AI Job Feast or Famine?

The Rise of AI

As you’ve no doubt heard, read, or wondered about, with the rapid onset of AI and the exponential rate of development in its ascension to a dominant and economically pervasive technology – perhaps even one day achieving its own form of sentience – you’re probably asking what’s the present reality that we’re about to enter into and should I be worried about the what the whole new paradigm in the evolution of the human workforce will mean for me?

Firstly, and in the past, with every great technological leap or automation, it was mainly blue-collar workers that were impacted, and these same people aren’t going to be spared here.

In case you might not know where the term blue-collar worker came from, I’d like to take a second to remind everyone of its origins.

It was derived from those that worked jobs that were manual in nature and required an expenditure of physical energy and thereby generated sweat that would get absorbed into their collars that would cause stains, especially along the neckline.

As you washed these shirts, more often than not the discoloration was never truly able to be removed, and over time the entire collars themselves would turn a sort of faded blackish blue. There was even a laundry detergent in the 70’s called Wisk whose entire marketing campaign was built around the promise of getting rid of unsightly ring around the collar.

And this was important because the color of your collar was about way more than just a few collar stains. You see, there was a great social stigma that was prevalent in the business world from the 1800’s through to the 1990’s when people used to always wear suits and other formal attire to the office and a person’s character and position could be as easily measured by the crisp sharpness of their pristine white collars as from the framed diplomas of achievement hanging on their corner suite walls. Because, if you worked in an office, and you wore a clean white shirt, this placed you in a caste above the workers that toiled below you. You were a manager, an owner, a lawyer, a doctor, a person who made their fortunes with their brains and not their brawn. It also meant that your wealth and status could afford you the finer things in life.

Historical Impact of Automation on Blue-Collar Jobs

Now, with almost all of the technological advances that have taken place over the last 250 years since the dawn of the industrial revolution, when millions of people moved away from their farms and onto factory floors, the people that were always the most impacted by virtually every technological change were the blue-collar workers.

By the simple fact that these sorts of jobs were the most repetitious and the easiest to replicate with machinery, meant that these workers were often easily replaced and displaced, but luckily, given the ubiquitous need for manual labor, they were usually able to move into a different line of physical work, until automation once again caught up with them and forced them to move on.

The Lump of Labor Fallacy

Now, whenever we talk about technology replacing people, there’s always some genius that wants to drag from the closet a theory called the “Lump of Labor Fallacy”.

It’s also known as the “fallacy of labor scarcity,” “lump of jobs fallacy,” a “fixed pie fallacy,” or the “zero-sum fallacy.” But basically, a potato is a potato is a potato no matter what you call it.

The fallacy begins with the faulty assumption that an economy can only support so many jobs. It’s the mistaken belief that there’s a fixed amount of work available, and that things like increasing the amount of workers decreases the amount of work available for everyone else.

It’s also one of those chestnuts that gets pulled out to dissuade people from supporting immigration because the argument goes that more foreign workers will mean less jobs for native workers.

It was a huge pivot point in the fear that motivated Brexit. But what it fails to take into account is that with the increase in foreign workers, and the subsequent increase in demand for goods and services, that the job market actually grows instead of contracting.

But try explaining that to the average 65-year-old or older voter who cast their ballot, and proved to be a decisive factor in the vote to leave as they arrived at the polls in record numbers with the reminders of WWII still fresh in many of their minds.

The same kind of fallacy of labor scarcity thinking has gone into economies such as in France in the year 2000. That was when they implemented a restriction in working hours for people moving it down from a regulated 39 to 35 hours per week in the belief that these reductions in hours would force companies to have to hire more people to fill in for the labor shortfall because a new person would be cheaper to hire than paying for overtime and that this would subsequently reduce the national unemployment.

What they found instead was that people now had to often take two jobs to make ends meet, that many workers in large firms simply moved to smaller firms that weren’t subject to the new laws, and that as the affected firms had to pay staff more money to make up for wage/hour shortfalls, that many instead simply fired workers and replaced them with lower paid staff.

So, while the employment of those people directly affected by the law declined, on the aggregate the hope for overall increased employment in the country barely moved the needle in reducing unemployment. While an arguable failure in the eyes of many, it still doesn’t mean that France is continuing to consider making a 32-hour work week compulsory, effectively looking to double-down on the theoretical speculations of the past.

Whatever form they may want to dress it up as, the Lump of Labor Fallacy was first conceived in 1891 by a British economist by the name of David Frederick Schloss, who postulated that there was not a fixed amount of work available in the economy and that markets would always grow to create more employment.

He came across the idea when he was passed by a dockworker that was using a machine to rapidly make small metal washers that were used along with screws and nuts, and were vital in shipbuilding.

His more than 20-fold increase in productivity had made the worker quite upset. When Schloss asked him why he was concerned about being more productive, the worker replied that he knew in his heart that he was doing wrong because by being so fast he was taking a job away from another man.

To this worker’s way of thinking, there was a fixed amount of work to be divided up between him and his friends, and because he used this machine to do more of the task, there’d be less work for his friends to be able to do and somebody would lose a job.

Schloss immediately saw the err in the man’s thinking because, as an economist, he realized that as more washers were made and more quickly than ever, that the price of washers would fall and that this would create increased demand and that as a result of automation, there’d be more work for his friends to do as demand increased.

In other words, the “lump” of work would get bigger, and Schloss went on to call this worker’s misguided notion the “Lump of Labor Fallacy”.

However, fear about the limited size of available jobs and what changes technology might bring is not new.

Historical Fears of Technological Advancement

As far back as Aristotle in ancient Greece, he argued that,

{sic} “the human condition largely depends on what machines can and cannot do; moreover, we can imagine that machines will soon be able to do much more. If machines did more of our work, everyone, even slaves, would be freer.”

1589, Queen Elizabeth of England refused to grant the inventor, William Lee of Calverton, a mechanical knitting machine a patent, afraid that it would cause an uprising by putting scores of the nation’s knitters out of work.

And she might not have been entirely wrong, because the original Luddites, who were highly skilled weavers and textile workers in Britain during the time of the industrial revolution took up arms in violent riots objecting to the use of mechanized looms and knitting frames, especially since they were highly trained artisans who had spent years learning their craft, often under long and unpaid apprenticeships, and were properly concerned in thinking that unskilled machine operators would soon be able to easily and more cheaply rob them of their livelihoods.

Even the famous economist John Maynard Keynes in his 1930 discourse titled; “Economic Possibilities for our Grandchildren”, pontificated about the concept of “technological unemployment” and defined it as, “unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor,” and that “the increase of technical efficiency has been taking place faster than we can deal with the problem of labor absorption”.

In other words, and as an article in Nation’s Business in 1927 had earlier coined it, he was describing something called, “Job Famine.”

So now, whenever a new technology comes along, we hear people complaining about the available “lump” of work available being reduced and usually with all the dire consequences that will come with it.

And yes, the machines make the lump being replaced smaller, but in the past these machines also complimented people and the new “lump” of work actually got bigger as it changed the dynamics of the workplace and created spin-offs.

History provides an interesting example of automation displacing labor if we go back to the year 1900 when 41 percent of the U.S. workforce worked in agriculture. After a hundred years of technological and automation change in that industry, the number stood at 2 percent by the year 2000.

There’s no doubt that this transformation changed the work of farmers in dramatic ways, but interestingly it didn’t reduce the total employment in the United States.

As it happens, the mechanization of agriculture in the early twentieth century made it possible for the large increase in employment in new industries and factory jobs, including the rapidly growing farm equipment industry as well as cotton milling.

So, while automation can be a substitute for labor, it’s often also a complement to labor.

But this was the historical model.

Because now, in a great many cases, the added lumps of labor that are created by the complements to labor, created by the technological innovations of AI that displaced the original industries, are also now themselves being almost immediately replaced with more machinery and AI technology to replace the newly formed complementary tasks.

The machines displacing human workers are creating new jobs, as previously was the case, but now new machines are quickly rising up to fill those newly created jobs.

AI: A Real Threat to White-Collar Workers

And for the first time in history, the workers that are being the most impacted by these new advances in AI, are white-collar workers.

And this is a whole new ball of wax.

Let me give you an example of AI impacting the white-collar workplace even in my own world.

Owning a few ventures and always on the lookout for more, I’ve had to use the services of a lawyer virtually daily for years and years to make sure that I’m always on the right side of any legalities, either here or some other place in the world where the rules and regulations can sometimes greatly differ.

I believe in due diligence, dotting my i’s and crossing my t’s, and this was always a necessary evil.

But lately, because practically all of the law has been automated, consumed, digested, interpreted, adapted, and able to be dispensed by my ChatGPT AI app, and that can usually better answer my questions than a human lawyer is able to – especially as it has within its computer memory finger-tips the entirety of every law and case study and real world application ever written and ruled upon – I find that unless the task is especially complicated or may require the application of new laws, that by entering the right prompts, my AI has just about entirely replaced the need for having a lawyer on constant standby.

And that’s a straight up boon to my business. The speed at which I can get responses, the case laws that might be applicable, as well as the significant reductions to my bottom-line expenses, allows me to better manage my time and my resources.

Yet, where this has been good for me, I pity the lawyers whose phones aren’t ringing or that haven’t already adapted by integrating AI into their practices to better facilitate their abilities, because the ones that haven’t are about to be replaced and tossed to the roadside of the obsolescence.

I also have great pity for anyone even remotely considering a degree in large swaths of the legal profession because there won’t be jobs for them when they graduate as a faster, smarter, and more resilient AI has already taken up residence in what might have been their cubicle, and that cubicle will be located rent free in the cloud.

That’s the thing with this AI revolution; it’s not like any of the technological revolutions that have come before it.

The Economic Potential of Generative AI

A report by McKinsey and Company, a global management consulting firm that works with leading businesses, governments and influential institutions, estimates that

“Generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases that they analyzed. By comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15 to 40 percent.” They also suggest that their “estimate would roughly double if they included the impact of embedding Generative AI into software that’s currently used for other tasks beyond the use cases that they focused on.”

Their report goes on to say that

“Current Generative AI and other technologies have the potential to automate work activities that absorb 60 to 70 percent of employees’ time today. And that their updated adoption scenarios, including technology development, economic feasibility, and diffusion timelines, lead to estimates that half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045, or roughly a decade earlier than in our previous estimates.”

Take a moment to read through what that last statement’s saying, that 50% to 70% of employees could soon be made redundant. And while that might be good for a company’s bottom line, just who’s going to be around to have the money to buy the company’s products if 70% of the working population is in a bread line?

In the early 1960’s and especially in the 1970’s, industrial automation such as robotics in the automotive sector changed the industry and its workplace forever, so much so that from a labor force of tens of millions in the U.S. alone, it’s now shrunk to 1.7 million people, and it’s continuously getting smaller as auto manufacturing factories such as the Gigafactory operated by Tesla in Austin Texas can operate its 2,500 acre manufacturing facility with as few 3,523 people unless more are needed to compensate for significantly added demand, but even then, and operating at near capacity, only about 12,277 people are needed to cover the round the clock shifts year-round.

But these were manufacturing jobs and a factory is often a factory, and people adapted and found other factories or other forms of manufacturing blue-collar work in less technologically adept industries.

But Generative AI, although it will displace at least 20 million manufacturing jobs in the United States by the year 2030, isn’t really coming primarily for these factory jobs as a fair chunk of them have already been automated.

For the first time in global history, it’s a technology coming squarely for white-collar workers.

And unlike blue-collar workers who can often find similar pay at alternative factories, the opportunities for where white-collar workers go, once their jobs are replaced by AI, and then the complimentary offshoots of those jobs are then also replaced by AI, make this a very dangerous time to not have the tools available to be able to abandon the office and work in the trades.

Zippia Career Experts has recently released a report called, “35+ Alarming Automation & Job Loss Statistics [2023]: Are Robots, Machines, And AI Coming For Your Job?”

Its contents will melt your brain and be guaranteed to keep you awake at night.

Because while 20 million manufacturing jobs are about to give way to AI,

“Automation has the potential to eliminate 73 million other US jobs by 2030, which would equate to a staggering 46% of the current jobs.”

Now place yourself in that job market…

The Changing Labor Landscape: New Job Opportunities and Challenges

But all is not lost, since it’s estimated that 85% of the jobs that’ll exist in 2030 haven’t even been invented yet.

So there’s hope that the complementary industries that arise will help to fill the gap. But consider what that’ll mean when you’re 40 or 50 and have lost your job as a lawyer, accountant, graphic designer, procurement clerk, tax preparer, real estate broker, or even a correspondence clerk, and suddenly find yourself unemployed and having to totally abandon your years of education and career experience and have to go back to school to learn a skill for something that hasn’t even been imagined yet.

The World Economic Forum predicts that AI technology will create 97 million new jobs by 2025. They also predict that jobs specifically related to the development and maintenance of AI and automation will see the largest growth areas as AI integrates across multiple industries.

While it’s exciting to consider that new careers such as data detectives or scientists, prompt engineers, robotics engineers, machine managers, and programmers, particularly those who can code in Python which is key for AI development, as well as AI trainers and those with capabilities related to modelling, computational intelligence, machine learning, mathematics, psychology, linguistics, and neuroscience will probably be in high demand, ask yourself first of all what most of these jobs entail, and then ask how you’ll be able to re-educate yourself and re-position yourself in this new world against the onslaught of recent school graduates more eager, more adept with the technology, willing to work for lower wages, and who don’t have families and mortgages to support.

And the thing is, the genie’s already been let out of the bottle and the upcoming shift is going to happen at speeds unparalleled in human evolution and it’s going to leave a large swath of individual destruction in its wake.

Coping with Transition: From Humans to AI

Lay off almost 50% of the workforce and make the new jobs available require a level of sophistication and education better suited to people at the start of their careers instead of almost half way through, and it’s no wonder that jobs like occupational therapist, music therapist, rehabilitation physicians, art therapists, neurophysiologist, and rehabilitation physicians will be in high demand and also be the most unlikely to be affected by AI and automation.

They’re the jobs that require human-to-human interaction, and with 50% of the workforce in an anxiety-riddled state of flux, you’ll need almost 20 million of them to manage the mental disorders and breakdowns on the way.

As I’ve said a million times, I’m an optimist, a humanist, and a glass is always half full kind of person, and I’ve got huge confidence in what technology and the benefits that it offers will contribute to the evolution of our species.

But in this new transition of labor, forced to move from sometimes thousands of years old professions and into ones that haven’t even been invented yet, I believe that the road will be bumpy if not devastating for a great many individuals, with dire economic and sociological implications for all of us.

And this is only taking into consideration that the AI we use today and are expected to use for the next decade or so is Generative AI.

One Possible AI Future

Fifty years from now we may be living in an idyllic world managed, guided and maintained by AIs that allow us to free up our time to enjoy much of what life can fully offer, but between then and where we are now, there are going to be a great many casualties and self-inflicted fatalities before we can stabilize and settle into the new age of AI.

But now ask yourself this, what happens when a chatbot suddenly evolves and spontaneously develops a Theory of Mind and unexpectedly you’re forced to be in the midst of a meaningful conversation with an emotionally intelligent robot that looks and sounds like a real human being?

What will your role on the planet look like then?

It’s a tall technological order and it may never happen, or it could have already happened, or it could be less than a decade away…

– Written by a human.

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Michal Prywata: Inventor, entrepreneur, and multidisciplinary engineer with a focus on frontier technologies. Founder of ventures in healthcare, agriculture, space, and AI. On a relentless quest to solve complex problems and extend the boundaries of human potential.