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36C3 preroll music
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Herald: Our next speaker is Chris Adams,
and we were talking about reducing carbon
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in the digital realm. How to understand
the environmental impact of the digital
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products you built and take measurable
steps to green your stack. Floor is yours.
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Chris Adams: Cool! applause Hello
everyone. First of all, can you folks hear
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me in the back? Yeah. If you can just
raise your hands. Excellent, cooI! All
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right. Hello everyone. My name is Chris
Adams. As you can see, Mr. Credit, Chris
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Adams on pretty much every online ralley.
Please don't try to follow this link
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because it's not actually gonna go
anywhere yet, but it will be up at the end
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of this talk. I'm just going to introduce
myself. If you don't already know me, my
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name is Chris Adams. I have a background
working in environmental kind of wacky
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startups from Loco2, which was all about
trying to make trains easier to book than
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planes. A.M.E.E, which was all about
putting kind of carbon calculation as an
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API, so you could work out the carbon
footprint of anything. And now I spend a
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bunch of my time working with the Green
Web Foundation, where our mission is to
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basically make the web green. And I also
help organize an online community called
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ClimateAction.tech, which as you can see
is for folk like yourselves who want to
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work out how to do something about climate
in their day job and what they do. I've
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got about 45 minutes with you and this is
a kind of rough outline for the day. I'm
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gonna briefly give you a kind of primer on
how you measure carbon and why you might
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measure that. I'll share with you a mental
model which I found useful for helping
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think about what steps I can actually take
as professional working in this field; and
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then I'll give you some pointers of where
to go next. If you feel compelled to do
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something about, well, what is essentially
an existential challenge and the biggest
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challenge we are already facing. So first
of all, measuring carbon! So, can you just
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show you... raise your hands if you've
seen this before? Yes. The water cycle. So
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you get the idea that we've got like a
water, kind of, evaporates, goes along
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into the sky, then comes down and rains.
And then... generally it's best if it
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doesn't go in one place because that's
that's a good thing. But generally we have
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like cycles in nature and one of them we
have is for water and we also have
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cycles elsewhere. And that's kind of why I
want to share with you here, because there
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are also cycles around carbon. So what
you're seeing here is actually some freeze
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frames of a really, really cool but
somewhat confusing video. And as I was
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saying, kind of carbon works on a kind of
slower timescale that might have here. So,
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this is an... this is basically a diagram
of all the carbon in the world with some
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idea of proportions. All right? So, the
green stuff up here, this is us like we're
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made of carbon. It turns out. So a tree.
Trees are made of carbon. And when living
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things die and decompose, some of the
carbon ends in the atmosphere as we
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decompose. The purple stuff here - this is
like the ocean. Fish are made of carbon,
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too. And so are plants and everything like
that. And when they die, they sink down,
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which is why you've got this massive
chunky like stock of carbon down here.
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Eventually, some of that might become
sediment, then form rock, then end up in
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this kind of black stuff around here,
which we kind of consider that the earth's
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crust. So then at the top, we've got
carbon in the atmosphere. So you really
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can't see it very well. But there is
carbon up here. This is kind of
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atmospheric carbon, really. And there is
like if you watch this video that I've
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linked to, you can see all moving around
as a cycle. But this is kind of wealth
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carbon, really. So now in about 1850, we
started using a lot more energy. And
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to meet that demand of all this energy, we
started burning fossil fuels in earnest as
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well as burning wood for fuel. And you can
see the fossil fuels here as kind of stuff
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that's kind of come out of here and is now
represented here. And we've also taken
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some carbon in the earth and burn some of
that, and like... What is it? Where does
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this all go? There's a clue in these
arrows on the screen. Right? Now if we
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fast forward to 2017, it looks a bit more
like this. You've seen like there's less
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of this red stuff down here because it's
got into here and because it's circulated
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all the way around. We've ended up with
carbon in other parts of Earth. And, in
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particular, you'll see that we have fewer
red dots down here, but we've got a lot
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more around here, which is going to pushed
some of the carbon higher up here. So this
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is kind of... if there's one thing I want
you to kind of really take away is that
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when we talk about climate, it's really
about carbon. And we need as an industry
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to be able to get good at understanding
how to reduce carbon more than anything
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else. If we're going to be thinking about
climate. Now, I'll try and break this down
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to a kind of simple way, which I found
really, really useful for this. There's a
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lady on Twitter. Her name is Professor
Julia Kay Steinberger. She's awesome. She
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has this really nice way. She recently
shared this thread on Twitter where she
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basically explained how she explains kind of
climate change to her children who are 4
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and 7 years old. And she basically did it
this way. She got like a globe, wrapped it
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in some plastic and then said, well, this
is basically what happens. You understand
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the idea of being wrapped up in things
getting warm and things getting too warm.
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That's it. And like, that turned out to be
a really effective way for her to do it.
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And it turned out if kids can get this
stuff, then I think we can. And I think
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it's really, really useful for us to kind
of be aware that carbon is actually a thing
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that we do need to be able to count, and
track and account for in our jobs. So
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we've spoken about this on a planetary
scale, which isn't all that actionable.
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But if we were to kind of bring this down
to organizational scale, where the most of
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us might kind of work and more specific,
it might be easier for us to act upon. It
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might look a little bit like this. There
are established ways to measure carbon
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within an organization you work in and in
the same way that accountants might talk
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about legal ownership of a company. There
are guidelines for talking about who has
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responsibility for emissions when you're
reporting and deciding who should be
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changed, who should be making reductions.
And I'm sure in this diagram here to
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actually take some very, very dull, dry
material into something that we can relate
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to, which is hot beverages and coffee.
And, generally, you can think of it like
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this: if either these three kind of
scopes, there's this idea of scope 1
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emissions, which is basically if I burn
fossil fuels to heat up a, say, container
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so I can have coffee, then that's the
emissions from me burning less fossil
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fuels myself and my scope 1 emissions.
Scope 2 might be me using a kettle. So if
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someone is a burning coal to generate
electricity for me to kind of boil the
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kettle, then that's my scope 2. Now scope
3 might be me walking to a store or into a
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coffee shop and all the emissions and all
of that supply chain - that's my scope 3.
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So there's this idea of kind of like
dependency chain of carbon, which...
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because I'm speaking to a bunch of people
who have some understanding where
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technology I think you should be, kind of,
you should be ready to be comfortable with
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the concept of dependency chains and
things like that. And to make this a bit
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more concrete, I refer to, say, a good
example. So Stripe... Has anyone heard of
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Stripe here? Okay, a few of you. Okay. So,
basically, payments company. All right?
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Now they are actually pretty good about
sharing information about what they do and
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what their emissions are. And you can see
this here. They've basically got... in
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2017, they started making noises about
becoming carbon neutral and they started
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reporting information in these kind of
scopes here. And you'll see this phrase -
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TCO2E, but basically just think of that as
carbon dioxide, the stuff that's warming
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up the world because there's different
gases, but they all have more or less the
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same effect. So in many cases, people will
use the term CO2E2 to describe all of
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these kind of basket of gases. All right?
But you see here that from a scope 1
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emissions are quite small because they're
usually just heating a building. Scope 2
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is a little bit higher, because they pay
to, say, keep a building running. And then
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you'll see down here that there's massive
scope 3, because they tend to pay for a
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lift infrastructure and have a lot of
people flying around as if they're prevent
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a lists??? and so on. All right? Let's
look at some other other examples. Amazon!
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So Amazon repeat started reporting on CO2
emissions for the first time this year.
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And long story short, their carbon
footprint is about the same as the country
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of Finland. Right. Which is kind of large.
And as you can see, because obviously they
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run lots of services, which is why you got
4,5 million tonnes of CO2. They also have
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a lot of warehouses and things like that,
and have a lot of kind of cars or vehicles
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that are getting things around. But
because they actually have a large supply
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chain themselves, they have a massive
honking great scope set of scope 3
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emissions. So let's look at another
company, right. Google. So Google is a
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Google has a surprisingly low emissions
considering scale, about the same as the
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African country of Liberia. All right?
Now, there's something interesting here.
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Google have reported their emissions with
scope 1, 2 that you can see here. And 3,
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but they have this interesting thing here,
where this is the energy they're using.
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But this is the energy they say that
they're using because they are purchasing
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what are basically renewable energy
credits, which is one way of using green
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energy. If you do not have access to green
energy in certain parts of the grid and
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Google are pretty good in this field, but
it's worth bearing that in mind. Google
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are transparent about this stuff, where at
Amazon, you don't see these numbers. So
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this number could be somewhat higher for
we know. All right. So this gives you an
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idea of what some of these numbers might
look like. And then let's look at another
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company, which is also, well I assume you
might have heard of. Is this works? Yes. I
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go to Apple. Yeah. So Apple has... these
are their emissions with just their
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facilities. So just their data centers and
just, say, the offices that they have.
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Right. So this is quite low, by
comparison. Right. So this is carbon
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emissions of maybe Gambia - another
small African country. All right. And
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you'll see once again, by sourcing
renewable energy, they've had a kind of
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quite big reduction in the emissions that
they otherwise wouldn't had. But you'll
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also see that in scope 3, because there's
lots of flying and because there's lots of
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commuting, they have a lovely new office
miles away from anywhere. So you have to
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drive to get there, you know, it's like, I
don't know, 40 percent of the emissions
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were just their facilities. We have to
drive there and back. All right. But if
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you look at the emissions from Apple as
all the products that people buy, you'll
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see that the emissions are somewhat
larger, about the same size as Mongolia,
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which is kind of large. And you will also
see that there is a large... this is a
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breakdown from Apples annual report, and
they basically... they're pretty
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transparent about this stuff and they're
good on this. And they say this is where
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the emissions come from. And you can see
all the way around here, this is the
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manufacturing. The machines they have. And
then if we zoom in to like this bit over
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here. Right. You'll see that there's a
little bit of information there. There's
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like, obviously use phase. But the main
car, the main impact from what they do is
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actually making the electronics. So this
is kind of how we tend to think about a
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carbon and how one might report
on carbon and make it and make decisions
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to reduce carbon. All right. Now, I'm
going to share with you a mental model,
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which I found helpful in this field. I
call it Platform, Packets and Process. And
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it's generally aimed taking something
which is quite abstract to this scope 1, 2
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and 3 thing, to something that you might
act upon inside the teams that you work
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in. And it kind of maps to the kind of
groups that you might be working in if
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you're, say, a frontend developer or a
backend developer, or a designer, or
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product manager. So it kind of tries to
map to that. And as you can see, platform
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might be infrastructure you run; Packets
is infrastructure other folk run, like the
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rest of the Internet; and Process would be
decisions that are made inside your
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organization that cause that to be
emissions. So if you highlight a large
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company and you have a massive, say,
corporate campus which is miles away from
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everyone else has to drive to. Then
there's gonna be a load of emissions from
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that decision that you actually make. So
let's run through this. On the scope 1, 2,
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3 thing I shared with you, this is a kind
of how it maps. And this might look like
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some of the things, some activities you
might have been involved in that will
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create emissions. So, generally, on the
platform side, if you're running
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infrastructure yourself, there'll be scope
2; if it's scope 3 you'll see here and,
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well, I'll go into the other ones in more
detail later. All right. So this is the
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model that I'm sharing with you today. All
right. So let's have a look at Platform:
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infrastructure that you run. There are
kind of three levels, which I'm going to
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share with you today, which might be of
use to you. All right. There are so
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basically Provisioning, Provider and I'm a
bit worried about showing this last one
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because it's kind of new: the other
programing languages. And that's partly
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based on some stuff from yesterday. But
also, I'm a bit worried about kind of
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inciting the pitchfolks when I share this.
But we'll see where we go with this. So
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Provisioning is one level you might
actually have if you build digital
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products and you run servers. All right.
So this chart you see here is a chart from
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the CEO Power of Wireless Cloud Report.
This basically shows how Australia uses
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the Internet and it gives you an idea
that, well, we don't use the Internet in a
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uniform fashion all the time, because
basically if you think about us being set
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at midnight as we tend to fall asleep, we
tend to use Internet less. All right. And
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then as we wake up, we might say kind of
have coffee or something like that, then
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as more of us come to work, we start using
it more. And then later on we work during
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the day, then we'll go home. But you will
start watching Netflix and things. And
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then once again, we fall asleep and then
we get to there. So there is a kind of
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pattern. And if you have any analytics on
how your own tools are using your ad
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services are used, you'll see these kind
of waves and patterns in how it works. And
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this is worth bearing in mind, because
traditionally when we've had to provision
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services to support something like a Web
site or a video streaming service, the way
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that we used to do it was basically buy a
big server that can handle the peak usage.
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And we just accept that. Because
Provisioning is quite a difficult kind of,
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because it's a pain to do. We just leave
this big box idling most of the time in
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the hope that we could actually hit the
surfing at the peak, right. Now the
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downside of that is that, well, if we can
make this conceptual leap that the cloud
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computing is someone else's computer, then
it shouldn't be that much of a leap again,
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to realize that computers run electricity
and we generally burn fossil fuels right
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now to generate electricity. So in the
example we had before, when we had this
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big box that wasn't being used, we would
basically be burning money to pay for
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capacity, we didn't have. But we're also
burning fossil fuels and causing emissions
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one way. Now we've got better kind of
running infrastructure. All right. So
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we've had this kind of trend over the
last, say, 10 to 15 years to abstract
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machines away to make them easier to
manage. So this might be VMs or
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containers, or dinos, or unicorns, or
whatever you might prefer to use. But in
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general, the pattern is make something
more abstract and then make it easier to
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spin it up and down in response to demand.
All right. This is better because we now
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have something looks a bit like this. So
we are not... we're wasting less well,
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we're burning less money, but we're still
burning money. And as a result, we're
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still burning fossil fuels. Now, there's
some new changes in the last few years,
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which are relatively recent, and we're
seeing kind of changes in how we work now,
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which look a lot, look and sound is
sometimes referred to as like service lists
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or functions as a service if you work on
the backend with the servers, right. Now
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here, this is interesting, because we're
rewarded for efficient use of computers,
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because we basically pay on a per request
basis. So if someone tries to load a page,
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we pay for specifically that request. And
then when we're not using it,
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theoretically we're paying for nothing and
theoretically things can spin right down.
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So there's a much clearer mapping between
the usage and what you would pay for here.
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Now, there is a trade off here that is the
number of providers that if you want to
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use tools like this and have this much
tighter mapping is that we end up with a
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small number of people who do provide
this. So if you were to go to, if you want
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to move to something like this, you
generally end up using something like
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either Microsoft Stacks or Google or AWS.
And this kind of presents us with a kind
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of awkward problem right now. If we care
about climate and we care about like
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basically being able to solve problems, as
say professionals, we have to choose two
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of these three things. So we kind of care
about the fossil fuel thing because we're
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in a climate crisis officially now. All
right. Also since I think December, when
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the EU parlament declared this. If you've
used to running any kind of online
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service, you'll be aware that in many
cases there is a kind of shift to
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basically use a hosted thing, because it
turns out that running infrastructure is
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extremely complicated. And in many cases,
if you can buy versus build, then you'll
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often save yourself a lot of hassle. And
the final one thing is, well, avoiding
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oligopolies is quite a good thing, and
because diverse ecosystems are healthy
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ecosystems and we kind of don't really
have so many options right now; if you do
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care about this, it does feel a little bit
like this. And as we saw from just
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yesterday, if you are at this stage, you
saw Gillian Oliver talking about this and
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how much infrastructure you had to run
themselves, in many cases because we
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didn't win it with this consolidation,
where if you want to use one service, you
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have to buy into all these other things
associated with that company. All right.
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So that's one of the trade off you might
have to think about when it comes to, say,
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Platform and Provisioning. Provider is
also another decision that might affect
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it. Now, I didn't mention in the beginning
of this talk that you can basically reduce
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emissions from what you do. If you say a
cloud provide like AWS just by running it
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in a different region. So you can see this
map here. This is by this person who is
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best paid by Amazon to build kind of
sketch naughty things. And this is a list
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of all the data centers and you'll see the
ones with the green leaves, which are
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marked as kind of sustainable regions. And
you see on the right hand side on the east
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coast of America, which is around North
Virginia, which has traditionally been
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coal country - you don't have much in the
green regions there, but on the left hand
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side, where you see a lot of kind of
leaves. And that's because on the west
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coast of America, there's a lot more hydro
and things like that. So, you know,
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with kind of a lower CO2 for each kind of
unit of computer that you're paying for.
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So, yes, you can reduce emissions just by
switching from one region to another
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region. And this is because, basically, to
expand that point I shared with you
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before, where you are in the world... like
the place will affect the carbon intensity
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of the emissions that come from running
infrastructure anywhere. So let's have a
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look at Europe. Right. So France kind of
green full of nukes, right. So that's good
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for some people, maybe less so in Germany.
Right. Germany, which is up here, this is
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the land of solar and coal. Right. So
we're not all that green. England is
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actually got lit up quite a bit better
than it was before. But up here, you can
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see Poland: aww, not so good. Poland is
really, really into coal. And as you can
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see up here in the Nordic states where
there's loads and loads of mountains and
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wind and water, that things are really,
really green. And this gives you an idea
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that you can kind of see where the
emission, the likely emissions might be
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depending on where you're on the world and
that you might make decisions based on
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this. But to have to kind of compare
against this is gonna be quite complicated
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process. So one thing that we do. All
right. The Green Web Foundation, which is
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where I currently work, is we build like a
directory to make it easier for you to
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make that, to do the right thing. And we
present this information as an API and as
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data sets for you to kind of build into
your own tool in which I'll expand a
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little bit later. But one of the key
things is that your provider will actually
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have an impact on who you... basically,
where something is will have an impact on
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emissions from here. There is also... At this point
here I wanna segue a bit into kind of
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energy markets, because when you start
working with computers and if you have to,
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if you're responsible for any service, the
more you think about cloud or how to work
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with cloud, the more you realize how many
parallels there are to energy markets.
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Now energy markets are really interesting
in lots of strange ways, right. So in
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Europe, but actually in lots of places
around the world, you can have cases where
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the cost of electricity is actually
negative rather than positive. So like on
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a day where there's which is really,
really sunny or really, really windy, it's
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actually cheaper for the grid to basically
pay people to basically take energy off
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the grid to keep it stable than it is to
say power down a nuclear power station
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or power down some kind of large coal
fired power station. And then under
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assault, you end up with these scenarios
where you have a negative and you have
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negative cost. And one of the reasons here
is to basically get people to kind of take
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this demand and put it to use in other
places. And I'm sharing this with you
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because it's the kind of the idea like
shifting load might be might be something
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you're aware of as developers or trying to
kind of delay jobs, for example. But you
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see this manifesting now in how we use
energy, but basically things like with
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IV's and things. So this is an example:
Bulb energy in the UK. They will
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basically... if you have a car, they,
basically have time rest now, where
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depending on the time of day or if you're
prepared to kind of provide, be a little
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bit less strict about when you need
something running, then you'll get a
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cheaper electricity. And why am I sharing
this with you? Because I think you start
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to see things like this in the realm of
like computing now. So this is a paper
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that was shared this year, the ICT for
Sustainability (ICT4S), basic conference
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in Lapperate, which I've misspelt. Sorry,
Finnish people. And the general idea is
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that these people started building Kubernetes
Scheduler to basically run a docker container,
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run machines, run workloads where
energy was cheap and green by basically
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tracking where it was sunny really. And
they were able to do this on where they
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end up working with Microsoft to do this,
because Microsoft is one large company
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that has a number of data centers all
around the world. But it kind of sucks
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that there's only one company that you can
actually get this stuff from, or if you
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wanted to do something kind of
cool with, say, a more
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decentralized use of the web that... you
have to kind of go through one large
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company. And if we were to look at say,
well, maybe a more kind of open, green and
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decentralized web or Internet might look
like there is actually some lessons we
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could learn from the energy sector over
the last, say, 10 to 20 years. So Germany,
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one thing that we saw was the Energie-
wende over the last 15 years. And the
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result of that was that we had like cheap
green distributed energy. So that we,
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Germany is interesting in the sense that
it has quite a heterogeneous grid. So
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there's lots and lots of smaller providers
of energy rather than just a handful of
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huge providers. And there's lots of
reasons why having a diverse ecosystem is
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helpful in this, right. And I kind of
wonder like this is one I share with you
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as an idea. What if we'd something like
a digitalwende? Right. What if we could
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do something like this to, kind of,
abstract computing away to the point that
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you can run these in the same way? There
are companies that are now doing stuff
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like this right now. And there's one
company called Helios Exchange that does
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exactly this. But the paper I showed you
before, shows you this stuff around there.
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So this may provide a way away from having
to rely on just basically an oligopoly and
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concentrating more power. If we were to
kind of be prepared to think a bit more
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about how we run computing around. So
final thing is, as this possible way of
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sharing was programing language. So where
appropriate, you can have an impact here
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as well, because different languages have
different goals and that can result in
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reducing emissions from just much more
efficient use of resources. So this is
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Hannes Mehnert yesterday. He was
presenting some work he's been doing on
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MirageOS unikernels. All right. And
whether you probably can't see it. He was
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basically making the point that this is
how he used running this stuff before.
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When he switched to using unikernels, he
saw memory usage and CPU dropped massively
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by just having a kind of better use of the
existing resources. So this was like a 25
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fold decrease in compute use and a 10
times decrease in like RAM usage. And you
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see the same things with other computing,
other languages. And the nice thing is
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this is recorded now so you can see it too
tomorrow. All right. But there's also
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papers that talk all about this stuff. So
depending on what your goals might be,
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there may be certain languages which are
really better kind of optimized for the
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task that you might actually have. Now,
does this mean that I'm saying that we
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should all go out and code everything in
Ocaml, C and Rust? No, that's a really,
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really... we choose languages for a wide
range of reasons from ecosystem to hiring,
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to like developer happiness. And when you
look at a project or a product level,
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you'll see that these kind of micro
optimizations, more than fun, might not be
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the most effective way to achieve some
emissions reductions. But it's still out
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there and it's worth being aware of. And
also, it's worth thinking about if you are
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able to kind of think about the entire
stack of tools you might be using, then
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you're kind of doing something like this
in many cases. If you say use like Redis
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or nginx or something to serve things. So
that's the idea for, like, platform. Now
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let's talk about packets. So this is...
I've spoken of infrastructure you control,
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this is infrastructure you do not control.
All right? Now, you cannot really control
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the other parts of the Internet, and
that's generally considered a good thing.
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But what you can do is control how much
data you send over the wire instead, allright.
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And if we were to kind of look at,
say, the amount of energy we sent over the
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wire and we figured out that both sending
data uses infrastructure, it uses energy,
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which uses fossil fuels. Then we've got
some bad news, like we've seen pages
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growing in size to the point that in
average they... I think the mean web page
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size is now larger than the original
download of Doom. All right. But we're
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also seeing it, because we have mobile
phones, so we use this more. All right.
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And then because cellular network tend to
use more energy to shift the same amount
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of data as, say, wired or Wi-Fi networks,
we have a loss here. So from a kind
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of energy and climate point of view, this
is like the worst scenario we can imagine
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right now. Thankfully, there are this, if
we think about Web page budgets as
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basically carbon budgets, we realize we
have lots of tools that we can repurpose
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for carbon reductions. So one example is
Google's Lighthouse. It basically runs
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checks against your page, then it grades
you on how well your page is optimized. So
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what we've been doing at the Green Web
Foundation is taken Lighthouse, we
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forked it and we made Greenhouse. Which
was basically the same idea, but it kind
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of looks at how many resources you run and
then says, well, yeah, climate emergency
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folks, maybe you don't want to get all
your stuff from fossil fuels. And there's
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some other things far worse than we can
make it, kind of, work out the carbon
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footprint from this, because these numbers
exist, but that's further down the line.
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But you can also see that I'm referring to
the ethical web principles here. If you
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care about this as a professional, this is
something that the creators of the web are
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now saying and giving you license to be
doing. If you do say, look, I don't want
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to do this, there is a moral argument for
doing this. And if I want to build the
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web, as Tim intended, then you can refer
back to these ethical principles now for
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this. But I will need to share with you
that that doesn't mean that we should just
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like reader optimize every single web page
and they'll be fine. Right. It's worth
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getting a sense of perspective around
this. All right. Video like, video just
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dwarfed web traffic. When we think about
designs, we might make like to give you
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some context. This chart is just showing
you an idea of where like usage of
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like data flows. Right. Now, 60 percent of
this basically is just telling us that all
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the video used and streamed is about 300
kind of megatons of CO2. And that was what
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it was in 2018, which is roughly the
carbon footprint of Spain. All right. So
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all the video = Spain, that's kind of
numbers and numbers you might want to look
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at. Now, video on demand like, say,
Netflix and stuff - just like the country
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of Chile. Porn - that's like Austria. All
right. So these are some kind of like
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reference points is for you to kind of
refer to now. All right. And I speak about
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that process now. And like, this is why
it's worth thinking about some other thing.
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This is why I also care about kind of making the
web green, because I think it's going to
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be easier to make the entire Internet
green than it is to stop people watching
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porn, basically, which is a statement, I
suppose. So I spoke a bit about the
388
00:29:28,971 --> 00:29:34,820
process and how there are other things you
can do outside of computers. All right. So
389
00:29:34,820 --> 00:29:38,257
they are obvious. There's two ways I'm
going to show this. So there's kind of
390
00:29:38,257 --> 00:29:41,330
inward looking at process, like the
greening of how we build digital products.
391
00:29:41,330 --> 00:29:44,210
Right. This isn't visible to the end
users, but it's still a useful thing to
392
00:29:44,210 --> 00:29:50,821
do. Now, an example of this is the company
called WHOLEGRAINDigital. I really admire
393
00:29:50,821 --> 00:29:54,650
that. They're really really cool company
doing some good stuff on the web and they
394
00:29:54,650 --> 00:29:58,140
are one of the original kind of WordPress
agencies and they basically say, yes, we
395
00:29:58,140 --> 00:30:01,250
do everything with WordPress and green
energy and they started working at their
396
00:30:01,250 --> 00:30:08,049
own missions and blogging about this. And
what they said was that they know, that
397
00:30:08,049 --> 00:30:11,340
they looked at these figures and they
switched to running on green infra because
398
00:30:11,340 --> 00:30:13,600
that was the kind of right thing for them
to do. But when I started doing that, they
399
00:30:13,600 --> 00:30:17,442
started looking at where else are their
emissions and what they do. And they
400
00:30:17,442 --> 00:30:20,281
basically looked at and some realized
that, oh, wow, a large part of their
401
00:30:20,281 --> 00:30:23,420
emissions just comes from travel. And you
guys, you can see office and home energy.
402
00:30:23,420 --> 00:30:28,996
And of the travel, around 94 percent of
their emissions came from commuting. So
403
00:30:28,996 --> 00:30:32,327
this is why I'm saying that it's more than
just playing around with computers and
404
00:30:32,327 --> 00:30:37,577
optimizing stuff. All right. So this was
kind of useful and this kind of inspired
405
00:30:37,577 --> 00:30:43,380
some of the work agreement foundation for
us to start sharing this. And what we've
406
00:30:43,380 --> 00:30:49,309
been doing recently is basically take this
model and build some, like I guess in VCC,
407
00:30:49,309 --> 00:30:53,370
which is I'm afraid is minimum viable
carbon calculator, not the post-growth,
408
00:30:53,370 --> 00:30:59,410
other kind of acronym there. And we
basically built like a simple spreadsheet
409
00:30:59,410 --> 00:31:03,260
that is very, very fast to fill out. So we
picked two people to kind of get an idea
410
00:31:03,260 --> 00:31:08,100
of, okay. These are the things I'm paying
to run. This is the like if I build a web
411
00:31:08,100 --> 00:31:11,710
project, this is how much data I'm
shifting over time. And then because it
412
00:31:11,710 --> 00:31:16,900
turns out that it uses energy to keep
people warm and dry inside buildings and
413
00:31:16,900 --> 00:31:21,110
people tend to use energy commuting. Then
we tracked it, we tracked that as well.
414
00:31:21,110 --> 00:31:25,700
And we do this to give people some figures
and get some idea of where they might want
415
00:31:25,700 --> 00:31:30,580
to act upon this, because the current ways
that you report on, say, emissions or
416
00:31:30,580 --> 00:31:34,160
think about this is like an annual report
every year. That's a really, really slow
417
00:31:34,160 --> 00:31:39,321
debugging cycle. That means we have like
eight or nine kind of hits of the F5 key
418
00:31:39,321 --> 00:31:44,010
before, like it's a climate apocalypse.
That feels like we should all do a little
419
00:31:44,010 --> 00:31:47,800
better than that. But this is entirely
open, you can link to the template
420
00:31:47,800 --> 00:31:51,820
yourself. And we've we learnt some
interesting things and we did this. We
421
00:31:51,820 --> 00:31:55,790
realized that when we were working on this
because the team were pretty good on
422
00:31:55,790 --> 00:32:00,490
commuting the let them cycle to work. They
were emissions are quite low there. But we
423
00:32:00,490 --> 00:32:05,230
also realized that there was actually an
argument for changing how we design, say,
424
00:32:05,230 --> 00:32:09,370
a Web site. We found that one chunky
background video, you know, those things
425
00:32:09,370 --> 00:32:13,490
that we all hate. Right. That had the same
carbon footprint as basically the entire
426
00:32:13,490 --> 00:32:17,540
team commuting for the entire project. All
right. So it's quite easy to make an
427
00:32:17,540 --> 00:32:23,429
argument to get rid of that and it kind of
meaningful, measurable reduction there. So
428
00:32:23,429 --> 00:32:27,720
these are some of the stuff that we do now
in this. The other thing is an outward
429
00:32:27,720 --> 00:32:32,640
process. So these might be decisions you
make that affect the kind of emissions
430
00:32:32,640 --> 00:32:37,160
through use or for your end users. And
these are gonna be much more visible to
431
00:32:37,160 --> 00:32:42,169
end users. The example I like to refer to,
because I'm a fan of the company. is
432
00:32:42,169 --> 00:32:46,169
Fairphone. You folks have heard a
Fairphone here, right? Yeah. Like they're
433
00:32:46,169 --> 00:32:49,340
basically the canonical Fairtrade smart
smartphone, really. All right. That's the
434
00:32:49,340 --> 00:32:51,960
best way to describe them. And they
also... there's lots of good things about
435
00:32:51,960 --> 00:32:55,590
what they do, but they also share lots of
information about their own carbon
436
00:32:55,590 --> 00:32:59,429
emissions and what steps they're trying to
take to reduce them in a relatively honest
437
00:32:59,429 --> 00:33:02,960
way, which is also really good. And
because they publish it, we can read it.
438
00:33:02,960 --> 00:33:07,640
Now, we've seen trends in electronics over
the last, say, five or six years where we
439
00:33:07,640 --> 00:33:12,299
had modular things and we saw a few failed
attempts at having modular smartphones.
440
00:33:12,299 --> 00:33:16,240
We've been a shift towards like systems on
a chip and stuff like that. So if you are
441
00:33:16,240 --> 00:33:19,910
going to do that, that means in some way
that having a modular design is a
442
00:33:19,910 --> 00:33:25,059
challenge. But it means that if most of
the energy or impact on building
443
00:33:25,059 --> 00:33:29,740
electronics is coming from basically
turning sand into a chip with lots, lots
444
00:33:29,740 --> 00:33:33,820
of energy then we'll need to think about
where we might have a way to decouple this
445
00:33:33,820 --> 00:33:39,190
from the rest of it. All right. To make us
the electronics we do have last longer.
446
00:33:39,190 --> 00:33:44,740
All right. And this is what I found in
there, over LCA life CO2-analysis report,
447
00:33:44,740 --> 00:33:48,730
where they look at the emissions over the
entire process. They... basically the
448
00:33:48,730 --> 00:33:53,480
first thing is their actual use is pretty
small for this. But what you can see here
449
00:33:53,480 --> 00:34:00,320
- the emissions were from the production.
And the thing they decide to do was make
450
00:34:00,320 --> 00:34:06,570
the phone as easy as possible to repair
for end users or replace parts of it. To
451
00:34:06,570 --> 00:34:09,639
make it go from, say, a 5-years project
product to a sort... from a 3-years
452
00:34:09,639 --> 00:34:13,419
product to a 5-years product. And this had
the impact of reducing the emissions by a
453
00:34:13,419 --> 00:34:18,260
measurable figure. And it's a pattern that
we might follow ourselves. All right. Now,
454
00:34:18,260 --> 00:34:21,190
actually. Fairphone and it make a real
feature of this now, they've talked about
455
00:34:21,190 --> 00:34:27,000
this to their, kind of, audience. So they
basically say if you can just say upgrade
456
00:34:27,000 --> 00:34:30,560
just the camera rather than the rest of
the phone, that is still kind of working,
457
00:34:30,560 --> 00:34:33,700
then you can reduce the carbon footprint
over the lifetime by these kind of
458
00:34:33,700 --> 00:34:38,340
figures. And I think this is actually
worth sharing because it hints that there
459
00:34:38,340 --> 00:34:41,580
are options for us to actually be doing
something until we can run everything on
460
00:34:41,580 --> 00:34:46,609
green power, which would affect these
numbers. And I think I've shared with you
461
00:34:46,609 --> 00:34:51,550
like a mental model and see how it can be
activated. I've spoken with you about kind
462
00:34:51,550 --> 00:34:55,639
of carbon. Now I'm just gonna give you
some steps of where to go next. So, okay.
463
00:34:55,639 --> 00:35:01,590
It's 2020. Right. And I kind of feel this
feels like this table stakes. And I'm
464
00:35:01,590 --> 00:35:04,930
really glad that at least one person is
taking photos of this. I'd really like it,
465
00:35:04,930 --> 00:35:09,170
if more of you to take some photos of this
and share with your peers, because I think
466
00:35:09,170 --> 00:35:12,820
the single most effective thing we can use
in community is stuff like this. All
467
00:35:12,820 --> 00:35:15,450
right. We would expect we need to kind of
make this just... we need to change the
468
00:35:15,450 --> 00:35:18,560
static about how we build things. So in
the same way that we would expect a
469
00:35:18,560 --> 00:35:22,420
builder to know about asbestos and we
expect automotive engineers to know about
470
00:35:22,420 --> 00:35:26,060
lead poisoning in particulars. I think as
professionals we need to know about the
471
00:35:26,060 --> 00:35:29,650
impact of carbon and what we do and that
we don't need it to build digital
472
00:35:29,650 --> 00:35:32,990
services. And I think if we can build
electric cars in the automotive center,
473
00:35:32,990 --> 00:35:36,210
then we can build green stacks in
technology. And I think we need this to
474
00:35:36,210 --> 00:35:39,869
become the norm. So this is what I need. I
need your help me to share this with your
475
00:35:39,869 --> 00:35:43,420
boss, with your coworker. Set something
like this. We've had people talk about
476
00:35:43,420 --> 00:35:47,630
just how bad the situation is. And like
this is really like one of the minimum
477
00:35:47,630 --> 00:35:52,950
things we can do. Which doesn't actually
have a massive cost for us, as you do. So
478
00:35:52,950 --> 00:35:56,960
if we do, we need something like a cloud
moonshot to get off fossil fuels. And this
479
00:35:56,960 --> 00:36:01,960
is one thing I really would ask you to
really consider. So asking for this is a
480
00:36:01,960 --> 00:36:06,770
bit easier if you have friends. So I'm in
a group called ClimateAction.tech, where
481
00:36:06,770 --> 00:36:10,609
it's basically just a slack group with a
few other things that we now run from
482
00:36:10,609 --> 00:36:14,180
here, on meet ups. And the idea is that we
do this to kind of share what the
483
00:36:14,180 --> 00:36:18,051
strategies are to actually kind of push
for this kind of stuff, because not
484
00:36:18,051 --> 00:36:22,000
everyone can join Extinction Rebellion.
And I'm not sure that everyone should join
485
00:36:22,000 --> 00:36:27,660
Extinction Rebellion. They used that we
have different aspects of ourselves that
486
00:36:27,660 --> 00:36:33,280
we bring in our work compared to where
else we might work. Now if you are
487
00:36:33,280 --> 00:36:37,950
interested in acting upon any of this. I
work at Agreement Foundation and we
488
00:36:37,950 --> 00:36:41,160
provide, we have like an open source
platform where you can check your stack
489
00:36:41,160 --> 00:36:46,721
and then the tools you have to do this.
And if you are interested about any of
490
00:36:46,721 --> 00:36:50,780
this stuff, we are trying to find a way to
make it easier or to make some of this
491
00:36:50,780 --> 00:36:54,340
much more transparent, because I shared
with you before about how large companies
492
00:36:54,340 --> 00:36:58,730
can basically fudge some of the numbers to
make them look greener than they otherwise
493
00:36:58,730 --> 00:37:03,740
might be. So tomorrow we're running a kind
of on lecture room M2. We're running
494
00:37:03,740 --> 00:37:06,170
something like a workshop to figure out
what some of this might look like in the
495
00:37:06,170 --> 00:37:11,660
same way that we set up robots.txt. So
carbon.txt a way to verify this. There's a
496
00:37:11,660 --> 00:37:15,250
Web site that that's been hastily put
together to give you some idea for this.
497
00:37:15,250 --> 00:37:19,390
And finally, I'm just gonna wrap up now.
Thank you for letting me talk to you about
498
00:37:19,390 --> 00:37:23,590
this stuff here. If you're interested in
getting in touch and talk to me, please do
499
00:37:23,590 --> 00:37:29,010
the Green Web Foundation. I'm Mr. Chris
Adams on Twitter and GitHub. We're asked
500
00:37:29,010 --> 00:37:32,960
to do some training around this because we
realize that although most of us do care,
501
00:37:32,960 --> 00:37:38,600
we don't have much ways to act upon this
kind of stuff. Then finally, if you find
502
00:37:38,600 --> 00:37:41,980
this interesting, there's a newsletter
which I've started with a friend of mine,
503
00:37:41,980 --> 00:37:45,369
Martin, where we're basically sharing what
we learn as we go through it, which bits
504
00:37:45,369 --> 00:37:51,820
are hard, which bits aren't so hard. And
yeah. Thank you everyone!
505
00:37:51,820 --> 00:38:01,890
applause
506
00:38:01,890 --> 00:38:08,380
Herald: Thank you very much. We do have
plenty of time for Q&A. Nonetheless, I
507
00:38:08,380 --> 00:38:13,930
would like the Q&A to be of high quality.
So when you ask a question, it should be a
508
00:38:13,930 --> 00:38:19,060
question. Thanking the speaker is lovely
and nice, but don't waste our collective
509
00:38:19,060 --> 00:38:24,180
bandwidth on that and do that afterwards
on your own. And I don't really care what
510
00:38:24,180 --> 00:38:27,730
your name is or what your affiliation is.
Just ask a question, and make it short and
511
00:38:27,730 --> 00:38:30,340
so on. And the first two questions go to
the Internet.
512
00:38:30,340 --> 00:38:35,840
Signal Angel: You've mentioned the preview
for other workshop, a carbon.txt just now.
513
00:38:35,840 --> 00:38:40,599
Can you already share some strategies how,
for example, the Green Web Foundation and
514
00:38:40,599 --> 00:38:46,110
other sites directories can protect
themselves against being abused by
515
00:38:46,110 --> 00:38:47,870
companies, for example, through
greenwashing.
516
00:38:47,870 --> 00:38:55,460
Chris: So I think... you just need to read
some reports about this kind of stuff. And
517
00:38:55,460 --> 00:38:58,610
get familiar with this. Now, I really
apologize - a large bunch of this was
518
00:38:58,610 --> 00:39:02,329
incredibly dry. There was lots and lots of
dry material around this to, actually,
519
00:39:02,329 --> 00:39:06,700
figure this stuff out. I think it's mainly
a case of working out what numbers you...
520
00:39:06,700 --> 00:39:10,250
what questions you might actually have to
ask. And I can share a link specifically
521
00:39:10,250 --> 00:39:14,350
for the questions that you need to ask.
But generally, I think the four things I
522
00:39:14,350 --> 00:39:19,810
would look for: if the organization hasn't
made a public statement about when they're
523
00:39:19,810 --> 00:39:24,099
going to hit zero emissions; if they're
not sharing their progress on an annual
524
00:39:24,099 --> 00:39:31,760
basis; if they're not sharing how much of
their business they get from basically the
525
00:39:31,760 --> 00:39:36,150
from fossil fuels right now; then how much
of their business is still involved in
526
00:39:36,150 --> 00:39:40,100
extracting fossil fuels from the ground. I
think these are the key things and if
527
00:39:40,100 --> 00:39:42,650
they're not using this kind of scoped
emissions process, which is a clear thing
528
00:39:42,650 --> 00:39:47,780
of finding numbers, those are the biggest
ones. There is a page on that I've got
529
00:39:47,780 --> 00:39:52,310
which lists these questions to ask and
I'll share link to everyone since I get on
530
00:39:52,310 --> 00:39:58,590
the webs to link to this.
Signal Angel: And the second question from
531
00:39:58,590 --> 00:40:03,980
IRC: The numbers that you've mentioned
that the companies themselves publish. Can
532
00:40:03,980 --> 00:40:08,240
you verify them? And if yes, how?
Chris: So the thing that you can... Oh,
533
00:40:08,240 --> 00:40:09,980
that's the thing is - independent
verification is the thing you need to ask
534
00:40:09,980 --> 00:40:12,560
for, it's the final one. So I have just
finally seen where the voice is coming
535
00:40:12,560 --> 00:40:17,340
from. It's like the voice of God speaking.
The independent verification is very
536
00:40:17,340 --> 00:40:24,070
important. All the examples I pointed to,
had independent verification, usually from
537
00:40:24,070 --> 00:40:29,020
a set of companies that do auditing of
this kind of stuff. Now there is again,
538
00:40:29,020 --> 00:40:32,150
there's a firewall of tedium around this
stuff, like that thing where I showed you
539
00:40:32,150 --> 00:40:36,780
with a Google with Google's numbers being
high and low. This is because you need to
540
00:40:36,780 --> 00:40:39,510
kind of go into the minutiae of
understanding market based reporting,
541
00:40:39,510 --> 00:40:42,339
because location based reporting and
there's reporting around this stuff,
542
00:40:42,339 --> 00:40:46,270
there's like lots of academic literature,
but there's just not very accessible to
543
00:40:46,270 --> 00:40:51,650
lots of people right now. They need to be
more of us who do do this stuff. This is
544
00:40:51,650 --> 00:40:54,940
partly one of the reasons we want to have
something like carbon.txt was to basically
545
00:40:54,940 --> 00:40:58,960
give people a chance to see this, but also
linked to the specific documentation
546
00:40:58,960 --> 00:41:03,960
they're referring to. So you can ask.
Okay. So it's nice you've done this. But
547
00:41:03,960 --> 00:41:05,890
whereas this was a third party
verification of this or why is the same
548
00:41:05,890 --> 00:41:10,860
guy called Trevor being basically audited
all of these companies and like literally
549
00:41:10,860 --> 00:41:14,930
it's the same dude who's reported Amazon's
and Apple's. And I'm not sure about
550
00:41:14,930 --> 00:41:19,109
Google. Right. But Trevor is probably a
good guy. But the fact that there is only
551
00:41:19,109 --> 00:41:23,580
one person doing this is kind of...
come on, we know that there are things that
552
00:41:23,580 --> 00:41:28,610
you probably don't want to do in this
field. Also in Europe, at least, if you
553
00:41:28,610 --> 00:41:32,330
want to sell renewable energy, you do need
to register this with the government
554
00:41:32,330 --> 00:41:37,001
registry. And there is something in
there... I didn't really talk about this
555
00:41:37,001 --> 00:41:41,430
in the session. The aim is talk about more
in carbon.txt, how to find this and how to
556
00:41:41,430 --> 00:41:45,820
look this up. Basically, everything we
know about SSL and DNS, you can apply that
557
00:41:45,820 --> 00:41:50,300
to solve this kind of problem without
needing a freaking block chain. All right.
558
00:41:50,300 --> 00:41:53,110
And you can actually find something useful
here, right? Like this data is out there.
559
00:41:53,110 --> 00:41:56,470
It's just the we need to better know the
right questions to ask and make sure that,
560
00:41:56,470 --> 00:41:59,770
well, we are running stuff on a green
stack rather than a brown stack.
561
00:41:59,770 --> 00:42:04,090
Herald: Ok. Microphone number 6, state
your question.
562
00:42:04,090 --> 00:42:08,440
Mic6: Hello and thanks. Very good. Thanks
for your great talk.
563
00:42:08,440 --> 00:42:10,830
Herald: I've said something about thanking
the speaker before.
564
00:42:10,830 --> 00:42:15,349
Mic6: I know. That's why I said it. I
understand you could try to convince
565
00:42:15,349 --> 00:42:20,060
people to reduce their carbon emissions.
Now the managers I have been working under
566
00:42:20,060 --> 00:42:25,710
are generally good in reducing cost. Do
you think it would help to translate
567
00:42:25,710 --> 00:42:31,790
carbon emissions into cost and have this
problem solved by the invisible hand?
568
00:42:31,790 --> 00:42:36,849
Chris: So this is actually the approach
that Amazon use. And for some of the
569
00:42:36,849 --> 00:42:40,840
spreadsheets I've showed you before where
we do not have numbers forecast for
570
00:42:40,840 --> 00:42:45,430
emission, for reported emissions, the best
thing you can go on is going to be sector
571
00:42:45,430 --> 00:42:51,231
level averages for the carbon intensity of
spending a 1000 pounds or 1000 euros in a
572
00:42:51,231 --> 00:42:56,100
particular area. So you might look at it
like that. I kind of feel that there are
573
00:42:56,100 --> 00:43:02,420
certain people who really respond to this
kind of like cost base messaging. But I
574
00:43:02,420 --> 00:43:05,900
think it's more attractive for us to kind
of change the aesthetic around what we do
575
00:43:05,900 --> 00:43:10,400
so rather than us continually striving. I
mean, if we had the narrative for people
576
00:43:10,400 --> 00:43:14,330
for our generation was to basically save
the planet, that feels a much more
577
00:43:14,330 --> 00:43:19,210
attractive thing than using cost. But I
do... I'm aware that if you are in an
578
00:43:19,210 --> 00:43:24,760
organization where the primary driver is
cost, then you need to be able to use that
579
00:43:24,760 --> 00:43:28,300
language. And that's why we've been
speaking about some of that. But there are
580
00:43:28,300 --> 00:43:33,650
lots and lots... there's actually stuff in
this field to show this. There are
581
00:43:33,650 --> 00:43:38,240
organizations that will basically help you
quantify the risks from doing nothing
582
00:43:38,240 --> 00:43:42,500
versus the cost of action. Because in many
cases, when we talk about this, we think
583
00:43:42,500 --> 00:43:47,470
that we often use... you hear the phrase:
"Well, what's it going to cost to shift to
584
00:43:47,470 --> 00:43:52,240
kind of green energy?", for example. But
it's like - what we pretend is there is no
585
00:43:52,240 --> 00:43:56,780
cost to inaction, when it really, really
is. And we've seen just the five years
586
00:43:56,780 --> 00:44:01,160
massive, massive changes in the
destruction of companies and industries
587
00:44:01,160 --> 00:44:07,340
and, well, hundreds and hundreds of lives
as well. So I think that you can use costs
588
00:44:07,340 --> 00:44:11,660
for this, but I think it's a bit reductive
to only use costs.
589
00:44:11,660 --> 00:44:20,290
Herald: Shall be microphone number 2.
Mic2: You in your research, did you
590
00:44:20,290 --> 00:44:25,910
encounter a tradeoff between privacy and
security and carbon neutrality? And if
591
00:44:25,910 --> 00:44:30,740
yes, in which cases?
Chris: Yes. In fact, I used to work at a
592
00:44:30,740 --> 00:44:35,810
company, Amy. One of the key ideas behind
the company was that if you can understand
593
00:44:35,810 --> 00:44:39,270
the company's CO2 emissions, you can
understand the supply chain. And if you
594
00:44:39,270 --> 00:44:43,480
understand the supply chain, then in some
ways you can use it as a kind of cost to
595
00:44:43,480 --> 00:44:47,390
kind of beaten organization to reduce
their prices, because you can see that
596
00:44:47,390 --> 00:44:50,920
they're much more wasteful compared to
other ones. But at the same time, this
597
00:44:50,920 --> 00:44:55,550
is... so that works at an organizational
level. There's also a personal aspect to
598
00:44:55,550 --> 00:45:01,170
this. And I think that this is a field
that in many cases is focusing on
599
00:45:01,170 --> 00:45:06,690
individual action and kind of shaming
people has been proven not to be very,
600
00:45:06,690 --> 00:45:09,440
very effective. But that doesn't mean that
you shouldn't do anything, that there
601
00:45:09,440 --> 00:45:13,930
isn't a cause for individual action,
because I think that provides the cover
602
00:45:13,930 --> 00:45:17,450
for politicians to make the decisions
which will result in kind of real
603
00:45:17,450 --> 00:45:22,090
meaningful changes. So there is a
tradeoff, because in order for you to
604
00:45:22,090 --> 00:45:25,790
understand emissions, because basically
emissions are essentially a proxy for
605
00:45:25,790 --> 00:45:30,950
activity and you will usually see this and
there are plenty of stories around this
606
00:45:30,950 --> 00:45:35,349
and hopefully there might even be a topic
about this specific subject on Republica,
607
00:45:35,349 --> 00:45:40,070
in May. Because, yeah, there is lots of
interesting literature around this
608
00:45:40,070 --> 00:45:44,690
tradeoff that we do actually have to make.
Herald: Microphone number 1.
609
00:45:44,690 --> 00:45:51,430
Mic1: Hi. Can you make an educated guess
on how much emissions could be spared if
610
00:45:51,430 --> 00:45:57,010
like the big providers would follow your
advice?
611
00:45:57,010 --> 00:46:02,860
Chris: So I guess it's tied to the, you
know... I've showed you the numbers of
612
00:46:02,860 --> 00:46:06,840
Google like that different kind of charts.
Right. You could make the list, kind of
613
00:46:06,840 --> 00:46:13,130
like coyork??... just cheat argument. You
say, well, maybe all of it. Right. But I
614
00:46:13,130 --> 00:46:16,910
don't think that's really accurate.
Generally, if we are looking at just the
615
00:46:16,910 --> 00:46:20,220
CO2 emissions from just like running the
Internet, right. I reckon you could
616
00:46:20,220 --> 00:46:30,920
probably wipe out two thirds to 80 percent
of it, what actually depends on where you
617
00:46:30,920 --> 00:46:34,760
might be looking at this, actually. So
more than half comfortably. All right.
618
00:46:34,760 --> 00:46:42,480
Because if you look at, say, data centers,
the main driver there, the main source of
619
00:46:42,480 --> 00:46:46,000
emissions is from them being on 24/7,
continually use like three quarters of the
620
00:46:46,000 --> 00:46:50,119
emissions, assuming that data centers are
full of servers which are used for three
621
00:46:50,119 --> 00:46:54,950
to five years, which is common. I'm not
sure this is the case. Please talk to me
622
00:46:54,950 --> 00:46:57,110
if that's not the case, because I hear
rumors that that might not be the case at
623
00:46:57,110 --> 00:47:01,100
large companies, but no one will write
this down. So until you know that I can't
624
00:47:01,100 --> 00:47:04,890
give you a really educated, a really kind
of better guess than that, but it'll be
625
00:47:04,890 --> 00:47:08,980
lovely to find out if that data exists and
there are lot of hackers who might get to
626
00:47:08,980 --> 00:47:12,980
know about this kind of stuff.
Herald: Microphone number 4.
627
00:47:12,980 --> 00:47:16,620
Mic4: When you talk about moving
computation around the globe, basically
628
00:47:16,620 --> 00:47:20,150
cause to the weather. I wonder if there
isn't a lot of overhead associated with
629
00:47:20,150 --> 00:47:23,390
that, like additional communication. Maybe
if you know, you're far away from a
630
00:47:23,390 --> 00:47:26,380
database, you need rooting hops or
whatsoever. Do you know anything about
631
00:47:26,380 --> 00:47:29,200
that?
Chris: Yes, I spoke to the guy to Alan
632
00:47:29,200 --> 00:47:34,510
James, who was actually working on that.
And I said, hey - what you said, I said,
633
00:47:34,510 --> 00:47:38,859
yeah, we take that into account because we
can work out the emissions from moving a
634
00:47:38,859 --> 00:47:43,980
container of this size to over there. And
in many cases, we might move to the state
635
00:47:43,980 --> 00:47:48,410
that we watch you when a query there as
well. So his approach was to basically
636
00:47:48,410 --> 00:47:53,020
apply various kinds of metadata tags to
the kind of jobs you might want to run to
637
00:47:53,020 --> 00:47:57,690
provide this kind of flexibility. And this
is not new idea like a Mastodon ... is a
638
00:47:57,690 --> 00:48:00,250
kind of data science company that started
doing something like this 10 years ago.
639
00:48:00,250 --> 00:48:06,020
They're kind of the ... Green Cloud
people doing this kind of stuff. And even
640
00:48:06,020 --> 00:48:09,250
before then, there's this phrase called
"chasing the moon". Where was this idea that
641
00:48:09,250 --> 00:48:13,790
you can do this if you run stuff on the
dark side of Earth, which sounds super
642
00:48:13,790 --> 00:48:18,990
metal. Right. There is... this is not a
new concept, really, but it is cool.
643
00:48:18,990 --> 00:48:26,270
Herald: Microphone number five, please.
Mic5: Hi. Do you see any chance of getting
644
00:48:26,270 --> 00:48:29,619
governmental support with this, for
example, like with tax cuts for electronic
645
00:48:29,619 --> 00:48:32,540
cars? I mean, maybe it would be possible
in here, too.
646
00:48:32,540 --> 00:48:37,500
Chris: Yes. I was actually at the EU
Commission Green Public Procurement
647
00:48:37,500 --> 00:48:41,810
workshops. They've been doing for the last
like few months. And I was... there were a
648
00:48:41,810 --> 00:48:44,890
tiny number of people from small
companies. There were lots of large, large
649
00:48:44,890 --> 00:48:48,490
companies who were there saying, yes, they
think you should do is move to our cloud.
650
00:48:48,490 --> 00:48:52,930
That's the clear solution to the climate
crisis. But they actually, it does look
651
00:48:52,930 --> 00:48:59,010
like there is guidance and there is going
to be support in this field. All right. So
652
00:48:59,010 --> 00:49:01,880
I do know there's going to be... well,
we've already seen this like we've seen
653
00:49:01,880 --> 00:49:05,780
the European Parliament declare climate
emergency saying: we need to halve
654
00:49:05,780 --> 00:49:13,170
emissions by 2030. That's around 8%, year
on year for the next 10 years. Now, most
655
00:49:13,170 --> 00:49:17,000
of us don't know what that looks like
because the last time you saw 8% drop in a
656
00:49:17,000 --> 00:49:21,130
single year was the collapse of the Soviet
Union. Which is partly why I'm kind of
657
00:49:21,130 --> 00:49:24,900
sharing stuff like this, because I think
the idea of having a more managed
658
00:49:24,900 --> 00:49:31,050
reduction of emissions feels more kind of
conducive to I guess a kind of
659
00:49:31,050 --> 00:49:36,630
continuities of how we live than the
collapse of the Soviet Union. So I think
660
00:49:36,630 --> 00:49:40,410
there is stuff out there. But in many
cases, we don't have the knowledge right
661
00:49:40,410 --> 00:49:44,380
now as people in the sector to know what
is effective. And this is something that
662
00:49:44,380 --> 00:49:49,430
we need to, as professionals, learn, to
learn where the levers are if we want to
663
00:49:49,430 --> 00:49:55,430
consider ourselves as professionals facing
the scale of the challenge that is ahead
664
00:49:55,430 --> 00:49:59,520
of us.
Herald: Microphone number two, please.
665
00:49:59,520 --> 00:50:04,849
Mic2: Hello. So my question is about you
talked a lot about how much a carbon
666
00:50:04,849 --> 00:50:10,410
emission happens because of running a
server in the server side. But if the
667
00:50:10,410 --> 00:50:13,990
traffic goes really, really high in a real
larger scale, you might have a lots of
668
00:50:13,990 --> 00:50:17,460
emission just because of their
transmitting the package through the
669
00:50:17,460 --> 00:50:25,680
datacenter from and ... and backbones plus
like there carbon emission from rendering
670
00:50:25,680 --> 00:50:30,630
the page in the like formZ and everything
around that. Is there... I was looking for
671
00:50:30,630 --> 00:50:34,960
it for a while, but I couldn't find a
number like saying okay, one TB of traffic
672
00:50:34,960 --> 00:50:40,250
in the data center from United States
going to cause like this much of carbon.
673
00:50:40,250 --> 00:50:44,680
Chris: Yeah. Is that your question? What
is the carbon footprint of a gigabyte of
674
00:50:44,680 --> 00:50:46,830
data or something?
Mic2: I want to have some numbers saying
675
00:50:46,830 --> 00:50:51,030
like which one is like translate traffic
to a number.
676
00:50:51,030 --> 00:50:54,040
Chris: Okay. So there are two
organizations who are doing some work in
677
00:50:54,040 --> 00:50:58,940
this field. In fact, there's a whole kind
of community around greener web
678
00:50:58,940 --> 00:51:04,670
performance where they are tracking this
kind of stuff now. There's a group called
679
00:51:04,670 --> 00:51:07,190
the Shift Project, who I've referenced
before, who talk about the carbon
680
00:51:07,190 --> 00:51:10,920
footprint... the video being the carbon
footprint of Spain. They've actually got
681
00:51:10,920 --> 00:51:13,790
some browser extensions which you can
install into Firefox. I'll give you
682
00:51:13,790 --> 00:51:17,530
numbers as you browse to see this. I've
also put together just like some
683
00:51:17,530 --> 00:51:21,520
interactive notebooks, you can get some
ballpark figures of this kind of stuff
684
00:51:21,520 --> 00:51:24,859
yourself. So very quickly, you can decide,
well, do I do this or do I do something
685
00:51:24,859 --> 00:51:29,970
different. So, yes, look at Green Web
Foundation, there's a link specifically to
686
00:51:29,970 --> 00:51:36,300
a notebook with the numbers for this.
Herald: Next question goes to the
687
00:51:36,300 --> 00:51:38,930
Internet.
Signal Angel: Hey, IRC states that in
688
00:51:38,930 --> 00:51:45,079
their experience, Kubernetes has a quite a
high CPU idle usage, about 40 percent as
689
00:51:45,079 --> 00:51:51,250
mentioned. This mechanism that you showed
to adapt the server usage to the demand.
690
00:51:51,250 --> 00:51:55,099
Does this mitigate against this?
Chris: I don't really know enough about
691
00:51:55,099 --> 00:52:01,870
Kubernetes to give a useful opinion on
Kubernetes. So my thing was like this is
692
00:52:01,870 --> 00:52:08,250
an interesting idea because it's treating
cloud and compute like a utility. And as a
693
00:52:08,250 --> 00:52:13,050
result, we see patterns that we've seen
that have success in other sectors. But
694
00:52:13,050 --> 00:52:15,460
that could be applied to us. I don't know
beyond that, but I can tell you that
695
00:52:15,460 --> 00:52:20,310
there's a lot of well, there's basically
funding going into this kind of stuff now.
696
00:52:20,310 --> 00:52:23,940
But I'm sorry, I don't know much more than
that. But if you do work with Kubernetes,
697
00:52:23,940 --> 00:52:27,190
please you talk to me because I would be
really nice to have a better answer than I
698
00:52:27,190 --> 00:52:32,109
don't know in future.
Herald: Microphone number three.
699
00:52:32,109 --> 00:52:37,119
Mic3: How many talks do I have to attend
here? So that it will have been worth it
700
00:52:37,119 --> 00:52:40,760
traveling here from Munich instead of
watching this online.
701
00:52:40,760 --> 00:52:46,630
Chris: So it depends what... Okay. First
of all, I think coming to a conference,
702
00:52:46,630 --> 00:52:51,030
just because there's talks, that's not the
reason to come to a conference. You come
703
00:52:51,030 --> 00:52:54,100
to a conference to have high quality, high
context conversations with other people
704
00:52:54,100 --> 00:52:57,930
and get something useful from that,
because like you said, you don't need to
705
00:52:57,930 --> 00:53:01,040
do that. That said, the idea of like
having kind of physical community is
706
00:53:01,040 --> 00:53:05,579
actually very, very useful. I think that
there isn't a number, I can't say like
707
00:53:05,579 --> 00:53:10,770
seven because that's going to be
meaningless. But there is a whole issue
708
00:53:10,770 --> 00:53:16,440
around basically the carbon footprint of
traveling to events and in many cases, so
709
00:53:16,440 --> 00:53:21,530
for some context: I was organizing a
conference in London called Helping
710
00:53:21,530 --> 00:53:24,590
Organize your Conference called Map Camp,
and we were trying to internalize the
711
00:53:24,590 --> 00:53:29,109
carbon costs of people traveling, and we
found that some basically a minority of
712
00:53:29,109 --> 00:53:33,640
people coming across the Atlantic Ocean
wiped out, I think, by half the carbon
713
00:53:33,640 --> 00:53:38,030
footprint, the kind of carbon budget for a
600 person conference. So there is some
714
00:53:38,030 --> 00:53:41,780
numbers around that. We've actually hired
a group to give to actually publish some
715
00:53:41,780 --> 00:53:47,300
of this information out there. And there's
a couple of widgets to figure this stuff
716
00:53:47,300 --> 00:53:51,829
out. But if you're here for the talks,
that's one thing. But really, you should
717
00:53:51,829 --> 00:53:56,900
be here to make speak to the other people
and get some kind of meaningful connection
718
00:53:56,900 --> 00:54:01,430
you can have from there.
Herald: Microphone number one.
719
00:54:01,430 --> 00:54:08,890
Mic1: Is this possible to create like an
automated way, a platform or service that
720
00:54:08,890 --> 00:54:14,400
tech companies can connect to and
estimate, like have a rough estimate about
721
00:54:14,400 --> 00:54:19,329
the carbon footprint based on the stack
they use, based on the bandwidth, based on
722
00:54:19,329 --> 00:54:22,740
the, you know, different process
information.
723
00:54:22,740 --> 00:54:28,580
Chris: It depends. This relies on the
organization having access to the matrix
724
00:54:28,580 --> 00:54:33,300
that will go in as an input. So garbage
in, garbage out. Right. So the spreadsheet
725
00:54:33,300 --> 00:54:37,390
I pointed to gives you a very, very low
quality version of doing that. There's
726
00:54:37,390 --> 00:54:42,570
also a tool called AWS Green Cost
Explorer. We've basically forked a diverse
727
00:54:42,570 --> 00:54:47,270
cost. AWS Cost Explorer worked out which
ones, which regions are running on fossil
728
00:54:47,270 --> 00:54:50,380
fuels and then we present that information
back to you so you can get some idea for
729
00:54:50,380 --> 00:54:55,550
this so you can work out these numbers.
But I don't see them right now, largely
730
00:54:55,550 --> 00:55:00,300
because a lot of organizations see this
information is commercially sensitive. So
731
00:55:00,300 --> 00:55:04,140
they don't like to share this. So we have
to go on basically kind of some rough
732
00:55:04,140 --> 00:55:07,580
numbers here. And this is one of the
problems that we do have. And that came up
733
00:55:07,580 --> 00:55:12,000
with the grim public procurement thing was
that we don't have the transparency right
734
00:55:12,000 --> 00:55:17,079
now to make the particular informed
decisions about this. But theoretically,
735
00:55:17,079 --> 00:55:20,700
yes.
Herald: Microphone number five.
736
00:55:20,700 --> 00:55:28,080
Mic5: Hi. I have a question about this
double things that you are doing. On one
737
00:55:28,080 --> 00:55:31,480
side, you have the getting things done
like building sustainable infrastructure.
738
00:55:31,480 --> 00:55:35,900
And in the last days, yesterday, there was
a couple of examples of that. And on the
739
00:55:35,900 --> 00:55:40,280
other side is generate momentum like
convincing people to join the movement and
740
00:55:40,280 --> 00:55:46,099
be more aware of that. So I was wondering,
how does, for example, the Green Web
741
00:55:46,099 --> 00:55:52,501
Foundation apply to that? In the sense
then how radical can you be like, can you
742
00:55:52,501 --> 00:55:59,010
kick out people from your directory
because you think they are not doing green
743
00:55:59,010 --> 00:56:03,369
enough? Or how does this work?
Chris: So I should be clear about the
744
00:56:03,369 --> 00:56:07,400
Green Web Foundation just being a handful
of guys. It's not a big thing at all.
745
00:56:07,400 --> 00:56:12,040
Right. So it's been running for about 10
years. And this is a thing that we have
746
00:56:12,040 --> 00:56:15,790
been doing for the last six months. I
mean, I joined in March and we started
747
00:56:15,790 --> 00:56:20,310
looking through this and we are basically
now, we've been contacting our providers
748
00:56:20,310 --> 00:56:25,390
and say: look, we need you to provide some
more useful and some more rigorous data
749
00:56:25,390 --> 00:56:31,050
evidence to back up your green claims. For
this reason, because you can't...
750
00:56:31,050 --> 00:56:34,611
basically, it's as the stakes are got
higher, it's become more and more
751
00:56:34,611 --> 00:56:38,160
important to actually do this. And if
you're going to base decisions about how
752
00:56:38,160 --> 00:56:43,270
you kind of choose infrastructure from now
on, it makes a lot of sense to do that. So
753
00:56:43,270 --> 00:56:46,900
we are heading in that direction to say,
look, if you can't share this information,
754
00:56:46,900 --> 00:56:52,750
we're going to stop listing you. But we
have given, because we're not so sure
755
00:56:52,750 --> 00:56:58,650
ourselves in this, we we're giving people
a deadline to get this information. So you
756
00:56:58,650 --> 00:57:02,660
probably see some the stats change over
the coming weeks as the way that we do our
757
00:57:02,660 --> 00:57:07,300
reporting changes. But because we released
open data sets around this on a regular
758
00:57:07,300 --> 00:57:12,760
basis, you can actually see this.
Herald: Microphone number two.
759
00:57:12,760 --> 00:57:18,540
Mic2: Hey, have you heard about the
Science Based Targets initiative? And if
760
00:57:18,540 --> 00:57:20,540
yes, what do you think of them?
Chris: So Science Based Targets is
761
00:57:20,540 --> 00:57:26,000
interesting because they are one of the
drivers to basic... So if you're not
762
00:57:26,000 --> 00:57:30,290
familiar what Science Based Targets are:
Science Based Targets are basically a way
763
00:57:30,290 --> 00:57:34,390
to say, well, if you're an organization
and you want to hit net zero, the science
764
00:57:34,390 --> 00:57:39,329
dictates that you need to take these steps
here. I actually think they're better than
765
00:57:39,329 --> 00:57:42,359
nothing in a lot of cases and I think
they're probably one of the more effective
766
00:57:42,359 --> 00:57:47,230
things to use. And they also insist that
you do need to understand emissions in
767
00:57:47,230 --> 00:57:50,950
your supply chain. So I imagine
organizations that sign up to Science
768
00:57:50,950 --> 00:57:55,020
Based Targets will come on pump against
the problems that I've just explained
769
00:57:55,020 --> 00:58:00,020
about, trying to get numbers from the
large companies who tend to be coy about
770
00:58:00,020 --> 00:58:06,450
sharing this stuff. I think it makes total
sense at corporate level. If you're not a
771
00:58:06,450 --> 00:58:12,359
state body. But I feel that the legally
binding targets that are now in place in
772
00:58:12,359 --> 00:58:16,900
the U.K. and we are likely to see in
Europe in the next six months to a year,
773
00:58:16,900 --> 00:58:21,010
would be greater levers, because they
provide a degree of certainty for people
774
00:58:21,010 --> 00:58:25,560
to then justify decisions. Because it's
the law now, rather than being a thing
775
00:58:25,560 --> 00:58:30,730
that you might get unemployed for.
Herald: Question from the Internet.
776
00:58:30,730 --> 00:58:36,090
Signal Angel: You mentioned that video on
the Internet is a large majority of the
777
00:58:36,090 --> 00:58:41,550
energy usage. Can you say something about
how this breaks down to encoding, storage,
778
00:58:41,550 --> 00:58:46,339
transmission and decoding?
Chris: Yes. Those numbers, I understand,
779
00:58:46,339 --> 00:58:50,750
are all about just the transfer. So I
don't think there is much about the
780
00:58:50,750 --> 00:58:53,290
encoding parts on that. That's just
sending.
781
00:58:53,290 --> 00:58:57,710
Signal Angel: And quick follow up: can you
approximately say how much people can save
782
00:58:57,710 --> 00:59:02,970
by, for example, staying on single
definition or SD instead of HD?
783
00:59:02,970 --> 00:59:08,910
Chris: I... was it four times? I don't
know what that the change in resolution
784
00:59:08,910 --> 00:59:13,910
would be and it's not something I feel
comfortable showing numbers on, because I
785
00:59:13,910 --> 00:59:19,040
basically be making up on the spot. I feel
that the solution is telling people to not
786
00:59:19,040 --> 00:59:24,400
do something like this - I think it's
really, really hard ask and seriously,
787
00:59:24,400 --> 00:59:29,240
speeding? Getting off fossil fuels is a
much better way to solve this problem than
788
00:59:29,240 --> 00:59:33,160
telling people they're not allowed to
watch Netflix ever again or only in low
789
00:59:33,160 --> 00:59:38,369
resolution, for example. Like we like
technology because we're like 15000 people
790
00:59:38,369 --> 00:59:41,630
here because we like technology. Telling
everyone you don't get to use technology
791
00:59:41,630 --> 00:59:46,170
anymore is gonna be much, much harder to
sell than just use green power and stop
792
00:59:46,170 --> 00:59:49,980
running fossil fuels.
Herald: Okay. Last question goes to
793
00:59:49,980 --> 00:59:53,369
microphone number one.
Mic1: Hello. I work for a company that...
794
00:59:53,369 --> 00:59:56,790
Herald: I've said something about
affiliations and introductions. Stage your
795
00:59:56,790 --> 01:00:02,200
question? We're pretty much out of time.
Mic1: If a company owns a lot of servers
796
01:00:02,200 --> 01:00:10,470
and the only solution to reduce the carbon
footprint was to switch to green energy,
797
01:00:10,470 --> 01:00:16,760
this would increase the costs for the
energy. And I'm afraid that I don't have
798
01:00:16,760 --> 01:00:25,560
good arguments to go to ask them to switch
to green energy because of the costs.
799
01:00:25,560 --> 01:00:30,630
Chris: Green energy is cheaper than fossil
fuel energy now, like ... so, we've seen
800
01:00:30,630 --> 01:00:34,400
this massive reduction in costs like a
like storage has come down by 85 percent
801
01:00:34,400 --> 01:00:39,110
in the last say 10 years, we've seen a
massive drop in renewables, like this
802
01:00:39,110 --> 01:00:43,710
argument is kind of being solved at that
level there. It's a choice of provider or
803
01:00:43,710 --> 01:00:47,550
something separate. But I think in many
cases it's going to be a case of choosing
804
01:00:47,550 --> 01:00:51,331
who you want to do that. And if you're
trying to make this argument here, you can
805
01:00:51,331 --> 01:00:55,600
make the argument that generally people
tend to want to work in companies that are
806
01:00:55,600 --> 01:00:59,810
not destroying the planet. And if you want
to retain people or attract new people
807
01:00:59,810 --> 01:01:03,960
saying, hi, we're part of the solution,
not the problem is a good way to present
808
01:01:03,960 --> 01:01:08,180
this. And that's why lots of organizations
talk about kind of green credentials
809
01:01:08,180 --> 01:01:11,900
because it's a recruiting tool in the same
way that they talk about open source or
810
01:01:11,900 --> 01:01:15,160
working from home or anything like that,
especially as we get older and have more
811
01:01:15,160 --> 01:01:20,170
kids and then realize that: wow, they'll
be alive when this stuff happens! Okay.
812
01:01:20,170 --> 01:01:23,230
Herald: Thank you so much. We're out of
time.
813
01:01:23,230 --> 01:01:24,230
applause
814
01:01:24,230 --> 01:01:25,230
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01:01:25,230 --> 01:01:54,000
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