacists, therapists, health aides, health technicians, childcare workers, community and social workers are needed for our growing healthcare demands and aging population.
Builders - Engineers, architects, construction workers, surveyors are needed for building new infrastructure
Technology Professionals - Computer Engineers and computer specialists
But, a fast adoption of automation puts that estimate at 375 million globally between now and 2030, thats more than the entire population of the United States. A large number of those jobs are the kind held in Canada and the USA, placing them both at a median estimate of 25% of jobs at risk in the next 12 years.
They candidly added that retooling a work force effectively on this scale would require an effort comparable to the Marshall Plan, aka cleaning up WW2.
So What?
Here’s the real question. How adaptable are most people?
A great example of a retooling work force is found in the new market of coding boot camps. I’ve dabbled in them myself and I can tell you almost everyone is there because their first choice of work didn’t pan out. Turns out the job market for liberal arts students doesn’t pay well. And these developer programs are really effective, people are funnelled through these programs quickly and handed off to companies that need them in a matter of months.
If you’re a fan of John Oliver’s “Last Week Tonight”, you might have seen the episode on coal, where an out of work coal miner learned how to become a developer through a community program to retool people in the changing job economy. How many people in the coal industry do you think will become a coder? They could only find one.
So What Do We Do?
As Richard Thaler (Nobel Prize winner for his work in behavioural economics) says in he research, when it comes to decisions people make infrequently, maybe even once in their lives, with long periods before they see the results, they often choose badly. This applies to mortgages, marriages, and yes career paths.
Lets take a page out of his book and suggest a government standardized information sheet for every university and college program that would state in simple terms the career applications for the program, current demand for these jobs, and susceptibility to automation. All of this information would be openly available, in standardized format, affording a clearer picture of where a student may stand upon graduation. Maybe we can go even further and incentivize programs for careers in demand with a sliding scale of government subsidy, with higher funding according to greater demand. But of course this doesn’t apply to everyone.
Your 39 year old box folder, who just lost her job to automation, will need fast retooling, and as we said before, she may find this too costly, and quickly fall out of the work force and end up on unemployment.
Germany has already dealt with this problem. Obviously. *eye roll*. The German apprenticeship program is the envy of the world, allowing Germany to experience its lowest level of unemployment in 37 years through cooperation between unions, government and companies to train people in the skills that are in demand. Maybe this could be emulated elsewhere, even Trump suggested something like that for the US.
In a story last year the CBC’s sources said that Canadian Government is looking into ways to help guide workers to jobs that are in demand, but “Predicting the future brings significant risk”, and officials believed that new jobs will replace old jobs because “thats just how economics works.”
Well officials will be relieved to know that they won’t have look much beyond the present to see evidence that this is already a problem. In the mean time we can expect more people with more precarious incomes, and the political consequences like Trump that come with it.
Jack Ma, the CEO of Alibaba, gave some pretty good advice at DAVOS in January. He says we’d all better get used to it, maybe learn to paint.
It goes like this: we don’t have to worry about robots, because every time new technology replaces jobs it also creates new ones. This is an opinion widely held, even by government officials.
It reeks of the unimaginative and anti alarmist mentality of old people unwilling to take a serious look at the future. But The McKinsey Global Institute, the most secretive, expensive and prestigious of consultant think tanks, came out with a study in December 2017. The consulting firm has been researching what the Public and Private sector should expect from the effects of tech on employment from now until 2030, and it turns out it’s a little more complicated than that.
There are a ton of factors contributing to what the future of employment entails for an individual, and it depends heavily on three main factors:
Which Jobs?
Do you do a repetitive task inside? You are screwed. Actually.
It is called “Predictable Work in Predictable Environments” and it’s the first thing to go. Factory jobs. I’m looking at you, Ingersoll, On. As advancements in robotics and AI progress it is this low hanging fruit that will quickly be chewed up by the machine. But it doesn’t stop there, other jobs that include simply connecting a frequent problem with a frequent solution is also up for grabs. Paralegals, IT workers, office support staff, administrative assistants, financial workers including procurement and payroll, these are all threatened with replacement in developed countries.
One glaring example panning out right now is at McDonalds, where self serve kiosks have replaced cashiers in most locations. McDonalds has stated that this has allowed their cashiers to be redeployed in back of house operations, but since these jobs land directly in the “Predictable Work in Predictable Environments” category, and with demands for a 15$ minimum wage across the US and Canada, how long will that “redeployment” last? As companies start looking at places to cut costs, what we consider “living wages” will look too expensive, and as economists are predicting, force wages down to compete with machines.
What happens when those employees are pushed into other lines of work?
Where?
One major component of the 2016 US election was the issue of manufacturing jobs in the rust belt region. Once juggernauts of American economic muscle, employment in these areas has been gutted in favour of globalized manufacturing and technological advancements. So what happened when people no longer had any job prospects? They stayed put. It is a relatively new feature of the job economy that people stay embedded in their communities even when there is no work. Given the precarious nature of work these days, most people aren’t willing to risk uprooting themselves for that level of uncertainty.
A drastic comparison between the old economy and the new economy, someone could compare the rust belt with silicon valley, with the rust belt decaying and silicon valley thriving. People are not uprooting from one and moving to the other because that requires financial security, skills retooling, and capability/willingness to learn those new skills. Instead people commonly give up looking for work, take unemployment benefits, and leave the work force.
This has led to political upheaval in many manufacturing centres, demanding the return of times long past.
When?
This is the biggest issue that confuses how people think about the problem. It is time that bridges both the “robots kill jobs” and “robots make jobs” arguments.
To be fair, there are somethings that robots do better than people and some things they do worse. There are also somethings that they do worse—that, in time, they will do better.
The McKinsey Global Institute places a premium on how long it takes for people to adapt to the demands of the changing economy. Their low estimates for a slow transition to automation puts 75 million jobs at risk globally between now and 2030 (Many other studies put jobs at risk of automation at much higher levels, but remember, the scope of this research covers only to 2030).
To counter balance this risk of job loss, three main areas of job growth in Canada and USA predicted by the study are as follows:
Care Providers - Doctors, nurses, physicians assistants, pharmacists, therapists, health aides, health technicians, childcare workers, community and social workers are needed for our growing healthcare demands and aging population.
Builders - Engineers, architects, construction workers, surveyors are needed for building new infrastructure
Technology Professionals - Computer Engineers and computer specialists
But, a fast adoption of automation puts that estimate at 375 million globally between now and 2030, thats more than the entire population of the United States. A large number of those jobs are the kind held in Canada and the USA, placing them both at a median estimate of 25% of jobs at risk in the next 12 years.
They candidly added that retooling a work force effectively on this scale would require an effort comparable to the Marshall Plan, aka cleaning up WW2.
So What?
Here’s the real question. How adaptable are most people?
A great example of a retooling work force is found in the new market of coding boot camps. I’ve dabbled in them myself and I can tell you almost everyone is there because their first choice of work didn’t pan out. Turns out the job market for liberal arts students doesn’t pay well. And these developer programs are really effective, people are funnelled through these programs quickly and handed off to companies that need them in a matter of months.
If you’re a fan of John Oliver’s “Last Week Tonight”, you might have seen the episode on coal, where an out of work coal miner learned how to become a developer through a community program to retool people in the changing job economy. How many people in the coal industry do you think will become a coder? They could only find one.
So What Do We Do?
As Richard Thaler (Nobel Prize winner for his work in behavioural economics) says in he research, when it comes to decisions people make infrequently, maybe even once in their lives, with long periods before they see the results, they often choose badly. This applies to mortgages, marriages, and yes career paths.
Lets take a page out of his book and suggest a government standardized information sheet for every university and college program that would state in simple terms the career applications for the program, current demand for these jobs, and susceptibility to automation. All of this information would be openly available, in standardized format, affording a clearer picture of where a student may stand upon graduation. Maybe we can go even further and incentivize programs for careers in demand with a sliding scale of government subsidy, with higher funding according to greater demand. But of course this doesn’t apply to everyone.
Your 39 year old box folder, who just lost her job to automation, will need fast retooling, and as we said before, she may find this too costly, and quickly fall out of the work force and end up on unemployment.
Germany has already dealt with this problem. Obviously. *eye roll*. The German apprenticeship program is the envy of the world, allowing Germany to experience its lowest level of unemployment in 37 years through cooperation between unions, government and companies to train people in the skills that are in demand. Maybe this could be emulated elsewhere, even Trump suggested something like that for the US.
In a story last year the CBC’s sources said that Canadian Government is looking into ways to help guide workers to jobs that are in demand, but “Predicting the future brings significant risk”, and officials believed that new jobs will replace old jobs because “thats just how economics works.”
Well officials will be relieved to know that they won’t have look much beyond the present to see evidence that this is already a problem. In the mean time we can expect more people with more precarious incomes, and the political consequences like Trump that come with it.
Jack Ma, the CEO of Alibaba, gave some pretty good advice at DAVOS in January. He says we’d all better get used to it, maybe learn to paint.