Humans Will Soon Be Unemployable

Physical Labor

When you think of automation, you probably think of this:

Giant, custom-built, expensive, and efficient, but really dumb robots, blind to the world and their own work. They’re a scary kind of automation, but they haven’t taken over the world because they’re only cost-effective in narrow situations. They’re the old kind of automation.

This is the new kind:

Meet Baxter. Unlike those dumb robots, which require skilled operators and technicians and millions of dollars, Baxter can learn what you want him to do by watching you do it, and costs less than the average annual salary of a human worker. Unlike his older brothers, he isn’t pre-programmed for one specific job. He can do whatever work is within the reach of his arms. Baxter is what might be thought of as a general purpose robot, and general purpose is a big deal.

Think about computers. They, too, started out highly custom and highly expensive. But when cheap-ish general purpose computers appeared, they quickly became vital to everything. A general purpose computer can just as easily calculate change, assign seats on an airplane, or play games just by swapping its software. This huge demand for computers of all kinds is what makes them both more powerful and cheaper every year.

Baxter today is the computer of the 1980s. He’s not the apex, but the beginning. Even if he’s slow, his hourly cost is pennies worth of electricity while his meat-based competition costs minimum wage. A tenth of the speed is still cost-effective when it’s a hundredth the price. And while Baxter isn’t smart as some of the other robots you’ll read about here, he’s smart enough to take over may low-skilled jobs. And we’ve already seen how dumber robots than Baxter can replace jobs. In supermarkets, what used to be 30 humans is now one human overseeing 30 cashier robots.

Or take the hundreds of thousands of baristas employed worldwide. There’s a barista robot coming for them. Sure, maybe your guy makes the perfect double-mocha-whatever and you’d never trust anyone else, but millions of people don’t care and just want a decent cup of coffee. (And, by the way, this robot is actually a giant network of robots that remembers who you are and how you like your coffee, no matter where you are. Pretty convenient, huh?)

We think of technological change as the fancy new expensive stuff —like the International Space Station — but the real change comes from last decade’s stuff getting cheaper and faster. That’s what’s happening to robots now. And because their mechanical minds are capable of decision-making, they are out-competing humans for jobs in a way no pure mechanical muscle ever could.

Luddite Horses

Imagine a pair of horses in the early 1900s talking about technology. One worries all these new mechanical muscles (cars) will make horses unnecessary. The other reminds him that everything so far has made their lives easier. Remember all that farm work? Remember running coast to coast delivering mail? Remember riding into battle? All terrible. These new city jobs are cushy (like giving carriage rides in New York City’s Central Park) and with so many humans in the cities there will be more jobs for horses than ever. Even if this car thing takes off, there will be new jobs for horses we can’t even imagine.

But you, dear reader, know what happened. There are still working horses, but nothing like before. The horse population peaked in 1915, and it’s been all downhill since then. There isn’t a rule of economics that says “better technology makes more better jobs for horses.” (It sounds shockingly dumb to even say that out loud.) But swap horses with humans and suddenly people think it sounds right.

As mechanical muscles pushed horses out of the economy, mechanical minds will do same to humans. Not immediately, not everywhere, but in large enough numbers and soon enough that it’s going to be a huge problem if we’re not prepared.

And we’re not prepared.

You, like the second horse, may look at the state of technology and think it can’t possibly replace your job. But technology gets better, cheaper, and faster at at rate biology can’t match. Just as the car was the beginning of the end for the horse, so now does the car show us the shape of things to come.

Automobiles

Self-driving cars aren’t the future; they’re here, and they work. Self-driving cars have traveled hundreds of thousands of miles up and down the California coast and through cities — all without human intervention. The question is not if they’ll replace cars, but how quickly.

They don’t need to be perfect. They just need to be better than us. (Human drivers, by the way, kill 40,000 people per year just with cars in the United States.) Given that self-driving cars don’t blink, don’t text while driving, don’t get sleepy, and don’t get stupid, it’s easy to see them being better than humans because they already are.

To describe self-driving cars as cars at all is like calling the first cars mechanical horses. Cars in all their forms are so much more than horses that using that name limits your thinking about what they can even do.

Let’s call self-driving cars what they really are. “Autos,” the solution to the transport-objects-from-point-A-to-point-B problem. Traditional cars happen to be human-sized to transport humans, but tiny autos can work in warehouses and gigantic autos can work in surface mines. Moving stuff around is who-knows-how-many jobs, but the transportation industry in the United States employs about 3 million people. Extrapolating worldwide, that’s something like 70 million jobs at a minimum.

These jobs are over.

The usual argument is that the unions will prevent it, but history is filled with workers who fought technology that would replace them, and the workers always lose. Economics always wins, and there are huge incentives across wildly diverse industries to adopt autos.

For many transportation companies, humans are about a third of their total costs, and that’s just salaries. Humans sleeping in their long-haul trucks cost time and money; accidents cost money; carelessness costs money. And if you think insurance companies will be against it, then guess what…their perfect driver is one who pays their small premiums and never gets into an accident.

The autos are coming, and they’re the first place where most people will really see robots change society. But there are many other places in the economy where the same thing is happening, albeit less visibly.

So it goes with autos, so it goes for everything.

The Shape of Things to Come

It’s easy to look at autos and Baxters and think technology has always gotten rid of low-skilled jobs we don’t want to do anyway. We’ll just get more skilled and do better educated jobs like we’ve always done. Even ignoring the problem of pushing a hundred million additional people through higher education, white collar work is no safe have, either.

If your job is sitting in front of a screen and typing and clicking — like maybe you’re supposed to be doing right now — the bots are coming for you too, buddy. Software bots are both intangible and way faster and cheaper than physical robots. Given that white collar workers are, from a company’s perspective, both more expensive and more numerous, the incentive to automate their work is greater than low-skilled work.

And that’s just what automation engineers are for. These are skilled programmers whose entire job is to replace your job with a software bot.

You may think even the world’s smartest automation engineer could never make a bot to do your job, and you may be right. But the cutting edge of programming isn’t super-smart programmers writing bots. It’s super-smart programmers writing bots that teach themselves how to do things the programmer could never teach them to do themselves. How that works is well beyond the scope of this article, but the bottom line is there are limited ways to show a bot a bunch of stuff to do, show the bot a bunch of correctly done stuff, and it can figure out how to do the job that needs to be done. Even with just a goal and no knowledge of how to do it, the bots can still learn.

Take the stock market — which, in many ways, is no longer a human endeavor. It’s mostly bots that taught themselves to trade stocks, trading stocks with other bots that taught themselves. As a result, the floor of the New York Stock Exchange is no longer filled with traders doing their day jobs. It’s largely a TV set.

Bots have learned the stock market, and bots have learned to write. If you’ve read the news lately, you’ve probably already read a story written by a bot. There are companies that teach bots (such as Quill) to write anything: sports stories, TPS reports, and even those quarterly reports that you write at work.

Paperwork, decision making, and writing. A lot of human work falls into those categories. And the demand for human mental labor in these areas going down.

But surely the professions are safe from bots, yes?

Professional Bots

When you think lawyer, it’s easy to think of trials. But the bulk of lawyering is actually drafting legal documents, predicting the likely outcomes and impacts of lawsuits, and something called discovery, which is where boxes of paperwork gets dumped on the lawyers and they need to find the pattern or the one out of place transaction among it all. This can be bot work.

Discovery in particular is already not a human job in many law firms. Not because there isn’t paperwork to go through — there’s more of it than ever — but because clever research bots shift through millions of emails and memos and accounts in hours, not weeks, crushing human researchers not just in terms of cost and time, but — most importantly — accuracy. Bots don’t get sleepy reading through a million emails.

But that’s the simple stuff. IBM has a bot named Watson. You may have seen him on TV destroying humans at Jeopardy. But that was just a fun side-project for him. Watson’s day job is to be the best doctor in the world: to understand what people say in their own words and give back accurate diagnoses. He’s already doing that at Sloan Kettering, giving guidance on lung cancer treatments.

Just as autos don’t need to be perfect — they just need to make fewer mistakes than humans — the same goes for doctor bots. Human doctors are by no means perfect. The frequency and severity of mis-diagnoses are terrifying, and human doctors are severely limited in dealing with humans’ complicated medical history. Understanding every drug and every drug’s interaction with every other drug is beyond the scope of human knowability, especially when there are research robots whose job is to test thousands of new drugs at a time.

Human doctors can only improve through their own experiences. Doctor bots can learn from the experience of every doctor bot, can read the latest medical research and keep track of everything that happens to all their patients worldwide, and make correlations that would be impossible to find otherwise. Not all doctors will go away, but when the doctor bots are comparable to humans and they’re only as far away as your phone, the need for general doctors will be less.

Professionals, white collar workers, and low-skilled workers all have to worry about automation. But perhaps you are unfazed because you’re a special, creative snowflake. Well, guess what.

You’re not that special.

Creative Bots

Creativity may feel like magic, but it isn’t. The brain is a complicated machine, and perhaps the most complicated machine in the whole universe. But that hasn’t stopped us from trying to simulate it.

There is this notion that just as mechanical muscles allowed us to move into thinking jobs that mechanical minds will allow us to move into creative work. But even if we assume the human mind is magically creative — it’s not, but for the sake of argument — artistic creativity isn’t what the majority of jobs depend on. The number of writers and poets and directors and actors and artists who actually make a living doing their work is a tiny, tiny portion of the labor force. And given that these professions are dependent on popularity, they’ll always be a very small portion of the population. There can’t be such a thing as a poem- and painting-based economy.

Talking about artificial creativity gets weird quickly (what does that even mean?), but nonetheless it’s a developing field. People used to think that playing chess was uniquely creative of human skills that machines never do — right up until the point machines beat the best of us.

And so it will go for all all human talents.

This may be a lot to take in, and you might want to reject it. It’s easy to be cynical of the endless and idiotic predictions of futures that never are. But that’s why it’s important to emphasize once again that this stuff isn’t science fiction. The robots are here right now. There is a terrifying amount of working automation in labs and warehouses around the world.

We’ve been through economic revolutions before, but the robot revolution is different. Horses aren’t unemployed because they got lazy as a species…they’re unemployable. There’s little work that a horse can do to pay for its housing and hay, and many bright, perfectly capable humans will find themselves the new horse: unemployable through no fault of their own.

But if you still think new jobs will save us, here’s one final point to consider. The U.S. Census in 1776 tracked only a few kinds of jobs. Now there are hundreds of kinds of jobs, but the new ones aren’t a significant part of the labor force.

Here’s the list of jobs ranked by the number of people who perform them.

• Transportation: 3,628,000
• Retail salespersons: 3,286,000
• First line supervisors: 3,132,000
• Cashiers: 3,109,000
• Secretaries: 3,082,000
• Managers, all other: 2,898,000
• Sales representatives: 2,865,000
• Registered nurses: 2,843,000
• Elementary school teachers: 2,813,000
• Janitors/cleaners: 2,186,000
• Waiters and waitresses: 2,067,000
• Cooks: 1,951,000
• Nursing, psychiatric: 1,928,000
• Customer service: 1,896,000
• Laborers and freight: 1,700,000

It’s a sobering list with the transportation industry at the top. Continuing downward, all of this work existed in some form a hundred years ago, and almost all of them are easy targets for automation. Only when you get to number thirty-three on the list (not shown above) is there finally something new: computer programmers.

Don’t think that every barista or white-collar worker need lose their job before this becomes a problem. The unemployment rate during the Great Depression was 25%. The 33 most common jobs in the United States encompasses 45% of the workforce. Just what I’ve written about here — the automation that already exists — can push unemployment over 25% pretty soon. And given that even in our modern technological wonderland new kinds of work aren’t a significant portion of the economy, this is a big problem.

This article isn’t about how automation is bad. Rather, it’s about how automation is inevitable. It’s a tool to produce abundance with little effort. We need to start thinking about what to do when large sections of the population are unemployable through no fault of their own — what to do in a future where, for most jobs, humans need not apply.