The Importance of Responsible AI in Green Software

In this episode of Environment Variables, we cover the State of Green Software Report with the Green Software Foundation’s very own lead researcher Tamara Kneese. She and host Chris Adams delve into the insights from the report including key topics such as the carbon footprint of crypto mining, regulations for generative AI, and the role of consulting firms in shaping emerging technologies. They also discuss how the results highlighted the impact of the tech industry, AI sustainability, and the need for responsible innovation. To find out just how interesting the results of the survey have been and everything in between tune in now!

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TRANSCRIPT BELOW:
Tamara Kneese: I think there's much more of a sense of urgency from policymakers, from advocates, from activists, from researchers, scientists who are looking at the numbers and looking at the data and thinking, we really need to do something now. And I think it's all part of the same general wave of really trying to find a way to live with tech in a way that is more sustainable, in a holistic sense, in a way that is actually good for people and for the planet.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, the podcast where we explore the world of sustainable software development. I'm your host, Chris Adams, and today we have a fascinating conversation lined up for you. Joining us today is Tamara Kneese, the lead researcher at the Green Software Foundation.

And today we'll be diving deep into her involvement in the groundbreaking state of green software report and at the Green Software survey for 2023. This survey aims to shed light on the current landscape of green software and the challenges and opportunities it presents. In this episode, we'll explore tomorrow's role in designing the survey, her research findings, and the implications for the future of sustainable software development.

We'll dive into the various insights provided by the survey that includes in identification of specialist green software tools, the progress made in decarbonizing software, and the potential of software to contribute to renewable energy infrastructure. So whether you're a software developer or an environmental enthusiast, or simply curious about the role of technology in shaping our planet's future, this episode is for you.

So that's me being talking for a while. Let's welcome Tamara Kneese to Environment Variables. Tamara, the floor is yours. Please introduce yourself.

Tamara Kneese: Thank you, Chris. So I'm Tamara Kneese and I'm the lead researcher at the Green Software Foundation. Very excited to be here with you. I'm an academic with a background in media studies, science and technology studies and gender studies. And now I'm about to start a new role as the project director of Data and Society's newly launched Algorithmic Impact Methods Lab.

Chris Adams: Wow. Congrats. That's a new development. This is how I spoke and that's, oh, I'm really glad to hear that actually.

Tamara Kneese: Thank you.

Chris Adams: Cool. You're welcome. Yeah. Okay. So if you have not listened to this podcast before, my name is Chris Adams. I am the executive director at the Green Web Foundation, and I work at the Green Software Foundation as the co-chair of the policy working group, which is where I met Tamara, and where we end up seeing each other on a more or less biweekly net basis. All right. Thank you for introducing yourself, Tamara. Before we dive into the State of Green software survey, I just wanna check anything we talk about will do our best to share links in the show notes like we do on a regular basis. And I think with that, we should probably go get into it, shall we Tamara?

Tamara Kneese: Yeah.

Chris Adams: All right. Okay, so the first thing, for people who've who are new to the whole Green Software report and the accompanying survey, could you maybe just give us an overview of the survey and the objectives please?

Tamara Kneese: Yeah, so I think it's worth noting that the entire process was actually quite lengthy. So we started doing preliminary survey design and other kind of necessary background research and work in Q3 of 2022. And we really were collaborating across companies and fields of expertise and knowledge. So basically a group of us who were part of the policy working group at Green Software Foundation came up with 25 questions that we thought captured really key information like demographics and other data to understand the level of awareness and adoption, points of friction, and also green software enablers from the perspective of software developers. So we were trying to go beyond the the surveys that are out there already of C-Suite and venture capitalists, and we were really trying to understand what was happening on the ground.

Because in order to make green software successful and scalable, we have to meet developers where they are. And we also wanted to leave some room for developer feedback, and I personally found this to be the most exciting and fascinating part of our findings because developers wrote in their own ideas and their own experiences and even frustrations, and through their feedback, we can really better understand the gaps between leadership or corporate goals and what developers are actually seeing and doing on the ground, and hopefully we can help to bridge that gap.

Chris Adams: And as I understand it, there was a fairly decent size chunk of the survey, went out to quite a few people and you had a substantial number of responses. That's my understanding of it, right?

Tamara Kneese: Yeah, so we had over 2000 responses in total and people from all over the world, which is great. And we also heard from developers from a broad range of companies. So we heard from people from the large companies like Microsoft and Intel and also from smaller companies and startups, and we actually reached a few people who are outside of our own core membership of Green Software Foundation.

We reached people through LinkedIn and through social media, even through Mastodon, which is lovely. So, And so people found us in a variety of different ways. So we really had a great range. And in order to kind of contextualize the survey findings, we did a lot of background research. And so while a lot of the insights are prompted by the survey results, I was also looking at the latest research reports from firms like McKinsey.

And also at leading academic journals, really sifting through what is the cutting edge kind of research on green software in the present moment. And we also did some background interviews and conversations with thought leaders from across the green software space.

Chris Adams: Okay, so I remember this being quite an undertaking actually, and uh, there was a number of people involved in this actually, who was, who involved, I remember being on a series of the week of the weeks, maybe it might be a nice time to just quickly name check some of the people. I think it was Zane who was involved on some of this and I believe shout out to Ismael as well, who's also doing some work as one of the researchers on some of this as well as basically various other people inside the policy working group. You said something interesting about the fact that you had like a decent number of people. That's a lot of free text to be like wading through, right? For all the kind of questions you had from there surely?

I.

Tamara Kneese: Yeah, so that was really quite interesting because analyzing the survey results, particularly when you have a lot of write-in material to wade through for 2000 people and clearly not everybody wrote in lengthy comments. Some people just filled out the survey questions and left sections blank, but it was still quite a bit of material and it was really interesting because it provided more sort of nuance and context that kind of, and some people actually almost included a meta commentary on why they filled in results the way they did. And they were like, I'm answering this question with my organization's priorities, not necessarily my own. Just to really provide a little bit more insight into why people were answering questions the way that they were.

And yeah, it, this was also, like I said, deeply collaborative. So Zane was my graduate intern at Intel and he helped with the survey design. Ismael was very much involved with carrying out a lot of the desk research and also with the survey design process. And I believe that he also did interview a number of green software thought leaders as well.

And then we had feedback from a number of people on who were part of the policy working group. Chris, you were there, and Lisa and Elise, and of course Asim and many others was providing feedback all along the way.

Chris Adams: Okay, thank you. And maybe it's briefly worth just talking a little bit about the goals, what we were trying to achieve for this, cuz it does seem a little bit contrived to me asking this cuz I remember writing one of the proposals to try and get some of this involved. But I know that this was something that you had to take and run with quite a lot actually.

So maybe if you just might expand on some of the particular things we were trying to shoot for this, then I might be able to chime in on some of it before we start jumping into the meat of the report and some of the real particular interesting insights.

Tamara Kneese: Yeah, absolutely. So one of the main goals was really to raise the profile of green software, and I was really interested to see the percentage of developers who actually had some degree of awareness. And so it makes sense that a lot of the people who filled out our survey already were somewhat aware and already interested.

Although there were a number of people who replied in the comments that this was the very first time they had been exposed to green software. And so by putting out this public report that can be taken up by the press, that can be taken up by policymakers, that can be taken up by academic researchers.

It is a way of really, getting the word out about green software, thinking about the report as a mechanism for evangelizing green software is really part of what we wanted to do. And we also wanted to understand after knowing that 92% of developers we surveyed said that they were concerned about climate change and wanna do something about it.

So what do they need to actually make that happen? What resources, tools, and other forms of support do they need to take action? And another key element of this is reaching out to ICT industry leaders to the C-Suite who really wanna know how and why they should make green software part of their organization.

And really trying to emphasize the business case for green software from their perspective was another really key part of this survey.

Chris Adams: Yeah, I remember actually that being one of the things that we were speaking about, cuz one, one of the kind of key. The reasons that we would try to actually get some funding and add a time and money to actually do this research was that it just made it we want to make it quite a bit easier to have conversations with people or give something just a few links that you can use when you're making an argument and like you can see some of this manifest in the shape of the report.

So typically when you might have a report, you might have maybe 20 to maybe a hundred pages that you might like slap on someone's table or something, but whether people actually read that or actually engage with the content is another matter. And this is probably reflected in the design, the fact that rather than having a long narrative that you'd run people through, it was made up of a series of like smaller insights that you could share for this.

And this is one thing that was, I think it was, it was a decision made quite early on, but it's still quite a lot of content. Like for 30 insights, that was quite a high word count by the looks of things. Maybe you could expand on that part there before we dive into one or two of the insights that caught your eye and my eye.

Tamara Kneese: Yeah, at some point I started doing a word count assessment looking at all of our various Google Doc collection that we had created. And yeah, in total there were around 13,000 words, which is a pretty substantial report and pretty much equivalent to what a standard sort of report would be from something like McKinsey.

And I think the trick was that we really wanted it to be digestible. And so breaking it up into smaller segments and making the website a bit more interactive, which was as them's idea, by the way. And also huge shout out to Osama, the Web developer and also our project managers for keeping track of all of this.

So both Anita and Oleg did a huge amount of work and is managing expectations and making sure that we were able to get all of this content into segments that were understandable. And Namrata also had a huge hand in editing the insights to make them more public facing. So she had a really great eye for figuring out how to frame particular insights to make them appealing to different kinds of audiences.

So for trying to reach somebody in the tech press, if we're trying to really appeal to C-Suite, if we're trying to reach developers, versus academics. What are the kind of key words and terms of phrase that really appeal to different groups? So we were thinking very much about audience as we designed this as well, so,

Chris Adams: Okay, cool. For anyone who is curious, you can visit it at https://stateof.greensoftware.foundation. But don't do that just yet. Cause we're about to jump into talking about some of the particular. Insights so you can hear about it directly from the source, as it were. All right, Tamara, if there's a particular insight that you would direct people to first, which one would you suggest or which one is like the ones that you found found most interesting to, to look into, for example,

Tamara Kneese: So I thought the ones that we included around both responsible AI and about the need for measuring carbon emissions as part of scaling sustainable AI, and then also finally our insight around decarbonization not being enough and really thinking about environmental impacts and social impacts and tandem with decarbonization goals is something that I thought was really important.

And it's worth noting that when we created this survey and when we sent it out, it was right on the cusp of ChatGPT and all of the hype around generative AI. So we, we didn't have any questions directly asking people about that, but from the comments you could see it beginning to percolate and there were a few references also to Web three and blockchain.

What has been really interesting for me is watching as AI has really come to replace crypto in a lot of the discourses around the environmental toll of information technology and a lot of the conversations that we heard about NFTs and their environmental impact. Now we're hearing about the environmental impact of ChatGPT and other generative AI.

Chris Adams: And you see the same patterns with influencers in LinkedIn. Everyone's just switched. I'm an expert in metaverse and crypto to, I'm an expert in AI now. Yeah, so you do see that actually. Okay. Maybe we could dive into one of the particular insights here, the insight that that was a takeaway, and I'll just link specifically to the URL in the show notes.

Measuring carbon emissions is crucial for scaling sustainable AI. Now this one here, we, you were talking about the fact that the world has moved. You know, a lot has happened since we saw this, and I couldn't help notice that your new role is actually to look at a bunch of this stuff. Are there any things that you, dr- what, what do you think has been the biggest change since the initial research and what you're seeing maybe in. June, 2023. Cuz in my view there's a few, there's a number of really significant changes. We've spoke about how this influx of open source models has come in, but also there's a real push for transparency in a way that there hasn't been.

But also you see some of this regulat regulation like taking place or kind of taking shape. Now maybe you could like elaborate on some of that stuff actually.

Tamara Kneese: Yeah, so clearly we have regulation coming out of the EU especially, uh, that is very much looking at things like the carbon footprint of different models, but also thinking about social factors and relationship to things like emissions or water use. And what's funny is, so in one of the insights, the one that you just pointed to reference research by Hugging Face, and they were looking at.

The life cycle analysis of their bloom model, which by the way is still way less impactful from a carbon perspective than other models. But really thinking about it, not just in terms of training and the emissions connected to the training itself, which is often how this is calculated, but also looking at all of the emissions tied to the manufacturing process for the equipment.

Uh, that facilitates the training and production of AI and also thinking about deployment. What are the emissions connected to use in the real world? And I think that this is going to become more of a standard. So as regulation catches up to where innovation and technological production are going, I think we'll see much more of a demand both on the part of regulatory bodies, but also from consumers, and presumably also from developers that really want to know the numbers and who want to know what the true impact of these technologies will be.

Chris Adams: I'm really late to the party and I just spent this weekend looking at some of these, look at some of these tools for the first time in a while. I know that Hugging Face, they have got their own kind of equivalent. Something like ChatGPT with the idea being that you can swap in different models. But the thing that I realized, and I figured it, My, I could ask, while you're here I'm gonna ask you. I really don't know what to, what even units I would use when talking about this. Like for example, when you talk about a website, people talk about maybe the carbon footprint per gi- megabytes sent over the wire and that has all kinds of issues in its own right. But I dunno what I would even use when I'm talking about this.

For things like say AI, right? Do people measure carbon on a per token basis or per question basis? This is something that I'm out at sea right now cause it feels, I dunno if it's well understood enough to even have a unit yet or something representing this functional unit that you might use to talk about this.

Tamara Kneese: Yeah, I, I haven't seen anyone come up with a sort of industry-wide standard yet for how to even talk about measuring uh, impact in this way. And so that will actually be quite interesting to see if the regulatory push forces the industry to come up with better standards because that, that's been the way things have worked in general in terms of calculating emissions and thinking about scope three emissions and all the things that were always tricky and very hard to measure. And I think especially because we don't fully know how generative AI will be used. So obviously there's been a lot of sort of movement towards incorporating different models into things like search engines,

Chris Adams: Yeah. Okay.

Tamara Kneese: um, and so, yeah.

Chris Adams: alright, so with that, so maybe we don't end up with a particular unit, we just see like an uplift in the same way that, let's say you've got like a coal fired power station and you're gonna make that carbon capture and storage using like a third of it. You just have a multiplier. Maybe it's something like that cuz this is one thing that I believe was referenced pre previously. The idea that, let's say, and like you just mentioned just now, about integrating LLMs into search. The fact that I'm just speaking to a robot rather than actually seeing the underlying sources, that is, that changes my relationship to the data that I'm actually able to access, for example.

But there is often an uplift in, for example, if I'm using say, an LLM Enabled search compared to a regular search, there's gonna be a multiply of maybe 1, 2, 3, some kind of figure. I know that I think the wide has an article that we've linked, which has a fivefold increase, but it could be, yeah. We basically don't have the numbers for this yet.

Maybe that's the way we talk about it. Hm.

Tamara Kneese: Yeah. And that I, yeah, the, that is the number that I believe we even linked to it in one of the insights as well. But it is interesting when we start trying to quantify these things, and that's another interesting connection to what was happening with figuring out, say, Bitcoin emissions, where you would often find articles saying the Bitcoin mining industry is equivalent to all of the emissions of X country or Y country and really trying to figure out what the true number is can be, can be a bit tricky. And, and then there's also maybe a point at which nobody even cares anymore. Does calculating the exact number, does it help in terms of, uh, making people, yeah.

Chris Adams: is it good or bad? Because this is, you're right, this is the thing that comes up again and again when you've seen numbers used, I don't know, I've done this and I've done, and it's created 10 tons of impact. That does beg the question. So what is the acceptable amount of impact that you do want to actually have in order to actually, uh, benefit from whatever is being provided here?

And that question there is seemed to be a very difficult question that. I think it's very hard to engage with when you see these discussions a lot of the time, cuz a lot of the time we don't necessarily have the literacy outside of technology to even make a comparison.

Tamara Kneese: Yeah, totally. And then that was another interesting question that came up too, in terms of balancing different kinds of considerations, especially when it comes to things like AI that might take a massive amount of energy, but also a massive amount of water. How, if you're trying to optimize for less water usage, it might actually conflict with your attempt to optimize for less energy

Chris Adams: and carbon. Yeah.

Tamara Kneese: And how do you balance that and how do you make a call about what should actually be prioritized?

Chris Adams: This is especially the case when you think about the supply chain, right? Because let's say your example here, I'm going to not use something which is using water locally, and as a result, I'm gonna use a lot more energy to actually account for that because for basically the largest use of water in most countries is actually coming from cooling.

It's actually from the actual thermal generation, like burning fossil fuels to heat up water, to turn a turbine, to actually generate the power. You end up in many cases, just moving some of the wa- usage into other places. This is one of the things that is, one of the takeaways I found was actually it's very much about the locality of where it's taking place.

So if you are in a city and you have a data center which is ha- is using lots and lots of water and it's pulling from an aquifer that everyone is drinking from. Yes, that's gonna have an impact in the same way that it's gonna impact, say the cost of electricity, or it can impact the cost of electricity compared to something happening further out.

If you're bringing in power from say, across a national border or something like that. This is why, I guess it's, in many cases it can be quite complicated and why I'm glad there is an actual report exploring some of this. So maybe I wanna ask you, we spoke a little bit about AI and I suspect we might come back to that again cuz it's the topic du jour.

There was also another insight here talking about Web three rings, the alarm for green software practitioners. Now I figured it'd be good to ask you about this cuz you have done a lot of research and this, so you authored another report around this. So you've got like some form and some, some background on this.

So maybe you could explain, maybe expand on this one here cuz this one caught my eye and I think there's a few interesting talking points in this one too.

Tamara Kneese: Yeah. And with crypto we did see a lot of legislation that was very much concerned about the carbon impact of Bitcoin mining particularly, but also of crypto mining in general. And it is interesting that with Ethereum, the shift to proof of stake and really lessening the carbon impact by over 99%. This was prompted, of course, by a lot of the public opinion and news stories about the harmful effects of NFTs on the environment and how can you claim to be creating this kind of technology for good that will lead to empowerment of marginalized communities and decentralized payment structures if you're also responsible for, all of these carbon emissions? And what's interesting is that as certain countries or states banned crypto mining, the crypto industry moved into different locations, they found workarounds. They partnered with existing energy companies and infrastructures. And so with generative AI in particular, it will be very interesting to see what effects the new wave of regulation has on practices. So how will companies find workarounds? How will, how will they change their practices to accommodate new laws and regulations?

But will it change the landscape of how, you know, development is happening?

Chris Adams: That's a good point actually, cuz when you think about, just like from a really kind of operational level, one of the reasons people have been talking about some kind of proof of work, cryptocurrency, like proof of work mining was the idea that yes, it loads of uses lots and lots of power. But I can turn it off and it's really plausible.

That's the idea. And there are lots and lots of parallels to essentially the extensive machine learning you might use for training. That's not something which is particularly latency sensitive. So you can see a lot of the same ideas being applied to this. So maybe you do see something like this. Maybe that is actually a new role we have for, I guess like may, maybe you can end up seeing AI just move directly into that kind of slot as you suggest actually.

And I guess maybe it might be worth actually talking about the role that consulting firms play in the role of this. Cuz if 12 months ago we had the whole thing about how the Metaverse and Web three were gonna be like the next big thing, then they turn out not to be the next thing thing. And now they are.

And now they're not. And then maybe this is one thing that's, we might. Look into the roles for this, cuz like you said, there was a real push now and I wonder if we're going to see a flip again now that we've seen like Apple release, another take on something which might be like a metaverse after we've seen Facebook burn through literally tens of billions of dollars on this stuff.

Tamara Kneese: Yeah, absolutely. Uh, I think it's really interesting that McKinsey in particular had these reports on the metaverse and also on crypto more generally, and how they would transform the industry and they would be worth between. X trillion and y trillion dollars. You know, it was, it's always in the trillion range and nobody really knows how these numbers are calculated or where they come from, but there's a lot of enthusiasm and I do think it creates the environment for a lot of kind of poorly thought out businesses, decisions to be made.

And so what I noticed with Web three, particularly among a lot of large tech companies, is that they were all trying to keep up with each other in connection to crypto, and they were like, we don't really totally understand this thing. But we think it might be important. There is clearly a lot of money in it, and so how do we follow the headwinds and make sure that we are keeping up on this new crypto thing as much as possible?

How do we talk about Web three or decentralization within the context of the enterprise? Then suddenly after the crypto crash and all the various scandals, the collapse of Silicon Valley Bank, there's a moment of disavow or denial like, ah, we're done with that. Toss it out. We don't need to invest in that anymore.

And you know, that's not great if you're in business decisions based on McKinsey's honestly, very dubious speculations about how much money a particular industry will be worth in the future. I think we were all hit over the head with the metaverse as a trend that we should all really pay attention to and care about, despite the fact that it was really just meta pushing this very particular vision of what the metaverse would be.

And maybe I'm speaking too frankly here, but I do think the problem that I'm seeing right now with the AI landscape is that companies are doing the same thing, and so they're all trying to out compete each other and make sure that they're hiring a lot of people who are AI experts and really making a push for AI to be the next big thing.

McKinsey also agrees that AI will be the next big thing, but we don't know yet what the uptake will actually be or what it will look like in practice. And I think with Web three, one of the largest issues is that there were just weren't very many use cases that made a lot of sense. And things like the carbon offset market, or one place where Web three really had a hold and as we saw from various news reports and studies,

Chris Adams: There wasn't much there. There.

Tamara Kneese: There that was all fluff too. And most of those offsets were not valid and even attempts to create standards in the space did not necessarily protect against fraud. And so the worry is that with some of the potential uses for generative ai, perhaps.

They will not play out as McKinsey or other consultancy firms are saying right now. And perhaps there's a different way that they will be used, but we don't yet know. And so I think a lot of the kind of push towards financial speculation and investment could lead companies down a bad road if they overinvest in things that are actually not going to pan out.

Whereas we do know that regulation is on the horizon. We do know that. Things like ESG are really prompting, not just consumers, but also investors and shareholders to take more activist stances on things like the environment and so I think paying attention to the things that are real is actually more important than trying to imagine some sort of speculative future.

Chris Adams: So more science and less tech bro FOMO, right? Yeah. Okay, great. That's actually, that's a, that's, thank you for sharing that actually, cuz this is a nice segue into, I was, did wanna have a go whole discussion and point everyone to this piece about McKinsey and company and AI and the, there's a really fantastic piece by Ted Chiang Chiang who spokes about talking about the idea of essentially AI as the next, as taking, filling in the same role that a management consulting firm might actually come in.

So you'll come in to help you in many ways justify some of the decisions you might be making anyway, or to help pro help support some of your priors that you might actually have. So if you have tech mo, tech bro FOMO about LLMs, then there's, it's really helpful to find someone to say, yeah, that's gonna be the case.

Cuz if you, cuz we can see some of these elsewhere, but I feel that some of the things with LLMs and should we just call it applied statistics? Cuz in many ways that's how a lot of it does actually feel like it's, do you know how like you have like autocorrect on your type on your phone and you just press buttons randomly you'll come up with sentences? I don't wanna call it ice spicy or a spicy autocorrect. Cause that feels like it's, that's not particularly fair, but I think there is some truth between these two things of having this being this biblical new techno technology and something which is somewhere else. And you spoke a little about regulation coming in, cuz this feels like it's one of the big drivers right now and this is one thing that was actually touched on in the report, a particular thing we're saying legislation is quadrupled in the last decade. So like this big swell of new laws and I guess a new enthusiasm for civil society to be part of this discussion rather than it being just accepting what's coming in.

Maybe you could expand on that a bit more actually tomorrow.

Tamara Kneese: Yeah, I think in general the tech industry, obviously really benefited from the pandemic and a lot of, so companies that were already doing really well started to do even better. But for a long time now, the tech industry has really dominated the economy in a lot of ways. They. Tech dominates the stock market.

They have an outsized impact on the economy and they've become a major seat of political power. But regulation really has not matched the pace of change within the tech industry and how quickly the tech industry has really become a very powerful entity in a global context and I think that what we're seeing with regulation right now is an attempt to rebalance and figure out how can we keep the things that we like about what technology affords us, but how do we make sure that it's not doing anything really harmful that wasn't really anticipated when these companies started? And so thinking about one obvious example would be Meta's influence on political elections and the spread of propaganda that can lead also to violence. And so beyond misinformation or disinformation, but also thinking about real world effects.

Chris Adams: referring to Burma and Rohingya people. Some, some of the, the violence. Yeah. Okay. I see.

Tamara Kneese: Yeah. And so thinking about the ways that companies that are built for one particular purpose then have an effect in ways that were not really an intended output of the technology itself. And so, I think what we're seeing right now is a way of attempting to mitigate harm and the environmental toll has become a focus in light of the climate catastrophe that we see unfolding all around us and with new reports from the IPC and thinking about the very short window that we have in which to act.

And I think there's much more of a sense of urgency from policymakers, from advocates, from activists, from researchers, scientists who are looking at the numbers and looking at the data and thinking, we really need to do something now. And I think it's all part of the same general wave of really trying to find a way to live with tech in a way that is more sustainable, in a holistic sense in a way that is actually good for people and for the planet.

Chris Adams: So hopefully finding a way to avoid a second gilded age and avoid to go from there straight into a burning age. Yeah, if you've, okay. All right. So that's one. So that's one thing we've looked into, and I suspect, I know that we've covered this on pre previous episodes before about how we're seeing some changes with, in Europe, like the corporate sustainability reporting directive. Actually that's one of them. And some of the recent laws there about basically getting organizations to disclose energy usage and disclose their resource footprint in a way they haven't had to before. You do see this kind of in this shift here actually, which is not something that we've seen something before, but, and I dunno if we have enough time to really talk about things like the role of like antitrust and organizations moving in and talking about, okay, if you have these large organizations, where are we actually redirecting all of the surplus?

Given them that we're in the middle of a literal emergency in some cases actually. So maybe this is one thing we could briefly just like close clo close out on actually, because you mentioned that there is dry, there is interest from a number of organizations or there's a number of different places you said there's pressure from staff, there's pressure from investors and you, and there's pressure from the regulators. Alright, Tamara, so we spoke a bit about regulation and. I'm a European, despite sounding like someone who isn't a European anymore. But one of the key things that we see, or comes up again and again is how you really see this appetite in Europe and to a lesser extent, the UK with things like the competition and markets authority, talking about getting organizations to be a bit more explicit about green claims, but we don't really hear that much about what's happening in America. And I know there, there have been some changes from the investor level, like the SCC and organizations wanting to be somewhat aware of their climate exposure, which is why you might wanna where you find CIOs being asked about digital footprint and stuff. But I wonder if there's anything else that you've seen on the horizon in America that might also suggest that yeah, there's actually there are changes coming down in America that people might wanna prepare for if they're technologists and like thinking about how this new world impacts the world of software, possibly even AI cuz that's one of your special, your areas now?

Tamara Kneese: Yeah, it's a great question and I, I think certainly quite a bit of movement in the US. And I think it is in part an attempt to catch up with regulation that's been happening in Europe. And everyone I know who's in the AI policy space here in the US is certainly paying attention to everything that's happening in the EU right now.

But one sort of development was back in October, The Biden administration and Alondra Nelson, who was working for the Biden administration, put out a blueprint for an AI bill of rights. And so really thinking about what it means to assess the impact of algorithms on civil rights. We also have a, a new sort of report and area of inquiry from the National Institute for Standards and Technology.

And they're looking at trustworthy and responsible AI, and they're assessing AI based on a number of different factors, including things like reliability, safety, security, and resiliency, accountability, privacy, fairness. And what's been interesting is that sustainability isn't always mentioned in a lot of these different policy recommendations for responsible ai, and I would argue that is something that we definitely need to have on horizon, is really being able to talk about the impact of AI on marginalized communities in a climate context as well. And that's something that another sort of beyond the policy kind of landscape.

Another interesting development would be groups like Amazon employees for climate justice which the seat of power for that is largely in Seattle and in the US in general, but these Amazon employees who were really pushing for Amazon to pay reparations to Pakistan for all of the devastating flooding there because of Amazon's role in climate change, and also making a connection between Pakistani American workers who are on H1B visas and really thinking about precarity in a labor context in conjunction with the catastrophic effects of climate change on people in the majority world. And I think we're going to see more activism like that probably from people with tech companies who are working with climate activists, environmental justice groups, people who are really being impacted by technology, and that is something that I'm certainly seeing even in academic communities.

So there are a number of kind of academic conferences, or even at places like Mozilla Festival where you have academic researchers and people at different sort of AI related nonprofits and policy think tanks who are bringing workers into conversation or bringing marginalized folks into their research conversations and treating them really as co-authors, as co-researchers, not as like subjects.

And so thinking about having people who participate in Amazon Mechanical Turk and other forms of micro labor on platforms. Actually bringing them into academic panels and having them carry out research on their own, that can also be taken up and used to influence policy as well. So really working from a really bottom up understanding.

And I think that's what we were attempting to do also with our SOGS report, is think about including a more bottom up perspective. So instead of just listening to what McKinsey's saying, or just listening to what venture capitalists or a C-suite or saying, also really taking a hard look at what the pain points are for people who are either building these technologies or interacting with them on a daily basis.

Chris Adams: Okay. Wow. God, there. I thought there's gonna be a lot to take into account for future Green software reports. And when we talk about where the boundary of influence might actually be for this, rather, not just the operational impacts, but the other things that it might be enabling. Okay. I think we've, just taking us up to a time here, before I say thank you, I just wanna ask, there are 30 different insights in this report and we've covered a bunch of these things.

If there is one thing that you'd ask people to start with, which one would it be and why?

Tamara Kneese: So I, I think the responsible AI is green AI insight is very,

Chris Adams: one. Yeah.

Tamara Kneese: Yeah, and you know, because it really gets at this need for a much more holistic understanding of what green could be, and I think it really gets at the need for a lifecycle analysis and an examination of entire supply chains and the effects of technology supply chains on marginalized communities. And that's something that I think many of us at Green Software Foundation at Green Web Foundation, we talk about these things, but how do we prioritize working with communities and that kind of collaboration in the kind of work that we do, even within our own organizations, within our own companies? And that's something that I think really could use a lot of attention.

Chris Adams: Okay. Thank you for that. That's a definite food for thought and I, this is, I really hope we do get to look into some of that more in future reports that come out from this. Tamara, thank you so much for giving us the time, uh, on what ended up being a public holiday. I really appreciate you doing this, and next time we'll make sure we don't actually have it booked up.

Booked up for this quick break. That's all for this episode of The Week in Green Software. All the resources for this episode are in this show description below, and you can visit podcast dot Green Software Foundation to listen to more episodes of Environment Variables. Tamara, thank you very much for that.

I really appreciate you sharing your insights with us. I wish you a lovely rest of the day and yeah, have a lovely week. Take care, Tamara. Bye.

Tamara Kneese: Thank you, Chris.

Chris Adams: Hey everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, 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'd love to have more listeners.

To find out more about the Green Software Foundation, please visit https://greensoftware.foundation. That's https://greensoftware.foundation in any browser. Thanks again and see you in the next episode.