[Music]
[Applause]
[Music]
[Applause]
[Music]
so rain is a marvelous machine you can
do lots of things it is responsible all
the thoughts emotions and complex
decisions that you’re making and
everyone in this room has one and only
one okay so with this Amar’e marvelous
machine we created AI which is getting
more and more powerful every day and now
we’re spending a lot of time thinking
about when AI might exceed us and begins
to threaten us and also we have the
challenge of controlling AI so that it
can benefit human society so the
question arises as to whether we can use
our brain in AI to understand ourselves
because in order to understand the
questions about the relationship between
humans in AI not only we have to
understand how the AI is created what it
can do but we also have to understand
who we are and what we are capable of
doing and my main argument today is that
we know far more about AI then about the
human brain that’s why I chose this
image because if you look at this image
carefully which was painted by my
favorite artist Rene Magritte
you can see that the mirror shows you
active reflection of the book the small
book but it’s not what you would expect
to see for the image of the person
standing in front of the mirror and
symbolically and figuratively I’d like
to argue that AI is like that small book
and we still don’t know exactly who you
are
even if you use the most powerful
scientific engine that we have developed
in our history and to illustrate that I
like to point out several interesting
features of our human brain what we what
the brains do well which might be
somewhat counterintuitive this might be
different from what you always assume
what the brains really do as a first
illustration I want you to focus on the
the the red da on at the center of this
image and try not to move your eyes try
to fixate the red dot and notice the
fact that while you’re doing that
probably all of you can see three other
colored dots in your peripheral vision
yellow green and white dot okay but
you’ll notice that those dots will
disappear from your vision once the moon
begins to rotate and please raise your
hand so that I have a sense as to
whether this is working on now when the
dots seem to disappear thank you so this
is a very famous illusion in psychology
called
emotion induced blindness and it’s been
confusing and baffling to many
psychologists because it’s not that easy
to explain as to why this happens but at
a higher level this is quite expected
because this happens because our brain
is a predictive machine a lot of us
think that the brain gives us a very
accurate and reliable reflect of
representation of the outside world like
the library where you can save
information for countless books and you
can retrieve the information you want
from a particular page or theater where
you can see the movements of all the
actors accurately but that’s not what
the brain is is good at what plan is
trying to do is always try to predict
what’s gonna happen it’s tuned and
constantly looking for things that are
unpredictable that you did not predict
and then try to minimize the errors or
discrepancy between what what you
predicted and what you observe in the
outside world and the reason why these
thoughts disappear after a few seconds
is because those starts are completely
predictable and therefore grant loses
interest quickly and therefore the B&C
raise it from your your mental mental
activity the kind of explanation can
deal with lots of other complex
phenomena zin in the brain for example
if you present any sensory stimulus such
as a flash or sound and then maintain it
for a while and then turn it off the
neurons in the brain do not follow that
pattern precisely instead what they tend
to do is that they show vigorous
response huge response at the onset of
the sensory
stimulus and then quickly reduces their
activity and then when the stimulus is
remove it briefly suppresses activity
the reason why they do that with one
explanation for that is because these
neurons are constantly looking for
surprising unpredictable events so when
the sickness is turned on unpredictable
lead neurons respond vigorously and then
when it’s turned off unexpectedly they
briefly suppress this activity but when
there are no changes in the environment
neurons actually are not that interested
in another example that’s consistent
with this kind of explanation is this
illusion called rotating snakes and if
you fixate any point in this image and
do not move your eyes you can confirm
that this image is completely static
there’s nothing in the screen that’s
moving around but as soon as you begin
to begin to move your eyes around you’ll
notice that a lot of these circles
briefly boot rotate
okay and again this is very confusing
why do we see motions that’s not there
in the physical world an interesting
study that’s been recent that was
recently published that if you build a
deep learning network this is a
cutting-edge AI model of our human
cognition and then train that network to
try to predict what’s gonna be the next
frame in a in a many in many different
movies that you give you used to train
this network thus though those kinds of
deep learning network will also see the
illusory mush motion did you see it with
this with this word rotating snake
illusion again suggesting that the
reason why you see this illusory motion
is because your brain is more interested
in predicting what’s gonna happen in the
next screen rather than analyzing what’s
currently on the screen okay so that’s a
one important feature of our brain that
we may not be aware of all the time that
I agree our brain is a predictive
machine so we might be able to predict
how the difference between the eye and
humans will change but we may not it
might be harder for us to understand
exactly what pre-human brains are and
what the difference between AI and human
human brain is second important feature
the human brain and mind that I’d like
to point out is that we
or you’re very efficient in categorizing
things so when I show you image like
this everyone in this room can
immediately recognize that all apples
and there are green apples and red
apples and of course there are many
other features in this image that you’re
instantaneously ignore such as subtle
changes in the colors and subtle changes
in the color in the in the size of the
apples but we are we can effortlessly
classify and categorize different
objects that we see and this is very
hard for AI to do okay and in fact many
AI algorithms sort of kind of show off
their performance by showing that they
can categorize different images into
cats and dogs and so on but humans are
really really good at does but this
comes at a cost as well because as soon
as you start categorizing things to
discrete value this could domains your
would start to ignore the subtle
differences between them so the question
is why are we so good at categorizing
things and why are also so good at
ignoring reached variations among
different different individual objects
so the reason why we’re so good at
ignoring different features is because
the brain evolved not to accurately
represent the outside world but to
choose the most beneficial action for us
and that requires different kind of
functions our properties so for example
imagine that you’re both tired and
hungry and so you need to sleep and eat
almost at the same time and imagine that
you are like indecisive and you’re
trying to switch between these two
activities constantly you’re going back
and forth between the bed and the
kitchen we will not accomplish either of
these objectives so in order in order to
deal with these kinds of conflicting
situations what the brain has to do is
build a networks that has these kinds of
structures where neurons that are
responsible for selecting sleeping
behavior once they get chosen that they
have to maintain their activity and then
suppress the the activities are
competing neurons that might be
promoting eating so that while you’re
sleeping you don’t get up constantly to
go to the cat
and vice-versa so these two functions
are often referred to as a self
excite-ation that maintains the activity
of neuron of persistently and then
mutual inhibition because you don’t want
the competing actions to interrupt your
ongoing activity in this type of action
selection might be the reason why even
when we’re trying to evaluate different
objects we see in the sensory world we
tend to categorize things right away so
third feature of our mind and brain is
the fact that we’re extremely social and
therefore our brain is also extremely
social and the reason is because social
activity is more important than
individual decision-making in every
their life point in almost every moment
in every moment in our lives and also
this requires very complicated
computations because unlike when you’re
making decisions individually when
you’re acting in a social context what’s
most important is for you to accurately
predict what other people will do
because success and failures of action
really depends upon your ability to
predict whether other people other
people will do but this is this gets
complicated very quickly because we and
you and me both you and I have similar
hardware’s
our brains and have similar objectives
and therefore just like I’m predicting
trying to predict what you’re gonna do
you are also trying to predict what I’m
gonna do and therefore for me to be able
to predict what you’re gonna do
accurately I also need to be able to
predict what you’re gonna predict that
I’m gonna do and this can go on many
many times and creates a very
complicated loop and therefore it
creates a lots of rooms for errors in a
lot of mental disabilities that we have
actually correspond to the failures in
this type of mental simulations and
imagining what other people might be
thinking and so on so that that’s the
cost of having a extremely successful
social social brain that dill deals with
these complicated social situations one
last feature that I’d like to point down
is that our brains are analog computers
and this is important to keep in mind
because we offer in order to understand
the spaz strategies that we have to
adopt when we’re dealing with the AI
rapidly developing a technology is that
we like to understand the relation a
difference between human computer human
brains and and digital computers and
often tend to think that a lot of the
features that digital computers have
might be applicable to human brains but
at the at the at the fundamental level
human brain is analog computers that
tosses analog signals rather than
processing bits and zeros and ones in a
binary number scheme and one good
example is that there are elements in
both human brain and super computers
that work like switch which changes has
a huge effect and on their own going
activities of the system by small
changes in the input in the computer
it’s called transistor that does the
work of the switching in the human brain
there are elements called synapses which
is where two different neurons are meet
and then begin to and where the exchange
information exchange occurs and when you
magnify these structures transistor and
synapse synapses you can see that
physically the transistor has a much
simpler structure synapse synapse is
much more complicated and they can
process analog information in a much
more complicated way then then a
computer transistor so and this also can
explain some additional similarities
between human brains and analog
computers because just like any human
brain analog computers can perform
different functions depending upon the
connections that you make between
different parts and similarly in the
human brain the brain is programmed it’s
not by entering some computer codes but
instead altering the connections between
different neurons so that’s another
similarity that makes a lot of sense
when you begin to realize that the human
brain is more like an analog computer
then it is the digital computer so
understanding these differences and also
similarities between human brains and
computers in a ing robots can actually
help us solve some
all ethical challenges that we face
ahead for example when you watch sci-fi
movie where robots act very much like
humans it’s very difficult to withhold
some empathy with these robots and also
allow the animals allow these robots to
have some rights which i think is very
dangerous and I think it could follow
from some of the tendencies that our
brain has as I already explained and
personally I think that the reason why
we feel empathy empathy to the robots
that look like us and behave like us is
not that different from the emotional
response to be my shell when somebody
for example this tries to destroy some
physical objects we value for example if
your musical fan and if you’re attached
to objects like piano and when somebody
smashes them it’s actually very painful
to watch them even though that piano has
no mental activity it has no emotion and
so on and I think those are due to the
similar properties of our human brain
and human mind and one last thing that
I’d like to point out is that getting
complete self-knowledge even using
marvelous scientific tools like the
tools that are currently developed in
neuroscience actually it’s really really
hard to in a way to get complete self
knowledge your self intelligence you’ll
probably have to record from all the
neurons in our brain and then analyze
them and extract all the meaningful
patterns from them which is not only
physically impossible but also has a
logical paradox in it as well which has
been noticed by many philosophers and
mathematicians and logicians in the in
the in the last century which has been
adopted in Masonic scientific movies so
for example in this particular Star Trek
episode Captain Kirk and his crews were
visiting a planet in fact they were
trapped in a planet which was dominated
by super AI Androids and in order to
escape from them the Captain Kirk told
this Android that I’m lying which
includes reference to his self and
therefore when this robot begins to
analyze this truth of the statement it
got overheated and burned itself and
therefore a louder the Captain Kirk
to escape that planet very safely so in
closing I like to actually do a short
experiment I have asked the the camera
crew earlier to aim the camera to the
screen as I was as I’m exiting this
stage which is is a kind of video
feedback which has been noted almost 60
years ago when people started connecting
the video camera to the to the computer
screen to the TV screen and you know way
you can see that as a an analogy to a
simple physical device like the computer
camera and a screen trying to understand
the self and you can see that it’s a
even phone camera which is much simpler
than our human brains this is a very
complicated process so I hope that you
enjoy this video thank you
[Applause] [Music]
[Applause]
[Music]
[Applause]
[Music]
so rain is a marvelous machine you can
do lots of things it is responsible all
the thoughts emotions and complex
decisions that you’re making and
everyone in this room has one and only
one okay so with this Amar’e marvelous
machine we created AI which is getting
more and more powerful every day and now
we’re spending a lot of time thinking
about when AI might exceed us and begins
to threaten us and also we have the
challenge of controlling AI so that it
can benefit human society so the
question arises as to whether we can use
our brain in AI to understand ourselves
because in order to understand the
questions about the relationship between
humans in AI not only we have to
understand how the AI is created what it
can do but we also have to understand
who we are and what we are capable of
doing and my main argument today is that
we know far more about AI then about the
human brain that’s why I chose this
image because if you look at this image
carefully which was painted by my
favorite artist Rene Magritte
you can see that the mirror shows you
active reflection of the book the small
book but it’s not what you would expect
to see for the image of the person
standing in front of the mirror and
symbolically and figuratively I’d like
to argue that AI is like that small book
and we still don’t know exactly who you
are
even if you use the most powerful
scientific engine that we have developed
in our history and to illustrate that I
like to point out several interesting
features of our human brain what we what
the brains do well which might be
somewhat counterintuitive this might be
different from what you always assume
what the brains really do as a first
illustration I want you to focus on the
the the red da on at the center of this
image and try not to move your eyes try
to fixate the red dot and notice the
fact that while you’re doing that
probably all of you can see three other
colored dots in your peripheral vision
yellow green and white dot okay but
you’ll notice that those dots will
disappear from your vision once the moon
begins to rotate and please raise your
hand so that I have a sense as to
whether this is working on now when the
dots seem to disappear thank you so this
is a very famous illusion in psychology
called
emotion induced blindness and it’s been
confusing and baffling to many
psychologists because it’s not that easy
to explain as to why this happens but at
a higher level this is quite expected
because this happens because our brain
is a predictive machine a lot of us
think that the brain gives us a very
accurate and reliable reflect of
representation of the outside world like
the library where you can save
information for countless books and you
can retrieve the information you want
from a particular page or theater where
you can see the movements of all the
actors accurately but that’s not what
the brain is is good at what plan is
trying to do is always try to predict
what’s gonna happen it’s tuned and
constantly looking for things that are
unpredictable that you did not predict
and then try to minimize the errors or
discrepancy between what what you
predicted and what you observe in the
outside world and the reason why these
thoughts disappear after a few seconds
is because those starts are completely
predictable and therefore grant loses
interest quickly and therefore the B&C
raise it from your your mental mental
activity the kind of explanation can
deal with lots of other complex
phenomena zin in the brain for example
if you present any sensory stimulus such
as a flash or sound and then maintain it
for a while and then turn it off the
neurons in the brain do not follow that
pattern precisely instead what they tend
to do is that they show vigorous
response huge response at the onset of
the sensory
stimulus and then quickly reduces their
activity and then when the stimulus is
remove it briefly suppresses activity
the reason why they do that with one
explanation for that is because these
neurons are constantly looking for
surprising unpredictable events so when
the sickness is turned on unpredictable
lead neurons respond vigorously and then
when it’s turned off unexpectedly they
briefly suppress this activity but when
there are no changes in the environment
neurons actually are not that interested
in another example that’s consistent
with this kind of explanation is this
illusion called rotating snakes and if
you fixate any point in this image and
do not move your eyes you can confirm
that this image is completely static
there’s nothing in the screen that’s
moving around but as soon as you begin
to begin to move your eyes around you’ll
notice that a lot of these circles
briefly boot rotate
okay and again this is very confusing
why do we see motions that’s not there
in the physical world an interesting
study that’s been recent that was
recently published that if you build a
deep learning network this is a
cutting-edge AI model of our human
cognition and then train that network to
try to predict what’s gonna be the next
frame in a in a many in many different
movies that you give you used to train
this network thus though those kinds of
deep learning network will also see the
illusory mush motion did you see it with
this with this word rotating snake
illusion again suggesting that the
reason why you see this illusory motion
is because your brain is more interested
in predicting what’s gonna happen in the
next screen rather than analyzing what’s
currently on the screen okay so that’s a
one important feature of our brain that
we may not be aware of all the time that
I agree our brain is a predictive
machine so we might be able to predict
how the difference between the eye and
humans will change but we may not it
might be harder for us to understand
exactly what pre-human brains are and
what the difference between AI and human
human brain is second important feature
the human brain and mind that I’d like
to point out is that we
or you’re very efficient in categorizing
things so when I show you image like
this everyone in this room can
immediately recognize that all apples
and there are green apples and red
apples and of course there are many
other features in this image that you’re
instantaneously ignore such as subtle
changes in the colors and subtle changes
in the color in the in the size of the
apples but we are we can effortlessly
classify and categorize different
objects that we see and this is very
hard for AI to do okay and in fact many
AI algorithms sort of kind of show off
their performance by showing that they
can categorize different images into
cats and dogs and so on but humans are
really really good at does but this
comes at a cost as well because as soon
as you start categorizing things to
discrete value this could domains your
would start to ignore the subtle
differences between them so the question
is why are we so good at categorizing
things and why are also so good at
ignoring reached variations among
different different individual objects
so the reason why we’re so good at
ignoring different features is because
the brain evolved not to accurately
represent the outside world but to
choose the most beneficial action for us
and that requires different kind of
functions our properties so for example
imagine that you’re both tired and
hungry and so you need to sleep and eat
almost at the same time and imagine that
you are like indecisive and you’re
trying to switch between these two
activities constantly you’re going back
and forth between the bed and the
kitchen we will not accomplish either of
these objectives so in order in order to
deal with these kinds of conflicting
situations what the brain has to do is
build a networks that has these kinds of
structures where neurons that are
responsible for selecting sleeping
behavior once they get chosen that they
have to maintain their activity and then
suppress the the activities are
competing neurons that might be
promoting eating so that while you’re
sleeping you don’t get up constantly to
go to the cat
and vice-versa so these two functions
are often referred to as a self
excite-ation that maintains the activity
of neuron of persistently and then
mutual inhibition because you don’t want
the competing actions to interrupt your
ongoing activity in this type of action
selection might be the reason why even
when we’re trying to evaluate different
objects we see in the sensory world we
tend to categorize things right away so
third feature of our mind and brain is
the fact that we’re extremely social and
therefore our brain is also extremely
social and the reason is because social
activity is more important than
individual decision-making in every
their life point in almost every moment
in every moment in our lives and also
this requires very complicated
computations because unlike when you’re
making decisions individually when
you’re acting in a social context what’s
most important is for you to accurately
predict what other people will do
because success and failures of action
really depends upon your ability to
predict whether other people other
people will do but this is this gets
complicated very quickly because we and
you and me both you and I have similar
hardware’s
our brains and have similar objectives
and therefore just like I’m predicting
trying to predict what you’re gonna do
you are also trying to predict what I’m
gonna do and therefore for me to be able
to predict what you’re gonna do
accurately I also need to be able to
predict what you’re gonna predict that
I’m gonna do and this can go on many
many times and creates a very
complicated loop and therefore it
creates a lots of rooms for errors in a
lot of mental disabilities that we have
actually correspond to the failures in
this type of mental simulations and
imagining what other people might be
thinking and so on so that that’s the
cost of having a extremely successful
social social brain that dill deals with
these complicated social situations one
last feature that I’d like to point down
is that our brains are analog computers
and this is important to keep in mind
because we offer in order to understand
the spaz strategies that we have to
adopt when we’re dealing with the AI
rapidly developing a technology is that
we like to understand the relation a
difference between human computer human
brains and and digital computers and
often tend to think that a lot of the
features that digital computers have
might be applicable to human brains but
at the at the at the fundamental level
human brain is analog computers that
tosses analog signals rather than
processing bits and zeros and ones in a
binary number scheme and one good
example is that there are elements in
both human brain and super computers
that work like switch which changes has
a huge effect and on their own going
activities of the system by small
changes in the input in the computer
it’s called transistor that does the
work of the switching in the human brain
there are elements called synapses which
is where two different neurons are meet
and then begin to and where the exchange
information exchange occurs and when you
magnify these structures transistor and
synapse synapses you can see that
physically the transistor has a much
simpler structure synapse synapse is
much more complicated and they can
process analog information in a much
more complicated way then then a
computer transistor so and this also can
explain some additional similarities
between human brains and analog
computers because just like any human
brain analog computers can perform
different functions depending upon the
connections that you make between
different parts and similarly in the
human brain the brain is programmed it’s
not by entering some computer codes but
instead altering the connections between
different neurons so that’s another
similarity that makes a lot of sense
when you begin to realize that the human
brain is more like an analog computer
then it is the digital computer so
understanding these differences and also
similarities between human brains and
computers in a ing robots can actually
help us solve some
all ethical challenges that we face
ahead for example when you watch sci-fi
movie where robots act very much like
humans it’s very difficult to withhold
some empathy with these robots and also
allow the animals allow these robots to
have some rights which i think is very
dangerous and I think it could follow
from some of the tendencies that our
brain has as I already explained and
personally I think that the reason why
we feel empathy empathy to the robots
that look like us and behave like us is
not that different from the emotional
response to be my shell when somebody
for example this tries to destroy some
physical objects we value for example if
your musical fan and if you’re attached
to objects like piano and when somebody
smashes them it’s actually very painful
to watch them even though that piano has
no mental activity it has no emotion and
so on and I think those are due to the
similar properties of our human brain
and human mind and one last thing that
I’d like to point out is that getting
complete self-knowledge even using
marvelous scientific tools like the
tools that are currently developed in
neuroscience actually it’s really really
hard to in a way to get complete self
knowledge your self intelligence you’ll
probably have to record from all the
neurons in our brain and then analyze
them and extract all the meaningful
patterns from them which is not only
physically impossible but also has a
logical paradox in it as well which has
been noticed by many philosophers and
mathematicians and logicians in the in
the in the last century which has been
adopted in Masonic scientific movies so
for example in this particular Star Trek
episode Captain Kirk and his crews were
visiting a planet in fact they were
trapped in a planet which was dominated
by super AI Androids and in order to
escape from them the Captain Kirk told
this Android that I’m lying which
includes reference to his self and
therefore when this robot begins to
analyze this truth of the statement it
got overheated and burned itself and
therefore a louder the Captain Kirk
to escape that planet very safely so in
closing I like to actually do a short
experiment I have asked the the camera
crew earlier to aim the camera to the
screen as I was as I’m exiting this
stage which is is a kind of video
feedback which has been noted almost 60
years ago when people started connecting
the video camera to the to the computer
screen to the TV screen and you know way
you can see that as a an analogy to a
simple physical device like the computer
camera and a screen trying to understand
the self and you can see that it’s a
even phone camera which is much simpler
than our human brains this is a very
complicated process so I hope that you
enjoy this video thank you
[Applause] [Music]
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