AI and Water Usage: Do we really need to be worried about it?

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AI is revolutionizing everything from
climate modeling to social media, but

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it's still creating a problem, a new
kind of environmental footprint, let's

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say, that we rarely talk about, and we're
gonna talk about it today about water use.

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What if data centers powering AI
are quietly reshaping the way water

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moves through our world and maybe
even affecting the ocean life itself?

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We're gonna talk about that
on today's episode of the How

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to Protect the Ocean Podcast.

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Let's start the show.

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Hey everybody.

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Welcome back to another exciting episode
of the How to Protect the Ocean Podcast.

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I'm your host, Andrew Lewin.

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This is the podcast where you find out
what's happening with the ocean, how

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you can speak up for the ocean, and what
you can do to live for a better ocean.

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By taking action.

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And on today's episode, we are
going to be talking about AI.

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Now, I have to admit, I am a big
user of artificial intelligence.

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I have an account with ChatGPT
the $20 account a month, and

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I use it to work this podcast.

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I do this podcast by myself.

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I publish three episodes a week.

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I work a full-time job.

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I have kids, I have a family, you
know, that I will like to spend time

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with and I like to enjoy my evenings.

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So instead of spending an hour and
a half or two hours to like do the

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show notes myself and write it out
and go through all the process and

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you know, mark everything, I use AI.

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I use AI to come up with the basic
things based on my transcript, which

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is using AI to get a transcript out.

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And then I publish it.

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I put it up, you know, on YouTube,
on the podcast apps everywhere.

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and it helps me.

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It saves me at least two hours.

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When I do interviews.

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I use AI to edit the interviews,
and that helps me just kind

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of like go through a process.

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It takes me two minutes to edit
an interview instead of, you

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know, it takes me two hours.

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So it saves me a ton of time.

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I do really appreciate it.

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It allows me to create more content
through video and audio like I do on my

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podcast, which I really, really enjoy.

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The other stuff in
writing is not my forte.

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It's not something that I thoroughly
enjoy doing all the time, although

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I like to get my message across.

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I'm starting to enjoy writing
a little bit more as I start

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to journal each and every day.

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There's times where I use AI
to really help me get through

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the process, and it helps.

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However, with that said, I have recently
realized the impact that AI has on water

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usage and why are we talking water usage?

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Well, this is how to protect the ocean.

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We're talking about fresh water.

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We're gonna be talking
about oceans as well.

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And the effect of AI to give you a broad
understanding of the effect of AI on

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water usage and really to set the stage
is, let's be honest, since Open AI came

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out with chat GPT, and even before that,

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it's kind of scaled to a point where I
don't think any of us really predicted.

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Maybe a few of us really predicted, but
I did not predict how big it was gonna

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be part of our lives and how quickly
it was gonna be part of a live, almost

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to the point where it's getting creepy.

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We're getting people who are building

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robots that become girlfriends
or partners to humans.

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So like robots that are partners
with humans, we're seeing that

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happen in front of our eyes.

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It's kind of weird.

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It's kind of creepy, but we're seeing it.

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It's gotten to the level where people
are using it to write their emails.

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People are using it, you
know, as a search engine.

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People use it.

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Like for me, I get my research from
it, not just like, Hey, ChatGPT,

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give me your opinion on this.

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say, pull all of the resources you
can together to get me the research

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that I need, including journal
articles and stuff like that.

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And it's great at doing that.

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Now, when I was researching this episode
and doing AI and water usage, I was a

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little concerned that chat GPT wouldn't
give me the resources that would really

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like talk about the information that I
need in terms of how much water is being

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used per year and all this kind of stuff.

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I actually use Google
and other search engines.

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And other places and looked at
reports to get some of my information.

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and it was pretty much the same.

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So it was pretty good that way.

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I was pretty happy, but it's definitely
weird using AI so much in our lives.

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It's happened so quickly especially
in my life, I use it quite a bit.

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I talk to it when I go through my
strategies of what I want to do next.

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By the way, on YouTube, I've got
my first level of monetization.

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So I can do memberships, I can
do merchandise, which is coming.

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I'm gonna include that on my Patreon
as well for people who don't watch

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this on YouTube and listen, but
the idea is like really this.

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AI is a productivity tool.

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It helps you with productivity to
become more productive in less time,

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which really helps a lot of us.

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But the thing is, is with this boom
and this huge scalability of ai, we

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are seeing data centers being built
all around the world, and these data

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centers are able to handle all the
inquiries that chat, GPT and Microsoft.

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So there's all these different types.

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Copilot is for Microsoft that
we're allowed to use at work.

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And there's all these
other different ones.

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There's Gemini with Google.

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They all have it.

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And every time you make an
inquiry, it uses water and you're

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like, Andrew, how does that work?

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I mean, robots aren't thirsty.

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Computers aren't thirsty.

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They're thirsty in a way though.

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They're thirsty in a way.

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and I'm gonna explain it to you.

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And there's two ways that data centers
that are being built to handle the amount

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of inquiries that are coming through.

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Like we're looking at billions
and billions and billions

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that are coming through.

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What happens is computers will take
those inquiries and they will generate

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an answer and they've gotta do all the
research and all the backend stuff.

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And they've had these servers that are
all situated within these data centers.

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Right?

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And these data centers look like massive
warehouses in certain situations,

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and sometimes smaller, depending on
where they are, let's just picture

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them like a big warehouse, like
almost like an Amazon warehouse.

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And you have all these like servers
in there and they're doing all

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these every time an inquiry is made.

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what's the weather gonna be like?

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Or, you know, help me
write these show notes.

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Or, how many species of bees are there?

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Like, all these different questions,
like, help me do this, help me do that.

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It generates heat every time the
computer is processing, right?

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Because like you've seen laptops and
you've seen computers, and you've seen

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TVs every time you use it for a long time.

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If you feel the fan or the back, there's
fans in there to cool that thing down.

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And so a lot of the times when these
data centers and the computers are

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working, they need to be cooled down
because they're heating up like crazy.

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If they heat up too much,
they'll just shut down.

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So they need to be cooled.

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They use water to cool
that, hence the water usage.

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So a lot of the times right now, from
what I know, and this is very rare,

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where you see where they have recycled
water, but they're actually using a lot

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of potable water, like drinking water.

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like drinking water sources to take
the water from lakes and rivers and

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wherever they can and bring it through
their computer system to cool down the

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data center, right, to cool down the
servers that are working constantly

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and constantly and constantly.

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So now you have that part of it where
they're being cooled and all these

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pipes are running through with cooled
water and it cools everything around it.

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Then you have, how do
these data centers operate?

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They need electricity.

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To get electricity, they need to like heat
water, and they need to like get water in.

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So a lot of times they're
being consumed by the heating

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of water to get that energy.

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So like hydropower and all that kind
of stuff, that's what comes through.

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So they're using that type of
water to power the electricity.

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They're also using fossil fuels.

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Everything like that, which
we'll talk about in a minute.

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But essentially that's what's happening.

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So you have direct cooling and you have
indirect cooling through electricity

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generation for that type of water use.

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So that's essentially what's happening.

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Now, here's the big problem, is they
have to find places to build these things

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across the world, not just in North
America, but across the world, right?

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So where they go, where do you think
they're gonna put these big data centers?

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Are you gonna think they're
gonna put a downtown Toronto

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or downtown New York City?

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No, they may put one or two, but they're
gonna go where the land is cheap.

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They're gonna go where the land
is cheap and where the land is

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cheap usually is not the best area.

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There's not a lot of water already.

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Could be in poorer neighborhoods or
poorer areas like where the people are

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poor, they don't have a lot of resources.

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They're putting it in areas where
there's already water problems anyway.

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Putting in places like Arizona, Uruguay,
places in Africa, all over the place.

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Like Arizona, all those different
places where there's cheap land.

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But also scarcity in water where
people are already having to be

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careful of how much water they use.

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So I think that is the major
problem that we're seeing.

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The amount of data centers that
are being built in these areas

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that are already have water use
problems, they're using more water.

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They need water for them, it's
diverting water from other people.

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They're like people to
actually like drinking water.

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And there's a huge problem there.

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So you have dry areas like Arizona,
Spain, even Alberta, Canada, some

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places in Ontario, excessive
groundwater pumping can cause salt

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water intrusion near the coast.

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So if you take the groundwater away,
which pushes the salt water away

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from the coast along the coastline,
salt water will come through into

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the groundwater where a lot of people
get their drinking water from, right?

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So like coastal aquifers
are, have problems.

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When sea water seeps inland
contaminating the fresh water that can

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be bad for people's drinking water.

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So along those areas are bad.

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Some facilities in arid regions
use desalinization, so like in

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the Middle East and so forth
which creates brine discharges.

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So really high salt water.

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So desalinization plants,
they take in salt water.

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They take out the salt, and they
bring in fresh water, but then they

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gotta get rid of the salt somewhere.

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So they gotta put it back into
the ocean, which causes really

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high salinity in certain areas.

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So they'll have local areas that are
affected on marine ecosystems near shore.

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There's a climate connection here.

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When you use different electrical sources.

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Right now a lot of the electrical sources
are being used are coal, oil, and gas,

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which are fossil fuels, causing more CO2
to be in the atmosphere, warming oceans,

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causing acidification, and then stressing
out corals, which you talked about a

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couple of episodes ago, where we're
already past some of the tipping points.

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All the demand for energy and water
is affecting the energy and water

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and the balance that is nature.

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And because of the amount of use
and the scalability of this, how

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much of a boom this has been, we
are going to start to see impacts.

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The problem is nobody is measuring it.

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The reason why I'm talking about this
in the first place is because I saw

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CBC, like the national news here in
Canada talk about water usage and AI.

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I'm looking at a video.

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I watched this before, the BBC
World Service Channel on YouTube.

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They talked about how thirsty AI is.

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I'm seeing a lot of different channels.

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I'm seeing a lot of different people on
social media talk about water issues,

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which hasn't really been discussed in
a large way because, you know, one, the

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big tech companies that are creating
these AI tools that are helping us

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with productivity and helping companies
and so forth, they don't wanna

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talk about it because it's an issue.

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And we've seen this before in
environmental fields where something

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goes big and it booms and then it
grows so fast that people don't

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wanna talk about the bad stuff.

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Like when crypto came out, the amount
of energy that these data centers for

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crypto to mine, the, cryptocurrency used
up was really bad for the environment,

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actually caused more climate change.

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Like it caused more CO2
and more greenhouse gases

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to go into the atmosphere.

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Right.

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Now.

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Does it mean we can adapt to it?

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No, absolutely not.

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AI is not going anywhere.

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We are going to continue
to use it in the future.

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If not, we are going to use
it even more than we do now.

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00:10:49,116 --> 00:10:53,196
We are just seeing the beginning of
AI, and so there are certain things

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00:10:53,196 --> 00:10:58,416
that we need to do and get done
before all this gets too out of hand.

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00:10:58,716 --> 00:11:01,173
The first thing is we
need to measure water.

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00:11:01,326 --> 00:11:04,776
We need to measure how much water usage
is happening at every single plant.

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00:11:04,776 --> 00:11:07,566
That means regulations
need to go into place.

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00:11:07,566 --> 00:11:09,211
That's what's Gonna happen.

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00:11:09,298 --> 00:11:11,978
We need to start using
recycled and non-potable water.

241
00:11:11,978 --> 00:11:13,298
So non-drinking water for cooling.

242
00:11:13,298 --> 00:11:16,268
So Google and Microsoft are testing
this, which is really great.

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00:11:16,375 --> 00:11:19,165
We need to see liquid immersion
or closed loop cooling.

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00:11:19,165 --> 00:11:22,435
that cuts evaporation losses, because
that's what happens too, when you bring

245
00:11:22,435 --> 00:11:27,213
water into these very high heated areas
like these data centers, you're gonna

246
00:11:27,213 --> 00:11:30,423
get water evaporation so that water
can't be returned to its original source.

247
00:11:30,423 --> 00:11:32,983
There's also geographical
scheduling, so like where the

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00:11:32,983 --> 00:11:34,633
location is is going to matter.

249
00:11:34,633 --> 00:11:37,483
And some of these AI companies, some of
these big tech companies may have to pay

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00:11:37,483 --> 00:11:41,046
more for the land that they do because
there'll be more water available, right?

251
00:11:41,046 --> 00:11:43,026
So like the location really counts.

252
00:11:43,026 --> 00:11:46,446
Location, location, location, it
absolutely counts in this situation.

253
00:11:46,446 --> 00:11:49,446
Stop going to where the land is the
cheapest because that's where the

254
00:11:49,446 --> 00:11:50,766
conflicts are really gonna happen.

255
00:11:50,766 --> 00:11:51,936
'cause people are already suffering.

256
00:11:51,936 --> 00:11:53,016
That's why the land is cheap.

257
00:11:53,016 --> 00:11:54,456
' cause there's probably not enough water.

258
00:11:54,456 --> 00:11:55,896
There's other problems that are at hand.

259
00:11:55,896 --> 00:11:58,956
Could be a poor area where people
are struggling and we don't want to

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00:11:58,956 --> 00:12:02,346
have these data centers causing these
people to struggle even more just by

261
00:12:02,346 --> 00:12:04,776
getting clean water into their houses.

262
00:12:04,776 --> 00:12:05,076
Right.

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00:12:05,076 --> 00:12:05,911
I think that's what it matters.

264
00:12:06,184 --> 00:12:07,078
That's another thing.

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00:12:07,228 --> 00:12:11,278
Renewable energy, obviously integration
to reduce indirect effects on

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00:12:11,278 --> 00:12:13,078
water footprints is really helpful.

267
00:12:13,078 --> 00:12:18,448
Wind, solar, tidal, all these different
types of renewable energy will help

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00:12:18,478 --> 00:12:20,563
cut down any green house gas emissions.

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00:12:20,803 --> 00:12:25,033
We're starting to level up and scale
up on the amount of wind power,

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00:12:25,033 --> 00:12:28,893
solar power, tidal power, renewable
energy sources, which is great.

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00:12:28,979 --> 00:12:32,789
Of course they come with some of their
own issues in terms of get buy-in from

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00:12:32,789 --> 00:12:36,389
certain governments and so forth to
really scale up and really help up.

273
00:12:36,389 --> 00:12:39,899
But we're starting to see increase
in that as well for most governments.

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00:12:39,986 --> 00:12:42,126
The big thing too is
policy and accountability.

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00:12:42,126 --> 00:12:45,756
So mandating public reporting of
water usage effectiveness, which

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00:12:45,756 --> 00:12:50,676
is WUE, integrating water stress
maps into site approval processes.

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00:12:50,676 --> 00:12:54,336
So making sure that when they put in where
they wanna put the data centers, make sure

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00:12:54,336 --> 00:12:55,956
there's enough water for everybody to use.

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00:12:55,956 --> 00:12:56,706
That's a huge thing.

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00:12:56,976 --> 00:13:01,266
Incentivizing any type of zero water or
dry cooling innovations, they're coming.

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00:13:01,266 --> 00:13:02,016
Those things are really happening.

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00:13:03,101 --> 00:13:05,801
I'm gonna link to a video
here the BBC World News.

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00:13:05,801 --> 00:13:07,724
They actually talked about
at the end of their video.

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00:13:07,774 --> 00:13:10,774
And it's very, very new and still in
research, but talking about putting

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00:13:10,774 --> 00:13:14,404
some of the backup data centers in
space because it's gonna be cool up

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00:13:14,404 --> 00:13:15,814
there and they can put it in space.

287
00:13:15,814 --> 00:13:17,284
We're already putting so
many satellites in there.

288
00:13:17,284 --> 00:13:20,614
Whether that's good or not for the space,
I don't know, but at least it takes some

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00:13:20,614 --> 00:13:24,728
of the pressure off the ocean and off
of different water sources around here.

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00:13:24,838 --> 00:13:25,738
Let's be honest.

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00:13:25,968 --> 00:13:28,968
Especially with fresh
water, we are running out.

292
00:13:29,074 --> 00:13:34,114
It's not a dire need at this point,
but later on in life, 50, 60, a hundred

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00:13:34,114 --> 00:13:37,328
years down the road, there is gonna be
a problem with fresh water, especially

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00:13:37,328 --> 00:13:39,248
as water levels are going down.

295
00:13:39,338 --> 00:13:41,888
Evaporation is increasing
due to climate change.

296
00:13:42,343 --> 00:13:46,063
We don't talk about how there could
be a lack of fresh water in the

297
00:13:46,063 --> 00:13:48,973
future, but that's definitely a
thing that we have to worry about.

298
00:13:48,973 --> 00:13:53,199
So ensuring that we can not only cool the
planet to stop that from happening, but

299
00:13:53,199 --> 00:13:57,579
also making sure that these data centers
don't cause extra stress on fresh water

300
00:13:57,579 --> 00:13:59,529
resources is going to be really important.

301
00:13:59,629 --> 00:14:02,449
Now, you know, there's obviously
connection to the ocean.

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00:14:02,566 --> 00:14:07,336
Climate and hydro logic impacts
ripple everywhere around the ocean.

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00:14:07,336 --> 00:14:11,176
So having these data centers more
inland, even if they're inland,

304
00:14:11,176 --> 00:14:12,436
they can still affect the ocean.

305
00:14:12,436 --> 00:14:14,386
Climate change is a huge thing about that.

306
00:14:14,386 --> 00:14:15,286
So indirectly.

307
00:14:15,383 --> 00:14:19,613
Water withdrawals can change river
flows that feed estuaries, which

308
00:14:19,613 --> 00:14:21,413
can be a huge problem as we start to

309
00:14:21,413 --> 00:14:24,383
increase the amount of data centers
that's in there or that are being built,

310
00:14:24,563 --> 00:14:27,983
energy related emissions accelerate
ocean warming and sea level rise.

311
00:14:27,983 --> 00:14:31,463
Of course, desalinization, we talked
about in industrial wastewater,

312
00:14:31,463 --> 00:14:33,899
create localized ocean salinity spikes

313
00:14:33,949 --> 00:14:36,709
When I was a private consultant,
environmental consultant, worked for

314
00:14:36,709 --> 00:14:40,159
companies and we would do a lot of
tests based on regulations that the

315
00:14:40,159 --> 00:14:44,096
government put out, provincial municipal,
as well as federal governments.

316
00:14:44,096 --> 00:14:46,916
When a sugar plant, let's just say
they have discharged, you know, they

317
00:14:46,916 --> 00:14:49,646
got discharged, all their waste,
and it goes through wastewater

318
00:14:49,736 --> 00:14:53,246
and it goes out into, say Lake
Ontario or any of the Great Lakes.

319
00:14:53,546 --> 00:14:55,916
but it's heated water and it
has a lot of nutrients in it.

320
00:14:55,986 --> 00:14:58,006
The big thing in the regulations
that they have to make sure of

321
00:14:58,006 --> 00:15:00,196
an engineers are involved, water
wastewater engineers are involved.

322
00:15:00,406 --> 00:15:03,226
They have to make sure that it
acclimate very quickly and that there's

323
00:15:03,226 --> 00:15:06,239
certain numbers at the end of the
pipe that matter, but the temperature

324
00:15:06,239 --> 00:15:08,329
difference coming out of those factories

325
00:15:08,329 --> 00:15:09,079
is unreal.

326
00:15:09,149 --> 00:15:10,049
It's definitely a difference.

327
00:15:10,049 --> 00:15:13,409
You see like this warm plume
that comes out and you can

328
00:15:13,409 --> 00:15:14,429
measure it through temperature.

329
00:15:14,429 --> 00:15:17,549
We used to do like these maps,
these temperature maps around the

330
00:15:17,549 --> 00:15:21,169
outlet for the outflow of this
water and the sugar water basically.

331
00:15:21,169 --> 00:15:24,319
And you would see how hot it would get
and you see all the fish come in because

332
00:15:24,319 --> 00:15:26,959
it's got a lot of nutrients and there's a
lot of plants that grow there and stuff.

333
00:15:26,959 --> 00:15:28,313
It's really, really interesting.

334
00:15:28,403 --> 00:15:29,663
But it has to be regulated.

335
00:15:29,663 --> 00:15:31,358
And the thing is it's not regulated.

336
00:15:31,358 --> 00:15:36,848
So the policy has to be put in place,
and it's not rare and not surprising to

337
00:15:36,848 --> 00:15:41,558
see a lot of these tech companies be very
cozy, cozy with different governments, not

338
00:15:41,558 --> 00:15:45,098
just the US but other governments because
they're lobbying those governments so that

339
00:15:45,098 --> 00:15:50,154
they can produce as much AI and produce
as many data sensors as possible, right?

340
00:15:50,154 --> 00:15:52,254
This is not a thing that
hasn't happened in the past.

341
00:15:52,254 --> 00:15:55,524
It's not just a tech company
that has provided these types of

342
00:15:55,524 --> 00:15:57,414
innovative lobbying kind of things.

343
00:15:57,564 --> 00:15:59,874
This has been happening in
agriculture and everywhere.

344
00:15:59,964 --> 00:16:01,494
So I think that's an important thing.

345
00:16:01,601 --> 00:16:05,711
So the big thing is, is like what we can
do about it, like the call to action for

346
00:16:05,711 --> 00:16:07,811
you is one advocate for transparency.

347
00:16:07,811 --> 00:16:11,561
So communities should know how much
water the local data centers use.

348
00:16:11,591 --> 00:16:14,171
First of all, do you know if
you have a local data center?

349
00:16:14,786 --> 00:16:16,826
Do you know if there's a data
center either being built or

350
00:16:16,826 --> 00:16:19,886
already built in your area, how
much water is it being used?

351
00:16:20,096 --> 00:16:22,943
Ask your region, your
county, wherever you are.

352
00:16:23,123 --> 00:16:25,853
Ask them why we don't have
that information, why they

353
00:16:25,853 --> 00:16:26,693
don't have that information.

354
00:16:26,693 --> 00:16:28,253
Ask them to mandate that information.

355
00:16:28,283 --> 00:16:30,023
'cause that's important to everybody.

356
00:16:30,203 --> 00:16:32,063
This is gonna affect everybody.

357
00:16:32,196 --> 00:16:33,936
Like I said, AI is not gonna go anywhere.

358
00:16:34,056 --> 00:16:37,836
Support cleaner, tech, you know,
renewables, clean tech, recyclable

359
00:16:37,836 --> 00:16:42,143
non-potable water, but like support
responsible AI companies that report

360
00:16:42,143 --> 00:16:43,613
their full environmental data.

361
00:16:43,613 --> 00:16:46,163
I don't even know what companies do
and don't, I don't even know what

362
00:16:46,163 --> 00:16:47,483
companies build these data centers.

363
00:16:47,513 --> 00:16:50,633
If it's like Google or Meta or open ai.

364
00:16:50,633 --> 00:16:53,379
Are they in charge of it or is it like
a different company that does that,

365
00:16:53,379 --> 00:16:54,639
or different companies that do that.

366
00:16:54,756 --> 00:16:56,646
Educate others on the
hidden water footprint.

367
00:16:56,646 --> 00:16:58,866
Share this video, share the
information that you have.

368
00:16:58,866 --> 00:17:00,786
If you have your own information,
if you know studies that

369
00:17:00,786 --> 00:17:01,843
have been done, share that.

370
00:17:01,946 --> 00:17:04,976
Streaming cloud storage, AI
tools all depend on cooling.

371
00:17:05,089 --> 00:17:07,129
We're using it more and more,
and this is gonna be huge.

372
00:17:07,219 --> 00:17:10,944
And then push companies to include water
metrics in digital infrastructure permit.

373
00:17:11,429 --> 00:17:13,854
We probably didn't even know we had
digital infrastructure permits, but

374
00:17:13,854 --> 00:17:16,764
they do, and we need to make sure
that they are following the law.

375
00:17:16,794 --> 00:17:17,994
This is the big thing.

376
00:17:18,114 --> 00:17:20,304
AI can help us solve ocean problems.

377
00:17:20,424 --> 00:17:22,194
They can help us with productivity.

378
00:17:22,304 --> 00:17:26,324
If we build it and power it
responsibly, we can really have

379
00:17:26,324 --> 00:17:27,824
a great impact on the world.

380
00:17:28,099 --> 00:17:30,029
AI and machine learning
can help overfishing.

381
00:17:30,029 --> 00:17:33,876
It could help with identifying areas
that are feeling the effects more

382
00:17:33,876 --> 00:17:37,686
identify faster ways to reduce climate
impacts, all these types of things.

383
00:17:37,686 --> 00:17:38,496
It could help us.

384
00:17:38,616 --> 00:17:41,616
We need to protect both the
freshwater ecosystem and the oceans

385
00:17:41,616 --> 00:17:45,426
by designing the technology that
respects the planetary limits.

386
00:17:45,446 --> 00:17:46,586
Like it really does.

387
00:17:46,586 --> 00:17:49,346
We are not above and
beyond the planet limits.

388
00:17:49,586 --> 00:17:52,016
If the planet goes, we
go and that's not good.

389
00:17:52,106 --> 00:17:53,853
And the goal is not to stop the AI.

390
00:17:53,939 --> 00:17:55,209
It's not to stop innovation.

391
00:17:55,273 --> 00:17:58,493
It's to make sure that innovation
doesn't come at the ocean's expense

392
00:17:58,493 --> 00:18:00,053
and doesn't come at water expense.

393
00:18:00,233 --> 00:18:01,553
I think that's the big thing to do.

394
00:18:01,553 --> 00:18:06,143
This is not a video to say AI is evil
and everything that's about it's evil.

395
00:18:06,143 --> 00:18:07,913
There's a lot of great
things that can be done.

396
00:18:07,913 --> 00:18:10,816
Obviously there's a dark side to it as
well, but there's a lot of great things

397
00:18:10,816 --> 00:18:12,221
that could be done in your own lives.

398
00:18:12,611 --> 00:18:15,274
As well as other people's
lives and in the ocean's life.

399
00:18:15,371 --> 00:18:19,601
but we just can't let it go without
being regulated for the environment,

400
00:18:19,601 --> 00:18:24,461
because if not, these companies will
not take the ocean limits and take the

401
00:18:24,461 --> 00:18:26,591
health of the ocean and water to heart.

402
00:18:26,591 --> 00:18:27,251
They just won't.

403
00:18:27,251 --> 00:18:28,361
They need to be regulated.

404
00:18:28,361 --> 00:18:31,766
So our governments need to get on
this quickly and do it right now.

405
00:18:31,906 --> 00:18:36,016
Other industries that use a lot of
water, the dominant one, agriculture.

406
00:18:36,371 --> 00:18:39,321
That uses over 70% of global fresh water.

407
00:18:39,468 --> 00:18:43,908
If you look at water usage for AI, it's
like less than 2% at this point globally.

408
00:18:44,011 --> 00:18:47,151
Energy production is huge, about
15%, manufacturing and heavy

409
00:18:47,151 --> 00:18:49,191
industries, about 20% mining.

410
00:18:49,191 --> 00:18:51,651
There's a lot of water usage,
food and beverage processing.

411
00:18:51,651 --> 00:18:54,506
There's a lot of water usage,
construction and materials technology.

412
00:18:55,029 --> 00:18:58,959
Semiconductor manufacturing data
centers, of course, is less than

413
00:18:58,959 --> 00:19:02,559
1% of the total industrial water
used globally, but growing fast.

414
00:19:02,559 --> 00:19:05,379
So we gotta put that in check, make
sure that we're regulating it and

415
00:19:05,379 --> 00:19:06,579
make sure that it's going well.

416
00:19:06,649 --> 00:19:08,359
and I think that's gonna
be really important.

417
00:19:08,359 --> 00:19:09,559
So that's it for today's episode.

418
00:19:09,559 --> 00:19:10,639
I'd love to hear your thoughts on this.

419
00:19:10,639 --> 00:19:13,369
Let me know in the comments
below because I think it's really

420
00:19:13,369 --> 00:19:15,364
important to start this conversation.

421
00:19:15,534 --> 00:19:17,844
if you're watching this on YouTube,
comments below if you're listening

422
00:19:17,844 --> 00:19:19,344
to this on your favorite podcast app.

423
00:19:19,439 --> 00:19:20,699
Let me know how you feel.

424
00:19:20,699 --> 00:19:23,129
DM me on Instagram at
How to Protect the Ocean.

425
00:19:23,129 --> 00:19:27,179
It's at How to Protect the Ocean, or
Go To Speak up for blue.com/contact.

426
00:19:27,179 --> 00:19:27,869
Let me know how you feel.

427
00:19:27,869 --> 00:19:29,609
Just fill out the form,
goes right to my email.

428
00:19:29,789 --> 00:19:32,129
I'll get back to you as soon as I can.

429
00:19:32,309 --> 00:19:34,979
I wanna thank you so much for
joining me on today's episode of the

430
00:19:34,979 --> 00:19:36,179
How to Protect the Ocean Podcast.

431
00:19:36,179 --> 00:19:37,159
I'm your host Andrew Lewin.

432
00:19:37,379 --> 00:19:37,979
Have a great day.

433
00:19:37,979 --> 00:19:39,959
We'll talk to you next
time in Happy Conservation.