In this episode of Environment Variables, host Chris Adams delves into the fascinating topic of the rebound effect with Vlad Coroamă, founder of the Roegen Center for Sustainability. They discuss how improvements in efficiency can sometimes paradoxically lead to increased consumption, using examples like teleworking and online shopping to illustrate the point. Through their conversation, they explore why this happens and what conditions make it more likely. Their insights shed light on the complexities of balancing technological advancement with environmental sustainability, offering valuable perspectives for anyone interested in building greener digital services.

TRANSCRIPT BELOW:
Vlad Coroama: When there is rebound, but if your digital service makes the activity sort of more affordable or simply more desirable, and it will be consumed more, but it will have changed in such a way that the footprint of the new activity, the modified one, is much smaller than the original one. And then although you might have rebound, the overall balance will be net positive.

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. Where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, the notion of efficiency comes up quite a lot. Take two forms of efficiency explicitly called out by the Green Software Foundation, software efficiency and hardware efficiency.

In the first case, you're talking about how much energy is needed to perform a given amount of computation. And in the second case, you're talking about how much hardware might need to be created by extracting material from the environment, refining it, then turning it into electronics that we run computation on.

In isolation, it's quite hard to argue against efficiency, and we can point to literally years of data showing how increases in efficiency in computing have blunted what might otherwise be eye-watering increases in the amount of energy consumption and other resources we have gone through in absolute terms.

Thing is, efficiency has second order effects too, because making things more efficient can make them more accessible too. Increasing the number of people who can use them. And we can point back to published work in 1865, observing this happen with coal-powered steam engines. So the common term for this is the Rebound Effect. And joining me today to explore what it means for greening digital services is Vlad Coroama of the Roegen Center for Sustainability.

I first came across Vlad's work when at a green cloud procurement workshop in 2019 held by the European Commission in Brussels. And over the years, I've had his writing and presentations about the rebound effect and digital sustainability, some of the most incisive and accessible work on the topic, on the subject.

Before I embarrass him further though, I think it might make sense to give him a bit of space to introduce himself. So Vlad, thank you so much for joining. I've been looking forward to this. Can I give you a few minutes to introduce yourself before we get into the meat of it?

Vlad Coroama: Hi Chris, many thanks for your kind intro, of course, for having me on your program. So I'm Vlad, the founder of the Roegen Center for Sustainability, which is a small company based in Zürich, Switzerland which tries to do a research, actually, more research than consultancy in the field of computing and sustainability, or if you want more from a, more from a deployment perspective, digitalization and sustainability.

Actually before that, this quite recent and before that for my entire life, I've been an academic and I've worked in the fields of computing and sustainability and also the more technical one of smart energy for about two decades now. And with both these hats on, so both with the more sort of hands on engineering system developing hat on, and with the more theoretical hat, what my work, which of course in the beginning, it was not so clear where the path leads to, but it became more and more clear that I want to understand how we can both make computing more sustainable, which is if you want perhaps green IT to use a general term, but also to see, and perhaps in my view, more importantly, to see how we can deploy computing or digitalization again from a deployment perspective, to induce environmental benefits across our societies and economies. So in other sectors, sometimes that it's often called Green by IT and these indirect effects, as you said, it's not only about direct effects, this is very much about indirect effects, are, or can be, so much more powerful than the direct footprint. And unfortunately, it's not only the positive effect. So it's not only how can we do, you know, society and economy more sustainable, by the way, society, societally sustainable as well. We'll talk mainly about the environment today, but much of what we discuss applies to societal implications as well, but to come back, so it's not only positive effects.

We also have, unfortunately, this indirect detrimental effects to sustainability, both societal, I mean, we've seen elections and so on, right? But also environmentally. That is, computing or ICT can induce more energy and material consumption, increased emissions, increased pollution, and so on in other sectors.

And with this, I think we sort of arrive at the topic of our discussion today, which is rebound.

Chris Adams: Indeed. Yes. Thank you very much for that, Vlad. So, just if you're new to this podcast, my name is Chris Adams. I am the executive director of the Green Web Foundation. That's a Dutch-based nonprofit focused on reaching an entirely fossil-free internet by 2030. I'm also the, one of the policy chairs of the Green Software Foundation's policy working group.

And here's a quick reminder, we're going to be covering a few papers and a few projects and links and websites. We have show notes at the end of every single episode, and there'll also be a transcript. So if there's something you miss, we will have that available so you can kind of catch up with this or basically submit pull requests if you see things you need to correct. All right, Vlad, are you good to go? I think, should we start with this? Okay, then. So we spoke about this. The topic of this is Greening the Rebound Effect. And I've touched on what the rebound effect is, but for the uninitiated who want to learn more than what I just said, what is the rebound effect?

And maybe you could tell us a little bit about where it comes from and whether it's a new thing.

Vlad Coroama: Okay. Thanks. So as you said in the introduction, your introduction, the very first time that we know this has been mentioned, it was in 1865 by the British economist, William Stanley Jevons, who wrote a book, The Coal Question, it's called, and it was about what we today call rebound effect, we called it such back then.

And by the way, this is a very cool thing, as a computer scientist, you seldomly get to cite, you know, a paper older than 20, 30 years, so it's really, it's really nice when writing a paper, you know, to cite something from the 19th century. So what Jevons noticed was that the more efficient steam engines and other, you know, coal using machinery was becoming in the 19th century.

At first glance, paradoxically, the overall coal consumption was not decreasing, but increasing and increasing at a very larger rate. So this is not necessarily counterintuitively, but yet it requires an explanation why. And of course the explanation is that the amount of engines was increasing because

the more coal, the more efficient machines were becoming, and by the way, some of these machines were steam engines that were helping in the very coal extraction. So coal extraction itself was becoming more efficient and thus cheaper. So both the running the machines was becoming cheaper and accessing coal was cheaper.

And this means you could deploy the coal for many more machines doing the same stuff that had been done before and for entirely new applications. And this is basically what we now call the direct free buffer, which means a good or a service becomes more efficient because the energy is more efficient or some other material that flows into it.

So it is more efficient to produce that good or service, thus it becomes more affordable. And thus, as we know from neoclassic, since Adam Smith, basically the demand for it tends to increase. So that's the first phenomenon. And this, by the way, lay dormant for over a century and late seventies, early eighties of the 20th century, of course, due to new researchers, Khazzoom and Brookes, 

Chris Adams: Ah, yeah. 

Vlad Coroama: we rediscovered the phenomenon in wave of the two oil crises, was the context.

And basically they talked about the same, about the direct rebound effect. And then this developed also to what we now would call the indirect rebound effect, which is actually an umbrella term for a variety of mechanisms and phenomena. But all have in common that something becomes more accessible in a way.

Some resource is being saved or is being used more efficiently. And that resource can be energy, but it can be any material. But it can also be immaterial stuff, such as time, and this we call time rebound. So if a technology saves us time, we'll do something with that time that likely will also require energy and produce emission.

Or if it saves us money, as before, we might not spend those money on more of the same good. But, and this is called the income effect, and this is another type of indirect rebound effect, we might use the disposable income to, you know, do something else that in itself might be energy intensive and, you know, responsible for lots of emissions.

Chris Adams: Okay. So, so we've got the Jevons. So there's Jevons paradox where it initially started with, and I believe you spoke about Khazzoom and Brookes. I think it's, is it called the posh term, the Khazzoom–Brookes postulate? Something like that. It's like the kind of term you'd use at a cocktail party to impress people.

And then you've also described, there's a few different flavors of rebound that we might talk about, and they might have different degrees of magnitude. And this is something we're going to, we can talk about a little bit later. So in time, you know, if I'm, if I save a bunch of money by buying a bunch of things at, say, a supermarket, a cheap supermarket, I might end up spending a bunch of money either eating out or buying, getting coffee, you know, posh coffee and stuff like that.

So that's, those are the, some of the rebound effects you're talking about. Okay. All right. Thank you for that potted history there, actually. And I didn't realize that it was so much based around the seventies, because presumably that's like relation to the oil crisis and when people suddenly started caring a lot more about efficiency.

Right?

Vlad Coroama: Yes. And actually they saw that and then also a more fuel efficient cars came around also in the U S and, but still the overall fuel consumption, not maybe short term during the, you know, the crazy months of the oil crisis, but over several years, the oil consumption, the petrol and so on was still increasing.

And that's how, so for a similar sort of trigger as Jevons, a century earlier, they started looking at it, how does this happen? And what they saw is people drive their cars more.

Chris Adams: I see. Okay. Thank you for that. And, so when we're talking about things becoming cheaper and more accessible and more widespread. It's not a huge leap of the imagination to think about things like electronics getting cheaper or more widespread, even cloud computing becoming cheap or more widespread.

So I guess maybe it's worth me kind of moving to this. So if we're gonna talk about things like the rebound effect or things like this, or why efficiency gains matter in the context of building digital services, maybe I could actually ask like, why does this matter when we talk about digital computing?

And why does it matter in a world where we are seeing more laws being passed now and a kind of influx of new kind of legislation or people setting new norms about this?

Vlad Coroama: So it, it matters, as you say, of course, this happens within computing as well, or within ICT, let's say, I think it's Koomey's law that, that says,

Chris Adams: Is the network halves every 18 months or something, isn't it?

Vlad Coroama: Yeah, it's that basically we are, or a consequence of Koomey's law, a consequence, not directly Koomey's law, is that we use all our gains for more computing and not for, you know, less energy intensive computing. And this of course makes sense. But the problem I think with computing or what does it mean, the, the big challenge of computing, but also environmentally, what can become an issue is that it's general purpose technology and that it induces efficiency, not only within computing, but also, and crucially outside it.

So we, when we talk about the rebound effect of, again, computing/ICT/digitalization, choose the term that you prefer... we have to distinguish between the rebound within ICT itself, more computing, perhaps, you know, more cloud, whatever, it's more affordable. But crucially, I think also the rebound outside this in all the other sectors that digitalization makes more efficient.

Chris Adams: I see. So there's, so in the context of digital, one thing you're saying is that, yes, there is, obviously we should be mindful of an efficiency argument, but because if you just only talk about efficiency rather than consumption, you can lose sight of the full picture and. If you take a second to step outside, the efficiency that you might see at a kind of digital level could also have like

absolute increases or decreases accordingly. So you should be, so we need to take, we need to be looking at the two of these basically.

Vlad Coroama: Yes, exactly.

Chris Adams: Okay, cool. Thank you for that. That's actually, okay, that's quite helpful. And I suppose when we talk about efficiency, it's worth looking at some of the numbers, for example.

So we have seen, say computing get quite a bit more efficient, but we've also seen, basically, we've also seen, for example, some of the hyperscalers, we've seen hyperscale companies like say Microsoft, Google and Amazon, it's not like they've stayed the same size and they haven't grown.

We ;have seen them growing, even as things get more efficient. So these are one of the things where we need to be somewhat aware of, yes, the absolute figures in this as well as the efficiency part here. And we've spoken about how, there's, digital can have an impact on the outside world, and you might be talking to things like, so like transportation examples or like ride hailing, things like that is what you're referring?

Maybe you could expand on some of those. Cause I think these are the things that I've seen you talk about quite eloquently in other places, actually.

Vlad Coroama: Yes, because there is the hope, right? And very often we have the claims that ICT or digitalization, let's say now, makes so much of the world more efficient by coordinating it better, by, you know, finding patterns, by we all know how Google did its cloud more efficient and so on. But then there are many other fields outside.

And in all of them, I see a pattern of how in the beginning everyone says, or a lot of the voices say, "Hey, great, you know, now we have your efficiency. Now it will be so much better." It's a sort of a techno-utopianism, if you want. I will give two-three examples. The one I will start with this one, I'm writing now actually about the rebound effects of teleworking.

And I've, so I've been reviewing many studies and it's very funny because the very early studies, teleworking has been around long before sort of the World Wide Web made it into the homes. Since the 70s, they started talking about this. And the first papers have titles such as, you know, 'Traffic Reduction by Telecommuting' and then similar things.

And then through the work of Jack Niles, it was, and especially Patricia Mokhtarian in the nineties already, they started to understand, "oops, wait, wait, wait, there is also lots of rebound effect." And today's papers have titles such as, you know, 'Does home-based telework reduce household total travel?' So lots of questions marked there.

You know, does telecommuting promote sustainable travel and physical activity? Does telecommuting reduce commuting emissions? And so on. These all, and I have many more, but I will not go into them. But so the phenomenon that happens there is that, yes, teleworking in first instance, of course, if you don't travel to work and travel is energy intensive, much more so than, you know, the little bit of energy that we consume now to have a call, it saves energy in the sum.

But then, because you have more time, because you are more flexible, you start, and because before you used to do other things while going to work or coming, you used to have multi purpose trips. So you, I don't know, dropping kids at school, you know, going to the gym, doing grocery, whatever. those other reasons still exist.

So you will still undertake other trips and much more so than you have subtle effects. If you only need to commute, say, twice per week to work, you might be very tempted to move much farther away from work, you know, in a nice countryside where the kids can play, you know, in nature and safely and so on.

And then you only commute twice instead of five. Well, four or five times per week, but for much longer distance and perhaps no, you can no longer do it by public transportation because you're not urban anymore, but you have to do it by car. And that's a classic. And this became more and more clear. So teleworking is not clear actually now whether, you know, the net effect is a positive or negative.

And I will not go into this detail for others, but we have this for e-commerce or slash online shopping as well. Again, lots of enthusiasm environmentally in the beginning, and then you see that many other things happen. You know, you, all of a sudden you order much more. It's so easy to order from the couch at 11 pm, you know, you don't need to go to the store. So all the consumption increases, or now more recently with AI, with autonomous vehicles. And this is perhaps the last example I want to give, and I think you've heard this before because it's a favorite example of mine. Also in the beginning, we had lots of enthusiasm, you know, how the cars will like coordinate with each other.

And then, you know, they, at some point we won't need traffic lights anymore. So then don't need to brake and waste energy and then reaccelerate. But this is all peanuts. What actually will happen is that, you know, they will substitute, autonomous vehicles will substitute a lot of public transportation because it will be so much more convenient to be driven by car and be able to work in the car or, you know, read a book, discuss whatever. So use the time efficiently.

Chris Adams: Okay. So you spoke about these, there's quite a few examples then of the rebound effect resulting in basically first in like direct efficiency leading to increases in usage in other ways, with some kind of actually quite vivid examples there. And that's, that feels like a nice segue to talk about, okay, we have this idea around rebound.

And there's different kinds of rebound that can take place. But as I understand it, there are certain conditions that make rebound more likely or increase the effects of rebound versus, making them somewhat smaller, for example. Maybe we could talk a little bit about that because I remember hearing about the kind of like vivid example of autonomous driving.

Like you mentioned, there was, yes, it increases the, it lowers the threshold of you doing things to the point that, you know, there's there's a famous study about someone sending autonomous cars to just pick up a sandwich they left at home because it was so easy to do now. And that's obviously not going to be a sustainability win.

So maybe you could talk a little bit about when you do see rebound and what conditions make it more likely to happen versus maybe when it's not so likely to happen, perhaps.

Vlad Coroama: Yeah, there are, I do not have general rules to provide an answer. So I cannot tell you this precise, you know, class of applications or yeah, digital services are more likely to rebound than the other not. But I can give you a couple of hints or perhaps examples, and the easiest is to start with that, with the example of the vacuum cleaner that you mentioned earlier, and which is of course outside digitalization, but I think it's very nice to understand the phenomenon. When the bagless cleaners emerged to, Dyson was the first on roads to invent them.

They also became so much more efficient. So they used to consume 1.5 to 2 kilowatt of power, and now they are 4-500 watts. So a factor of it's like 20 to 25%, a factor of four to five, reduced power. And the question is, do we vacuum much more? So it is of course, cheaper to run them. Do we vacuum much more?

Probably we do it a bit because, you know, they are also more convenient. They are cordless very often and so it's easier to grab them. But certainly this rebound is relatively small and not, you know, 400% it doesn't overcompensate with certainty, because, well, you only need so much to vacuum your house and it's probably also not the most people... the favorite activity for most.

So one of this thing is when there is something like, when the demand is satisfied,

Chris Adams: Ah, like an upper limit.

Vlad Coroama: not have rebound, you need to not have the rebound mechanism. And this mechanism being often, not always, again, it can be with time or transaction costs or other things, but often it is monetary.

You save money and then you, you know, consume more of that good. And in this case, if the demand is satisfied, then you don't need more. So, for example, smart heating in a home, to come again now back to computing, if you have smart heating, I mean, we used to have our homes up to the seventies, even at 13, 14 degrees centigrade in winter.

We don't do it anymore. We all have whatever 19, 20, 21, wherever we feel comfortable and we don't need more than that. So, a smart heating system will make our, our heating more efficient, then we'll save 10%. And that can be financially quite interesting. We'll not use those money to hit more because there is no need for it.

I mean, we might perhaps, you know, let a bit more fresh air in and thus waste a bit more energy, but it will certainly not compensate the savings. So that would be one such example where at least a directory bound. It is, is unlikely,

Chris Adams: Ah, I see. I'm really glad you mentioned the vacuum one because I remember watching your talk just after I bought a cordless vacuum cleaner myself, and I remember saying like, "okay, there's an upper limit to how clean my flat can actually be." And like, yeah, it's a lot more fun to use, but yeah, I, it doesn't make me... making me slightly more efficient at vacuum cleaning does, it didn't double how much I enjoy vacuum cleaning, right?

Well, I might enjoy it more, but there's an absolute upper amount of vacuum cleaning hours I'm prepared to invest into my flat, for example. Okay. So that's, so there's this upper limit of satisfaction that if you have something like that, that's maybe one kind of hint that you might be looking for, for example, and we might be able to kind of take some ideas into another domain domain for that.

Vlad Coroama: And if you want, I can give another such hint. So when there is rebound, but if you sort of, if your digital service makes the activity sort of more affordable or simply more desirable and it will be consumed more. But it will have changed in such a way that the footprint of sort of the new activity, the modified one, is much smaller than the original. And then although you might have rebound, the overall balance will be net positive.

And again, a short example outside of digitalization is LED lamps, right? There is certainly, once you have LED lamps, there is certainly a rebound in the, in a sort of light rebound, in the amount of light that you're using. You will, because you know, they take six watts and not 60 anymore. You are not so concerned with like turning it off anymore.

So there is some light rebound, but in terms of energy, the rebound is really small because even if you leave it like twice as much, you will still save 80 percent and not 90 percent, but still the net save will be... and the same in digitalization. We did, for example, a conference for it in 2009 between two continents.

And that conference happened at two sites simultaneously in Nagoya, Japan, and in Davos in Switzerland. Of course, it was a seven hour difference, so there was just a four hour common slot in the Swiss morning and the Japanese afternoon. And why we did this? Because for a conference, the main environmental impact are flights of participants to the conference, and in particular, intercontinental flights.

So the hope was to save intercontinental flights. And according to our survey afterwards, we have indeed succeeded to save some, around 80 intercontinental flights of people who would have flown to the other side of the world. And we induced much more, around 200 intracontinental flights. But you know, a short haul flight has such a smaller footprint than a long haul flight that although we had many more participants

and many more flights. Because those flights were much shorter, the overall impact was still positive. And again, we only talk direct rebound here. I like to stress this point. The system boundaries, as they say in environmental sciences, the system boundaries of indirect rebound are basically the words. So it is very, very tough and we do not have yet the right tools to profoundly assess the, you know, the overall impact of digital technologies, unfortunately. And this is one of the areas I'm most interested in.

Chris Adams: I see. Okay. Can we just dive into that a little bit more before we move into the next topic? So you spoke, we spoke a little bit about say, forms of rebound where there's an upper limit where there is, it's like me having a more efficient vacuum cleaner is one thing. And then you mentioned this other thing where there is like,

where you're somehow, where the savings end up being kind of almost somewhat circular. So if I'm, maybe I can reduce, say the cost of cloud computing, you mentioned that in many cases, because I've made it cheaper, I would then recirculate those into doing more rather than actually reducing the total energy use.

Is there anything, have you, maybe you could expand a little bit more on that part, because when I think about things like, say, AI, or I think about some kind of, some things related to cloud computing, we can totally see this, and there are very much arguments basically being made right now, that say, "Oh, well, all you need to do is focus on your cloud bill going down by half," for example, "and then that will be, and that will achieve your savings."

Well, that's what you need to care about." And it sounds like, if I was to focus a bunch of time into halving my cloud bill, I'd then have a product manager or my CEO say, "well, okay, look at all this, look at all this money we've saved. Let's reinvest it into doing more so we can do, so we can have more of a competitive advantage in our particular field," for example.

Vlad Coroama: Yeah, of course, if you want... reducing your impact means always reducing your overall impact and not becoming more efficient. So in a sort of narrow view of what you asked, if your manager came to you and said, "hey, let's be twice as efficient," the answer should be "no, let's overall consume less." This being said of course, it's again, it's very difficult because AI in particular, and AI is the most uncertain domain, as you very well know, or certainly one of the most uncertain how it will develop in terms of energy consumption.

And so it might go through the roof or it might not, you know, and it will depend on so many factors, but it also has, it brings about, and I keep coming back to the indirect effect. Sorry for that. But, you know, you cannot forget them. So I hear very often the argument of sobriety, of digital sobriety.

And of course, it's good because to achieve various, you know, goals, whether they're achievable or not, or any goal, any limit we want to achieve, of course, all sectors have to go down. But then AI can use substantial societal or environmental benefits when it's environmental benefits, and if you can really put your finger on them, then it's easy.

Then you, then it's a no-brainer. Of course, it's worth spending, you know, the additional data center to train our models better. Also, by the way, the energy consumption in our devices for a model inference. Because, for example, I have now a paper under review where we measured a bakery chain in Germany and they deployed AI to predict the demand for bread and thus to reduce food waste and the results show, so we made a sort of a benefit-cost analysis.

And the benefits, energetically speaking, are so much larger than the costs of deploying that AI system, training it, inferencing and so on. So when there is, then it's a bit of a no brainer. Unfortunately, you sometimes have, you know, societal benefit at an environmental cost. And then it again becomes harder because then it's a scientifically non-answerable question, then it's an ideological question, right?

"How important?" Or a value-based question. But to come back to actually your question, because I think I went perhaps a little too far away from that, I keep, I keep bringing the indirect effects because I think they are so underrepresented in the discourse, both academic, but even more so societal.

So your question was about the efficiency of, or could you say it again? Sorry.

Chris Adams: Yes, so the question I'm putting is, say, if I want to reduce emissions, it's very easy for me to just talk about, "look at how much more efficient I can be" if I'm a developer, I often think that, you know, I've, I'm incentivized and I am rewarded by making things more efficient. It feels like, if I just focus on halving that cloud bill, for example, there's a risk that they'll just bring that cloud bill back up again, for example, or bring the environmental impact back up again by using some of the savings to do new things.

So the thing I would need to, things we'd kind of need to be able to do is basically have this notion that, okay, we do need to be on a kind of glide path downwards in absolute terms, for example. We can't just talk about emissions intensity, because this is a common thing that you see being, that's coming up in quite a few places.

And this is something that organizations tend to report now a bit more as a way to avoid talking about absolute figures. But it feels like if we're going to do this, we need to look at absolute consumption, just as much as efficiency. And efficiency is one of the strategies you would use to reduce consumption in total, in absolute terms.

Right?

Vlad Coroama: Yes. Yes. Absolutely.

Chris Adams: Brilliant. Okay. Thank you for clearing that part up. I...

Vlad Coroama: Well, it was more you clearing it... But yes.

Chris Adams: This is part of what we're now doing is we, running through some of these to make sure that I understand it and i, when I'm doing this, I'm basically standing, this is helps me explain it to other people as well. So this is a, yeah, this is totally okay.

All right. So we spoke a little bit about rebound. There's a few different flavors of this that we had. And you touched on this idea that if you just look at one aspect, then you can miss some of the kind of wider systemic issues and systemic impacts. And this feels like a nice kind of segue to talk about some of the other work that you've been doing, because it's actually where I came across some of your other work about trying to quantify the environmental impact of a service across multiple areas, basically.

And I found this really helpful where, when I first read it in 2020, because it found, it provided a somewhat kind of rigorous way to help address the fact that a lot of the time people will overstate either the savings, overstate the damage being done in this, in these areas. And I think the name of the paper was, sorry, it's a bit dry.

It's Methodology for Assessing the Environmental Impacts Induced by ICT Services. But one thing that was really nice about this is you would say, "well, you need to think about how much more efficient something might be, but you also need to think about what kind of take up that might be for something."

So, and all of these things here. So. Maybe I could actually talk to you a little bit about this because it's very, very common to see very, very kind of extraordinary claims about efficiency or extraordinary claims about savings under perfect circumstances. So maybe we could talk about like, when you look at this stuff, are there common mistakes or common kind of omissions to look out for when you see people talking about the savings delivered by maybe a new service, for example, so you can help develop some kind of intuition? Because this is one thing I think we don't really have the language to talk about this right now. And I think one thing that your papers did was actually introduce some helpful terms or some helpful language to talk about some of this.

Vlad Coroama: Yes, in all honesty, I... first disclaimer, we didn't provide a cookbook recipe how to do it and how to arrive at a net impact. Again, system boundaries are the word and we don't yet have the tools for that, but this being said, you can try avoiding the most common and sort of low hanging pitfalls if you want.

And perhaps the most common is that, that you read is, you know, a juxtaposition or direct footprint of a service and the benefits in fitting uses. So direct footprint, which is by definition, it's inherently negative from an environmental perspective, as almost any human activity, and the other side, the indirect benefits.

But then conveniently, and I'm not saying that this is necessarily purposeful, it can be out of naivety or, you know, but it is convenient for getting the indirect negative impacts. So you always have, so I think that's a helpful way of thinking about it. You have the direct footprint, negative by definition, and then you have indirect effects, which are both positive and negative. Ideally, you would try to cover them both. The very sort of high level indirect ones, which are systemic, you cannot cover. But you can at least take care of the direct rebound, for example.

Chris Adams: All right. Thanks for that. So you spoke about, so there's leaving omissions from here. There's one thing I've seen that in a few places, so I've seen like, say, caching services basically say, "well, look how much, look at the savings you've received," for example, without telling you the full amount. And this is something that I think Uber have released.

They've shown, there's now a calculator to see how much cleaner your ride would be if you use an EV car versus another one, but you don't see the absolute numbers, for example. I mean, what's wrong with this? Like, is this a thing that... is this a good idea or should, or if you were to do this properly, like, how would you make this more representative, for example, when you see examples like this?

Vlad Coroama: Well, I don't know those particular calculators. I haven't used them or seen them. But from how, what I understand about them, it's very often a question of baseline or of the counterfactual. What is your counterfactual? If I hadn't used this, you know, for example, green taxi service in your example, what would I have done?

If the assumption, if the baseline is, I would have used, you know, a very inefficient internal combustion engine-powered car instead, then, of course, depending also a bit on the electricity mix of the grid, usually it will be positive, right? The overall impact. But the thing is, it might have replaced public transportation or no trip at all.

And then it's a rebound effect. So if I am keen, you know, I am taking a taxi and you know, it just tells me, "Hey, if you now take the green one instead of this," then I would say it's probably a reasonable assumption. We have some production issues, so from a life cycle assessment, of course, it's a bit complex, than it's probably pictured, but in essence, it's probably not incorrect.

But overall, what happens is that if a taxi ride is cheaper, or if I have what is called a moral hazard, so I have a clear conscious, "oh, I'm going green so that I can take it," and then I'm taking one that would not have existed in the counterfactual, then of course the net effect is there.

Chris Adams: Okay. So that last part is like, I get an Uber or I get an electric taxi and, so I sort of, to a restaurant and I then decided to eat a big fat steak, as an example, like as a way to kind of balance these out. Like there's maybe an indirect, there's a direct saving, but systemically, I still have created more of an emissions. Like, I'm not going to try and do the calculations between steak and a drive, but you get the general idea.

Okay. So that's where some of that comes in. You mentioned this thing called a counterfactual. And I think this is actually one thing that might be quite helpful because we've seen a number of papers and reports being used to talk about how, you know, you can achieve sustainability through AI and we've seen them written in, say, in the early 2010s or even the early 2020s.

And then there is often a lot of interest in talking about how good something could be, but there seems to be less, historically, we've been less good at tracking whether those savings have been delivered. Is this something that maybe you could talk a little bit about that? Cause I remember you write, I saw recently you wrote a little bit about the, this kind of reporting, the fact that there's a kind of gap in how we talk about this and the following through part, maybe you could just follow, just expand on, on this and why you need this, this extra information to kind of see if things are working basically.

Mm

Vlad Coroama: Yes. So for AI, I think it's a bit too early to tell, we have not yet seen like a series or I'm not aware of any, a series of studies or even like one old study that made some predictions and the authors didn't come back to it to say whether anything was delivered on. And I think it's not also a typical, like, computing thing that we do lots of predictions. And as the old adage goes, "predictions are difficult, particularly about the future."

Chris Adams: Yeah.

Vlad Coroama: Yeah So first, you know, when our predictions were right, we might like to go back and highlight this that we were right already back then. And otherwise we might conveniently forget that we made those predictions.

For the computing domain generally and not AI, because again, AI, I think it's a bit too young for that phenomenon to be seen one way or the other, but for computing generally, there is a track record of various, both companies and sort of lobby groups of the IT industry or of the telecom industry doing sort of predictions and then continuing. One very known example is GESI, Global E Sustainability Initiative that published every couple of, every four to five years, starting 2008.

They publish a series of studies. The first one was called SMART 2020, then SMARTER 2020, then SMARTER 2030, and so on. And there are predictions, the first two ones are called SMART 2020 and SMARTER 2020 because they're where to the year 2020.

Chris Adams: Ah, I see.

Vlad Coroama: And and they predicted many gigatons that would be saved through digital technologies.

I think the first one was 7 point something and the second study around 9. 1 or 2. And that's, that's quite a chunk of the sort of fifth of CO2 equivalent that the humankind puts into the atmosphere every year. So that's a very substantial chunk. And if that would have been true, it would have been amazing.

But now, well, 2020 is past, heh, and we published newer studies, but they didn't look, you know, how did this stand up to the test of time?

Chris Adams: Wow. Okay. That's, that feels like quite a gap that we probably should be trying to close. If we're going to be talking about, we're doing research in this and seeing what is going to be effective as time is ticking down. Right. Vlad, that's actually, I really want to dive down in that rabbit hole, but we're coming up to time.

So I'm going to have to be a good boy and try my best to stay inside the time we do have. Vlad, we've covered quite a lot of interesting areas and dived into quite a lot, and I've shared a couple of links. The show notes have series of links to the papers and things like that. If people do want to continue this work or continue following what you're up to, where should people be looking beyond just the show notes of this podcast for example? Is there a website that we should point people to, or do you have a online presence you would direct people's attention to?

Vlad Coroama: Well, anyone, if, I mean, you can post my, a link to my LinkedIn account, if anyone wants to contact, I'd be happy to, you know, to engage in conversation and continuing discussions, this is what I do. So other than this, there is no value that is specifically say on rebound effects of digital technologies.

I wouldn't know of any, but there is, for example, the ICT4S conference. So the ICT4Sustainability, that, that conference that started back in 2013 and where indirect effects of ICT are quite a powerful presence. This year's edition will be end of June in Stockholm, Sweden, and I'm co-organizing with a couple of other researcher.

So, with Mattias Höjer at KTH, with Tristan Brehmer in Lancaster, Charlie Wilson in Oxford, and Dan Schien in Bristol, we are organizing a workshop on this very topic, indirect effects of... called wait, I'm no longer sure what acronym stands for, but something with indirect something. So a workshop on assessing indirect effects.

So there are a couple of venues that are scientifically dedicated to this, but I, there is no unfortunately, no like, you know, portal where everyone has the topic.

Chris Adams: Like Institute of Rebound. Yeah. Okay. And yourself, I understand that there's the organization that you work for. The Roegen, is it Roegen Center of Sustainability? That's the one. Yep. So that's roegen.ch is the place people would look to if they want to see any future publications and research in this field from you.

Brilliant. Well, Vlad, thank you so much. I've been looking forward to this and I have to admit, I'm a bit of a fan boy. I've really enjoyed a bunch of the papers and things you've been publishing over the years, and I really hope you continue to do them because they come up with really nice examples that I can help explain to other people.

So thank you once again. And yeah, hope you have a wonderful week. Take care, Vlad.

Cheers. You're too kind, Chris. Thank you as well. And by the way, thanks for your great work that you and your foundation are doing. So thanks for that as well. And thanks for having me. Cheers.

Cool! Thank you. 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 greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!