The Rise of the Machines – Why Automation is Different this Time


How long do
you think it will take before machines do your
job better than you do? Automation used to mean big stupid machines
doing repetitive work in factories. Today they can land aircraft,
diagnose cancer and trade stocks. We are entering a new age of automation
unlike anything that’s come before. According to a 2013 study,
almost half of all jobs in the US could potentially be automated
in the next two decades. But wait; Hasn’t automation
been around for decades? What’s different this time? Things used to be simple. Innovation made human work
easier and productivity rose. Which means that more staff
or services could be produced per hour using the same
amount of human workers. This eliminated many jobs, but also
created other jobs that were better which was important because the
growing population needed work. So, in a nutshell, innovation,
higher productivity, fewer old jobs, and many
new and often better jobs. Overall, this worked well for a majority
of people and living standards improved. There’s a clear progression in
terms of what humans did for a living. For the longest time,
we worked in agriculture. With the Industrial Revolution, this
shift into production jobs and as automation became more widespread,
humans shifted into service jobs. And then only a few moments ago in human
history, the Information Age happened. Suddenly, the rules were different.
Our jobs are now being taken over by machines much faster
than they were in the past. That’s worrying of course… but
innovation will clearly save us, right? While new information age
industries are booming, they are creating fewer
and fewer new jobs. In 1979, General Motors
employed more than 800,000 workers and made about
$11 billion US dollars. In 2012, Google made about $14 billion US
dollars while employing 58,000 people. You may not like this
comparison, but Google is an example of what created
new jobs in the past: Innovative new industries. Old innovative industries are running
out of steam. Just look at cars. When they became a thing 100 years
ago, they created huge industries. Cars transformed our way of life,
our infrastructure, and our cities. Millions of people found jobs
either directly or indirectly. Decades of investment
kept this momentum going. Today, this process is largely complete.
Innovation in the car industry does not create
as many jobs as it used to. While electric cars are great and all,
they won’t create millions of new jobs. But wait; what about the internet? Some technologists argue
that the Internet is an innovation on a par of the
introduction of electricity. If we go with this
comparison, we see how our modern innovation differs
from the old one. The Internet created
new industries, but they’re not creating
enough jobs to keep up with population growth or to compensate for
the industries the Internet is killing. At its peak in 2004, Blockbuster had 84,000 employees and
made $6 billion US dollars in revenue. In 2016, Netflix had 4,500 employees and
made $9 billion dollars in revenue. Or take us, for example. With a full-time team of just 12 people,
Kurzgesagt reaches millions of people. A TV station with the same amount
of viewers needs way more employees. Innovation in the Information
Age doesn’t equate to the creation of enough new
jobs, which would be bad enough on its own but now, a
new wave of automation and a new generation of machines
is slowly taking over. To understand this, we need to
understand ourselves first. Human progress is based
on the division of labor. As we advanced over thousands of years,
our jobs became more and more specialized. While even our smartest machines
are bad at doing complicated jobs, they are extremely good at doing narrowly defined and predictable tasks. This is what destroyed factory jobs. But look at a complex job
long and hard enough, and you’ll find that it’s
really just many narrowly defined and predictable
tasks one after another. Machines are on the brink
of becoming so good at breaking down complex jobs
into many predictable ones, that for a lot of people, there will be
no further room to specialize. We are on the verge of being outcompeted. Digital machines do this
via machine learning, which enables them to acquire
information and skills by analyzing data. This makes them become better at something
through the relationships they discover. Machines teach themselves. We make this possible by
giving a computer a lot of data about the thing we
wanted to become better at. Show a machine
all the things you bought online, and it will slowly learn what to recommend
to you, so you buy more things. Machine learning is now meeting more
of its potential because in recent years, humans have started to
gather data about everything. Behavior, weather patterns, medical
records, communication systems, travel data, and of course,
data about what we do at work. What we’ve created by accident
is a huge library machines can use to learn how humans do things
and learn to do them better. These digital machines might
be the biggest job killer of all. They can be replicated
instantly and for free. When they improve, you
don’t need to invest in big metal things; you can
just use the new code. And they have the ability to
get better fast. How fast? If your work involves complex work on
a computer today, you might be out of work even sooner than the people
who still have jobs in factories. There are actual real-world examples of
how this transition might be happening. A San Francisco company offers a
project management software for big corporations, which is supposed to
eliminate middle management positions. When it’s hired for a new project, the
software first decides which jobs can be automated and precisely where
it needs actual professional humans. It then helps assemble a team of
freelancers over the Internet. The software then distributes tasks to
the humans, and controls the quality of the work, tracking individual
performance until the project is complete. Okay. This doesn’t sound too bad. While this machine is killing one job,
it creates jobs for freelancers, right? Well, as the freelancers
complete their tasks, learning algorithms track
them, and gather data about their work, and which
tasks it consists of. So what’s actually happening, is that the freelancers are teaching
a machine how to replace them. On average, this software
reduces costs by about 50% in the first year, and by
another 25% in the second year. This is only one example of many. There are machines and
programs getting as good or better than humans
in all kinds of fields. From pharmacists to analysts,
journalists to radiologists, cashiers to bank tellers, or the
unskilled worker flipping burgers. All of these jobs won’t
disappear overnight, but fewer and fewer humans
will be doing them. We’ll discuss a few cases
in a follow-up video. But while jobs disappearing is
bad, it’s only half of the story. It’s not enough to
substitute old jobs with new ones. We need to be generating
new jobs constantly because the world
population is growing. In the past we have solved
this through innovation. But, since 1973, the generation of new
jobs in the US has begun to shrink. And the first decade of the 21st
century, was the first one, where the total amount of jobs in the US,
did not grow for the first time. In a country that needs to create
up to 150,000 new jobs per month, just to keep up with
population growth, this is bad news. This is also starting to
affect standards of living. In the past, it was seen as
obvious that with rising productivity, more and better
jobs would be created. But the numbers
tell a different story. In 1998, US workers worked
a total of 194 billion hours. Over the course of the next 15 years,
their output increased by 42 percent. But in 2013, the amount of hours worked
by US workers was still 194 billion hours. What this means, is that
despite productivity growing drastically, thousands of new
businesses opening up, and the US population growing by over
40 million, there was no growth at all in the number
of hours worked in 15 years. At the same time, wages for
new university graduates in the US, have been declining
for the past decade, while up to 40 percent of
new graduates, are forced to take on jobs that
don’t require a degree. Productivity is separating
from human labor. The nature of innovation
in the Information Age is different from everything
we’ve encountered before. This process started years ago
and is already well underway. Even without new disruptions like
self-driving cars, or robot accountants. It looks like
automation is different this time. This time, the machines
might really take our jobs. Our economies are based on
the premise that people consume. But if fewer and fewer people have decent
work, who will be doing all the consuming? Are we producing ever more cheaply
only to arrive at a point where too few people can actually buy
all our stuff and services? Or, will the future see a tiny minority of
the super rich who own the machines… dominating the rest of us? And does our future
really have to be that grim? While we were fairly dark
in this video, it’s far from certain that things
will turn out negatively. The Information Age and modern
automation, could be a huge opportunity to change human society, and reduce
poverty and inequality drastically. It could be a seminal
moment in human history. We’ll talk about this potential,
and possible solutions like a universal basic income, in
part 2 of this video series. We need to think big, and fast. Because one thing’s for
sure, the machines are not coming; They are already here. This video took us
about 900 hours to make, and we’ve been working on
it for over nine months. Projects like this one
would not be possible without your support
on patreon.com. If you want to help us
out and get a personal Kurzgesagt bird in return,
that would be really useful. We based much of this video on
two very good books: and You can find links to both of them in the
video description; highly recommended! Also, we made a little robot poster. You can buy it and a lot of other
stuff in our DFTBA shop. This video is part of a larger
series about how technology is already changing and will
change human life forever. If you want to continue
watching, we have a few playlists.

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