Kind: captions
Language: en
the following is a conversation with
Kevin Scott the CTO of Microsoft before
that he was the senior vice president of
engineering and operations at LinkedIn
and before that he oversaw mobile ads
engineering at Google he also has a
podcast called behind the tech with
Kevin Scott which I'm a fan of this was
a fun and wide-ranging conversation that
covered many aspects of computing it
happened over a month ago before the
announcement that Microsoft's investment
open the eye that a few people have
asked me about I'm sure there'll be one
or two people in the future they'll talk
with me about the impact of that
investment this is the artificial
intelligence podcast if you enjoy it
subscribe on YouTube give it five stars
in iTunes
supported on a patreon or simply connect
with me on Twitter at lex friedman
spelled fri d-m am and I'd like to give
a special thank you to Tom and a lot the
big housing for their support of the
podcast on patreon thanks Tom and alon
the-- hope I didn't mess up your last
name too bad your support means a lot
and inspires me to keep the series going
and now here's my conversation with
Kevin Scott you described yourself as a
kid in a candy store at Microsoft
because of all the interesting projects
that are going on can you uh try to do
the impossible task and give a brief
whirlwind view of all the spaces that
Microsoft is working in it was the
research and product if you include
research it becomes even even more
difficult so so like I think broadly
speaking Microsoft's product portfolio
includes everything from a big cloud
business like a big set of SAS services
we have you know sort of the original or
like some of what are among the original
productivity software products that
everybody uses we have an operating
system business we have a hardware
this where we make everything from
computer mice and headphones high-end
high-end personal computers and laptops
we have a fairly broad ranging research
group where like we have people doing
everything from economics research so
like this is really a really smart young
economist Glenn Weil who like my group
works with a lot who's doing this
research on these things called radical
markets like he's written an entire
entire technical book about about this
whole notion of a radical market so like
the research group sort of spans from
that human-computer interaction to
artificial intelligence and we have a we
have github we have LinkedIn we have a
search advertising and news business and
and like probably a bunch of stuff that
I'm embarrassingly not recounting and in
this gaming to Xbox and so on yeah
gaming for sure like I was I was having
a super fun conversation this morning
with with Phil Spencer so when I was in
college there was this game that Lucas
arts made called day of the tentacle
that my friends and I played forever and
like we're you know doing some interest
in collaboration now with the folks who
made day of the tentacle and I was like
completely nerding out with Tim Schafer
like the guy who wrote a day of the
tentacle this morning just a complete
fanboy which you know sort of it like
happens a lot like you know Microsoft
has been doing so much stuff it's such
breadth for such a long period of time
that you know like being CTO like most
of the time my job is very very serious
and sometimes like I get to I get caught
up and like how amazing it is to be able
to have the conversations that I have
with the people I get to have them with
you had to reach back into the
sentimental and what's the the wreck of
radical markets and they and they had
economics so there the idea with radical
markets is like can you come
up with new market-based mechanisms -
you know I think we have this we're
having this debate right now like does
capitalism work like free markets work
can the incentive structures that are
built into these systems produce
outcomes that are creating sort of
equitably distributed benefits for every
member of society you know and I think
it's a reasonable reasonable set of
questions to be asking and so what Glenn
and so like you know one motor thought
they're like if you have doubts that the
that the markets are actually working
you can sort of like tip towards like
okay let's let's become more socialist
and you know like have central planning
and you know governments or some other
central organization it's like making a
bunch of decisions about how you know
sort of work gets done and you know like
where the you know where the investments
and where the outputs of those
investments get distributed Glenn's
notion is like lean more into like the
market-based mechanism so like for
instance you know this is one of the
more radical ideas like suppose that you
had a radical pricing mechanism for
assets like real estate where you were
you could be bid out of your position
and in in your home you know for
instance so like if somebody came along
and said you know like I've I can find
higher economic utility for this piece
of real estate that you're running your
your business and like then like you
either have to you know sort of bid to
sort of stay or like the thing that's
got the higher economic utility you know
sort of takes over the asset and which
would make it very difficult to have the
same sort of rent seeking behaviors that
you've got right now because like if you
did speculative bidding like you would
you very quickly like lose a whole lot
of money and so like the prices of the
assets would be sort of like very
closely index to like the value that
they can produce and like because like
you'd have this sort of real-time
mechanism that would force you to sort
of mark the value of the asset to the
market then it could be taxed
appropriately like you couldn't sort of
sit on this thing and say oh like this
house is only worth ten thousand bucks
when like everything around it is worth
ten million
let's finish so it's an incentive
structure that where the prices matched
the value much better yeah
so the Anglin does a much much better
job than I do at selling and I probably
picked the world's worst example you
know and and in but like in its it's
intentionally provocative you know so
like this whole notion like I you know
like I I'm not sure whether I like this
notion that like we could have a set of
market mechanisms where I could get bit
out of faith that was my property you
know but but you know like if you're
thinking about something like Elizabeth
Warren's wealth tax for instance like
you would have I mean you'd be really
interesting in like how you would
actually set the the price on the assets
and like you might have to have a
mechanism like that if you put a tax
like that in place it's really
interesting that that kind of research
at least tangentially is touching
Microsoft Research yeah
the years really thinking broadly that
maybe you can speak to this connects to
AI so we have a candidate Andrew yang
who kind of talks about artificial
intelligence and the concern that people
have about art you know automations
impact on society and arguably Microsoft
is at the cutting edge of innovation in
all these kinds of ways and so it's
pushing AI forward how do you think
about combining all our conversations
together here with radical markets and
socialism and innovation in a item that
Microsoft is doing and then Andrew
Yang's worried that that that will that
will result in job loss for the low and
so on how do you think about that I
think it's sort of one of the most
important
shins and Technology like maybe even in
society right now about how is AI going
to develop over the course of the next
several decades and like what's it going
to be used for and like what what
benefits will it produce and what
negative impacts will it produce and you
know how who gets to steer this whole
thing you know I'll say it at the
highest level one of the real joys of
getting to do what I do at Microsoft is
Microsoft has this heritage as a
platform company and so you know like
Bill Bill's has this thing that he said
a you know a bunch of years ago where
you know the the measure of a successful
platform is that it produces far more
economic value for the people who build
on top of the platform than is creative
for the the platform owner or builder
and I think we have to think about AI
that way like satellite form yeah it has
to like it has to be a platform that
other people can use to build businesses
to fulfill their creative objectives to
be entrepreneurs to solve problems that
they have in their work and in their
lives it can't be a thing where there
are a handful of companies sitting in a
very small handful of city cities
geographically who are making all the
decisions about what goes into the AIA
and and and like and then on top of like
all this infrastructure then build all
of the commercially valuable uses for it
so like I think like that's bad from a
you know sort of you know economics and
sort of equitable distribution of value
perspective like you know sort of back
to this whole notion of you know like do
the markets work but I think it's also
bad from an innovation perspective
because like I have infinite amounts of
faith in human beings that if you you
know give folks powerful tools they will
go do interesting things and it's more
than just a few tens of thousands of
people with the interesting tools it
should be millions of
people with the tools so sort of like
you know you think about the the steam
engine and the late 18th century like it
was you know maybe the first large-scale
substitute for human labor that we've
built like a machine and you know in the
beginning when these things are getting
deployed the folks who got most of the
value from the steam engines were the
folks who had capital so they could
afford to build them and like they built
factories around them in businesses and
the experts who knew how to build and
maintain them but access to that
technology democratized over time like
now like like an engine is not a it's
not like a differentiated thing like
there isn't one engine company that
builds all the engines and all of the
things that use engines are made by this
company and like they get all the
economics from all of that like never
like fully democratize like they're
probably you know we're sitting here in
this room and like even though they
don't that they're probably things you
know like the the MEMS gyroscope that
are in both of our float like there's
like little engines you know sort of
everywhere they they're just a component
and how we build the modern world like
AI DS to get there yeah so that's a
really powerful way to think if we think
of AI is a platform versus a tool that
Microsoft owns as a platform that
enables creation yeah on top of it
that's a way to democratize it that's
really absolutely interesting actually
and Microsoft in its history has been
positioned well to do that and the you
know the tie back to the to this radical
markets thing like the so my team has
been working with Glenn on this and
Jaron Lanier actually did just so Jaron
is the like the sort of father of
virtual reality like he's one of the
most interesting human beings on the
planet like a sweet sweet guy and so
Jaron and Glen and folks in my team have
been working on this notion of data as
labor or like they call it data dignity
as well and so the the idea is that if
you you know again going back to this
you know sort of industrial analogy if
you think about data is the raw material
that is consumed by the machine of AI in
order to do useful things then like
we're not doing a really great job right
now and having transparent marketplaces
for valuing those data contributions so
like and we all make them like
explicitly like you go to LinkedIn you
sort of set up your profile on LinkedIn
like that's an explicit contribution
like you know exactly the information
that you're putting into the system and
like you put it there because you have
some nominal notion of like what value
you're gonna get in return but it's like
only nominal like you don't know exactly
what value you're getting in return like
service is free you know like it's low
amount of like procedure and then you've
got all this indirect contribution that
you're making just by virtue of
interacting with all of the technology
that's in your daily life and so like
what Glen and Jaron and and this data
Dignity team are trying to do is like
can we figure out a set of mechanisms
that let us value those data
contributions so that you could create
an economy and like a set of controls
and incentives that would allow people
to like maybe even in the limit like
earn part of their living through the
data that they're creating and like you
can sort of see it in explicit ways
they're these companies like scale AI
and like they're a whole bunch of them
in in China right now that are basically
data labeling companies so like you
you're doing supervised machine learning
you need you need lots and lots of label
training data and like those people are
getting competent like who worked for
those companies are getting compensated
for their data contributions into the
system and so that's easier to put a
number on their contribution because
they're explicitly labeling they're
correct but you're saying that we're all
contributing data in all kinds of ways
and it's fascinating to start to
explicitly try to put a number on it do
you think that's you that's possible I
don't know it's hard it really is
because you know we don't have as much
transparency as
is I think we need in like how the data
is getting used and it's you know super
complicated like you know we we you know
I think it's technologists sort of
appreciate like some of the subtlety
there it's like you know the data the
data gets created and then it gets you
know it's not valuable like the the data
exhaust that you give off or the you
know the explicit data that I am putting
into the system isn't value valuable
it's super valuable atomically like it's
only valuable when you sort of aggregate
it together and you know sort of large
numbers it's true even for these like
folks who are getting compensated for
like labeling things like for supervised
machine learning now like you need lots
of labels to train a you know a model
that performs well and so you know I
think that's one of the challenges it's
like how do you you know how do you sort
of figure out like because this data is
getting combined in so many ways like
through these combinations like how the
value is flowing yeah that's that's
that's tough yeah and it's fascinating
that you're thinking about this and I
wish I wasn't even going to this
conversation expecting the breadth of
research really that Microsoft broadly
is thinking about you are thinking about
it Microsoft so if we go back to 89 when
Microsoft released office or 1990 when
they at least windows 3.0 house.the in
your view I know you weren't there the
entire you know there was history but
how is the company changed in the 30
years since as you look at it now the
good thing is it's started off as a
platform company like it's still a
platform company like the parts of the
business that are like thriving and most
successful or those that are building
platforms like the mission of the
company now is the missions change it's
like changing a very interesting way so
you know back in 89 90 like they were
still on the original mission which was
like put a PC on every desk and in every
home like in it was
basically about democratizing access to
this new personal computing technology
which when Bill started the company
integrated circuit micro processors were
a brand-new thing and like people were
building you know homebrew computers you
know from kits like the way people build
ham radios right now yeah and I think
this is sort of the interesting thing
for folks who build platforms in general
Bill saw the opportunity there and what
personal computers could do and it was
like it was sort of a reach like you
just sort of imagined like where things
were you know when they started the
company versus where things are now like
in success when you've democratized a
platform it just sort of vanishes into
the platform you don't pay attention to
it anymore like operating systems aren't
a thing anymore like they're super
important like completely critical and
like you know when you see one you know
fail like you you just you sort of
understand but like you know it's not a
thing where you're you're not like
waiting for you know the next operating
system thing in the same way that you
were in 1995 right that's like in 1995
like you know we have Rolling Stones on
the stage with the windows 95 rollout
like it was like the biggest thing in
the world everybody was lined up for it
the way that people used to line up for
iPhone but like you know eventually and
like this isn't necessarily a bad thing
like it just sort of you know it the
success is that it's sort of it becomes
ubiquitous it's like everywhere and like
human beings when their technology
becomes ubiquitous they just sort of
start taking it for granted so the
mission now that Satya Ari articulated
five plus years ago now when he took
over as CEO of the company
a mission is to empower every individual
and every organization in the world to
be more successful and so you know again
like that's a platform mission and like
the way that we do it now is is
different it's like we have a hyper
scale cloud that cloud or building our
applications on top of like we have a
bunch of AI infrastructure that people
are building their AI applications on
top of we have you know we have a
productivity suite of software like
Microsoft Dynamics which you know some
people might not think is the sexiest
thing in the world but it's like helping
people figure out how to automate all of
their business processes and workflows
and you know like help those businesses
using it to like grow and be more so so
it's it's a much broader vision in a way
now than it was back then like it was
sort of very particular thing and like
now like we live in this world where
technology is so powerful and it's like
such a basic fact of life that it you
know that it it both exist and is going
to get better and better over time or at
least more and more powerful over time
so like you know what you have to do is
a platform player is just much bigger
right there's so many directions in
which you can transform you didn't
mention mixed reality yeah you know
that's yep that's that's probably early
days or depends how you think of it but
if we think on a scale of centuries just
the early days of mixed reality
oh for sure and so yeah with hololens
the Microsoft is doing some really
interesting work there do you touch that
part of the effort what's the thinking
do you think of mixed reality as a
platform to know sure when we look at
what the platform's of the future could
be so like fairly obvious that like AI
is one like you don't have to I mean
like that's you know you sort of say it
like someone and you know like they get
it but like we also think of the like
mixed reality and quantum is like these
two interesting you know potential
computing yeah okay so let's get crazy
then so so you're talking about some
futuristic things here
well the mixed reality Microsoft is
really it's not even feature a stick is
here it is incredible stuff and it in
look and it's heaven and it's having
impact right now like one of the one of
the more interesting things this
happened with NYX reality over the past
couple of years that I didn't clearly
see is that it's become the computing
device for for folks who for doing their
work who haven't used any computing
device at all to do their work before so
technicians and service folks and people
who are doing like machine maintenance
some factory floors so like they you
know but because they're mobile and like
they're out in the world and they're
working with their hands and you know
sort of servicing these like very
complicated things they're they don't
use their mobile phone and like they
don't carry a laptop with them and you
know they're not tethered to a desk and
so mixed reality like where it's getting
traction right now where hololens is
selling a lot of a lot of units is for
these sorts of applications for these
workers and it's become like I mean like
the people love it they're like oh my
god like this is like for them like the
same sort of productivity boost that you
know like an office worker had when they
got their first personal computer yeah
but you did mention it's really obvious
AI as a platform but can we dig into it
a little bit red how does a I begin to
infuse some of the products in Microsoft
so currently providing training of for
example neural networks in the cloud
yeah we're providing put pre train
models or just even providing computing
resources whatever different inference
that you want to do using you on that
works yep well how do you think of AI
infusing the as a platform that
Microsoft can provide yeah I mean I
think it's it's super Android it's like
everywhere and like we we run these we
run these review meetings
now where it's be and satya and like
members of sathyas leadership team and
like a cross-functional group of folks
across the entire company who are
working on like either AI infrastructure
or like have some substantial part of
their of their product work using AI in
some significant way now the important
thing to understand is like when you
think about like how the AI is gonna
manifest in like an experience for
something that's gonna make it better
like I think you don't want the a
eyeness to be the first-order thing it's
like whatever the product is and like
the thing that is trying to help you do
like the AI just sort of makes it better
and it you know this is a gross
exaggeration but like i yet people get
super excited about like where the AI is
showing up in products and i'm like do
you get that excited about like where
you using a hash table that code like
it's just another just the tool it's a
very interesting programming tool but
it's sort of a like it's an engineering
tool and so like it shows up everywhere
so like we've got dozens and dozens of
features now in office that are powered
by like fairly sophisticated machine
learning our search engine wouldn't work
at all if you took the machine learning
out of it the like increasingly you know
things like content moderation on our
Xbox and X cloud platform you know when
you mean moderation to be like the
recommenced it's like showing what you
want to look at next no no it's like
anti-bullying so that's that so you use
your social network stuff they yeah deal
with yeah correct but it's like really
it's targeted it's targeted towards a
gaming audience so it's like a very
particular type of thing where you know
the the line between playful banter and
like legitimate bullying is like a
subtle one and like you have to like
it's sort of tough like I have
I'd love to if we could dig into it
because you're also you let the
engineering efforts to LinkedIn yep and
if we look at if we look at LinkedIn as
a social network yeah and if we look at
the Xbox gaming is the social components
the very different kinds of I imagine
communication going on on the two
platforms yeah right and the line in
terms of bullying and so on is different
on the GUP platforms so how do you I
mean in such a fascinating philosophical
discussion of where that line is I don't
think anyone knows the right answer
Twitter folks are under fire now Jack a
Twitter for trying to find that line
nobody knows what that line is but how
do you try to find the line for you know
trying to prevent abusive behavior and
at the same time let people be playful
and joke around and that kind of thing I
think in a certain way like even if you
have what I would call vertical social
networks it gets to be a little bit
easier so like if you have a clear
notion of like what your social network
should be used for or like what you are
designing a community around then you
don't have as many dimensions to your
sort of content safety problem as you
know as you do in a general purpose I
mean so like on on LinkedIn like the
whole social network is about connecting
people with opportunity whether it's
helping them find a job or to you know
sort of find mentors or to you know sort
of help them like find their next sales
leave or to just sort of allow them to
broadcast their their you know sort of
professional identity to their their
network of peers and collaborators and
you know sort of professional community
like that is I mean in like in some ways
like that's very very broad but in other
ways it's sort of you know it's narrow
and so like you can build a eyes
like machine learning systems that are
you know capable with those boundaries
of making better automated decisions
about like what is you know sort of
inappropriate and offensive comments or
dangerous comments or illegal content
when you have some constraints you know
same thing with the same thing with like
the gaming gaming social network
sufferance it's like it's about playing
games not having fun and like the thing
that you don't want to have happen on
the platform it's why bullying is such
an important thing like bullying is not
fun and also you want to do everything
in your power to encourage that not to
happen and yeah I but I think it's it's
sort of a tough problem in general it's
one where I think you know eventually
we're gonna have to have some sort of
clarification from our policymakers
about what it is that we should be doing
like where the lines are because it's
tough like you don't like in democracy
right like you don't want you want some
sort of democratic involvement like
people should have a say in like where
where the lines lines are drawn like you
don't want a bunch of people making like
unilateral decisions and like we are in
a we're in a state right now for some of
these platforms where you actually do
have to make unilateral decisions where
the policy-making isn't gonna happen
fast enough in order to like prevent
very bad things from happening but like
we need the policy-making side of that
to catch up I think is as quickly as
possible because you want that whole
process to be a democratic thing not a
you know not not some sort of weird
thing where you've got a non
representative group of people making
decisions that have you know like
national and global impact as
fascinating because the digital space is
different than the physical space and
which nations and governments were
established and so what policy looks
like globally what bullying looks like
globally what healthy communication
looks like global is there's open
question and we're offering and freaking
it out
yeah I mean with you know sort of fake
news for instance and deep fakes and
fake news generated by humans yeah so
even we can talk about defects like I
think that is another like you know sort
of very interesting level of complexity
but like if you think about just the
written word right like we have you know
we invented papyrus what's three
thousand years ago where we you know you
could sort of put put word on on paper
and then five hundred years ago like we
we get the printing press like where the
word gets a little bit more ubiquitous
and then like you really really didn't
get ubiquitous printed word until the
end of the nineteenth century when the
offset press was invented and then you
know just sort of explodes and like you
know the cross-product of that and the
industrial revolutions need for educated
citizens resulted in like this rapid
expansion of literacy and the rapid
expansion of the word but like we had
three thousand years up to that point to
figure out like how to you know like
what's what's journalism what's
editorial integrity like what's you know
what's scientific peer review and so
like he built all of this mechanism to
like try to filter through all of the
noise that the technology made possible
to like you know sort of getting to
something that society could cope with
and like if you think about just the
piece the PC didn't exist fifty years
ago and so in like this span of you know
like half a century like we've gone from
no digital you know no ubiquitous
digital technology to like having a
device that sits in your pocket where
you can sort of say whatever is on your
mind to like what would it Mary Heaven
or mary meeker just released her new
like slide deck last week you know we've
got 50 percent penetration of the the
internet to the global population like
they're like three and a half billion
people who are connected now it's it's
like it's crazy crazy croelick
inconceivable like how
all of this happens so you know it's not
surprising that we haven't figured out
what to do yet but like I gotta like we
got a really like lean into this set of
problems because like we basically have
three millennia worth of work to do
about how to deal with all of this and
like probably what yeah amounts to the
next decade worth of time so since were
on the topic of tough tough you know
tough challenging problems let's look at
more on the tooling side in AI that
Microsoft is looking at space
recognition software so there's there's
a lot of powerful positive use cases
yeah for face recognition but there's
some negative ones and we're seeing
those in different governments in the
world so how do you how does Microsoft
think about the use of face recognition
software as a platform in governments
and companies yeah how do we strike an
ethical balance here yeah I think we've
articulated a clear point of view so
Brad Smith wrote a blog post last fall I
believe this sort of like outline like
very specifically what you know whatever
what our point of view is there and you
know I think we believe that there are
certain uses to which face recognition
should not be put and we believe again
that there's a need for regulation there
like the the government should like
really come in and say that you know
this is this is where the lines are and
like we very much wanted to like
figuring out where the lines are should
be a democratic process but in the short
term like we've drawn some lines where
you know we push back against uses of
face recognition technology you know
like this city of San Francisco for
instance I think is completely outlawed
any government agency from using face
recognition tech and like that may prove
to be a little bit overly broad but for
like certain law enforcement things like
you you really III would personally
rather be overly sort of cautious in
terms of restricting use of it until
like we have you know
to find a reasonable democratically
determined regulatory framework for like
where we we could and should use it and
you know the the other thing there is
like we've got a bunch of research that
we're doing and a bunch of progress that
we've made on on bias there and like
there all sorts of like weird biases
that these models can have like all the
way from like the most noteworthy one
where you know you may have
underrepresented minorities who are like
underrepresented in the training data
and then you start learning like strange
things but like they're they're even you
know other weird things like we've I
think we've seen in the public research
like models can learn strange things
like all doctors or men for instance
just yeah i mean so like it really is a
thing where it's very important for
everybody who is working on these things
before they push publish they launch the
experiment they you know push the code
you know online or they even publish the
paper that they are at least starting to
think about what some of the potential
negative consequences are some of this
stuff i mean this is where you know like
the deep fake stuff I find very
worrisome just because there gonna be
some very good beneficial uses of like
Gann generated imagery and I and funny
enough like one of the places where it's
actually useful is we're using the
technology right now to generate
synthetic synthetic visual data for
training some of the face recognition
models to get rid of the bias right so
like that's one like super good use of
the tech but like
you know it's getting good enough now
where you know it's gonna sort of
challenge normal human beings ability to
like now you're just sort of say like
it's it's very expensive for someone to
fabricate a photorealistic
fake video and like ganzar gonna make it
fantastically cheap to fabricate a
photorealistic
fake video and so like what you assume
you can sort of trust as true versus
like be skeptical about is about to
change
yeah and like we're not ready for it I
don't think the nature of truth right
that's uh it's also exciting because I
think both you and I probably would
agree that the way to solve to take on
that challenge is with technology yeah
right there's probably going to be ideas
of ways to verify which which kind of
video is legitimate which kind of is not
so to me that's an exciting possibility
most most likely for just the comedic
genius that the internet usually creates
with these kinds of videos yeah and
hopefully will not result in any serious
harm yeah and it could be you know like
I think we will have technology too that
may be able to detect whether or not
something's fake a real although yeah
the the fakes are pretty convincing even
like when you subject them to machine
scrutiny but you know that we we also
have these increasingly interesting
social networks you know that are under
fire right now
for some of the bad things that they do
like one of the things you could choose
to do with a social network is like you
could you could use crypto and the
networks to like have content signed
where you could have a like full chain
of custody that accompanied every piece
of content so like when you're viewing
something and like you want to ask
yourself like how you know how much can
I trust this like you can click
something and like have a verified chain
of custody that shows like oh this is
coming from you know from this source
and it's like sign
I like someone whose identity I trust
yeah yeah I think having that you know
having that Chain of Custody like being
able to like say oh here's this video
like it may or may not have been
produced using some of this deep fake
technology but if you've got a verified
Chain of Custody where you can sort of
trace it all the way back to an identity
and you can decide whether or not like I
trust this identity like oh no this is
really from the White House or like this
is really from the you know the office
of this particular presidential
candidate or it's really from you know
Jeff Weiner CEO of of LinkedIn or Satya
Nadella CEO Microsoft like that might
that might be like one way that you can
solve some of the problems and so like
that's not the super high tech like
we've had all of this technology forever
and back but I think you're right like
it has to it has to be some sort of
technological thing because the the
underlying tech that is used to create
this isn't not going to do anything but
get better over time and the genie is
sort of out of the bottle
there's no stuffing it back in and
there's a social component which i think
is really healthy for a democracy where
people be skeptical about the thing they
watch yeah in general so you know which
is good skepticism in general is good
and it's good content so deep fakes in
that sense of creating global skepticism
about can they trust what they read it
encourages further research I come from
the Soviet Union where basically nobody
trusted the media because you knew it
was propaganda and that encouraged that
kind of skepticism encouraged further
research about ideas
yeah posters just trusting any one
source look I think it's one of the
reasons why the the you know the
scientific method and our apparatus of
modern science is so good like because
you don't have to trust anything like
you like the whole notion of you know
like modern science beyond the fact that
you know this is a hypothesis and this
is an experiment to test the hypothesis
and you know like this is a peer review
process for scrutinizing published
results but like stuffs also supposed to
be reproducible so like you know it's
been better
by this process but like you also are
expected to publish enough detail where
you know if you are sufficiently
skeptical of the thing you can go try to
like reproduce it yourself and like I I
don't know what it is like I think a lot
of Engineers are like this where like
you know sort of this like your brain is
sort of wired for for scepticism like
you don't just first order trust
everything that you see an encounter and
like you're sort of curious to
understand you know the next thing but
like I think it's an entirely healthy
healthy thing and like we need a little
bit more of that right now so I'm not a
large business owner so I'm just I'm
just a huge fan of many of Microsoft
products I mean I still actually in
terms of I generate a lot of graphics
and images and I still use PowerPoint to
do that it beats illustrator for me even
professional a sort of is this
fascinating so I wonder what is the
future of let's say windows and office
look like is do you see it I mean I
remember looking forward to XP wasn't
exciting yep when XP was released just
like you said I don't remember when 95
was released but xp for me it was a big
celebration and and 110 came out I was
like okay what's nice it's a nice
improvement but yeah so what do you see
is the future of these products and you
know I think there's a bunch of exciting
I mean though in the office front
there's going to be this like increasing
productivity winds that are coming out
of some of these AI powered features
that are coming like the products are
sort of get smarter and smarter in like
a very subtle way like there's not gonna
be this Big Bang moment where you know
like Clippy is gonna reimagined it's
gonna wait a minute
okay well have that wait wait wait
Clippy coming back in but quite
seriously
so injection of AI there's not much or
at least I'm not familiar sort of
assistive type of stuff going on inside
the office products in like a clippie
style a
assistant personal assistant do you
think that there's a possibility of the
future alright so I think they're a
bunch of like very small ways in which
like machine learning power and
assistive things are in the product
right now so there are there a bunch of
interesting things like the auto
response stuffs getting better and
better and it's like getting to the
point where you know it can auto respond
with like okay let you know this person
is clearly trying to schedule a meeting
so it looks at your calendar and it
automatically electrons to fines like a
time in a space that's mutually
interesting like we we have this notion
of Microsoft search where it's like not
just web search but it's like search
across like all of your information
that's sitting inside of like your
office 365 tenant and like you know
potentially in other products and like
we have this thing called the Microsoft
graph that is basically a API federated
at you know sort of like gets you hooked
up across the entire breadth of like all
of the you know like what were
information silos before they got woven
together with the graph like that is
like getting increasing with increasing
effectiveness sort of plumbed into the
into some of these auto-response things
where you're gonna be able to see the
system like automatically retrieve
information for you like if you know
like I frequently send out you know
emails to folks were like I can't find a
paper or a document or whatnot there's
no reason why the system won't be able
to do that for you and like I think the
the its building towards like having
things that look more like like a fully
integrated you know assistant but like
you'll have a bunch of steps that you
will see before you like it will not be
this like Big Bang thing where like
Clippy comes back and you've got this
like you know manifestation of you know
like a fully fully powered assistant
so I think that's that's definitely
coming in like all of the you know
collaboration co-authoring stuff's
getting better you know it's like really
interested like if you look at how we
use like the office product portfolio at
Microsoft like more and more of it is
happening inside of like teams as a
canvas and like it's this thing where
you know you've got collaboration is
like at the center of the product and
like we we built some like really cool
stuff that's some of which is about to
be open source that are sort of
framework level things for doing for
doing co-authoring so in is there a
cloud component to that so on the web or
is it I forgive me if I don't already
know this but with office 365 we still
the collaboration would do if you're
doing word which still send the file
around no advice yeah this is it
we're already a little bit better than
that and like you know so the fact that
you're unaware of it means we've got a
better job to do feel like helping you
discover discover this stuff but yeah I
mean it's already like got a huge huge
clock but and like part of you know part
of this framework stuff I think we're
calling it like I like we've been
working on it for a couple years so like
I know the the internal code name for it
but I think when we launched it a bill
is called a fluid framework and but like
what fluid lets you do is like you can
go into a conversation that you're
having in teams and like reference like
part of a spreadsheet that you're
working on where somebody's like sitting
in the Excel canvas like working on the
spreadsheet with a you know chart or
whatnot and like you can sort of embed
like part of the spreadsheet in the
team's conversation where like you can
dynamically update it and like all of
the changes that you're making to the to
this object are like you know coordinate
and everything is sort of updating in
real time so you can be in whatever
canvas is most convenient for you to get
your work done so I out of my own sort
of curiosity is engineer I know what
it's like to sort of lead a team of 10
Engineers Microsoft has I don't know
what the numbers are maybe fifty maybe
sixty thousand engineers with a lot more
genius I don't know exactly what the
number is it's a lot it's it's tens of
thousands sites this is more than ten or
fifteen what I mean you've uh you've led
different sizes mostly large size of
Engineers what does it take to lead such
a large group into a continued
innovation continue being highly
productive and yet develop all kinds of
new ideas and yet maintain like what
does it take to lead such a large group
of brilliant people I think the thing
that you learn as you manage larger and
larger scale is that there are three
things that are like very very important
for big engineering teams like one is
like having some sort of forethought
about what it is that you're gonna be
building over large periods of time like
not exactly like you don't need to know
that like you know I'm putting all my
chips on this one product and like this
is gonna be the thing but like it's
useful to know like what sort of
capabilities you think you're going to
need to have to build the products of
the future and then like invest in that
infrastructure like whether and I like
I'm not just talking about storage
systems or cloud api's it's also like
what does your development process look
like what tools do you want like what
culture do you want to build around like
how you're you know sort of
collaborating together to like make
complicated technical things and so like
having an opinion and investing in that
is like it just gets more and more
important and like the sooner you can
get a concrete set of opinions like the
better you're going to be like you can
wing it for a while small scales like
you know when you start a company like
you don't have to be like super specific
about it but like the biggest miseries
that I've ever seen as an engineering
leader are in places where you didn't
have a clear enough opinion about those
things soon enough and then you just
sort of go create a bunch of technical
debt
and like culture debt that is
excruciating ly painful to to clean up
so like that's one bundle of things like
the other the other you know another
bundle of things is like it's just
really really important to like have a
clear mission that's not just some cute
crap you say because like you think you
should have a mission but like something
that clarifies for people like where it
is that you're headed together like I
know it's like probably like a little
bit too popular right now but you've all
her re book sapiens one of the central
ideas and in his book is that like
storytelling is like the quintessential
thing for coordinating the activities of
large groups of people like once you get
past Dunbar's number and like I've
really really seen that just managing
engineering teams like you you can you
can just brute force things when you're
less than 120 hundred fifty folks where
you can sort of know and trust and
understand what the dynamics are between
all the people but like past that like
things just sort of start to
catastrophic ly fail if you don't have
some sort of set of shared goals that
you're marching towards and so like even
though it sounds touchy-feely and you
know like a bunch of technical people
will sort of balk at the idea that like
you need to like have a clear like the
missions like very very very important
you've always write write stories that's
how our society that's the fabric that
connects us all of us is these powerful
stories and that works for companies -
and it works for everything like it mean
even down to like you know you sort of
really think about like a currency for
instance is a story a constitution is a
story our laws or story I mean like we
believe very very very strongly in them
and thank God we do
but like they are there they're just
abstract things like they're just words
it's like we don't believe in them
they're nothing
and in some sense those stories are
platforms and the kinds some of which
Microsoft is creating right you have
platforms on which we define the future
so last question what do you think if
philosophical maybe bigger than you know
Microsoft
what do you think the next 20 30 plus
years looks like for computing for
technology for devices do you have crazy
ideas about the future of the world yeah
look I think we you know we're entering
this time where we've got we have
technology that is progressing at the
fastest rate that it ever has and you've
got you get some really big social
problems like society scale problems
that we have to we have to tackle and so
you know I think we're gonna rise to the
challenge and like figure out how to
intersect like all of the power of this
technology with all of the big
challenges that are facing us whether
it's you know global warming whether
it's like the biggest remainder of the
population boom is in Africa for the
next 50 years or so and like global
warming is gonna make it increasingly
difficult to feed global population in
particular like in this place where
you're gonna have like the biggest
population boom I think we you know like
AI is gonna like if we push it in the
right direction like you can do like
incredible things to empower all of us
to achieve our full potential and to you
know like live better lives but like
that also means focus on like some super
important things like how can you apply
it to health care to make sure that you
know like air quality and cost oh and in
sort of ubiquity of health coverage is
is better and better over time like
that's more and more important every day
is like in the in the United States and
like the rest of the industrialized were
also
in Europe China Japan Korea like you've
got this population bubble of like aging
working you know working aged folks who
are you know at some point over the next
20-30 years they're gonna be largely
retired and like you you're gonna have
more retired people than working age
people and then like you've got you know
sort of natural questions about who's
gonna take care of all the old folks and
who's gonna do all the work and the the
answers to like all of these sorts of
questions like where you're sort of
running into you know like constraints
of the you know the the world and of
society has always been like what tech
is gonna like help us get around this
you know like when I was when I was a
kid in the seventies and eighties like
we talked all the time about like oh
like population boom population boom
like we're gonna like we're not gonna be
able to like feed the planet and like we
were like right in the middle of the
Green Revolution we're like this this
massive technology driven increase in
crop productivity like worldwide and
like some of that was like taking some
of the things that we knew in the West
and like getting them distributed to the
you know to the to the developing world
and like part of it were things like you
know just smarter biology like helping
us increase and like we don't talk about
like yep overpopulation anymore because
like we can more or less we sort of
figured out how to feed the world like
that's a that's a technology story and
so like I'm super super hopeful about
the future and in the ways where we will
be able to apply technology to solve
some of these super challenging problems
like I've I've like one of the things
that I I'm trying to spend my time doing
right now is trying to get everybody
else to be hopeful as well because you
know back to the Harare like we we are
the stories that we tell like if we you
know if we get overly pessimistic right
now about like the the potential future
of technology like we you know like we
may fail to fail to get all the things
in place that we need to like have our
best possible future and that kind of
hopeful optimism I'm glad that you have
it because you're leading large groups
of engineers that are actually defining
that are writing that story that are
helping build that future which is super
exciting and I agree with everything you
said except I do hope cliff he comes
back haha we miss him I speak for the
people
Alan thank you so much for talking to
now thank you so much for having me it
was pleasure
you