Humans Need Not Apply

Every human used to have to hunt or gather to survive. But humans are smart…ly lazy so we made tools to make our work easier. From sticks, to plows, to tractors we’ve gone from everyone needing to make food to, modern agriculture with almost no one needing to make food — and yet, we still have abundance. Of course, it’s not just farming, it’s
everything. We’ve spent the last several thousand years building tools to reduce physical
labor of all kinds. These are mechanical muscles. Stronger, more reliable, and more tireless
than human muscles ever could be. And that’s a good thing. Replacing human labor
with mechanical muscles frees people to specialize and that leaves everyone better off – even those
still doing physical labor. This is how economies grow and standards of living rise. Some people have specialized to be programmers
and engineers whose job is to build mechanical minds. Just as mechanical muscles made human
labor less in demand so are mechanical minds making human brain labor less in demand. This is an economic revolution. You may think
we’ve been here before, but we haven’t. This time is different. ## Physical Labor When you think of automation, you probably
think of this: giant, custom-built, expensive, efficient, but really dumb robots blind to
the world and their own work. They were a scary kind of automation but they haven’t
taken over the world because they’re only cost effective in narrow situations. But they’re the old kind of automation, this
is the new kind. Meet Baxter. Unlike these things which require skilled
operators and technicians and millions of dollars, Baxter has vision and can learn what
you want him to do by watching you do it. And he 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 computers, they too started out as 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 or assign seats on an airplane or play a game or do anything just by swapping
its software. And 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 Baxter is slow his hourly cost is pennies
worth of electricity while his meat-based competition costs minimum wage. A tenth the
speed is still cost effective when it’s a hundredth the price. And while Baxter isn’t
as smart as some of the other things we will talk about, he’s smart enough to take over
many low-skill jobs. And we’ve already seen how dumber robots than
Baxter can replace jobs. In new supermarkets what used to be 30 humans is now one human
overseeing 30 cashier robots. Or take the hundreds of thousand baristas employed
world-wide? There’s a barista robot coming for them. Sure maybe your guy makes the double-mocha-whatever
just perfect and you’d never trust anyone else — but millions of people don’t care
and just want a decent cup of coffee. Oh, 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. We think of technological change as the fancy
new expensive stuff, 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 will make horses
unnecessary. The other reminds him that everything so far
has made their lives easier — remember all that farm work? Remember running from coast-to-coast
delivering mail? Remember riding into battle? All terrible. These city jobs are pretty cushy, and with so many humans in the cities there will be more jobs for horses than ever. Even if this car thingy takes off – he might say – there will be new jobs for horses we can’t imagine. But you, dear viewer, from beyond 2000 know
what happened — there are still working horses, but nothing like before. The horse population
peaked in 1915 — from that point on it was nothing but down. 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 for humans and suddenly people think it sounds about
right. As mechanical muscles pushed horses out of
the economy, mechanical minds will do the 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
are not prepared. And we are not prepared. You, like the second horse, may look at the
state of technology now and think it can’t possibly replace your job. But technology
gets better, cheaper, and faster at a 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 travelled 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 replaces cars,
but how quickly. They don’t need to be perfect, they just need to be better than us. Humans
drivers, by the way, kill 40,000 people a year with cars just in the United States.
Given that self-driving cars don’t blink, don’t text while driving, don’t get sleepy
or stupid, it’s easy to see them being better than humans because they already are. Now 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 the name limits your thinking about what they can even do.
Lets 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 pit mines. Moving stuff around is
who knows how many jobs but the transportation industry in the United States employs about
three million people. Extrapolating world-wide that’s something like 70 million jobs at
a minimum. These jobs are over. The usual argument is that 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 their total costs. That’s just the straight salary costs. Humans sleeping
in their long haul trucks costs time and money. Accidents cost money. Carelessness costs money.
If you think insurance companies will be against it, 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 the robots changing society. But there are many
other places in the economy where the same thing is happening, just 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-skill jobs we don’t want people doing
anyway. They’ll get more skilled and do better educated jobs — like they’ve always done. Even ignoring the problem of pushing a hundred-million
additional people through higher education, white-collar work is no safe haven 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. How that works is well beyond the scope of
this video, 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 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 isn’t filled with traders doing their day jobs anymore, it’s largely a TV set. So bots have learned the market and bots have
learned to write. If you’ve picked up a newspaper lately you’ve probably already read a story
written by a bot. There are companies that teach bots to write anything: sports
stories, TPS reports, even say, those quarterly reports that you write at work. Paper work, decision making, writing — a
lot of human work falls into that category and the demand for human metal labor is these
areas is on the way 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
outcome and impact 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 in
terms of not just 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 destroy 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. And he’s already doing that at Slone-Kettering, giving guidance on lung cancer
treatments. Just as Auto 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 misdiagnoses are terrifying — and human doctors are severely
limited in dealing with a human’s 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 whole job it is to test thousands of new drugs at a time. And human doctors can only improve through their
own experiences. Doctor bots can learn from the experiences of every doctor bot. Can read
the latest in medical research and keep track of everything that happens to all their patients
world-wide 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. So professionals, white-collar workers and
low-skill workers all have things to worry about from 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 — 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 just 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 are professions 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. Oh, by the way, this music in the background
that you’re listening to? It was written by a bot. Her name is Emily Howell and she can
write an infinite amount of new music all day for free. And people can’t tell the difference between her and human composers when put to a blind test. Talking about artificial creativity gets weird
fast — what does that even mean? But it’s nonetheless a developing field. People used to think that playing chess was
a uniquely creative human skill that machines could never do right up until they beat the
best of us. And so it will go for all human talents. ## Conclusion Right: this may have been 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. So that’s why it’s important to emphasize 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 have been through economic revolutions
before, but the robot revolution is different. Horses aren’t unemployed now because they
got lazy as a species, they’re unemployable. There’s little work a horse can do that 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 is one final point to consider. The US census in 1776 tracked only a few kinds
of jobs. Now there are hundreds of kinds of jobs, but the new ones are not a significant
part of the labor force. Here’s the list of jobs ranked by the number
of people who perform them – 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 targets for automation. Only when we get to number 33 on the list is there
finally something new. Don’t that every barista or white collar worker need lose their job before things are a problem. The unemployment rate during the great depression
was 25%. This list above is 45% of the workforce. Just
what we’ve talked about today, the stuff that already works, can push us over that number
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 video isn’t about how automation is bad
— rather that automation is inevitable. It’s a tool to produce abundance for little effort.
We need to start thinking now 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.

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