 Okay. All right, everyone. Welcome to tonight's Technical Critical Assemblies with Lindsay Woodstrom and Luke Wilson. Our speakers tonight are radically changing the ways that we think of and visualize performance in architecture and design via technology and other digital tools and their work at very different skills. They're both using technology and data analytics or even the idea of data to make or to start to inform us how to make critical decisions prior to what is typically thought of as the design process. So from material specificities taking into consideration a much larger embodied energy cycle to visualizing the urban experience by, say, measuring the city that never sleeps or basically thinking of the urban experience of the entire sort of 24-hour time cycle and other urban phenomena, their work opens up the design process to larger cycles of really trying to quantify active processes rather than say, of course, the final static object, which we all know is never the case. And while doing this, making visible and creating these amazing visualizations or sort of very active tools in how we can start to fold this into the entire design process from even before the first thought of design is put on paper. So first up, we have Lindsay. Lindsay, she's an architect, designer, researcher, and educator currently teaching at GSAP. And who have collaborated with many sort of renowned design studios such as Studio Gang, Aranda Lash, The Living and with a group who builds her architecture. Her work has been shown and published recently, but widely in Factor Journal, it's been shown at the MoMA, Urban Design Forum and the Trinale di Milano. Next, we will see a presentation from Luke Wilson. Luke is a director at KPF, where he directs the think tank there, the KPF Urban Interface, or the KPF UI. There's like an amazing research that's being done to use computational research and super custom built digital tools for really large scale urban planning and architectural projects. So many of which you've heard of, like say, sidewalk labs or, you know, in New York, sort of working with the city to rethink the town. He runs many research collaborations with academic institutions such as, of course, Columbia, GSAP, Cornell, Harvard, as well as working with the city. So the New York City Department of City Planning to use these tools. And he has published widely from, you know, academically within architecture, but also popular publications such as The Economist or Wired or The New York Times. So with that, I will turn it over to our speakers and we will first start with Lindsay. Sounds good. Okay. Can everyone see my screen with my name on it? Okay, perfect. Well, thanks for having me, you know, tear to this time this evening. It's great to be with you all. And thanks for the introduction. I was calling this talk pre-projective materials, which it sounds like it's right on par with a lot of the things that you all are thinking about and working on in studio. So tonight, I'll share a number of a kind of wide range of collaborative projects that I feel come together to create what is my practice, much of which includes building up knowledge on material culture, like CZ mentioned, in anticipation of architecture and design. So first, who builds architecture? A lot of my methodology has grown out of working with who builds our architecture. If you don't know about them, they're a nonprofit organization that emerged from Columbia University. WBYA asks architects and allied fields across engineering to construction to better understand how the production of buildings connects their design and consulting practices to the workers who ultimately build them, build the buildings. So when you originally wrote the field guide in 2015, the book introduced new key terms. So a new lexicon, it asked new questions, used case studies and kind of situated a proposal that identified a location where architecture is within the complex of transnational networks, obviously of materials moving across oceans, but also knowledge moving across oceans and kind of connecting people who are designing buildings in the West to problems faced by construction workers who exist within that system in the East. So it shifted the focus from how buildings are conceived by architects to how they're materialized by this broad network of actors. So I joined Mabel Wilson and Conabari Bashe in 2015 and throughout the years, WBYA has worked to employ the representational tools and techniques that we all learn in architecture, studio and deploy in typical practice, but adding critical analysis in order to explain and make legible this kind of entanglement that we have with geopolitical and economic structures in the construction world. So here's a design drawing from our Boston architecture college gallery exhibition. So in this case, so what we do is we'll have like a number of exhibitions maybe to a year and each time the project will be advanced or iterated on. So here we explore the transposition of actors, not as drawings on pieces of paper, but rather as one to one scale figures projecting to the streets of Boston. Construction materials are manufactured as we know in many different places around the world as part of this elaborate network of resource relationships and economies. So each material travels and has value added across the supply chain, right? Each time it stops, it gets a little bit more valuable. This accounting happens with technology and certain people, certain folks have access to that technology and that control. So we explore how those kinds of power dynamics might be dematerialized at this exhibition. There's a lot of workers engaged with each of these sites with the transformation of materials and their experiences too are shaped by architecture. So the architecture of housing, architecture of factories. WBYA continues to accomplish recommendations when it comes to the many ways that we as architects can eliminate forms of modern slavery from material and labor supply chains. So keep your eye on that. Moving to a next project, we're responsible for the health, safety and welfare of the public right. This is kind of our primary role in the world as architects. But I think this can be interpreted at varying scales. So most often it's interpreted at the local scale, at the building scale on opening day, say, or maybe 10 years after when your insurance covers you. But as WBYA and my own practice explores ways that we are also responsible for the health, safety and welfare of non-local publics implicated in architectural sites. So in three material stories, I was published as part of them by Energy and Design. I explore an architect's material expertise across three materials, so steel, concrete and wood, and how our expertise expands far beyond the site that they're constructed in, but also the sites that they move through in order to get there. So designing, this is essentially designing a material supply chains from the inside out. This demands a new form of projection. This is my proposal and this is in order to allow ourselves to see in a non-local way. So all of the projection styles, perspective, plan, section, those have been designed as viewpoints as ways to see in a local way. And so one question that was asked during this project was how can we kind of create a new projective technique that allows us to include those other sites. So in this case, these become like unrolled worlds in which scale is more relative. And the narrative is told through a viewer's head movement as I explore the world from the inside out. So here's an example of how that might happen. So throughout the book embodied energy and design, these hand-drawn aquarctangular virtual reality sketches are peppered as kind of title pages of different essays. And they're meant to kind of bring you through the supply chain of the three materials as you explore the other amazing work that's in the book. If you were to jump inside these images, you can kind of also take a visit to the site. So in each case, they're like a different station, so retail or cultivation or logging, in the case of wood. And then I'll jump ahead. So in this case, it's the entire supply chain is kind of accessible this way. So if you have the book, I encourage you to take a photo of the paper and then jump inside the world. So when I kind of reflect on this project, I think a lot about how material choice, especially in this kind of time we find ourselves in with climate change, material choice is the moment that we actively eliminate carbon from our pallet. So it's when existing or new supply chains are either affirmed or denied. Material choice is essentially a vote for the factories, the working conditions, the trade agreements, the mining protocols, the fuel that's used. So these decisions at the scale of a building impact the long term health of citizens, both local and global. And that's how our kind of material expertise as architects is implicated. So this expertise has been tested, I've been tested in real in real world projects. So most recently, the schematic design phase for an engine factory for Airbus with my team at the living. So we recently finished this design for that client. In this case, we use generative design to explore, analyze and visualize the tradeoffs between qualitative and quantitative performance, especially how mass timber renewable construction connects to those metrics. This includes things like the energy. It's a little bit blurry. The the energy that's involved so embodied energy and body carbon for that material, but also operational energy when it comes to geometry. So that includes natural daylight, natural passive ventilation, energy savings, construction costs, worker experience, production flow efficiency. So we're using generative design to cast a wide net to explore 10,000 options to better understand and quickly quickly understand what's possible when you start to discuss with the client tradeoffs. So you might say, you know, here is one that solves for, you know, flow production efficiency. So when you're designing a factory, typically that's what designers are solving for is production efficiency. But in this case, we were able to kind of describe how when you only solve for one metric, you're kind of losing a lot of other qualities like material lifespan or let's say worker happiness. So we're trying to understand those better and to be able to measure them. So we went even further and we tried to track qualitative metrics offsite, like I was mentioning these non local measurements, conducting a social lifecycle assessment of the project. We asked things like who is involved in the making of the materials from all stages and how do those folks come together on the construction site. So in these moments of design decision making, we're we kind of carbon brokers and this has kind of been put into practice in this case, we're negotiating between civilization's needs and the earth itself, you know, between not humans and non humans. One example of this project was we wanted to have a certain flower planted near the near the building, but it attracted a particular type of bird, which we wanted to protect from the airplanes. And so that just becomes like this very sensitive understanding of species that are in the region and species that are endangered. And that's kind of where I think architecture becomes very interesting when you're kind of understanding what's at stake, what your site is creating. So not surprisingly from this point of view, beauty, I think that beauty and access to beauty starts to emerge with immense importance. Like most often beauty is the contract through which carbon is given value. And we ask ourselves, and the client asks themselves, is this worth it? So another project most recently, and I'm not keeping time, so you can give me the Yeah, I'm just enjoying talking to myself in my Zoom room. Okay, so most recently, as an answer to urban design forums call for the city after coronavirus speculation, I collaborated with a colleague Galen Party on a project we're calling nine reciprocities. So this was a hundred year vision for a self sustaining block in New York City. So the name provokes a sensibility that architecture is always in flux, whether you design for it or not, we hope that you do obviously because social contracts and cultural habits are are varying across time. And architecture has to become a platform to enable those exchanges to continue to occur. So we didn't want to call this nine rooms or nine programs, because it's neither physical nor programmatic, but it's really a kind of relationship with one another on the site. So in this case, we looked at these nine ways that architecture can become a place of collectivity. So assembly, daycare, gym, workshop, store, office, greenhouse, bank, and then the skin of the of the site. So COVID has obviously exposed some critical oversights in our existing understanding of social contracts and the value of work and unequal distribution of ownership, health care and opportunity, highlighting the need to jumpstart and strengthen those social ties to combat future epidemics, economic downturns and approaching climate change catastrophes, you know, in the city. Beyond responding to this kind of public health problems posed by structures of pandemic and quarantine, our project nine reciprocities took a look towards the next 100 years and intensify this kind of social equality and environmental resilience. So the framework, and I don't need to go through every detail, but we kind of imagined the sequencing of the nine kind of piggybacking on each other. So you would first imagine an interior renovation that allows you to assemble in order to make decisions as a block. So you're initiating a block trust. Second, you would have a daycare and gym to enable more people to join in that assembly, and to give access to health. And then we thought of the workshop as more of a place where community relationships are forged, as opposed to things are produced, kind of like, if you're getting to know someone or having a coffee date, it's kind of intimidating when you're staring across the table from each other into their eyes. And you're like, let's get to know each other. It's quite intense. But rather, if you were to like, be doing something next to each other, like throwing a clay pot or doing an art class, you're kind of in your periphery starting to just get to know people and it's a more natural space to get to know your neighbors. And then to build on these kind of small pavilion additions to the block, we imagined what's called like a material store. So as interiors are renovated or gutted, that material can stay on the site as an asset, as opposed to being waste. Obviously, there's constraints to that. But a lot of the partitions and wall partitions that we see going up in the city are already kind of innately modular and can be stored. So we are thinking that with that material store in place, now it's a launching ground or kind of staging ground to build a mass timber overbuild, which it becomes this kind of lightweight three story bridge, landing on differently aged existing brick buildings. So we were looking and studying kind of capacity of those brick buildings to host this new overbuild. And then over time, as the overbuild completes itself, it actually the material can like the wood material as it is replaced or recycled can also be brought down into the brick to replace structural walls that are failing and eventually metabolize the entire block. So then rather than focusing on like buildings as a solution, you know, we wanted to explore generating systems that would support initiatives already in progress and kind of enhance them and intensify them and reveal, let's say what what might happen if those were to remain in place as opposed to being pushed out of the city. The architecture builds on the programs here like a community bank is already here, a pharmacy, a grocery. The addition is imagined to be funded and initiated by a kind of self collective government with tenant and common financing. So we're thinking a lot about how the economics would work, how many units would be coming here and how it would be stabilized. So the buildings are at different heights and you can kind of see the magenta indicates all of the new or, you know, growth over time. So by maximizing the blocks at they are and keeping the air rights on the site, the community of workers, retirees, experts and visitors inhabiting this block can expand their space into the overbuild construction and demolition is recycled and kind of reuse within the block and we imagine to the the entrance to all of these apartments would be these tram walls that are a little bit more to kind of heat up the space. It's a kind of like traditional architecture move. But we're not sure why they don't exist everywhere. So we are thinking of ways that like a narrow greenhouse can be your entry way and it can warm up your apartment while also kind of creating oxygen and even growing a tree that could become wood potentially. And at the same time trying to think about how this representation might be questioned, typical representation. So in this case, it's like cutting across all levels and understanding how any kind of new addition on the block, it would not be kind of new on top, old on bottom, but implicate the entire block as an ecosystem and include all the programs big and small that exist. So the the addition is less vertical and more stabilizing. And this is the video that we created that we submitted. So I'm just going to speak over it. What if there was a place for making decisions together, a place for voting, sharing knowledge, welcoming folks from neighboring blocks? What if there was a space for record keeping, a space for rent collection and shareholder health coverage, a space for emergency funds and blockadee accounting for liability insurance? What if there was a place for bake sales, a place for local repairs and apprenticeship? What if there was a place for teaching skills? What if if you taught skills you could offset your rent? What if there was a place for exploring creativity on the weekends and getting to know your neighbors? What if there was a place to put your materials? What if there was space to support free and future fixes? What if you knew who could fix your sink? What if there was a space for minimizing waste and maximizing lifespan? What if there was a place for oxygen production? A place for carbon sinking and vegetable growing? A place that guaranteed that you'll have lower blood pressure? What if there was a greenhouse? What if there was a place for childcare? What if there was a place for closing the gender gap? What if there was a place and space for empowering moms and families and multi-generational families? What if there was a place for equitable learning and learning how to help others? What if there is a place for after school games, a place for exercise or a friendly competition? What if there was space for small co-working within your neighbors or within your apartment or near your neighbor's apartment or even for job training? What if there was space for a hot desk outside your apartment and more time with your family? What if there was space for less of a commute? What if there was a space for promoting a larger worldview on the skin of your building? A space for exterior billboard income and a block stimulus? What if there was space for interior wayfinding and promoting an internal barter system? What if we rolled the credits and we gave everyone credit for producing this block and keeping it alive? Okay, so there's one one last quick project that I'll share and it kind of relates to my work at GSAP. So last but not least, Fringe Timber. So this project is an ongoing research initiative focused on mass timber, you know, building on three material stories, but and the Airbus project, but diving more deeply into species driven design. So the work includes the advance for architecture studio, the MRC studio here at Columbia, but also I kind of regularly collaborate with foresters, developers and architects from around the country actually in an effort to explore what this means and what the limits of our kind of natural resources are. So when it comes to renewable construction, we kind of we have to weigh worth and value again, questioning projection and representation techniques of course, while also widening the exploration space as I showed you with generative design. But in this case, the hope is that it's not just for geometry, but actually exploring a wide search space for possible non-local relationships. So if you could solve more for like forest resilience and biodiversity, which are really complex systems, there's a lot of foresters that already deal in this complexity when it comes to ecosystems. One of the consortiums that I look to and I'm in contact with is Quorum, a number of universities that build data together and build simulations of natural resources for the next hundred years. So perhaps these types of relationships can be enabled by an architecture that's first and foremost defined by a deeper understanding of regions, territories and species needs. The research itself is premised on the passing of the most recent Timber Innovation Act in this country in 2018. It was part of it was kind of slipped into an agricultural bill, but to outline new initiatives for R&D of mass timber, which is what kick started CLT integration in Austria and Germany and all over Europe about 30 years ago. So we've been behind the ball because we haven't invested in R&D here. So this is kind of the first big phase of that, that launched investment for construction projects and supply chain development, which means investing in new factories and new kind of energy efficiency or like adapting existing factories to produce engineered timber as opposed to just lumber, dimensional lumber. So the goals are to lower the carbon footprint of construction, but also to provide jobs, which you've heard from the Biden climate plan for my jobs and rural economies. This includes one of some of the things that I look at are small holders, silver culture, intercropping, rewilding, afforestation and genetically modified trees. These are all emerging as sources of new renewable income. And they're emerging as competing with other agricultural practices. So all of a sudden we're facing this question like, what should we do with our land? What is the most valuable thing to do with it? The forthcoming IBC, the International Building Code of 2021, acknowledges the high performance of mass timber, which is great. It allows buildings up to 18 stories and confirms fire resistance and in some cases rival steel. So together, these policies is kind of political changes. They're inviting this new era of renewable construction, an era that's by no means inevitable. Renewable materials require us pushing reset on like most of our existing systems. So it's kind of like steering a really heavy boat in the opposite direction. Right now as it's designed to add fuel to the fire here, cross-laminated timber relies on the growth rate, strength and predictability of Douglas fir, spruce and pine. Codification of this architectural product through ANSI interlocks the biological makeup of our forests to the needs of the built environment, like we've never before. This incentivizes the proliferation of only three tree species. So in our region in the northeast, most land is privately owned with a history of preservation. More species, we have more biodiversity and more forest fragmentation than the West Coast or then Europe, where CLT is more common, where mass timber is more common. In this context over here and around New York, an increase in timber construction would actually conserve the forest counterintuitively because it incentivizes landowners to avoid having to clear trees for agricultural or urban development. So this increased market would only exist, though, if a variety of species are incorporated into engineered wood. And that won't happen unless there's demand. So you can imagine this like chicken or the egg relationships across the supply chain, everyone's waiting for architects to just specify it. So a lot of excitement, I think, for us, you know, in the world of speculation and thinking about possibility. And so this is where this kind of work is headed. One of the reasons I keep mixing research with professional practice and you probably share this conviction is that our climate continues to transform and the new normal is most likely going to be ever changing. This present and future field kind of turbulence is very turbulent kind of relationship we have with practice. It demands a kind of parallel designed dismantling of long and trench linear systems while also proposing flexible and open source reciprocal relationships. This kind of balance of the same happening at the same time as where, where at least I'm headed and I'm sure a lot of you are thinking similar terms. OK, thanks so much. Stop there. That was awesome. I can see why we were paired together, but the different scales and scopes will be really interesting to to engage with everyone here in a discussion around the application of. Technology data and performance, let me. Jump here. I'm going to talk about how we use computation data and technology and the design and planning of cities within KPF and then how we're thinking about also using those same approaches to actually shape the regulations that allow what is built so that they can be kind of. A smarter and more adaptable. I want to talk by first by bringing up the the nest, the nest, if you're not familiar with it, is a smart home thermostat that learns from your behaviors to automatically adjust the thermostat and it turns any home into a smart home. When you put it in, it doesn't matter if the design of the home itself. And so one of the things that we see with the development of ideas around the smart cities, it's really focused on the smart and less the city. So kind of technology layered on to the existing city, independent of how it's designed. And so one of the things that we've been exploring is how can we use technology and data to design the city itself, rather than just as a framework for the application of technology on top of the existing. City, you know, for example, when you're when you're thinking about sustainability, the most effective solutions are passive, right? Not not active. So in a similar way at the urban scale, we're thinking about that. And our approach kind of really comes down to three three buckets in terms of testing different combinations around the space itself, mapping the networks of within those spaces, so where people are and then measuring the performance of the buildings and the spaces. And in doing this in a large project from planning firms, seeing a more traditional process and how this could both augment and supplant it. Is it in a traditional process? At the beginning, you might have five iterations. It's quickly down to three and then one. And then there's kind of a static document that's delivered at the end. And then the planner and the architect exit the project. And there's just kind of this static document that never gets updated. But with a computational process, you maintain optionality further along. You're constantly narrowing it, but you can respond to different conditions. As climate changes, new parts of the plan develop the economy changes, you can return to a model like this and change the inputs and options and see the response. So we see this as kind of a more flexible system, the traditional one. I'm going to talk a little bit about the how, but I want to focus more on since we're talking about performance and representation. So I'll go through this a little bit quick. But our models that we build are in three parts, inputs, rules and metrics. So the inputs are the things that you want to test, most often things like the program that makes density targets approaches to public space, how the program is distributed and then the rules. How do we take those inputs and create geometry out of them? And then how do we measure the performance of those in a way that we can understand if we're establishing our goals? And while our model is set up like this one, two, three, the conception of these always starts with stating your goals, your desired outcomes and then backing out how you can start to measure, measure that outcome. And then what are the formal kind of implications of that that you want to test? So I'll just kind of click through these. So this is just taking those steps out and thinking about and showing them graphically. We make some mesmerizing parametric grids. In actuality, more often we we hand draw our street grids because there's more intentionality in those that we want to test that come from a deep history of kind of our design practice. Then it's kind of worth the effort of making a grid like this. We'll test programmatic variation through things like this is creating a pixel map reach. Color in the pixel represents a use in the saturation represents density. I mentioned that the inputs, these are showing a range of those from density to street grid. And it it's very project specific. So this is just kind of a general application and sort of the secret sauce, but then also the most area for kind of putting your own bias into these models is the procedural generation. So how do we take all these inputs and direction and turn them into geometry and buildings? And so on the one hand as an architecture firm with a deep practice, we have a lot of experience in building building types, but that's also kind of embedded in our own education in terms of kind of Eurocentric design and modernism. And so if we're using these to explore new modes, how we design a planet city, but ultimately we're creating these rules that that take the inputs and manifest those into geometry. That's something that we kind of actively think about as well. And then finally, we have the metrics for evaluation. And so these are some common ones we use. I'm going to dive into some more specific examples around kind of quantifying subjective issues. We're looking things like outdoor comfort, energy generation, daylight, views, visual interests, mobility. But kind of talking about visual interest, that's one of the things that we spend a lot of time analyzing and trying to to visualize. So what you're seeing here, for example, is just a 2D kind of spatial pulse, how open or closed the spaces as you walk through this. And for a lot of these new qualitative analysis tools, we don't use them to say better or worse, but to add context to our designs. So are we creating a space that's more like Covent Garden and or more like Manhattan? And is that the desired spatial effect, for example? We're also experimenting with using computer vision to try to analyze the bulkiness of a building and so to kind of qualify the sequence of spaces. Well, there's things like a bulk score or a visual variety score at the bottom, because one of the things we do is we design really large buildings and towers who are concerned with the kind of the spatial effect and impact of those. This next sequence is from a master plan where we were we were carefully designing the the the network and the experience of the public spaces. And we're doing two things, looking at kind of the spatial analysis of what you see here is the overall spatial variety, which was a similar one to this, kind of how open or close are these. Are you viewing kind of buildings or nature at any given point? And is it comfortable? And that there wasn't one perfect score, but we were wanting to create a variety of experiences. But then kind of as important, we were trying to understand where people are likely to go and when so we could kind of understand is there kind of a variety in the options? Can you take a route that has kind of a very open spatial experience or a very closed one? Do you have kind of options in in similar routes? And so we're exploring doing this kind of origin destination routing. And then this is kind of showing a typical setup where we're looking at nine a.m. versus six p.m. So the commutes, but starting to think about how we can layer in some of the spatial analysis to see how that changes. So for example, this is when we account for comfort. This is an extremely hot climate where shade is always good. And so you see the kind of the shift that happens. We're not changing any of the routing or the destinations. It's primarily coming from the subway access in the buildings and going and the bus terminal and going to office buildings. Oops. But in the morning commute because you're getting shade over here, this is not oriented correctly in terms of north and south. You're going along this route here, which is an extremely large highway, but is the most comfortable and shortest route to your destination. And one of the things that we found as we were designing this within kind of a larger master plan is that this primary spine here, which is intended as kind of the social connector of the overall master plan was unlikely to get used often because of thermal discomfort. And it didn't connect ways and didn't connect buildings in a convenient way. So we explore different options like what if you shade it already you can see we're taking people off of there and what if you introduce different connections through blocks and kind of ultimately coming through this computational design model, the promise is that we can come up with a set of high performing options. Some that have tradeoffs. We discussed those to make kind of informed decisions in the planning process, but we found kind of a number of challenges within those. So there's many stakeholders and changing priorities. There's different. You have to reconcile different priorities and goals. And even with the same set of stakeholders, those often change as they learn from the analysis and modeling. Oftentimes, you're not looking for the best solution. So for example, this is from an experiment we did at a conference a couple years ago, simulation, architecture, urban design, where we asked we asked both the conference goers and the general public via our Twitter account to explore design space that we made available through a a web tool and propose what they thought were the highest performing options. And what we found, the bar graph shows the counts of how many of these grids were submitted as the best performing is what we found. So the one that got the most vote, this kind of medieval grid was not the highest performing. The best performers were the weave in this radial grid. And what happened was most people would first kind of filter for their desired spatial experience in terms of kind of the grid and approach to parks. And once they have that, they'd vary other things such as kind of density distribution or program until they got the best performing option they could find for their preference, which is something that was kind of interesting in terms of you know, kind of the balance of the qualitative and quantitative building off of that. We spent a while trying to use machine learning to derive insights from the data we create from computational design models. So we think we're doing thousands and tens of thousands of options that each have a number of data features associated with them. The kind of magical machine learning should be able to get us faster insights out of these. And one of the things that we found was that a human was much better at relating at identifying the relationship between performance and form. So let's say if you if you have a stated preference around performance, a human can quickly look at options that perform well for a number of categories and articulate why they perform well, that the towers are staggered this way and the parks are distributed this way. So that must be affecting energy generation and views, for example, and it was incredibly hard to teach a computer to do that. And so one of the things that we've done instead is create a web based visual framework for exploring design spaces. So to make it accessible to anyone to explore and come to their own conclusions, we found really what it wasn't about really narrowing down design decisions, but creating a framework for communication and collaboration essentially to sponsor a discussion where you're using data in a way that helps facilitate that discussion. And so kind of that leap from kind of this is a way of us trying to make something that us as experts within our own office accessible beyond just us to design teams and design teams and the broader public and clients that we engage in. We've also been looking at how we can use that to develop performance based zoning. And so what is we're talking about performance? So it's a it's a different approach to creating rules that regulate what we can build in cities. And it's as simple as a description of stated goals, for example, comfort. Comfortable public spaces and a set of standards that can be used to measure whether the goal is achieved, for example, minimum average daylight hours. So kind of very straightforward, especially using kind of data and performance to help guide development in cities. Has lots of benefits. Explicit goals as I tied to measurable outcomes. It encourages innovation through potentially allowing higher densities if those goals are met, it's dynamically adjustable and flexible. And because of the explicit goals tied to measurable outcomes, there's transparency and accountability of the outcome that doesn't currently exist in zoning. So it's conceptually clear if we care about comfort, let's measure it. It's technically challenging. And kind of these these first two are where I'm going to end with is how we can use data and computational design in kind of establishing specific performance criteria and development of technologies for assessment of compliance and the accessibility of those tools. I'm going to skip some of this. So the perform proposed framework is defining clear goals based on desired and measure outcomes of similar to computational design models, analyzing the existing city, according to those performance criteria. But as part of this process, soliciting public feedback to establish thresholds and targets. And that's also a way of accounting for bias. Anytime we're establishing performance, thresholds and targets, it's based on kind of my own judgment experience, unless it's kind of something coming out of a more scientific measurement in terms of environmental performance, for example, but especially qualitative issues. And even with things like outdoor comfort, while we can quantify that, that has a subjective range testing and calibrating the performance criteria through computational model and public engagement and then create accessible tools for the assessment of compliance. I'm going to skip this. So I want to talk about we were talking about before kind of time based measures. This is a little bit divergent, but I think is good for the conversation in our conception of zoning regulations. And this is related to the network analysis as we really want to know when and where people are going. For example, we don't have to make a space comfortable all the time, but when people are going to use it. So this is using Google Places data as a as a proxy for activity. So these are business count open business counts three p.m. on a weekday. We can start to look at those animations not working. Well, let's skip that. Let's see. Did all of those stop? Well, that doesn't matter for this. We looked at the aggregate open businesses for New York City over time. So this is 12 a.m. to 12 a.m. And theoretically, New York City's infrastructure is sized for this capacity up here. It's working granted, maybe we think things are overstressed. But what if through performance based zoning and kind of encouraging of changing how we use our spaces, we can shift these activity bars just a little bit more. We can theoretically get more capacity out of our infrastructure and house more people without having to build new infrastructure. You know, and so, for example, I just skipped this. This is a daytime nighttime disparity map. So anything in this green has about the same number of active businesses at 9 p.m. as it has at at 12 p.m. during during the day. So everything over pink has unused kind of infrastructural capacity potentially. And I'm just going to end. Let me see. I'll end with this because I know we want to make sure you have time for discussion. And I think one of the most important parts is how do you engage the public? Kind of what do they think and how do you you can measure something, but how do you calibrate what's the minimum acceptable? What's a target for incentives? And we did a project with the Hawaii Public Housing Center and the University of Hawaii Design Lab to help them with public engagement in creating mixed use transit oriented developments. And they did a number of new light rail stops that they were looking to do that type of development and to do development that was denser than was typical in Hawaii. And so they wanted to do two things. First, educate the public on the benefits of high density mixed use transit oriented development, but also gauge what were their preferences, even knowing what they thought the benefits were. So we built a computational design model for them through Scout, where they could residents could submit their kind of the options that they like with some demographic data so they could use that to understand kind of preferences by that. And they went on a public engagement tour. So I think kind of anything using data and computation to create rules in the way that I'm proposing relative to zoning, getting early public engagement to frame kind of the the goals and how we measure if they're not met is really important. But one of the great things is now there's more and more accessible tools for doing this type of engagement. And so I think the last thing is building off of that. Like the technical capacity is here to do this types of thing. There's kind of simple plot plugins that you can use for widely used modeling software once you've actually established the performance targets. You can leverage cloud based simulation. You can use can create kind of public web interfaces for reviewing the compliance of the zoning. So we can get at a framework informed by data and design that ultimately doesn't need the type of in-house expertise and capability of a firm like KPF. How is that? Hopefully not too. We have. Four minutes for questions. I can stay after eight. I know we're one of your speckful of everyone's time. Well, thank you so much. Luke and Lindsay for the presentations. I mean, one, the visuals are just amazing and it's sort of something that maybe it's really expanding like the vocabulary of how we think of the policy I've been playing or even just materiality. I guess maybe I'll just ask. Well, you guys should think of a question. But I was going to keep it really short. I think you kind of started started to address it at the end of your presentation. But, you know, I was wondering, it's like where in terms of making decisions of how you choose to visualize or how you choose to represent these sort of the sort of processes that you're trying to to communicate, you know, like like where where does the like sometimes where does the the metrics as set by the clients versus the, you know, the the users sort of start to like maybe conflict with each other or does it ever adjust and you as your role of a designer, you know, sort of how do you like navigate between what you're producing for and who you're also producing for? Yeah, that's a good question. And it's actually why we do a computational design approach instead of a generative, which is essentially saying we test everything because we found because of the changing nature of the stakeholders, we are constantly rewriting our generative models. And so like, OK, like, we're going to have to leave some options on the table, but we're going to kind of force ourselves to be critical about that and then create a subset and then more a framework for people to explore and come to their own conclusions. And so that's kind of hopefully the ideal is that we we've created a design space that hits on enough enough of the kind of range of combinations of inputs that people would expect that they can use it to answer and explore their own own questions. So trying to create more of a bottom up process through really a visual interface for exploring data. And so I guess that's the a roundabout way of saying for all the like like novel visualizations I showed in terms of like like networks and time and spatial experience, the kind of dynamic and intuitive visual interface through the web has been the most effective way at kind of communication. Yeah, I had to say that I think that's it's a really good question. It's like we're having to jam a lot of things into our drawings and consider a lot of people and these layers of, you know, which public we're really directing our message towards or who who we really want to elicit feedback from or who do we want to invite to be critical of our work? Is it other architects or is it public? I really like Luke, your example of, you know, creating interfaces to engage with folks that are experts in other sorts of things, you know, using. Allowing people to interact with this kind of complexity. That's a that's a great gateway. And when I'm creating drawings, one thing I like to think about, I don't know how well I have done it in the past, but like your first impression of the drawing is accessible to everyone. And then that's like a layer of design of your strongest intent. And then as you continue to look deeper and deeper, there's more for people to explore if they stay with the drawing. But that first impression is really key. Yeah, it's kind of like a handshake. That's such a good point. And that that makes me think of the framework we use for that, which we crib from the Smithsonian. When we were working with them, we learned how they approach the design of exhibits and they designed for skimmers, swimmers and divers. Those three level of experience. Like if someone's just walking by, they're not interacting with it, what do they get? And that's maybe the hardest thing. It's us, the handshake you're describing. Like oftentimes you're already designing for the diver because you're doing something that's really complex. And if someone's going to spend the time, but how do you do for these other two, which is much more challenging? And I think it was easier for us in a web interface to set that up because we could have different modes than a single drawing, which is maybe more challenging to achieve because you could switch between modes and we can hide complexity in a way that we could address those three modes of interaction. Yeah, when we did the Airbus project, we went to Hamburg and did there was three production lines that were crisscrossing in the factory. And those three groups of people, like rarely, they would rarely talk. They would typically not work in the same space. So it was the first time that they were trying to figure out their relationship while we were kind of in the room attempting to help and setting the table. So in a way, this kind of setting the table, it's a phrase that's commonly used when you're doing community engagement with community engagement specialists. They're kind of setting the table, having, if you imagine, not like like a board game, but it's not a board game. It's like pieces and parts and tools and all the things are available and ready and prepared for people to be able to communicate their kind of ambition and people who are not visual communicators, who are usually either writing something or typing something or maybe not even working with, you know, text or visuals, just, you know, doing other types of jobs like labor or something. And so to have them be able to express themselves is quite interesting. It's most often like them drawing like a single line on, you know, you kind of ask, you know, what do you think about this layout? And they say, you know, here or there. And the first couple of hours are very like timid and tentative. And then as soon as they start drawing, it's like they're empowered. And now they're trying to draw on all of the plans and have their input on all of these different drawings. And I think that in a way what I learned from that experience was and I think there's a few folks working on this, but how can you get that the the connection between your hand and your brain is is like unparalleled when it comes to a computational design? You're thinking so quickly and your ability to evolve is so much faster. But how can that become part of the complexity that in a platform that you're building? I think that would that would become an interesting future, I think. That's interesting for that. So for that process, did you use like technology or data to drive the engagement? Or did you take what came out of the engagement and then use that to drive your model? And maybe if you didn't use data and technology to drive it, any thoughts on like ideally, like if you had something that did this? Like that would have been really great. Like if I could have linked this line to something generative or. Yeah, it's a good question. What what we do when we work on generative projects, which is not all of the work, but in this case, it was probably the most metrics we've ever integrated. There's a way so if you have, say you have three dimensions of metrics, you'll have like an X, Y and Z axes. And then you can plot the score, you know, for each one of those, according to their X and Y and Z values in three dimensional space. But when you have like 12 dimensions, visualizing those scores becomes its own project. So what we would do is switch between visualizations of the already pre-run GD model in order to show high performing in like three categories or something like that. And then emphasize three other categories. And we'd have that up on the screen. So the visualization was able, we could switch it from different states and it could display like, you know, A, B and C axes or X, Y and Z axes and the kind of winning iteration of those isolated iteration or, you know, metrics. And then we would hand draw like a response. So it's like very manual and automated at the same time. We're kind of iterating kind of in the room. That's interesting. So you set, you use the design space to create scenarios within it based on different like goals or stated preferences or if you cared about this, this is what it, yeah, that's really interesting. That's similar. The project that we worked on with Sidewalk Labs when things that manifested is, was an actual physical device that you could toggle inputs of a design space and see the performance of those options. And at the opening, there was a woman who was there for quite a while and someone from Sidewalk Labs went over and kind of played down and asked her, oh, can you explain this to me? And she's like, well, I can design the city I want here by doing this and I see how it performs. And I started by saying, I want it, I want my own backyard. So I want the least amount of green space or say the most amount of green space, the least amount of people. But then she saw it performed really poorly for outdoor comfort and energy generation because of the colder climate in Toronto. I said, well, I really care about this thing. And so she toggled the knobs until she had better performance across the metrics. And at the end, she said, I realize I care more about those than having my own backyard. And like, if that could be consistently replicated, you might change for the use of this type of data and design is to empower people to both learn and come to their own conclusions, like without having experts interpret it for them. Yeah, it's a great example. Like how when you are able to access complexity, your assumptions are, you know, turned on their head, not like you're, you know, don't have, like we like to simplify things so that it feels like you're more confident in your kind of belief or like your assumption, let's say. So you probably started with that complexity, but you kind of boiled it down to like, I just want a bigger yard. But then if you go back to what your original complex understanding of the city through this process is, then you're kind of more enabled to make an intelligent or like frame your opinion more eloquently. Like there's no rush. People aren't rushed anymore into saying one thing. But it's kind of, in a way, so I mean, one of the troubles of that, and I'm curious to hear, you know, what you think about this is with complexity, it's difficult to tell a story. And people really like a really solid, clear thesis when it comes to architecture and design. So when you say like, when I think back about on your presentation, the thing that stands out most for the master plan example that you showed was the shade itself, the implications of moving shade had on the way that people moved around the city. Way that people moved around the city, but I'm sure that you had like 12 other things you were measuring, but the word shade just like sticks in my head as one of the most intense levers in that project scenario. You know, you move the shade and a lot of other things shift. So in a way, there's this very like human aspect like we found too in our, in the Airbus case, you're having a lot of metrics and you're trying to set the table and understand deeply the trade-offs when it comes to like money and, you know, CapEx and OpEx, capital expense and operational expense. And even with all of that data, even with all of those tools, decision-making tools, still the client makes an emotional decision based off of what their impression is of potential. So this is something that I'm very interested to know more about, like how our brains really parse storytelling or thesis in a story. What's the most memorable aspect of something? Because that seems like it's almost as impactful as this data. Yeah, yeah, that's a really interesting point. And like, I think there's kind of two things there. One, on the visualization, some of our analysis tools that get the most traction with our clients, like one of them in particular I'm thinking of is the analysis itself is really simple and not very precise, but the visualization is really straightforward, so they get it. It's like doing like view contours as you go up in height. It's just a point. It doesn't take into account form of the building, but they get it. They understand it's just laid on top of Google Earth, like you're masking out what is blocked by buildings. But of everything we do, that's probably resonates the most and tries the most decision making because of that clarity of preference. It's something you said that we're good at stating one or two ideas or preferences, but then how do we navigate that back up to the complexity of the city? And that's what I'm hoping machine learning can come in, because we've experimented with a little bit we're not data scientists, but the ways in which we've tried to use it, we haven't found that we are applying it to problems that actually benefit from. But if machine learning could be used to negotiate between those simple questions and the complexity of the city in a way that helps maybe reconcile that perceived dissonance of simplifying something relative to the complex project, so maybe it's like AI as like collaborator and helping you take care of those complex relationships. I don't know. I'm hoping to find like computer scientists that are down to tackle something like that. Yeah, they're OK. Are we doing it good, Cece? You guys are doing it very well. Do you guys have, I mean, I don't, do you guys have questions specific that you want? You guys want to ask? I actually have a question. And sorry, I have duplicates because my internet connection is really crappy, Cece is on my phone. I have a question regarding are either of you ever afraid of maybe overextending the accessibility of designing high performance buildings to your clients? Because we're designing these tools that essentially will in a couple of years be able to do our job, our. I know you've both mentioned that there is a need for this human touch in the end and this emotional reaction. But are you ever wondering if like, I don't know, let's say in 50 years, a client can just purchase a license to a software that will let them know what kind of a building or what kind of a shape of a form they need on a site. And like, basically, our jobs are defunct, like we're no longer essential in a way. And we're just people designing the tools that do the design instead of being the humans who create design. But I think it's really cool. I love the technology. I'm just like trying to look at it from this other perspective. No, it's a common question. I think it's a valid question. It's been a question since any kind of automation or any machine was ever invented. The second to sewing machine was inventive. It was like, oh my gosh, what are we going to do? What about all the people who know how to sew? So automation, I guess it's a really, I would encourage you to read someone who's more eloquently gathering their thoughts on that answer because there are some really key essays out there. I wish I had them on the, maybe we can follow up, but I think the general idea is that automation in any field will bring advancements and only encourage people to learn new things. So there's, if you look back at automation of different industries, like farming, farming I think went through a huge automation in a short period of time. And there was a lot of fear in the industry that farmers would be out of business. But in fact, it made it a more profitable field because their skill set had to shift. So yes, they're not like hand picking potatoes, but now they're driving a machine. They're still someone that's operating the system. So in general, automation typically increases the amount of jobs historically. Yeah, and I think that shift you talk about is gonna be critical for the architecture profession where right now we deliver a service which is generating drawings so a building can be built and we bill hourly for each hour we spend drawing those and we need to shift that into kind of the knowledge production into the tools that we produce and that's the service. So I think you're right that we're gonna start authoring more and more tools, but I mentioned, for example, our secret sauce is the procedural generation portion because we're designers. And so we're designing the rules that create a framework for generating a range of options, but it's very specific to the project, the client, the context, the climate, I don't know if I said the same thing twice, but it's so specific that it's allowing us to kind of manifest our expertise kind of faster in a more productive way. So I think there is gonna be the shift, but we need to be proactive about changing how we offer and bill our services to take proper advantage of it so that we can have the same shift you're describing with the farming industry. That was gonna be my, that was why I asked the question because I was wondering, well, overdeveloping the software, then suddenly our rates, well, we're not careful because it's not, because a lot of people think, and already think, well, you're just doing something on a computer, can't you just like click a button and there you go? Why do I have to pay you this much money to just, I don't know, make a model, make this drawing, make this, isn't it just a sketch? So I'm just wondering like, we all have to kind of lead, how to educate people on how difficult this technology is. It's not just a button, it's not just something anybody can click and go, I can do this, I don't need to pay you this much money to give a great design. And even to get to the level automation we're talking about, it's kind of, while you can reuse pieces, there's still the calibration that's project specific. So it's not like we're starting from scratch every time, but it's not like kind of a one size fits all model. Or if it is, it's so general, it may help answer some initial questions. Granted that's gonna change as kind of, we continue to develop these tools and apply more kind of sophisticated models within it, but. Yeah, the field also changes so slowly like that. I would be surprised if a client is really asking that. And if that's the case, then yeah, it's our job to help clients learn how to be better clients. That would be one way that I would field, whether I would wanna work with someone is if they understood and valued what I do. In that case, that's less so if you're assuming that it's a button. Like Grasshopper and Revit have been around for like ever, 10, 20, I mean, Revit's been around for 20 years now. And it's finally becoming now the kind of central, you know, software that's cities. Like everyone, all of these actors are kind of on board with. And yeah, in like the, in 2012, 2013, there was this, everyone was worried like you are about Revit. Oh my gosh, how the heck am I gonna learn Revit? This is an emergency. And there were some really interesting startups, like if anyone, maybe Luke, of course you Luke and Cici remember like David Fanno and Tase, you know, starting this consultancy, you know, to help architects re-up their kind of Revit experience in order to remain competitive. That's like a common, it's a common thing that architects have always had to do to stay competitive, to understand the market, to understand what clients want and what, you know, cities demand. So it's not quite as urgent as that. And I'm sure that there's a lot that could happen, let's say, and to don't be scared. I don't know what else to say, but it's very, it's a complex, like it's a super slow moving field and there's a lot of these ideas present in conversations like this, sort of like, I mean, 20 years out. I would also interject to say that I've never learned Revit. And it doesn't matter. Yeah. And I think the near-term automations are for boring repetitive tasks we don't wanna do anyway, laying out parking lots or initial designing of office cores because so much time has actually spent doing those that if we can do that, it frees us up to do stuff that we're actually good at. And so actually recently my team, we're pivoting a bit some of our goals, while we're still continuing some of this kind of more intense kind of computational design, we're shifting to trying to automate some of the most common boring repetitive tasks in the office now. Like, all right, can we apply this type of thinking to that type of problem? Because I think that's where we'll get some really good benefit within the office. So I think in the next five years we'll see that type of automation, but not the type that's good. It'll get us home two hours earlier rather than getting us out of a job. It's a good question though. Well, I mean, there's so much I could say to that even, but it is 20, I don't wanna like, take up more of everybody's time. I guess, sorry, the only one though, as you think with automation and sort of like the development of technology, of course, it's not sort of symmetrically and evenly applied as we sort of have all these different contexts of the sad reality is, even if we develop the technology to produce a parking deck with half the amount of time, we're still living in a society that produces cheap labor via internships and lowly compensated sort of social structures that it's gonna cut in on that on the sort of large scale. But however, I would like to, I know that they're pressing though, but I would like to thank everybody and especially Luke and Lindsay. I mean, just honest to this drawings and the processes were incredible and I would encourage everyone to dig around, maybe even bother them if you have any additional questions and I hope everyone has a good evening. Thank you so much. Thanks so much everyone. Yeah, this was great. Thanks, Cici. Bye, take care. Bye.