What is Automation?
Automation is the use of technology to run systems or to perform jobs that were once done by people, or the use of technology that helps people run systems or perform their jobs.
The following video was released by IBM in 2014.
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.
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.
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
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.
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.
How do you prepare for a disrupted future? By planning for the new jobs.