Name: Brainstorm Design 2023: How To Use Data To Create Better Cities For Everyone
Uploaded: 2023-12-06
Duration: 14 min 41 s
Description: Liselott Stenfeldt, Director of R&D, Gehl

Liselott Stenfeldt, Director of R&D, Gehl

Brainstorm Design 2023: How To Use Data To Create Better Cities For Everyone

Conferences

Sarah Stein Greenberg, Executive Director, Stanford d.school

G architects approach to city planning focuses on creating human centric urban environments and prioritizing the needs and well being of people designing cities that are not only functional but also enjoyable and sustainable. Gel's incremental approach to transform in Copenhagen from an auto centric city to one designed to accommodate the needs and habits of pedestrians and cyclists has inspired a global movement to redefine how we live. LSAT Sten Feld is the Director of Gels Cities Team in Copenhagen, as well as head of R and D lies a lot develops urban strategies using your mobility and data services to expose new patterns and unfold social connections. Please welcome lies at Stel. Hi, everyone. So nice to be here today and I'm really thrilled about how this morning started with the discussions. I was myself a student from the school of architecture but always looking for something else. So I actually went over to study data sciences and I also studied interaction design to actually try to encourage how you meet people and how you work with interaction. This later brought me back to architecture and now I am at Gale uh working with how to use data to create better cities for everyone. We are a global urban strategy and design firm and we're working with understanding how people and place shape one another because they do relate to each other. We are about 100 and 40 people. We're based in Copenhagen, New York and San Francisco. And I think we started off being an architect company and most people still know us as urban planners. But to be honest, it's only 40% that are urban planners in Gael today. And we more see ourselves as urban change makers, data or social scientists, strategists and designers. You can see this also as a sign on how complex cities are and how they're changing and how we need other competences. We have been working, we are working in very many cities in the world. We have data going back 45 years. That is observational data about how people move, how they stay in cities and how they interact with each other. We also understand that cities cannot drive the change by themselves is this and this is not only relating to budgets, which is a big part of it, but it's also relating to how you can have an impact. We do believe that it is shaped by public and private sectors. So our client list includes both. So when working, for example, with Google, we actually help creating like better opportunities for brand activation in public space and in place when we work with IKEA, we bring them closer to their end users and to the citizens and give them a voice in the cities. So coming back to this, the physical environment affects how people behave. People's behavior also affects the public space. What we want to do is to make it as easy as possible for people to choose the right thing when coming to maintain it. Empathy in the age of A I in urban context, we think it requires a thoughtful and intentional approach. There's so many ethical matters that we are actually confronted with in public space. There's a matter of trust, there's something about allowing transparency. There's a lot of aspects to think about in public space. This makes it a very good test bed. It also make it a tricky place. So for us, it's not important to be high tech. It's uh we are digital. I think we're hoping we're digital. Uh We do use digital technology. But for us, it's more important to understand what the intention is and to change something and have an impact. We are working with the glands. We developed a lot of digital tools in house. That's what our research and development team does. Uh where we actually connect data, we connect lived experience data with big data sets with online service with neighborhood life with spatial characteristic. And we want to call it thick data. It's not big data, not small data. It's something in between I will use some examples today to talk about how we actually bring data to action because I think this is also part of the importance. This first one is something about how to change culture. It's about how to actually translate data into stories that can have an impact Times square we worked with already in 2006. Uh we went out, we studied, we were supposed to create a better traffic flow. What we found out was that about 90% of the physical space were for cars, but at the same time, about 90% what we saw was people moving on this 10% of space. So this led us to the times square has no square. So when we worked with this, we could see how this data could actually help change policy. So this data actually helped uh the City of New York uh Department of Transportation to make a case to say, how can we actually change this into a square? So we were allowed in 2008 to free the space to do a weekend where we try to just put our chairs, just see what happens. This was measured. Obviously, we like to measure we are very database in that way. And that led us to doing this over a longer time. We were actually allowed to paint the pavement. We were allowed to put out better chairs and we were allowed to make people sit down and enjoy the cultural heritage, which is actually a and now 2019, many of these things have been implemented in the permanent uh way times square loop. And these are just some of the data that we then presented to the city where we can see decrease in pedestrian injuries, we can see decrease in traffic injuries, we can see improved travel time and so on. So this is how it's looking later. And one thing that I think is very important in this is the scalability. So we created a framework and over the last seven years, just there has been 70 plazas in New York where they have used this framework that we developed over this temporary time that has then changed on the utilized spaces. The next project is looking more on how we can work with cleaner air and cleaner air infrastructures. We're looking more on shorter term and we're looking at how we can create better places for, for a more well for Children in this case and for citizens that might not be considered as important in all all development cases. We connect the data between Google and us and we took our best experts. We wanted to know what eye level looked from a 95 centimeter perspective. From a three year old. We had a lot of three year olds in this project, we had asked their parents. So they were, it was ok. We followed them, they had cameras on their head and they reminded us what the eye level is and what kind of data we need to understand, to design for Children with Children. So what we did here was to connect all the data to connect data from Google, that was actually nanoparticles that was based on like street level data. So we could actually connect the data where this more air pollution was and where there were Children and where there were less air pollution. So this enabled us to then do a strategy for the city of Copenhagen where we worked with reduce and invite. So where can we reduce exposure for Children to be? And how can we invite people where there's less air pollution and make it more attractive? And this gave us a lot of uh guidelines. We created guidelines, we created design principles. I'm unfortunately not going to talk very much more about this project today. But this is also to give an example of what we use our data for. I continue with Shanghai Riverfront with is a project where we actually, I could talk about the strategy we developed in 2018, but I'm actually not going to do that today. I'm going to talk about the evaluation we did and the impact assessment we did because when we create a strategy like where we worked with creating a better connection in the city, we're working with active edges, we're working with diverse spaces. How do we know that it actually has an impact. This project was very unique because we did the strategy in 2018, 2021 after COVID, this is how it looked 42 kilometers public space. All of a sudden 15 minutes from about almost 5 million people. That's almost all Denmark. I just want to say uh what we did to evaluate was actually collect the data. Um We collect the data from social media to actually understand where is the high density of what people post and what do they post? We interviewed people on the ground to understand. Do you live here? Are you visitors? Uh Is this a time you like to spend time or a place to spend time? Uh We also looked at the spatial qualities, had it actually changed to have this connection to the city to have better access to metro and are people now not arriving as much with car? And these were some of the things we looked at to actually understand what what's behind this because the pictures in itself were nice. It is already like a really vibrant place to be. It's intriguing people are using it. But also did it live up to the strategy we created? Uh Here, you can also see taking away the car, make it walkable, actually creating vibrancy. The last project I want to talk about today is Stanford New School. And I think this is a very important project when coming to talking about data and talking about technology in this project, we wanted to understand how technology can actually make us understand the more subjective part and belonging. Um Stanford is creating their first new school in 70 years and they are focusing the school on sustainability and how you can work with sustainability in all different ways. They have been interested in involving people that maybe are not always part of the discussion about sustainability and also have them relate to this place and have them like share their feeling of belonging. So what we did was actually inviting people for photo walks. We wanted them to be very place space. We wanted them to share their experience about when they were walking around in the area. What feeling they have to the school and how they could actually relate this feeling, whether bad or or good to the physical space. We actually found that there were actually no tools for us to use. This is something we often find in ga uh we have some very clear ideas on what we want to understand, but we don't know how to get that data. So we actually developed our own tool, which is this eye level city app. And with the app, uh participants can simply take a photo, they can tell us if they like it or not and then they can annotate them and then they send it like postcards to us, then we get them in and here is a lot of dots that are all uh of course a photo and we had over 1000 photos coming in where they were annotated. And we all of a sudden could do a lot of um connection to other data we have gathered because yes, we had also interviewed people, we have talked to people. We very rarely use one data set. And then we could start to see the pattern. We could start to see that there is there is a clear line between positive tagged picture and whether there are people present, other people present in the place. And I will say that the old uh old thing J Gail always said was like where people are, people want to be. And I think this is kind of confirming us over and over again. It is important to design for social meetings. And we could also see that the top four words between all participants that were very different from each other was mental, well being architecture, physical comfort and atmosphere. Then we also have nature and community that are very strong indicators of where people said they felt they belong, they often belong in nature that was not very manicured, but very wild and natural. And coming back to this, people make places, this community feeling was something people were searching for. Uh and something they talked very much about when coming to having spaces to work into. Um some of this were was then translated into first guidelines, they were workshopped together with the people designing this the permanent part of this. Um And then we did something like this where we created, for example, the collaboration space you can see on left which is kind of the messy place where people can meet and it's more spontaneous and it's more like micro communities coming together and having these kind of flex places and making them adaptable has been a very big part of the outcome of how you then can define this. So this is just one of many examples on how it's important to also take the data and create actions for it. And I think this is kind of the take away from this talk I wanna give is I think it's important when coming to A I that A I and technology in general is still algorithms that reflect on our society. It's still something that is coming from society. And therefore we have to ask questions, we have to understand better how people behave, how we interact um to actually be able to do something sustainable, but also to make something that is really social, sustainable for everyone. So thank you.