so this session it's gonna be in about
three segments so we've got two
ten-minute discussions from thought
leaders in moving people in smart cities
and then we've got two panels and I'll
introduce each of those panels as they
come but as is standard for the way I
love to moderate a stage the first two
speakers the ten-minute slots each I'm
gonna tell really fun quirky insights
into them because that's kind of what
it's about so Jamie Heywood who is the
regional GM for UK and northern uber he
was an extra in a Chinese movie when he
was in China and he played foreign
soldier how's that for a dramatic pause
and the movie was about the opium wars
I'm just gonna leave it at that then
Dave Davis also agreed to be my personal
bouncer in case any of you guys are
badly misbehaved he used to be a
competitive Thai boxer so behave back
there or else um I'm gonna SiC Dave on
you okay so with that Jamie I'd love to
invite you to stage and enter foreign
foreign soldier is that okay can
everyone hear me at the back okay great
so what I wanted to do is spend ten
minutes talking a little bit about an
uber what we think how we think
transportation in cities is going to
change and the role that we want to play
as part of that change
so I want to start by maybe just taking
you back 10 years so 10 years we're
probably this tunnel did not exist the
King's Cross building site did not exist
before Boris bikes existed when
congestion and pollution was no longer
one of the the concerns that people had
around getting around a city they were
quarter of a million fewer bike journeys
in London ten years ago there was no
ruber and nearly every
seventeen-year-old believed getting a
car was a rite of passage to adulthood
now you know in that time obviously uber
has launched and we now help over 3.5
million Londoners get around the city on
a regular basis and we're part of the
fabric of helping London function and we
recognize that there are
responsibilities that come with the
growth that we've seen and with the role
that we play as a part of London's
infrastructure and there's sort of three
areas that that we think where those
obligations for us are very real and we
take them very seriously the first one
is around reducing emissions so it's
around clean air the second one is
around reducing congestion so stopping
traffic jams or preventing traffic jams
and the way we really want to do that is
our primary commit which which is
actually the cause of both of those
which is reducing private car ownership
now if we went forward ten years from
from today hopefully you'll be coming to
the that the version of this in in ten
years time I think one thing that's
clear is that the the way we transport
people around cities now which is based
on private car ownership is not
sustainable and there's there's three
reasons for that firstly it's
environmentally unsustainable so 50
percent of roadside emissions are caused
by cars and that affects city health
that affects life expectancies that
affects quality of life secondly it's
hugely expensive so with the amount of
time that Londoners spend in traffic
jams that cost London about eight
billion pounds a year which is about one
and a half thousand pounds per Londoner
so that's an avoidable cost that that we
are currently bearing because of the way
people get around and the third thing is
it's a really bad use of space so the
average car park in London now costs 200
thousand pounds which is more than the
average house
in the UK and when buildings are built
now they're built with 20 30 sometimes
40 percent of space allocated to cars
now that doesn't make sense for an asset
that sits empty ninety-five percent of
the time now I joined uber about twelve
months ago and the first thing I did was
I went through the process of getting a
private higher vehicle license so I I
joined uber and I started driving around
the city and what's what's really
interesting as a driver is you you you
see London from a dev very different
perspective you see how London breathes
so my first trip of the day would always
be i live in crouch and my first trip of
the day would always be being pulled
into central london on someone's commute
and then you get pulled out for the rest
of the day and you're helping people
live their lives and get around in
london and so I drove nurses to the
hospitals
I drove teachers to school i drove kids
and their parents back from school i
drove people to bars I drove drunk
people back from bars I then drove back
to the bar with the person to pick up
the suit that he left and then back home
and he left the suit in the car and I
then had to do that that I mean you you
feel how London lives and you feel the
city breathe through the perspective of
uber and so that was a great insight
into I think you know some of the
important some of the role that uber
plays as part of the fabric of London
but ride-hailing so the uber X product
is not going to be enough and I'm I've
also been very proud in the 12 months
that I've been enrolled to start to
broaden
ubers role in helping people get from A
to B so we were discussing earlier we
launched jump bikes in Islington a
couple of weeks ago and we integrated
buses and public transport and the tube
into the app so now if you're going
anywhere in London one of the options
you'll have is public transport you'll
have accurate information about how long
that will take and health at how much
that will cost and that will give you
the choice as to how you want to get
around
and we're also doing a lot of work to
improve our pool service which is our
shared ride service which is great for
Londoners because by putting more people
in in one car you reduce congestion you
reduced reduce emissions and you
obviously therefore reduce prices for
passengers while still making sure that
drivers earn a fair wage so what we're
starting to see through this combination
of of building what you know working our
way into the fabric of London lives and
and launching new modes of transport is
we're starting to see that people are
giving up their private cars now this is
a trend that will take many years to
work through but the early signs are
already available teenagers are
currently 40% less likely to have a
driving licence than they would have
been 10 years ago four out of lung ten
Londoners say that they would consider
not owning a private car and using uber
and other modes of transport instead and
a quarter of Oberland uber uber users
actually bring their baby home from
hospital in an uber so we really are
building ourselves into into helping
people live the lives they want to as
well as reducing congestion and
Commission and emissions so the process
which as I've said is going to be a long
process of reducing of reducing private
car ownership and meaning that people
start to use transportation through the
app and that the phone starts to replace
the car I wanted to take you through
three things that we're doing now to
help make that happen the first one is
around reducing emissions so some of you
may may know but we've made a commitment
in London to by 2025 make sure that
every driver enabled through the app is
in a electric vehicle and the way we've
launched that is through the Clean Air
Fund so some of you may have seen as
you've driven around at the bottom of
your receipt a small charge that we that
we charge and that money is going into
driver savings accounts and accumulating
to help drivers upgrade into
electric vehicles so we've raised
currently for drivers thirty million
pounds today which is 15 percent of the
way towards our aspiration of raising
two hundred million pounds for drivers
to help get them into electric vehicles
by 2025 and although we're early on the
journey we're starting to see some good
signs so we've seen the number of
electric vehicles on the platform
increased back three hundred percent
this year and we're already doing over
2.5 million kilometres of trips in v's
every week in London so you know a long
journey but but a good start
the second part the second thing we're
doing to try and mean that people give
up their private cars and replace it
with their phone is just about giving
people more options so I've spoken about
transit and integrating public
transportation in the app we've done
that in London we're looking to take
that that out further I've spoken about
launching jump which in the moment is in
just Islington we're looking to grow
that and I've spoken about pool and our
shared rides product which again is in
London and we'll be looking looking to
try and grow that and change user habits
about about how people think about
getting around the city and we're also
in other areas that I look after within
northern and eastern europe rolling out
on demand bus services and a range of
other things to try and explore other
ways of getting people around the third
thing is partnering for cities so
obviously we didn't always get it right
right
Uber's had a a difficult two to three
years as we've sort of had a license not
renewed and then renewed and you know
the commitment that we are making and
one of the key things that I've been
doing in my year is to listen to cities
and to make sure that they understand
that we're a better partner and that
we're part of the solution to the way to
helping Londoners get a little get
around and improving Londoners quality
of life not part of the problem and one
of the ways we do that is we share all
of the data that we have on the app so
we share with TfL and other regulators
and other third parties the data about
all of the journeys that
they're doing every every month and that
allows them to use that in traffic
planning and other things so to wrap up
the way we move matters the way we move
matters because it finds the air we
breathe it defines the shape of the city
we operate in it defines that the way
buildings are designed and I think
London is pioneering some of the changes
there firstly with some of the
congestion charging and emission
charging that has been introduced and
which I think go some way towards it but
it's going to be a long journey and it's
a journey that we are over are committed
to being a good partner for thank you
very much thanks Jamie
and now I bring Dave Sweeney from sorry
guys from o2 motion ouch are there can
we get the slides please so you're
probably wondering why there's a guy
from o2 standing in front of you talking
about transportation and moving people
around hopefully by the end of the
speech you might have some idea it's a
good good chance to see how that our how
times are changing here we go so if the
reason being it's all about it's all
about our data so mobile phone companies
obviously need to know where you are at
any point so if you go telephone call
send a text message we can connect you
and we can we can give you that service
and we take that mobile phone data and
we anonymize it we aggregate it and we
extrapolate it to give a really good
understanding of crowd movement of
population movement the data samples
that we work with as a cellular company
at a vast so 25 million 25 million
customers across the UK we actually also
do this in 13 other countries across the
globe and then the telefónica footprint
that's why 25 million customers produces
6 billion events a day on the mobile on
the mobile phone s across 2g 3G and 4G
when five-cheese introduced that
number will really really skyrocket we
saw a vast jump from in the introduction
of 4G a good few years ago now but what
we do we take that data and we process
it into insights so as you can imagine
the data that comes out of the mobile
phone network isn't designed to be used
for insight purposes so it comes out in
a very strange way and it's not quite as
simple as just literally pulling the
data out putting it on a database and
saying that's where everyone is and that
that's how they're moving around the
cellular network is a is a big moving
beast and it's constantly balancing the
network based on people's movements and
capacity loading and so on and so on so
there's quite a lot of different
techniques we have to use in order to
understand how things work but we've
been working with this data now for a
number a number of years and we started
to build out a number of use cases as
you'll see from from the slides there we
take we pull across demographic insight
again all anonymized and aggregated so
we're not actually tracking any
individuals the data we use is not
classed as PII which means we're not
impacted by GDP are we have persistent
IDs on the data so we can understand
people's patterns and commutes and
journeys of interest places of interest
we processed the data looking for
specific things in speeding patterns in
the data to understand for example
different modes of transport so to put
that into into context if you're if
you're traveling on a on a train with a
hundred other people you'll all be
handing over from one cell to the next
at the same time as you go through a
tunnel and come out the other side all
of your phones will be reaching to the
network to try to get a connection so
it's very easy for us to take into
consideration the speed that you're
travelling at the speed of the trains
are traveling at with a clustering
algorithm to say these people were
definitely on the train and we use a
number of different techniques to
identify lots of different modes of
transport we've done quite a lot of work
in infrastructure we've got some great
projects that have gone way past proof
of concept some rolled out with highways
England's probably our biggest and best
product to date we've got the with built
something called the trip information
system which process the years worth of
data
for the whole of the UK and highways
England make their data available for
different consultants who's working on
their transport modeling projects to
understand demand and the way that
people are using the strategic network
and they can literally split the data by
I want to look at 7:00 a.m. to 8:00 a.m.
on every Tuesday for the year and make
any cut type of data by the mode of
transport they want to do TfL have done
a very similar project as you can
imagine when you start to work in a city
like London you introduce other other
problems within the data so there's
there's more people that grab the
resolution of the data doesn't quite
support the mobile mobile phone network
there are more cells there's more modes
of transport so that the algorithms that
we have to develop have been worked on
over a number a number of years but it's
not enough within a city so we take our
data as a base layer and then we use all
TFLs data to overlay on top so we're
taking feeds from Oyster card data I bus
data I think it's about 15 different
data sources that we use to produce this
model called Project Edmund which again
is available for planning purposes
across the city we've started now to
develop the data into real time purposes
so all the stuff with your previously
was retrospective based on historic data
now assigned to pull the data through in
real time that firstly that does narrow
down our use cases a little bit because
all the analytics we would apply to the
data previously can't all be hard-coded
in on the real time platform so we
reduce our capability slightly that said
we also open up all the different use
cases to us so if we're running with
real time data we've got real time
traffic flow information public sector
can start to make decisions based off of
that data you can start to react to
things that happen you can start to look
at specific events and make decisions
across the network that can you can
support all sorts of things the other
interesting thing about mobile phone
data is its multimodal there were very
few data sources that are used in
transport plan in or in traffic rooms
that actually cover all the different
modes and mobile phone data is a problem
a very few that illicitly sits across
all those different modes of transport
so the introduction of real-time beta
now has really moved us into almost a
different world and it's taking this
into the smart cities world so if you
think about smart cities two of the
probably strongest verticals within
there are the ones that there's a lot of
interest about transportation and then
environment and pollution I would see
the two quite heavily linked as well and
so we've started to move in into that
world and when you start to break down
the components of a smart city it makes
more more rare than what makes more
sense for a phone company to be involved
in it so obviously we've already do the
data piece connectivity is going to be a
huge part of any smart City you know
things need to happen in real time very
low latency um so again it fits if you
think about the partners that that tell
you telcos have the people that provide
our networks the hardware the software
they're all very these companies all the
same companies that are providing a lot
of IOT devices and a lot of IOT
solutions
so we're it very well place to start
working in this in this sector the first
project that we're working on for in the
smart cities world is one called Thames
Valley live labs and it's it's a product
that it's a it's a project that we're
leading on and we're you can see all the
names the different partners are
involved it's heavily heavy heavy input
from public sector so it's right across
the Thames Valley region and the main
study air will be bark shit will go
really fast now so I'm running way out
of time I'm gonna quickly talk about
some of the use cases that we're running
so we're looking at five different use
cases potholes energy air quality
traffic flow and health and in each in
each solution we're taking different
part different partners different
complex models to work out and give give
ourselves different results but the
whole purpose of this is to say all
these products all this technology all
works in in the lab but does it work in
the real world so for example the
pothole ones very obviously a massively
sexy topic but a huge problem for for
public sector whether it's noise
pollution by lorries rambling over the
holes whether it's the damage it's
caused or wherever it even causes
accidents and we're putting devices on
board some come
County vehicles they drive across they
show us where the potholes are we then
take the mobile phone datas create a
priority matrix to say these are where
all the potholes are these are the ones
you need to fix first because these are
the roads that are used the most the
second one is air quality we're going to
be one of our partners is Siemens we run
all the traffic light systems we've put
in air quality sensors on the traffic
lights so that we can help to understand
what the pollution levels are like again
we reference the mobile phone data which
gives us an understanding of this is
that this is the quality of the air and
at these times of day in these areas and
these are the people that are exposed to
it so again it starts to give us some
interesting data the output of that is
to say start to share that information
with with the citizens with the public
to say would you make a different
decision about what time you travel or
what mode of transport you use if you
knew if you knew this was this was the
case and the final one I wanted to speak
to so I knew I'm running a little bit
out of time is traffic congestion so
congestion have massive Crippler for the
economy if we can start to use data to
improve the way that the roads run that
traffic flows then it's a mass it's a
massive step in the right direction
we're pulling through real-time over
mobile phone data we're also taking data
using IOT connectivity out of the
traffic lights in order to start to
optimize the traffic light so we can
move the traffic flows much quicker it's
widely thought that traffic lights were
optimized but it's all done on historic
and it doesn't react to any situation
that's around so can we do it all in the
real world what is it what does it look
like and then once we understand the
learnings and we're starting to
communicate to the citizens how does it
scale up and can we actually turn it
into a smart city hopefully we'll have
the answer in two years Thanks
thanks Dave
got a good audience out there so next up
we're gonna have two panels the first
one is gonna be on data and people
moving and then the next one is going to
be on new uses of data and services but
before that I'm gonna ask you guys to do
something funny I want to take a picture
of everyone because it's kind of fun so
can you all like make faces wave your
arms do something silly because you know
the photographer's gonna do it and I'm
gonna do it with my iPhone come on guys
on the count of three one two three come
on yay one more one more come on one two
three come on there we go that's good I
like that it's such a cool venue we have
to get some kind of cool photo hopefully
that works for you as well cool okay so
next up the moderator for the next two
panels is Andrew Eiland from deepmind
now Andrew right now leads the deepmind
team of software engineers that are
bringing technology to google's and HS
partners which is phenomenal but
actually he used to run Google Maps in
the UK so he knows what he's talking
about I think it's fair to say now again
quirky fact about Andrew is he bakes two
loaves of sourdough what is a week a
week yeah some times a day and he showed
me a photo and it looked quite delicious
I'm quite upset you didn't bring any for
us backstage and he also makes homemade
jam which i think is quite cool so with
that the panel on data and people moving
so can I get the other panelists up
please and over to you Amanda thanks
pindy
thanks very for joining so we're gonna
have a discussion here with Dave and
Jamie through you've just heard from
also I'd like to welcome Claire Fram to
the stage product manager it's Arif I
think maybe to start perhaps if clay you
could introduce
erika little because obviously not
having given little talk and not being a
technology company i'm not sure how
we're people in the audience will be of
the firm so it'd be great to hear a
little bit more about the firm and
you're all they're wonderful i'm really
good to be here on kind of andrews white
couch I'm Claire Fram I'm a product
manager at Arup and if you're not
familiar with Arab we are a global
company of more than 14 thousand
designers engineers consultants planners
it's really easy to talk about Arab here
at this venue because Arab was involved
in a lot of the king's costs and cold
drops yard work King's Cross is a great
example of planning IT work
engineering all coming together to
deliver kind of a final product my
particular role as a product manager is
a little bit of a new area for Arab but
in many ways fits in with the work that
we've we've always done the product that
I am managing currently is mobility
mosaic so I'm working with our transport
team we're really trying to who've
identified a gap our clients are trying
to understand how people are actually
moving around cities so that they can
plan infrastructure that meets right
user needs human centered design we know
that's so important and the way
transport consultants do you thought or
have traditionally done that is using
whatever data is available to them which
could be census data or pen and paper
surveys or might have some kind of
information about supply so particular
vehicle fleets or transport use but not
necessarily the overall kind of end to
end so that is a little bit about me and
why I'm here thanks thanks so
fascinating talks from Jamie and Dave
one of the things that interests me
personally having worked mapping systems
for many years is how transportation
actually has the power to change the
environments around and we talked a
little bit earlier in your talks about
how data can do that and I think there
are a couple of concepts that you
mentioned during the talks I'd like to
pick up on one is on the real-time
aspect you know traditionally
transportation planners have measured
people and bicycles and cars by going
out on the streets with pens and paper
and now presumably the product suits
both uber and OTR working on give you
much more kind of accurate real-time
counts and I was wondering how that kind
of changes the the transportation
planning process in your minds perhaps
start with Dave yeah I mean I think the
benefits are endless you know we talked
about the reduction in congestion I
think all of it starts with
understanding the situation now
understanding what's going on and using
the data and the insights to to build up
that picture but ultimately it's good
once you understand the position in the
situation you can then give the sits and
information and let them make decisions
based on the real data and the real
information that could potentially you
know change what they're doing maybe
change the mode of transport so that
they're using and that sort of things so
I think ultimately you know the the end
results and the benefits are all
directed at systems Jamie how do you
feel that there so obviously I mean for
those who view but it's a very real-time
service you get your you get your etas
and it works I think the the the
interesting thing one of the interesting
things we've been grappling with this
year is actually how you make shared
rides work so pool is a really really
interesting real time challenge because
what you have is you have an individual
in a car going from saying imagine it's
my commute right from crouch end to
gate and what we you know what what our
task in that is is as that car is going
from crouch end to Aldgate how do we
bring other people to sit in the
remaining two or three seats and that is
a that is a that is a challenge that is
working out second by second and minute
by minute and we need to do it in a way
that optimizes not just for the riders
and drivers because obviously the more
people you put in the car the better it
is for congestion the better it is for
emissions and the better it is for
riders who will pay less but you also
have to do that in a way in a way that
gets the right balance between
utilization in the vehicle and
convenient for the riders and drivers so
you don't take huge trips that go long
distances out of the way so that the new
shared Rise product which we launched
which I mentioned earlier actually what
we found is one of the best ways of
optimizing this in real time is to is to
ask riders to walk up to 250 meters at
the beginning and end of their journey
and when you do that you you actually
allow a much more optimal solution that
works for everyone but that's a
real-time solve so we have algorithms
and we have systems that are working on
that sort of every second of the day
across London across millions of rides
that really seems like fantastic use of
data to help you drive that that
decision about where to kind of pick
people up I noticed that in your talk
you you mentioned a lot about how you
see you BER as being part of the fabric
of London and it's interesting that when
I think about the kind of the fabric of
transportation in London you think about
roads you think about bus lanes you
think about the the green taxi driver
cafes that are providing welfare support
for the actual black cab drivers is that
something that you a mover of thought
about about how it over interacts with
the actual physical infrastructure of
cities so we we have we have a number of
sort of sites in in London and the other
cities we operate which we call green
light hubs which are which are when
drivers come in and they go through the
the onboarding process and if they have
queries or they want to talk with us
about any questions they have they can
come on on board so there's one
if for anyone who's interested in being
in an uber driver one may all get our
happy to share the address afterwards so
yes we have physical infrastructure but
obviously we're primarily a sort of
virtual service and we think that
probably makes sense to keep it that way
obviously so I think you've both talked
about how the data that you're producing
both rubra notes you can influence our
kind of planning processes and
transportation planning
obviously player working at our of Eric
I've been involved in in transportation
planning for many many years using kind
of existing data sets and I just wanted
to dig in a little more detail about how
you as a company approach kind of
managing the data that you need to kind
of make those decisions managing data to
support kind of transport planning
exactly yes and so it will really depend
on the question and the the client and
we work with both main big cities and
transport authorities who will want to
know what does it look like if we want
to extend a metro line for example and
so understanding how to access that data
is always the first question and is
always the hardest question our clients
often don't know what data is available
what is actually in the data that
they're promised and so they're kind of
these traditional methods that have been
used for a long time which is looking at
census data
pen-and-paper survey data and trying to
understand what can I actually get out
of new data which isn't new right it
we've had mobile data and kind of
vehicle fleet traffic data for quite
some time
I'd say then that's that's paired with a
lot of modeling work and again not
modeling transport modeling is also
kind of old and and that's one of the
things I'm working with our team to to
update to take advantage of new ways of
using data yeah of course I mean so we
did we do a lot of in this place as well
and I think it's it's about choosing the
right data sets features together
because there's so many de says out
there really did complement each other
so for example we'll use we've got
really good understanding of macro
movements on on a large scale and
obviously countrywide but GPS data set
for example gives you a far granular far
better understanding of granular
movements or but albeit not as big date
sample so if for example you put
together
uber day to a vote to data might be on
something here Jamie by the way and then
you you you know you will have something
that's stronger than some of its parts I
mean for us I think the key thing is
actually what's the problem we're trying
to solve and then the way we we approach
that is if the problem is clear then how
do we have data that can help address
that problem so one of the problems
we've we've got which got sort of a
lines to our commitment to take the term
help drivers upgrade into electric
vehicles by 2025 is where's the charging
infrastructure and the problem made even
more real than that is that per head of
population the charging infrastructure
in London is about a tenth that of world
leading cities in the Nordics so
obviously our commitment to help our
drivers move to v's creates a problem
which is how you know they have to be
able to charge so one of the things
we're working on is how do we use data
to address that problem which is where
should the charges be so what we're
doing now is we we we obviously have a
lot of data about where uber drivers
drive and and where they stop and how
they work and we are using that data to
populate and interfacing it with in the
the tech roadmaps of the e V vehicle
providers and battery life and battery
capacity charging times to come up with
the optimal layout of charging
infrastructure in London
as as it progresses as our fleet
upgrades and as battery technology means
that you can actually charge quicker and
last longer and you know that's then
that then is allowed us to sort of work
both publicly with some of the councils
who obviously have a key role in in this
in this area of sort of creating the
space where parking can can also be
enabled for charging but also then
private providers for whom this is a
commercial interest so that will be an
example where we're using data to solve
a very real problem which is hopefully a
you know a problem that will make cities
more livable or a solution that will
make cities more livable so I think this
is just showing how valuable data is and
I'm really interesting this question
about the value of data so I think there
was a lot of talk in the talks earlier
about its use of the word sharing of
data and I'd like to kind of explore a
little more what that means in practice
you mentioned that sharing data has been
part of boobers discussions of CFL
licensing and the like and I think Dave
you also mentioned sharing of data how
do you view that value is this for
example 402 a commercial concern and for
part of attacks of operating in a city
like how does that work out if I also
there so I I think you know we as a
partner for cities in helping people
sort of get around in within cities I
think it's essential that we share our
data so we we've created a tool called
uber movement which brings together
aggregates our data and then allows
regulators and other third parties to
interrogate that tool for traffic flows
traffic information speeds etc that
that's something we make openly
available I wouldn't call it tact attack
so much as a desire to do the right
thing by cities and how about you Dave
is that for more of a commercial
proposition all right I think
and we said we do commercialize the data
we mean provide it into public sector we
you know we do charge for it and I think
as I've explained we don't we don't just
pull the data out the network it's quite
a lot of platforms and processes that
required an order in order to get it
into a usable state so we couldn't
really do that if you wanted to and I
think but but if you look at the data
sources the public sector of you
traditionally we are just as a very very
small percentage of the cost of some of
the data sources and if you look at the
budgets that public's like to have for
this type of things they're saving a lot
of money by embracing some new
technologies I think the other point to
make is whatever the value of the data
is today will be very different in a
year's time as it was two years ago and
so on some because technologies and data
sources and Internet of Things there's
just more and more more and more data
available every every day let alone
everything every year so that you know
the new solutions and those sources are
quickly being disrupted yeah and if I
can jump in I'm glad that you asked
about sharing of data and what I think
is really interesting about this
particular panel at Cog X is that we
actually have data providers essentially
in this room and talking where the lots
of the other focus on cog X is done like
the use of the data and so here we have
kind of a collection of people who are
both producing and then using data and
some of the other themes that have come
out through the cog X conference have
been about how to what is the
responsibility of kind of everybody in
this community around data I was at a
great panel yesterday
the Alan Turing is 2/10 about data in
areas of conflict and about the the
misuse and potential abuse of data right
that's that's quite kind of intense view
of how data can be used but kind of one
of the themes that came out was making
data transparent being transparent about
what is in it the provenance and
intended purpose of it
just thinking about have that then fits
with something that Martha Lane Fox
identified which was that there's really
lots of Education needed between or for
our leaders in the public sector so
there's a lot of misunderstanding of how
to make use of data and then and I'm
just thinking about kind of and then the
responsibilities right climate change
and the sustainable development goals
are again a core kind of theme to this
conference so you kind of have this how
do you we talk about transparency how do
we talk about sharing data in a way that
is you know elicits consent from users
of these products and I'm just wondering
what you think kind of as data providers
and users your role might look like
maybe today and then you know Stephanie
fantastic question me and Dave you
mentioned earlier that one of the
reasons why o two is keen to make this
data commercially available was to
empower citizens to make decisions and I
wondered how you yourselves go about the
decisions about which data products to
offer what kind of data to aggregate and
how that fits into the general product
planning I mean obviously the the
products that we offer are largely
controlled about by the type of basis
that we do have I think the
anonymization and aggregation rules also
limit some of the use cases and it kind
of brings us to a place where we're
providing data this population movement
focus that are very macro
level about the the transparency angle
about how important do you think it is
to explain that so it took us quite a
while fraud to get our datasets accepted
into public sector so public things have
lots of policies and rules and processes
about evaluating the datasets that they
use so we've talked about some of the
historic data sets that you use but it's
you know people with clickers by the
side of the road whether its induction
live data whether it's census um and
whilst a lot of that data rows you know
huge weaknesses they're accepted into
public sector because they've been using
them for a number of years when you are
introducing a new technology it's very
important that you're very clear about
the limitations of the data so when we
first started people thought oh you've
got mobile phone data you must have
everything and it isn't quite as simple
as that and obviously we wouldn't be
able to use it on an individual level
anyway so it was about getting across
the message around where our data starts
and stops the use cases that it could be
used for and the data sources that could
be fused with it to complement it to
give the better answer so it's important
to say it all out like that otherwise
it'll probably take you another to two
years longer than it should do and I
think if we look at kind of other
innovative uses of data in the public
sector
TfL for example or right now doing a lot
of work around modeling population flow
through stations using fine grained
Wi-Fi tracking and as part of that
process there was a not insignificant
kind of public awareness campaign
through kind of posters and publicities
explaining like this is the kind of data
we're going to be collecting and and
this is the use cases we're going to
take perhaps I'd I'd like to hear kind
of from both Jamie and David like how
you feel about that kind of in get like
proactive engagements in letting your
kind of potential users know how data
will be used downstream so we in terms
of sort of proactively
or using information to pro
actively reach out an area we are very
focused on is safety and how do we how
you know how do we use that the data we
have to make every single journey safer
and one of the things we've we've been
looking at in the States for example is
if we if we if the data shows that a car
has been with a rider and a driver in it
has been stationary for a certain period
of time and is not in traffic
just we make an outbound contact to
proactively to both rider and driver to
check their alright so so that's an
example where we are trying to sort of
use the data we have to make ride safer
by proactively doing something that that
we can do using using the underlying
data so okay and and Dave how it's kind
of OH - approaching this problem of
educating your mobile subscribers about
the potential downstream uses of this
data I think it's an interesting point
and obviously privacy is very important
obviously we just had gdpr introduced so
I think with the introduction of gdpr
there are less gray areas around what
should and shouldn't be done how data
should or shouldn't be used and for us
personally we're not using any
individual data individual level data is
no personal identifiable information in
there you can't reverse engineer our
data in order to understand where an
individual is at any point but I think
it does open up another interesting
question around keeping citizens
informed because there's lots of talk
around how some of these smart cities
technologies are going to evolve in
order for the assistance to be able to
make money or to get things for their
data there's an interesting project
small cities project a place in Portugal
called Qashqai I think it's Deloitte
working working on where they've created
an incentive scheme for citizens but
they've got an app and they've given all
the citizens in this city it's only
250,000 people a phone and they can
literally go onto the app and say right
it's a pothole in the road there take a
photo of it send it on and they'll get
points they can redeem against public
sector and all sorts of different things
like that so the people's data should
could well become a currency and so for
that reason it's very important that you
let them know exactly what you do
accidentally I think we're just about to
close this this panel probably time for
one final closing remark from each
person I'd love to know what your kind
of hopes and dreams are for the next
couple of years of mobility in urban
environments I'm starting over January
so I think the key thing for me is the
the goal we have of trying to have
helped people replace their private car
with their phone is not going to happen
unless we get deep cooperation across
both the public and private spaces so
this is a big ambition I think we will
all be better off as a result but it's
not going to be done by one company or
one person alone Dave I think when I
look at smart city technologies I don't
see any reason why we can't completely
get rid of congestion within 10 or 20
years and I'd love to see that happen
and every city that we talked to wants
to increase active travel so that's
helping people cycle and walk for most
of their trips so figuring out how to do
that and how to make things like
congestion charges actually effective I
don't know that it's simply replacing a
personal car with an app I think that
that may be one piece of a larger kind
of infrastructure and overall system
design to encourage people to travel
using using cleaner technology really
thanks one round of applause for our
panelists thank you
how are you guys all doing you're
surviving without Wi-Fi yeah all right
we've got one last panel and while the
turnaround is happening Andrew will be
leading that panel and for me I don't
know what you heard about this but sort
of congestion collaboration cycling and
walking yep their hopes for the future
the speakers from this panel will be
leaving and you can obviously go talk to
them but I encourage you to stay for
this last panel and then you can go talk
to all six speakers at the very end it's
also a lunch break from 12 1:45 to 2:30
before the afternoon sessions start in
here so can I get the next group of
panelists to come up here please do you
want to go to the back guys
we're hearing if you go to the back to
get your microphones on yeah just there
through there yeah should we do like a
bit of a a song and dance routine tell
me about Google Maps like all the data
that you guys sit on hold on for size
I'll get your microphone on two minutes
okay all the fun part about the
changeover seeing as there's only one
way in and one way out which is kind of
fun so data and Google Maps yeah data
with what you're doing with deep mind I
mean yeah that's one of the reasons why
I'm so interested in the role of data
and the urban environment is obviously
Google Maps we have the traffic layer
you can turn on a layer in Google Maps
and see how busy the roads are and many
people tell me that is ultimately like
changed their life is cut hours of their
commutes from being able to understand
how busy roads are and when you think
about it the amount of data that you
need to estimate something like the
traffic layer in Google Maps is
relatively small and it's not
particularly identifiable
you just need the average speed of a car
going down one particular Road as you
get more into the details of more
complex urban environments more advanced
infrastructure you start needing more
and more data about people and then so I
think it becomes a very interesting
question about like how do those
decisions happen who gets to decide how
data is used in these these environments
yeah and it was really interesting
listening to the other CDO paddle and
how they consider the use of data and AI
so thank you for that really cool
insight I'm hoping that the panelists
are miked up and ready to go let me just
zip backstage are you guys ready at the
back yeah do you want to come on out
okay
finals final panel so over to you Andrew
and this is about data and services
which I think should be super
fascinating yeah so I would like to
introduce Samar ed and Jennifer to the
stage perhaps the the best way to start
would be a quick once two-minute pitch
of who you are and what are you doing at
COEX on this panel today probably
starting with someone sure thank you so
guys I run a company called Juno which
is a which is an on-demand aggregator
for autorickshaw so small talk talks
three-wheeler taxis which are very
popular in India so it's similar to Ober
and other apps but just a get get it get
it took Tok instead of a taxi and
recently what we have done is we have
actually diversified into our platform
as a service that in the in the way that
people essentially all over the world
are now running their own businesses on
top of the app which is like a big
differentiator from the other apps which
you know are essentially a top-down
approach so so that's that's what we do
and we are hoping to to launch even in
England through this different model and
I'm here to study the market and see how
good or feasible it is to launch
something here and thanks then tell me
about escape so I co-founded Sky
Technologies about three years ago and
essentially we allow devices to
understand where they are and what's
around them using a camera so if you
fast forward to what the world looks
like in five years time we're going to
have augmented reality devices we're
going to have robotics we're going to
have semi autonomous cars and drones and
all of those devices essentially need to
know more about their environment than
ever before and the degree of fidelity
that they need we can't currently
provide with existing technology such as
GPS and compass and whatnot so we
provided a pipeline that allows devices
to recognize their location with an
incredibly high degree of precision
using a camera and we provide a
essentially an API that allows you to
send our system an image and we return
back a very accurate location and
orientation of where that device was
taken and Jennifer from humanizing
autonomy hi humanizing autonomy we
developed a software to understand
behaviors of people and predict their
intent to make autonomous system safer
and more convenient to communicate with
to give you an example today it's
already very good if you know that there
is a pedestrian that this pedestrian is
maybe moving and where this pedestrian
is compared to a vehicle at humanizing
autonomy we go inside that bounding box
and understand if that pedestrian is
distracted by an iPhone for example or
talking to another person and if this
person is about to step onto the road or
not me as a cyclist for example I know
in a split second if this person is
going to cross the road if I need to
slow down or speed up and I can navigate
central London very efficiently and
safely and it's humanizing autonomy with
our software that used computer vision
and behavioral data science
we capture some of that kind of human
superpower that we have today to
integrate in tournament systems isn't so
I'm super interested about the different
kind of types of urban environment these
technologies operate in and kind of how
that affects the development of the ERG
you know we just had Jamie from uber on
the panel
uber have been operating in London and
and had as Jamie's got a difficult year
in kind of dealing with local
governments and the restrictions and
constraints around the what are the
emerging constraints and laws around
operating rideshare services some are
perhaps you could tell me a little bit
better how that has happened in your
expansion of auto rickshaws do you see a
similar thing or is the kind of your
Indian market quite different in terms
of adoption of you technologies sure
so actually you know the market is a
very different when you go to any
developing market so so the biggest
difference is actually that the
regulations are not really clear even
though they're defined but they're not
followed so so for example you know if
you go to India nobody would really
follow a fixed fare right you're just
expected and to haggle every time before
you hail a ride and what it means is
that actually authorities are very Pro
ride-sharing services because customers
are being overcharged by the by the
drivers and the moment somebody steps in
who regulates those issues so
authorities are actually fairly fairly
ok with it and the second thing is we
are not really stepping on somebody's
toes in the in the traditional sense
because the most you know regulatory
issues are created because the taxi
unions are against ride-sharing services
and if you go to India it's a different
story right I mean they're much more
taxi or auto rickshaws than demand so so
people are are pretty okay with this new
technology so in a way it's you can
think of this trend as leapfrogging of a
traditional in taxi infrastructure so
essentially
very difficult to hail a taxi on the
road which is not an app-based taxi
today right and that's that's I think
the biggest difference because in in the
developed world you can actually hail a
cab or a cab
anywhere without an app but in India
actually it's almost impossible to do
that so so it's it's essentially
leapfrogging the traditional
infrastructure creation yeah and another
guy is going to leap frogging
infrastructure i mean we you know
autonomous vehicles has long been the
savior in the tech industry of many
urban problems but then you know
actually deploying on those streets of
team-like relatively slow and yet
actually that technology has huge
potential so perhaps Jennifer can you
speak to a little bit about how some of
the kinds of technology that you're
working on can actually help improve the
safety of existing systems yeah I really
appreciate that question if we think we
have a serial vision that we want to
achieve zero accidents by 2050 might be
wrong to wait for autonomous vehicles
fully autonomous vehicles to to achieve
that and so our some of the ways that
are there so that our software is being
used today for example is as part of
advanced driver assistance systems so to
help drivers today to detect pedestrians
and cyclists in general vulnerable road
users and support them in driving
basically so we've just showcased a
product in Michigan with Ann Arbor
Public Transport Authority where our
software will be part of a bus and
supporting the bus driver
alerting about the inter situations and
another opportunity I think for these
artificial intelligence software's is in
the intelligence transport ecosystem
kind of in the vehicle to infrastructure
communication
so we are working on a project where in
Japan where we want to make crosswalks
safer not only miss vehicle can still
not look around the corner but if we
have this technology and roadside
infrastructure communicating with
pedestrians with drivers and in the
future with autonomous vehicles we can
alert everybody in the surrounding
system about a dangerous situation in
the head that's interesting they're
actually thinking about how that would
physically change the environment rather
than just the software that sits on top
of it and and obviously Escape has done
amazing work in in modeling the world
and I think typically when you see these
high-precision 3d modeling technology
demo videos and like they're typically
autonomous cars driving around suburban
America around Phoenix and you know if
you everybody who's walked around at
this conference the Kings Cross
environment the Kings Cross environments
is a very different style of environment
as a Phoenix you know we there are very
few things that traditionally look like
a road I'm wondering how you being a
london-based company of approach that's
modeling the new kind of urban
environment which is not really he
car-centric
necessarily got it well then just to
illustrate why accurate location is is
so important we've all experienced it
when we've cut the tube station we've
looked down at our phone and our blue
dot is jumping around and it's only
after we've walked halfway down the road
and turned around several times that we
actually know which direction we're
going now for us that's an annoyance but
for a self-driving car or a robot or a
drone that could be catastrophic right
and the reason why that happens is
because of these things called
urban canyons and actually we have them
in London we have them in Manhattan we
have them in big cities around the world
where tall skyscrapers essentially
bounce the GPS signals between them
increasing the inaccuracy of your
location and that's in terms of the GPS
and in for the compass actually the the
steel and metal inside buildings around
is affecting what's called a
magnetometer which is actually in the
device itself which it uses for the
compass so the challenges that we're
faced with for accurate location is
actually amplified in these dense urban
environments where the technology that
we want to exist self-driving cars and
whatnot
are actually most needed now in order to
solve that challenge behind the scenes
of our visual positioning system we've
essentially had to build a large 3d map
from from imagery and inevitably you're
going to have a chicken-and-egg problem
with a visual positioning system because
unless you have built a map of a
particular area you don't have anything
to compare against and when we started
there are only three companies in the
world that had the type of density or
quality of imagery that you need to
build these types of maps and they were
Google TomTom who've been working with
apples to create their maps for several
years and a company called here Maps who
is now owned by a conglomerate of car
companies but essentially none of them
would give that information that date
away freely because it was so valuable
for what they need to build the
foundations for self-driving cars or
mental reality robotics and so on and so
forth so one of the challenges that we
had was we had to overcome that chicken
and egg problem and we did that by
collecting our own data sets of map data
in over 100 cities around the world and
we did that in less than a year with a
fraction of the cost and time that it
would have taken a company like Google
to create the cause of the way that we
structured our data collection and data
processing pipeline everything so I know
that both Jennifer and Samar you touched
on the relationship between technology
and regulation there somewhere you
talked about how actually authorities
were very interested in right heading
technologies because it gives them a
vector to control a market that wasn't
there before and Jennifer you mentioned
about how this technology can be used to
improve safety and obviously
safety gets very close to being a
regulated industry and so I'm really
interested in how your two companies are
approaching those conversations so what
are you thinking about as you enter
conversations with kind of city
governments like how do you balance
their desires against the desires of the
users who are using your service
perhaps not secure so I think there are
two aspects to two regulations right I
mean one is one is of course safety and
and there shouldn't be any when
gardeners cut and we as a company have
to really put safety first right because
even though you know as a market India
is not really focused on safety and I
mean cost is the biggest driver of
product consumption but but at the same
time as a company we have to put safety
first so but other aspect which is which
is kind of odd is that there's a lot of
regulation which is actually designed to
save or safeguard the legacy system
right I mean you talk about taxi systems
or or there's a lot of regulation that
would say that that would try to
safeguard government monopolies like you
know bus systems which are in place
which aren't making money and and the
government still wants to save them for
political reasons and stuff so I think
that is the regulation which which is
tricky to deal with as a start-up
because you know it's fairly illogical
and pretty much everybody knows it but
just that you know because of the the
shift because of that economic force has
to happen is that it's just that nobody
wants to be the bad guy pulling the
trigger so in that case I think you know
startups need to so at least in India
what we do is we combine forces and try
to lobby and and really just you know
reason with people it takes time but
slow and steady we are getting there and
Jennifer how do you how do you see the
salasi that you're working on it's
rising with regulated spaces I feel like
we're at a very interesting point where
we see for example two European
Commission that's just published
an updated vehicle safety and pedestrian
safety regulation where it sees buses
and heavy goods vehicle can have
pedestrian detection and cyclist
detection mechanisms on their car is
mandatory and I think that's I like this
kind of step by step approach to
autonomy and what we are doing with our
project and with our technology I think
fits very well into that step-by-step
approach where you can break it down and
use parts of our software or inter
artificial intelligence to solve issues
like yeah accidents by buses that cost a
lot cost a lot of lives and also kind of
I think when these systems get safer we
can also promote kind of possessive
transport I think and if that's also in
interest of cities that making transport
systems inside the city safer can kind
of support many regulations that cities
are trying to get around so get people
to walk to cycle and also support new
transfer modes so you have I would say
in the future a lot more vulnerable road
users with scooters ebikes and I think
cities will have to kind of take that
onto these step by step regulations for
introducing these new technologies on
vehicles I'm just to support these modes
of transport certainly the the desire to
increase active transport in cities for
health problems is is a huge trend I
think we'll be seeing in the in the
coming years now add obviously your
downstream of a lot of services because
you're building out what I understand to
be a technical positioning platform but
obviously anytime you build out a
technical platform it's got some really
interesting trade-offs there in terms of
for example how do you think about it
restrictions on the use cases that the
platform could be placed upon you know
are you you know
guiding autonomous vehicles seems like a
really good idea but perhaps there are
other use cases you wouldn't necessarily
be comfortable using your service with
and also in terms of kind of correct
coverage what you often see in kind of
new technology products is that they
work perfectly in dense urban
environments like London where you have
ten million people who are a captive
market but then you move outside into
the countryside where perhaps the market
economics don't quite work and then
suddenly you don't have services anymore
so how are you thinking about those yeah
quite right it's it's it's always a
challenge when you're building for a
future that doesn't quite exist yet and
you're having to make predictions over
how that future looks and as I talked
about the the various different
industries
you know we're entering into an era of
something called spatial computing which
is basically the the movement from
computers or devices that we've accessed
behind a 2d rectangular screen to a
device that sits in and lives in the
world around us and that could be
anything from drones robotics autonomy
blah blah blah however all of those
different industries have various
timelines associated with them they have
various distribution opportunities that
you can you can target today and they
have various different safety risks as
well
now we've chosen that out of all of
those industries one of the main
industries that we're targeting is
augmented reality and that's because
there are two billion people with
smartphones sitting in their pockets
that can build the type of
infrastructure will essentially lay the
foundations for everything else that is
is yet to come but yet today there still
is not a a killer application for
augmented reality so we have to work
with the opportunities we have to
partner with other companies who fill
out some of the rest of the ecosystem
and that includes people who are
actually creating products in their own
right where
applications or anything else or handset
manufacturers who are actually getting
this into people's hands in the form of
hardware now you asked about whether
there are use cases of this that you
know we would or would not support we've
tried to make our API or services at
generic as possible but I will obviously
stop at a certain limit when you're
working to put a car on the road and
drive people from A to B safely without
any intervention from a driver you need
to go pretty deep to make sure that that
is working as optimally as it possibly
can for that particular use case in the
same way people you could see
opportunities to use this type of
technology in in warfare for example
being able to identify where someone is
and therefore display where other people
are around them very accurately however
with that example as well you're going
to have to go a pretty long way to
ensure that your generic solution is
optimized for a particular use case and
will take it or ourselves to decide
which of those use cases we want to
proceed with and which we do not so you
at the moment you are making a
case-by-case decision about whether or
not you you allow a particular usage of
that yeah we're working very closely
with any other partners that we that we
work with exactly just thinking one
company meant that you said that both
one of your kind of key target use cases
there is augmented reality and yet you
don't believe there is a killer
application out there for augmented
reality yes do you think do you have an
imagination of what that could could be
what makes you so sure that that is the
the direction to be going so I guess the
the closest thing to a killer
application that we've seen where they
are is of course may I say Pokemon go
and
over the lotta the few days that Pokemon
go has released the public it the market
cap went up by something like 13 billion
and in the first month it generated a
hundred one hundred million dollars it's
now raised or generated over well over
two billion dollars worth of revenue
that is as close as we've got so far but
really what we're talking about is we're
getting augmented reality is all about
getting the graphical user interface
into the real world and removing that
layer of a distraction that we use when
we use our our mobile phones or our
screens now it might be that we are
waiting for a new form of display
technology that will allow us to do that
ie headsets but I do think the work that
people do to uncover the product
innovations are going to happen on the
mobile phone first before transitioning
over to the a our headsets themselves I
think we're about at the end of time for
questions
of this panel I don't want to eat into
people's lunch time anymore especially
since it wasn't raining when we came
down here I just like to end with one
question for the each of you on the
panel which is what are your hopes and
dreams for the next two years and why
you would like to see your field it's
nothing as well so see from from India
perspective I think you know we are we
are actually hoping to be where the
world is already there so so I think
there's a long way to go but at the same
time I think I I think what we really
want to do is make public transport or
mass transport safe in India because if
you look at the ratio of cars that you
know UK or US has you know in terms of
population it's never going to be
possible for India so India if it has to
be you know a proper society it has to
bypass private car ownership and get
into the getting to the shared mobility
as a service era so I think that's where
what we are working towards and in two
years time I think in fact this year's
it's till this time
car sales are down by 17% even though
it's an alarming number for economies
guys but I think it's it's clearly
shifting towards mobility as a service
trend and I think in the next two years
we can really decrease the car ownership
I think that's that's where we are
hoping to be as a company okay if I
might expand the time frame a little bit
before working away we're back I mean
what we're really trying to do is to
fill in the missing piece of
infrastructure that connects devices to
the environment in the same way that the
internet connects them to each other
now over the next two years we're going
to see a huge amount of additional
hardware and distribution opportunities
different form factors of devices that
can actually start to lay their
foundations that will allow that to
happen
whether that is in Apple's a headset
that they're supposedly going to be
releasing or or new vehicles that are
traversing the world capturing that data
and laying those foundations for devices
to come after Jennifer I would hope that
we can we can make these new transfer
the software that goes into future
transport systems as inclusive as
possible and that kind of includes all
different cultures if we think about
where autonomous vehicles are being
tested and where data is being collected
at the moment it does not cover every
part of the world and then also if we
think about all the new transport modes
are kind of sprouting up everywhere I
think it would be important too for
these future transport systems to
include these well to actually make them
make them safe excellent thank you very
much and thank you very much for joining
us thanks everyone
