Kind: captions
Language: en
the following is a conversation of Chi
Fuli he's the chairman and CEO of sin
evasion ventures that manages a two
billion dollar dual currency investment
fund with a focus on developing the next
generation of Chinese high-tech
companies he's the former president of
Google China and the founder of what is
now called Microsoft Research Asia an
institute that trained many of the
artificial intelligence leaders in China
including CTOs or AI execs at Baidu
Tencent Alibaba innova and Huawei he was
named one of the 100 most influential
people in the world by Time magazine
he's the author of seven best-selling
books in Chinese and most recently the
New York Times bestseller called AI
superpowers China Silicon Valley and the
New World Order
he has unparalleled experience in
working across major tech companies and
governments and applications of AI and
so he has a unique perspective on global
innovation in the future of AI that I
think is important to listen to and
think about this is the artificial
intelligence podcast if you enjoy it
subscribe on YouTube and iTunes
supported enough patreon or simply
connect with me on Twitter at lex
friedman and now here's my conversation
with chi foo lee
I emigrated from Russia to US when I was
you emigrated to us at about the same
age the Russian people the American
people the Chinese people each have a
certain soul a spirit that permeates
throughout the generations so maybe it's
a little bit of a poetic question but
could you describe your sense of what
defines the Chinese soul I think the
Chinese soul of people today right we're
talking about people who have had
centuries of burden because of the
poverty that the country has gone
through and suddenly shined with hope of
prosperity in the past 40 years as China
opened up and embraced market economy
and undoubtedly there are two sets of
pressures on the people that of the
tradition that of facing difficult
situations and that of Hope of wanting
to be the first to become successful and
wealthy so that it's a very strong a
hunger and strong desire and strong work
ethic that drives China forward and is
their roots to not just this generation
but before that's that's deeper than
just the new economic development is
there something that's unique to China
that you could speak to that's in the
people yeah
well the Chinese some tradition is about
excellence dedication and results and
the Chinese exams and study subjects in
schools have traditionally started from
memorizing ten thousand characters not
an easy task
to start with and further by memorizing
his historic philosophers literature
poetry so it really is the probably the
strongest rote learning mechanism
created to make sure people had good
memory and remembered things extremely
well that's I think at the same time
suppresses the breakthrough innovation
and also enhances
the speed execution get results and that
I think characterizes the historic basis
serve on China that's interesting
because there's echoes of that and
Russian education as well as rote
memorization to memorize a lot of poche
I mean there's just the emphasis on
perfection in all forms mmm that's not
conducive to perhaps what you're
speaking to which is creativity but you
and you think that kind of education
holds back the innovative spirit that
you might see in the United States well
it holds back the breakthrough
innovative spirits that we see in the
United States but it does not hold back
the valuable execution oriented
result-oriented value creating engines
which we see China being very successful
so is there a difference between a
Chinese AI engineer today and an
American AI engineer perhaps rooted in
the culture that we just talked about or
the education or the very soul of the
people or no and what would your advice
be to each if there's a difference well
there's a lot that's similar because AI
is about mastering Sciences about using
known technologies and trying new things
but it's also about picking from many
parts of possible networks to use and
different types of parameters to tune
and that part is somewhat rote and it is
also as anyone who's built AI products
can tell you a lot about cleansing the
data because AI runs better with more
data and data is generally unstructured
error error fall and unclean and the
effort to clean the data is is immense
so I think the better part of American
engineering ai engineering process is to
try new things to do things people
haven't done before and to use
technology to solve most if not all
problems so to make the algorithm work
despite not so great data find you know
error tolerant ways to deal with the
data the Chinese way would be
- basically enumerate to the fullest
extent all the possible ways by a lot of
machines try lots of different ways to
get it to work and spend a lot of
resources and money and time cleaning up
data that mean that means the AI
engineer may be writing data cleansing
algorithms working with thousands of
people who label or correct or do things
with the data that is the incredible
hard work that might lead to better
results so the Chinese engineer would
rely on and ask for more and more and
more data and find ways to cleanse them
and make them work in the system and
probably less time thinking about new
algorithms that can overcome they there
are other issues so where's your
intuition what do you think the biggest
impact the next 10 years lies is it in
some breakthrough algorithms or is it in
just this at scale rigor a rigorous
approach to data cleaning data
organizing data onto the same algorithm
packed in the applied world is well if
you're really in the company and you
have to deliver results using known
techniques and enhancing data seems like
the more expedient approach that's very
low risk and likely to generate better
and better results and that's why the
Chinese approach has done quite well now
there are a lot of more challenging
startups and problems such as autonomous
vehicles medical diagnosis that existing
algorithms may probably won't solve and
that would put the Chinese approach more
challenged and give them more
breakthrough innovation approach more
more of an edge on those kinds of
problems so let me talk to that a little
more so you know my intuition personally
is that data can take us extremely far
so you brought up autonomous vehicles
and medical diagnosis so your intuition
is that huge amounts of data might not
be able to completely help us solve that
problem right so breaking that down
further in autonomous vehicle I think
huge amounts of data probably will solve
trucks driving on highways which will
deliver a significant value and China
will probably lead in that and full l5
autonomous is likely to require new
technologies we don't yet know and that
might require academia and great
industrial research both innovating and
working together and in that case us has
an advantage so the interesting question
in there is I don't know if you're
familiar on the autonomous vehicle space
and the developments with Tesla and Elon
Musk I am where they are in fact full
steam ahead into this mysterious complex
world of full autonomy l5 l4 l5 and
they're trying to solve that purely with
data so the same kind of thing that
you're saying is just for highway which
is what a lot of people share your
intuition yeah they're trying to solve
with data it's just a linger on that
moment forever do you think possible for
them to achieve success with simply just
a huge amount of this training on edge
cases on difficult cases in urban
environments not just highway and so on
I think they'll be very hard one could
characterize Tesla's approach as kind of
a Chinese strength approach right gather
all the data you can and hope that will
overcome the problems but in autonomous
driving clearly a lot of the decisions
aren't nearly solved by aggregating data
and having a feedback loop there are
things that are more akin to human
thinking and how would those be
integrated and built there has not yet
been a lot of success integrating human
intelligence or you know call it expert
systems to be well even though that's a
taboo word with the machine learning and
the integration the two types of
thinking hasn't yet been demonstrated
and the question is how much can you
push a purely machine learning approach
and of course Tesla also has an
additional constraint that they don't
have all the sensors
I know that they think is foolish to use
lidar s but that's clearly a one less
very valuable and reliable source of
inputs that they're forgoing which may
also have consequences I think the
advantage of course is capturing data no
one has ever seen before and in some
cases such as computer vision and speech
recognition I have seen Chinese
companies accumulate data that's not
seeing anywhere in the Western world and
they have delivered superior results but
then speech recognition and object
recognition are relatively suitable
problems for deep learning and don't
have the potentially need for the human
intelligence analytical planning
elements in the same on the speech
recognition side your intuition that
speech recognition and the machine
learning approaches to speech
recognition won't take us to a
conversational system that can pass the
Turing test which is sort of maybe akin
to what driving is so it needs to have
something more than just simply simple
language understanding simple language
generation roughly right I would say
that's based on purely machine learning
approaches it's hard to imagine it could
lead to a full conversational experience
across arbitrary domains which is akin
to l5 I'm a little hesitant to use the
word Turing tests because the original
definition was probably too easy we
probably do that yeah the spirit of the
Turing test that's what I was referring
of course so you've had major leadership
research positions at Apple Microsoft
Google so continuing on the discussion
of America Russia Chinese soul and
culture and so on
what is the culture Silicon Valley in
contrast to China and maybe us broadly
and what is the unique culture of each
of these three major companies in your
view I think in aggregates Silicon
Valley companies and we could probably
include Microsoft in that even though
they're not in the valley is really
dream big
and have visionary goals and believe
that technology will conquer all
and also the self confidence and the
self entitlement that whatever they
produce the whole world should use and
must use and those are historically
important I think you know Steve Jobs
famous quote that he doesn't do focus
groups he looks in the mirror and asks
the first in the mirror what do you want
and that really is an inspirational
comment that says the great company
shouldn't just ask users what they want
but develop something that users will
know that they want when they see it but
they could never come up with themselves
I think that is probably the most
exhilarating description of what the
essence of Silicon Valley is that this
brilliant idea could cause you to build
something that couldn't come out of
focus groups or a be tests and iPhone
would be an example of that no one in
the age of blackberry would write down
they want an iPhone or multi-touch a
browser might be another example no one
would say they want that in the days of
FTP but once they see it they want it so
I think that is was Silicon Valley's
best at but it also comes with came with
a lot of success these products became
global platforms and there were
basically no competitors anywhere and
that has also led to belief that these
are the only things that one should do
that companies should not tread on other
companies territory so that's a you know
Groupon and the Yelp and then open table
and the GrubHub with each field ok I'm
not gonna do the other company's
business because that would not be the
pride of innovating whatever each of
these four companies have innovated but
I think the Chinese approach is do
whatever it takes to win and it's a
winner take all market
and in fact in the internet space the
market leader will get predominantly all
the value extracted out of the system so
and the and the and the system isn't
just defined as one narrow category but
gets broader and broader so it's amazing
ambition for success and domination of
increasingly larger product categories
leading to clear market winner status
and the opportunity to extract
tremendous value and that develops a
practical result oriented ultra
ambitious winner-take-all gladiatorial
mentality and if what it takes is to
build what the competitors built
essentially a copycat that can be done
without infringing laws if what it takes
is to satisfy a foreign country's need
by forking the codebase and building
something that looks really ugly and
different they'll do it so it's
contrasted very sharply with the Silicon
Valley approach and I think the
flexibility and the speed and execution
has helped the Chinese approach and I
think the Silicon Valley approach is
potentially challenged if every Chinese
entrepreneurs learning from the whole
world US and China and the American
entrepreneurs only look internally and
right off China as copycat and the
second part of your question about the
three companies the unique elements of
the three companies perhaps yeah I think
Apple represents while the user please
the user and the essence of design and
brand and it's the one company and
perhaps the only tech company that draws
people with a a strong serious desire
for the product and the knee and the
willingness to pay a premium because of
the halo effect of the brand which came
from the
attention to detail and great respect
for user needs microsoft represents a
platform approach that builds giant
products that become very strong modes
that others can't do because it's well
architected at the bottom level and the
work is efficiently delegated to
individuals and then the the the whole
product is build by adding small parts
that sum together so it's probably the
most um effective high tech assembly
line that builds a very difficult
product that and the whole process of
doing that is kind of a differentiation
and something competitors can't easily
repeat are there elements of the Chinese
approach and the way Microsoft went
about assembling those little pieces and
dominating them was essentially
dominating the market for a long time or
do you see this is distinct I think
there are elements that are the same I
think the three American companies that
had or have Chinese characteristics and
obviously as well as American
characteristics are Microsoft Facebook
and Amazon yes that's right Amazon
because these are companies that will
tenaciously go after adjacent markets
build up strong private offering and and
find ways to extract greater value from
a sphere that's ever-increasing and they
understand the value of the platforms so
that's the similarity and then with
Google I think is a genuinely value
oriented company that does have a heart
and soul and that wants to do great
things for the world by connecting
information and that has also very
strong technology genes and
wants to use technology and has found
out-of-the-box ways to use technology to
deliver incredible value to the end-user
we can look at Google for example you
mentioned heart and soul there seems to
be an element where Google is after
making the world better there's a more
positive view I mean I used to have the
slogan don't be evil yeah and and
Facebook a little bit more as a negative
tint to it at least in the perception of
privacy and so on do you have a sense of
how these different companies can
achieve because you've talked about how
much we can make the world better in all
these kinds of ways with AI what is it
about a company that can make give it a
heart and soul gain the trust of the
public and just actually just not be
evil and do good for the world it's
really hard and I think Google has
struggled with that first that don't do
evil mantra is very dangerous because
every employees definition of evil is
different and that has led to some
difficult employee situations for them
so I don't necessarily think that's a
good value statement but just watching
the kinds of things Google or its parent
company alphabet does in new areas like
health care like you know eradicating
mosquitoes things that are really not in
the business of a Internet tech company
I think that shows that there is the
heart and soul and desire to do good and
willingness to put in the resources to
do something when they see it's good
they will pursue it that doesn't
necessarily mean it has all the trust of
the users I realize while most people
would view Facebook as the primary
target of their recent and happiness
about Silicon Valley companies many
would put Google in that category and
some have named Google's business
practices as predatory also so it's kind
of difficult to have the two
parts of a body the brain wants to do
what it's supposed to do for shareholder
maximize profit and then the heart and
soul wants to do good things that may
run against at what that brain wants to
do so in this complex balancing that
these companies have to do you've
mentioned that you're concerned about a
future were too few companies like
Google Facebook Amazon are controlling
our data are controlling too much of our
digital lives can you elaborate on this
concern and perhaps do you have a better
way forward
I think I'm hardly the most vocal a
complainer of this course there are a
lot louder complaints out there I do
observe that's having a lot of data thus
perpetuates their strengths and limit
competition in many spaces but I also
believe a AI is much broader than the
internet space so the entrepreneurial
opportunity still exists in using AI to
empower financial retail manufacturing
education applications so I don't think
it's quite a case of um full
monopolistic dominance that makes that
totally stifles innovation but I do
believe in their areas of strength is
hard to to dislodge them I don't know if
I have a good solution probably the best
solution is let the entrepreneurial VC
ecosystem work well and find all the
places that can create the next Google
the next Facebook so there will always
be increasing number of challengers in
some sense that has happened a little
bit you see uber Airbnb having emerged
despite the strength of the that the big
three and and I think China as an
environment may be more interesting for
the emergence because if you look at
companies between let's say 50 to 300
billion dollars China has emerged more
of such companies than the you
in the in the last three to four years
because of the larger marketplace
because of the more fearless nature of
the entrepreneurs that and and the
Chinese Giants are just as powerful as
American ones Tenzin Alibaba very strong
but by tense has emerged worth 75
billion and financial well it's Alibaba
affiliated it's nevertheless independent
and worth 150 billion and so III do
think if we start to extend to
traditional businesses we will see value
very valuable companies so it's probably
not the case that in five or ten years
we'll still see the whole world with
these five companies having such
dominance so you've mentioned a couple
times this fascinating world of
entrepreneurship in China of the
fearless nature of the entrepreneur so
can you maybe talk a little bit about
what it takes to be an entrepreneur in
China what are the strategies that are
undertaken what are the ways to achieve
success what is the dynamic of vfc
funding of the way the government helps
companies isn't one what are the
interesting aspects here that are
distinct from they're different from the
Silicon Valley world of entrepreneurship
home many of the listeners probably
still would brand Chinese entrepreneur
as copycats and no doubt ten years ago
that would not be an inaccurate
description back ten years ago an
entrepreneur probably could not get
funding if he or she could not describe
what product he or she is copying from
the US the first question is who has
proven this business model which is a
nice way of asking Corey copying and and
that reason is understandable because
China had a much lower internet
penetration and and didn't have enough
indigenous experience to build
innovative products and
secondly the internet was emerging link
startup was the way to do things
building a first minimally viable
products and then expanding was the
right way to go and the American
successes have given the shortcuts that
if you took your if you build your
minimally Viable Product based on an
American product it's guaranteed to be a
decent starting point then you tweak it
afterwards so as long as there's no IP
infringement which as far as no there
hasn't been in the mobile and AI spaces
that's a much better shortcut and I
think Silicon Valley would view that as
still not very honorable because that's
not your own idea to start with but you
can't really at the same time believe
every idea must be your own and believe
in the Lean Startup methodology because
Lean Startup is intended to try many
many things and then converge one that
works and it's meant to be iterating
changed so finding a decent starting
point without legal violations there
should be nothing morally dishonorable
about that so just a quick pause on that
it's fascinating that that's is why is
that not honorable right he's exactly as
you formulated is it seems like a
perfect start for business yeah is to to
take you know look at Amazon and say
okay well we'll do exactly what Amazon
is doing let's start there yeah in this
particular market and then let's I'll
innovate them from that starting point
yes I'm up with new ways I mean is it
wrong to be accept the word copy catchy
sounds bad but is it wrong to be a
copycat it just seems like a smart
strategy but yes doesn't have a heroic
nature to it yeah that like I said like
a Steve Jobs Elon Musk sort of in
something completely coming up with
something completely new yeah I like the
way you describe it it's a non heroic
acceptable way to start the company and
maybe more expedient so that's the
that's I think a baggage for silicon
vally that if it doesn't let go then it
made limits the ultimate ceiling of the
company take snapchat as an example I
think you know Evans brilliance he build
great products but he's very proud that
he wants to build his own features not
copy others while Facebook was more
willing to copy his features and you see
what happens in the competition so I
think putting that handcuff on a company
would limit its ability to reach the
maximum potential so back to the Chinese
environment copying was merely a way to
learn from the American masters just
like we if you would we learned to play
piano or painting you start by copying
you don't start by innovating when you
don't have the basic skill sets so very
amazingly the Chinese entrepreneurs
about six years ago started to branch
off with these lean startups built on
American ideas to build better products
than American products but they did
start from the American idea and today
we we Chad is better than whatsapp Weibo
is better than Twitter and Yahoo is
better than Korra and so on so that I
think is some Chinese entrepreneurs
going to step two and in step three is
once these entrepreneurs have done one
or two of these companies they they now
look at the Chinese market and the
opportunities and come up with ideas
that didn't exist elsewhere so products
like and financial under which includes
Ali pay which is mobile payments and
also the financial products for loans
built on that and also in education VIP
kid and in social video social network
tick-tock and in social ecommerce pin
dodo and then in ride-sharing mo bike
these are all Chinese innovative
products that now are being copied
elsewhere so and and the additional
interesting herbs
raishin is some of these products are
built on unique Chinese demographics
which may not work in the US but may
work very well in Southeast Asia Africa
and other developing worlds that are a
few years behind China and a few of
these products may be armed Universal
and are getting traction even in the
United States such as tick tock so this
whole ecosystem is supported by VCS
as a virtuous cycle because a large
market with with innovative
entrepreneurs will draw a lot of money
and then invest in these companies so as
the market gets larger and larger u.s.
mark china market is easily three four
times larger than the u.s. they will
create greater value and greater returns
for the VCS thereby raising even more
money
so at San ovations ventures our first
fund was fifteen million our last fund
was five hundred million so it reflects
the valuation of the companies and our
us going multistage and things like that
it also has government support but not
in the way most Americans would think of
it the government actually leaves the
entrepreneurial space as a private
enterprise so they're self-regulating
and the government would build
infrastructures that would around it to
make it work better for example the mass
entrepreneur mass innovation plan builds
eight thousand incubators so the
pipeline is very strong to the VCS for
autonomous vehicles the Chinese
government is building smart highways
with sensors smart cities that separate
pedestrians from cars that may allow
initially an inferior autonomous vehicle
company to launch a car without
increasing with lower casualty because
the roads or the city is smart and the
Chinese government at local levels would
have these guiding funds acting as LPS
passive LPS to funds and when the fund
makes money part of the money made is
given back to the GPS and potentially
other LPS to reach increase everybody's
return at the expense of the
government's return so that's
interesting incentive that and trusts
that task of choosing entrepreneurs to
VCS who are better added in the
government by letting some of the
profits I'll move that way so this is
really fascinating right so I look at
the Russian government as a case study
where let me put it this way there is no
such government driven large-scale
support of entrepreneurship and probably
the same is true in the United States
but the entrepreneurs themselves kind of
find a way yeah so maybe in a form of
advice or explanation how did the
Chinese government arrive to be this way
so supportive entrepreneurship to be in
this particular way so forward-thinking
at such a large scale and also perhaps
how can we copy it in other countries
yeah that how can we encourage other
governments given the United States
government to support infrastructure for
autonomous vehicles in that same kind of
way perhaps yes so these some techniques
are the result of several key things
some of which may be learn the both some
of which may be very hard one is just
trial and error and watching what
everyone else is doing I think it's
important to be humble and not feel like
you know all the answers the guiding
funds idea came from Singapore which
came from Israel and China made a few
tweaks and turned it into a because the
Chinese cities and government officials
kind of compete with each other because
they all want to make their city more
successful so they can get the next
level in their crew in their political
career and it's somewhat competitive so
the central government made it a bit of
a competition everybody has a budget
they can put it on AI or they can put it
on bio or they can put it on energy and
then whoever gets the results the city
shines the people are better off the
mayor gets a promotion
so the tools
kind of almost like an entrepreneurial
environment for local governments to see
who can do a better job and also many of
them try different experiments some have
given award to very smart
researchers just give them money and
hope they'll start the company some have
given money to academic research labs
maybe government research labs to see if
they can spin-off some companies from
the science lab or something like that
some have tried to recruit overseas
Chinese to come back and start companies
and they've had mixed results the one
that worked the best was the guiding
funds so it's almost like a Lean Startup
idea where people try different things
and what works sticks and everybody
copies so now every city has a guiding
fund so that's how that came about
the autonomous vehicle and the massive
spending in highways in smart cities
that's a Chinese way it's about building
infrastructure to facilitate it's a
clear division of the government's
responsibility from the market the
markets should do everything in a
private freeway but there are things the
market can't afford to do like
infrastructure so the government always
appropriate large amounts of money for
infrastructure building this happened
happens with not only autonomous vehicle
in the eye
but happened with the 3G and 4G you'll
find that the Chinese a wireless
reception is better than the u.s.
because massive spending that tries to
cover the whole country whereas in the
US it may be a little spotty it's a
government driven because I think they
view the coverage of of cell access and
3G 4G access to be a governmental
infrastructure spending as opposed to as
opposed to capitalistic so that's of
course the state-owned enterprises also
public
traded but they also carry a government
responsibility to deliver infrastructure
to all so it's a different way of
thinking that may be very hard to inject
into Western countries to say starting
tomorrow
bandwidth infrastructure and highways
are going to be governmental spending
with some characteristics what's your
sense and sorry to interrupt but because
it's such a fascinating point do you
think on the autonomous vehicle space
it's possible to solve the problem of
full autonomy without significant
investment in infrastructure well that's
really hard to speculate I think it's
not a yes/no question but how long does
it take question you know 15 years 30
years 45 years clearly with
infrastructure augmentation where
there's ro the city or whole city
planning building a new city I'm sure
that will accelerate the day of the l5 I
I'm not knowledgeable enough and it's
hard to predict even one we're
knowledgeable because a lot of it is
speculative but in the US I don't think
people would consider building a new
city the size of Chicago to make it a I
slash autonomous city they're smaller
ones being built I'm aware of that
but is infrastructure spent really
impossible for us or Western countries I
don't think so the u.s. highway system
was built was that during President
Eisenhower or Kennedy as Eisenhower yeah
so so so maybe historians can study how
the President Eisenhower get the
resources to build this massive
infrastructure that surely gave us
tremendous amount of prosperity over the
next decade if not century if I may
comment on that then it takes us to
artificial intelligence a little bit
because in order to build infrastructure
it it creates a lot of jobs so I'll be
actually interested if you would say
that you talk in your book about all
kinds of jobs that could
could not be automated I wonder if
building infrastructures one of the jobs
that would not be easily automated
something you could think about because
they think you mentioned somewhere in
the talk or that there there might be as
jobs are being automated a role for
government to create jobs that can't be
automated yes I think that's a
possibility
back in the last financial crisis China
puts a lot of money to basically give
this economy a boost and a lot of it a
lot of the one into infrastructure
building and and I think that's a
legitimate way and the government level
to to deal with the employment issues as
well as build out the infrastructure as
long as the infrastructures are truly
needed and as long as there isn't an
employment problem which no we don't
know so maybe taking a little step back
if you've been a leader and a researcher
in AI for several decades at least 30
years so how is AI changed in the west
and the east as you've observed as
you've been deep in it over the past 30
years
well a I began as the pursuits of
understanding human intelligence and the
term itself represents that but it kind
of drifted into the one sub area that
worked extremely well which is machine
intelligence and that's actually more
using pattern recognition techniques to
basically do incredibly well on the
limited or domain large amount of data
but relatively simple kinds of farm
planning tasks and not very creative so
so we didn't end up building human
intelligence
we built a different machine that was a
lot better than us some problems but
nowhere close to us other problems so
today I think a lot of people still
misunderstand when we say artificial
intelligence and what various products
can do
people still think it's about
replicating human intelligence but the
products out there really are closer to
having invented the internet or the
spreadsheet or the database and getting
broader adoption and peeking further to
the fears near-term fears that people
have about AI
so you're commenting on the sort of the
general intelligence that people in the
popular culture from sci-fi movies have
a sense about AI but there's practical
fears about AI the kind the narrow AI
that you're talking about of automating
particular kinds of jobs and you talk
about them in the book so what are the
kinds of jobs in your view that you see
in the next 5-10 years beginning to be
automated by AI systems algorithms yes
this is a also maybe a little bit
counterintuitive because it's the
routine jobs that will be displaced the
soonest and they may not be displaced
entirely maybe 50% 80% of a job but when
the workload drops by that much
employment will come down and also
another part of misunderstanding as most
people think of AI replacing routine
jobs then they think of the assembly
line the workers well that will have
some effect but it's actually the
routine white-collar workers that's
easier to replace because to replace the
white-collar worker you just need
software to replace a blue-collar worker
you need robotics mechanical excellence
and the ability to deal with dexterity
and maybe even unknown environments very
very difficult so if we were to
categorize the most dangerous
white-collar jobs there would be things
like back-office
people who copy and paste and deal with
simple computer programs and data and
maybe paper and OCR and they don't make
strategic decisions they basically
facilitate the process the software and
papers
don't work so you have people dealing
with new employee orientation searching
for past lawsuits and financial
documents and doing reference check for
basic searching and management of data
data that's the most in danger of being
lost in addition to the white-collar
repetitive work a lot of simple
interaction work can also be taken care
of such as telesales telemarketing
customer service as well as many
physical jobs that are in the same
location and don't require a high degree
of dexterity so fruit picking
dishwashing assembly line inspection our
jobs in that category so all together
back office is a big part and the other
the the the blue-collar may be smaller
initially but over time they I will get
better and when we start to get to over
the next 15 20 years the ability to
actually have the dexterity of doing
assembly line that's a huge chunk of
jobs and and when autonomous vehicles
start to work initially starting with
truck drivers but eventually to all
drivers that's another huge group of
workers so I see modest numbers in the
next five years but increasing rapidly
after that I'm worried of the jobs that
are in danger and the gradual loss of
jobs I'm not sure if you're familiar
with Andrew yang yes I am so there's a
candidate for president of the United
States whose platform Andrew yang is
based around in part around job loss due
to automation and also in addition the
need perhaps of universal basic income
to support jobs that are folks who lose
their job due to automation and so on
and in general support people under
complex unstable job market so what are
your thoughts about his concerns him as
a candidate his ideas in general I think
his thinking is generally in the right
direction
[Music]
but his approach as a presidential
candidate maybe a little bit head at a
time
I think the displacements will happen
but will they happen soon enough for
people to agree to vote for him
the unemployment numbers are not very
high yet and I think you know he and I
have the same challenge if I want to
theoretically convince people this is an
issue and he wants to become the
president people have to see how can
this be the case when an employment
numbers are low so that is the challenge
and I think I think we do I do agree
with him on the displacement issue on
universal basic income at a very vanilla
level I don't agree with it because I
think the main issue is retraining so
people need to be incented not by just
giving a monthly $2,000 check or $1,000
check and do whatever they want because
they don't have to know how to know what
to retrain to go into what type of a job
and guidance is needed and Retraining is
needed because historically when
technology revolutions when routine jobs
were displaced new routine jobs came up
so they there was always room for that
but with a eye on automation
the whole point is replacing all routine
jobs eventually so there will be fewer
and fewer routine jobs and an AI will
create jobs but it won't create routine
jobs because if it creates routine jobs
why wouldn't a I just do it so therefore
the people who are losing the jobs
aren't losing routine jobs the jobs that
are becoming available are non routine
jobs
so the social stipend needs to be put in
place is for the routine workers who
lost their jobs to be retrained maybe in
six months maybe in three years takes a
while to retrain on a non routine job
and then take out a job that will last
for that person's lifetime now having
said that if you look deeply into
Andrews document he does cater for that
so I'm not disagreeing with what he's
trying to do but for simplification
sometimes he just says ubi but simple
ubi wouldn't work and I think you've
mentioned elsewhere that I mean the goal
isn't necessarily to give people enough
money to survive or live or even to
prosper the point is to give them a job
that gives a meaning that meaning is
extremely important that our employment
at least in the United States and
perhaps it cares across the world
provides something that's forgive me for
saying greater than money it provides
meaning so now what kind of jobs do you
think can't be automated you talk a
little bit about creativity and
compassion in your book what aspects do
you think it's difficult to automate for
an AI system because an AI system is
currently merely optimizing it's not
able to reason plan or think creatively
or strategically it's not able to deal
with complex problems it can't come up
with a new problem and solve it a human
needs to find the problem and pose it as
an optimization problem then have the AI
work habits so in AI would have a very
hard time discovering a new drug or
discovering a new style of painting or
dealing with complex tasks that such as
managing a company that isn't just about
optimizing the bottom line but also
about employee satisfaction corporate
brand and many many other things so that
is one category of things and because
these things are challenging creative
complex doing them creates a higher high
degree of satisfaction and therefore
appealing to our desire for working
which isn't just to make the money make
the ends meet but also that we've
accomplished something that others maybe
can't do or can do as well
another type of job that is much
numerous would be compassionate jobs
jobs that require calm
empathy human touch human trusts hey I
can't do that because AI is cold
calculating and even if it can fake that
to some extent it will make errors and
that will make it look very silly and
also I think even if they added okay
people would want to interact with the
people another person whether it's for
some kind of a service or a teacher or a
doctor or concierge or a masseuse or a
bartender there are so many jobs where
people just don't want to interact with
a cold robot or software I've had an
entrepreneur who built an elderly care
robot and they found that the elderly
really only used it for customer service
and huh
but not to service the product but they
click on the customer service and the
video of a person comes up and then the
person says how come my daughter didn't
call me let me show you the grandkids so
people learn for that people people
interaction so even the robots improved
people just don't want it and those jobs
are going to be increasing because AI
will create a lot of value 16 trillion
dollars to the world in next 11 years
according to PwC and that will give
people money to enjoy services whether
it's eating a gourmet meal or tourism
and traveling or having concierge
services the the service is revolving
around you know every dollar of that 16
trillion dollars will be tremendous it
will create more opportunities that are
to service the people who did well
through AI with with with things but
even at the same time the entire society
is very much short in need of many
service oriented compassionate oriented
jobs the best example is probably in
healthcare services there's going to be
2 million new jobs
not coming replacement just in brand-new
incremental jobs in the next six years
in health care services that includes
nurses orderly in the hospital
elderly care and and also at home care
it's particularly lacking and those jobs
are not likely to be filled so there's
likely to be a shortage and the reason
they're not filled is simply because
they don't pay very well and that the
social status of these jobs are not very
good so they pay about half as much as a
heavy equipment operator which will be
replaced a lot sooner and they pay
probably comparably to someone on the
assembly line and if so if we ignoring
all the other issues and just think
about satisfaction from one's job
someone repetitively doing the same
manual action and assembly line that
can't create a lot of job satisfaction
but someone taking care of a sick person
and and getting a hug and thank you from
that person in the and the family I
think is is quite satisfying
so if only we could fix the pay for
service jobs there are plenty of jobs
that require some training or a lot of
training for the people coming off the
routine jobs to take we can easily
imagine someone who was maybe a cashier
at the grocery store s stores become
automated learned to become a nurse or a
at home care also to one the point now
the blue-collar jobs are going to stay
around a bit longer some of them quite a
bit longer
you know a I cannot be told
go clean an arbitrary home that's
incredibly hard arguably is an l5 level
of difficulty right and then AI cannot
be a good plumber
because plumber is almost like a mini
detective that has to figure out where
the leak came from so yet AI probably
can be an assembly line and auto
mechanic and so on so one has to study
which blue-collar jobs are going away
and facilitate retraining for the people
to go into the ones that won't go away
or maybe even will increase I mean it is
fascinating that it's easier to build
a world champion chess player than it is
to build a mediocre plumber yes right
very true iji and that goes
counterintuitive to a lot of people's
understanding of what artificial
intelligence is so it sounds I mean
you're painting a pretty optimistic
picture about retraining about the
number of jobs and actually the
meaningful nature of those jobs once we
automate repetitive tasks so overall are
you optimistic about the future where
much of the repetitive tasks are
automated that there is a lot of room
for humans for the compassionate for the
creative input that only humans can
provide I am optimistic if we start to
take action if we have no action in the
next five years I think it's going to be
hard to deal with the devastating losses
that will emerge so if we start thinking
about retraining maybe with the
low-hanging fruits explaining to
vocational schools why they should train
more plumbers that other mechanics may
be starting with some government subsidy
for corporations to have more training
positions we start to explain to people
why retraining is important we start to
think about what the future of education
how that needs to be tweaked for the era
of AI if we start to make incremental
progress and the greater number of
people understand then there's no reason
to think we can't deal with this because
this technological revolution is
arguably similar to what electricity
industrial revolutions and internet
brought about do you think there's a
role for policy for governments to step
in to help with policy to create a
better world absolutely and I and the
government's don't have to believe an
employment will go up and they don't
have to believe automation will be this
fast to do something revamping
vocational school would be one example
another is if there is a big gap in
health care service employment and we
know that a country's population is is
growing Oh
more longevity living older because
people over 80 require five times as
much care as those under 80 then it is a
good time to incent
training programs for elderly care to
find ways to improve the pay maybe one
way would be to offer as part of
Medicare or the equivalent program for
people over 80 to be entitled to a few
hours of elderly here at home and then
that might be reimbursable and that will
stimulate the service industry around
the policy do you have concerns about
large entities whether it's governments
or companies controlling the future of
AI development in general so we talked
about companies do you have a better
sense that governments can better
represent the interest of the people
then companies or do you believe
companies are better representing the
interests of the people or is there no
easy answer I don't think there's an
easy answer because there's a
double-edged sword
the companies and governments can
provide better services with more access
to data and more access to AI but that
also leads to greater power which can
lead to uncontrollable problems whether
it's monopolies or corruption in the
government so I think one has to be
careful to look at how much data that
companies and governments have and and
some kind of checks and balances would
be helpful so again I come from Russia
there's something called the Cold War so
let me ask a difficult question here
looking at conflict the Steven Pinker
written a great book that conflict all
over the world is decreasing in general
but do you have a sense that having
written the book AI superpowers do you
see a major international conflict
potentially arising between major
nations whatever they are with its
roster China European nations United
States or others
in the next 10 20 50 years around AI
around the digital space cyberspace do
you worry about that that is there
something is that something we need to
think about and try to alleviate or
prevent I believe in greater engagement
a lot of the worries about more powerful
AI are based on a arms race metaphor and
the when you extrapolate into military
kinds of scenarios AI can automate and
and and you know animus weapons that
needs to be controlled somehow and
autonomous decision-making can lead to
not enough time to fix international
crises so I actually believe a Cold War
mentality would be very dangerous
because should two countries rely on AI
to make certain decisions and they don't
in talk to each other they do their own
scenario planning then something could
easily go wrong
I think engagement interaction some
protocols to avoid inadvertent disasters
is actually needed so it's natural for
each country to want to be the best
whether it's in nuclear technologies or
AI or bio but I think is important to
realize if each country has a black box
AI and that don't talk to each other
that probably presents greater
challenges to humanity then if they
interacted I think there can still be
competition but with some degree of
protocol for interaction just like when
there was a nuclear competition there
were some protocol for deterrence among
US Russia and China and I think that
engagement is needed so of course we're
still far from AI presenting that kind
of danger but what I worry the most
about
is the level of engagement seems to be
coming down the level of distrust seems
to be going up especially from the US
towards other large countries such as
China and of course Russia and Russia
yes is there a way to make that better
so that's beautifully put level
engagement and even just basic trust and
communication as opposed to sort of you
know making artificial enemies out of
particular particular countries did you
ever you have a sense how we can make it
better
mentionable items that as a society we
can take on I'm not an expert at
geopolitics but I would say that we look
pretty foolish as humankind when we are
faced with the opportunity to create
sixteen trillion dollars for for
Humanity and we we're in yet we're not
solving fundamental problems with parts
of the world still in poverty and for
the first time we have the resources to
overcome poverty and hunger we're not
using it on that but we're fueling
competition among superpowers and that's
a very unfortunate thing if we become
utopian for a moment imagine a a
benevolent world government that has
this 16 trillion dollars and maybe some
AI to figure out how to use it to deal
with diseases and problems and hate and
things like that world would be a lot
better off so what is wrong with the
current world I think the people with
more skill than then I should just think
about this and then at your politics
issu