Humans Need Not Apply

Every human used to have to hunt or gather
to survive.

But humans are smartly lazy,
so we made tools to make out 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 have been here before,
but we haven't. This time is different.

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 are 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 the 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 electricty,

while his meat-based competition costs
minimum wage.

The tenth of the speed is still
cost-effective when its 1/100th the price.

And while Baxter isn't as smart as some of
the other things we all talk about,

he's smart enough to take over many low-
skilled jobs.

And we've already seen how dumber robots
than Baxter can replace jobs.

In new supermarkets, what used to be
thirty humans is now one human overseeing

thirty 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 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 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

in a way no pure mechanical muscle ever
could.

Imagine a pair of horses in the early
nineteenth hundreds talking about

technology.

One worries all these 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 all
that running from post to post delivering

mail; riding into battle; all terrible.

These new city jobs are pretty pushy
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 2,000
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 in technology that says
better technology makes more better jobs

for horses. Sounds shockingly dumb to even
say that aloud, but swap horses for humans

and suddenly people think it sounds about
right.

As mechanical muscles push horses out the
economy, mechanical minds will do the same

with 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
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 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 traveled hundreds
of thousands 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 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 seeing them be 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're
really are: autos. The solution to the

transporting objects from point A to B
problem.

Traditional cars happen to be human sized
to transport humans, but tiny autos can

work in warehouses and gigantic autos can
work can work in pit mines, moving stuff

around. Who know how many jobs,
but the transportation industry in the

United States employs about 3,000,000
people. Extrapolating world wide.

That's something like 70,000,000 jobs at
a minimum, these jobs are over.

The usual argument is that the unions
will prevent, but history is filled with

workers who fought technology that would
replace them, and workers always lose.

Economics always wins and there are huge
incentives across widely diverse

industries to adopt autos.

For many transportation companies,
humans are about a 1/3 their total cost.

That's just the straight salaries.
Humans sleeping in their long haul trucks

cost time and money; accidents cost money;
carelessness cost money.

If you think insurance companies will be
against it, guess what, they're perfect

is the 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.

Its easy to look at autos and Baxter's
and think technology has always gotten rid

of low skilled 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
100,000,000 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,

maybe your 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 than white collar workers are from a
company prospective 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 make think even the world's smartest
automation engineer can never make a bot

to do your job and you may be right,
but the cutting edge of programming isn't

supper smart programmers writing bots,
it's supper 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 how
to do it the bots can still learn.

Take the stock market, which in many ways
is no longer a human endeavor.

Its mostly bots that taught themselves to
trade stocks trading stocks with other

bots that taught themselves.
As an result the floor of the New York

stock exchange isn't filled with traders
doing they're day jobs anymore.

It's largely a TV set. The 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, TBS
reports, even say those quarterly reports

that you write at work.

Paperwork, decision making, even a lot of
human work falls into that category,

and the demand for human mental labor in
these areas is on the way down.

But surely the professions are still safe
for bots. Yes?

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 botsism

paperwork get 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 accounts in

hours not weeks, crushing human
researchers in terms of not just cost and

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 of 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.

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
misdiagnoses is terrifying and human

doctors are severely limited on dealing
with the humans complicated medical

history.

Understanding every drug and every drugs
interaction with every other drug is

beyond the scope of human notability,
especially when there are research bots

whose whole job 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
experience of every doctor bot