SUBTITLES:
Subtitles generated by robot
00:00
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 lab 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
00:31
what's different this time the things
that used to be simple innovation made
human work easier and productivity rose
which means that more staff or services
can be produced per hour using the same
amount of human workers this eliminated
many jobs it also created other jobs
that were better which was important
because the growing population needed
work so in a nutshell innovation higher
01:09
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
01:40
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 wiring 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 u.s. dollars in 2012 Google
made about 14 billion u.s. dollars while
02:12
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
02:44
today this process is largely complete
innovation in the car industry does not
create as many jobs as in Houston 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 power 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
03:15
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 for
take us for example with a full-time
team of just 12 people courtesan 2
reaches millions of people a TV station
with the same amount of viewers needs
way more employees innovation in the
03:47
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
04:17
smartest machines are bad at doing
complicated jobs they are extremely good
at doing now redefined 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
ready 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 but for a lot of
people there will be no further room to
specialize we on the verge of being out
04:48
completed digital machines do this fly
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
so 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
05:20
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
05:50
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
06:22
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 ok this doesn't
sound too bad
while this machine is killing one job it
creates jobs for freelancers right well
06:54
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
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fields from pharmacists to analysts
journalists to radiologists cashiers
bank tellers or the unskilled worker
flipping
all of these jobs won't disappear
overnight but fewer and fewer humans
will be doing we'll discuss a few cases
in a follow-up video but while jobs
disappearing it's bad it's only half of
the story it's not enough to substitute
old jobs with new ones we need to be
07:56
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 u.s. 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
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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
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despite productivity growing drastically
thousands of new businesses opening up
and the u.s. population growing by over
40 million there was no growth at all
when 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 one up to
40 percent of new graduates are forced
to take on jobs that don't require a
degree
productivity is separating from human
neighbor the nature of innovation and
the information age is different from
09:36
everything we 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
10:07
too few people can actually buy all our
stuff and services all will the future
see a tiny minority of the Civic who own
the machines dominating the rest of us
and does our future-ready have to be
that grim while we were fairly dark in
this video it's felt a certain that
things will turn out negatively the
Information Age and modern automation
could be a huge opportunity to change
human society and reduced poverty and
inequality drastically it could be a
seminal moment in human history we'll
10:39
talk about this potential and possible
solutions like a universal basic income
in part two of this video series we need
to think thick 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
you get a personal coach because out
bird in return that would be really
11:10
useful we based much of this video on
two very good books the rise of the
robots and the second Machine Age you
can find links to both of them in the
video description highly recommended
also we make 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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