 Hi, everyone. I am Laura Kurgan and I wear many hats at the, at GSAP. I'm a professor of architecture. I'm director of the Center for Spatial Research, which I'm going to be talking about today, current work, some projects in process, and also some finished work. And I'm also the director of the Visual Study Sequence, which somewhat feeds in to the work we do in the, in the center as well. But before I start, I'd actually, I'd love to get a sense of who you are. So maybe just if you can put into the chat, whether you're an incoming student, your name, or whether you're a current student, whether you're simply a person of the public, I would love to just get a sense of who is here. So how about if I give you just two minutes, because it'll also help me, I'm not reading a presentation today, it'll really help me frame a little bit how I approach showing the work. Right, so this is really fantastic. And I'm looking at the list of students and it really is in the spirit of how we think of ourselves in the center as a, as something which bridges between architecture, urban planning, urban design, science program in architecture. And further than that, we are actually a hub of spatial research between the humanities and also make bridges to data science and the grant that helped to establish us also helped to ensure that we could make those kinds of connections. So I will switch to the slides so that I can start with the actual presentation. Okay, so this probably means I'm going to become just a little speaking head and start the, and start the presentation. And thank you all for coming and I'm really happy to see some incoming students continuing students and for students that appears as well so I got a few messages from them. So, oops. Okay, before I even start, I want to want to say that all the work that I show here is number one, seriously collaborative and collaborative across disciplines. We work with the history department we work with data science English, the Center for the study of ethnicity and race, the Center for the study of social difference. The Institute of comparative literature and society we've done team courses with all of those people and really cross tried to cross the university. And more importantly within the lab. We have an amazing team right now and Darryl Burley who has just graduated from urban planning this past year is the assistant director of the Center. Maria Zhang is an associate research scholar and she this is her second year during that third year. Dan Miller is also a research associate and particularly working on the historical New York City project I'm going to show you a little bit of that as we move forward. We have some current students who are working with us Adalyn Chum who's in the March program, Audrey Danden also in the March program Nadine Fatale in the CCCC program, Tola Onayangi has just graduated she worked with us for three years and was the GIS TA and worked as a research assistant on many of our projects. And this summer we have a large team as well Adalyn Chum again. Nelson Dehesus he's a March student Nadine who's a CCCP student Spencer who's an MR student and same with Adam. So we do a large range of projects as I talked about and these are the kinds of themes that we always address. So, although we are a data center and a data analytics center, we approach our work from a humanities point of view, which means that we ask really difficult questions about the data that we use we don't take anything as given. We don't think of anything without the history of where something originates. And we have many audiences for our work from policy arena to museum exhibitions to public facing websites to things that we are just actually doing for an archive so that it becomes a resource for future academics and activists. So all kinds of things really thinking of mapping as the medium through which we do our work and mapping as the way that we question both the history of cities and the future of cities. Our most famous project which I'm not going to talk about today but if anybody in this group wants me to give a longer lecture about how this project unfolded and where it's going now because we're going to especially in the context of black lives matter. It has become an important sort of touching touch touchstone for for a lot of different disciplines, even especially at Columbia. And this was a project which addressed mass incarceration and instead of making maps of crime and maps of crime are ones which really address the police they are there to encourage police to come to a certain part of the city and soul for something we instead mapped incarceration which showed where people who are currently housed in prison. What the home address was and was completely different approach which in which instead says how much does it cost to community and to the city to incarcerate people from mostly poor communities of color, rather than invest in those communities and think about alternatives to incarceration think about how we can prevent the prison to the school to prison pipeline and other ways of what we're calling nowadays the politics of care and I'll show you a little bit more about that project as we as we proceed so there's a lot about this project on the website you can download PDFs it's a chapter of my book and it's really been a constant project in the center. So, but what I want to do today is I'm going to show two projects which are about the urban origins of specific algorithms which have a huge impact on the way on networks are designed and the architecture of our networks. So, you know, just a little paragraph that describes this whether it is online or in our daily physical routines. We interact with others close friends acquaintances familiar and unfamiliar strangers in ways that over time come to show patterns. Network theory represents these relationships as graphs using the visual language of ties and lines connecting loads and circles to describe the topography and dynamics of families friendships groups workplaces neighborhoods and communities by representing complex systems as graphs network science also allows us to link macro and micro phenomena to understand how ideas and things are transmitted and disseminated how they travel and spread. But what exactly are these ties and how do they matter. How does the framework of network analysis synthesize represent and evaluate them. So to do this work. We, we took on the papers of two prominent social sociologists three actually prominent sociologists. The first paper is called friendship and as a social process. And it was written by Paul was Lazarus felt and Robert Merton and Robert Merton was a sociologist long time sociologists at Columbia, and we had access to a huge archive at the in in Butler library about this work. And the second one is a paper by Mark Grandveter cool and this the first paper was written in 1954 the second one in 1973 by Mark Grandveter called the the strength of weak ties and both of them based their research in you know utopian so called utopian housing projects of the 50s where it was a federal program to desegregate housing. And then the second paper was grounded in in the 70s where in urban renewal programs which demolished these very same housing projects so that's kind of where we started. And then also just to remind you that my own history. You know I began using the internet like most other people in a hugely optimistic way where they were things like the independence of declaration of independence of cyberspace right in the early 90s. Governments of the industrial world you very giants of flesh and steel I come from cyberspace the new home of my mind. On behalf of the future I asked you, you have the past to leave us alone. You're not welcome among among us you have no sovereignty where we gather. You will create a civilization of the mind in cyberspace may be more humane and fair than the world your governments have made before right so it was a direct rejection of the government in favor of private networks, and it was supposed to be a utopian one everybody was included, except, you know. There was even this idea that there was no race, no gender, no disabilities right here they're only minds we can only think of utopia so. I think we've learned by now that this was a mistake, you know there's, in fact, over this long history there was very little Africa on the Internet. And what we have come to understand is the deep polarization that is happening in our social networks, and this research that we're doing on the urban history of algorithms tries to take on this this history. You know so that we, we can open up the black box of the algorithms that are really actually directing our social lives and because our social lives online so deeply tied to physical space nowadays. We really have to understand the origin of some of these ideas. So again, this project was done with a large team, I'm as a principal investigated Darryl Broly Brian House was a research associate two years ago Gia Zhang and Wendy Chun, who was teaching at Brown at the time and now she runs a research center at Simon Frazier University in in. In Vancouver, and we're still working with her on this on this project. So we start by saying that these two sociologists actually coined the word homophily and you know if I was in a classroom right now I would ask you how many people have even heard of the word homophily. If you have taken computer science you likely have heard the word. If not, you know if you've never studied network science that's very likely you you don't understand this very important concept, which really has a huge influence over our networked lives. So to coin this word homophily Lazarus felt and Merton asked themselves the question. Do birds of a feather flock together right does similarity breed connection and importantly they asked this as a question and to answer that question they decided to interview residents of this housing project, which is in Pittsburgh. Pennsylvania. And although this was a desegregated housing project black and white people lived in different buildings so in in the white squares the white residents live in the hatch squares the black residents live. And this is an aerial photograph. And these are some photographs by famous photographer Charles teeny Harris. And you can see even the photographs have mostly black people, mostly white people in the frames depending on which housing they They were photographing very rarely like this image on the left were the residents coming cold. Okay, so to do their research they asked they asked a lot of questions 90 questions in fact, but to come up with their definition of what what homophily is they asked that they, they limited the survey results the tabulation of the two questions. Do you think white and colored people should live together in housing projects. Yes or no, or 26 on the whole do you think that white and colored That colored and white in the village get along pretty well or not so well right get along pretty well don't get along so well. So all the respondents in the survey they were 518 people that was 100% of the population. And as you can see, the results were, you know tabulated as liberal ambivalent they didn't know whether what they thought or illiberal they didn't like living with black people or black people didn't like living with white people, right. So that's how they tabulated their results. And then they tried to account for the opposite right we must hear confine. So, this is a summary to white residents, since they are too few illiberal or ambivalent Negroes this is their word. So black people with friends in hilltown to allow comparative analysis. Further details statistics will be found in the patterns of social life selected summaries of these statistics are sufficient for the present purposes right so We, we found in the in the in the archive, we were going back to try and figure out how they made these decisions right so they also had to go through this process of saying who their three closest friends were And where do each of them live and you know friendships were not defined as family they were defined as you know not not part of not part of your family so this again further bias this survey. Right, but then we found this astonishing little scribbled upon sketch in fact Wendy Chun found it when she once came to visit us in the library and it really started the collaboration. And what they were showing were hilltown whites versus hilltown blacks, and they were showing right that black people had no problem living with white people. But that white people showed what they called an over selection right they were 31% of white people in the population of housing projects and 45% of them were considered liberal which meant they wanted to live with black people. And they, you know, they kept going with this with this observation of over selection and over selection is something that you need to make a statistical point right and there was no over selection in the black population. In fact, there was an under selection right so moving forward from here they they ignored the surveys of the black residents in order to define the word homophily. And then, not only that they wanted to try and define the opposite how homophily, right, which is heterophily right so. Right so I hope you can understand how where this is where this is moving right so to understand to define homophily, which started as a question do birds of a feather flock together. They only counted the survey results of white people in that population. So what effect did that have. So I'm going to show over here how our team thought that these effects played out. When they were applied to social networks like Facebook, for example, right so when Merton West and Jehuda developed the survey questionnaire for the residents of as Addison Terrace to ask respondents to name the three closest friends excluding family members and colleagues casual acquaintances and neighbors. So it took view of society made their subsequent analysis possible. It's fell short of representing the many ways that people share information and develop values within the community. Right. So then we made a big jump, right. And I was showing you before that graph theory, you know networks are defined with points as nodes and lines which connect them. If you start with a network that has, and this is about the design of the network now, if you start with a network that has a 67% tolerance level, right, which means you are liberal and you're willing to make connections with people who are not like you. And if you start adding nodes to that network, right, your network will stay diverse, it'll stay mixed, it'll stay, you know, with people of lots of opinions. But, but if you design your network with a 33% tolerance, right, you can see that it'll start polarizing a little bit with 10% tolerance, it polarizes even more. So on Facebook, they have this algorithm called triadic closure, which allows you to make friends, you know, with with other people. If there is that 67% tolerance on Facebook to you as well your network would stay more diverse. Okay, now I just want to say we're guessing over here we don't have Facebook algorithms you cannot unpack that black box. But this is network theory and so we've taken it in a theoretical level. So because on Facebook, the tolerance is likely designed to be 10% because in fact the financial model of Facebook is that advertising is directed particularly to you based on how you click on things and say what you like and you don't like. So to make that model effective the tolerance in Facebook is much is much less right so if you start with a tolerance of 10% your network will become further and further and further polarized. So that was the basic of this research is trying to to demonstrate that homophily was in fact when when the researchers were defining it posed as a question became naturalized and an axiom in the world of network science. And so we tried to show this by an unpublished version of the paper versus the published version of the paper where they were much more open ended in their questions of what homophily was you know they say observed as a dominant pattern but you know in the in the longer paper it's a descriptive concept or process rather than an observation it's misleading without indicating the nature of the social context right so it's a much more complex topic, which got simplified by network science, and then we undertook an analysis of of how homophily was was cited over time and the paper was written in 1954 and you can see it's only in the year sort of 2000 2005 even 2010 right but it really starts being cited and it's mostly being cited by computer science, social science, you know all these all these different fields who are grappling with online networks. Okay, and then we've done some other this is just a fun thing showing the context of the use of the word in the scent in the abstract sentence of the society of the article that's quoting it. So what this did was it ignored the ambiguity of the initial question of the of the term and this is Lazarus. This is Lazarus felt it's another archival image because he ran a media center and a radio network, where in the background of they can see this like it's like button so it was the first kind of radio survey where they would ask participants if you like this program press the button if you don't like it press the button and they had these kind of user groups so in fact it was in some ways the history of that like button which is causing such incredible problems on on social on social media. And then we took this further to looking at the work of an economist named Shelling. Who used the who used homophily to create an algorithm of sorts but it was a game that he played with students and presuming homophily right and this was about neighborhoods and it was about white flight from cities. And he said, because of homophily, you want to live near neighbors who are like yourself right so they had this whole game it was actually they played it with pennies and dimes. But the idea was, you know, if this purple point over here is not next to three purple, you know, three crosses, it's going to be unhappy and it's going to move itself and it's going to keep moving and keep moving and keep moving until it's surrounded by four neighbors that are like it. And this was a model to which was predictive of the way residents organize themselves in suburban communities. So I'll show you the Chicago architecture Biennale version of this project a little later when I talk about the exhibits, but what we did was we ended that article asking the question, you know, would, if they had taken the answers of the black residents into account, would they have been more heterophily, and would that concept have been defined differently, right. And then as we moved further, we realized that actually heterophily is not the opposite of homophily. And we started researching this concept of weak ties, which was a paper written by Mark Granaveter in the 70s, and to do his research right so it starts from a tie between two people. And then talking about, you know, the time and the intimacy of that relationship and the emotional intensity and the way people exchange thing between one another results in the strength of a tie. But then when you have multiple friends joining together, you know, you're trying to look at whether there's a strong overlap between two groups by the amount of friends that people have in common between those two groups, right. And then you realize that if there is a strong density of friendships like this one over here where where people are, you know, all tied together in a strong density versus the 60% percent density images where there's two two friends are connected together but the third friends are not connected together. Then, you know, that shows different degrees of density and how intense the overlaps of these network really have an effect on on community. So, you know, that's why we call it sort of micro connections between two people and how it results in macro phenomena how communities end up interacting with each other and particularly in cities. Right, so we've done all these different studies of how ideas travel across networks. This is very much work in progress and Granaveter defines this term of bridging tie where you have two groups of strong networks and if two of those if two or more of those people connect with each other you have that bridge between two different communities which joins them which joins them together. So the way that Granaveter did this work is he connect he quoted a study and for those of you who might have done architecture urbanism in your undergraduates, a book by Herbert Gans called the urban villagers and Herbert Gans quote wind of urban renewal of the West End of Boston and before it was to not demolished he went as an ethnographer and studied the lives of these people. And he took photographs like this and the people he studied were mostly Italian immigrants who had lived in the United States maybe two or three generations. You know very tight knit communities on small blocks, but this was not a very affluent community. And what we started asking was, you know, how, so what Granaveter started asking was how that study by Gans resulted or how those networks between the people in that neighborhood which had been defined by urban the urban renewal project as an obsolete neighborhood right of no use anymore. The, you know, the space the air flow between the blocks was bad and you know all kinds of crazy reasons which would not hold master today and proposed a new plan for this area and it was very close to downtown and a new commercial district was being formed. And this area was demolished right here is showing that advantage of the central location of the West End and Boston, which made it a prime location for urban renewal. Right and then they did all these studies about the conditions of the dwellings that was highly biased towards their demolition, you know, talking about things like lack of air or, you know, the age of the building. Nothing to do with the strong communities that were living in these neighborhoods. So the important point over here was that Gans was studying these smaller units right these peer groups. And Granaveter using his research decided that they were not enough strong ties between the different peer groups to be able to succeed against the demolition of this really large neighborhood. And what we what we're showing is that the urban renewal plan itself looked at all these multiple peer groups and saw them as one unified neighborhood. So Gans would never have agreed that, you know, there was that this was a neighborhood at all. It was just a group of smaller community blocks and neighborhoods which associated together but didn't think of themselves as a neighborhood and was only the aerial view of the urban renewal plan, which defined it as a neighborhood until then it didn't even have a name. And this resulted in the demolition of this neighborhood. So, in a, in a very vibrant dialogue back and forth between Granaveter and Gans they were arguing about why this neighborhood ended up being demolished. And that goes back again to the to the assembly of networks and to the formalization of the network and how they operate between each other. And what we've decided as a team is that actually although this neighborhood was demolished. And that Granaveter was right about the weakness of the strength of the weak ties, which allowed this, which disallowed this community from mobilizing politically and becoming activists to stop the demo to stop the bulldozers. Were there leaders who could have activated the networks to join together, perhaps there could have been a different outcome. And many articles which which quote this Granaveter article which cited talk about activation activation networks between the weak ties. And so we've come to believe and we're putting a paper together about how to activate weak ties in social networks so that you can foster networks that are not homophilus right and you know those are the networks that wouldn't necessarily you know be the ones that are linked to advertising as you know for making money for networks, but might require us to design and form new social networks new ways of mediating between online and offline platforms. So that we can actually encourage difference and encourage multiplicity of types of communities, etc. Okay, so that's where we are with the urban history of algorithms. I'm going to move quickly to mapping the politics of care, which is a project that we're going to launch very quickly. We're going to work in the next five days so consider yourself seeing a preview of this. And it's something that we're working on faculty and students and staff of the Department of epidemiology and microbial diseases at Yale School of Public Health and the center for spatial research. The reason that we're doing this is that we read an article by Greg Gonzales and Amy Keptinski who have initiated this project, talking about what they're calling the new politics of care. So one which is organized around a commitment to universal provision for human needs, countervailing powerful workers, people of color, and the vulnerable and a rejection of carceral approaches to social problems. The question now is how to connect that vision to programmatic responses that address the needs of the moment and beyond. We need to aim at non reformist reforms, reforms that embody a vision of a different world that we want. And, and that work from a theory of power building that recognizes that real change requires changing who has a say in our political process right so it's very connected to the network analysis. The goal is to create, which is one place to start to build a new movement that heals us and our body politic and will allow us all of us to survive a pandemic and then to thrive. So what we did was, we started with what is called a social vulnerability index, which, which we've underlaid on our map, as a way of biasing and actively biasing how the cova data is read and what to do about it right so what the social vulnerability index does is says that every community must prepare for and respond to hazardous events, whether a natural disaster like a tornado or disease outbreak or an anthropogenic events such as a harmful chemical spill. The degree to which community exhibits certain social conditions, including high poverty low percentage of vehicle access overcrowded households may affect that community's ability to prevent human suffering and a financial loss in the event of a disaster. These factors describe the community's social vulnerability right so it's it's defined by the center for disease control and prevention, and it's called the social vulnerability index right. So using this as a background. The project is to make a map which helps public health workers help public health officials decide how to measure the need for community health workers and how to assign them right so there has been this decision that oh goodness this is in the wrong place. Yeah. There has been a decision a decision in many states that case workers will be assigned to do contact tracing right to figure out who had covered and how it has been spread. The group that I'm working with is very opposed to cell phone tracking and does it in the old style public health model of making phone calls making house visits, etc. So you can see here on Apple show the number of case of covert cases right will also have a tab. Which shows new cases as the percent of the population right so this if you've done GIS it shows the hotspots it shows and this map will always be within two weeks up to date. The third one shows the the FBI. And then the fourth one shows FBI in relation to hotspot analysis. Right so then the second part of the legend is how do we want to measure the need for community health workers and how many community health workers can your county state whatever it is pay for right and the agreed upon number is 30 community health workers 400,000 residents. So over here, you can see this is the number of covert cases and what would happen if you had 50 case workers. You know if you could afford 50 case workers per 100,000 people, and it's showing you in those two weeks where the need is okay when we launch the project will be up to date. So this is the same thing new cases as percent of the population and here 30 case workers are assigned and it's telling you what we think are the counties that are most in need of case workers and we've prioritized that by social vulnerability. Right, so it's not to say that if we're in New York and there's people on the Upper East Side who have covered and we should attend to them. But what we're trying to show is that Elmhurst Queens is more in need of case workers at a particular at a particular moment in time based on their vulnerability to the illness. So it has a political point of view which is every single map that is drawn has an argument has a community point of view and we strongly believe that as a mode of research that we do. And then this shows when you zoom in, you can see the weightedness that gives you information that's for a more educated user in, you know, how you should assign various cases. And that moves forward. Okay, so that project will be launched next week. This is another project which is very, very much work in process, but I've never shown it before and I'm really excited because we've actually made quite a lot of headway with it. It's mapping historical New York, the PIs on the project on myself. Me and I, who is a history professor, historian of immigration, Rebecca Cobrin, Gergo Beich, who's at Barnard, who both of them are also historians, urban historians. Lea Meisterlin in urban planning is also an advisor to the project and she's done a lot of work with Gergo Beich with a previous version of some data like this. So what we have is, you know, we've taken the census from some historic years, 1850, 1880 and 1910. At the moment, we're only working on Manhattan and Brooklyn, but hopefully we will have our funding renewed to include the Bronx, Queens and Staten Island. And to do this, we have taken three different atlases which have previously been digitized by the New York Public Library and the Brooklyn Historical Society, and we have patchworked them together as the underlays for our maps. So when you zoom in, you can see this is the, this is the digitized historical work that is underlaying this map. From that, we are creating this digital street grid which has not been drawn before in this particular way. And so now you can see that that's the streets in Manhattan and Brooklyn in 1850, in 1880 and in 1910 where by 1910 you can see there's a complete street grid. The other thing we're doing is we're taking a handwritten census, which was typed up by the Mormon Church actually and made accessible to public researchers, and then have taken that historical census and tabulated it so that it can be like any any GIS file where if you have a name, an address, you can put a dot on a map, right? And so here is the, you know, like 400 to 500,000 people who lived in New York in 1880 and the same amount of people in Brooklyn. Over here you can see a dot where a person has been counted for each household and over here is a really nice rendition of their occupation. So Clark, builder, dentist, plumber, money broker, coffee and tea agent, congressional, congregational minister, just all kinds of painting manufacturers. So it's a really incredibly detailed portrait. And in this map over here, the census at this time actually asked your country of origin. And so blue is people from England, red is people from Ireland, green is people from Germany. So really what we're showing here in some ways is the history of of whiteness of white New York and how immigrants moved here on the one hand, we're part of the colonization that had occurred a century before the Manhattan grid was laid out in in 1811. But never before has this kind of analysis happened at this incredible at this incredibly detailed on scale. So here is a map of Brooklyn Manhattan has been, this is actually the first time such a detailed historical map of Brooklyn has been drawn and and this one is particularly interesting because it's about an area, maybe a lot of you know from a flat bush in 1850 and it shows farm lines and roads that are digitized by project. The edge of the city of Brooklyn's grid is to the north at the top at the top of the image. And here are the streets that we've digitized from 1850 to 1910 to neighborhood to the neighborhood level it's subdivided and gridded urbanized already and consolidated into the fold into the borough of Brooklyn. As it became part of New York City, right Brooklyn, I can still this point wasn't part of New York City. A gridded system of roads and property lines is implemented and so what we'll also be able to show is how the property leases changed hands, etc. And so here is just showing the influence of those county roads and farm lines which can still be seen in the form of Brooklyn's grid and how they sort of collide with one another. Okay, so that's that. And I don't know how much time do we have Lila I as much as you need I would I would encourage you to just go through the presentation presentation. Okay, I'm just going to very quickly show you some more finished projects because those ones are I really wanted to show you work in progress and how we do all of our work. So this is a couple of projects that ended up in Biennales and I thought it's a good way to show some finished work so we ran a big project in the center called conflict urbanism lepo and we were tracking the war as it happened and made one of the few interactive maps which number one located the names of neighborhoods in Aleppo we based it on an open street maps map and Why is it doing this. And then, on the other hand, because there was a war going on and we couldn't go and visit Aleppo obviously we we used YouTube video and a lot of activist channels of YouTube video to begin to Understand and analyze what was going on in Aleppo and and through this have actually created an archive that is that exists now that anybody who wants to study Aleppo can look at, you know, a specific neighborhood and know in this neighborhood they were eight 184 videos and you can go and look at them and they're Organized by date. And the reason that we could do this is, you know, during the seminar that I was teaching because we had actually my dear merchant had made the map of neighborhood names. And some people in the seminar including Nadine fatale who is working in the in the center now and violet Whitney who's teaching in visual studies collaborated with Nadine's Arabic knowledge and violence programming Facility to put this map together so that it exists forever. That's not guys. The other thing that we were doing is we were tracking urban damage and for this we were using data that was generated by UNHCR which showed all the Damage through pouring over satellite images. If you don't know much about Aleppo for most of the war the city was divided between the government held West and the so called rebel controlled East and as the war preceded They were fights over Infrastructures particular highways, water access electricity, etc. Which in the end the government succeeded in creating a siege in eastern Aleppo And what you see over here is the damage in the informal parts of the city, which were over 60% of the damage in the city. And we've written a paper just to show that these informed formal parts of the city had become part of the planning process prior to the war, where the Assad regime had wanted to get rid of these neighborhoods in the first place so we ask a lot of questions about Infrastructure and war and more and more war up being wars are being fought Within the within the boundaries and within the domestic spaces of cities. Okay, so there's a number of case studies on the website which you should all look at At the Biennale we were very excited to be have this exhibit location in the Museum of archaeology and within the museum there was actually an actual piece still us from the Citadel of Aleppo and then we thematically sort of themed the whole exhibit around this this column that was in the museum. Also at the at the Istanbul Biennale we did a much more extract exhibition, we were collaborating with the newly formed Sacramento Institute mind brain behavior center and we called it one brain 100 billion neurons 100 trillion connections. Some architecture students worked with neuroscientists to take their connector model, which is like each of us have a very unique structure in our brain, which networks ourselves and our memories together so it's a newly formed network model of the brain. As opposed as opposed to a spatial model of the brain which says you know your memory is here your mobility is here it all is network together and it's also part of this idea that we all have very deep memories, which we don't know how the brain is the messiest part of our body. Scientists still don't understand it. There's many people talking right now about you know the generations of memory that are constructed within us and networked into into our brain so although this is you know a more aesthetic exhibit it's part of an ongoing research that we're doing about network. Network culture and network society and I'm trying to use this to write a future article about the image Kevin Lynch's book the image of the city which was based on neuroscience principles of the 70s and cognitive science and cognitive mapping. I'm trying to link it to a new body of research, which is about, you know where Lynch was talking about place sells new scientists are talking about grid cells. And I'm trying to link these two things together as they're called the GPS for the brain and I'm trying to understand that in terms of in terms of network society. And these were laser printed models of very intricate neurons, which are not things that have been 3D rendered in physical space very often right so this is giant huge magnification of of the molecules that are in your brain which are called neurons. Another project that was displayed at the Oslo Trianale. This was led up by one soldier yoga who's from Columbia, and we were looking at the victims registry, which, which took the swath of the Civil War in Columbia from the 70s to now. And the database itself is created by the government to think about reparations to its citizens, especially if they were forcibly moved from one part of their country to another. But what we saw in this database was an amazing opportunity to show urban rural migration urban urban migration in a country over a 50 year period because the where they came from and where they moved to was written into the database so you hear this so much as a cliche. Nowadays that there's urban rural migration, but it's very, very, very hard to map. And this was because of this amazing database, however uncertain and incomplete and imperfect it is it allowed us to create this picture, and you can look at this further on our website. And then this is the last project that I'll show and it was for the last Biennale in 2018 we collaborated with Diller and Scafidia and Renfro and Robert Pietrusco, Richard Pietrusco teaches at Harvard. And we were assigned the global scale. It was a show called dimensions of citizenship and it started from the individual scale to the group to the neighborhood scale to the, I don't know, the territorial scale it's all on the on the website and to the planetary scale to the network scale. Everybody each team had a different assignment and we were given the global scale and to do this, we looked at I'll just show you this how we unroll the map. I just love that part of didn't have much conceptual weight but it does show how difficult it is to go from a 3D version of a globe to a 2D version of a globe. So what we did was we took to NASA a NASA data set which had been recently released in 2016 which was the night lights version of the sky and this is a composited view, the clouds are gone. It's about, I don't know, 300 images stitched together and it's often used to show a view of the connected world, you know, because there's so many lights, the world is connected as one big happy family. When I look at this image, the only thing I see are the gaps. Look at all those dark spaces, huge swaths of the world with no lights, no electricity. And started asking a question about what that meant. To ask the question about what it meant, we used a data set that is generated by season that is a lab up in the Palisades, a Columbia University lab and what they do is they collect censuses from all around the world and they put them together on a one kilometer by one kilometer grid so that you can click on any grid on that map and you can see according to that census, how many people live there, right? So this is very, again, very imperfect data set. The census in the United States, for example, is much better counted than the census in India or at least released to the public in a form that is counted. But nevertheless, we still, you know, use this as a as a guiding principle and we looked for the gaps, right? So for the places in the world where they were lights and no people and places in the world where there were people and no lights. And then we started, we threw an algorithm that Will Geary wrote and then we ended up with these 16,000 points, right? The yellow is lights and no people, blue is people, no lights. And then we started looking for categories like how you could tell stories with 16,000 points and we figured out that for people and no lights they were like wealthy enclaves, you know, in Colorado they want dark sky, they ask people to turn off their lights at night so that you can see the stars, right? But also refugee camps sometimes have no electricity. There was an outage in Aleppo, this was in 2016, there was no electricity in Aleppo because of the war, right? Indigenous territories, that's very complicated because some people think, oh, you need electricity Indigenous territories and other people say no, leave them alone, right? So there's all these political decisions that are built into this kind of thing. So, and then, you know, we showed the daylight view, right? And suddenly, you know, where there's no light, you can see there's urban development and tons of people, right? And this became our storytelling device. What became more interesting were the places where there were lights and no people, contiguous to places where there were people and no lights, and that in fact told the strongest, most powerful story. And so we fixated on these six categories, industrial farms, power plants, tourism sites, ports, natural gas extraction sites, military bases, borders and strip mines. And I'm going to show you only one of these stories, which is in the Central Democratic Republic of the Congo. It's operated by Glencore, an Anglo-Swiss mining company. And you notice that there's a dam on the one side of the country and an open pit mine on the other side of the country. And what happens is that the government prioritizes a high-voltage line which carries electricity from the dam to the mine and make sure it always has electricity and that the cities and villages along the way are not even allowed to draw power from this line. And so if you live in this part of the Cameroon of the DRC, you will have very uneven electricity, right? And then at the end of each thing, we showed that there were many, many sites like this in the world. In this case, these are part of 220 Glencore mines, which have very similar patterns in relation to where they are located and who the electricity benefits. In fact, one of my students in the Conflict Urbanism Seminar last semester showed how this was true in Mozambique as well. Where all electricity was sent to European countries rather than helping people in Mozambique. And I think that is my last slide. Thank you so much, Laura, for this amazing presentation. I am going to now make it possible for participants to unmute themselves. So if someone wants to ask the first question, you're welcome to do that. I will also read questions to Laura from the chat so that they exist in the audio archive. So, again, thank you for this amazing presentation. Obviously, there are, you know, we could speak for hours and hours and hours on visual studies and all of the work of CSR. Anyone who would like to break the ice and ask the first question? Go ahead, Christopher. One of the questions I have is about how you choose which area to research next or like what are the things that you're considering when you're picking something to really dive into. Yeah, well, you know, because we're a mapping center, right, we really focus on methods and rather like, if I was a historian and I was doing, you know, modern history or, you know, Indigenous culture, I would be an expert in that. But because we do mapping and our approach is to have a critical lens on the data that we use and to tell stories about things that might not have been noticed, we often collaborate across disciplines. Again, we choose within that what we're interested in. We also often, you know, you could see Aleppo and now we're doing coronavirus. We often focus on current events and then uncover the history, but very much choose collaborators and are chosen by collaborators. So it's a it's a very good question, but I think you can see that the underlying approach is that the approach mapping as a counter cartography. And we really underscore the politics and the history associated with each particular method that we use and each particular topic that we address. So that helps. So often it's very common with a mapping, a mapping center. More questions. Question. Yeah. So I'm particularly interested in the mapping historical New York City project that you're doing. And I was just wondering, like, because I know you briefly mentioned that it's also showing like history of whiteness and like white New York. And I was also wondering, like, when you do a project like this, do you kind of have like a thesis that you're formulating your argument around doing your research or does it just kind of accumulate into something. Yeah. Well, this is, you know, this was a three year long project. And, you know, main eye is a historian of immigration, Rebecca Cobrin. Research is deeply the history of of New York. Gargoyle Bych is a, again, a methodologist of GIS and history. And we applied for this grant because this hasn't been done before, right. So there's, they have been, there's been incredible work done before of digitizing old maps and, but if you do, if you digitize it and create it into an actual GIS format. You could, you could ask all kinds of analytical questions. And so we've only gotten to the stage where we've almost fully digitized Manhattan and Brooklyn over these three years. And Dan Miller in CSR has done huge amounts of work with a lot of students. This has a lot of students have participated in this project and Wright Kennedy is a postdoc in the history department and we really have had tons and tons of students work on it. We are now ready to ask analytic questions. So, you know, and we, we're, we're thinking of all kinds of ways, you know, what were the top 10 jobs in. Oh my God, it's wondering outside. What are the top 10 jobs, you know, in 1850 versus 1880 versus, you know, how many black people had come to New York, although the great migration was later in history. Are there invisible communities that weren't counted by the census. So, we're asking, where were the most overcrowded actually Leah Meisterlin and Geregovic showed that Manhattan was more crowded in the early in the early in the 1800s, then it is now. The other parts of New York now that were crowded but the incredible overcrowding around, you know, factories and things like that which were in the city was very intensive. So this all so on the one hand, but that one, we are going to have a public facing website and we're going to tell the public certain things about historical New York. But we're also making this amazing database available to historians to ask their own questions. And we have no idea what those questions will be that we're the goal is to make it public. That's incredible. Thank you so much. You're welcome. Thanks Laura. The next question is from Lori was entered into the chat. She says yeah, thank you for the wonderful talk. You mentioned your research on activating weak ties and reinforcing them in communities that are not homophilus. Can you please elaborate on some of the ways you're achieving the connections. Okay, that is that's a very good question. And, you know, we're we're actually just finishing up that paper. And what we're trying to say, you know, we're not reinforcing them in communities that are not homophilus we're trying to think about how to create conditions that are not homophilus and that if our social networks were designed differently, if our cities had different policies, we might be able to achieve something different than what then when homophily is naturalized as an axiom of social life, which it was never ever defined as So you should, I can't answer the question but there was a credible housing activist Catherine Bauer and there's a book that's recently been re-released by her and her theories, you know, if social policy had listened to Catherine Bauer, we might have very different cities than we have today. So very different housing policies. But it's really it's a project we don't, we, you know, we really actually want to work with computer scientists to try and figure out ways of activating weak ties. That's part of our, that's going to be part of our ongoing work this year. Okay, thank you so much Laura. I think we'll give the guests in the chat just maybe two more minutes to have one additional question. I think this one will be our last so we can end an hour and 15 minutes. Okay, Susanna is wondering, where does all of the data come from, of course, and from the Mormon New York census is acquiring the right amount of data difficult for the center researchers. Yeah. Acquiring data is a major part of our research right so the million dollar blocks data that's the hardest data to get we've actually just requested more data from the, from the, from Albany from where the prison data is is held and it's not publicly accessible data. We have scraped data from the web, you know, like the way we did the YouTube video that we had to, you know, figure out in genius ways of doing that and because we had these neighborhood names collated we could do that. The, we got access to the Columbia database through one and connections he had in Columbia, the data that we had is a much finer grain then was given to the public which is why we could do such amazing work with it. Every project has a different, you know, some data is publicly available but not mapped in the same way so for example the season gridded population of the world is just this amazing resource if you go to their website it just looks like a bunch of pixels right. So we've animated it and we've worked with it in more creative ways through software programs like processing or like D3, you know, so there's not only the data that's there but it's thinking of the data as a storytelling device as an analytic project. In terms of, you know, how to use it in the most responsible in the most responsible and also innovative ways so you know our lab grew up around the word data visualization for our first 10 years we were called the spatial information design lab and we've transformed into the center for spatial research and it's unknown what the future of it will be. Yeah. Actually, Bahara has asked to ask one more question so I'm not sure if you wanted to mute yourself or type it into the chat. Okay. I'm just going to mute it and I'm going to ask it here. Thank you so much Lara for the great presentation. My question is about the first the hemophilus project. Yeah. Have there ever like been a study to show an algorithm result about it's the pattern of the community that black and white people choose to live with each other like changes. How that impact them psychologically and like serving them in a way like to show their emotions and feelings and just finding an algorithm about instead of like having a natural, you know, hemophilus like if that pattern changes and they have to like live with each other so how that impacts them psychologically. Right. I'm sure they are studies like that I haven't you know because we were looking at how it as a concept became naturalized and implemented in social network so that was our trajectory. Wendy Chun has she's been looking at the ambivalent population answers but yeah I don't I don't psychology is not my field. I'm sure they are if you if you look up if you look up. If you look it up. Yeah, you so much. Yeah, it's definitely a concept that has been studied. Yeah. So again, Laura, and I just want to mention, you can find CSR at CSR dot Columbia dot edu online. It's actually C for SR C the number. Yeah, yeah. You can go into the chat Laura you can also find that on Instagram and on Twitter to see updates on on what they're working on. So I'll leave the group open for just a few more seconds but thank you so much Laura for all of your work. Yeah. And thanks everyone for coming and please email me especially incoming students or anyone if you have questions.