[Music]
[Music] you
there’s a cold wet miserable evening in
there’s a cold wet miserable evening in March 18 11 when a group of frustrated
March 18 11 when a group of frustrated
March 18 11 when a group of frustrated disgruntled textile workers decided that
disgruntled textile workers decided that
disgruntled textile workers decided that had enough they marched onto the village
had enough they marched onto the village
had enough they marched onto the village of Arnold in Nottinghamshire and cheered
of Arnold in Nottinghamshire and cheered
of Arnold in Nottinghamshire and cheered on by the local crowds they started
on by the local crowds they started
on by the local crowds they started going from factory to factory smashing
going from factory to factory smashing
going from factory to factory smashing up the equipment inside and this started
up the equipment inside and this started
up the equipment inside and this started six years of riot and rebellion across
six years of riot and rebellion across
six years of riot and rebellion across Britain where similar groups would go
Britain where similar groups would go
Britain where similar groups would go from town to town from factory to
from town to town from factory to
from town to town from factory to factory vandalizing what they found in
factory vandalizing what they found in
factory vandalizing what they found in sight these people were doing this for
sight these people were doing this for
sight these people were doing this for one reason they were scared for their
one reason they were scared for their
one reason they were scared for their future they were scared for their jobs
future they were scared for their jobs
future they were scared for their jobs they saw the automation they saw the
they saw the automation they saw the
they saw the automation they saw the steam and the coal and all the things
steam and the coal and all the things
steam and the coal and all the things that were happening in the world and
that were happening in the world and
that were happening in the world and they knew that the jobs that they and
they knew that the jobs that they and
they knew that the jobs that they and their parents and their grandparents and
their parents and their grandparents and
their parents and their grandparents and generations before had done they knew
generations before had done they knew
generations before had done they knew that those jobs were over that new jobs
that those jobs were over that new jobs
that those jobs were over that new jobs were coming to the place and they didn’t
were coming to the place and they didn’t
were coming to the place and they didn’t know what that meant for them we recall
know what that meant for them we recall
know what that meant for them we recall this group of people the Luddites and we
this group of people the Luddites and we
this group of people the Luddites and we look back on them now and history
look back on them now and history
look back on them now and history doesn’t look kindly on them we think
doesn’t look kindly on them we think
doesn’t look kindly on them we think that they were against progress that
that they were against progress that
that they were against progress that they were against technology they
they were against technology they
they were against technology they couldn’t see the wonders of the
couldn’t see the wonders of the
couldn’t see the wonders of the Industrial Revolution that we’re going
Industrial Revolution that we’re going
Industrial Revolution that we’re going to happen and we even used the word
to happen and we even used the word
to happen and we even used the word Luddite as a little bit of a insult if
Luddite as a little bit of a insult if
Luddite as a little bit of a insult if you haven’t got the latest smartphone on
you haven’t got the latest smartphone on
you haven’t got the latest smartphone on a date and on snapchat Luddite there’s a
a date and on snapchat Luddite there’s a
a date and on snapchat Luddite there’s a new revolution coming the artificial
new revolution coming the artificial
new revolution coming the artificial intelligence revolution and the secret
intelligence revolution and the secret
intelligence revolution and the secret is I’m a little bit of a Luddite not in
is I’m a little bit of a Luddite not in
is I’m a little bit of a Luddite not in the snapchat I don’t have snapchat but
the snapchat I don’t have snapchat but
the snapchat I don’t have snapchat but in the traditional sense you see I’m
in the traditional sense you see I’m
in the traditional sense you see I’m afraid of what’s going to happen to
afraid of what’s going to happen to
afraid of what’s going to happen to people’s jobs so I’m afraid of what
people’s jobs so I’m afraid of what
people’s jobs so I’m afraid of what artificial intelligence means for the
artificial intelligence means for the
artificial intelligence means for the world
AI is really hyped by the media
AI is really hyped by the media everywhere you look you hear about
everywhere you look you hear about
everywhere you look you hear about artificial intelligence at the moment
artificial intelligence at the moment
artificial intelligence at the moment every time there’s a game where their
every time there’s a game where their
every time there’s a game where their computer beats the human the media
computer beats the human the media
computer beats the human the media screams if the robots are about to take
screams if the robots are about to take
screams if the robots are about to take over when the
over when the
over when the blooby Gary Kasparov or when jeopardy
blooby Gary Kasparov or when jeopardy
blooby Gary Kasparov or when jeopardy was finally conquered by IBM what’s more
was finally conquered by IBM what’s more
was finally conquered by IBM what’s more more recently in the news we’ve heard
more recently in the news we’ve heard
more recently in the news we’ve heard about how deep mind solutions conquered
about how deep mind solutions conquered
about how deep mind solutions conquered go we have this sort of perverse desire
go we have this sort of perverse desire
go we have this sort of perverse desire to find computers that are smarter than
to find computers that are smarter than
to find computers that are smarter than us the reality is that actually for the
us the reality is that actually for the
us the reality is that actually for the last 20 years artificial intelligence
last 20 years artificial intelligence
last 20 years artificial intelligence has been slowly permeating into our
has been slowly permeating into our
has been slowly permeating into our society into a world in much quieter
society into a world in much quieter
society into a world in much quieter ways the spam filter that looks at the
ways the spam filter that looks at the
ways the spam filter that looks at the email coming in the GPS system that you
email coming in the GPS system that you
email coming in the GPS system that you use to navigate your car the Ford
use to navigate your car the Ford
use to navigate your car the Ford protection system that protects your
protection system that protects your
protection system that protects your credit-card transactions or the medical
credit-card transactions or the medical
credit-card transactions or the medical diagnosis system the Google search or
diagnosis system the Google search or
diagnosis system the Google search or the advert that’s a little bit eerily
the advert that’s a little bit eerily
the advert that’s a little bit eerily too tailored to you all of these are
too tailored to you all of these are
too tailored to you all of these are examples of artificial intelligence in
examples of artificial intelligence in
examples of artificial intelligence in the real world and they’re all examples
the real world and they’re all examples
the real world and they’re all examples of how a AI is using digital data to
of how a AI is using digital data to
of how a AI is using digital data to make conclusions about what’s happened
make conclusions about what’s happened
make conclusions about what’s happened but over the last five to ten years
but over the last five to ten years
but over the last five to ten years things have really started changing and
things have really started changing and
things have really started changing and improving a new technique called deep
improving a new technique called deep
improving a new technique called deep learning has come along which means we
learning has come along which means we
learning has come along which means we can take any problem any input set and
can take any problem any input set and
can take any problem any input set and through really teaching a computer to
through really teaching a computer to
through really teaching a computer to learn we can find a solution to it so
learn we can find a solution to it so
learn we can find a solution to it so let’s take an example close your eyes
let’s take an example close your eyes
let’s take an example close your eyes actually and imagine in your imagine in
actually and imagine in your imagine in
actually and imagine in your imagine in your mind a snowy scene and imagine a
your mind a snowy scene and imagine a
your mind a snowy scene and imagine a cute little fluffy puppy just you can
cute little fluffy puppy just you can
cute little fluffy puppy just you can just see its face and snow next to it is
just see its face and snow next to it is
just see its face and snow next to it is a cute little fluffy kitten if I asked
a cute little fluffy kitten if I asked
a cute little fluffy kitten if I asked you to describe to me which one’s the
you to describe to me which one’s the
you to describe to me which one’s the kitten and which one’s the puppy and why
kitten and which one’s the puppy and why
kitten and which one’s the puppy and why that is and how you know that you’d
that is and how you know that you’d
that is and how you know that you’d actually find it extremely difficult if
actually find it extremely difficult if
actually find it extremely difficult if you tried to explain it to a computer
you tried to explain it to a computer
you tried to explain it to a computer using mathematical terms you would most
using mathematical terms you would most
using mathematical terms you would most definitely find it impossible and for
definitely find it impossible and for
definitely find it impossible and for decades people have been trying to work
decades people have been trying to work
decades people have been trying to work out how we can solve problems like this
out how we can solve problems like this
out how we can solve problems like this how we can get computers to understand
how we can get computers to understand
how we can get computers to understand what things actually are and what they
what things actually are and what they
what things actually are and what they mean and what deep learning is done is
mean and what deep learning is done is
mean and what deep learning is done is it’s it’s changed the equation it’s
it’s it’s changed the equation it’s
it’s it’s changed the equation it’s allowed us to build learning systems
allowed us to build learning systems
allowed us to build learning systems that can learn like humans the way deep
that can learn like humans the way deep
that can learn like humans the way deep learning works is we pass into a system
learning works is we pass into a system
learning works is we pass into a system hundreds of thousands of photos of dogs
hundreds of thousands of photos of dogs
hundreds of thousands of photos of dogs of cats of pigeons of lions and we let
of cats of pigeons of lions and we let
of cats of pigeons of lions and we let the computer work out what’s what we
the computer work out what’s what we
the computer work out what’s what we tell it this is a cat and this is a dog
tell it this is a cat and this is a dog
tell it this is a cat and this is a dog but we let the computer
but we let the computer
but we let the computer work out what that means and that’s just
work out what that means and that’s just
work out what that means and that’s just how we teach humans if you think about
how we teach humans if you think about
how we teach humans if you think about how you would teach a child what’s a
how you would teach a child what’s a
how you would teach a child what’s a kitten or a puppy is you would show it
kitten or a puppy is you would show it
kitten or a puppy is you would show it to them you would show them books with a
to them you would show them books with a
to them you would show them books with a cute kitten or a cute puppy you take
cute kitten or a cute puppy you take
cute kitten or a cute puppy you take them to the park and they would see
them to the park and they would see
them to the park and they would see those things and they would learn what
those things and they would learn what
those things and they would learn what these things are what they mean and
these things are what they mean and
these things are what they mean and that’s what deep learning does and deep
that’s what deep learning does and deep
that’s what deep learning does and deep learning because of this ability to
learning because of this ability to
learning because of this ability to learn any problem is more interesting
learn any problem is more interesting
learn any problem is more interesting things than being able to differentiate
things than being able to differentiate
things than being able to differentiate between a cat and a dog it can tell us
between a cat and a dog it can tell us
between a cat and a dog it can tell us just by looking whether that mole is
just by looking whether that mole is
just by looking whether that mole is cancerous or whether it’s benign it can
cancerous or whether it’s benign it can
cancerous or whether it’s benign it can tell whether the words that we’re using
tell whether the words that we’re using
tell whether the words that we’re using your friendly or whether they’re hostile
your friendly or whether they’re hostile
your friendly or whether they’re hostile it can understand what you mean when
it can understand what you mean when
it can understand what you mean when you’re talking to a lexer or it can
you’re talking to a lexer or it can
you’re talking to a lexer or it can understand which biomolecules we want
understand which biomolecules we want
understand which biomolecules we want when we need to fight the Ebola virus
when we need to fight the Ebola virus
when we need to fight the Ebola virus that’s spreading through the world in
that’s spreading through the world in
that’s spreading through the world in complex systems like a self-driving car
complex systems like a self-driving car
complex systems like a self-driving car it can understand which way to turn the
it can understand which way to turn the
it can understand which way to turn the steel steering wheel or whether you push
steel steering wheel or whether you push
steel steering wheel or whether you push on the accelerator or or the brake pedal
on the accelerator or or the brake pedal
on the accelerator or or the brake pedal and all of these are just doing the same
and all of these are just doing the same
and all of these are just doing the same things they’re looking at image they’re
things they’re looking at image they’re
things they’re looking at image they’re learning what that image means and
learning what that image means and
learning what that image means and they’re being able to recognize and
they’re being able to recognize and
they’re being able to recognize and detect things in it these are now
detect things in it these are now
detect things in it these are now systems that are no longer just
systems that are no longer just
systems that are no longer just interacting with digital data like
interacting with digital data like
interacting with digital data like emails or GPS coordinates but
emails or GPS coordinates but
emails or GPS coordinates but interacting with sensory data with
interacting with sensory data with
interacting with sensory data with things that they can see and things that
things that they can see and things that
things that they can see and things that they can hear these systems can learn
they can hear these systems can learn
they can hear these systems can learn anything that we can learn that doesn’t
anything that we can learn that doesn’t
anything that we can learn that doesn’t mean they’re intelligent in the same way
mean they’re intelligent in the same way
mean they’re intelligent in the same way as humans it doesn’t mean that they have
as humans it doesn’t mean that they have
as humans it doesn’t mean that they have creativity or rational behavior but it
creativity or rational behavior but it
creativity or rational behavior but it does mean that if we can teach something
does mean that if we can teach something
does mean that if we can teach something to a child or even an adult we can now
to a child or even an adult we can now
to a child or even an adult we can now teach it to a deep learning system
teach it to a deep learning system
teach it to a deep learning system empower louts of all this we’ve seen
empower louts of all this we’ve seen
empower louts of all this we’ve seen massive improvements in MOBOTIX urge you
massive improvements in MOBOTIX urge you
massive improvements in MOBOTIX urge you will after this to go and look up a
will after this to go and look up a
will after this to go and look up a robot called atlas atlas has been in
robot called atlas atlas has been in
robot called atlas atlas has been in development for many years and there are
development for many years and there are
development for many years and there are lots of videos that come out it started
lots of videos that come out it started
lots of videos that come out it started off as a humanoid 6-foot robot that
off as a humanoid 6-foot robot that
off as a humanoid 6-foot robot that could go into a factory and start
could go into a factory and start
could go into a factory and start stacking shelves and today it can now
stacking shelves and today it can now
stacking shelves and today it can now still do that but it can also jump up
still do that but it can also jump up
still do that but it can also jump up stairs and backflip significantly better
stairs and backflip significantly better
stairs and backflip significantly better than me off the box if you compare what
than me off the box if you compare what
than me off the box if you compare what deep learning can do and you bring it
deep learning can do and you bring it
deep learning can do and you bring it these advances in robotics is it’s clear
these advances in robotics is it’s clear
these advances in robotics is it’s clear to see that hey I can very quickly start
to see that hey I can very quickly start
to see that hey I can very quickly start to replace jobs so then there’s an
to replace jobs so then there’s an
to replace jobs so then there’s an obvious question of will it well when
obvious question of will it well when
obvious question of will it well when you think
you think
you think this warehouse worker is not going to
this warehouse worker is not going to
this warehouse worker is not going to need any sick leave or lunch breaks when
need any sick leave or lunch breaks when
need any sick leave or lunch breaks when you think you can sack that HR
you think you can sack that HR
you think you can sack that HR department and you don’t need any health
department and you don’t need any health
department and you don’t need any health and safety requirements anymore it
and safety requirements anymore it
and safety requirements anymore it suddenly becomes quite obvious why a
suddenly becomes quite obvious why a
suddenly becomes quite obvious why a factory or warehouse would choose to
factory or warehouse would choose to
factory or warehouse would choose to have robots not people they also
have robots not people they also
have robots not people they also advantages like you can patch the hole
advantages like you can patch the hole
advantages like you can patch the hole or every single robot with the same
or every single robot with the same
or every single robot with the same software upgrade at once if you’ve got
software upgrade at once if you’ve got
software upgrade at once if you’ve got one worker at the moment that’s a bit
one worker at the moment that’s a bit
one worker at the moment that’s a bit annoying or keeps making the same
annoying or keeps making the same
annoying or keeps making the same mistake you can maybe give them
mistake you can maybe give them
mistake you can maybe give them education and you know help try and fix
education and you know help try and fix
education and you know help try and fix them but that doesn’t help fix everyone
them but that doesn’t help fix everyone
them but that doesn’t help fix everyone else in that workshop or warehouse when
else in that workshop or warehouse when
else in that workshop or warehouse when they get stuff wrong with these systems
they get stuff wrong with these systems
they get stuff wrong with these systems you teach one thing and they all learn
you teach one thing and they all learn
you teach one thing and they all learn and there is a real sense of collective
and there is a real sense of collective
and there is a real sense of collective learning here when you’re born that’s
learning here when you’re born that’s
learning here when you’re born that’s that’s you all of your experiences all
that’s you all of your experiences all
that’s you all of your experiences all of your learning are then yourself with
of your learning are then yourself with
of your learning are then yourself with these self-driving cars for example the
these self-driving cars for example the
these self-driving cars for example the reason that they’ve come on so quickly
reason that they’ve come on so quickly
reason that they’ve come on so quickly is because every single road a
is because every single road a
is because every single road a self-driving car drives down it’s not
self-driving car drives down it’s not
self-driving car drives down it’s not just it that’s learning about that road
just it that’s learning about that road
just it that’s learning about that road every other car is learning about that
every other car is learning about that
every other car is learning about that road every time somebody bashes into the
road every time somebody bashes into the
road every time somebody bashes into the back of a car which has happened all of
back of a car which has happened all of
back of a car which has happened all of these are the cars learn from from that
these are the cars learn from from that
these are the cars learn from from that mistake there’s the hive mind going on
mistake there’s the hive mind going on
mistake there’s the hive mind going on between all these systems so it’s
between all these systems so it’s
between all these systems so it’s obvious to me and to anyone in this
obvious to me and to anyone in this
obvious to me and to anyone in this field that big companies very quickly
field that big companies very quickly
field that big companies very quickly are going to start embracing and using
are going to start embracing and using
are going to start embracing and using this technology so we know that already
this technology so we know that already
this technology so we know that already Amazon are trying to have drones instead
Amazon are trying to have drones instead
Amazon are trying to have drones instead of delivery people and we know as soon
of delivery people and we know as soon
of delivery people and we know as soon as the technology is ready that they’ll
as the technology is ready that they’ll
as the technology is ready that they’ll sack their 400,000 warehouse workers and
sack their 400,000 warehouse workers and
sack their 400,000 warehouse workers and we place them with robots
we place them with robots
we place them with robots uber have already said that they want to
uber have already said that they want to
uber have already said that they want to get rid of 3 million of their taxi
get rid of 3 million of their taxi
get rid of 3 million of their taxi drivers and replaced them with
drivers and replaced them with
drivers and replaced them with self-driving cars and why wouldn’t they
self-driving cars and why wouldn’t they
self-driving cars and why wouldn’t they every single taxi trip will have a
every single taxi trip will have a
every single taxi trip will have a hundred percent gross margin for that
hundred percent gross margin for that
hundred percent gross margin for that company forever from that point and once
company forever from that point and once
company forever from that point and once that happens everyone else will have to
that happens everyone else will have to
that happens everyone else will have to follow suit to be able to keep her a
follow suit to be able to keep her a
follow suit to be able to keep her a company that’s got a workforce of a
company that’s got a workforce of a
company that’s got a workforce of a hundred people can’t financially compete
hundred people can’t financially compete
hundred people can’t financially compete with an equivalent company that pays no
with an equivalent company that pays no
with an equivalent company that pays no one there were lots of studies into this
one there were lots of studies into this
one there were lots of studies into this at the moment and most of these studies
at the moment and most of these studies
at the moment and most of these studies are showing that between 10 and 50
are showing that between 10 and 50
are showing that between 10 and 50 percent of jobs are vulnerable to this
percent of jobs are vulnerable to this
percent of jobs are vulnerable to this sort of AI robotic automation over the
sort of AI robotic automation over the
sort of AI robotic automation over the next 20 to 25 years and that’s all sorts
next 20 to 25 years and that’s all sorts
next 20 to 25 years and that’s all sorts of jobs it’s not just the obvious jobs
of jobs it’s not just the obvious jobs
of jobs it’s not just the obvious jobs that you
that you
that you think of it’s not just the warehouse
think of it’s not just the warehouse
think of it’s not just the warehouse work or the production line staff or the
work or the production line staff or the
work or the production line staff or the taxi driver I have the privilege of
taxi driver I have the privilege of
taxi driver I have the privilege of working with some of the smartest
working with some of the smartest
working with some of the smartest doctors in the world on some of the most
doctors in the world on some of the most
doctors in the world on some of the most complex problems and when I recently
complex problems and when I recently
complex problems and when I recently went to dinner with them and I asked
went to dinner with them and I asked
went to dinner with them and I asked them whether they thought they would be
them whether they thought they would be
them whether they thought they would be replaceable in the next 15 20 years they
replaceable in the next 15 20 years they
replaceable in the next 15 20 years they were very quick to tell me about how
were very quick to tell me about how
were very quick to tell me about how important empathy is and how important
important empathy is and how important
important empathy is and how important their creative problem-solving is but
their creative problem-solving is but
their creative problem-solving is but they’re also very open that actually a
they’re also very open that actually a
they’re also very open that actually a lot of what they do is just procedural
lot of what they do is just procedural
lot of what they do is just procedural it’s stuff they learned at medical
it’s stuff they learned at medical
it’s stuff they learned at medical school and they’ve learned for their
school and they’ve learned for their
school and they’ve learned for their career and now they’re just applying
career and now they’re just applying
career and now they’re just applying that knowledge think about yourself if
that knowledge think about yourself if
that knowledge think about yourself if you went to a any accident an emergency
you went to a any accident an emergency
you went to a any accident an emergency and you think you might have a broken
and you think you might have a broken
and you think you might have a broken leg the doctor will ask some questions
leg the doctor will ask some questions
leg the doctor will ask some questions that sort of prompt over a little bit
that sort of prompt over a little bit
that sort of prompt over a little bit they’ll take you down to the x-ray room
they’ll take you down to the x-ray room
they’ll take you down to the x-ray room where you’ll get an x-ray and they’ll
where you’ll get an x-ray and they’ll
where you’ll get an x-ray and they’ll bring you back they’ll add those
bring you back they’ll add those
bring you back they’ll add those different things together and give you a
different things together and give you a
different things together and give you a diagnosis they’ll then tell you in the
diagnosis they’ll then tell you in the
diagnosis they’ll then tell you in the kindest way about yes you’ve got a
kindest way about yes you’ve got a
kindest way about yes you’ve got a broken leg you are out of sport for the
broken leg you are out of sport for the
broken leg you are out of sport for the next two years and they’ll know that if
next two years and they’ll know that if
next two years and they’ll know that if they tell me that that’s probably
they tell me that that’s probably
they tell me that that’s probably matters less than if they tell a
matters less than if they tell a
matters less than if they tell a professional athlete that that last bit
professional athlete that that last bit
professional athlete that that last bit is very human it’s very empathetic but
is very human it’s very empathetic but
is very human it’s very empathetic but everything else they’re doing is
everything else they’re doing is
everything else they’re doing is practical formulaic system that can be
practical formulaic system that can be
practical formulaic system that can be and will be automated so I will replace
and will be automated so I will replace
and will be automated so I will replace jobs now economists have a phrase they
jobs now economists have a phrase they
jobs now economists have a phrase they use and that phrase is the Luddite
use and that phrase is the Luddite
use and that phrase is the Luddite fallacy it echoes back to the Luddites
fallacy it echoes back to the Luddites
fallacy it echoes back to the Luddites we talked about at the beginning and it
we talked about at the beginning and it
we talked about at the beginning and it says actually we shouldn’t fear for loss
says actually we shouldn’t fear for loss
says actually we shouldn’t fear for loss of jobs the Luddites were bong it’s not
of jobs the Luddites were bong it’s not
of jobs the Luddites were bong it’s not that jobs disappear it’s that when some
that jobs disappear it’s that when some
that jobs disappear it’s that when some jobs go technology brings other jobs
jobs go technology brings other jobs
jobs go technology brings other jobs instead there’s a change of composition
instead there’s a change of composition
instead there’s a change of composition of jobs in the economy that was true in
of jobs in the economy that was true in
of jobs in the economy that was true in the Industrial Revolution if a weaver
the Industrial Revolution if a weaver
the Industrial Revolution if a weaver saw a new weaving machine a loom that
saw a new weaving machine a loom that
saw a new weaving machine a loom that was ten hundred times faster than it the
was ten hundred times faster than it the
was ten hundred times faster than it the weaver would be out of work but somebody
weaver would be out of work but somebody
weaver would be out of work but somebody would then need to maintain and build
would then need to maintain and build
would then need to maintain and build the Loom itself so they could just
the Loom itself so they could just
the Loom itself so they could just quickly retrain and move into a
quickly retrain and move into a
quickly retrain and move into a different Factory Britain of old used to
different Factory Britain of old used to
different Factory Britain of old used to be and powered by horses every
be and powered by horses every
be and powered by horses every transportation would be riding on a
transportation would be riding on a
transportation would be riding on a horse suddenly steam trains and you know
horse suddenly steam trains and you know
horse suddenly steam trains and you know modern transportation came along what
modern transportation came along what
modern transportation came along what happened to the stable boys that were
happened to the stable boys that were
happened to the stable boys that were there shoveling out the horses muck
there shoveling out the horses muck
there shoveling out the horses muck every night while they went into the
every night while they went into the
every night while they went into the trains they started filling those with
trains they started filling those with
trains they started filling those with with coal instead we used to have these
with coal instead we used to have these
with coal instead we used to have these things in Britain that I sort of wish we
things in Britain that I sort of wish we
things in Britain that I sort of wish we still had which were called knock of
still had which were called knock of
still had which were called knock of uppers
uppers
uppers he would walk down the street tapping
he would walk down the street tapping
he would walk down the street tapping the window at an allotted time to get
the window at an allotted time to get
the window at an allotted time to get you up for work someone invented the
you up for work someone invented the
you up for work someone invented the alarm clock which must have really
alarm clock which must have really
alarm clock which must have really annoyed them but those people then just
annoyed them but those people then just
annoyed them but those people then just moved on to the production lines making
moved on to the production lines making
moved on to the production lines making alarm clocks the Industrial Revolution
alarm clocks the Industrial Revolution
alarm clocks the Industrial Revolution didn’t destroy jobs
didn’t destroy jobs
didn’t destroy jobs it changed the jobs it changed the
it changed the jobs it changed the
it changed the jobs it changed the composition of jobs in the workforce but
composition of jobs in the workforce but
composition of jobs in the workforce but this won’t happen with artificial
this won’t happen with artificial
this won’t happen with artificial intelligence if we are saying that AI
intelligence if we are saying that AI
intelligence if we are saying that AI and modern MOBOTIX are going to be able
and modern MOBOTIX are going to be able
and modern MOBOTIX are going to be able to replace any doing bits of jobs then
to replace any doing bits of jobs then
to replace any doing bits of jobs then just because there’s a new doing bit of
just because there’s a new doing bit of
just because there’s a new doing bit of a job coming instead and I will just do
a job coming instead and I will just do
a job coming instead and I will just do that if uber makes three million of its
that if uber makes three million of its
that if uber makes three million of its taxi drivers redundant they’re not
taxi drivers redundant they’re not
taxi drivers redundant they’re not suddenly going to train to be software
suddenly going to train to be software
suddenly going to train to be software developers so they can manage the
developers so they can manage the
developers so they can manage the self-driving cars they won’t have the
self-driving cars they won’t have the
self-driving cars they won’t have the skills the education knowledge to be
skills the education knowledge to be
skills the education knowledge to be able to do that and even if they did we
able to do that and even if they did we
able to do that and even if they did we don’t need three million new software
don’t need three million new software
don’t need three million new software developers Microsoft Windows only has
developers Microsoft Windows only has
developers Microsoft Windows only has five thousand people working on it and
five thousand people working on it and
five thousand people working on it and it powers half the computers in the
it powers half the computers in the
it powers half the computers in the world so what will happen to these
world so what will happen to these
world so what will happen to these people what does this mean for society
people what does this mean for society
people what does this mean for society well it opens up some very scary
well it opens up some very scary
well it opens up some very scary questions if we’re saying 10 to 50
questions if we’re saying 10 to 50
questions if we’re saying 10 to 50 percent of jobs of vulnerable in 25
percent of jobs of vulnerable in 25
percent of jobs of vulnerable in 25 years that’s half a billion to two and a
years that’s half a billion to two and a
years that’s half a billion to two and a half billion jobs that are going to go
half billion jobs that are going to go
half billion jobs that are going to go where do we find two and a half billion
where do we find two and a half billion
where do we find two and a half billion new jobs and if we find that how do we
new jobs and if we find that how do we
new jobs and if we find that how do we how do we train how do we educate two
how do we train how do we educate two
how do we train how do we educate two and a half billion people to go and do
and a half billion people to go and do
and a half billion people to go and do those jobs our education system isn’t
those jobs our education system isn’t
those jobs our education system isn’t set up for this we teach skills we teach
set up for this we teach skills we teach
set up for this we teach skills we teach knowledge we teach vocation but we don’t
knowledge we teach vocation but we don’t
knowledge we teach vocation but we don’t teach is how to learn we don’t teach is
teach is how to learn we don’t teach is
teach is how to learn we don’t teach is creativity and critical thinking and how
creativity and critical thinking and how
creativity and critical thinking and how can we build economies that can actually
can we build economies that can actually
can we build economies that can actually cope with this economy’s a built on
cope with this economy’s a built on
cope with this economy’s a built on production the companies that output the
production the companies that output the
production the companies that output the most the countries that output the most
most the countries that output the most
most the countries that output the most of the countries that win when the
of the countries that win when the
of the countries that win when the output is done by robotics and what
output is done by robotics and what
output is done by robotics and what humans are doing is the creativity and
humans are doing is the creativity and
humans are doing is the creativity and the critical thinking what does that
the critical thinking what does that
the critical thinking what does that mean through an economy and what happens
mean through an economy and what happens
mean through an economy and what happens what happens to the people if we can’t
what happens to the people if we can’t
what happens to the people if we can’t do this what if there aren’t two and a
do this what if there aren’t two and a
do this what if there aren’t two and a half billion new jobs and even if there
half billion new jobs and even if there
half billion new jobs and even if there are what happens before we make those
are what happens before we make those
are what happens before we make those jobs and retrain people we’re gonna have
jobs and retrain people we’re gonna have
jobs and retrain people we’re gonna have a point where we can
a point where we can
a point where we can have ten fifty percent of our workforce
have ten fifty percent of our workforce
have ten fifty percent of our workforce unemployed in 25 30 years it’s going to
unemployed in 25 30 years it’s going to
unemployed in 25 30 years it’s going to be a long time before the word jobs to
be a long time before the word jobs to
be a long time before the word jobs to replace those people we are facing mass
replace those people we are facing mass
replace those people we are facing mass unemployment in the very near future how
unemployment in the very near future how
unemployment in the very near future how do we deal with that as a society and
do we deal with that as a society and
do we deal with that as a society and how do people as individuals deal with
how do people as individuals deal with
how do people as individuals deal with that we know that retirement increases
that we know that retirement increases
that we know that retirement increases the risk of depression by 40 percent I
the risk of depression by 40 percent I
the risk of depression by 40 percent I couldn’t find stats for redundancy but
couldn’t find stats for redundancy but
couldn’t find stats for redundancy but imagine what we didn’t see with the
imagine what we didn’t see with the
imagine what we didn’t see with the knowledge that you’ve probably got no
knowledge that you’ve probably got no
knowledge that you’ve probably got no job ever again imagine what that’s going
job ever again imagine what that’s going
job ever again imagine what that’s going to do it’s a mental health in a society
to do it’s a mental health in a society
to do it’s a mental health in a society where mental health is already our
where mental health is already our
where mental health is already our biggest issue it’s also important to
biggest issue it’s also important to
biggest issue it’s also important to think back to the Industrial Revolution
think back to the Industrial Revolution
think back to the Industrial Revolution we look back on the Industrial
we look back on the Industrial
we look back on the Industrial Revolution and we we think of it as a as
Revolution and we we think of it as a as
Revolution and we we think of it as a as a sweeping progress we think yeah there
a sweeping progress we think yeah there
a sweeping progress we think yeah there was some little hiccups but the
was some little hiccups but the
was some little hiccups but the Industrial Revolution was also horrible
Industrial Revolution was also horrible
Industrial Revolution was also horrible time it was a time of exploitation it
time it was a time of exploitation it
time it was a time of exploitation it was a time of the wealthiest almost
was a time of the wealthiest almost
was a time of the wealthiest almost using the the purse to slaves and today
using the the purse to slaves and today
using the the purse to slaves and today we still have modern-day slavery we have
we still have modern-day slavery we have
we still have modern-day slavery we have mass exploitation through the whole of
mass exploitation through the whole of
mass exploitation through the whole of society and it was bloody as well like
society and it was bloody as well like
society and it was bloody as well like the Industrial Revolution caused the
the Industrial Revolution caused the
the Industrial Revolution caused the rise of capitalism the rise of communism
rise of capitalism the rise of communism
rise of capitalism the rise of communism it caused war after war afterwards
it caused war after war afterwards
it caused war after war afterwards people try to find ideologies that could
people try to find ideologies that could
people try to find ideologies that could answer the questions of what the
answer the questions of what the
answer the questions of what the Industrial Revolution means it caused
Industrial Revolution means it caused
Industrial Revolution means it caused tens of millions of deaths we look back
tens of millions of deaths we look back
tens of millions of deaths we look back on the Luddites as foolish but actually
on the Luddites as foolish but actually
on the Luddites as foolish but actually were they foolish actually did they not
were they foolish actually did they not
were they foolish actually did they not understand that transitioning a whole
understand that transitioning a whole
understand that transitioning a whole economy from one thing to another was
economy from one thing to another was
economy from one thing to another was maybe harder than a few rich politicians
maybe harder than a few rich politicians
maybe harder than a few rich politicians thought and what happened this time when
thought and what happened this time when
thought and what happened this time when actually it’s not sort of 10% of people
actually it’s not sort of 10% of people
actually it’s not sort of 10% of people unemployed and everyone else just having
unemployed and everyone else just having
unemployed and everyone else just having to do jobs they don’t want but it’s
to do jobs they don’t want but it’s
to do jobs they don’t want but it’s actually 50% of people out of work so we
actually 50% of people out of work so we
actually 50% of people out of work so we need to prepare both people and society
need to prepare both people and society
need to prepare both people and society we need to be educating children and
we need to be educating children and
we need to be educating children and adults in a way that means they can
adults in a way that means they can
adults in a way that means they can learn new skills that they can choose to
learn new skills that they can choose to
learn new skills that they can choose to learn they can learn we need to focus on
learn they can learn we need to focus on
learn they can learn we need to focus on critical thinking in our education
critical thinking in our education
critical thinking in our education system and we need to prepare with
system and we need to prepare with
system and we need to prepare with society as government’s as welfare
society as government’s as welfare
society as government’s as welfare states how does a welfare state cope
states how does a welfare state cope
states how does a welfare state cope when 50% of your population are giving
when 50% of your population are giving
when 50% of your population are giving and 50% are taking
and 50% are taking
and 50% are taking we’ve currently been trying things like
we’ve currently been trying things like
we’ve currently been trying things like basic income many countries of
basic income many countries of
basic income many countries of experiments with this and this is the
experiments with this and this is the
experiments with this and this is the idea that you we give a small amount of
idea that you we give a small amount of
idea that you we give a small amount of money to somebody enough maybe to put a
money to somebody enough maybe to put a
money to somebody enough maybe to put a roof over their head and to keep them
roof over their head and to keep them
roof over their head and to keep them fed but that then they can choose what
fed but that then they can choose what
fed but that then they can choose what they do at their time they can train for
they do at their time they can train for
they do at their time they can train for new skills they can go and get a job if
new skills they can go and get a job if
new skills they can go and get a job if they can find one or they can just relax
they can find one or they can just relax
they can find one or they can just relax at home we don’t know where the basic
at home we don’t know where the basic
at home we don’t know where the basic income is going to work or not yet it’s
income is going to work or not yet it’s
income is going to work or not yet it’s too early to tell but it’s important the
too early to tell but it’s important the
too early to tell but it’s important the society recognizes these challenges and
society recognizes these challenges and
society recognizes these challenges and start experimenting with ideas like this
start experimenting with ideas like this
start experimenting with ideas like this and maybe this is a positive thing maybe
and maybe this is a positive thing maybe
and maybe this is a positive thing maybe this is a future of the rise of the
this is a future of the rise of the
this is a future of the rise of the artisan if everything can be
artisan if everything can be
artisan if everything can be mass-produced
mass-produced
mass-produced at scales we can’t even imagine by by
at scales we can’t even imagine by by
at scales we can’t even imagine by by these robotic AI systems maybe the thing
these robotic AI systems maybe the thing
these robotic AI systems maybe the thing the human makes with its imperfections
the human makes with its imperfections
the human makes with its imperfections is actually the beauty maybe a society
is actually the beauty maybe a society
is actually the beauty maybe a society we start to reward creativity and art
we start to reward creativity and art
we start to reward creativity and art and music in a way that we just don’t at
and music in a way that we just don’t at
and music in a way that we just don’t at the moment because it doesn’t make
the moment because it doesn’t make
the moment because it doesn’t make people richer or maybe the future of
people richer or maybe the future of
people richer or maybe the future of humanity is just netflix and chill’
humanity is just netflix and chill’
humanity is just netflix and chill’ maybe it’s getting back to animalistic
maybe it’s getting back to animalistic
maybe it’s getting back to animalistic boots and sitting at home and doing
boots and sitting at home and doing
boots and sitting at home and doing whatever embracing nature enjoying the
whatever embracing nature enjoying the
whatever embracing nature enjoying the world for what it was maybe actually
world for what it was maybe actually
world for what it was maybe actually work is a burden but I know for myself
work is a burden but I know for myself
work is a burden but I know for myself that the creativity the challenge the
that the creativity the challenge the
that the creativity the challenge the risk and reward that work brings are
risk and reward that work brings are
risk and reward that work brings are things that give me purpose and drive if
things that give me purpose and drive if
things that give me purpose and drive if you take that away from me what does
you take that away from me what does
you take that away from me what does that leave me with what gets me out of
that leave me with what gets me out of
that leave me with what gets me out of bed in the morning so what do we do what
bed in the morning so what do we do what
bed in the morning so what do we do what are the solutions well the first thing
are the solutions well the first thing
are the solutions well the first thing that’s important to say is that you do
that’s important to say is that you do
that’s important to say is that you do not want to leave this to geeks like me
not want to leave this to geeks like me
not want to leave this to geeks like me to sort out this isn’t a problem for AI
to sort out this isn’t a problem for AI
to sort out this isn’t a problem for AI developers or software developers to
developers or software developers to
developers or software developers to sort out this is a problem for society
sort out this is a problem for society
sort out this is a problem for society to sort out we need the sociologists and
to sort out we need the sociologists and
to sort out we need the sociologists and psychologists that understand human
psychologists that understand human
psychologists that understand human behavior we need the business people who
behavior we need the business people who
behavior we need the business people who are going to have to choose between
are going to have to choose between
are going to have to choose between hiring a robot or hiring a person we
hiring a robot or hiring a person we
hiring a robot or hiring a person we need the doctors who are going to see
need the doctors who are going to see
need the doctors who are going to see changes in their healthcare system they
changes in their healthcare system they
changes in their healthcare system they can I imagine we need the 50% we’re
can I imagine we need the 50% we’re
can I imagine we need the 50% we’re going to lose their jobs to have voices
going to lose their jobs to have voices
going to lose their jobs to have voices not just have things imposed on them
not just have things imposed on them
not just have things imposed on them this is a problem not just for me not
this is a problem not just for me not
this is a problem not just for me not just for the people that are making this
just for the people that are making this
just for the people that are making this software but it’s a problem for
software but it’s a problem for
software but it’s a problem for everybody else in society and we need to
everybody else in society and we need to
everybody else in society and we need to come to
come to
come to gather an experiment we need to try
gather an experiment we need to try
gather an experiment we need to try things we need to come up with ideas and
things we need to come up with ideas and
things we need to come up with ideas and we need to discuss and debate not with a
we need to discuss and debate not with a
we need to discuss and debate not with a iesson nightmarish hell or some godlike
iesson nightmarish hell or some godlike
iesson nightmarish hell or some godlike thing that’s going to take over the
thing that’s going to take over the
thing that’s going to take over the world of us some hyped up hoaxes it’s
world of us some hyped up hoaxes it’s
world of us some hyped up hoaxes it’s none of those things
none of those things
none of those things hey isn’t complex to understand it’s not
hey isn’t complex to understand it’s not
hey isn’t complex to understand it’s not difficult it’s not it’s not challenging
difficult it’s not it’s not challenging
difficult it’s not it’s not challenging you can go out there and you can read
you can go out there and you can read
you can go out there and you can read things on it to understand what AI is
things on it to understand what AI is
things on it to understand what AI is what deep learning is what the future
what deep learning is what the future
what deep learning is what the future holds you can see the debates over the
holds you can see the debates over the
holds you can see the debates over the talk I’m having whether it will remove
talk I’m having whether it will remove
talk I’m having whether it will remove jobs whether it won’t but you need to go
jobs whether it won’t but you need to go
jobs whether it won’t but you need to go out there and educate yourselves and you
out there and educate yourselves and you
out there and educate yourselves and you need to make your voices heard
need to make your voices heard
need to make your voices heard artificial intelligence can bring such
artificial intelligence can bring such
artificial intelligence can bring such amazing power to the world it can
amazing power to the world it can
amazing power to the world it can potentially cure any disease it can
potentially cure any disease it can
potentially cure any disease it can potentially fix the planet fix the
potentially fix the planet fix the
potentially fix the planet fix the damage we’ve done to it it can
damage we’ve done to it it can
damage we’ve done to it it can potentially get us to Mars and take us
potentially get us to Mars and take us
potentially get us to Mars and take us across the whole galaxy exploring the
across the whole galaxy exploring the
across the whole galaxy exploring the reason I work in artificial intelligence
reason I work in artificial intelligence
reason I work in artificial intelligence is that for me it’s the most exciting
is that for me it’s the most exciting
is that for me it’s the most exciting field you could possibly be in but it
field you could possibly be in but it
field you could possibly be in but it comes with risks and it comes with
comes with risks and it comes with
comes with risks and it comes with dangers and we cannot be naive to that
dangers and we cannot be naive to that
dangers and we cannot be naive to that unless somebody else sort that problem
unless somebody else sort that problem
unless somebody else sort that problem out the future is in our control it’s in
out the future is in our control it’s in
out the future is in our control it’s in your control you can choose how the
your control you can choose how the
your control you can choose how the future is shaped for you for your kids
future is shaped for you for your kids
future is shaped for you for your kids for the generations to come but if you
for the generations to come but if you
for the generations to come but if you just sit by and let other people sort
just sit by and let other people sort
just sit by and let other people sort this out then the rich will get richer
this out then the rich will get richer
this out then the rich will get richer the corporation’s will have the robots
the corporation’s will have the robots
the corporation’s will have the robots the purr will get purr and the world
the purr will get purr and the world
the purr will get purr and the world will not be a fun place to be so I urge
will not be a fun place to be so I urge
will not be a fun place to be so I urge you I beg of you to go and learn to go
you I beg of you to go and learn to go
you I beg of you to go and learn to go and educate yourself and to debate and
and educate yourself and to debate and
and educate yourself and to debate and to fight and to think about what is
to fight and to think about what is
to fight and to think about what is right for society thank you
right for society thank you
right for society thank you [Applause]
[Applause]
[Applause] [Music]
[Music]
[Music] you
[Music] you
there’s a cold wet miserable evening in
there’s a cold wet miserable evening in March 18 11 when a group of frustrated
March 18 11 when a group of frustrated
March 18 11 when a group of frustrated disgruntled textile workers decided that
disgruntled textile workers decided that
disgruntled textile workers decided that had enough they marched onto the village
had enough they marched onto the village
had enough they marched onto the village of Arnold in Nottinghamshire and cheered
of Arnold in Nottinghamshire and cheered
of Arnold in Nottinghamshire and cheered on by the local crowds they started
on by the local crowds they started
on by the local crowds they started going from factory to factory smashing
going from factory to factory smashing
going from factory to factory smashing up the equipment inside and this started
up the equipment inside and this started
up the equipment inside and this started six years of riot and rebellion across
six years of riot and rebellion across
six years of riot and rebellion across Britain where similar groups would go
Britain where similar groups would go
Britain where similar groups would go from town to town from factory to
from town to town from factory to
from town to town from factory to factory vandalizing what they found in
factory vandalizing what they found in
factory vandalizing what they found in sight these people were doing this for
sight these people were doing this for
sight these people were doing this for one reason they were scared for their
one reason they were scared for their
one reason they were scared for their future they were scared for their jobs
future they were scared for their jobs
future they were scared for their jobs they saw the automation they saw the
they saw the automation they saw the
they saw the automation they saw the steam and the coal and all the things
steam and the coal and all the things
steam and the coal and all the things that were happening in the world and
that were happening in the world and
that were happening in the world and they knew that the jobs that they and
they knew that the jobs that they and
they knew that the jobs that they and their parents and their grandparents and
their parents and their grandparents and
their parents and their grandparents and generations before had done they knew
generations before had done they knew
generations before had done they knew that those jobs were over that new jobs
that those jobs were over that new jobs
that those jobs were over that new jobs were coming to the place and they didn’t
were coming to the place and they didn’t
were coming to the place and they didn’t know what that meant for them we recall
know what that meant for them we recall
know what that meant for them we recall this group of people the Luddites and we
this group of people the Luddites and we
this group of people the Luddites and we look back on them now and history
look back on them now and history
look back on them now and history doesn’t look kindly on them we think
doesn’t look kindly on them we think
doesn’t look kindly on them we think that they were against progress that
that they were against progress that
that they were against progress that they were against technology they
they were against technology they
they were against technology they couldn’t see the wonders of the
couldn’t see the wonders of the
couldn’t see the wonders of the Industrial Revolution that we’re going
Industrial Revolution that we’re going
Industrial Revolution that we’re going to happen and we even used the word
to happen and we even used the word
to happen and we even used the word Luddite as a little bit of a insult if
Luddite as a little bit of a insult if
Luddite as a little bit of a insult if you haven’t got the latest smartphone on
you haven’t got the latest smartphone on
you haven’t got the latest smartphone on a date and on snapchat Luddite there’s a
a date and on snapchat Luddite there’s a
a date and on snapchat Luddite there’s a new revolution coming the artificial
new revolution coming the artificial
new revolution coming the artificial intelligence revolution and the secret
intelligence revolution and the secret
intelligence revolution and the secret is I’m a little bit of a Luddite not in
is I’m a little bit of a Luddite not in
is I’m a little bit of a Luddite not in the snapchat I don’t have snapchat but
the snapchat I don’t have snapchat but
the snapchat I don’t have snapchat but in the traditional sense you see I’m
in the traditional sense you see I’m
in the traditional sense you see I’m afraid of what’s going to happen to
afraid of what’s going to happen to
afraid of what’s going to happen to people’s jobs so I’m afraid of what
people’s jobs so I’m afraid of what
people’s jobs so I’m afraid of what artificial intelligence means for the
artificial intelligence means for the
artificial intelligence means for the world
AI is really hyped by the media
AI is really hyped by the media everywhere you look you hear about
everywhere you look you hear about
everywhere you look you hear about artificial intelligence at the moment
artificial intelligence at the moment
artificial intelligence at the moment every time there’s a game where their
every time there’s a game where their
every time there’s a game where their computer beats the human the media
computer beats the human the media
computer beats the human the media screams if the robots are about to take
screams if the robots are about to take
screams if the robots are about to take over when the
over when the
over when the blooby Gary Kasparov or when jeopardy
blooby Gary Kasparov or when jeopardy
blooby Gary Kasparov or when jeopardy was finally conquered by IBM what’s more
was finally conquered by IBM what’s more
was finally conquered by IBM what’s more more recently in the news we’ve heard
more recently in the news we’ve heard
more recently in the news we’ve heard about how deep mind solutions conquered
about how deep mind solutions conquered
about how deep mind solutions conquered go we have this sort of perverse desire
go we have this sort of perverse desire
go we have this sort of perverse desire to find computers that are smarter than
to find computers that are smarter than
to find computers that are smarter than us the reality is that actually for the
us the reality is that actually for the
us the reality is that actually for the last 20 years artificial intelligence
last 20 years artificial intelligence
last 20 years artificial intelligence has been slowly permeating into our
has been slowly permeating into our
has been slowly permeating into our society into a world in much quieter
society into a world in much quieter
society into a world in much quieter ways the spam filter that looks at the
ways the spam filter that looks at the
ways the spam filter that looks at the email coming in the GPS system that you
email coming in the GPS system that you
email coming in the GPS system that you use to navigate your car the Ford
use to navigate your car the Ford
use to navigate your car the Ford protection system that protects your
protection system that protects your
protection system that protects your credit-card transactions or the medical
credit-card transactions or the medical
credit-card transactions or the medical diagnosis system the Google search or
diagnosis system the Google search or
diagnosis system the Google search or the advert that’s a little bit eerily
the advert that’s a little bit eerily
the advert that’s a little bit eerily too tailored to you all of these are
too tailored to you all of these are
too tailored to you all of these are examples of artificial intelligence in
examples of artificial intelligence in
examples of artificial intelligence in the real world and they’re all examples
the real world and they’re all examples
the real world and they’re all examples of how a AI is using digital data to
of how a AI is using digital data to
of how a AI is using digital data to make conclusions about what’s happened
make conclusions about what’s happened
make conclusions about what’s happened but over the last five to ten years
but over the last five to ten years
but over the last five to ten years things have really started changing and
things have really started changing and
things have really started changing and improving a new technique called deep
improving a new technique called deep
improving a new technique called deep learning has come along which means we
learning has come along which means we
learning has come along which means we can take any problem any input set and
can take any problem any input set and
can take any problem any input set and through really teaching a computer to
through really teaching a computer to
through really teaching a computer to learn we can find a solution to it so
learn we can find a solution to it so
learn we can find a solution to it so let’s take an example close your eyes
let’s take an example close your eyes
let’s take an example close your eyes actually and imagine in your imagine in
actually and imagine in your imagine in
actually and imagine in your imagine in your mind a snowy scene and imagine a
your mind a snowy scene and imagine a
your mind a snowy scene and imagine a cute little fluffy puppy just you can
cute little fluffy puppy just you can
cute little fluffy puppy just you can just see its face and snow next to it is
just see its face and snow next to it is
just see its face and snow next to it is a cute little fluffy kitten if I asked
a cute little fluffy kitten if I asked
a cute little fluffy kitten if I asked you to describe to me which one’s the
you to describe to me which one’s the
you to describe to me which one’s the kitten and which one’s the puppy and why
kitten and which one’s the puppy and why
kitten and which one’s the puppy and why that is and how you know that you’d
that is and how you know that you’d
that is and how you know that you’d actually find it extremely difficult if
actually find it extremely difficult if
actually find it extremely difficult if you tried to explain it to a computer
you tried to explain it to a computer
you tried to explain it to a computer using mathematical terms you would most
using mathematical terms you would most
using mathematical terms you would most definitely find it impossible and for
definitely find it impossible and for
definitely find it impossible and for decades people have been trying to work
decades people have been trying to work
decades people have been trying to work out how we can solve problems like this
out how we can solve problems like this
out how we can solve problems like this how we can get computers to understand
how we can get computers to understand
how we can get computers to understand what things actually are and what they
what things actually are and what they
what things actually are and what they mean and what deep learning is done is
mean and what deep learning is done is
mean and what deep learning is done is it’s it’s changed the equation it’s
it’s it’s changed the equation it’s
it’s it’s changed the equation it’s allowed us to build learning systems
allowed us to build learning systems
allowed us to build learning systems that can learn like humans the way deep
that can learn like humans the way deep
that can learn like humans the way deep learning works is we pass into a system
learning works is we pass into a system
learning works is we pass into a system hundreds of thousands of photos of dogs
hundreds of thousands of photos of dogs
hundreds of thousands of photos of dogs of cats of pigeons of lions and we let
of cats of pigeons of lions and we let
of cats of pigeons of lions and we let the computer work out what’s what we
the computer work out what’s what we
the computer work out what’s what we tell it this is a cat and this is a dog
tell it this is a cat and this is a dog
tell it this is a cat and this is a dog but we let the computer
but we let the computer
but we let the computer work out what that means and that’s just
work out what that means and that’s just
work out what that means and that’s just how we teach humans if you think about
how we teach humans if you think about
how we teach humans if you think about how you would teach a child what’s a
how you would teach a child what’s a
how you would teach a child what’s a kitten or a puppy is you would show it
kitten or a puppy is you would show it
kitten or a puppy is you would show it to them you would show them books with a
to them you would show them books with a
to them you would show them books with a cute kitten or a cute puppy you take
cute kitten or a cute puppy you take
cute kitten or a cute puppy you take them to the park and they would see
them to the park and they would see
them to the park and they would see those things and they would learn what
those things and they would learn what
those things and they would learn what these things are what they mean and
these things are what they mean and
these things are what they mean and that’s what deep learning does and deep
that’s what deep learning does and deep
that’s what deep learning does and deep learning because of this ability to
learning because of this ability to
learning because of this ability to learn any problem is more interesting
learn any problem is more interesting
learn any problem is more interesting things than being able to differentiate
things than being able to differentiate
things than being able to differentiate between a cat and a dog it can tell us
between a cat and a dog it can tell us
between a cat and a dog it can tell us just by looking whether that mole is
just by looking whether that mole is
just by looking whether that mole is cancerous or whether it’s benign it can
cancerous or whether it’s benign it can
cancerous or whether it’s benign it can tell whether the words that we’re using
tell whether the words that we’re using
tell whether the words that we’re using your friendly or whether they’re hostile
your friendly or whether they’re hostile
your friendly or whether they’re hostile it can understand what you mean when
it can understand what you mean when
it can understand what you mean when you’re talking to a lexer or it can
you’re talking to a lexer or it can
you’re talking to a lexer or it can understand which biomolecules we want
understand which biomolecules we want
understand which biomolecules we want when we need to fight the Ebola virus
when we need to fight the Ebola virus
when we need to fight the Ebola virus that’s spreading through the world in
that’s spreading through the world in
that’s spreading through the world in complex systems like a self-driving car
complex systems like a self-driving car
complex systems like a self-driving car it can understand which way to turn the
it can understand which way to turn the
it can understand which way to turn the steel steering wheel or whether you push
steel steering wheel or whether you push
steel steering wheel or whether you push on the accelerator or or the brake pedal
on the accelerator or or the brake pedal
on the accelerator or or the brake pedal and all of these are just doing the same
and all of these are just doing the same
and all of these are just doing the same things they’re looking at image they’re
things they’re looking at image they’re
things they’re looking at image they’re learning what that image means and
learning what that image means and
learning what that image means and they’re being able to recognize and
they’re being able to recognize and
they’re being able to recognize and detect things in it these are now
detect things in it these are now
detect things in it these are now systems that are no longer just
systems that are no longer just
systems that are no longer just interacting with digital data like
interacting with digital data like
interacting with digital data like emails or GPS coordinates but
emails or GPS coordinates but
emails or GPS coordinates but interacting with sensory data with
interacting with sensory data with
interacting with sensory data with things that they can see and things that
things that they can see and things that
things that they can see and things that they can hear these systems can learn
they can hear these systems can learn
they can hear these systems can learn anything that we can learn that doesn’t
anything that we can learn that doesn’t
anything that we can learn that doesn’t mean they’re intelligent in the same way
mean they’re intelligent in the same way
mean they’re intelligent in the same way as humans it doesn’t mean that they have
as humans it doesn’t mean that they have
as humans it doesn’t mean that they have creativity or rational behavior but it
creativity or rational behavior but it
creativity or rational behavior but it does mean that if we can teach something
does mean that if we can teach something
does mean that if we can teach something to a child or even an adult we can now
to a child or even an adult we can now
to a child or even an adult we can now teach it to a deep learning system
teach it to a deep learning system
teach it to a deep learning system empower louts of all this we’ve seen
empower louts of all this we’ve seen
empower louts of all this we’ve seen massive improvements in MOBOTIX urge you
massive improvements in MOBOTIX urge you
massive improvements in MOBOTIX urge you will after this to go and look up a
will after this to go and look up a
will after this to go and look up a robot called atlas atlas has been in
robot called atlas atlas has been in
robot called atlas atlas has been in development for many years and there are
development for many years and there are
development for many years and there are lots of videos that come out it started
lots of videos that come out it started
lots of videos that come out it started off as a humanoid 6-foot robot that
off as a humanoid 6-foot robot that
off as a humanoid 6-foot robot that could go into a factory and start
could go into a factory and start
could go into a factory and start stacking shelves and today it can now
stacking shelves and today it can now
stacking shelves and today it can now still do that but it can also jump up
still do that but it can also jump up
still do that but it can also jump up stairs and backflip significantly better
stairs and backflip significantly better
stairs and backflip significantly better than me off the box if you compare what
than me off the box if you compare what
than me off the box if you compare what deep learning can do and you bring it
deep learning can do and you bring it
deep learning can do and you bring it these advances in robotics is it’s clear
these advances in robotics is it’s clear
these advances in robotics is it’s clear to see that hey I can very quickly start
to see that hey I can very quickly start
to see that hey I can very quickly start to replace jobs so then there’s an
to replace jobs so then there’s an
to replace jobs so then there’s an obvious question of will it well when
obvious question of will it well when
obvious question of will it well when you think
you think
you think this warehouse worker is not going to
this warehouse worker is not going to
this warehouse worker is not going to need any sick leave or lunch breaks when
need any sick leave or lunch breaks when
need any sick leave or lunch breaks when you think you can sack that HR
you think you can sack that HR
you think you can sack that HR department and you don’t need any health
department and you don’t need any health
department and you don’t need any health and safety requirements anymore it
and safety requirements anymore it
and safety requirements anymore it suddenly becomes quite obvious why a
suddenly becomes quite obvious why a
suddenly becomes quite obvious why a factory or warehouse would choose to
factory or warehouse would choose to
factory or warehouse would choose to have robots not people they also
have robots not people they also
have robots not people they also advantages like you can patch the hole
advantages like you can patch the hole
advantages like you can patch the hole or every single robot with the same
or every single robot with the same
or every single robot with the same software upgrade at once if you’ve got
software upgrade at once if you’ve got
software upgrade at once if you’ve got one worker at the moment that’s a bit
one worker at the moment that’s a bit
one worker at the moment that’s a bit annoying or keeps making the same
annoying or keeps making the same
annoying or keeps making the same mistake you can maybe give them
mistake you can maybe give them
mistake you can maybe give them education and you know help try and fix
education and you know help try and fix
education and you know help try and fix them but that doesn’t help fix everyone
them but that doesn’t help fix everyone
them but that doesn’t help fix everyone else in that workshop or warehouse when
else in that workshop or warehouse when
else in that workshop or warehouse when they get stuff wrong with these systems
they get stuff wrong with these systems
they get stuff wrong with these systems you teach one thing and they all learn
you teach one thing and they all learn
you teach one thing and they all learn and there is a real sense of collective
and there is a real sense of collective
and there is a real sense of collective learning here when you’re born that’s
learning here when you’re born that’s
learning here when you’re born that’s that’s you all of your experiences all
that’s you all of your experiences all
that’s you all of your experiences all of your learning are then yourself with
of your learning are then yourself with
of your learning are then yourself with these self-driving cars for example the
these self-driving cars for example the
these self-driving cars for example the reason that they’ve come on so quickly
reason that they’ve come on so quickly
reason that they’ve come on so quickly is because every single road a
is because every single road a
is because every single road a self-driving car drives down it’s not
self-driving car drives down it’s not
self-driving car drives down it’s not just it that’s learning about that road
just it that’s learning about that road
just it that’s learning about that road every other car is learning about that
every other car is learning about that
every other car is learning about that road every time somebody bashes into the
road every time somebody bashes into the
road every time somebody bashes into the back of a car which has happened all of
back of a car which has happened all of
back of a car which has happened all of these are the cars learn from from that
these are the cars learn from from that
these are the cars learn from from that mistake there’s the hive mind going on
mistake there’s the hive mind going on
mistake there’s the hive mind going on between all these systems so it’s
between all these systems so it’s
between all these systems so it’s obvious to me and to anyone in this
obvious to me and to anyone in this
obvious to me and to anyone in this field that big companies very quickly
field that big companies very quickly
field that big companies very quickly are going to start embracing and using
are going to start embracing and using
are going to start embracing and using this technology so we know that already
this technology so we know that already
this technology so we know that already Amazon are trying to have drones instead
Amazon are trying to have drones instead
Amazon are trying to have drones instead of delivery people and we know as soon
of delivery people and we know as soon
of delivery people and we know as soon as the technology is ready that they’ll
as the technology is ready that they’ll
as the technology is ready that they’ll sack their 400,000 warehouse workers and
sack their 400,000 warehouse workers and
sack their 400,000 warehouse workers and we place them with robots
we place them with robots
we place them with robots uber have already said that they want to
uber have already said that they want to
uber have already said that they want to get rid of 3 million of their taxi
get rid of 3 million of their taxi
get rid of 3 million of their taxi drivers and replaced them with
drivers and replaced them with
drivers and replaced them with self-driving cars and why wouldn’t they
self-driving cars and why wouldn’t they
self-driving cars and why wouldn’t they every single taxi trip will have a
every single taxi trip will have a
every single taxi trip will have a hundred percent gross margin for that
hundred percent gross margin for that
hundred percent gross margin for that company forever from that point and once
company forever from that point and once
company forever from that point and once that happens everyone else will have to
that happens everyone else will have to
that happens everyone else will have to follow suit to be able to keep her a
follow suit to be able to keep her a
follow suit to be able to keep her a company that’s got a workforce of a
company that’s got a workforce of a
company that’s got a workforce of a hundred people can’t financially compete
hundred people can’t financially compete
hundred people can’t financially compete with an equivalent company that pays no
with an equivalent company that pays no
with an equivalent company that pays no one there were lots of studies into this
one there were lots of studies into this
one there were lots of studies into this at the moment and most of these studies
at the moment and most of these studies
at the moment and most of these studies are showing that between 10 and 50
are showing that between 10 and 50
are showing that between 10 and 50 percent of jobs are vulnerable to this
percent of jobs are vulnerable to this
percent of jobs are vulnerable to this sort of AI robotic automation over the
sort of AI robotic automation over the
sort of AI robotic automation over the next 20 to 25 years and that’s all sorts
next 20 to 25 years and that’s all sorts
next 20 to 25 years and that’s all sorts of jobs it’s not just the obvious jobs
of jobs it’s not just the obvious jobs
of jobs it’s not just the obvious jobs that you
that you
that you think of it’s not just the warehouse
think of it’s not just the warehouse
think of it’s not just the warehouse work or the production line staff or the
work or the production line staff or the
work or the production line staff or the taxi driver I have the privilege of
taxi driver I have the privilege of
taxi driver I have the privilege of working with some of the smartest
working with some of the smartest
working with some of the smartest doctors in the world on some of the most
doctors in the world on some of the most
doctors in the world on some of the most complex problems and when I recently
complex problems and when I recently
complex problems and when I recently went to dinner with them and I asked
went to dinner with them and I asked
went to dinner with them and I asked them whether they thought they would be
them whether they thought they would be
them whether they thought they would be replaceable in the next 15 20 years they
replaceable in the next 15 20 years they
replaceable in the next 15 20 years they were very quick to tell me about how
were very quick to tell me about how
were very quick to tell me about how important empathy is and how important
important empathy is and how important
important empathy is and how important their creative problem-solving is but
their creative problem-solving is but
their creative problem-solving is but they’re also very open that actually a
they’re also very open that actually a
they’re also very open that actually a lot of what they do is just procedural
lot of what they do is just procedural
lot of what they do is just procedural it’s stuff they learned at medical
it’s stuff they learned at medical
it’s stuff they learned at medical school and they’ve learned for their
school and they’ve learned for their
school and they’ve learned for their career and now they’re just applying
career and now they’re just applying
career and now they’re just applying that knowledge think about yourself if
that knowledge think about yourself if
that knowledge think about yourself if you went to a any accident an emergency
you went to a any accident an emergency
you went to a any accident an emergency and you think you might have a broken
and you think you might have a broken
and you think you might have a broken leg the doctor will ask some questions
leg the doctor will ask some questions
leg the doctor will ask some questions that sort of prompt over a little bit
that sort of prompt over a little bit
that sort of prompt over a little bit they’ll take you down to the x-ray room
they’ll take you down to the x-ray room
they’ll take you down to the x-ray room where you’ll get an x-ray and they’ll
where you’ll get an x-ray and they’ll
where you’ll get an x-ray and they’ll bring you back they’ll add those
bring you back they’ll add those
bring you back they’ll add those different things together and give you a
different things together and give you a
different things together and give you a diagnosis they’ll then tell you in the
diagnosis they’ll then tell you in the
diagnosis they’ll then tell you in the kindest way about yes you’ve got a
kindest way about yes you’ve got a
kindest way about yes you’ve got a broken leg you are out of sport for the
broken leg you are out of sport for the
broken leg you are out of sport for the next two years and they’ll know that if
next two years and they’ll know that if
next two years and they’ll know that if they tell me that that’s probably
they tell me that that’s probably
they tell me that that’s probably matters less than if they tell a
matters less than if they tell a
matters less than if they tell a professional athlete that that last bit
professional athlete that that last bit
professional athlete that that last bit is very human it’s very empathetic but
is very human it’s very empathetic but
is very human it’s very empathetic but everything else they’re doing is
everything else they’re doing is
everything else they’re doing is practical formulaic system that can be
practical formulaic system that can be
practical formulaic system that can be and will be automated so I will replace
and will be automated so I will replace
and will be automated so I will replace jobs now economists have a phrase they
jobs now economists have a phrase they
jobs now economists have a phrase they use and that phrase is the Luddite
use and that phrase is the Luddite
use and that phrase is the Luddite fallacy it echoes back to the Luddites
fallacy it echoes back to the Luddites
fallacy it echoes back to the Luddites we talked about at the beginning and it
we talked about at the beginning and it
we talked about at the beginning and it says actually we shouldn’t fear for loss
says actually we shouldn’t fear for loss
says actually we shouldn’t fear for loss of jobs the Luddites were bong it’s not
of jobs the Luddites were bong it’s not
of jobs the Luddites were bong it’s not that jobs disappear it’s that when some
that jobs disappear it’s that when some
that jobs disappear it’s that when some jobs go technology brings other jobs
jobs go technology brings other jobs
jobs go technology brings other jobs instead there’s a change of composition
instead there’s a change of composition
instead there’s a change of composition of jobs in the economy that was true in
of jobs in the economy that was true in
of jobs in the economy that was true in the Industrial Revolution if a weaver
the Industrial Revolution if a weaver
the Industrial Revolution if a weaver saw a new weaving machine a loom that
saw a new weaving machine a loom that
saw a new weaving machine a loom that was ten hundred times faster than it the
was ten hundred times faster than it the
was ten hundred times faster than it the weaver would be out of work but somebody
weaver would be out of work but somebody
weaver would be out of work but somebody would then need to maintain and build
would then need to maintain and build
would then need to maintain and build the Loom itself so they could just
the Loom itself so they could just
the Loom itself so they could just quickly retrain and move into a
quickly retrain and move into a
quickly retrain and move into a different Factory Britain of old used to
different Factory Britain of old used to
different Factory Britain of old used to be and powered by horses every
be and powered by horses every
be and powered by horses every transportation would be riding on a
transportation would be riding on a
transportation would be riding on a horse suddenly steam trains and you know
horse suddenly steam trains and you know
horse suddenly steam trains and you know modern transportation came along what
modern transportation came along what
modern transportation came along what happened to the stable boys that were
happened to the stable boys that were
happened to the stable boys that were there shoveling out the horses muck
there shoveling out the horses muck
there shoveling out the horses muck every night while they went into the
every night while they went into the
every night while they went into the trains they started filling those with
trains they started filling those with
trains they started filling those with with coal instead we used to have these
with coal instead we used to have these
with coal instead we used to have these things in Britain that I sort of wish we
things in Britain that I sort of wish we
things in Britain that I sort of wish we still had which were called knock of
still had which were called knock of
still had which were called knock of uppers
uppers
uppers he would walk down the street tapping
he would walk down the street tapping
he would walk down the street tapping the window at an allotted time to get
the window at an allotted time to get
the window at an allotted time to get you up for work someone invented the
you up for work someone invented the
you up for work someone invented the alarm clock which must have really
alarm clock which must have really
alarm clock which must have really annoyed them but those people then just
annoyed them but those people then just
annoyed them but those people then just moved on to the production lines making
moved on to the production lines making
moved on to the production lines making alarm clocks the Industrial Revolution
alarm clocks the Industrial Revolution
alarm clocks the Industrial Revolution didn’t destroy jobs
didn’t destroy jobs
didn’t destroy jobs it changed the jobs it changed the
it changed the jobs it changed the
it changed the jobs it changed the composition of jobs in the workforce but
composition of jobs in the workforce but
composition of jobs in the workforce but this won’t happen with artificial
this won’t happen with artificial
this won’t happen with artificial intelligence if we are saying that AI
intelligence if we are saying that AI
intelligence if we are saying that AI and modern MOBOTIX are going to be able
and modern MOBOTIX are going to be able
and modern MOBOTIX are going to be able to replace any doing bits of jobs then
to replace any doing bits of jobs then
to replace any doing bits of jobs then just because there’s a new doing bit of
just because there’s a new doing bit of
just because there’s a new doing bit of a job coming instead and I will just do
a job coming instead and I will just do
a job coming instead and I will just do that if uber makes three million of its
that if uber makes three million of its
that if uber makes three million of its taxi drivers redundant they’re not
taxi drivers redundant they’re not
taxi drivers redundant they’re not suddenly going to train to be software
suddenly going to train to be software
suddenly going to train to be software developers so they can manage the
developers so they can manage the
developers so they can manage the self-driving cars they won’t have the
self-driving cars they won’t have the
self-driving cars they won’t have the skills the education knowledge to be
skills the education knowledge to be
skills the education knowledge to be able to do that and even if they did we
able to do that and even if they did we
able to do that and even if they did we don’t need three million new software
don’t need three million new software
don’t need three million new software developers Microsoft Windows only has
developers Microsoft Windows only has
developers Microsoft Windows only has five thousand people working on it and
five thousand people working on it and
five thousand people working on it and it powers half the computers in the
it powers half the computers in the
it powers half the computers in the world so what will happen to these
world so what will happen to these
world so what will happen to these people what does this mean for society
people what does this mean for society
people what does this mean for society well it opens up some very scary
well it opens up some very scary
well it opens up some very scary questions if we’re saying 10 to 50
questions if we’re saying 10 to 50
questions if we’re saying 10 to 50 percent of jobs of vulnerable in 25
percent of jobs of vulnerable in 25
percent of jobs of vulnerable in 25 years that’s half a billion to two and a
years that’s half a billion to two and a
years that’s half a billion to two and a half billion jobs that are going to go
half billion jobs that are going to go
half billion jobs that are going to go where do we find two and a half billion
where do we find two and a half billion
where do we find two and a half billion new jobs and if we find that how do we
new jobs and if we find that how do we
new jobs and if we find that how do we how do we train how do we educate two
how do we train how do we educate two
how do we train how do we educate two and a half billion people to go and do
and a half billion people to go and do
and a half billion people to go and do those jobs our education system isn’t
those jobs our education system isn’t
those jobs our education system isn’t set up for this we teach skills we teach
set up for this we teach skills we teach
set up for this we teach skills we teach knowledge we teach vocation but we don’t
knowledge we teach vocation but we don’t
knowledge we teach vocation but we don’t teach is how to learn we don’t teach is
teach is how to learn we don’t teach is
teach is how to learn we don’t teach is creativity and critical thinking and how
creativity and critical thinking and how
creativity and critical thinking and how can we build economies that can actually
can we build economies that can actually
can we build economies that can actually cope with this economy’s a built on
cope with this economy’s a built on
cope with this economy’s a built on production the companies that output the
production the companies that output the
production the companies that output the most the countries that output the most
most the countries that output the most
most the countries that output the most of the countries that win when the
of the countries that win when the
of the countries that win when the output is done by robotics and what
output is done by robotics and what
output is done by robotics and what humans are doing is the creativity and
humans are doing is the creativity and
humans are doing is the creativity and the critical thinking what does that
the critical thinking what does that
the critical thinking what does that mean through an economy and what happens
mean through an economy and what happens
mean through an economy and what happens what happens to the people if we can’t
what happens to the people if we can’t
what happens to the people if we can’t do this what if there aren’t two and a
do this what if there aren’t two and a
do this what if there aren’t two and a half billion new jobs and even if there
half billion new jobs and even if there
half billion new jobs and even if there are what happens before we make those
are what happens before we make those
are what happens before we make those jobs and retrain people we’re gonna have
jobs and retrain people we’re gonna have
jobs and retrain people we’re gonna have a point where we can
a point where we can
a point where we can have ten fifty percent of our workforce
have ten fifty percent of our workforce
have ten fifty percent of our workforce unemployed in 25 30 years it’s going to
unemployed in 25 30 years it’s going to
unemployed in 25 30 years it’s going to be a long time before the word jobs to
be a long time before the word jobs to
be a long time before the word jobs to replace those people we are facing mass
replace those people we are facing mass
replace those people we are facing mass unemployment in the very near future how
unemployment in the very near future how
unemployment in the very near future how do we deal with that as a society and
do we deal with that as a society and
do we deal with that as a society and how do people as individuals deal with
how do people as individuals deal with
how do people as individuals deal with that we know that retirement increases
that we know that retirement increases
that we know that retirement increases the risk of depression by 40 percent I
the risk of depression by 40 percent I
the risk of depression by 40 percent I couldn’t find stats for redundancy but
couldn’t find stats for redundancy but
couldn’t find stats for redundancy but imagine what we didn’t see with the
imagine what we didn’t see with the
imagine what we didn’t see with the knowledge that you’ve probably got no
knowledge that you’ve probably got no
knowledge that you’ve probably got no job ever again imagine what that’s going
job ever again imagine what that’s going
job ever again imagine what that’s going to do it’s a mental health in a society
to do it’s a mental health in a society
to do it’s a mental health in a society where mental health is already our
where mental health is already our
where mental health is already our biggest issue it’s also important to
biggest issue it’s also important to
biggest issue it’s also important to think back to the Industrial Revolution
think back to the Industrial Revolution
think back to the Industrial Revolution we look back on the Industrial
we look back on the Industrial
we look back on the Industrial Revolution and we we think of it as a as
Revolution and we we think of it as a as
Revolution and we we think of it as a as a sweeping progress we think yeah there
a sweeping progress we think yeah there
a sweeping progress we think yeah there was some little hiccups but the
was some little hiccups but the
was some little hiccups but the Industrial Revolution was also horrible
Industrial Revolution was also horrible
Industrial Revolution was also horrible time it was a time of exploitation it
time it was a time of exploitation it
time it was a time of exploitation it was a time of the wealthiest almost
was a time of the wealthiest almost
was a time of the wealthiest almost using the the purse to slaves and today
using the the purse to slaves and today
using the the purse to slaves and today we still have modern-day slavery we have
we still have modern-day slavery we have
we still have modern-day slavery we have mass exploitation through the whole of
mass exploitation through the whole of
mass exploitation through the whole of society and it was bloody as well like
society and it was bloody as well like
society and it was bloody as well like the Industrial Revolution caused the
the Industrial Revolution caused the
the Industrial Revolution caused the rise of capitalism the rise of communism
rise of capitalism the rise of communism
rise of capitalism the rise of communism it caused war after war afterwards
it caused war after war afterwards
it caused war after war afterwards people try to find ideologies that could
people try to find ideologies that could
people try to find ideologies that could answer the questions of what the
answer the questions of what the
answer the questions of what the Industrial Revolution means it caused
Industrial Revolution means it caused
Industrial Revolution means it caused tens of millions of deaths we look back
tens of millions of deaths we look back
tens of millions of deaths we look back on the Luddites as foolish but actually
on the Luddites as foolish but actually
on the Luddites as foolish but actually were they foolish actually did they not
were they foolish actually did they not
were they foolish actually did they not understand that transitioning a whole
understand that transitioning a whole
understand that transitioning a whole economy from one thing to another was
economy from one thing to another was
economy from one thing to another was maybe harder than a few rich politicians
maybe harder than a few rich politicians
maybe harder than a few rich politicians thought and what happened this time when
thought and what happened this time when
thought and what happened this time when actually it’s not sort of 10% of people
actually it’s not sort of 10% of people
actually it’s not sort of 10% of people unemployed and everyone else just having
unemployed and everyone else just having
unemployed and everyone else just having to do jobs they don’t want but it’s
to do jobs they don’t want but it’s
to do jobs they don’t want but it’s actually 50% of people out of work so we
actually 50% of people out of work so we
actually 50% of people out of work so we need to prepare both people and society
need to prepare both people and society
need to prepare both people and society we need to be educating children and
we need to be educating children and
we need to be educating children and adults in a way that means they can
adults in a way that means they can
adults in a way that means they can learn new skills that they can choose to
learn new skills that they can choose to
learn new skills that they can choose to learn they can learn we need to focus on
learn they can learn we need to focus on
learn they can learn we need to focus on critical thinking in our education
critical thinking in our education
critical thinking in our education system and we need to prepare with
system and we need to prepare with
system and we need to prepare with society as government’s as welfare
society as government’s as welfare
society as government’s as welfare states how does a welfare state cope
states how does a welfare state cope
states how does a welfare state cope when 50% of your population are giving
when 50% of your population are giving
when 50% of your population are giving and 50% are taking
and 50% are taking
and 50% are taking we’ve currently been trying things like
we’ve currently been trying things like
we’ve currently been trying things like basic income many countries of
basic income many countries of
basic income many countries of experiments with this and this is the
experiments with this and this is the
experiments with this and this is the idea that you we give a small amount of
idea that you we give a small amount of
idea that you we give a small amount of money to somebody enough maybe to put a
money to somebody enough maybe to put a
money to somebody enough maybe to put a roof over their head and to keep them
roof over their head and to keep them
roof over their head and to keep them fed but that then they can choose what
fed but that then they can choose what
fed but that then they can choose what they do at their time they can train for
they do at their time they can train for
they do at their time they can train for new skills they can go and get a job if
new skills they can go and get a job if
new skills they can go and get a job if they can find one or they can just relax
they can find one or they can just relax
they can find one or they can just relax at home we don’t know where the basic
at home we don’t know where the basic
at home we don’t know where the basic income is going to work or not yet it’s
income is going to work or not yet it’s
income is going to work or not yet it’s too early to tell but it’s important the
too early to tell but it’s important the
too early to tell but it’s important the society recognizes these challenges and
society recognizes these challenges and
society recognizes these challenges and start experimenting with ideas like this
start experimenting with ideas like this
start experimenting with ideas like this and maybe this is a positive thing maybe
and maybe this is a positive thing maybe
and maybe this is a positive thing maybe this is a future of the rise of the
this is a future of the rise of the
this is a future of the rise of the artisan if everything can be
artisan if everything can be
artisan if everything can be mass-produced
mass-produced
mass-produced at scales we can’t even imagine by by
at scales we can’t even imagine by by
at scales we can’t even imagine by by these robotic AI systems maybe the thing
these robotic AI systems maybe the thing
these robotic AI systems maybe the thing the human makes with its imperfections
the human makes with its imperfections
the human makes with its imperfections is actually the beauty maybe a society
is actually the beauty maybe a society
is actually the beauty maybe a society we start to reward creativity and art
we start to reward creativity and art
we start to reward creativity and art and music in a way that we just don’t at
and music in a way that we just don’t at
and music in a way that we just don’t at the moment because it doesn’t make
the moment because it doesn’t make
the moment because it doesn’t make people richer or maybe the future of
people richer or maybe the future of
people richer or maybe the future of humanity is just netflix and chill’
humanity is just netflix and chill’
humanity is just netflix and chill’ maybe it’s getting back to animalistic
maybe it’s getting back to animalistic
maybe it’s getting back to animalistic boots and sitting at home and doing
boots and sitting at home and doing
boots and sitting at home and doing whatever embracing nature enjoying the
whatever embracing nature enjoying the
whatever embracing nature enjoying the world for what it was maybe actually
world for what it was maybe actually
world for what it was maybe actually work is a burden but I know for myself
work is a burden but I know for myself
work is a burden but I know for myself that the creativity the challenge the
that the creativity the challenge the
that the creativity the challenge the risk and reward that work brings are
risk and reward that work brings are
risk and reward that work brings are things that give me purpose and drive if
things that give me purpose and drive if
things that give me purpose and drive if you take that away from me what does
you take that away from me what does
you take that away from me what does that leave me with what gets me out of
that leave me with what gets me out of
that leave me with what gets me out of bed in the morning so what do we do what
bed in the morning so what do we do what
bed in the morning so what do we do what are the solutions well the first thing
are the solutions well the first thing
are the solutions well the first thing that’s important to say is that you do
that’s important to say is that you do
that’s important to say is that you do not want to leave this to geeks like me
not want to leave this to geeks like me
not want to leave this to geeks like me to sort out this isn’t a problem for AI
to sort out this isn’t a problem for AI
to sort out this isn’t a problem for AI developers or software developers to
developers or software developers to
developers or software developers to sort out this is a problem for society
sort out this is a problem for society
sort out this is a problem for society to sort out we need the sociologists and
to sort out we need the sociologists and
to sort out we need the sociologists and psychologists that understand human
psychologists that understand human
psychologists that understand human behavior we need the business people who
behavior we need the business people who
behavior we need the business people who are going to have to choose between
are going to have to choose between
are going to have to choose between hiring a robot or hiring a person we
hiring a robot or hiring a person we
hiring a robot or hiring a person we need the doctors who are going to see
need the doctors who are going to see
need the doctors who are going to see changes in their healthcare system they
changes in their healthcare system they
changes in their healthcare system they can I imagine we need the 50% we’re
can I imagine we need the 50% we’re
can I imagine we need the 50% we’re going to lose their jobs to have voices
going to lose their jobs to have voices
going to lose their jobs to have voices not just have things imposed on them
not just have things imposed on them
not just have things imposed on them this is a problem not just for me not
this is a problem not just for me not
this is a problem not just for me not just for the people that are making this
just for the people that are making this
just for the people that are making this software but it’s a problem for
software but it’s a problem for
software but it’s a problem for everybody else in society and we need to
everybody else in society and we need to
everybody else in society and we need to come to
come to
come to gather an experiment we need to try
gather an experiment we need to try
gather an experiment we need to try things we need to come up with ideas and
things we need to come up with ideas and
things we need to come up with ideas and we need to discuss and debate not with a
we need to discuss and debate not with a
we need to discuss and debate not with a iesson nightmarish hell or some godlike
iesson nightmarish hell or some godlike
iesson nightmarish hell or some godlike thing that’s going to take over the
thing that’s going to take over the
thing that’s going to take over the world of us some hyped up hoaxes it’s
world of us some hyped up hoaxes it’s
world of us some hyped up hoaxes it’s none of those things
none of those things
none of those things hey isn’t complex to understand it’s not
hey isn’t complex to understand it’s not
hey isn’t complex to understand it’s not difficult it’s not it’s not challenging
difficult it’s not it’s not challenging
difficult it’s not it’s not challenging you can go out there and you can read
you can go out there and you can read
you can go out there and you can read things on it to understand what AI is
things on it to understand what AI is
things on it to understand what AI is what deep learning is what the future
what deep learning is what the future
what deep learning is what the future holds you can see the debates over the
holds you can see the debates over the
holds you can see the debates over the talk I’m having whether it will remove
talk I’m having whether it will remove
talk I’m having whether it will remove jobs whether it won’t but you need to go
jobs whether it won’t but you need to go
jobs whether it won’t but you need to go out there and educate yourselves and you
out there and educate yourselves and you
out there and educate yourselves and you need to make your voices heard
need to make your voices heard
need to make your voices heard artificial intelligence can bring such
artificial intelligence can bring such
artificial intelligence can bring such amazing power to the world it can
amazing power to the world it can
amazing power to the world it can potentially cure any disease it can
potentially cure any disease it can
potentially cure any disease it can potentially fix the planet fix the
potentially fix the planet fix the
potentially fix the planet fix the damage we’ve done to it it can
damage we’ve done to it it can
damage we’ve done to it it can potentially get us to Mars and take us
potentially get us to Mars and take us
potentially get us to Mars and take us across the whole galaxy exploring the
across the whole galaxy exploring the
across the whole galaxy exploring the reason I work in artificial intelligence
reason I work in artificial intelligence
reason I work in artificial intelligence is that for me it’s the most exciting
is that for me it’s the most exciting
is that for me it’s the most exciting field you could possibly be in but it
field you could possibly be in but it
field you could possibly be in but it comes with risks and it comes with
comes with risks and it comes with
comes with risks and it comes with dangers and we cannot be naive to that
dangers and we cannot be naive to that
dangers and we cannot be naive to that unless somebody else sort that problem
unless somebody else sort that problem
unless somebody else sort that problem out the future is in our control it’s in
out the future is in our control it’s in
out the future is in our control it’s in your control you can choose how the
your control you can choose how the
your control you can choose how the future is shaped for you for your kids
future is shaped for you for your kids
future is shaped for you for your kids for the generations to come but if you
for the generations to come but if you
for the generations to come but if you just sit by and let other people sort
just sit by and let other people sort
just sit by and let other people sort this out then the rich will get richer
this out then the rich will get richer
this out then the rich will get richer the corporation’s will have the robots
the corporation’s will have the robots
the corporation’s will have the robots the purr will get purr and the world
the purr will get purr and the world
the purr will get purr and the world will not be a fun place to be so I urge
will not be a fun place to be so I urge
will not be a fun place to be so I urge you I beg of you to go and learn to go
you I beg of you to go and learn to go
you I beg of you to go and learn to go and educate yourself and to debate and
and educate yourself and to debate and
and educate yourself and to debate and to fight and to think about what is
to fight and to think about what is
to fight and to think about what is right for society thank you
right for society thank you
right for society thank you [Applause]
[Applause]
[Applause] [Music]
[Music]
[Music] you
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