CXO Bytes

Host Sanjay Podder speaks with Kerry O’Donnell, a technology and sustainability leader, about how organizations can embed environmental responsibility into digital transformation and AI adoption. Kerry explains why sustainability must be treated as a value driver, how architecture and procurement can enforce greener decisions, and the importance of measuring IT and AI footprints to manage them effectively. They cover practical tactics such as right-sizing AI models, running workloads where clean energy is available, and demanding transparent carbon data from vendors to ensure innovation supports climate goals rather than undermines them.

Learn more about our people:
Sanjay Podder: LinkedIn
Kerry O’Donnell: LinkedIn | Website

Find out more about the GSF:
The Green Software Foundation Website
Sign up to the Green Software Foundation Newsletter

Resources:
The incompatibility of AI and decarbonization [09:12]
The Cloud and the Climate: Navigating AI-Powered Futures [10:30]
Software Carbon Intensity (SCI) Specification [14:31]

If you enjoyed this episode then please either:

Follow, rate, and review on Apple Podcasts
Follow and rate on Spotify
Watch our videos on The Green Software Foundation YouTube Channel!
Connect with us on Twitter, Github and LinkedIn!
Hosted on Acast. See acast.com/privacy for more information.

Host Sanjay Podder speaks with Cooper Elsworth, Google’s lead for AI and cloud emissions insights, about the real energy, carbon, and water footprint of AI systems. They discuss Google’s groundbreaking research on measuring AI’s environmental impact using empirical data rather than estimates, revealing a comprehensive methodology, with Cooper explaining how Google’s full stack approach, spanning hardware, software, data centers, and clean energy procurement, has cut Gemini’s carbon footprint by 44x in a year. The conversation also explores the balance between energy efficiency and water usage, the role of transparent metrics in driving climate action, and how AI can be scaled sustainably without undermining net-zero goals.

Learn more about our people:
Sanjay Podder: LinkedIn
Cooper Elsworth: LinkedIn | Website

Find out more about the GSF:
The Green Software Foundation Website
Sign up to the Green Software Foundation Newsletter

Resources:
Measuring the environmental impact of delivering AI at Google Scale [00:53]
TPUs improved carbon-efficiency of AI workloads by 3x | Google Cloud Blog [01:45]
Measuring the environmental impact of AI inference | Google Cloud Blog [01:52]
Green AI Position Paper | GSF [24:48]
Software Carbon Intensity (SCI) Specification | GSF [28:13]

If you enjoyed this episode then please either:
Follow, rate, and review on Apple Podcasts
Follow and rate on Spotify
Watch our videos on The Green Software Foundation YouTube Channel!
Connect with us on Twitter, Github and LinkedIn!
Hosted on Acast. See acast.com/privacy for more information.

Host Sanjay Podder speaks with Dr. Katia Chaban about uniting IT and sustainability through circular economy practices. Dr. Chaban shares her journey into sustainable IT, the importance of addressing e-waste and embodied carbon, and the growing challenges posed by AI. She highlights how circular thinking, training, and cross-industry collaboration can help CXOs and technology leaders embed sustainability into IT strategies while reducing costs and environmental impact.

Learn more about our people:
Sanjay Podder: LinkedIn
Dr. Katia Chaban: LinkedIn

Find out more about the GSF:
The Green Software Foundation Website
Sign up to the Green Software Foundation Newsletter

Resources:
Software Carbon Intensity specification [11:02]
The Carbon Literacy Project [20:16]
Environment Variables - Real Time Cloud with Adrian Cockcroft [30:34]
Updating the Materiality of Sustainability Management | NTT DATA Group [34:25]
Global Data Centers 2025 Sustainability Report | NTT DATA [40:26]
Green Software Practitioner | GSF [45:56]
Awesome Green Software | GSF [43:54]
The Green Software Foundation Expands Efforts to Incentivize Decarbonization in the Software Industry
NTT DATA Announces First Sustainability Report for its Global Data Centers Division
Global Data Centers 2025 Sustainability Report | NTT DATA
NTT DATA named a Leader by Everest Group in Sustainable IT Services PEAK Matrix® Assessment 2025 report

If you enjoyed this episode then please either:
Follow, rate, and review on Apple Podcasts
Follow and rate on Spotify
Watch our videos on The Green Software Foundation YouTube Channel!
Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Sanjay Podder: Hello and welcome to CXO Bytes, a podcast brought to you by the Green Software Foundation and dedicated to supporting chiefs of information, technology, sustainability, and AI as they aim to shape a sustainable future through green software. We will uncover the strategies and a big green move that's helped drive results for business and for the planet.

I am your host, Sanjay Podder.

Welcome to another episode of CXO Bytes, where we bring you unique insights into the world of sustainable IT from the view of the C-Suite. I am your host, Sanjay Podder. Today's guest, Dr. Katia Chaban. Brings over 30 years of global IT leadership, including with NTT Data, EDS, and many others to our current mission, harnessing technology, business and people so that enterprises, ecosystems, and the planet can thrive.

Katia, welcome. Excited to dive in.

Dr. Katia Chaban: Thank you. I am as excited as well. Appreciate the opportunity.

Sanjay Podder: Katia, can you, introduce yourself? You know what? You have been doing and what got you interested in the field of, you know, uniting sustainability and technology? You know, that will be very interesting to know.

Dr. Katia Chaban: It's actually a funny story because back in 2021, I had been with NTT Data actually, and back in 2020, 2020 I started my doctorate. During the period of COVID I decided. That I needed to do something right other than be upset about what was happening in the world. And so I started my education, so my doctorate in business. And then in 2021, I decided to actually leave corporate world, leave the IT industry and go and focus on school.

And I did that. And as I was trying to research my dissertation, like what is my topic going to be? I mean, it's a big part of that education through your doctorate. I had, I had two choices. I came up with this really interesting concept around acceleration of the digital transformation, right? How do we apply that emergency change behavior from COVID to digital transformations?

But then I also had this idea where I kept seeing this sustainability topic, this ESG topic in all of our strategy courses and all my readings and discussions, and then I came across this thing called the Circular Economy, and I'm like, "what is this thing?"

And so I started doing research about it. And so I then decided that I wasn't gonna do something that I had already been doing for a very long time.

I wanted to restart my brain and focus on something new. And so I did, and I focused on circular economy actually in the consumer goods industry. So not even in IT, but it was with that dissertation, its business impacts, and it turned out to be, you know, planet impacts with the amount of waste that comes from the returns process.

So I graduated, I accelerated that schooling and I graduated and I thought, "yay, I am out of IT! I'm gonna go and work in sustainability and save the world. This is awesome." And then I started talking to people and really building that network, from around the world and got to speak at a conference in Thailand where I got to,

and then, but I started talking to all my IT friends and some folks are like, "Hey, you know, there might be an opportunity for you in sustainability in IT."

I'm like, "what you talking about?" So as an academic now I've started to do the research and I went, oh my goodness, the water, the waste, the emissions, the carbon, what is the rare earth mineral? What is happening? And this, to me, this invisible impact of IT is a massive sustainability, and with the advent of AI and the other, is going to be something that we have to control.

And I said, well, I guess I can't get out of IT. I'm gonna go back to IT but I'm going back to IT with a new lens, a new purpose, and a new focus. And that's really to become that advocate, right, that evangelist, and to really drive the practices that we need to have in order not to be the negative impact to the planet, right?

We really have to maximize all the positive things that IT can do and at the same time minimizing our harm. So I thought I was outta IT after all those years, but now I'm back, but really energized on the topic itself because it really will have a massive impact.

Sanjay Podder: No, absolutely. I agree with you on that. In fact, some of the studies shows that, by 2040, 14% of global greenhouse gas emissions will come from IT. And this data came from a research which is, which predates the rise of generative AI. So we can just imagine how things can be. Before we dive in further, I just wanted to let the audience know that everything we discussed today, will be linked in the show notes below this episode.

So, Katia, you know, you are now focused on sustainability and technology and your background research in the area of circularity, right. You know, that is very interesting. How do you see all of this together? Like what are the big opportunities you see when it comes to, say, circularity in the IT context?

Right. You know, are people missing it? Because most of the time we talk about, for example, carbon emissions. We talk about usage, operational emissions, right? So, but when we talk about circularity, would be very interested, given you have been an expert in this topic, how do you see those opportunities in the IT context?

Dr. Katia Chaban: Yeah, so there's massive opportunities. One, circularity is a way of thinking, right? It's almost a, it's a philosophy and it can be applied to everything. So even when we're talking about software development and the SCI and how we're calculating emissions and what those environmental impacts are, what we're also trying to

teach people is that whole lifecycle develop development of keeping things in use for longer, and how do you develop things that are more modular and can be replaced and repaired versus having to create something in a whole and then get rid of it, right? So that's a philosophy, but where it really comes into play is hardware.

So we look at corporations with massive amounts of end user assets. We look at IT assets, your servers, your network devices. I mean, and the larger the organization, the more these assets are out there. And so from a circularity perspective, it's, for me, the big focus for those assets is something called e-waste diversion, right? And so how do we buy these things? How do we treat these things? How do we, end of life, dispose of these things in a way that we are not contributing to a massive, already massive e-waste problem? A problem that's gonna continue to get worse with AI, right? Because as we're building more data centers, we need more equipment, we need more things to run our AI on, and those things are gonna be end of life very quickly because just of the usage on them, the energy that it's, and where are we gonna put it?

What's gonna happen with those things? And so where circularity is a, is massive. And by the way, circularity then also causes, right, e-waste causes emissions. So it all comes around to emissions and it all comes around to climate change. But we have to look at, you know, very different things.

The other thing in circularity that people don't consider is how do you make these things. And so it's rare earth minerals. It's, we take things from the ground, right? And we use those things to make things, chips and LEDs and all of these things within our electronic devices. And the one thing I tell people, which is interesting to see their reaction is

when you take that stuff out of the earth, it doesn't grow back.

And people are like, "what do you mean it doesn't grow back?"

You know, there's just this preconceived notion that, you know, whatever we take, it's like a, it's like a weed. You pull it out and it comes back and it doesn't. And so the more and more that we are mining, the more and more that we're taking those virgin minerals out, the less and less there is.

And so as we see demand increase for IT assets, because we have this increase in AI infrastructures and our cloud and all these kind of stuff, there's a decrease in availability. So there's cost issues there as well, but there's just availability issues, which should then force the conversation about how do we recycle these components and reuse these components.

And again, going back to that modular design, create our assets in a way that we can easily go in, take the things out that we can reuse and remanufacture, avoid massive carbon emissions, because we're not completely building from new anymore, right? It's 80% of the emissions in a laptop is when you actually make it.

And so avoiding that is avoiding the emissions conversation as well. So circularity is a mindset. Circularity is something we can actually contribute to our IT assets. And we have a massive program that we've just launched right now to meet our circularity metrics around E-waste avoidance and responsible management of those assets.

And by the way, anybody that's in IT knows how hard hardware asset management is, and I've never met an organization that has a perfect asset management in their organization. And so this also is a benefit because we have to be able to manage our assets in order to meet circularity. So there's benefits also in the IT organization that says we're gonna get a better handle on our assets.

We're gonna have a better handle on those costs associated with those assets. We have to manage the life cycles and we have to change the way we buy.

Right, and so just don't buy the new, but start to look at those programs that are being introduced by those OEMs that are actually selling repurposed and remanufactured items.

The interesting part about that is people's mindset, and I saw this in my research too, on circularity, is people don't wanna buy something that's 'used.' Everybody wants something new, right? New cars, new clothes, new this, new that. And so there's a behavioral change and a mindset change that comes along with this that says a laptop that's been remanufactured by an OBM that comes with a guarantee is just as good as the new one, but it's even better because we just avoided all those emissions and we just help achieve our circularity targets by buying in this manner. So it's massive, right? it's a massive impact.

Sanjay Podder: And, you know, that is probably also one of the reason when we defined the Software Carbon Intensity standards, we factored in embodied carbon, right? So, because most of the time people forget embodied carbon, you know, the carbon that goes during the manufacturing of the servers themselves.

And, many a times people don't factor that in when they do procurement of the hardware, for example. Or just extending the life of the assets by a year more, you know, can help you lower your carbon emissions. so I think these are some great points and this is obviously

the other aspect would be end user devices as well, right. You know, there's such a proliferation of end user devices. Normally we only think about the servers in the data centers. you know, but then, that has been like so much of end user devices. Again, there's a lot of embodied carbon. You mentioned about the laptops themselves, you know, 80% of their lifetime emission is doing the manufacturing process.

So, you know, how do you manage that? I think definitely this is a big opportunity for the industry. Now, when we think about some of the recent innovations happening in this space, and you briefly touched upon AI and generative AI. Something that strikes me, how does this whole challenge amplify in the age of generative AI?

Right, because, if I think aloud, we are already looking at new data centers coming up every week, right? If I think about, you know, more and more models getting created, right. You know, and then, the emissions from inferencing are quickly surpassing the emissions because of training those models.

So, wearing your hat of an expert in the field of circularity, has this bothered you? How does the Gen AI world make this problem even more difficult to manage?

Dr. Katia Chaban: So it's funny, I've done a few talks and panel discussions and I always start out with, I say, I hate AI. And I hate AI, it's gonna be, there's gonna be great things, but it's like the center of attention, right, for everything. And so it is so critically important to get our arms around

AI and I look at it in a couple of different lenses. There's the responsible AI, so it's the governance of how we implement and how we manage that. So back to your comments around models. How are we training our models? What modals are we using? And there's a difference between AI that's hosted in the cloud versus on-prem, right?

And you're building your own models versus AI models. And then when you're in the cloud, it's the token usage, the input token usage, output. How do you put thresholds on those things? How do you force certain use cases to use certain models? 'Cause you don't need the big choppy GPT-5 model. You can use a mini model to be able to get, so there's that responsible AI layer. Then there's the sustainable AI part of it, right? That starts to say you have to put in metrics to be able to measure the emissions associated with that. So if you're in a cloud environment, Azure or Google, and you're building your Azure platforms or your AI platforms, measure that, what does that mean?

And you have to measure the models. You have to measure the throughputs, the outputs, all of those different types of things. And then you have to wrap in tech innovations that help to mitigate the harm associated with it. So yesterday we had a fascinating conversation on quantization, right? So the, how, what they're doing, and I won't even pretend to get into what those details, but it's how do you minimize

the impacts from those models that you're training? And then, you know, then we're looking at things like innovation that helps with improved prompting, right. Because that's the big issue is people put in their prompts. People are like, please and thank you to AI. Right? So you have all this great but they're, people aren't good at good specificity, right? They're never gonna get their first answer on the first try. And so what you're trying to do is build those types of prompting where you're caching things and you're able to provide better responses, but you're also doing better prompting.

So there's all those things. And then there's the ethical AI component, and then there's the inclusivity AI, right? To make sure that everybody gets access to it. Because if we continue to keep building AI and only we get access to it, right, we continue to build that digital divide, which is not good.

And so there's all those aspects. So when I say I hate AI, it's because it is moving, it's the fastest moving tech that I've seen in my career. Probably that you've seen, right. And just the adoption of it and it's almost like we're just running in second place all the time, try and get arms around what's happening. And nevermind the security challenges.

I was at a security conference last week and they were talking about some of the security issues related to AI, which was frightening alone. So they talked about, you know, how it's learning on its own and it's gonna make its own decisions and all those types of things. So we talked about, what is it, Odyssey 2001 movie where Hal can't get control of his robot.

And I bring the perspective of those old movies that say, well, I'm a Mad Max, right? So now we're running around on a planet that doesn't have any water, doesn't have any wildlife, doesn't have any of that, and that could possibly happen too, unless we can catch up, take a breath and make sure that we, wrap that AI or really put a lot of people on it to get that governance in place.

So, it's massive. So when we talk about circularity, yeah, how do we manage the infrastructure that is being built to support it in a manner, how do we ensure that it's more modular? All of those things, right? And then, how do we use software to, and AI, to manage how we're doing all those types of things?

So not only do you have an issue with climate and whatnot using AI, but we also wanna use AI to manage our AI. And so how do you do that in a way that you just not continually harming things, but you're actually, you know, mitigating the bad by doing the good. And we have to do that through that circular thinking, especially on the replenishment of those infrastructures. And then again, the coding, right? Optimization. How do we optimize every prompt, every query, and all the models in such a fashion that we are, we don't have to use as much energy, that we know causes an emissions issue.

Sanjay Podder: Well, great points. And that actually takes me to the next question because traditionally, software engineering did not involve all this disciplines, right. So sustainability was by far not a NFR, non-functional requirement. Security was, but sustainability never, right. And now that we are seeing that sustainability is an NFR, it's an important one,

direct bearing on climate impact on energy use. And another important thing, the cost of IT. Because, you talked about circularity, you can really reduce the cost of, you know, procuring devices by delaying the devices you're currently using, you are using them more. So what we are really looking at is rewiring our talents our software engineering talent, our IT workforce to think differently and enabling them with skills,

so that they can build systems that are not only functional, but also sustainable at the same time. In your opinion, from the vantage point you sit in for the last few decades, how easy is that? You know, how do you really, because most of the time we think it's about, okay, let me give some training to some software engineers.

It's not as that, as simple as that. So, for large enterprises like the ones you are leading, how do you see this transformation or change happen? Any insights from your own experience?

Dr. Katia Chaban: So you have to hit it from multiple sides, right? Training is absolutely essential, but it has to be meaningful training. I'm happy. Our organization, we just, we've just launched what we call carbon literacy training. We've partnered with an organization, the Carbon Literacy Project, and we've created training that's focused on digital and tech sector, and it includes our NTT strategies and goals.

And it's intensive. It's e-learning training and it's workshop, and so it's eight hours of somebody's already-busy life, to talk specifically about climate change, emissions, what is GHG? What is methane gas as well? All the science around these things and then how it impacts your daily lives individually, the choices that you make individually,

but then from a digital and tech sector, what those impacts are. What is the impacts of AI? What is the impacts of circularity? What is the impacts of these things? And so, the workshop is then intended to really have deeper conversations so when people have their learning, they walk away, really, it's been, now they've taken away at least one or two things that's associated with not only their individual carbon footprint and potentially how they can reduce that, but what they can do in the role that they do, whether a software developer, whether a service desk agent, whether a field engineer, supporting all those end user devices, whether they're an architect, take away those couple things that say, this is what I can do in my job to be able to make a difference, so that training has to be impactful. The other thing that has to happen is you have to include it in your governance. And from an IT perspective is it's right from the ideation, so I have a great idea, I have an innovation, or our business partner or a client has some innovative ideas.

And so right at that point, you need to start asking those sustainability guardrail questions. Does this entail the use of hardware? If it does, what would you think about what you would do with that hardware? Is this software development? Okay. If it's software development, we start to throw in things like how would you measure SCI, but on all through the lifestyle.

So you go through ideation and then you go through checkpoints where there's approvals of project. You go through your ARB types of processes, right, with your architects that have to be also trained and aware that say, alright, we're gonna design these solutions, but how do we do it that it's low code, lower minimal infrastructure, that it's more modular, it's all these types of things, right?

If it's, if it does have assets, what is that end of life plan? Are we gonna purchase them in a way where we don't have to do the disposal? We're not responsible for that, right? And so, we have to govern that, and there has to be metrics associated with, with how that's governed. So really including the criteria and the mechanisms to ensure that technology innovation throughout the life cycle is environmentally, is socially and economically sustainable,

for the client and for the corporation. So you have the training level, and then you've got that lifecycle level where you have to, and then you've gotta have the, I'm monitoring and measuring you, right? So then you have to have the dashboards and the visibility into all of these things.

What are my circularity practices? What are emissions practices with our strategic application portfolio? What is the emissions associated with our cloud footprint, with our on-prem footprint? All those types of things. And then they all, link back. And by the way, not have an organization that's somebody's monitoring those dashboards and giving people,

like, you know, here you have to do something. My approach is those dashboards are being created by the people that have to manage those every day. So they start to learn about what these things are. So I'll give you an example. It was super, yesterday was a really exciting day for me because I've got a cloud team that I'm working with and they're, you know, always ", right? FinOps, go save money, optimize right size, do all the right things.

And we've been working with a partner to take a look at what our emissions data is within the Azure environment. And we have now built that dashboard. We thought this was super important, but it's the team that's doing this.

It's not Katia and some folks over here. It's the team that's building a dashboard that can align costs with carbon down at the resource level. And they said to me yesterday, like what we've learned is not a one-to-one ratio between cost and carbon. And I'm like, "yes, no, it's not."

You know, it isn't. And there's water associated with, so we're looking at water.

So now we're not only are they looking at the, Hey, there's a right sizing opportunity where we can save money and carbon and water, but they're also saying, Hey, there's opportunities where we can save carbon and water. It might only save $12 and 72 cents, but I think this is the right decision to reduce our carbon footprint.

But it's them, it's that operational group that you're instilling that thinking into and that ownership and that accountability into, to do that. So you've gotta train 'em, you've gotta put it throughout the life cycle, but you have to integrate it into how people are doing their work.

And you have to do that by engaging them, talking to them, and educating them.

Sanjay Podder: Absolutely. And what makes it very interesting, Katia, in my experience, has been, this has been an emerging area, so to a great extent, you know, most practitioners were not aware, as you rightly mentioned, you need to train them. There have been, there has been no standards, that you know you can use to measure, because you can only start reducing once you measure and know where you are, your baselining,

right? And that's where I found that, you know, all this in cross-industry collaborations are helping. What has been your own experience with cross-industry collaboration and the emergence of new standards, like we mentioned, SCI and the role in accelerating this journey. What have you observed?

Dr. Katia Chaban: Do you know what's super exciting about sustainability in IT, is the amount of collaboration and the amount of people that are embracing the topic, but are also willing to share. And I say that because

there has been a long time where we don't wanna give away our secrets, right? There's been a long time where you minimize the amount of discussion and collaboration,

'cause you don't wanna, to your competitors, give away the secret sauce or to your suppliers, you're trying to hide some cards so you can negotiate better. With sustainability, we are all driving towards the same goal. And so the openness in discussion and collaboration with others in my industry on how they're doing things is amazing.

And in fact, as a member of the SustainableIT.org organization, I got involved with them very early on this journey, and there's a taxonomy that was created based on Nicholas's, you know, book and kind of that momentum, but that taxonomy is a nice framework to be able to start with, right? It's got the energy types of metrics, the emissions metrics, social metrics, governance metrics, and of course, included in there is a lot of focus on your sustainable sourcing, right?

How you're buying things and how you're monitoring that. And so for me, having that framework and having be able to just have those discussions with people across the industry, across the world about the use of that framework and what they're doing has, it just helps me, right? And I would do the same.

Anybody that wants to call and say, I've got a problem. How do you integrate this? Or how do you do this? Very open. I'm not afraid of giving away any secret sauce because we are all on a giant mission with the same end goal, right? And that is to reduce the impact of climate change.

And so for me that's super cool.

And then internally, what I'm finding is even though everybody is already busy, we have incredible leaders that support this, but people are embracing it almost at a pace where I can't keep up with providing them the information and the things that they need to know because it feels so, it makes their job much more purposeful now, the same as the way I feel about the role.

So the cross collaboration is great. Now, where it's not great, is in the supply chain. And as you know, even when you're trying to calculate the SCI metrics, right, we're trying to look at emissions metrics, there's a vast amount of data that we need to get to that specificity and that validity of those numbers.

And we can't get that. And so for me that that collaboration and that transparency, and it's the one thing, you know, you see on, in discussions and forums is the Microsofts of the worlds, the OpenAIs of the world, all, they have to be much more transparent with what they're using and where they're using it to help us really understand what the impacts are.

And so I, you know. That's an, that's a tough nut to crack, and I'm not sure if that's something that you've come across and you maybe have any guidance, but while we as leaders are on that goal and we can share and collaborate, we don't have that same level of transparency within our supply chain.

Sanjay Podder: You're absolutely right. That's a challenge everybody's grappling with. But in fact, we did a podcast with Adrian Cockcroft on Real Time Carbon Calculation or Carbon Accounting, because every hyperscaler tends to give you data of different granularity and different frequency, so it gets very difficult to compare apples and oranges, you know, it's, very difficult. And also, as you rightly said, some of the closed LlM models, you don't really know much. You know, I was very happy to see Mistral coming up with some of the data recently. But all that does impede our ability to understand where we stand today,

in terms of emissions. We have to then, you know, go around trying to use other ways of, you know, guesstimating what the emissions, the proxies, what the emissions could be. And hopefully all these things will resolve as, you know, sustainability becomes a key consideration in the way we use AI.

People would love to use AI which is more environmental friendly. Earlier in the discussion you did mention fit for purpose, you know, maybe a smaller model. You don't need to use the largest of the models for every purpose. So there will be a need for the model providers to be more transparent around the emission numbers on training and inferencing. I did see, read Sam Altman's blog on the emissions so that he has, without giving much of a context, he has revealed a few numbers, which I hope is the tip of the iceberg, and we get to see a lot more what's happening, you know, in the closed LLM space.

Katia, you kind of pointed to a very important fact, and it is the journey of adoption of sustainable IT, right? You know, we have these wonderful ecosystems, you know, SustainableIT.org, Green Software Foundation, everybody coming up with the collective wisdom of, the members and making it available for everybody to use and aspirate the journey.

Also emergence of new standards. The taxonomy you mentioned. GSF has been coming up with a lot of standards, like last year we released the ISO standard for Software Carbon Intensity. We are right now working on the SCI for AI. Hopefully that becomes another useful standard. There are a lot of open source tools that one can use as well.

Now, looking at the whole community of CIOs, you know, CTOs, CIOs, large organization, medium organization, you know, if they have to start on this journey, what would be your advice to them? Where do they start? You know, how, what is the smartest way to make progress? You know, any thoughts there?

Dr. Katia Chaban: Yeah, I, well, I have a lot of thoughts on there. So it's funny, I had a conversation with a CIO organization that were starting on the journey and they're like, just give us a couple of easy things to start with. And I said, well, okay, but if it was really easy then, you know, everybody would be doing it.

But let's think about, let's think about this more impactfully. So I'll share the journey or my thinking on this. And this is what I would tell everybody, right? You, it's like any strategy that you're gonna implement, you have to understand what you want to accomplish. What are your goals? What are the visions?

What are the missions? What, are the things that you actually wanna do? And then, you've gotta figure out where you are, right. So how far away that gaps analysis are you from that vision? So, when I started in this role, you know, I knew what my mission was and you said it in the introduction, right?

It's harnessing that power of people and technology so that we're doing good things for our business, the planet and the people. But I didn't know where we were. And we're talking about a global organization across 50 different countries, 152,000 employees worldwide. And what do we do? And so we did

an assessment like anybody does, right, from an IT perspective to take a look at multiple capabilities from that sustainable IT lens within the organization. And this was something that we did through, our SustainableIT.org front. So we were looking at what is the awareness and commitment of the organization?

What is the strategy from an IT perspective? What are the roles, what are the resources that you have in the organization? What are the, what is the level of skills and training related to sustainability? what kind of change management do you have? What kind of procurement practices do you have? And so on and so forth.

Right? So there's a number of capabilities and I talked to the CIOs across all the regions and their EAs, and we got ourselves a score very similar to like an SDLC score, one to five in a maturity. We rated ourselves where we thought we were and then we also said where we wanted to be and that was a great starting point.

Then I surveyed my organization. So all the employees about their awareness, their understanding, do they know what sustainability is? Do they know what sustainable IT was? Right? And would they be interested in training? So now I've got it from my leaders and where they think we are from a capabilities and where they wanna go.

And now another data point from the organization itself across different countries and across different roles about their awareness and even our awareness of our actual sustainability strategy, which we have. And so that also then gave me all right, here's where we are, here's where we are, and here's where we need to go.

And that was all the input that I needed from a strategy perspective. Then you gotta get visibility, right? And so, what is our footprint with some things? What are we doing with the circular, with circularity? what are these things that are important, right? So now I've said I want to have us be able to measure carbon emissions.

We've gotta, we improve all the capabilities to get there, but what visibility do we have? And for me at that time, I wasn't looking for perfection in the numbers like I wanna get to with an SCI type of number on everything where I can use that in an auditable finance or a sustainable report, right?

For me, it was just get me some numbers. Now, it wasn't the dashboards that were provided by, you know, hyperscalers and whatnot. It was a little bit more scientific than that. And luckily we have Gadhu as part of our organization who also is from GSF, so we got good guidance on how do we calculate a variety of things. And so understanding what that just looked like as we get smarter, I could have spun my wheels on perfection and how we're measuring things or

I could have just started to get visibility and get people engaged in understanding what these numbers meant. So we're going through a massive transformation, let's say in Office 365, and we're reducing a number of the tenants that we have. Well, that should be a massive data improvement, and that should be a massive emissions improvement.

We wanna monitor that. So I didn't wanna wait a year to find the best tool and implement and be all, but we created something together very quickly so that team could then set a target for themselves, for our missions for this year and, and move, and move forward, right.

And so my advice would be,

know what your vision is. Know where you are in your capabilities and the maturity of your organization. Know your people and what they think too, right. Because you, your perspective as a CIO or a CSO may be a little different than somebody that's on the ground. So get that perspective. And then figure out what you wanna do and don't wait for perfection.

'Cause that's, that can be the evil, right? So start to take a look at where are your big environments, so for us, it's cloud and a lot of our apps are in cloud. It's end user devices. It's, you know, these areas where you want to go and get that visibility and perfect that visibility as you go. But without visibility, you can't start making any impacts.

And so do that, but, back to that training and awareness, that one pillar that I talked about with our carbon literacy training for the organization, that was based on the feedback that I got from the employees. I can put visibility, we can create dashboards, we can put reports together all we want, but if the people that are doing that work every day don't understand why we're doing it,

and how they're involved in doing that, it's not gonna work. And so your people have to understand. And so it's that employee engagement and awareness and training in however it is. So it sounds like a lot, but when you start to put your strategy together, right, that's an important pillar.

But don't wait for perfection.

Sanjay Podder: Cannot agree more. Yeah. No, those are great points. How do people keep track of all the good work you're doing in this space? Is there some website they can go to? What is the best resource?

Dr. Katia Chaban: You know, right now I think we just do celebrations on LinkedIn, when we have some good things, we'll celebrate that way. And hopefully what we'll see start to see at the end of the year, because we'll have a full year, is we will provide a kind of that impact report specifically in the global IT organization within NTT.

And hopefully we'll see a lot of great impact and we can share that again with my peers and colleagues across my SustainableIT.org and those that are interested and we'll be creating, for me, it's a playbook, right? I have to have a playbook that I can pass on to my successor and whatnot that says, here's how we did the things.

Here's how we're measuring these things. Here's why things. So it's almost that to do, that we'll also be able to share across the community.

Sanjay Podder: Wonderful. If you have any question for me.

Dr. Katia Chaban: I think, you know, back to what you said at the beginning, you and I talked about the podcast and I'm a, I've been finding that very similar to your experience, you just talk to people and they don't understand the impact of hitting enter and what that does from an energy and emissions perspective.

And sometimes people just really get engaged. So I often think about should I do a podcast? And would people really care about what that would be? And so I guess my question for you is, what's the best way to get to that larger, there's millions of people out there that are in the IT industry,

How do we get to them all so we can start making sure that they all understand what those impacts are?

Sanjay Podder: Right. I think, I mean, not able to tell you what is the best way, but I can share with you what we have tried to do, to achieve that objective. The very first thing we did, Katia, when we started the foundation. The foundation itself was in that direction, right? Like we felt that, you know, no single organization can solve a problem of this scale.

We have to come together. So we need to form a consortium of like-minded people, and the GSF was formed that it has been ever since doing very well. So that was step number one. Step number two is, you mentioned about the need to make people aware our sustainability, because software engineers never knew what is greenhouse gas emission and how is it linked to that work.

So the very first thing that the GSF did, was released the Principles of Green Software training, which became a huge success for many of the CIOs who have come to the podcast. They did confide to me saying "Sanjay, when I personally took the training, I was so happy that I learned so many things in such a short period of time that I mandated everybody in my leadership team to go through it because it was an eye-opener," right?

So, as I say, it comes from the top. So the whole focus has been, we have to empower the developers, the practitioners, but we also want to make the leadership aware so that the mandate comes from the top, because otherwise this is not going to be sustainable. There has been a lot of Green Software Foundation Summits we have done around the world.

And many of the people who come and participate, they're not even a GSF member, but the whole idea is to come, collaborate, learn, and take it back. Right? So those are some of the things we have been creating, for example, Awesome Tools list, which is a collection of some of the open source tools and best of the tools that people can come and start using it.

Similarly, standards, right? We believe that by creating this collective intelligence, we can influence a collective action about this whole area. So that is, that I believe is very effective so far. Is this the best way possible? I do not know. The podcast is also a part of that journey, where, you know, people will learn from experts like you, right?

You know, from many experts who are coming. You know, I was just, this is our annual year, for the CXO Bites, and I was compiling, what did I learn from each of the leaders? It was mind boggling. You know, I should write a book on it now, saying, you know, what are the insights? You know, otherwise you won't get that any one source.

So I think, those are some of the ways we are trying to accelerate this journey. And the outcome has been very positive, very encouraging, and I hope we can collectively achieve newer heights. So, yeah. Katia, it was so wonderful having you, and thanks for sharing all your insights from circularity to how you're driving it in your organization.

You know, like all good things have to come to an end, you know, we are now coming to the end of our podcast episode. And I want to say thank you for, coming over and sharing your deep insights to CXO Bytes, from entire Green Software Foundation. Thank you so much, Katia.

Dr. Katia Chaban: Thank you for having me. I really appreciate it.

Sanjay Podder: Thank you so much. That's all for the episodes of CXO Bytes. All the resources for this episode. In the show description below and you can visit Podcast.GreenSoftware.Foundation to listen to more episodes of CXO Bytes. See you all in the next episode. Bye for now.

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In this episode of CXO Bytes, host Sanjay Podder speaks with Marc Zegveld, Managing Director of ICT at TNO, about the competitive value of green IT. Drawing on the recent Green IT Value Case, real-world case studies, and research, they explore how sustainability initiatives can enhance business performance—from cost savings and supply chain clarity to talent attraction and regulatory preparedness. Marc emphasizes that green IT is not just a climate imperative but a strategic differentiator, requiring top-down leadership, grassroots innovation, and effective change management. Together, they discuss how businesses can embed sustainability across operations to thrive in a tech-driven, low-carbon future.

Learn more about our people:
Sanjay Podder: LinkedIn
Marc Zegveld: LinkedIn | Website

Find out more about the GSF:
The Green Software Foundation Website
Sign up to the Green Software Foundation Newsletter

Resources:
The Green IT Value Case | TNO [05:57]
Awesome Green Software | GSF [23:26]
Software Carbon Intensity (SCI) Specification | GSF [23:39]

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TRANSCRIPT BELOW:

Sanjay Podder: Hello and welcome to CXO Bytes, a podcast brought to you by the Green Software Foundation and dedicated to supporting chiefs of information, technology, sustainability, and AI as they aim to shape a sustainable future through green software. We will uncover the strategies and a big green move that's helped drive results for business and for the planet.

I am your host, Sanjay Podder.

Marc Zegveld: Hi, Sanjay. Thanks for inviting me on this, on this podcast. I'm really happy to join. I think it's very important and relevant topic what we discussed. My background is, I'm now a two year Managing Director of the Unit Strategy, Policy, ICT at TNO. We are an independent research organization based out of the Netherlands.

But we work internationally. We do that for both business to business as well as business to government, both in industry as well as in, for defense. My background before that, I've been working 15 years at IBM. And mainly as a European services leader for the industrial sector.

And before that I've been teaching innovation, high tech at the TU Delft, at my own consulting firm. And I used, I was a columnist for the leading financial newspaper in the Netherlands. Now I'm an engineer by background, but also, I got my PhD in business strategy economics.

I'm intrigued by competitiveness and what triggers competitiveness. That's, one. And just to elaborate on that a bit, and then we go to the second, is, so competitive is not something which comes easy. You need to stand out, you need to invest, you need to, build.

It's based on,

most of the time, hard work, technology, but also reputation. It's a lot of elements which you need to bring to the table to gain and sustain sustainability. And I'm pretty convinced that from the green IT movement, this is competitive, by heart. And creating competitiveness by heart.

As it's, you're able to combine a reduction of cost if you organize it well. It can bring you more clarity in your complex supply chain.

It gives you a better insight in decision making from an investments perspective, but also from a Marceting reputational side it can enhance your position. But only if you're able to combine all these different threats into one specific aspect of competitiveness. And I think that's where I'm intrigued, and that's why, we did this study together with Accenture, and picked out some relevant cases and draw some conclusions.

But that's one. There's another step I'm intrigued by, is the following, we hear, we read and hear a lot about, let's say the doomsday clock or whatever. About that we have a small earth that we have a lot of carbon emissions, et cetera. And if you're an optimist, if you're a pessimist, I perfectly, I don't care.

But there's something we can do just better, improve, compared on what we do without losing quality of life, quality of on what we do for planet as a whole. Now finding that whole combining with competitiveness, I think that's the strengths which should unique companies, which should unique all other organizations around the globe to see what we can do together.

Sanjay Podder: Wonderful. And, you know, one thing that really strikes me here is you started with competitive space, right? Because this is a space where people primarily drive the conversation with concerns around climate change, the greenhouse gas emissions. What you did talk about in the second part,

you know, we are, the planetary boundaries. We are a small planet. But typically in my own experience, I have seen that, given the challenging business environment that we are seeing today, the leading this conversation with greenhouse gas emissions is not as appealing to business as competitiveness that you mentioned.

Right. And cost efficiencies, operational efficiencies and competitiveness. Many businesses do not see that part today. They can still relate to cost efficiencies, which is equally attractive, improving their bottom line. But competitiveness, you know, is very rare for people thinking that green software, green IT, green cloud, green AI is a competitive differentiator. Right. And I'm glad you started the conversation with competitiveness, which I think it'll be great if you can throw a bit more spotlight, because that to me is the most critical point in this whole conversation for businesses to realize that this is not some altruistic thing they're doing for the planet, but this is for them to survive, to thrive and be ahead of the rest of the competition.

So Marc would love to hear a little bit more, and I'm sure you put a lot of it in your Green IT value case. Right. So, you know how have you articulated that?

Marc Zegveld: No, it's a fair point, Sanjay. And, absolutely, competitive first.

And I'm not sure how you see it, but for me, it's all about change. And change starts with the action. So, internally within companies, you need to fire up you need to ensure that indeed there is action and then competitiveness or the underlaying parameters in boosting competitiveness is key to start that change.

And once more companies, more organizations, understand and work that way, I'm convinced, without being altruistic, but I'm convinced that indeed, a greener IT, a greener situation, a healthier planet can be can be started. But if we start that discussion from a planet perspective, we can agree or disagree, but we more have a debate than that what we have in action.

And I'm more an action-oriented person. And I think that's what companies, and that's why I like this conversation, as well, Sanjay is, with you, with your team. You're more action-oriented. And I think that's where the trigger and that's where it really starts.

So competitiveness, for my end, is a multifaceted aspect.

It's about not only attracting capital and of course within, we have more and more sustainable capital providers, it's also about attracting talent, the new kids from school, I would say, attracting them, gen Z and others, it's more difficult to attract them and to keep them.

And once you, your part, when you tell your story about green IT, about the relevance of green IT that it's indeed not only strong for their environment, but definitely it's strong for boosting the company. It's strong for their career. It's a relevant aspect on being competitive as well. It is a competitiveness indeed for the full supply chain backward looking, but also forward looking. Most of the supply chains are very complex. If indeed we're able to detangle and create some more clarity also from a sustainability perspective, from a green perspective.

In most of the cases we've seen, we're able to reduce cost. We were able to optimize. So there's several aspects, and I think instead of going to the root of only cost cutting, here, competitiveness is a multifaceted aspect, and especially if we're able to create that interplay between these different facets, then we really can build strong, stronger, more competitive organizations, more competitive companies.

Sanjay Podder: Wonderful. And, you know, I think you touched upon various aspects like the talent getting attracted to companies which embrace sustainability. Right? And you spoke about the supply chain. I think another area where, though it might not be an imperative today, it might turn out to be of an important area for business is regulations coming up in this space. Today, the regulations are fairly voluntary. Even the EU AI Act when it comes to, you know, environmental impact, you know, it's much more stronger on the social aspects of responsible AI and stuff like that. I think that would be another area for business to be ready for the future when regulations are much more stringent around these areas, at least in certain part of the geographies, right? So that would be important. So, Marc, one of the thing that I wanted to discuss more is examples of businesses that are turning this into a competitive differentiator. I remember in some of my early conversations in the field of sustainable AI, when we would talk about techniques like quantization, pruning of models, creating smaller models fit for purpose. All that seemed great from a theory point standpoint, theoretical standpoint, right? And, but the moment DeepSeek did all of this and suddenly came out with, you know, large language models much more cost effective.

You know, they built, they trained the model and a fraction of cost compared to other large language models, and we could see that they used the green principles and they have converted it into a competitive differentiator, creating something very unique. You know, and suddenly people started thinking, "do we really need so much compute?" Right. And, the outcome was good enough. Now, have you come across, such examples, in your own study, in the light of the green it value case as well, where you felt that certain organizations or certain industries have changed the outcome or rather, brought this green practices to further enhance outcomes. So are there any examples that come to you, top of your mind?

Marc Zegveld: Yeah, there's several examples, Sanjay. Think more, probably more examples that then we have time for this specific podcast.

I'm sorry you about that one. But there are definitely a few. But if you're okay, and please step in if you want to deviate from it, but I think the regulation part, which you alluded on, is highly relevant. And sometimes it sense that regulation is, comes from top down. It comes from governments or European bodies, whoever. And then it is, it's killing innovation or it is pressing energy or power in that sense from and pressing competitiveness down downwards.

And I think there are lots of examples indeed where it is, where that does happen. So the trick is to create some regulation where indeed companies can thrive and take the action and thrive from, on their competitiveness in the direction of it's green, or it is sustainable, or it is responsible or what it is.

And I think that's a very thin line, and it's always difficult, specifically now today with all these trading blocks, to create a global view. But regulation, also within companies, that's where I like to make the bridge, is highly relevant. 'Cause in the cases, and we'll have some cases, I want to elaborate on or discuss with you.

It's also where the top would identify what's the KPI. So what is the target we are in for? And maybe we don't see it as a regulation in a sense, but internally in an organization it's a KPI. And we all know that a KPI is driving behavior, which how we run our organizations, which is fine, but so identifying what is the KPI is highly relevant. So just to give two examples here, so we have a hospital in the Netherlands who wants to, wanted to reduce its carbon emission. And normally, organizations like hospitals and others, they will look internally and in having less waste or having other kind of initiatives. And they were thinking the other way around.

It was like, if we have less patients visit to the hospital, we have less people driving their cars, if we, through automated kind of

dialogue and assessments and monitoring patients, we have a better insight, then from a full value chain and value system perspective, we have a much better in view, inside view and reduction on carbonization than otherwise.

And so, the KPI here was relevant, but only relevant indeed If they would not look at it from their own organization, but from the full value system. And so that's a highly relevant aspect. So that's also with KLM, Air France, the airline. They do, I would say, these green laps and it's not only internally, but they do it with their partners.

They do it with their clients. Just not only looking internally in their own organization, but in the full value system on what they can gain and what they can do. And here you see a very interesting effect because they take the initiative, it strengthened their relation with their partners.

They have a better, a much deeper insight in the full value system, in their value chain, and as a result, their competitiveness are, however difficult to measure, strengthens. And here you see finding the KPI, identifying what to do and how to drive it. Different organizations will play differently.

Phillips is doing something different. ABM AMRO, which we've, we as Accenture analyze, is doing something different as well. And I think that's where indeed the, there's so many ways to pick that up and to drive it that at the ends, it's more interesting to see about what we did, these 20 or 15 companies and organizations and just distill, what is possible and what are the triggers and what can you do, initiate yourself, for your own organization to start going.

Sanjay Podder: Good.

No, absolutely. I think you have addressed both the, how organizations are using it as a competitive advantage, as well as on the regulations. And I'm with you on the point that you don't have to wait for regulations to come, you know, businesses who are the leaders in their sector, they set up those standards, their own business standards, and then they try to make sure that their business processes are within those guardrails, right, as they operate. Now one of the things that I often, you know, observe is that when we talk about green ICT or green software, there are many terminologies, people typically think it is only about writing green code, code that takes less energy or in the process, emits less carbon. But as even your value case, you know, puts a spotlight on, there's a lot more things for an organization to become green. Right? It is, you mentioned the supply chain itself, procurement practices, for example. So, how do you see organizations grappling with embedding these green practices end to end?

Because this is not something confined to one department or couple of people, right? If you want this value, this competitive differentiation, it is a change management process, a complex change management process. In your research, did you find organizations having developed a good way to do this or are there challenges?

What's your observation about this change management process?

Marc Zegveld: So let me, if you're okay, let me just elaborate a bit on my experience and our studies, but also Sanjay would really hear on from your experience from the Foundation and see where it matches or where it differs.

Sanjay Podder: Yep.

Marc Zegveld: I think there are three key aspects. The first one,

it starts from the top.

Senior management, the board, needs to lead by example. Maybe not in an extremely detailed way of what needs to be done and the KPIs, et cetera, but definitely it's a relevant aspect. And you can bring that also towards a message on competitiveness, a message on why we do business and how we should do business.

That's, I think, where it starts. Then we have on the, I won't say the bottom part, but at the operational part, also in your organization, Sanjay, but in a lot of let's say global or larger organizations we have lots of people, extremely smart, extremely hardworking and driven with a certain purpose.

So let them speak. Let them try. Let them give, let us give them some time on bringing up ideas and suggestions. I think that's motivating people and if we'll do that via small laps or various initiatives, it's all possible.

And then we have, what I would say, the people in the middle, which in many of the cases, let's say also in management reports, they defined as the people who always block.

it's not my experience in a sense. I think these are the people who needs to organize with the various initiatives on the various ideas, and really make that work and ensure that the people on the operational level are able to deliver, and are able to facilitate it. And I know this is all, let's say, highbrow managerial talk, but then we can go through the various initiatives and if it's Philipps or it's ABM AMRO, or it's KLM or it's AWS, I think that's where it happens.

And then once we see some pearls of indeed the real action and progress, then the top can step in and say, "Hey, this is a great example. I want to have more of these examples. Hey, this is what we did in this business unit. Let's see what we can grasp in other business units as well." And then we have a kind of wheel rolling, and get started.

And I think we have enough, quite some examples over there on how that works. Would it mean that if we would completely organize it all every round, that it won't work?

No. But on the majority of the cases we've seen, that's how we combine the motivation, the energy, the ideas, the suggestions, the smartness of people with the sense of direction, the board would identify this is highly relevant to go. How would you see that, Sanjay, from your experience?

Sanjay Podder: Yeah, no, I think I agree with everything you mentioned. You know, I would, I can relate both from my role in the Green Software Foundation as well as in Accenture as we embraced the green software practices. Right? So starting with our foundation, when we started the foundation, we realized that we wanted, you know, people to do green software without even defining, clearly having, what is green software? What are the tools? How do you measure, you know, you can only, you know, reduce emission once you start measuring. Right? And, I think, some of the foundational elements that we did upfront was getting the collective

intelligence of our members, right? So who has best, like Microsoft had a great principles of green software training, which we made available to all members, and that helped us baseline that people know, what are the key terminologies, what is carbon aware, what is carbon efficient? How do they relate to greenhouse gas emissions, for example? And that training has been appreciated by not only the developers, but many of the CIOs I talk to, they say "we love that training. The first thing I did after taking the training, I told each of my direct reports, you need to take that training."

Right? So that was like, you know, making sure that we are all talking the same language. Right. And then there has been plethora of tools. Some of them are open source tools, some of the best guidelines, we created the awesome tools list for people to go through it and see which of these tools are relevant for them.

And then, the third thing was about measurement. How do you measure emissions? How do you measure and express it? And I think one of the big achievements, in my tenure during the chairmanship, was the ISO standard that the Green Software Foundation helped create, called the Software Carbon Intensity, which talked about not only operational emissions, but also embodied emission. And how do you express it in a common way? You know.

So that has been an excellent outcome from the collective effort of our foundation members. And we are now trying to extend that to the AI space with, you know, SCI for AI as an example. So, the way we have tried to bring this culture change or to this change management, is we have, you know, created all these working committees where we have me all member representations, and then these groups, they work together to come up with the standards, tools and so on, so forth. And then our members are, you know, Accenture is one of the member, as an example. So we are, we can then take some of those best practices and bring it into our own organization and sometimes it's a reverse. Some of our best practices go into the Green Software Foundation, for example. Now

reflecting on my own experience within Accenture, I think this change management process is not straightforward. It is, especially because we are a huge organization, so all the elements you said, you know, it has to come from the top. Absolutely. The leadership mandate has to be there. And then we have to make sure we are embedding it into all our processes, methods, into our tools so that, you know, it becomes, by default you are getting, if you are generating code from a code generator, the code you are getting is a green code.

You don't get a code, and then the human in the loop trying to make it green, the code generator gives you a green code and you can always enhance it, right? So how do you integrate it in your methods, in your tools, in your training, for example? And many organizations are doing gamification.

They want to recognize the best teams. They have done something great and make it like a role model for others. Right? And I've heard this from MasterCard and many other, organizations who have been in this podcast, you know, so these are like, some of the ways one can do. I also, we were very happy to have the Singapore government, IMDA, they are very active in this field.

Setting up standards for Singapore and, in fact, they have played a big role in SCI for AI conversation, you know, that we are doing in the foundation. And what the Singapore government has been doing is the Green Software trials program where they're taking all the best practices of things that work and making it available to the ecosystem in Singapore.

Marc Zegveld: Nice. Yeah.

Sanjay Podder: So small medium industries can now use this practices. So, you know, these are like great examples, very inspiring examples, all led by some few fantastic leaders. Right? You know, so, I think the change management is complex. That has been my first observation. But, you know, a lot of things, interesting things we can do around it to make sure that people absorb this.

Right. And, this gets translated into a competitive differentiator, as you rightly pointed out. Now, you know, slightly in an adjacent area, Marc, we are looking at a very interesting time, a time where that is clearly a sustainability challenge. A time where technology is getting more powerful than ever before, right? With artificial intelligence, generative AI, in particular, large language models, business is transforming. What do you feel will be the future of leadership, therefore, in these changing times where, you know, leaders will have to grapple with technology, the sustainability challenges and various other challenges that we are all seeing today. Right. Do you have any perspective on, in this new green world, if I may put it, what kind of leadership we need?

Marc Zegveld: Oh, that's a very difficult, but a highly intriguing question, Sanjay. And we're, I personally as well, but we're also try to understand and work on that. And that's specifically more let's say on the, what kind of dialogue do you need to have within the board, indeed combining that competitiveness with IT

in fairness, more AI both on opportunity, threats, risks. And what kind of leadership, but also what kind of dialogue do you need to have and who should be in their boardroom? But if we distill that from what kind of leadership there is or there should be, specifically with IT and now AI, we have something pretty unique and in my word, invasive, coming.

It is that, we all talk about it, but the number of people who truly understand what's going, who understand not directly the technology, but its ramifications, implications for a reputation, for a supply system, for relationship within the organization is pretty limited. So we need to have a

and I think that's what we're gonna build up in the upcoming 5 to 10 years is a leadership who really leads and sets a pace, sets a direction but combines that with having big ears and really willing to learn and to listen within the organization, around the organization, on what the new technology, on what AI, what IT is doing, can do, what it brings to people, what the risks are, and what we can do about it. And I think that's not a, based on the last 50 years, that's not a standard archetype kind of leadership. 'Cause we are well known with the people who know and set the direction and set the pace and set everything in motion.

And then everybody will start spinning and doing. Then we have the people, whether for a limited time, who said, "okay, we have all these business units and you just take the initiative." And from a capital allocation perspective, we see, 'cause we are convinced that the sum of the parts will be bigger than the whole, and now we need to. have a leadership who sets the pace, sets the direction, but how we do it and how all these interrelationships work. specifically from an AI perspective, nobody will know beforehand. So we need to be very adaptive and we need to be eager to learn, eager to listen, and to play with the information that we have.

And that's a, I would say, unique typology of leadership.

And definitely there are examples on where we see it happen. But that will be my, that would be my two cents now based on where we are. So with the study and based on our assessments.

So from your experience, Sanjay, what will you see from that leadership role, of the leadership perspective? What will change?

Sanjay Podder: I think given the dynamic times we are looking into, the days of command and control structures are over, right? And leaders, in some sense, more from being the face of the organization, they have to be the coach of the organization. You know they, because they need more leaders, every organization will need more leaders given the pace of change, the number of areas and organization will have to fight, which means you need more leaders. And those leaders, the senior leadership will have to be the mentor, coach, and I think it's, in some sense, sometimes we call it leading from the back. But the, in the future, the future model of leadership will be, how do you, not only do you lead your role, but you create more leaders in the process, right?

That is the, that is one of the way you create team of teams in the process, right. And how do you bring outside in innovations? so for example,

the Green Software Foundation is a great example, right? You know, where people are collaborating, trying to solve for a common challenge, which is a planetary challenge, like climate change. And then we are bringing those learnings back into the organization to fine tune our own process, right? So leaders will have to have an open mind. They will have to be like a mentor, a coach. They'll have to generate more leaders internally. Everyone becomes a leader in that sense. So it's going to be a very interesting, model in my mind, keeping the dynamic nature of organizations that we are looking into going forward, from the traditional command control that we are, we have been used to. But again this, you know, it is a lot of intellectual power is going into it. I'm sure people are learning everyday new things with the AI and everything else that's coming around us. We are still grappling with what impact AI will have in our lives, in our work.

So it'll be an interesting observation. How does leadership change as a result of it?

Marc Zegveld: Oh, definitely. Yeah.

But I think where you have, where you started with the Green IT Foundation, and we from a TNO perspective, we did our study, which is limited compare to what you and your organization have been pulling off. I think it's a great example of indeed leadership where from, let's say individual companies, organization's perspective, there's there's found common ground to learn from one another and to see where you can accelerate. And that's based not only from data transparency, it's also from all different angles. And I think that's a great example also in, let's say in the future ahead.

If we look at it from an AI perspective or other perspective, if we talk about regulation, et cetera. I think this is a way forward.

Maybe it's not the fastest way, but it's, at least it's a way where

indeed we're all able to cooperate, to collaborate and we can learn from one another because we all know if you need to do it yourself, it's too costful, it's too painful, too risky.

Sanjay Podder: Absolutely. So, Marc, this has been such a great conversation. For anyone who wants to dig deeper into the Green IT Value Case or connect with your work, where should they go?

Marc Zegveld: Go to the website of TNO, tno.nl, and there you will find more information about the Green IT Value Case and the work that we do. And specifically from the unit IcT Strategy Policy. Yeah. And if there are, if you can find it, please send me a note, Marc Zegveld.

Sanjay Podder: Great. So, Marc, we're at the end of this podcast. And probably if there's any area you'd like to talk more about to let me know, then I can further explore. But I think we are fine for the day, otherwise.

Marc Zegveld: Great. Thanks. Was a joyful hour, Sanjay. Thanks.

Sanjay Podder: So, well we have come to the end of our podcast episode, all that's left for me is to say thank you so much, Marc. That was really great. Thanks for your contribution and we really appreciate you coming on to CXO Bytes.

Marc Zegveld: Great, Sanjay. Thanks for inviting me.

Sanjay Podder: Awesome. That's all for this episode of CXO Bytes. All the resources for this episode are in the show description below, and you can visit

podcast.greensoftware.foundation to listen to more episodes of CXO Bytes. See you all in the next episode. Bye for now.

Hey, everyone. Thanks for listening. Just a reminder to follow CXO Bytes on Spotify, Apple, YouTube, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show. And of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again, and see you in the next episode.

Hosted on Acast. See acast.com/privacy for more information.

In this episode of CXO Bytes, host Sanjay Podder speaks with Adrian Cockcroft, former VP at Amazon and a key figure in cloud computing and green software, about strategies for reducing the environmental impact of AI and cloud infrastructure. Adrian shares insights from his time at AWS, including how internal coordination and visibility helped drive sustainability initiatives. He also discusses the Real-Time Cloud Carbon Standard, the environmental impact of GPUs, the challenges of data transparency, and the promise of digital twins like meGPT in scaling sustainable tech practices.

Learn more about our people:
Sanjay Podder: LinkedIn
Adrian Cockcroft: LinkedIn

Find out more about the GSF:
The Green Software Foundation Website
Sign up to the Green Software Foundation Newsletter

Resources:
Stern Review - Wikipedia [02:26]
OS-Climate [05:55]
Amazon Sustainability Data Initiative [06:31]
Real Time Energy and Carbon Standard for Cloud Providers | Notion [12:47]
Real TIme Cloud | GitHub
Software Carbon Intensity (SCI) Specification [27:21]
Kepler | CNCF [27:49]
Measuring Carbon is Not Enough | Adrian Cockcroft [37:15]
Virtual Adrian Revisited as meGPT [40:15]
Soopra.ai [43:44]
OrionX.net
Will AWS Have Anything New To Say About Sustainability at re:Invent 2024? (Nope…) | by adrian cockcroft

If you enjoyed this episode then please either:
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TRANSCRIPT BELOW:

Sanjay Podder: Hello and welcome to CXO Bytes, a podcast brought to you by the Green Software Foundation and dedicated to supporting chiefs of information, technology, sustainability, and AI as they aim to shape a sustainable future through green software. We will uncover the strategies and a big green move that's helped drive results for business and for the planet.

I am your host, Sanjay Podder.

Hi. Welcome to another episode of CXO Bytes, where we bring you unique insights into the world of sustainable software development from the view of the C-Suite, I am your host, Sanja Poddar. Today we are thrilled to have with this Adrian Cockcroft, a pioneer in cloud computing and a passionate advocate for sustainability and sustainable tech practices.

Adrian has been at the forefront of transforming software practices, driving the adoption of greener and more efficient cloud solutions. As a prominent figure in the Green Software Foundation, his insights are invaluable for anyone looking to build scalable and eco-friendly tech infrastructures. Adrian, welcome to the show.

Kindly introduce yourself.

Adrian Cockcroft: Thank you very much. thanks, Sanjay. I'm Adrian Cockcroft. I'm a consultant and analyst currently at Orionx.net. Happy to be here. I retired from corporate life at Amazon where I was a VP in 2022. And nowadays, I'm an advisor to several companies, from fast flowing global public organizations like Nubank, to emerging startups like NetAI.ai, and various other small things that I dabble in, in the startups space.

Sanjay Podder: Wonderful, and we'd like to hear more about all this. Before we dive in here, a reminder that everything we talk about will be linked in the show notes below this episode. Adrian, you have had an illustrious career in cloud computing and sustainability. Could you start by sharing what inspired you to focus on green software and how your journey led you to your involvement with the Green Software Foundation?

Adrian Cockcroft: Yeah, we have to go quite a long way back. Somewhere in the early 2000s there was a report, I think it was called the Stern Report, and it was a report on the economic impact of climate change. And around that time we sort of, a big rise in climate denial and a big attack, what I saw it as an attack on science. Good science. I have a physics degree, so I feel my, you know, going back in very long time ago, but I see myself as a scientist and someone that's able to look at a bunch of science and decide, you know, "this makes sense, this doesn't make sense." And what I saw was that the denialist arguments were incoherent.

They'd argue different points depending on who they were talking to. It just, it didn't add up. Whereas the, scientific arguments were consistent. And we're worrying, right? We were on a path to a lot of problems, which are happening now. We haven't been addressing them fast enough. So that was the initial thing.

It was nothing to do with my work at the time. I was probably at eBay at that time. I joined Netflix soon afterwards. So I was working on migrating, well, working on some personalization things with Netflix and then working on the architecture for migrating Netflix to AWS. And then, we've sort of dived in a little bit, I adopt, had solar panels for 2009, the electric cars since 2011. So sort of put, tried to act as a bit of a, you know, "put your money where your mouth is" as a someone that people could, you know, happy to be the early adopter and figure things out. And then after I joined Amazon in 2016, I could see Amazon was, had actually quite a lot going on that was related to climate and efficient use of energy and things like that. But they weren't really telling that story. And I tried to get involved to see if I could, you know, get involved at any way. And I, it took me a little while to do that. What I found was, you know, I was basically the vice president in charge of the open source program and also out there, acting as sort of a evangelist, explaining to people how you should move to cloud.

Doing lots of public speaking, I keyed some of the AWS summits and things, but there was no messaging around sustainability in the standard PR approved corporate messaging, which, you know, that's what you have to follow. So the challenge was how do we get PR to include the messaging in the standard,

you know, so that everybody knows what they can say and has the information to back it up? And AWS is a very strict PR policy. It's very managed, and you have that, you have to get them on board and and build all of the right content and get everyone lined up to do that. So that was the challenge.

And then, I found that somebody was trying to join a standards group called OS Climate, which is a Linux Foundation organization, as is GSF, and I'd previously been involved in, the work to get AWS to join the, CNCF, the Cloud Native Computing Foundation. I was the initial board member for AWS,

representing them at CNCF and the whole Kubernetes AWS and Kubernetes Arena. So I was, I understood how to join a standards body, basically. And so I helped Amazon join OS Climate. And that got me much more involved in the sustainability organization because they, it was open source climate information that was being shared for, mostly for financial analysts to do risk analysis.

It's a very specific thing. So you can go look at OS-Climate.org if you want to see what they've been doing since. This would've been in about 2000, around that time. And then that was related to something called the Amazon Sustainability Data Initiative, which is a whole lot of climate related data that is shared for free on AWS, one of the programs that most people hadn't heard of.

And eventually, I managed to make an internal move to the sustainability organization because they realized they needed to gather together everything that was going on. What was happening was customers were asking salespeople, what are we doing about sustainability? And they were calling, they were either making something up or they were calling random people in the sustainability organization.

And that organization's job was to do the carbon footprint for all of Amazon. It wasn't to talk to AWS customers. Right? And so the VP that runs that organization, Kara Hurst, basically created a position for me as a, as another VP to move across to that group, and to gather together everything that going on across AWS and act as sort of a, all of this incoming requests and information and whatever, and makes sense of it.

So this is actually kind of an interesting problem you have, right? If you're running a corporation, you find that there's a groundswell of enthusiasm around climate and it's driven by, you know, kids coming home from school and saying, "so what are you doing to make the world the place I can live in when I grow up?"

Right? everything from that to board members, suppliers, legal mandates, there's many reasons why people have a need to be either greener, or to manage and report their carbon information. And it was popping up in all different directions. So that's, so what we did, there was a couple of tricks.

One was that we started an internal email newsletter that went out every Monday. This is a very powerful trick. It's a pain in the neck to actually do every week. It's like, "damnit, I gotta write this stupid thing and get it out." I did it for a while and then I had a, luckily I had managed to hire someone to do it for me.

But the, what it did was it said, well, here's a group and what they're doing. And then at the end of the email was a list of every group I could find and who, what roughly what they were doing and who to call. So like a "who are you gonna call? List," right. And. That email got passed around and people say, "well, I'm not on that list."

So it gradually accumulated this long list of all the stuff, and if you ever read this message, you looked at the end, "wow, there's a lot of stuff going on." So it makes work visible, which is one of those principles of management, right? Make work visible.

It made the work that was going on visible so people could see just how much stuff was going on.

And each week we'd feature a different one of these groups that we'd run into a little bit more detail on what they were doing or any actual announcements that were going on publicly, like we just say some more wind farms or stuff like that were announced or as we got through like the reinvent conference where we got some things going.

So that was one piece of gathering everything and getting everyone on track and generating enough internal sort of, Amazon and AWS are very distributed organization. There are lots of very independent teams, so the challenge is always doing one central thing. That's the hard thing to do at Amazon corporately.

So this was, you have to have a technique that gathers it together. So we got that together. We also had a principal marketing manager working for me, and she also worked with the Amazon Reinvent team to create a track at Reinvent that is branded sustainability. So every year there's, you can go look for sustainability related talks and there're all different areas, but there's like 20 or so talks every year.

So creating that track was also a big argument that eventually, "yeah, okay, we'll do it because there are only so many different tracks that they will create." And then we managed to get, there was also this well architected program for how to do software better for cloud, well architected for, you know, cost optimization or efficiency, sustain, security, all these different things.

And we pitched that there should be a sustainability one and got somebody to write it. Got it through the system. I'd edited a little bit of it, but mostly I was sort of the corporate sponsor to get it through the process of getting it released, keeping it all on track. So we got that released. We did a talk at Reinvent where we announced it.

And then finally there was the customer carbon footprint tool, which a team was already trying to produce. They knew they needed to produce it because various customers needed this data and it was being released to them in, you know, dribs and drabs under NDA. "Oh, here's some numbers." Right, but there was no standard way of getting this data.

It was being done on a one-off basis, which doesn't scale. So there was a, at least an attempt to put together a basic tool with the information you need for, basically accounting data. Like if you're doing your annual carbon footprint, you need to know how many are, how many tons to buy offsets for that kind of thing.

So that was really only for that purpose. But as somebody that's got a developer background, I always wanted to have something that was more real time. If I'm running a workload, what's the work, "what's the carbon footprint of this workload" was something I was very interested in. But the annual, you know, accounting information is much more like a CFO cares about that.

It's, but that data is not that useful for doing individual workloads. So that was roughly where we got to. I'd been at AWS for about six years and I was kind of done with it. And, I felt for various reasons, some personal reasons and some just like I was that, that it was the time that I wanted to retire.

So I retired from Amazon in 2022. Sort of left behind this sort of what we'd got done. And then, basically became this sort of independent consultant and started right talking about green software and things like that and talking to the Green Software Foundation. And eventually we decided, you know, I, that it would make sense to make a proposal.

So I proposed the realtime cloud project and I think that was 2023 we started doing that. So that was a long answer, but hopefully that's useful.

Sanjay Podder: I think that's a fantastic answer. A lot of things to learn from there. And, since your time outside of AWS with GSF and other groups, have you seen the sustainability in tech become more of a first class citizen, or is it still an afterthought? You give an example of PR where you know, and I often see that even today many organizations forget to highlight the work they're doing on the sustainability side.

And in many cases they are doing it, but they miss it completely. And you give a good example of that awareness you created by just collating all the good work together. Suddenly you see, wow, you know, we are actually doing a lot of work but nobody paid attention to it. So do you see this changing with time as people are getting more aware of sustainability dimension of tech and making it a first class concern, rather an afterthought?

Adrian Cockcroft: I think we've seen some movement in that area. There are quite a few companies that have a public position, which is that we are green, whatever. You know, Apple is an, is a good one, for example. they have very clear public messaging and they need to do all of the work to back that up. So I think that's what drives it, right? At a corporate level, you want to say, we want to make a position on this company being green as a corporate thing, right? So you need to have the data to back that up. You need to have it, and then it sort of flows down. Everyone cares about it. If it's something, if it's not one of your priorities that the executives talk about, then you know you can do stuff around the edge, but you're basically being driven then by regulatory, supplier, you know, and employee enthusiasm, right? And so there's some level of that. And I think that the, with Amazon, there's the Climate Pledge program, which they've been pushing, which is basically, you know, we say we're going to be carbon neutral by 2040 rather than 2050.

So it was an acceleration of the Paris Agreement. And that, that was sort of the core public thing going out to get people to sign up to it. And you know, and Amazon itself sort of working to that goal internally, which drives a lot of internal activity. But the frustrating thing was we, it was hard to get projects that were going on internally that you could talk about publicly. It was very difficult and we were sort of had a big battle to get what we got out through sort of the PR filter. And people like taking pot shots at big companies. And the, it's sort of like the PR organization is very gun shy around this topic because they keep, it's a negative, right?

And unless you can come out with a story that's so strong that it becomes a positive, if you're in PR, you just avoid stories that are a negative. So, I mean, so they're doing rationally the right thing for the company, but it's very frustrating because there is actually quite a lot of good stuff. But it's hard to assemble it into a really big positive story when the, at a corporate level, it's a thing that Amazon does, but it's not as central as it is to some other organizations.

And sort of the position AWS has is that we're gonna buy enough green energy and, you know, building wind farms and whatever, that you don't need to worry about this. We'll just take care of all your carbon for you, right? Like, we'll take care of the data centers for you. It's a concern that we will, deal with for you.

And that works for some people, but it doesn't, I don't think it's enough for what the general discussion is. And it also means that it's hard to get enough information to, say, optimize a workload. So I have a thing I need to run for my company. I could choose where I can run it.

I can choose which cloud provider, which region, which country maybe, and if one of the metric, one of the objectives I have is to do that in a green way, then I need some information like which data center in which country, which provider? What's the difference going to be? And that's kind of the information that we've been trying to gather so that we can say this region, on a region by region basis

you can compare things like a PUE, energy usage efficiency, and water usage and the carbon offset that they have, you know, how much carbon free energy is being generated in that region, things like that. So you could make that comparison and that's really what we ended up producing in the GSF, realtime carbon,

the real time cloud group, right? So it's a, took all of the data that we could find from all the cloud providers, which is a huge mess, different models, different standards, different ways of looking at things, and tried to put it into a common format. And then the other thing is that data about regions is quite old.

It's a year or two old. So we've come up with also estimates for now what we think the, you know, if you're trying to measure, say, well, what's a workload gonna be like today, we trend some of the metrics and we figure out some others that don't, you know, to work out what, would today's data look like?

Sanjay Podder: Two questions come to my mind. One is, in the time that we live in with AI as fast turning out to be one of the most important workloads in the data center, and some of the more popular ones are closed source, which means that very little is known about how big are the models and if you have to green it, therefore, you know, do you see the same challenge that you were articulating earlier with not as much information there? But now is that problem getting more compounded because there may be more things that we don't know and therefore to green the whole thing becomes a challenge, what's your perspective on that?

Adrian Cockcroft: Yeah, the emergence of the current LLM based, I mean, AIs have been around for a while, but

the recent emergence of the LLM based AI, sort of the explosion of it, is causing multiple things to happen. One is a real change for computing to be GPU centric, which is much more energy intensive.

And it turns out that although it's very difficult to get realtime energy for the CPUs in a, particularly in a cloud environment, the way people run GPUs, you go to the NVIDIA interface and it tells you how many watts it's using, in real time, once a second. So there is actually very good energy data available for the GPU workloads. And the GPU is dominating. So if you've got that data, you could add a percentage for everything else, but it will give you a pretty good basis for the energy being used by a workload. And. Measured in real time. So that's actually quite helpful. the reason that CPUs don't provide energy information is usually they're virtualized and the virtualization, is there's effectively a security issues around Being able to measure the energy use of a system when you're actually just a VM running on the system, right? They don't have the energy on a per VM basis, but GPUs are normally used as entire GPUs, and you can find out the energy usage of it.

So that's one piece of this. Can you measure it? Okay. We can measure it actually really well. In fact, some people tune their AI workloads by power, like if it, they tune it until it's running maximum power. 'Cause that's how they know it's doing maximum flops, right? The energy, right? If it's running at low power consumption, it means it's not running efficiently, which is a bit perverse, but it makes some kind of sense that you want to use your hardware efficiently.

So that's one thing. But then what we've found is that there are now huge data centers being built, and this wasn't part of the plan a few years ago. So if you're planning data centers and the energy infrastructure to support data centers, that planning is on a, like a three to five year, maybe two years would be quick.

You know, three to five years is normal for planning out where you are going in terms of energy or putting up buildings and doing very large scale infrastructure. Takes time. And this just turned on its head and all of a sudden there was a shortage. So there's a shortage of buildings and power, and I think it'll come back into alignment.

Probably oh in like maybe three to five years, we will be in a new steady state where we know what, where everything is, you know, we have enough energy to do what we need to do, but in the very short term, there was a sudden increase in the amount of energy needed for data centers, and this would be really bad if we didn't also have a rapid increase in electrical energy for cars and space heating, right?

If you look around, those are the three big new drivers that we are, we are switching from gas to electricity, gasoline and methane basically to electricity. So we've already, we already knew we needed a lot more electricity. And that's been driving investment in energy sources. But the AI data center has caused a, like a very rapid increase in a very short period of time.

So that's a problem. And what we've got effectively is there's going to be less clean energy for a few years as we get catch up. You can't just stand up wind farms in three months. It takes too long. So that's the second sort of thing that's happened with AI. And then the third thing is,

can you use AI to help?

And I think the main problems we have are just lack of data and the fact that everything is very messy. AI might be able to help here and there. But I don't think that AI is really, I mean, there are people telling selling tools that will use AI to help you optimize your carbon footprint and things like that.

But I think the things you need to do are pretty obvious. The AI is going to help at some point as an optimization, but it's not the main driver. The main driver is wanting to do it in the first place and being able to get measurements out of the system at all. Right? If you can do that, your most of the way is pretty obvious what you need to do.

You don't necessarily need AI to tell you to make all your computers run twice as busy so that you need half as many of them. Alright, that's, kind of the obvious. My obvious thing to do is to work on utilization. Most people have very underutilized systems. If you can increase utilization, you save money.

'Cause if you use half as many computers, you pay half as much and it's half the carbon footprint. And people just seem to accept wasting, you know, leaving CPUs idle and GPUs idle when they should be being kept busy. Or if you're on a cloud provider, you should be, you know, giving them back so somebody else can use them.

Sanjay Podder: Absolutely. Coming back to the real time cloud carbon standard project that you have been driving. How real time is this real time? Because part of the hyperscalers, as we know, their reporting is not of the same granularity, both in terms of frequency as well as what they report.

So how are we ensuring that we bring some amount of uniformity when we talk about real time cloud carbon standard?

You know that, there may be a lot of unknown. I think you even spoke about some of the challenges in your earlier role. So how are you trying to address this gap?

Adrian Cockcroft: I had say the word real time in there is aspirational. What we'd like is in real time, meaning I am running a workload, I want to know what is the energy use of that workload? What is the carbon footprint of that workload now? And if I'm trying to predict a workload, I want to be able to know I need enough granularity to be able to do that.

And like I said, you can kind of do that with GPUs because you can get real time data out of them. But in general, we went to the cloud providers and said, "we'd like this data," and they said, well, it's too expensive to build. And it's not just expensive in cost, the carbon footprint of adding additional metrics and instrumentation is not zero. And then the number of people that would use it and the amounts that they would save is also. You have to kind of look at, it's gotta be used pretty universally. But we have cleaned up some of the data that they do have. So I think that the main thing is to try the point of real time is like, is to make it relevant to somebody trying to run a benchmark.

In particular, if you look at SCI, the other GSF standard, I want to generate an SCI number for a workload, that means I need to know what is the carbon, like for that workload, right? That this is what we're, you know, in real time so that I can have an SCI number. That's kind of what we're trying to do, is if you're running that workload in the cloud, then you need to gather data that you can at least estimate what you're going to do.

The CNCF has a project called Kepler that works with Kubernetes. So if you have a Kubernetes namespace that defines a workload, you can find all the pods in that name space, it'll estimate the energy use of those pods as a subset of the energy use of the nodes they're running on, and give you the best guess of a real time number for energy.

And then you can go look at the region that you're running in and say, okay, that region has whatever, you know, 80% carbon free energy, meaning that the, that carbon, that cloud supplier has a lot of,

80% of its energy is coming from either wind or solar or battery or, and some mix of the grid, right?

Or you can decide you just want to look at the grid. It's up to you whether you want to do market based or location based kind of numbers. Different people have different reasons for doing these things, but the data is all there to come up with an estimate for what is the carbon of a particular scenario that you're looking at.

So in that sense, that's what, why it needs to be real time as opposed to the sort of accounting annual data that is sort of my,

the non-real time stuff, if you like.

Sanjay Podder: Makes sense. And do you see in future that you'd also like to extend it to other environmental resources like, say, water? Right? Where a lot of times people are concerned about the use of water for cooling, for power generation. So, are there any plans that, you know, we will have some kind of a similar standard that just does not talk about just carbon, but also about water?

Adrian Cockcroft: Yeah, we do have water in there. The data is published by some of the cloud providers, and there are two metrics for water. One is water usage efficiency, which is basically liters per kilowatt, right? The other one is replenishment rate, which is clean water, the water coming in versus water going out, right?

Because you have wastewater coming out, and it's a little odd because you can bring in dirty water and clean it up and put out clean water, which means your replenishment rate is greater than one. Right? If you take in, if you bring in dirty water and clean it up, so what they care about is the amount of clean water that comes out, versus the amount of water going in.

So it's a much more complicated sort of,

and I mean these things, all of these metrics, when you dig into them, they all get complicated, right? Right. Carbon's the same, but water has these two characteristics, which is the water flowing through, and then how much is it related to the energy usage?

So there's an efficiency thing, which is really related to how efficient your cooling system is. And then the water treatment system is like where you're getting your water from, how much are you using, versus what is it going to. And there are definitely some plants out there, there's some of the AWS ones that take in dirty water from industrial sources and they put out water that's clean enough to be used directly for irrigation in farming. Right. That's a, that is defined as a clean water effectively. Right? They take out all the pollutants as it goes through the system. So that's, you know, that's a nice thing. Others are, some of the older data centers are incredibly inefficient.

They take in masses of water and just boil it off and have terrible replenishment rates. Right. But if it wasn't something you were looking at, then it typically will be bad. I'd say data centers built in the last five years are much better. It's the older ones, which are worse. So it's kind of odd because if you look at a data center, it might be very good on carbon, but very bad on water.

Or vice versa. It just, they're not correlated, really. But the latest builds are good on both. Right?

If you're building a brand new data center today, it's likely to be very good on water usage and power usage efficiency and low carbon. Particularly the big ones that are being built for running these big GPU environments. You shouldn't use the average numbers from a few years ago to apply to those data centers because they are, the cost of the water and the energy is very high and they're optimized to use as little as possible. So they're, we're seeing some very clean systems there. And then the energy sources is another area that's quite interesting.

There's a whole lot of innovation right now in terms of alternatives to wind, solar, and gas, basically.

Sanjay Podder: Adrian, in your opinion, how far are we from being able to express, not just at a data center level with water usage efficiency, but at a workload level, if I have to say something similar to SCI right, if I have to say that for this workload, this is, for example, if the workload is related to AI being used for fraud detection.

You know, if I say it's x liter of water per hundred fraud detection that we are trying to do. Now, that's, that we are talking at a different level of abstraction than WUE. But how easy to do that.

Adrian Cockcroft: Yeah,

you could because you have the, you know, whatsoever, you run a number of these fraud checks that uses a kilowatt of energy, a kilowatt hour of energy, right? The kilowatt hour is a, is the energy, capacity, energy of it. And then you can say that used, you know, half a liter of water and its carbon footprint was, you know, 30 grams or something or whatever, right?

So those numbers are directly available once you know the energy of a workload. All right. The trouble is figuring out the energy of the workload. That's, well, that's part of the problem. And then the other question is where you get the numbers from to give you your water and energy, and how accurate do you want them to be?

Because a lot of these numbers are annual averages. And if you want something that's much more specific, you're trying to optimize hour by hour, an annual average won't show that. So if you're doing very tight optimization, you want to be using say, hourly data, and that's where the system, that's where you start digging into much more complex environments.

But ultimately I think that as we get better at doing this, we'll end up doing, This sort of fine grain, real time optimization, sort of minute by minute, hour by hour, rather than trying to do stuff at the monthly or annual level.

Sanjay Podder: Right. Yeah. That would be nice to be right. You know, because that makes it very actionable for the developer community to reduce the emissions. And if they know that I am having x tons of carbon dioxide emission and I'm using, you know, y kilowatt of energy and I'm using x liter of water per hundred fraud detection, can I lower it?

Or, you know, per, customer supported, you know, so it becomes very actionable for people to track. Hopefully we'll reach that state very soon in the working around.

Adrian Cockcroft: Yeah, I think somebody did. Somebody did an analysis of ChatGPT because people have been very worried about it, and I forget the exact numbers. There's, I think you, we should be able to find the story, but it was a totally trivial amount. Like even if you do lots and lots of queries on chat GPT in a day, it's still, like a very small amount, you know, a few grams of carbon and a few milliliters of water and it's much less than, you know, going to the bathroom or drinking a cup of coffee, right? So you have to have a sense of proportion sometimes on these things. And because we see the sort of training workloads are huge, but what we care about is how efficiently the inference workloads run.

And what, how often people are using them. So you have to kind of be a little careful and not get carried away with the numbers and look at how does it relate to something that you are also doing, right? And if having a meeting to discuss saving carbon uses more carbon than the carbon you were gonna save, then it doesn't make sense.

Right? Just flying internationally is probably the biggest use of carbon that we have, on a personal basis. It's like a ton of carbon or something like that to fly from the US to Europe, for an economy flight, for an economy seat. It takes an awful lot of other things to add up to that much.

So there's a sense, one of the things that I think people tend to lose is their sense of proportion, because these numbers are just, there are too many big numbers floating around. I did a blog post on consequential, sort of, analysis as well. That was something that I came outta talking to Henry from WattTime, who gave, who really gave me a lot of feedback to really help me understand this.

And as I was trying to understand this, I wrote it down. So I ended up with a post on trying to understand the consequences of what you're doing and make, which is part of understanding the bigger picture of not just how much does this thing here consume, but how much impact does that have on everything around it?

And what bound. If you want to really say you're saving the world, then you have to think about the world as the boundary. Whereas most people are talking on a corporate level about the, "this is our corporate footprint." And just because you reduced your corporate footprint, you don't know whether that, you might find that the money, the carbon you saved was caused extra carbon to happen somewhere else. You know, the sort of, the kid's party balloon animal problem, like you squeeze one leg and the other leg gets bigger, right? That, there's a lot of that happens and a lot of double counting and missing things.

So it's just a big, messy area and I think that's the hardest problem. I think we can directionally say that there are things we do that make it better. When if you try to come up with very detailed measurements, you get down rat holes that become unproductive fairly quickly. So I think the biggest thing you can always do is just run more efficiently, use less, and that's always gonna be better.

Sanjay Podder: And be carbon aware, right. In terms of...

Adrian Cockcroft: Yeah.

You know, think of it about where you're doing things. We still have the problem that most of the carbon, most of the high carbon regions are in Asia,

Sanjay Podder: Yeah.

Adrian Cockcroft: depending on which cloud provider and where in Asia. But Europe and the US are pretty low carbon now, and Asia has going to take another 5 to 10 years to clean up.

So it is just kind of a phasing thing. It's a, for the next few years try to avoid, if you can choose to put a workload in or a like, say an archive backup. You want to put an archive in another region, put it in Europe. 'Cause that's likely to be the lowest carbon place to put your archives for backup purposes, right?

If you leave them in Singapore, you're going to find that's high carbon.

Sanjay Podder: There's a very good article very recently published in MIT Sloan Review the Maths of AI, with a lot of input from the recent work done by Sasha, from Hugging Face as well as you Boris from Salesforce. And it does give you different scenarios to show how the emissions and water can very quickly snowball to big numbers as we, look at, the growth in the sector.

Right? Yeah. So I also think you recently wrote a blog post on Virtual Adrian Revisited as MeGPT. What was the, you know, thought behind it about this digital twin, personal digital twin, and how do you see digital twin AI tools like MeGPT contributing to soft sustainable software development practices?

Adrian Cockcroft: Yeah, so I mean, I've been writing code for a very long time, and so one of the ways of understanding a new thing when it comes along is just try to use it, right? Just try to build something using it. And so I wanted to get my hands a little dirty, doing some work and I've been using, I've been coding in Python using, they call it vibe coding now.

Basically telling, like the cursor, Claude thing I have, please write me some code that processes YouTube videos, YouTube playlist into individual videos and stores them as a .json, blah, blah, blah, right? And it goes and writes that code in about 60 seconds and then run it and it works, right?

You point at a YouTube playlist and it prints out a bunch of resources that you can then share and ingest into an LLM, something like that. So that part of it was me playing around. And part of it is that I've got about 20 years worth of content that I've produced. I'm a sort of a developer advocate.

My actual title at Amazon was a VP of Evangelism for one of my roles. And the job was to go out and tell stories. So I have massive amounts of video and podcasts and presentations and all these things, right? And it's there to try and influence spread ideas. I'm not trying to monetize it, like people say, I don't want people using my AI content because I'm trying to monetize it.

That's one problem. I'm trying to spread this idea. So the more they get, the more they get spread, the better. So the easier I make it for the LLMs to understand my content, the more influence I have in the world. So I'm looking at it from that point of view. And this is like a marketing point of view.

If you want to spread some information about your product, you might want to build a expert for your product, really. All the documentation and examples and things. How do you teach the LLM to use that so that the LLM knows how to use your product versus somebody else's product when somebody says, "Hey, I need to solve a problem."

That's the area. And part of that corpus of data includes all the things I've written about carbon and optimization and performance tuning and all the other things I talk about, from everything from corporate innovation to DevOps to whatever, right?

All the software, architecture, cloud, migrations, all those things.

So that information is all in, basically indexed by this MeGPT. It's on, if you go to GitHub, Adrian Co, which is my GitHub account, MeGPT. And the idea there is that as an author, I have sort of a virtual Adrian co author containing all my information. And you run, you build it and you end up with an MCP server that you can attach to your LLM, and then it will know how to query the body of content I have. And then there's a company called Soopra. There's several companies, but the main one I've been working with's called Soopra.io, soopra.io. And they have a persona based system where you load your information into it and they generate a persona that you can then query and have conversations with.

And it answers questions as that person. So it understand, it sort of, kind of follows your voice a little bit. But it, in my case, what it does is it pulls out all the information from these blog posts and things I've written. So it's a way for me to, and one of the things, I mean, you work for a consulting organization, they always say consulting doesn't scale, right?

You have to hire more people. So in some sense, this is a way of making consulting scale as we get better at getting the knowledge of a consultant, somebody like me that's got a 40 year career, I can dump what I know into this system and then people can query it and it, you know, I'm no longer, I don't have to be there in person.

So in some sense I'm sort of sharing that information.

Sanjay Podder: Right. You have your digital persona. I was about to ask you a question on where people can learn more about what you're doing and your work. Looks like you have already defined a lot of digital personas to help people to easily understand more.

Adrian Cockcroft: Yeah. I mean, you can find me on LinkedIn relatively easily, and if you go to orionx.net, there's, we have a monthly podcast where we talk about what's going on in the industry, and things like, you know, whatever coal weaves, stock price going up like crazy or whatever, you know, what's happening with green energy sources and bitcoin things.

There's different, it's not my expertise, but one of the other people in our, in OrionX is deeply into that area. Quantum computing, all these things. So we have an interesting little group of analysts. There's four of us that chat about stuff once a month. So we have a podcast, but you can find that at

OrionX.net along with links to myself, and if anyone wants to chat to me about, you know, tuning up their workloads or help figuring out how to, you know, work on a better sort of carbon strategy and sort of generally, I mean, I'm sort of semi-retired, so I'm not looking for work on a daily basis, but I'd be open to interesting opportunities to work with people.

Sanjay Podder: Wonderful. So I think, I guess we have come to the end of our podcast episode and all that's left for me is to say thank you so much, Adrian, and this was really great. Thanks for your contribution and we really appreciate you coming on to CXO Bytes.

Adrian Cockcroft: Thank you. That was fun.

Sanjay Podder: Awesome. That's all for this episode of CXO Bytes. All the resources for this episode are in the show description below, and you can visit podcast.greensoftware.foundation to listen to more episodes of CXO Bytes. See you all in the next episode. Bye for now.

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