Episode 58 - Avoided emissions thanks to Tech: the Vinted use case with Laetitia Bornes

Episode 58.a

Laetitia Bornes (00:00)
We shouldn't reduce this complexity to a single figure. I don't think we should stop a second hand platform at all, but I think we should rethink the way they are designed, service design, the platform design, the business model design, so that we improve the carbon emissions or maybe other social environmental

Gael Duez (00:26)
A lot of phones raised in the air at Green IO of Paris last year when her colleague, David Ekchazer shared their findings on stage. Not sure it was good for the people's individual footprint, but a clear signal of the interest of the participants for the topic of avoided emissions and how to assess the true impact of tech for good companies. And it was indeed big numbers which were discussed there, with Vinted, the second-hand marketplace at Behemoth now in the circular economy field, claiming they avoided 680 kilotons of CO2 equivalent thanks to their operation. It's not the only company doing so. Backmarket, another platform specialized in second-hand electronic goods, assessed the greenhouse gas emissions saved thanks to its operation to have reached accumulated 1 million tonne of CO2 equivalent in 2023. A CTO was in a Green IO podcast earlier this year and she made no mystery that these statements and their overall mission is a massive asset for employee engagement and retention, both PhD students, decided to apply the latest research in systemic modeling to investigate these claims and their findings were surprising and enlightening for the IT sector and nuanced. Yes, it's still possible to have a calm discussion about a complex topic these days.

Today, I'm delighted to be joined by Laetitia, the co-author of this paper, who couldn't be on stage at Green IO Paris because she was finalizing her thesis defense before completing her PhD in Human-Computer Interaction, Systems Engineering and Systemic Design in Toulouse, France, Laetitia worked for five years as a UX designer. Her research has resulted in the development of a methodology and tools to enable designers and decision makers to address the complexity of sustainability with a particular focus on the indirect effects of digital technologies. Specifically, she has developed Rebound Archetypes, a workshop and a card game for anticipating and mitigating rebound effects, and Magnitude, a software for the consequential modeling of direct and indirect effects to inform environmental decision-making. So, welcome on the show, Laetitia, and congrats for your graduation. Shall I call you Dr. Borne now?

Laetitia Bornes (03:02)
Thank you very much for your invitation. And yes, you can call me that since last December, but really you don't have to. You can call me Laetitia.

Gael Duez (03:13)
Okay, so let's stick to Laetitia. A bit of context first about these IT companies positioning themselves as tech for good companies. And honestly, from an outsider perspective, it seems pretty obvious that they do. So the companies enabling or accelerating the circular economy seem to be part of the good guys in our fight to make our economic system, would say, compatible with the respect of the planetary boundaries for sustainable human life on Earth. Here the struggle seems to quantify this positive impact, this handprint, the opposite of a footprint, which has gained some popularity since the 90s. Vinted tried it and you somehow debunked or maybe shall I say fine-tuned its claim. Could you explain to us why you conducted this study and its main findings?

Laetitia Bornes (04:09)
Yes, of course. So that's a big question. So I will try to answer gradually and you can interrupt me if it's too long. So first of all, I would like just to add some nuance to the presentation of Vinted as a tech for good company. ⁓ That wasn't the original goal, in fact, of Vinted. So it was more about someone moving house and wanting to get rid of their clothes. So I don't know their intention now. in fact, wasn't ⁓ neither the communication until relatively recently, the slogan was, if you don't wear it, sell it. So it's more about making money. And in the case of Vinted, there are some clues in the design of the service and the platform itself that show that the primary goal is more profit. For example, the lack of any possibility to sort or filter by distance the results. It's because Vinted taxes transactions with delivery and therefore they have no interest in users meeting to do the transaction in which is in fact totally contradictory to reducing the environmental impacts. So I don't want to put Vinted on the trial now. And I can't speak for the other tech for good companies. And also, I want to insist on the fact that it doesn't mean that they can't have actually a positive impact in the end. And they can still bring their strategy in line with their communication.

Gael Duez (05:46)
Just to bounce back on what you say, that's for true that I put BackMarket and Vinted in the same bucket in my introduction. And BackMarket, right from the start, they wanted to be B Corp and they positioned themselves from a very clear environmental perspective and being part of this sort of tech for good movement. And actually you're right to correct me because Vinted… It was not the original positioning. It doesn't mean that they don't do good things, but then as far as I know, not a B Corp or they didn't chase any take for good label or things like that. thanks for bringing this precision on my introduction, much appreciated. But please, okay. So your findings now, what did you find and how it can help other decision makers and people working in the tech for good environment to have a nuanced approach on how much good and how much avoided emissions they can claim.

Laetitia Bornes (06:40)
Yeah, so first why we decided to do this study. So for my part, my objective was that I needed a case study to show designers the importance of rebound and indirect effects in concrete terms. So we have a specific case study and how design can be used to address those rebound effects. I don't know if I have to define rebound effects here.

Gael Duez (07:08)
I was about to ask you to define rebound effect to make sure that everyone is on the same page. I'm pretty sure that a lot of listeners are familiar with the concept, but it's not that an easy concept to apprehend. yeah, feel please free to so.

Laetitia Bornes (07:10)
Hahaha. Okay, let's say that the first observation of ⁓ rebound effect mechanism was called the Jevons paradox after the man who discovered it and concerned the coal train. So the introduction of a new, more efficient steam engine technology did not reduce the overall coal consumption and actually it increased it. And in fact, this mechanism is that the improvement in efficiency meant that less coal was needed per kilometer. So the cost of this transport per kilometer was reduced, making it more accessible to more people, increasing the overall consumption. So this is really the first definition of rebound effect. And in this case, it's the most serious case known as backfire the rebound effects is more important than the initial gains. But sometimes the rebound effects will just simply reduce the initial gains without exceeding them. depending on the community's concern, the term rebound effect is used to describe more and sometimes more complex mechanisms. So maybe we'll go back to this concept with some examples, but you can have not only the rebounds, but also the time rebounds, the skill rebounds. So if you make to people that wouldn't access it because of skills, for example, the driving license, if you have autonomous cars and you can take a car without a driving license, then we would call it a skill rebounds.

Gael Duez (09:11)
this skill rebound, is the rise of all this software as a service solution a good example as well. let's take the example of podcasting. mean, 20 years ago, recording, editing and broadcasting an audio show was truly for professional. Now I can do it, and I'm not a trained engineer in audio So would you consider also the software as a service solutions that are mushrooming all over our digital world as a good example for skill rebound effect?

Laetitia Bornes (09:49)
I guess actually it's a perfect example of skill rebound. Yes.

Gael Duez (09:55)
Okay, and so I've got a good grade. I'm happy with it. And the two other rebound effects that you've described, they were the time rebound effect and the economic rebound effect. Could you share maybe an example for each of these?

Laetitia Bornes (10:11)
Yes, economic rebound effect is the one I illustrated with the coal train. So something is more efficient, it gets less expensive, so you can use it more intensively or maybe more people can use it. Then the time rebound will be ⁓ if, for example, before when you had to mail to send a mail to someone, it was much longer because you had to write it on a paper, you had to go to the post station, and you had to send physically. Now you can send an more quickly. guess what? You are sending probably much more email than you would send a postal mail. So that's also a ⁓ time rebound.

Gael Duez (10:55)
Yeah. Okay, got it. and if I try to keep on having good grades with you, professor, I mean, you're not a professor yet, but maybe you want to consider an academic career, but you're a doctor. So let's go for doctor. I think one very good example of the economic rebound effect in the IT sector is obviously the rise of public cloud services with much, much, much cheaper access to computing and storage facilities than it was the case before. And a lot of people accessing servers by literally just snapping fingers while before it was really expensive. Is it good example of this economic rebound effect?

Laetitia Bornes (11:37)
Yes, yes, it's a good example as well. mean, you got it. There are a lot of rebound effects in digital technologies. And I didn't mention, but for example, for the time rebounds, you've got Gen AI. So all the things that you can do in less time, thanks to AI, you will probably do it more intensively or do other stuff that is carbon intensive with the time that you have freed. So

Gael Duez (11:48)
Okay.

Laetitia Bornes (12:07)
There's a lot of rebound effects in digital technologies, but in mind that rebound effects is just a concept. It's something to mentally understand some phenomenon. It's a bit fictional because you have to real scenario with a fictional scenario where a given technology wouldn't exist. So when I compare the postal mailing with email. Maybe it's a bit far in the past, you So it depends to what is your reference scenario. But yeah, in digital technology, you have a lot of rebound effects.

Gael Duez (12:35)
That's a very important point that measuring a rebound effect simply doesn't exist. We assess a rebound effect based on different models, based on different methodologies, I guess, and using different scenario, and we compare two scenarios or several scenarios together to say, okay, if that didn't happen, all things equal then we might consider that we had this rebound effect. So it's bit of a theoretical, albeit very insightful exercise. Am I right?

Laetitia Bornes (13:21)
Yes, absolutely. That's it. Yeah, you can't measure it precisely. You can just like, yeah, assess it. Exactly.

Gael Duez (13:29)
Okay, so thanks a for all this precision on rebound effect and how they are conceptualized. it's very enlightening. Can we go back now to your main study, which is Vinted, and what were the main results and how did you build these results and these assessments and these modelizations as we just discussed?

Laetitia Bornes (13:51)
Yeah, sure. So maybe a last word about the why. I wanted to have a concrete example about rebound effects and how design can intervene in the face of those rebound effects. And then I met David at a conference during the workshop on the assessment of indirect effects using specific methodologies, as you said that we called back in time, avoided emission methods. And we were both concerned about the potential limitations of these methods. David wanted to work on a consequential cycle analysis example. So we chose to work on vintage because it's a case study that illustrates many complex rebound and indirect effects as it's often the case, fact, in circular economy-based solutions. And because we had access to the results of a huge consequential study conducted by Valu on the vintage case based on a solid survey with over respondents, and which was very well documented, actually. So that's why we chose this case study. And regarding the main results of the study, there were two aspects. So first, the limitations of avoided emissions calculation methods that we identified. And then the opportunities that we identified in systemic approaches to answer to those limitations.

Gael Duez (15:30)
There is so much to unpack here, but let me pause just for a second and ask you for clarification's sake, what is a consequential life cycle assessment?

Laetitia Bornes (15:43)
Yeah, sure. as opposed to an attributional life cycle assessment, the consequential approach seeks to understand not only the direct effects, but also the indirect effects. And for that, we're going to compare two scenarios. One scenario is the real scenario where Vinted exists. And the other scenario is a fictional scenario, as I said, where Vinted doesn't exist. And to build fictional scenario, we rely on the answers of a survey. here, the survey that was conducted by Vyu, in this survey, they asked people, especially to buyers, what would you have done if Vinted didn't exist? So would you have bought the same item brand new elsewhere? Would you have bought the same item but secondhand as well in another platform like Le Bon Coin or at a charity? Or would you have bought it at all because this was impulsive buying and you were just scrolling the platform and saving for they asked if the seller would have ⁓ sold the item Vinted did exist or if they would it away or thrown it away, for instance. So then you can assess the impacts of each scenario. And when the impacts of the scenario where Vinted exists is lower, you can talk about avoided emissions.

Gael Duez (17:22)
Okay, got I would love and I think we will go back to this methodology, the potential methodology bias and all the complexity, I guess, with administrating 300,000 people questionnaire and all the analysis, the different analysis that can be done with the answers. But just to sort of go straight to the results you mentioned that you've seen some opportunities and some issues as well with the, I would say, traditional claim that they avoided several hundreds of kilotons of CO2. Could you tell us what are those limitations and what are these opportunities that you've spotted?

Laetitia Bornes (18:08)
Yeah, sure. So in the calculation methods, they ignored some indirect effects. to name a few, first, the study doesn't fully take into account impulsive buying, because in on the Vinted platform, you have some new or almost new clothes, sometimes new clothes with the tag. So in the case of impulsive purchases on the platform. If those clothes are new, the study doesn't take into account the additional impacts linked to the production of these clothes. They take into account the transportation of these clothes of impulsive buying, but not the production of the new clothes that were on the platform by impulsive buyers.

Gael Duez (18:59)
How would you quantify impulsive buying?

Laetitia Bornes (19:04)
It's with question actually so there is obviously a big bias because people just answer what they can and maybe they can have a desirability bias meaning that they will answer something think is socially acceptable. But ⁓ yeah the question is like would you have bought it if it didn't exist and if people say. Now I was just scrolling on the platform, then it's considered to be impulsive buying.

Gael Duez (19:36)
Got it. So that's the first limitation, not taking into account impulsive buying. What are the other limitations?

Laetitia Bornes (19:45)
So you have effects that weren't taken into account. For instance, fact that Vinted allowed ⁓ sellers to sell ⁓ their items. Some of them answered that without Vinted, it would have been too difficult to sell those items. They wouldn't have it on another platform. So they would have thrown it away or it away. So in those cases, the money that those sellers earn thanks to Vinted, the way they will spend this money will have some impacts, especially if they use this money to buy some new clothes from Fast Fashioned.

Gael Duez (20:28)
Was it the case that people are actually using the money from second hand platform to buy fast fashion clothes? Did you quantify or assess this trend?

Laetitia Bornes (20:42)
OK, so I quantify precisely because I relied on the existing Vayuu study. don't want to give some figures because I used the older reports from 2021. And there is a much recent report from 2023, I think. But you a part of the sellers who say that they will use the money earned from sale to buy brand new stuff. It's not precise if it's fast fashion, but I think it's quite obvious that you have, and it has been documented by researcher called Elodie Juge, that you have some vintage users who use the platform just to sell their clothes and to be able to renew their wardrobe more frequently without having to pay for it. So you'll have some users that buy some brand new stuff from fast fashion markets that will use items a few times and then sell it on vintage for almost the same price and then renew their wardrobe. So yeah, that's difficult to isolate and to quantify, but I know that from the survey. You could have the figure of people using the money earned from sale to buy brand new stuff.

Gael Duez (22:14)
And so that's the second effect or side effect. I don't know which wording shall we use. Is it like all of these are rebound effects or do you have a more precise academic wording for it?

Laetitia Bornes (22:30)
You have a lot of different taxonomies about indirect effects. They can be classified between the first order, second order, third order. You have a lot of different classification and personally in my research, to make it simpler to designers and decision makers, I consider all the indirect effects that are linked to a change in behavior or practice to be a rebound effect if it can have somehow negative social environmental impacts. So that would be, my perspective, not every researcher would agree with that, but from my perspective, this is a rebound effect.

Gael Duez (23:11)
Okay, got it. so you mentioned several indirect effects, which are rebound effects because they actually reduce the avoided emission claims that is made or assessment because it's not necessarily a claim at this time of the study. What other are worth sharing with the audience?

Laetitia Bornes (23:30)
So to conclude with the indirect effect, would say that in this kind of study of survey, not only the vintage one, the indirect effects that have social impacts are systematically excluded because they are difficult to assess. So that's one of the things we think is really big limitation is that those kind really focus on carbon emissions and not the other kind of impacts. And they also only on what can be quantified. And so for instance, by making it easier to sell their clothes, Vinted encourages people to stop donating to charities. And charities such as the Emmaus receive fewer donations, in quantity and quality. And this has an impact on their social and solidarity activities and on the vulnerable people they help. And that is impossible to quantify. that's not because it's not possible to quantify it, that it's not important. But that's why for me, a rebound effect can encompass things that are not initial gains, because initial gains are something we expect to happen, and this is linked to the intention and so on. So I would have a broader conception of a rebound effect, and those kind of rebound effects are not taken into account in these studies.

Gael Duez (25:04)
And overall, and I know this is an assessment and that might be wild guessing. So it's not like a very precise answer that I'm expecting, but overall, would you say that your study found that we should reduce what is estimated to be avoided carbon emissions or that it is actually completely offset and we're in the sort of a Jevons paradox again situation where creating a secondhand platform does not actually help producing carbon emissions, but would increase it. So basically, where do you put the needle? it reducing the avoided carbon emissions, which has been estimated, or do you think that we're completely wrong and actually they are contributing to higher carbon emissions because of all of these indirect effects cumulated that you've just described?

Laetitia Bornes (26:03)
It's a bit difficult to answer that question because there are so many uncertainties that sometimes you can't say if you are in the positive or the negative. What I would recommend, one of the statements of the paper that we worked with David is that it's not a good question. Maybe we shouldn't say, Is it good or bad? Maybe we should say, how can we improve it? also, if we focus just on the carbon emissions, because if you want to say if it's just good or bad, you need to have just one figure. So that's why we focus on the carbon equivalent. That's how you say it's positive, or no, it's not good, or it's negative. We have avoided emissions, and it's good. What we think is that it's more complex than that and we shouldn't reduce this complexity to a single figure. I don't think we should stop a second hand platform at all, but I think we should rethink the way they are designed, service design, the platform design, the business model design, so that we improve the carbon emissions or maybe other social environmental

Gael Duez (27:14)
Laetitia, you're a perfect guest because I wanted to move the discussion from what you found to what could be done with this question that I asked quite often. And actually it comes with two flavors this time. My first question was, if I were Vinted's CEO and I was genuinely concerned about the social and environmental impact of the world and of my platform more precisely. How should I react to such a study? I mean, your research paper. And what should I change? In my second question, and you might want to articulate both of them, is if I were one of vintage product leader or UX leader what should I do? Because it comes with two flavors. You've got like the overall strategy that the CEO having some sort of a wake up call, and saying, my God, we need to change quite a lot of things in the way we assess, the way we run our business, et cetera, et cetera. But there might be also things that can be done at a lower hierarchical level without a full change in the strategy of Vinted by a product leader and UX leader. And I wanted to drop the two questions so that you can decide which one you want to answer first and how you want to articulate this two levels of decision, I would say.

Laetitia Bornes (28:34)
So first thing, just the study that we conducted with David is not aimed specifically at the CEO of Vinted or at Vinted project or UX leaders, but rather at researchers and professionals who assess the indirect and indirect effects of digital technologies. So the purpose was not initially to evaluate Vinted, but to provide a critique of the methods used to calculate the avoided emissions or net impacts using Vinted as an example. being if the CEO of Vinted reads this study, he may have two reactions, I think. Either he is only interested in making profits and will therefore try to forget it or to discredit it or he may wish to improve on the social environmental impact, then take inspiration from the study or even contact us for more details and is invited to do So there are a lot of things that can be done at several levels and I think that they should be thought with a systemic perspective and that considering all these levels. For iinstance, I mentioned the example of the by distance of the results. You don't have it it would be bad for the business because the business model is to tax every transaction with delivery. If you change the business model to a subscription, instance, you will then want to have more users which will not want to have more transactions with delivery. So everything is connected and the way you design your business model, we have some impacts on the way you design your platform itself. And those things have to be thought all together. And that's why a methodology during my PhD, which is called modeling methodology and its collective modeling involving people from different hierarchical level in the company and also people from outside the company to reduce the risk of So yeah, I think that everything has to be thought all together. And now as a vintage product or UX leader, you can try to push for this kind of methodology to be put in place. actually occurred with a whose name I won't mention, but ⁓ they were developers, not designers, but they were sensitive to environmental impacts. And they a presentation of our work at a conference. It actually was last Green IO conference in Paris. And they contacted us to run a workshop just some awareness raising about indirect effects. And ⁓ one thing led to another, and we are now about to conduct the whole methodology with them over several months, involving a wide range of profiles, including different hierarchical levels. So that proves that it's possible as an employee to push this kind of methodology. Although it probably depends on the company you work in. But yeah, that's possible.

Gael Duez (32:04)
Okay, I have to say that you didn't tell me this information when we were preparing the recording. So I've got like a big stupid smile on my face like, oh cool, the Green IO Conference has helped connections and move things in the right direction. So now I need to focus back because this super interesting what you've just said, but thanks a lot for the feedback because you made my day. So getting some focus back and thanks a lot for stressing how important it is to have a holistic view and putting all the different stakeholders around the table and using the workshop framework that you've coined during your research. And I get this is the right approach now for the sake of understanding, and I'm not saying this is what you say that should be done, but just for the sake of illustration, could you share? One or two other examples of features, change in design that you would see in the Vinted platform to offset or to counter some of these negative rebound effect, or actually rebound effect are always I follow your definition, for the Vinted platform. And as you say, there's nothing personal against Vinted, it's just for the sake of illustration. But you mentioned already the absence of filter for the location of the good. But would you add other features, design changes?

Laetitia Bornes (33:37)
Yeah, sure. I worked with designers that weren't designers from Vinted, but that were professional designers interested in systemic approaches. And they worked on the Vinted case study. So I can share with you some ideas design to improve the social environmental impact of Vinted. And I definitely do not say that we should do all at once because it has to be strategy with different steps or let's say design interventions that must be coherent and that must be assessed before being put into place. you can have actions that can be from the lower level to the higher level. So a low level would be, for instance, acting on the direct of transportation. So for instance, using a better transportation system or things like that. We had the idea of promoting ⁓ group shipments, ⁓ providing local sales or collection points to reduce the transportation. Then you have other ideas to charities. Designer, they thought about a portion of the profits to charities or ⁓ redirecting users to donate to charities when a clothes didn't sell or when they reached a quota. with the tool that to the designers during the workshops, so the Magnitude tool, which is a modeling tool, they could compare different design strategies. And for instance, it was much more effective to redirect users to donate clothes in some cases, rather than donating a portion of the profits of Vinted.

Gael Duez (35:34)
Would you reach such a conclusion? How can you say it seems to more efficient to donate when I cannot sell it rather than reallocate a portion of my revenues to charities?

Laetitia Bornes (35:46)
So in fact, we modeled it in the magnitude tool. So we calculated the loss ⁓ of revenue for charities and we compared the difference between, for instance, donating 1 % of the profits of vintage, which would be huge, and redirecting the users to donate their clothes, maybe in, let's say, 5 % of cases. I don't remember the exact figure. So we just made that ⁓ seemed to be relevant to the designers during the workshop, and we compared it. And that makes sense, because when you give a portion of the profits of vintage you don't want to give a lot of this and this profit is just a few percentages of a given sale and if you redirect a seller to give his ⁓ item then whole price of the item goes to the charity so it's a much bigger impact, let's say. Does that make sense?

Gael Duez (36:59)
It makes total sense. Thanks a lot. And this modeling was from an overall economical perspective, from the charity perspective were you also able to model the perspective from the user?

Laetitia Bornes (37:17)
So this is part of the methodology, but it's not part of the quantitative model at all. So to be honest, the modeling tool is quite basic. It's like you could do almost the same thing with an Excel sheet, but it's dynamic. So you can have a simulation through different months or years. And it's more visual and it's easier to work with as a group of different stakeholders who are not experts in consequential modeling, for instance. But it's quite basic, and that's really a choice that I made. You have different, let's say that you have basically two approaches to model social complex systems. Or you can model with a top-down based on systems dynamics, and that's what I did. Or you can model with an agent-based approach that is more bottom-up and you are just describing the behavior of individuals, you put them together and you expect to have emergent phenomenon. my case, I considered that the people in the room, so the designers, makers, maybe academics, experts in textile industry and so on, would be more capable of imagining impact of something on the users than the model itself. So most of the things are in the brain of the modelers and the stakeholders involved. And a few things, just the orders of magnitude, and that's why the software is called magnitude, are in the model. So they would say, for instance, OK, we could put into place a virtual currency that really force the sellers in using the money they earn from sale on second-hand items, either on vintage or with partners. If we do that, we will probably lose this amount, this percentage of sellers. And we will just put in the model the variation of the number of sellers that we expect and the variation of the percentage of the money that is used ⁓ to buy fast fashion clothes, for instance. they will imagine all the emergent phenomenon, all the user's behavior, and they will make some hypothesis, and they will test it on the model just to have the impact on the final figures of the key indicators for them that would be carbon emissions, but also loss for charities and other impacts the model will be based on mixed data. of the calculation is based on data that you can find the literature, for instance, the carbon intensity of a kilometer traveled by parcel or a truck. Then you have some data that is based on the survey. So what is the percentage of people doing impulsive buying? What is the percentage of people who are actually buying clothes instead of brand new clothes thanks to Vinted and so on? And then you have the assumptions of the team of stakeholders working on the model. So that's how you use it. And it's really a tool for reflection, but it's definitely not a tool for prediction. That's more the way you use it.

Gael Duez (40:51)
Okay. You know what? There are so many things that I would like to unpack with what you say that actually I think I'm going to pause for a moment on this modeling things. And I think we will do a double episode if you don't mind. because I would love to ask you several questions regarding the limit to modeling and it's not every day that I have an academic on the show. So discussing a bit scientific methodology, see a lot of interesting angles here with this specific use case and even playing with model and what is systems but I would say to close our focus on the vintage use case, I would love actually to zoom out quite seriously and not talking about avoided emission of a specific company. But truly zooming out and talking about digital technology and the entire digital sector or IT sector. There are a lot of discussions about the assessment of the footprint and the handprint of digital technologies that goes way beyond the micro level, which you illustrated with the vintage use case. And maybe to quote a big name here, I'm a big fan of Gautier Roussille's job. And he wrote several articles on the… avoided greenhouse gas emissions thanks to digitalization, challenging the conventional assumption that ⁓ digitization is by default good for the environment. We hear this a lot, like the need for a twin transition or transformation with the digital working hand in hand with the ecological transition. I know that it's really going from micro level to macro level, but did you make some connections also between what you found in your research paper and his findings? And is this question even relevant or there are two different words and we shouldn't mix them?

Laetitia Bornes (42:52)
Yes, that's absolutely relevant. In fact, I totally agree with this criticism of the twin transition narrative, which seems to argue that digital technology will enable the ecological transition and which suggests that this is the case whatever the context. So the first problem that I see is that it seems to suggest somehow that since digital technologies will enable the ecological transition, we don't need to deeply rethink our lifestyles. And what's more, it seems suggested also that it doesn't matter if the direct impacts of digital technologies are increasing since they are offset by its indirect effects. So through the decarbonization of other sectors like transport, agriculture, construction and so on. first of all, there's nothing to prove that this is true in any case, not even close. And for this, I invite you to read the ADEM report, environmental assessment of the direct and indirect effects of digital technology on use cases. So it's a French reference, but it has been translated to English. And additionally, even when certain digital technologies actually help to reduce carbon emissions, they also lead to other impacts intensification of resource extraction and pollution. And on the top of that, the negative indirect effects of digital technologies. So in particular, the rebound effects we were talking about are often underestimated or completely ignored in the calculation, especially those that cannot be quantified as I mentioned. Of course, doesn't mean that digital technologies aren't necessarily bad either, obviously, but I think that the concept of Twitter transition is a bit techno-optimistic and a bit misleading. So in my opinion, we need to be much more cautious and nuanced. And that's exactly what the vintage case study and our study shows, in fact. So think there is a wrong thing with this narrative and focusing on each micro case won't results in a coherent transition. We have to plan it.

Gaël Duez (45:31)
This is the end of the first part of this long episode with Laetitia Borne. In the second part, we will deep dive more on the theoretical aspect of model and systems thinking with a lot of insights and a lot of resources that she has happily shared with us. So stay tuned. Episode will be released next week.

Episode 58.b

Laetitia Bornes (00:01)
The problem is when you put a model that has been made for a given purpose in the hands of someone who doesn't know who doesn't want to recognize its scope and who therefore uses it outside of its field of validity.

Gaël Duez (00:18)
Hello everyone, welcome to Green IO I'm Gaël Duez and in this podcast we empower responsible technologists to build a greener digital world, one bite at a time. Twice a month, on a Tuesday, our guests from across the globe share insights, tools and alternative approaches enabling people within the tech sector and beyond to boost digital sustainability. And because accessible and transparent information is in the DNA of Green IO. All the references mentioned in this episode, as well as the full transcript, are in the show notes. You can find these notes on your favourite podcast platform and, of course, on our website greenio.tech.

This is the second part of my long episode with Letitia Born, a doctor in human-computer interaction, systems engineering and systemic design, who is one of the co-authors of a research paper investigating the claims made by the second-hand digital platform Vinted about the avoided carbon emissions thanks to its operations. As we saw in the first part, their findings were surprising, enlightening for designers and nuanced, with potential applications for the entire digital industry regarding how we assess its potential footprint and handprint, that is the positive impact it brings on our planet and our societies. In this second part, we moved away from the Vinted use case and discussed modelling, the scientific method and system thinking in general. You can enjoy this discussion without having listened to the first episode. However, I would suggest you do so to enjoy all the references, especially to the Vinted study. So Laetitia, when we were discussing how you model the vintage use case and all the results that came along, I had like a ton of question about what are the limit to modeling? What are these assumptions that you built your research paper on, et cetera, et cetera. And I think it's a great opportunity to have a trained researcher, a doctor now on the show to discuss a bit about not the vintage use case itself, but how we actually can do systems thinking in a proper scientific manner. And maybe it's a bit provocative here. My first question about it is, because we know that there is limit to model everywhere, where are you unhappy with the way you model the vintage use case? Whether it's a boundary that you would have changed, some proxy data, which you would have preferred having primary data instead, or it's assumption that you couldn't really double check or shortcuts that you had to take. It's just a sort of transparency exercise that, it's not because you've got a published research paper that everything is flawless and that you didn't have actually to put limitations to the scope of what you wanted to investigate.

Laetitia Bornes (03:43)
Yeah, So I would say that ⁓ I regret that my model focuses mainly on carbon emissions and not on the other impacts, apart from the loss of income from charities. But this is linked to the fact that I drew on the value study, which focused on avoided emissions in carbon equivalent. I've also made a big shortcut by displaying the number of sales per month to assess the economic viability of a scenario. Because if you change the business model in an intervention scenario, instance, by to a subscription then the economic viability would no longer depend on the number of sales with delivery, but on the number of users. It's not really complicated to change in the model in reality. It's just that I've never taken the time to do it. also, I must admit that the system that calculates the sales per month is quite basic and not really realistic. But all of this is not really a problem for the purpose of my modeling, which was only to demonstrate the sensitivity of assumptions and the fact that very different results can be obtained on the basis of the same study if we include other indirect effects. I wanted also to demonstrate the value of transparent and dynamic modeling and of comparing interventions to strategies. So I did it with the help of the that participated to my workshops. ⁓ And yeah, so I wanted to carry out a formative evaluation of magnitude, my modeling tool with professional designers that I ⁓ could do so as well. it depends on the purpose of your modeling. In my case, the way I use modeling is really not, let's say, rigorous, ⁓ even if it's shocking, because the aim is to predict precisely something. So yeah, in my case, it was to demonstrate some things. If I would have done it for Vinted in a real we would have made it more rigorous, for sure. Yes.

Gael Duez (06:09)
That was the exact question that I wanted to ask to bounce back on what you said, because thanks a lot for this transparency exercise, but also to remind people that we model things in a certain way to achieve certain goals. And your goal was not to provide Vinted a better model to assess their claims on avoided emissions. And that being said, as you just mentioned, what would what have done differently if the model had a different objective which is providing to Vinted a more accurate or a more nuanced way to assess their avoided emission? Could you just share maybe two or three examples? Obviously, you're not going to write a new research paper live on the show. I mean, you can do so if you want.

Laetitia Bornes (06:54)
Okay. It's difficult to anticipate the things that we want to include in the model rely on the methodology. So before doing the methodology the actual people from Vinted, it's difficult to anticipate. But I think if I had all the time and resources that I want, I would have more investigated. The way people use the money they earn from sales and the impact of Vinted on the fact that people renew their word more frequently. So can we quantify how many users buy more items because they can sell it on Vinted? That's something that I would definitely investigate and yeah, have a better idea of what people do with the money they are from but it's anyway you can do a new survey you will still have a lot of uncertainties and something that is not in the model but in my software and that is definitely lacking is a way of visualizing the quantitative uncertainties so you have uncertainties that you can't quantify but you have some uncertainty that you can quantify. And for the moment, my software doesn't help with So for the moment, get a range of uncertainty, you'll have to do for each context two scenarios, one optimistic with every parameter at an optimistic value and one pessimistic. And then you say, OK, I'm between those two values or graphs. to conclude, I said that it would depend on the whole methodology that I would conduct but those were the main things that I would like to investigate personally.

Gael Duez (08:49)
Okay, so the level of uncertainty with as well as the direct connection between the sales and the amount of opportunistic buy. Am I right to say or am I missing some other items here?

Laetitia Bornes (09:09)
Yeah, the rate of sale and the way people renew their wardrobe and also the way they spend their money on from sales.

Gael Duez (09:19)
And actually, the third point was actually the way they spend it. And you beautifully explained it previously with a significant share, which is not quantified in this research paper, but that you could assess is that it is spent on fast fashion items. So it's actually not helping the planet that

Laetitia Bornes (09:43)
Yeah.

Gael Duez (09:45)
So, you know, while you were explaining in a very transparent way, all the limits and all the choices you made for your research paper I had this sentence bouncing back in my head. I think it's from a British statistician, George Epibox. All models are wrong some are useful. And I had this sentence a lot in my mind also when we were preparing this episode. And I wanted to ask you how wrong was your Vinton model and was it still useful? But I think you already perfectly answered this question. But I had another question related to it because this sentence, all models are wrong, some are useful, is sometimes used in the wrong way to, for instance, push back against IPCC models defend other models which would question anthropic climate change. So to broaden a bit our perspective, I'd like to ask you this question. Why should we consider with more scientific robustness the modeling exercises done by the IPCC than the one done by a climate denier who holds a PhD in physics, let's say, or even a Nobel Prize, as in the case of the Dr. John Closer, And another way to put my question is, can you give us a scientific methodology, one-on-one courses in two minutes?

Laetitia Bornes (11:20)
So first about the quotation. Actually, I included it in my thesis So that's funny that you mention it. And in its long version, it says in fact, all models are wrong, but some models are useful. So the question you need to ask is not, is the model true?

Gael Duez (11:31)
Excellent.

Laetitia Bornes (11:43)
Because it never is, but is the model good enough for this particular application? And in fact, this quote is absolutely not a criticism of models in general, but rather a way of saying that models should not be taken out of context. So the problem is when you put a model that has been made for a given purpose in the hands of someone who doesn't know who doesn't want to recognize its scope and who therefore uses it outside of its field of validity. So it's also important to understand that there are many, many different kinds of use for models. for instance, in my case, and it can be also the case if we have a look at models that are used by IPCC, ⁓ you have some models that are predictive models. So they seek to represent reality as closely as possible and to predict the future, which is possible if we are in a linear situation or if we know perfectly the mechanisms of evolution. So that's the case for weather forecasts, for instance, you have always a kind of uncertainty. And then you have exploratory and prospective models which seek to facilitate a reflection in the what-if logic. So we wonder what might happen on the basis of different sets of hypotheses which we consider to be likely or to be extreme and so on. So that's the way I use models for instance. So to come back to the question about the IPCC, there are different things. So the IPCC produces or rather evaluates and shares that are based on different sets of assumptions as a basis for reflection and political decision making. So these are what-if scenarios and they are exploratory. is kind of predictive of a situation assuming a set of hypotheses and they are perfectly legitimate within this scope. if we accept the So for instance, regarding the anthropogenic nature of climate change, there is exploratory about it. statement is actually unquestionable because despite the huge number of researchers and increasingly accurate climate models, no model has ever been able to explain the observed climate change without including human activities in the hypothesis. So… a proof of the anthropogenic nature of climate change. And I'm not necessarily able to go into more detail about it, I recently read a book by Pablo Jensen is called Your Life in Numbers, Modeling Society for Data. So this is the version in English, but in French, it's totally different. I think it's literally why we can't put our society into equations, something like And yeah, he is really good about explaining the different kinds of models and how the weather forecast model has become so accurate and why the anthropogenic nature of climate change has been proved.

Gael Duez (15:19)
That's interesting what you mentioned because you say no model has ever been able to prove that the climate change has not a massive part of a human made, causality. However, we can find models of people and sometimes people with some degree in physics. We've got even, as I mentioned, the case of one Nobel Prize, not experts in climate, but that's a different question, but still a Nobel Prize, who would push a model saying that anthropogenic nature of climate change is not assessed. So I guess modeling is just the first part of the story. What makes a model the model or the source of truth at a certain point of time in history? Because science is always evolving. And what makes you so sure now, thanks to the IPCC work, for instance, that you say that it is an absolute truth that climate change is human made? And I know that I'm playing the devil advocates here, all the listeners in you, you know about it, but it's me playing a bit dumb saying, but I see other model and they're written by people who seem to be pretty clever. So which model shall I trust? Because you know, all models are wrong and blah, blah, blah, and blah, blah, blah. So what would you say to these people and how would you debunk this partial approach to what is modeling and what is science?

Laetitia Bornes (16:53)
Yes, so the problem is that unfortunately there are, as you said, some people who sound very serious but who use their influence to say things that are completely outside their field of competence. So it's a bit like getting a model to say something that is outside its field of validity. It's quite the same thing. So for example, although I'm a doctor, I don't have any legitimacy to talk about quantum physics. And if I did, I shouldn't be given any more credits than a bricklayer or a baker or whatever. what ensures the validity of science is the research system, although it has many flaws that we clearly don't have the time to go into here, I think. It is organized to verify the knowledge produced. So when an article is published in a serious journal or conference, it has been reviewed by several researchers anonymously who have judged it to be solid and well-funded. And even if a questionable article has managed to be published, then the scientific community can intervene to have it withdrawn. A scientist should only speak publicly about his field of research and particularly about his published research work, because the science is by the publishing system. So you can do ⁓ whatever model if you don't publish it. And if you made the assumption and the hypothesis behind this model in your lab alone, with nobody to check it, it's not science. And in the case of IPCC reports, there is a new assessment of the published literature. So this literature has already been assessed and published. And then the people from the research of IPCC, there is a consensus building in the relevance research community. So it's really difficult to get something much more solid than the reports produced by IPCC.

Gael Duez (19:05)
I think that was our one-on-one crash course on scientific methods. Thanks a lot for reminding this to us. Going back now to the question of a model and systems thinking, I promise I will stop grilling you and you can go back to your normal life because otherwise this episode will last for four hours and we don't want to do this. But to prepare our episode, and to be honest, also to use it in my new Green IT course, I reread Thinking in Systems, the Seminole, Donnellas, Meadows book. And it connects a lot what you explained previously, starting with the importance of system boundaries and using the model for answering the right question and not trying to use the model to answer all questions and really fit for purpose, I would say. However, there's something that really puzzles me in her book, which is an emphasis on free information and short feedback loop. And she sees it really as the number one tool to influence the system, mostly for positive outcomes. And today we have access to all the information about climate change, resource exhaustion, etc. And it seems that our willingness to act for the greater good of the entire planet Earth system, or would say our capacity to embrace complexity is actually reducing. And I was wondering, and that's super incredibly pretentious to just state it, but did she miss something? Or much more likely, is it me who's missing several things? Like, is it a case of bounded rationality, especially our biases, a bit like you explained with the researchers out of their scope of knowledge, I would say, or the information flow being crippled by the frequency and quantity of inflows in our digital world, or information being too manipulated. But I really wanted to get your feedback. And I know it's really like pure systems thinking theory about the importance of information to enhance a system and why she puts so much emphasis on it and why it doesn't seem to work despite having such a great access to information today. You've got a lot of time to answer this question.

Laetitia Bornes (21:36)
Perfect. So first, thank you for mentioning Danila Meadow's work and the levels for intervention that she worked on. So I obviously rely on Danila Meadow's work and on her identification of levels for intervention. I just don't use the 12 leverage points which seems to me to be too detailed and too complicated to explain to people. But I rather work with the four main categories ⁓ of leverage points. So the fourth one would be acting on the constants and the parameters of the system. The third one would be acting on the feedback loops and delays. The second one would be modifying information flows, as you mentioned, and changing system rules. And the first one would be changing the goals of the system and maybe altering the underlying So as I understand it, these levels should be ideally combined because they are moving from the fourth category to the first one, levers are from the fourth category, are quicker or easier to mobilize, but more effective just in the short term. And the first category of levers longer and longer to mobilize, but they are increasingly powerful in truly transforming a system over the long term. So you might want to combine them and not to act only on the long term ones. unfortunately, as we mentioned, providing information is not always enough, especially when it remains abstract. 

Gael Duez (23:32)
Environment, you mean by abstract?

Laetitia Bornes (23:34)
Yeah, because you know about the climate change, you know about the impacts of what you buy, not always in fact actually. So have the information in our world society, we have it partially, but anyway we have a lot of information about climate change and environmental impacts and so on. But it remains abstract because it's figures or because it's events that are not always we are actually living. So you have some people that are quite shocked because they knew a landscape and this landscape changed affected by climate change.

Gael Duez (24:13)
Like the glaciers or things. Like this.

Laetitia Bornes (24:16)
Yes, so I think that if the social environmental impacts of a certain type of conception or a certain type of actions were to be felt immediately and in a very tangible concrete way by the people at the very point of the this would mean that we would somehow act on the delay of the propagation of information. And I would say on the intensity of the information or the way it is felt. I think that this would change things radically. And above all, from what I have understood, beyond information, you have this profound paradigm shift. And this paradigm I think that the way that the information remains abstract is kind of a barrier between this information and the paradigm shift that we need. So when I say paradigm shift, it's what's acceptable in our society, we value, when we make decisions and so on. So yeah, I think we have information, but it remains partial to just some people and this information in an abstract form. I'd like to say that it's not a problem to question the work of Donela Medos because actually she didn't hide the fact that she identified those categories of leverages intuitively and that further research was needed on this subject. There were not a lot of research afterwards. And in fact, a researcher called Ryan Murphy, so he's a systemic designer. He has published a year ago or maybe two years ago, an article on this subject, which explains this very well and which invites the scientific community to continue research into the categories of leverage. So yeah, that's supposed to be a work in progress, but people use it as a recipient. I think it's really useful for thinking about possible intervention. And for instance, I used it in my case study, for instance, in Vinted. As I said, there are different levels of intervention. And I gave these four categories to my designers, my participants, so that they can think of different kind of interventions. for instance, about information, they would informing the users about the environmental cost of a clothes, of an item. Or system rules would be banning certain ⁓ brands of fast fashion from the platform. But then if you move to the paradigm shift, there would have other ideas like enabling closing exchange or promoting clothing repair and customization. So you know you can have a strategy that would combine these different kinds of approaches and of levels.

Gael Duez (27:24)
So that is so much interesting. And I could go on and on and on and asking you tons of other questions. thanks for the honest answer that it's still working progress. It really had this feeling and that was just a feeling thought pretty much worthless that she comes from a generation where internet was not invented and she lived long enough to say it's wide adoption, but sharing information was key and they lived on this assumption. Like you just share information and that's it. And now with all the elaborate answers that you provided like here, but there is information and information there is abstract information and comprehensible information. There is information in how people are ready to receive it because of all these values and all the, as you mentioned, the potential paradigm shift that will be required to people to actually accept this information or accept to do something with this information and so on and so on. So I'm parroting what you say. So I'm going to stop here, but really I think this work in progress approach that you mentioned is super important because it's not information for the sake of information and we will share obviously the link to Murphy's article. Now, if you indulge me one last question before the usual closing questions. It will be also related obviously to systems thinking. And I was wondering also rereading this book, is systems thinking compatible with the way our societies work now? And by this, mean, I'm especially concerned with this crazy focus on short term that we have. can, for instance, see it with listed companies having to display quarterly revenues and so on. And even more like physiologically speaking, the chase for this immediate shot of dopamine that is provided a lot by our digital platforms. I was really like my fist in thinking is somehow the quest for some sort of long-term understanding of things and is our species, at minimum is our society and especially our Western world still compatible with this sort of long-term thinking? And once again it's a question I guess you can take several days to answer but I just love to get your immediate reaction on it and I promise after that we're done because otherwise you will stay with us for days.

Laetitia Bornes (30:06)
So I think that systems thinking is not only compatible with the way our societies work, but it's essential more than ever because we are in an increasingly complex inter-twin set of social-technical systems. So yeah, I think it's more necessary than ever because otherwise we can't understand the systems we are evolving in. Regarding the short term and ⁓ shoot-up dopamine things, think certain thinking should be maybe, yeah, it requires some time. ⁓ It's not as immediate as other stuff. So it has to be explained. Maybe we have to prove its efficiency on the long term to make people accept it. But I think there is a lot to do in the education system. And without exactly mentioning it, there is a really nice book about that that is wrote by Sean, and that is called The Reflective Practitioner. And he explains how we have specialized education in silos and why it's not relevant to the complexity of real world. So that's, I think, a good reference to mention here. So I think maybe it should come from education. I don't know exactly how, but I think that it's necessary more than ever and that in all sectors. So I think it's essential to use system thinking to debunk or at least reframe false good ideas of innovation. If you look at AI with a systemic perspective, the claim benefits the adults on the floor long. So yeah.

Gael Duez (32:11)
You see things in a very different way when you embrace systems thinking. That's for sure. And actually, and that's going to be a smooth transition. For people interested in system thinking and being sort of beginners or just like amateur, I would say, besides Donnela Amido's book, would you have one or two resources that you would like to share with them so that they could sort of ramp up their knowledge in this field?

Laetitia Bornes (32:41)
Yes, sure. So ⁓ if we hold the first generation of systems thinking, which is more about modeling, I would recommend definitely Limits to Growth, which is also written by Danila Meadows and her husband and other folks. I also would Business Dynamics written by Sterman. And the more recent book by Smaldino, which is called Modeling Social Behavior, Mathematical and Agent-Based Model of Social Dynamics and Cultural Evolutions. So that's for the of systems thinking, but there are many branches of systems thinking. And I would also definitely recommend Checkland, Senge, and Michael Jackson, which is a system thinker and not a music artist.

Gael Duez (33:40)
And as usual, we will share all these references in the show notes. So it will be super easy for people to double check these books, all these articles. Maybe just for people already quite literate in systems thinking. mean, what is the latest cool stuff in the research field? Beside your work.

Laetitia Bornes (34:01)
I don't know if it's the latest cool stuff, I think that if you're already familiar with systems thinking, should follow conference called Relating Systems Thinking and Design. So I'm making an advertisement for systemic design, which I think is really useful and interesting and I think it's definitely worth following the work of Ryan Murphy, whom I mentioned earlier, because he a lot of really interesting stuff.

Gael Duez (34:36)
Okay, excellent. Thanks a lot. That's going to be a lot to digest for the readers. Maybe, and that will be my final and usual question, we shared a lot. was both very hands on with this Vinted case and very theoretical. And that's good sometimes to tool up with theories and models to be able to embrace the complexity of the world. But just to finish on a more optimistic note, would you share a piece of good news regarding sustainability, with the listeners.

Laetitia Bornes (35:07)
So it can be maybe related to systemic design, but what interests me a lot at the moment is the concept of protopia. I think that we&