Episode 8 - Future of Design Methods - Design Theory and Methodology 2019

Speaker 1 Guess what? I have a breakfast. This morning. What? Rinse. I Speaker 2 drink that. Yeah, so did I how do you feel? They're really good job. Speaker 1 Hello, is Peter here? This is the final podcast in this year's DTM series. And in it, we explore what the future might hold for design methods and particularly how Ai and data will change the process of design or maybe not. First of all, I talked to Alicia Jack. Cardi, a professor here in delft and someone who explores how cutting-edge Technologies are changing the way we think about designing after the interview Mica and I try to figure out the future and surprisingly return to some familiar DTM Concepts, perhaps, the future isn't so different to how we design now. Well, to find out the answer to this question, we'd better get on with the podcast. So, I'm here in the studio with Eliza Jake Hardy, who is a professor of interactive media design here at IDE and delft. And also Professor post industrial design at you mayor University in Sweden. So you have a two major roles, but you're also an expert in artificial intelligence and designing, and we're going to talk about the future of design, methods and design processes. So welcome to the DTM podcast at Lisa. Speaker 2 Yes. Thank you. Peter. Thank you for having me. Me the expert in artificial intelligence and design might be a little bit too Speaker 1 much, but Speaker 2 I certainly am very interested in artificial intelligence and disruptive Technologies in general. Speaker 1 Not good. So you've recently written a really interesting paper, but you gave me to read getting across the idea of more than human design. And I think we'll come on to talk about that in more detail. But the my first question was, how did you come to be interested in Ai and design? Speaker 2 Yes. I have always been quite fascinated by technology because I'm interested in how humans communicate and interact. And through that build, it reality around themselves and today more so that happens through technology. So any kind of technology that does have an impact on how we communicate or how interact for me. It's absolutely fascinating. And then I started to look into digital networks very early on. Looking into Web 2.0, architectures, social media, internet of things. Now, artificial intelligence is kind of a natural. Speaker 1 So you've had a long history of yeah, snoring technology in your paper, to quote from your paper. You say something that I thought was really interesting actually and it's the design process is no longer something that happens before production. I think we're very used to having the idea of design. The Producers something the end of it, or the process results in. In a product at the end of it. So Kendall is stabilizing Speaker 2 process. Yeah, the Speaker 1 end. Yeah. So what can you describe what you mean Speaker 2 by that? Yeah, it's the kind of design as we know. We don't often teach it. Particularly in our Bachelor, programs really comes out of the logic of industrial production. And so when when we used to design cheers from us production, then we needed to make sure that what we were designing was right and we developed Ways of doing doubt methods for prototyping iteratively, and, and try to minimize risks of mus replicating for so shortcomings in what we were designing. But the kind of technologies that we have now like, data Technologies and artificial intelligence in particular really Challenge and a very different from that kind of logic. So what happens is that not only what? We design can be constantly updated at a lower cost before a, if we didn't get it. Right, then. It was a problem or the think, you know, the testing has to be done before production because changing something afterward was very difficult and complicated and very costly. And now, not only we can do it in a more agile way. The very product that we are, experiencing is coming into being so to speak. At runtime is assembly alone time. So my Netflix looks very different and behaves very differently than your Netflix because it comes together as a something that I can experience. Yeah, in the very moment of views and it feeds on that I use. So, with this type of technologies that are based during information data, the distinction, between production and consumption is almost dismantled. And design in a way continues in use and after use, and it feeds into Speaker 1 that what you're describing is a, much more fluid. There's more fluidity. It seems like that in the in what we produce as products because we're very used to the idea that at the very beginning of the design processes. Those are the decisions that have that you need to get right for production because they're cheap to make at the beginning but they're expensive to make it the ends. Is that that turns around that whole process them into something? So what are we actually designing? Then? Speaker 2 What are we actually designing? We are designing conditions for certain type of interactions and experiences to come to expression, or for a certain value, propositions to become worth alas interacting with the product, or with the service. There is a fluidity. So there is a man. Liability. That is intrinsic to the different type of material that we're working with. But there is also, I like to think of it as a, as a more probabilistic character to what we Speaker 1 make. Can you give an example of a product may be in health care or something like that, Speaker 2 or in, for example, there is these startup in the UK called vitality. And I believe you can call it as often is referred. As an injured Tech is using data technology to monitor people's physical activity, and use that to provide a certain type of insurance plan and benefits. And so that insurance plan does not exist. Prior to, you find the wearable, very neat and the forming the new everyday activities. Exercising. Yeah, taking walks and so on and so forth. So in that sense, it's probabilistic because that there is, of course, a set of parameters that are set, but the outcomes of that is not necessarily always Speaker 1 predicted find or yeah, so it's more like kind of setting a sequence of or a set of parameters in motion. As a as a kind of design, or rough design, and then seeing what happens. So that it's constant prototyping. I Speaker 2 guess it is. Yes. It's sort of a constant for the typing Roy Osgood. Who was my PhD? Supervisor long time ago, was used to call it. A kind of seeding seeding conditions and in some cases this may be parameters. In other cases may be constraints or a certain type of interaction, but it's sitting right in there. Planning ahead completely. Yeah, Speaker 1 and I think it's really interesting. Just the idea that we in education. We're still teaching a design process is very much aimed at I've certain product in an outcome and assessing that outcome. And but the loop the loops are Speaker 2 really really tricky because in a way we we need and want to be able to anticipate. Yeah, to an extent the outcome, but we cannot fully completely. We anticipate it at design time. So we need to be able to anticipate, not the outcome in invite self. But the type of interactions that may feed into certain type of outcome. So producer and kind of consequences. And that's the shift that, I don't think we're conceptually and methodologically really, it keeps to. Yeah. Yeah, Speaker 1 there are two aspects that you talked about in the paper, which I think are really interesting. There's sort of a maybe at different ends of the design process. One is the idea. It we're used to the user or the person being at the center of a design process, you know, we design for people, the design process is aimed at sort of understanding people peoples requirements. That's one aspect of design. Then the other one. Is this, the stakeholders in a process and how we bring various groups to participate in the design process, you know, that may be a client. It may be certain user groups or manufacturers, or, but we used to this idea. Idea of thinking about stakeholders and I want to kind of explore those two concerts. So first of all, the kind of user. What does it mean? When you know, you're not having that that user at the center of the Speaker 2 process anymore. Yeah. No, it's actually a very interesting questions. I never really I guess try to articulate it in that in that way, but it is quite interesting. So the critique of focusing on the user is not so much because what people want Need matter less, but because of these logical industrial production that has informed the way in which we think about design. We still approach the design of this type of Technologies and the products and services platforms that come with it as something that is there to be used and consumed in a certain way according to a particular intention. But because of these intrinsic character of The object of design which is probabilistic. The reality is that there is not just one single use their many different uses. And so if you take, for example, fide spook, it's quite classical example. Write it the way in which it makes sense to me as a certain type of user might be for how it allows me to curate certain events or certain relationships in my life, but For another user ocean, we call it stakeholder. And then yeah, it's instead about the data that I can use for advertising because Speaker 1 there's so they're kind of unknowable Speaker 2 uses. So the same system is basically serving the needs of many different users, how many different stakeholders Speaker 1 and then the device is trying to understand that you Speaker 2 somehow well the desire to it. Yeah, it does author, a value to all of them. Hmm, all of this. Same time. Yeah, and so and so maybe we need to think in terms of stakeholders rather than just simply Speaker 1 users. So that leads me onto the stakeholders, which I think you met. You make a really nice point which is is that when we think of participation in design, you think of it as a kind of democratic in a way that you're giving people different voices in the design process, but when one of the participants in the design process is an artificial intelligence. Yeah, it gets rid of that idea because of democracy because Sweet, they don't have any, right, so we're not giving them any right to express themselves. So, how does that affect the hottest the Speaker 2 process? Right? No, I think it's an important distinction to be made the claim that we make in that article that in order to move forward in how we think of the conceptual space that we need for dealing with this new type of complexity and we talk of intelligent products. Artificial Intelligence being a participant in the design process. It's not because they have immoral stand in the process because they need to be involved on the basis of that more us attending. But because they, the data-driven Logics that come with the machine Behavior are Logics that we do not fully understand because Speaker 1 they are intelligent on there. In terms, they have known human and it's, Speaker 2 you know, they participate in making things in making your Netflix. Yes. Coming to life in making the price of your next boober, right in making your insurance plan. Yeah, they take part in that and so in a way, they are actively involved in the design process and they A dude according to Logics and perspectives. There are non-human. So I just want to be able to understand them and account for those and Factor than in the design process. Yeah, and for doing that, I need to bring them to the table in a different way than just thinking of them as tools that I can use for a specific purpose because that's just not what Speaker 1 happens. Yeah. Yeah. Speaker 2 Yeah. And soon we for example, have developed methods. Techniques to interrogate those kind of lodgings and to try to understand them and Factor them in the design Speaker 1 process. I think you make a good point about human participants in design process processes. Have some sense of responsibility to wear as artificial intelligent agents, they're responsive, but they're not responsible. So they're, they're, they're reacting in the same way that we react to. Yes, situations, but they're not, they're not responsible for their The decisions that they make order Speaker 2 but that's where it becomes interesting, right? Because they're not responsible in moral terms. But there is this beautiful code. But by ingold that says that ultimately all responsibilities a matter of responsiveness. Okay, I can be responsible only when I can respond. So even if for a moment, we bracket a notion of morality is a way to Understand responsibility and we start considering responsibility as the ability to respond. I think it becomes very interesting because then also machines might have different ways of responding or tuning their responses and in that could be quite an interesting design challenge for Speaker 1 us. I guess we're used to the the phrase of code designing a lots of the idea that everyone contributes something you have a phrase that the That's Co performance. Cool performance, which I really like because it's sort of suggest that you really have to do something a little bit differently with co-design. You sort of think everyone in the room kind of knows what they're doing, or what the purpose is with Co performance is much more of a sort of exploration. And Speaker 2 yeah, but I think also that the core performance of really is about the interplay between humans and machines or non-human entities and it's an idea. A'that is fundamentally based on the knowledge meant that the kind of things that a human and a machine can do calling court. Well or quite differently, they're quite different. And so cool performance is a way of taking advantage of that complementarity, but it's very much positioned in use could. So you could also say the co.design continues after an initial design, phase with this. Type of Technologies and in an Adder article, they talk about this. A sustained. Co-creation that's enabled by this kind of Technologies between humans and machines but the core performance really stresses the element of how we contribute to shaping certain type of social practices Speaker 1 together. Yeah. I know, I really like that. So I think we've sort of been talking around the idea of responsibility and I think the interesting thing about how processes and methods might develop in the future is They become ethical questions. Yes, they Embrace ethical issues to a much larger extent. I think than design methods have in the past, which I think opens up interesting discussions because we're sort of used to thinking of the design process is about anticipating consequences or being able to somehow predict consequences, and we try to limit unintended consequences. So we tend to we want to limit accidents happening and and really back to the user. We want the user to have this experience that we intended them to have. Yes, does the embracing a artificial intelligence designed as it? Does it open up unintended consequences? Is it, is it more liable to Speaker 2 that? I think that, at least. Let's put it in this way. I hope that by better understanding machine Behavior, we can account for those unintended consequences better, and And in a way, the what I think is needed is not so much developing ways that can help us really fully anticipate these consequences in terms of outcome. But understanding what are the maybe distinct rules of for the interaction or for the way in which different, let's say stakeholders participate in the design of process one. That is ethical. One that he gives enough enough handles for humans to still be autonomous in their decisions or that gives enough space to find meaning in the outcome of that specific interaction in a project. For example, that we have just wrapped up. Last year. We did take some of these ideas into practice and in doing that we really critiqued what What we thought of quite an ethical push of using that case, machine learning as a way to impose certain type of behaviors on two elderly people, which was the specific Target for our project. We are looking into assistive Technologies for older people and how using machine learning can become instead a way of empowering them. When you understand that there are different ways in which you can design, the algorithms. He's not just for accurately predicting the outcomes, but for facilitating sort of type of interactions in daily life. That in this case. We're just very simple resourceful strategies, that older people often put in place to cope with their agent skills. So how can machine learning reinforce that facilitate that? So in that sense? I would say the ethical uptake is what we refer. Over in that article that that you read as an ethical know how rather than an ethical know what? Speaker 1 Okay. So what's thinking about the future? What will it design method of the future? Look? Like how will Design is interact with them? If we think now that methods are things that we write down in books and on websites and which which bits of the process? I think maybe it's useful to think in terms of which bits will become more automated some Because I think, I think, I think the idea of automation is, it's very difficult to think about, they are using it, but it's sort of alternates, these things that you're not quite aware of. Speaker 2 So, I mean, they are already aspects or the design process that are automated and I think that we will see more of that. But then again, going back to the core performance. What are we good? And what machines are good at certain type of data collection, or permitting me to say that? Speaker 1 The Speaker 2 parameterization that one that that, that can be. Easily be done by machines, right? So, even benchmarking, for example, but any interpretation of the data or the patterns that are extracted, for example, through machine learning, any kind of sense, making, that is not something that you can fully automate. And so, what I think that a method assuming that methods are not fixed and that you need to appropriate them and make them yours. What a method of the future might look like, perhaps thinking of some, some of the methods that we have developed so far to deal with this or methods, that help you gain access to these non-human perspectives. So, for example, we have developed a way of conducting ethnographic observations that we called thin ethnography, where we can either add sensors and software to objects of everyday, use to understand how They are already connected before being connected to the internet and how that type of ecosystem have implications for how people will interact with the product or to interrogate existing products. For example, right now, we are being asked increasingly to use some of their techniques were developed like interview with things to look into the biases that are built into conversational agents. So you can think imagine a method that has Again these insights. Yeah challenges in challenges you to to to consider things that you thought were not relevant. Only that you couldn't see because at a different scale perhaps but also that you perhaps thought the we're not remarkable or not relevant for that specific problem and indeed they are. Speaker 1 Yeah, so I think there's a you sort of describe the whole range of design outcomes. You do you tend to think of it, intelligence is a The computational thing it is a computational thing, but it doesn't only apply to interactive products. It could be something like buildings or cars, you know, the parameterization and the suggestion by a computation computational agent of certain Solutions and that that dialogue all the code that kind of echo performance that you call that partnership. Yeah. Yeah. Yeah. Is I can see that developing in the future as much as you know, something like a design method body. Not sitting on your work, on your work top, monitoring your performance and telling you what to Speaker 2 do. I mean, I think that's certainly what we will see, is the rehearsal of these new Partnerships. Right? So, if we take the idea of machine intelligence, seriously, we can imagine that there will be an array of methods and ways to bring that intelligence or that type of perspective to the table in the design process as co-ed now go. Record as I knew as just a way to question, maybe certain choices, but I see it very much as a dialogue. A lot us. You were saying too old, not so much to automate the process, which, of course, it will happen. But it's Speaker 1 the coat is movie:. Yeah, the cope of the performers. Speaker 2 They did the hybrid design partnership that the hybrid sense-making process. Speaker 1 Yeah. Well, because I think in some sense, a design process is it's a cup Co performance in the sense that you, when you have Other people in the process, you're trying to work out what form of intelligence, they have somehow, you know, it might be expertise, but it might be, you know, the believability of the things that they say in the process. And I think the artificial intelligence. It's the same thing. You're trying to work out what that intelligence can do to. You can set set it certain problems in, it can solve them within you know, 500 milliseconds. Speaker 2 Yeah. So Speaker 1 that was a Lisa. It's quite a complex. So abstract discussion, I thought it touched on quite a few sort of philosophical issues almost and I have to say that I did I did with the recording so I missed the last bit of the discussion. There was only a little bit and I did thank Eliza at the end. So, okay and it did sound like it ended very abruptly. Yeah, so I wondered what you thought weaker. Yeah, it made me make me think. So I really liked her her thinking is not usually awake. A, I think about design and, you know, I know you are also interested in the role of intelligence and artificial intelligence in design methods because if we're talking about the future of design methods, I guess I've always been looking at it from the other side and it's nice to kind of bring the two sides together. So when I say the other side, I mean that what we've seen over the past 10 years of service that designs really expanded in terms of its application domain, right? So more in the areas of, you know, what design can do for businesses and when it can, what I can do, For society in general. And I've actually studied how designers are kind of adapting, their design methods and practices to this new expanded field. But what Eliza I was talking about is more. You know, how technology kind of is changing design at the same time. So it's actually quite interesting to to compare those thing. I'm and bring those those together. I thought it was. It was interesting when you sort of think of a computational future, how many familiar Concepts you can sort of talk about? Out to. So we talked about, you know, kind of stakeholders and co.design in a slightly different way. Adds this like different. Yeah, aspect to the discussion in terms of introducing a kind of different intelligence and the idea of a computer or computational Intelligence being a stakeholder in the grossest. It just it makes you do a double-take. Doesn't it? You know, what would that be? And yeah, one of the things I thought, right? The end of the interview. There were two concepts that I thought were interesting to pick up on and that was When was, you know, when you talk about AI, you talk about machine learning. And obviously, a lot of the course has been about learning, you know, learning in the design process and the other thing. Right? At the end, at Lisa mentioned, the idea of dialogue to and they I think there were two of the fundamental things that we wanted to introduce in the course the idea that design is this kind of dialogue and also that the design process is a learning process. So I wondered, you know bending back to the first podcast about reflective practice that using computers in this way. Makes you kind of reflect on what you're trying to do and you know what, you learn and what other other intelligence is learned during the Speaker 2 process. Yeah, and how that in terms is comes Speaker 1 into those learning Loop. See ya and what kind of dialogue you actually have with people because I mean, in the sense is an artificial distinction between people and computers because people are very active, very people are very different to. I think we talked about in the interview about, you know, in a co.design session, you're trying to work out what kind of intelligence other people can bring in. The discussion not everyone is equal, are they? They're trying to, you know, they bring their expertise and you're in a sense, you're trying to work out what that expertise can bring and how you can work on the design together. Yeah. One of the things I was thinking about is that I read an article a year ago about the term artificial intelligence. So when the first car was introduced, it was not called a car. I was called a Horseless Carriage because they could only compare it to a carrot with horse. So when artificial All intelligence was introduced is always been, it's called artificial intelligence as in, you know, it's similar to what people do, but actually it's it's artificial, it's not that but if you think about it, it's really something fundamentally different because it's not, you know, a different version of a human being. It is bring something else it. So if we're talking about dialogues between, you know, human beings and different types of stakeholders and designers and computers. Then what does that type of dialogue? Really mean? I mean, it's still What? We need to learn and we're still learning a lot about dialogue. Yeah, Queen human being. Yeah. And alone when you bring other times, I mean, I think looking back over the last, maybe 25 years. I mean, since card was introduced in the 70s. We've been used to sort of computer using computational tools. I think, at Lisa, mentioned it to this idea that computers are at all that we can that we can use and that we use in a sense to reflect on, we have that kind of dialogue, if you're especially the kind of more intelligent cab these days, Days, it sort of gives you kind of kind of options, you can set a range of parameters and you can think you can follow our kind of a process that that you work with the computer in in developing. But I think what I got from that interview was that we're going up a level here that they're not kind of more passive tools. They're much more kind of active tools and actually, computers are actually participating in the process of design. Yeah, and it doesn't end. It doesn't end actually. Yeah. So yeah, you know, That's something he's, you know, before the product. Yeah, but here we talk about technology in the products. That's continuously. It's a signing and change. Exactly. Yeah. I mean, I think that was really striking we know that data is the kind of future and I think that opens up all kinds of questions about the use of data, the collection of data how things collect data and understand human behavior. Those things are all sort of caught up in the idea that we're trying to you know, and sign becomes much more fluid and diffuse, you know, it's not like you're trying to manage this kind of moving stream of data somehow. Yeah. So like a designer of the future is going to have to be able to understand and color manipulate the during the interview. I had the feeling that it was much more like playing, you know design will be able much more about playing and sort of seeing seeing what happens but within certain ethical boundaries, I think that's always going to be a something that humans bring is an ethical stance Speaker 2 designing. It reminded me of This talk of John Seely Brown from Xerox, Parc, but he Speaker 1 was talking about how fast Society is changing, how fast technology is changing. And he says, well, we're basically living in exponential times because things are changing so fast that no one can become an expert in anything and everyone will always be a newbie. So that's quite a scary thought. But he says, well, all you need to do in these kind of context is that you need to adapt. So you need to constantly We adapt, and I think that's what's also happening to design. You know, with these kind of new technological developments. We as designers, we need to constantly adapt and that's an interesting concept, because what does that mean them for students who studying design, you know, they started they studying these different design methods, but I think we should also be eating them all learning together, how we can actually adapt to a changing world. Yeah. It's that sense of I think the term is negative capability where you'll P in situations that are ambiguous. You can live in those situations and you can you sort of play with them. You don't get stressed. When things aren't resolved and I think that's an ability that design is, you know, good designers have that. Anyway, I think but the idea that a method is this thing that you can grasp hold off this kind of life jacket that's going to save you because it's a very, you know, a structured process that I do maybe that's not true in the future. That's something that, you know, that's an old way of Designing. I think that idea of User-centered design that Lisa was trying to kind of shift away from the idea that you know, right in the middle of the process is this set of user needs that you're trying to fulfill Once you turn that around and actually the design is all about exploring user experience and you know design is a bit more automated. I think that's the abilities and capabilities. You need change quite a lot. I think yeah. Something that complements that is that in my research. I'm looking at how designers deal with complexity in the world. Not necessarily it. It's just that we're dealing with complex societal challenges. And one of the things that we're seeing is that designers are more and more focused on relationships between people. So not just users, not just stakeholders, but relationships between different stakeholders and Speaker 2 the tensions that this causes and the Speaker 1 opportunities, you know, one of the examples as I studied this project, which was for Primary School teachers, and you know, what? We could do to help those teachers. Do their job better. And the first approach was well, let's just design a product or something that To help those individual teachers, but they ended up designing a speed sharing events. So an event when teachers come together, learn from each other. And in true, that means can do their job better. So, that's a good example, very, you know, kind of using the relationships between people and and I think in a way you're setting up the conditions for designed to happen and I think that and that's what I think at least always talking about, you know, she talked about seeding the design process. So you so as a designer you just Use that sort of important things in a kind of an abstract way and you, you set things in motion and then you allow designed to to happen. Somehow you're not in control of the pro, you kind of in control of the process because you set up the process, but but there are outcomes that you you won't expect. So you need to be able to deal with that ambiguity. Like you said, we need to think about the world in a different way. Creating platforms are things that enable or conditions. I think it also requires humbleness. Because if we're not humble about what we're doing, then we won't really learn. If we talk about adaptation. How do you adapt to adapt by, also learning from others? Also, from other disciplines, for example, so I think the future of design methods, we also be working much more with other disciplines and maybe feed into each other disciplines. For example, I thought the one of the methods, the future design methods are at least a talked about that. I thought was interesting was to try and understand what's happening. The perspective of a thing. I was an observing thing over, you know, I don't know. Like a temperature sensor or something. Thats collecting data about human behavior and trying to it's a common. But she called it was the digital ethnography or something. Yeah. I know it'll work. I think he used a cattle. Yeah. Yeah. Where you're trying to put yourself in the shoes of a physical thing to understand what it sees, as an example of a new method. I think that would That's quite Speaker 2 interesting exciting Speaker 1 times. Well, it's clear that, I mean the data science aspect of it on the data. That's generated. I think what I was quite interested in is when we sort of began to touch on the ethical aspects and how often ethical aspects come up in this kind of discussion with data and the what the final thing that I thought was interesting, was the idea Co performance to the, you know, I hadn't really had come across that term before the the interview and I suddenly thought that's quite a nice way of describing. Even even Design without computers. It's quite a nice way of describing design as a sort of performance that you're trying to stay each something in setting up a kind of collaborative process. And there is a kind of performance of gestures and language, and there's a kind of theater of Designing that's implied. In that term. I think is quite quite accurately captures, some of them or the physical aspects of Designing somehow or the the. So if the zionists go performers, then I our designers more playing directors, automating Rose. Well, I guess, I guess. Yeah, it opens up that kind of the map, that metaphor of theater. Yeah, it's quite a good one for dessert. Yeah, Direction and role playing. And you know, kind of the dialogue aspect, I think comes in. Okay, acting classes. Yeah. No, absolutely. Well, I think, I mean, and partly the second video. I think some of the videos that we seen have students have taken roles and acted out those roles. And I think that's a really I've always thought that's a useful. Way of trying to understand situations that you haven't experienced. It. Actually try and put yourself in my shoes. Yeah. So I think a discussion about the future of design touches on lots of things outside of what you'd you'd naturally, think of. So, I thought was the interview was good. And in sort of eliciting, those kind of discuss all the other way just to think about it is, you know, if we talk about the future of design, we can see all those changes. But it's also interesting to think about what is it? That will stay. Yeah. We still be designers. And yeah, what is it? Yeah, I think the Speaker 2 more we're changing, the also, the more we need to clarify. What what design really is Speaker 1 a good point to end on? Yes. Okay, that's our Speaker 2 final Speaker 1 podcast. Well, we may have a but we may have one more podcast. Yeah, just just giving our thoughts on the course, but that probably won't be for a few weeks. But I think that's the last kind of content podcast. And I really enjoyed talking about all these subjects. And I do think the podcast is a good way of just introducing people to the different aspects of design. I really loved making this podcast. I'm definitely going to do it a lot more in the in Speaker 2 the future. Speaker 1 And yeah, I think I really enjoy the discussions. We've had in this little, a little Studio, this little box. Yeah. I know. It's been great. Yeah. Thanks pretty, good fun. Yeah. Thanks Peter. Okay, and by everyone. Thanks for listening. Bye.