Ralph Loura: 0:03

We're being pulled into conversations and say, Hey, you guys, you're at the heart of the thing we, we want to do a better job in a green economy. AI is wonderful, but like, it seems to be moving in the wrong direction. Can you guys help? So we're, we're having a lot of conversations about bridging the gap between, a number of people are talking about ethical AI. We've actually just released a white paper and are coming out with a conversation about sustainable AI.

Tom Raftery: 0:26

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Climate Confident podcast, the number one podcast showcasing best practices in climate emission reductions and removals. And I'm your host, Tom Raftery. Don't forget to click follow on this podcast in your podcast app of choice to be sure you don't miss any episodes. Hi, everyone. Welcome to the Climate Confident podcast. My name is Tom Raftery. And with me on the show today, I have my special guest, Ralph. Ralph, welcome to the podcast. Would you like to introduce yourself?

Ralph Loura: 1:03

Yeah, thanks a lot. I'm happy to be here. My name is Ralph Lora. I'm a, I guess a serial CIO. I've been CIO at a number of companies and industries over a long career. And now I'm spending my time with an organization I helped co found called sustainableit. org. I'm the chairman of the board and we'll talk a bit about what sustainable IT is doing.

Tom Raftery: 1:23

And why? What made you decide to co-found sustainableit.org?

Ralph Loura: 1:30

It, it seems to me I've observed, I think not not the first to observe, but technology change has gone through cycles or eras. We had the kind of mainframe era, the distributed computing era, we had the mobile era, the internet era, and so on. The last era seemed to be the digital everything era. And a a and looking ahead, it seemed like we've created a few problems along the way, and we tend to create the problems, and then over a decade or so, we find ways to clean them up. And then the new the new era comes out, and we we start the cycle all over again. One of the common things we do is we create-waste. We, we are in a rush to adopt things. We adopt them all over the place. And then later we go back and decide what's useful, what's efficient, and then we kind of do that work. And so one of the common themes of all these trends has been this, the, the, the-waste we generate, the e-waste, the, the electricity overconsumption some of the impact we have on people and projects and processes along the way. And so it just seemed like, Hey, why don't we actually found some, some effort around that, the real issue of how do we get more effectively use the resources of the planet? How do we more effectively use the resources of our organization? And how do we ensure the work we're doing is benefiting you know, kind of the people and things around us? And and we were sitting around with a bunch of CIOs and, and, and asking about common problems. And one of the common problems was or common thoughts and problems they had was this. And then, and then lastly, maybe, maybe just you know, I'm of a certain age as are a number of my peers are kind of looking to the next generation and thinking, you know, maybe we didn't do such a great job as our job as stewards. So maybe we need to do a better job of stewarding resources for the next gen when that does kind of the background of how sustainable IT came, came about.

Tom Raftery: 3:11

And for people who are unaware, can you tell us what Sustainable IT is and does?

Ralph Loura: 3:18

Yeah, so, uh SustainableIT.org is a non-profit. We're created by, led by technology executives. And the idea is to advance sustainability around the world through technology leadership. So, lots of people are focussed on carbon, or decarbonisation, or yYou know, equity around the world, which is wonderful. But technology leaders often play a unique role in these sort of things. We, in many companies, you're the largest consumer of power. You own the e-waste stream and some other things. We didn't feel like we were doing enough. And so, you know, one of our, our kind of tenants is for too long, sustainability has been someone else's problem. We think it should be our problem and we should lean in. So we're creating specifically best practices, frameworks. We've established a standard and we've got a version of our standard published that you can consume. We're pursuing and creating certifications in this space. We're doing a lot of work on education, training, and awareness. We've engaged with the World Economic Forum, for instance, and attended Davos. We'll be back at Davos again this year, kind of pushing this message. And what's even more important in the era of AI, which you know, it seems to be an era these days AI is magical technology in some ways, but it's also incredibly energy intensive carbon intensive and e-waste intensive technology. And more and more we're being pulled into conversations and say, Hey, you guys, you're at the heart of the thing. We, we want to do a better job in a green economy. AI is wonderful, but like, it seems to be moving in the wrong direction. Can you guys help? So we're, we're having a lot of conversations about ethical AI. We've actually just released a white paper and are coming out with a conversation about sustainable AI.

Tom Raftery: 5:01

Okay, so seeing as you brought it up, what are you calling sustainable AI?

Ralph Loura: 5:08

Yeah. So, I guess AI is, we're early days. People have seen it do magical, interesting things. I can go create deep fakes. I can create, you know, great content. It's got some issues as well. So we've come out with essentially a framework and the framework, you know, trying to be catchy a bit and, and, memorable is reflect, reframe and reimagine. And the idea is, so reflect is pretty simple. Consider the intended uses and desired outcomes of your applications. It takes somewhere between 10 and 50 X, the amount of power and resource consumption to do a AI enabled search versus a non AI search. Does every search you do really need to be AI powered? Do you really need to use 50 times the amount of energy and therefore carbon or you know, or not. Reframe so, governance is a bit different in the world of AI because I'm not setting you know, because things are happening to some degree outside of my control, perhaps outside of my understanding in some of these models. So. Re-architecting rules, processes, roles and skill sets you know, thinking differently about architecture to maximize the benefits and minimize some of the negatives. And we've heard some of the negatives, you know, hallucinations and bias and things like that. And then reimagine conceptualize new business applications, processes and experiences that are AI, unique to AI's capabilities. So typically when we adopt early technology, the first thing we do is take our existing way of working and then skin it with the new technology. So an example of this might be if your Airbnb come comes out and you're a traditional hotelier, you're going to roll out your mobile app. What does it do? Well, mostly it just scrapes your website and gives you static information on the mobile app, but it takes you five or 10 years. And eventually what you've done is rebuilt it. So now it's my door key and I can chat with the concierge and I can do lots of things with that mobile environment. So reimagining says you want to get to that, that new version faster. Don't just reskin your existing processes with AI. And, and in doing so, you may in fact be able to use AI for good, so to speak more quickly. And then under that we have nine commitments of deployment. Do due diligence on risk, do due diligence on sustainability, do due diligence on ethical usage optimize your data for AI so that you're being efficient there build trustworthy outcomes, drive AI literacy across your company and user base. And then be human first, be inclusive, and innovate responsibly. So, worry about the impact you're having on the organization and people before you do it.

Tom Raftery: 7:47

Okay. And will it be available online? I mean, can I include a link in the show notes, for example, for people who are interested to check it out?

Ralph Loura: 7:55

Yeah, absolutely, absolutely. Like I said, we've got a white paper, it should be up on the website. Actually, if it's not up today, it'll certainly be up by the time the podcast is out. You can get a link for that.

Tom Raftery: 8:04

Cool. Perfect. Great. And talk to me a little bit about standards, because I know that's something that, you know, you guys are quite bullish about. Do you see them as a, a necessary burden or as a potential game changer in how businesses approach sustainability?

Ralph Loura: 8:23

Yeah, I think it's an opportunity, right? Which is, which is a polite way of saying both. You know, I think John Chambers once said education is what you get when When things don't turn out the way you expected. So, so, this is sort of fits that, that criteria a bit. So, so, one, it's an opportunity, right? We, we should be measuring what we're doing, be thoughtful about what we're doing, and unless you're gathering data and, and then organizing it in a way where you can compare it with others it's, it, it's difficult to understand if I made progress.

Tom Raftery: 8:54

Um,

Ralph Loura: 8:54

Back to the UN. The UN established the Paris Climate Accord some decades ago, a set of objectives around carbon reduction and so on. And then they did what they call a stock take, a check in to see how we're doing a few years back. So on the kind of 20th year anniversary, we went, okay, how are we doing? Not surprisingly, not great. So we made some progress, but nowhere near what was expected or what was committed. And part of the reason is, you know, we're not consistently measuring it in a way we're not holding each other accountable annually. And so now they're, they're driving to do some of those things, things more actively. So, so when we set down to set the standard, one of the things we found an old adage I like to quote the great thing about standards are there's so many to choose from. And, and the same, the same is true for reporting. Like, you know, you're reporting for, oh, I operate in the EU so I have to do this. The UK is different, Germany's different. The US, California is different than the rest of the US, you know, so there's a million standards and a million kind of things you've gotta address. So we looked to make it easy. We said, great we're gonna take some of these core standards, we're gonna extract from them the bits that are relative to this conversation. So, so I may have a 28 page reporting standard I've gotta do for my 10 k or for something else. And there's two sentences or two paragraphs on IT, or two paragraphs on carbon. So we pulled them all out into one place. We, we organized it in a way that we think makes sense. There's an environmental, a governance, a societal branch. And each of those branches then allow you to go kind of double click on those standards. And every one of the data elements we recommend you gather links out to each of the standards and where in those standards that you're required to do as well. So, our belief is if you follow our standard and you publish that data, you're going to be 80 or 90% compliant with everything else you need to report anyway, because that data's there and you'll be able to kind of cross link it. And then our commitment is as new things come out, we'll be revising and updating our standard as well. And the beauty is if you're an IT leader you already own the standard, because we've partnered with ServiceNow, and ServiceNow has adopted our standard as part of their core platform. And so you can literally go into, if you're using ServiceNow, you can go in and kind of flip a switch and it can start telling you kind of how you're doing in some of these key areas.

Tom Raftery: 12:19

Nice. Okay, cool. And what about the increasing pressure of regulations and reporting requirements? How are the CIOs that you speak with? How are they navigating these challenges?

Ralph Loura: 12:32

Yeah, it's a, it's a challenge. And I think that's one of the reasons people are coming to us and embracing this conversation is this sense of not only feel like we're going to catch up on the new standards all the time. It'd be great at some point to get in front of it. And we think it's an opportunity here to actually lead, to demonstrate to those standards bodies, to those regulatory groups, hey, we care, we do care about this conversation, and we are compliant, and we are doing this work, because most of the times they'll roll out a new standard, and there's a deadline, but then there's a grace period. You know, it's a deadline, but if you're showing intent toward working toward this, we're going to give you grace. So we think if you've got a, an active forward looking posture around gathering data, driving improvement if you don't tick a box on, you know, on a new standard perfectly, you'll probably get grace around, around evolving to that.

Tom Raftery: 13:23

Okay. Okay. You mentioned earlier the problem of e-waste. It's a, it's obviously a huge, huge problem, especially with the tech boom. And as you mentioned, AI's rapid growth as well. How can IT leaders turn this challenge into an opportunity, or can they to reshape consumption and disposal behaviors?

Ralph Loura: 13:45

Yeah, the production of, and disposal of AI related hardware in particular is driving this, like, through the roof. It was bad enough before, right, with all our mobile phones and, you know, our consumption economy. The carbon emissions and e-waste the global volume of that today is predicted about 120 million tons annually. And by 2050, we think it'll be double what it is today. And 2050 isn't that far away. So the other really disappointing fact is less than 20 percent of that is formally recycled today. So big opportunity day one right now. You don't have to wait for anything technology. Is it like engage with a partner? We've, we've got a partnership with a company called Human AI, great organization globally that will partner with companies and help solve this some of the e-waste stream problem recycling, or more importantly, reuse problem. So, so these guys are wonderful. I tried as a CIO before to donate a number of out of cycle laptops to a local charity. And after six months of trying to go through hoops, I finally gave up. Oh, wait a minute. You've got these under a corporate Microsoft license. They don't have an operating system with them. Oh, wait, you know, like the, the asset tag issue. Like, like, what if something, what if it ended up in a land landfill later and it comes back? Like it was just impossible. And these guys have solved that problem. So they, they take, they strip the asset, they, they, they take ownership of the asset, so it's now owned by them. They then transfer ownership, they solve the operating system problem by some licensing agreements they have as a non profit. And they're doing great work taking, what to us is a three or four year old laptop might be considered no longer enterprise grade. It's got another four or five years of life on it. If you're a, if you're somebody who doesn't have access to the internet because you don't have a computer at home. So, huge, huge opportunity there. Additionally people are starting to do things like, Hey, it's four years, like, computers these days are quite powerful. Do I really need another computer every four years? And do I need a whole new computer? So, you know, I'm very Apple, of course, has been out in front in this conversation about getting to, to, to carbon zero. So, the iPhone 15 Pro is one of the most repairable phones ever made. So it used to be you cracked the screen, in fact, virtually had to throw your phone away and get a new one. Now it's designed and engineered so almost any problem the phone has can be repaired in under two hours at the at the Apple store. So, that's the sort of thing that will get us to where we're going or at least taper off the growth of what's happening is if we can start looking at, hey, how can I extend the life of these? So, for instance, today, people that are buying, you know, that are queuing up and haranguing NVIDIA so they can get their allocation of GPUs to go build their AI farm should be thinking today about what happens in three years when those GPUs are no longer cool, and I want to buy the cooler GPU, where do those GPUs go? Like, is there a secondary use case? And where should I be thinking about those versus scrapping those? And putting them in a landfill somewhere.

Tom Raftery: 16:54

Yeah, yeah, no, absolutely. Yeah. Yeah. On, on the phone issue. It's the, the right to repair is obviously a huge one, but also they're starting to be designed as well for take apart at end of life, aren't they?

Ralph Loura: 17:08

Yeah. Yeah. Yeah, because one of the reasons that so few things are, are recycled is the, the cost essentially to disassemble and sort the bits. And so because because that's a big issue yeah, they're designed now so they're a lot easier to sort into the recyclable component bits so that they can more, more easily be done in an economically viable way.

Tom Raftery: 17:29

Yeah, Yeah, yeah, yeah. It's it's great to see advances there. What about, I mean, you talked about AI and it is a hot topic right now. How should CIOs balance the promise of AI with the the need for sustainable practice, I mean, particularly as, as you said, already with AI, causing so much e-waste and also it's massive power consumption.

Ralph Loura: 17:56

Yeah, yeah so, so again, some of the data essentially since 2012 the AI training runs are exponentially consuming more power. So they're doubling every three and a half, about 3.4 months. I mean, just crazy curve. Even GPT three used about 1. 3 gigawatt hours to train. GTP4 is 10X larger than that. So GTP4 used just, you know, the same amount of power as a small city for about four months of a small city's power, just to train that model. Google AI today burns around 2.3 terawatts of power annually which is as much, as much electricity as it takes to power the city of Atlanta for, for a year. So, it's just kind of like getting your head around how big these numbers are. It's huge. What can you do about that, right? So, so one we've talked about already. Hey, AI doesn't fit every problem. Let's not do, let's not do, do that. There are a bunch of things researchers are doing to improve on that, but both because, you know, it's good for the world and good for the economy, but also, frankly, it's good for their bottom line because it costs literally billions of dollars to train these models. Hey, what if I could figure out a way to do it more efficiently? And so, so one of the things today is, you know, these models on a very oversimplified level are taking, you know, one word in a document, kind of correlating it mathematically to every other word in the document and going to word number two and doing the same. Well, what if I knew three steps in which branch was going to be a dead end and I could prune that branch and not, not, not train that branch. So using techniques like that, you can save, literally you can be 80% more efficient to power consumption and get to about a 90 to 95% as a good model. And maybe that's good enough. And certainly considering the money and the power savings it's certainly worth considering. People are looking at that. There are also solid state models where they're training very differently that are much, much less energy. So we're getting better at understanding that piece. The analogy I would use, and I think the lesson for most CIOs is or IT leaders is it's like the first time you use the cloud all of a sudden there's this like virtually free container or VM. And really cheap storage sitting out in the cloud. And so I could go consume that and it just seemed like, ah, these, it's virtually free resources and they're infinite. This is amazing. And then one day, maybe a month later, a quarter later, two quarters later, you woke up and got a bill from Amazon. Your, your first million dollar AWS bill. And you went, what the, where did, oh my goodness. And, and so then you start applying governance and you start turning off these things that aren't being used and so on. So, same applies here. You turn on AI, you encourage everybody in the company to start using it. And, and I'm getting almost free, my API calls are almost free. And, and almost is the keyword, right? And then one day you go, wait a minute, okay, now we're going to restrict AI to only the legal team and finance because you guys are... so, so, think about that up front. Like, let's govern usage, let's put in smart, thoughtful processes. Yes, you want to encourage use, but do it in a thoughtful way.

Tom Raftery: 20:53

Okay, do you see quantum computers stepping in at some point and taking over AI because they would be, I would have assumed far more efficient at doing some of those processes?

Ralph Loura: 21:05

Yes and no. So quantum computers won't be at the scale for some time. So, so quantum computers are very good at certain things, certain mathematical difficult mathematical problems. But they don't have the massive parallelism that, you know, that GPU, I mean, GPUs win because of the, the sheer number of cores. Just, you know, a convincing number of cores. The real challenge and opportunity with quantum computing, as I was saying, it will do some things very differently. So it'll be good at some things and really poor at other things that current computers are inversely skilled at. The real thing that people are starting to worry about is cyber security as it relates to quantum. And I've started to see people requesting in RFPs and so on, requesting things to be quantum safe. Meaning in the inevitability that quantum computers become more available, today's 256 bit, you know, encryption keys are assuming current computers and it takes, you know, years to, to brute force hack it. Well, under quantum computing, maybe it's hours. So, now what do I do? And I think, I, I don't know that we have terribly good answers to that just yet, but a lot of folks, I think, are worrying about it and, and I think for good, for good reason. We, we know there are state agencies that have literally archived. Terabytes of encrypted data just waiting for the opportunity to decrypt it once the technology is available.

Tom Raftery: 22:28

Yeah, Everyone Ralph loves a good story. Do you have a favorite example of a CIO member, for example, how their sustainability efforts might have led to a meaningful outcome, you know, and what could others learn from that success?

Ralph Loura: 22:42

Yeah, a couple come to mind . So one is maybe not the outcome, but the, the driver. One of the things people struggle with is, how do I get momentum behind an initiative? Like I care, but how do I get everybody else in my company to care? And. I was in Germany and in fact at a meeting in Germany in Jan-Feb last year and spoke with the CIO of the German rail system. And she was saying they countrywide. Germany has an initiative to reduce auto transport by some, I forget the number, some staggering number, like 30 or 40 percent over a very short amount of time, three or four years. That's impressive that as a country, you guys are, you know, rallying behind the cause of sustainability so, so vehemently. And she went, Oh, no, like, yeah, we care, but that's not why. And I said, Well, then why? Well, because, you know, the war in Ukraine means we no longer have access to you know, oil to create petrol, and our whole economy and way of life is at risk if, you know, we don't do something about this. And I went, Okay, now there's motivation, right? It's almost a live or die kind of proposition. And I think so obviously not everybody has that kind of lever but it does remind you that never waste a good crisis, you know, kind of advice. If something is driving change in your industry, some competitive threat is out there, some like find a way to connect some of what you're doing to those opportunities and you'll get a lot more traction of, of going but, but probably the best example, and this isn't a typical example, there's a company we were talking to. And they're not public about this, this, what they've done. So I, I can't mention names, but they were running away for fat in, in Asia and they were trying at a green initiative and they really wanted to use more you know, more, more green power and they, there just wasn't, it's not available in the grid because everybody else wants to buy green power and there's not enough solar or wind in the local, in the local grid. And so they're kind of scratching their head and, but by now they've talked to the, all the generators, they've talked to the. The power grid company, they've talked to their own floor and they started and they gathered a bunch of data and they decided almost on a whim. They said, well, what if we let's go ask AI this problem? AI is supposed to be so smart. And they looked at a bunch of data that they gathered into their AI model and then trained it and did some work. And ultimately they came back with a, an idea that they hadn't thought of. And the idea was, well, what if instead of just trying to buy, you know, reduce power or buy green power, what if we could essentially live in the valleys of, of of demand? And by that, you know, the typical power grid, there's peaks of demand and then there's, you know, valleys of usage. And the notable thing about the power grid, certainly in most develop, developing and developed countries, is there's no buffer capacity. So when you turn on your light switch. It's not like you're drawing power that was stored some time ago and until and while somebody else, you're, you're, you turn that on power is essentially coming out of the reactor over the lines to your house. Like there's no buffer capacity in the middle to speak up. And so, so what they were able to do using AI is look at the the data, the use of power from every machine and device on the factory floor. Match that against the power distribution grid when it was busiest or in least demand and match it against the same with the power generators and they were able to, at the same production output level, the same amount of output, were able to reduce essentially energy consumption by almost 80%. Now they're using the same amount of power but they're using it at a lower cost of power. Because they're using it in these troughs where, where it's demand pricing. And, and, and that, it meant they didn't have to bring another reactor online. They don't have to build another, you know, coal fired power plant et cetera, in that region. Because they're more efficiently using the power when it's available. Which is, so again, not everything is about net reduction of, of carbon footprint or net, like, sometimes it's just, hey, let's optimize for the resource use that's available to us. to prevent the need to go create more.

Tom Raftery: 26:53

Yeah, yeah, no, I think particularly when talking about electricity grids, I think the demand side management is an underutilized possibility resource, whatever you want to call it, because it's not being done enough. But I think going forward, it's going to be something that's going to be very, very powerful.

Ralph Loura: 27:14

There's a former Tesla one of Tesla's early battery scientists and engineers left Tesla and formed his own company. And what they're trying to create is a essentially economical battery platform. So there's more battery storage distributed around neighborhoods. And it's using a very different kind of batteries. It's not the nickel, it's not the The lithium and kinda rear metal kind of stuff. It's using literally rust. It's a, it's using iron oxide to create these much cheaper easier to store kind of batteries that have longer life and are kind of environmentally more friendly, but may help help solve some of this grid you know, this kind of grid imbalance problem.

Tom Raftery: 27:52

Yeah, iron air batteries, aren't they? Yeah. Yeah. Heard about them. Very good. So for your CIOs or for organizations who are looking at this, what kind of metrics or KPIs should they focus on to measure the success of their sustainability initiatives and that, you know, how can they ensure continuous improvement?

Ralph Loura: 28:15

Yeah. So, you know, again, again, somewhat self serving. I would put you back to our standards. I think there's a bunch of them there. And often we'll get the question. Where do I start? You kind of start with what you have. Turn on what you have. Start there. And then look at the areas that where you have gaps. So there'll be a lot of data that you don't have access to, or you have to go create manually, which is fine. Sometimes it's worth doing that, that seed run to go create a bunch of manual data to see where you are on your carbon uses, your e-waste or or, and some, some industries water usage is a big, a big issue and increasingly an issue in, in the AI conversation because. It used to be located your data center near the fiber optic lines because you wanted low latency to the internet. And now you locate your data center where there's power. Because you need to power these big, big, big AI farms and AI farms. Basically, one of the problems in computing is power translates to heat because these things dissipate a lot of heat. And now we got to cool that. So now I'm running water through to cool it. And in some rural areas, all of a sudden the little data center that got built, you know, in the prairie is consuming 10% of the water, of the, the local municipality. So, big issue. So, so look at what matters to you. Begin measuring that, and if you're doing it manually, fine. But then find a way to automate that. Find a way to begin accessing that data in a, in a, in a more automated way. Because over time that's what really helps is this, it's the, the. Looking at the chart and looking in the trend and understanding what you can do about making the needle move in the right direction.

Tom Raftery: 29:47

Okay, cool. Nice. Quick left field question. If you could have any celebrity or fictional character as a spokesperson for your project, who would it be and why?

Ralph Loura: 30:05

That's a good question. It is bit left field. You know, there are so many kind of celebrity spokespeople that I think, you know, in certain topics, people, people get aren't particularly amenable to that. If I look back historically what I would say is somebody politically, if I go back to like, like US president Roosevelt, who looked at a big problem you know, the global recession depression, Great Depression, and didn't try to solve it in a kind of haphazard way. He thought, really, you know, thought it through and said, Hey, we're going to create a social safety net. We're also going to put people to work, to do infrastructure projects. We're going to pay them for that work. They're going to have pride and ownership of what they've built, they didn't get a handout. So he thought about the problem in this sort of circular way. He looked kind of at the circular economy and said, how do I solve all the problems we're having? Not just the surface level of the problem. And that's really what we're trying to do is like, look at the holistic problem and provide holistic solutions, not, not just easy solutions kind of off the top.

Tom Raftery: 31:08

Nice, good one, yup I like it. We're coming towards the end of the podcast now, Ralph. Is there any question I did not ask that you wish I had or any aspect of this we haven't covered that you think it's important to make people aware of?

Ralph Loura: 31:22

Yeah. the one thing that we have, the area we haven't gotten into which I'd used to be quite happy to avoid is the area these days of politics, right? And geopolitics is unfortunately becoming a bigger part of our lives because behaviors are driving a lot of things. And one of the things that's happening in the US and increasingly spreading to the EU is this sort of ESG backlash. In the US, there's this backlash against what they call the woke agenda and a bunch of other things that we're getting lumped into. And so, so, you know, what should we do about that, I guess, would be the question I would ask. And I think how I would answer that is it don't, don't kind of, don't let people paint us into a corner. Don't let people tell us what we stand for. We, we aren't you know, just out there, do gooders out there, like, trying to save the world kind of thing. Most of us are, you know, we're practical people that have businesses to run or businesses we contribute to. And what we're doing is we're doing what we're doing we think is smart and, and ethical and reasonable for not just the short term profit and benefit of the company and the world, but also the long term profit and benefit. So, don't let people frame you in a corner, like reframe the conversation around the other reason we're doing, you know, we worry about carbon footprint is among other things, I can be a more efficient at consuming. power. I can also, if I operate in a world that's increasingly hotter and increasingly more polluted, what does that do from the long term health and benefit of my company, employees, customers, et cetera. So, like, we're just thinking we have a longer term lens than you do if you're not worried about those sort of things. And so reframe the conversation away from politics and more toward Hey, we're doing this because like we're trying to be thoughtful, smart people about the work we're doing, and we're trying to create positive outcomes for our customers and communities.

Tom Raftery: 33:11

Super Ralph, if people would like to know more about yourself or any of the topics we discussed on the podcast today, where would you have me direct them?

Ralph Loura: 33:20

Yeah, first of all, sustainableit. org. You can read up on much of what we've talked about there and, and stay connected for future updates as we release more more information and so on. I can be found fairly easily on LinkedIn. It's just Ralph Loura, L O U R A. And I'm happy to connect there and and see if we can further each other's missions.

Tom Raftery: 33:39

Tremendous. Ralph, that's been fantastic. Thanks a million for coming on the podcast today.

Ralph Loura: 33:44

Thanks Tom, I really enjoyed it.

Tom Raftery: 33:46

Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about the Climate Confident podcast, feel free to drop me an email to tomraftery at outlook. com or message me on LinkedIn or Twitter. If you like the show, please don't forget to click follow on it in your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.