 Thanks for coming to the last, and potentially best lecture of the semester, our Lectures in Planning series. Today we have Erin McElroy. Erin McElroy earned her doctoral degree in feminist studies from the University of California, Santa Cruz, with her dissertation project entitled, Unbecoming Silicon Valley Techno-Imageries and Materialities in Post-Socialist of Romania. This project analyzes the politics of space, race, technology, and displacement in Romania and Silicon Valley, as well as modes of resistance and deviance. Erin is also co-founder of the Anti-Election Mapping Project, a counter-mapping and digital storytelling collective that documents dispossession and resistance struggles under identifying landscapes, focusing on the San Francisco Bay Area, Los Angeles, and New York City. Recently, Erin co-founded the new Radical Housing Journal, a peer-reviewed journal bringing together a scholar-activist housing justice work trans-nationally. Currently, Erin is a post-doctoral researcher at NYU's AI Now Institute and is in the midst of launching a new project that investigates the artificial intelligence behind property technology, looking to the unfolding of data and property regimes. And today, Erin will be presenting her talk on the ethics and data of mapping displacement on the work of the Anti-Eviction Mapping Project. So with that, I welcome Erin for the introduction. And thanks for being here and letting me talk with you all, hopefully, not just to you. So please, I want this to be a conversation and not just this, this didactic picture. So please, endure up to me. If something doesn't make sense, let me know, and hopefully it will be a generative 40-minute or so presentation. So, yeah. Yeah, so I am one of many people involved in this project called the Anti-Eviction Mapping Project that I'm going to focus on today. We are a counter cartography collective and data visualization, data analysis collective that's been producing work to fight evictions and gentrification, mostly in the San Francisco Bay Area since 2013. Two years ago, we launched a new chapter in New York in LA. Those chapters are newer, but now that I'm in New York, I'm able to plug into the New York one. But we're a pretty horizontal group, so I'm going to be showing a lot of work today. That's not just mine, it's collective work. So I just really want to make that known. But I also want to contextualize it alongside some recent work that I've been doing on property technology and the sort of data practices that landlords in the real estate industry are using in order to do kind of the opposite of what we're trying to do. So we're working to collect data and produce tools and technology for housing justice. And I want to position this in this landscape in which real estate speculators and landlords are producing data and maps for housing injustice and how we're trying to think about the ethics of mapping displacement in that landscape, if that makes any sense. Hopefully it does. So I'm going to talk a little bit first about actually platform real estate technology and data that's being produced for housing injustice, then get into the work of the mapping project and then wrap it up with a little conversation on data ethics. And some of this new work that I've been doing at the A&M Institute where I'm doing this postdoc is also being done in collaboration with a geographer named Desiree Field. So some of you might know, he now teaches at UC Berkeley and has been studying platform real estate for some time now. We're currently working on an international project looking at property technology and platform real estate. And I'm supposed to focus on the US, which is no easy task. She's been looking at this in Berlin lately. But just to kind of contextualize, there's this emergent field of property technology or some people are calling it platform real estate. That really began maybe around 2012, 2013. It's about an $18 billion global industry right now and Wall Street seems to be its epicenter. I've been attending some of these prop tech conferences and trying to learn from some of the insiders, but also I've been working with some tenants who have been fighting its various instantiations in New York. So this is kind of how I'm grounding myself in this New York space right now. I'm going to kind of go through this relatively quickly. So just raise your hand if something doesn't make sense, because I want to get to the mapping project work as well. But you know, platform real estate, it's not just the sort of digitization of real estate listings. There's this whole wave and various ways really that the real estate industries is now trying to catch up. There's this idea that real estate is this legacy heritage industry and now it needs to catch up so that it can take advantage of this new tech boom era that we're in, which means using IoT, artificial intelligence, and various databases and data collection modes, data brokerage modes in order to collect data around property, which can also kind of lead to real estate funneling money into these various types of management and development and kind of looking at housing now as a service. There's this idea that we need to, I guess the hotelization or monetization of housing is where real estate should be funneling its money, because that's what millennials want. That's the idea that you can find circulating in a lot of kind of strange prop tech conferences that might have panels like this. This was a conference that I went to in Wall Street a few months ago, so you can just sort of, you don't need to read all of this, but get a sense as to where the industry is headed right now and how the industry is thinking about data and technology. In New York, some of you might have heard there's been a lot of pushback against one form of prop tech, in particular, facial recognition of property technology that really came to your head over this last year in Brooklyn and Brownsville, where a public housing complex at Lena Plaza Towers, it's a 718 unit building, or really two buildings. The landlord, Robert Nelson, decided he was going to install facial recognition technology from this Kansas-based tech company called Stonelock, and the idea was that tenants would have to give up their key fobs and replace them with, or basically instead subject their faces to this weird biometric heat wave mapping that Stonelock has produced. Stonelock apparently contracts with 40% of all Fortune 500 companies and has various ventures globally. This technology never was installed in Atlantic Plaza Towers because the tenants organized and fought back, but apparently it has already been installed in other locations in New York without tenant consent. And there's this other FST-21, it's another facial recognition kind of technology that uses motion detection that's already been installed in Knickerbocker Village in the Lower East Side. And you know, Atlantic Plaza Towers, it's a predominantly, well, both buildings have predominantly tenants of color, mostly women. Atlantic Plaza Towers is predominantly black, Knickerbocker Village is mostly Asian American, and many tenants are immigrants. The company that invented this particular software has contracts with the IDF and comes from a military background, so a lot of tenants are worried that their data is being given to ICE. Tenants in Atlantic Plaza Towers were worried that their data would be given to the police. And we know already that a lot of this technology disproportionately works on white men and not women and not people of color. So the tenants in Knickerbocker Village have been talking about how in order to get into their building now they have to do these humiliating dances in order to be seen and enter their buildings. There is a company called Teamon, made by this comedian named Ari Teamon from New York who's installed this facial recognition doorman, as he calls it, called GateGuard, a number of 700 buildings in New York right now. Most of them, they were higher end buildings where people actually want this because they see it as a perk. And yet, this is this weird mailing Teamon sent out to a bunch of landlords recently that looks like a joke, but he's actually saying that if you install this strange doorman thing, it can help you get rid of tenants that you might not want and raise rents and reduce rent stabilized housing and turn it into market rates. So it's not lost on the people inventing some of this that it can be used in order to raise rents and revenue. That's the thing. Some of it's being installed in market rate and luxury housing because people think of it as a perk. You don't have to have a key anymore because you have your face. But in the case of Atlantic Plaza Towers or Knickerbocker Village, it was public and then affordable housing. And so it's sort of interesting how it gets rolled out and if we can have a long conversation around the ethics of how it's rolled out. So I think part of, yeah, that's part of what I'm in maneuvering cards. Yeah. And so Teamon also has this database platform called Property Panels XYZ. He also has this thing called Sublet Spy. But Property Panels XYZ integrates with his official recognition hardware and this Sublet Spy tool he created in order to detect illegal sublets. So that if you install one of his cameras, any data that that camera gathers is going to get integrated into this database system. And then he can offer landlords access to this database system to learn more about tenants and whether or not they might be illegally subletting, in which case he suggests that they be evicted. So it's this kind of new way that data and surveillance is being financed by the real estate industry through technology in order to raise runs. And yeah, get rid of tenants that are paying less. In San Francisco, this looks really weird, but there's actually this company called Poo Prince that landlords are using to mandate that tenants dogs get DNA tested. And then a dog poop is found on a property and can be linked to the dog of a tenant that tenant can get a fine or get evicted. So it's biometrics, not through official recognition, but through DNA testing of animals, which is like this whole other very strange demand that I never thought I would be entangled in that this is currently being rolled out in at least 100 properties in San Francisco right now. Yeah, there's a company in Maryland that now has automated eviction notices so you don't get evicted through paper eviction notices, but through an app. And the list goes on. One big company called CoreLogic, maybe some of you know about it. It doesn't offer official recognition or biometric testing, but what it does offer is information to landlords and property owners and property managers about properties and about tenants. It currently claims to have information about 99% of all parcels in the US, I think also Australia, New Zealand and the UK going back 50 years. And for $20,000 you can access it and learn about your property or property you might want to acquire. But you can also learn about potential tenants. They have these kind of bundles that they offer, such as registry crime safe and crime check that can alert landlords if tenants are, and this is their language, criminals or terrorists and they're currently being sued in Connecticut because of the racist implication of this. But this just kind of, this magnifies something. Teaman's only working in New York. This is a sort of global network of data collection being used by the real estate industry right now in order to bolster it and kick out tenants that are undesirable or prevent them from moving in in the first place. And then probably folks have been following, but on a national level we have the Department of Housing and Urban Development now proposing an alteration to interpretation of the 1968 Fair Housing Law which was a civil rights error law to prevent racist discrimination in housing. And basically the proposal that Trump rolled out was that if a third-party algorithm is used that results in racist discrimination, then the landlord's not responsible because it's an algorithm and that's not the landlord's fault. So this sort of makes the federal government the ultimate champion of racist property technology. And maybe folks have been following tools such as Amazon Ring which has now partnered with over 400 police departments in the U.S. to offer information about potential criminals again to the police. So the sort of entanglement of private and proprietary software, hardware, database systems, etc. with police, ICE, and the federal government in general is real and very complicated and something new that it's new and it's old, but some of the actual technology is new. These relationships are old and well and alive, right? But I wanted to switch gears now. I first learned about PropTech actually when I was in Romania where I was doing research for a lot of my dissertation project which was about how Western tech companies are relating to the gentrification of particular cities in Romania such as Cluj which is in Transylvania and has been recently recognized as this new like Silicon Valley Eastern Europe. Of course it's not, but there are hundreds of Silicon Valley's around the world right now that have these aspirational politics of being recognized as Western. Cluj is really the center of a lot of outsourcing for Western tech companies and I was doing a lot of interviews with people who work night shifts for Western tech companies like Oracle, IBM, Microsoft, etc. but also looking at how these outsourcing firms are contributing to the gentrification of Cluj and I realized that a lot of people in Cluj are actually working the night shift for this company called Yardee which is a PropTech company that manages the property for all of Blackstone which is as probably folks know like the leading largest landlord and has the subsidiary Invitation Homes which manages all the rental housing at Blackstone and so basically all of Black, all of Invitation Homes and you can see on this map not very well but just some of Invitation Homes homes in California they're getting managed through this PropTech company called Yardee which outsources all of this labor to Romania so if tenants in the US use one of Yardee's platforms like Rent Cafe which is very prolific in New York, San Francisco, etc. and if a tenant has a problem like with their washing machine or they can't get into their house they call what they think is a local person managing their property but they're actually calling somebody likely working the night shift in Romania and so this is how I learned about PropTech and I think there's a lot of it including team and outsources a lot of his work to Eastern Europe so there's a global dimension to it that we don't often think about and what caught my attention in Cluj is that the infrastructure where this outsourcing is taking place and is sitting upon the ruins of former socialist Arab factories and which you can see here and leading to the displacement mostly of Roma communities from the city center and this was part of my dissertation project was looking at how as Cluj revitalizes and becomes this sort of outsourcing hub a lot of tenants many of whom are Roma are being squeezed out and made to live in their urban peripheral wastelands so there's this entanglement between the exploitation of tenants in this small town in Romania that many people have never heard of and all of Blackstone invitation homes property management in the U.S. So that's how I began thinking about this and it's that's where I'm continuing to try to do work but these tenants have been resisting there have been a lot of protests led by this group that I'm affiliated within Romania called Casa Cialla Social Housing now and they've been doing amazing organizing work and meanwhile here in New York tenants at Atlantic Plaza Towers this is Trinea who's one of the tenant organizers have also been writing back and this is a recent city council hearing in New York that successfully now has thwarted Nelson from implementing the spatial recognition technology so there are ways that that pushback is alive and well I think one of the places that we need to do more work is uniting these different struggles which are often very isolated and not thought of as connected and yet they very much are on a material level which which brings me to you the question of how so if property technology is being implemented in a very literal transnational way to to facilitate housing injustice how do we think about technology projects to bolster housing justice and that's really the question that's animated the work of the anti-addiction mapping project which I got and I've been a part of since the beginning in 2013 which I'm now going to pivot to to show you some of what we've been doing and well actually before I do that I I do want to just note that we're not the only ones doing that I don't want to pretend that we are these are just some images of a variety of really amazing tech data housing justice collectives some of which are in New York such as JustFix NYC the housing data coalition etc etc there's a great tool called Onit that's made up by a group named Sage in Los Angeles there's this great property proxies that's based out of Detroit so we're one in many groups and I'm not going to get into all the cool groups now but I just don't want to continue pretending that we're the only ones that are doing this we began again in 2013 really during this moment when we were seeing this surge of addictions take place in San Francisco very much connected to the birth of the tech boom two-point era 2.0 era so probably folks know this but the dot-com boom in the Bay Area really bled into San Francisco in a very visceral way in the late 90s and early 2000s in which real estate speculators started taking advantage of a lot of new wealth being generated by Silicon Valley and evicting long-term foreign working class tenants to create housing for this kind of new wealth flocking into the area to work in Silicon Valley some of that petered out when the dot-com boom crashed and then you have the foreclosure crisis and then following that we had this that now a lot of us refer to as the tech boom 2.0 which we date as beginning in around 2011 2012 and what we began to see was the surge of addictions correlate with this boom this was the very first math we made we made it when a few of us none of us had any background in mapping we just realized we needed to make a math to understand where addictions were happening because we knew that a lot of folks in our community were being evicted we sat down in the San Francisco Tenants Union which technically houses the anti-addiction mapping project and thought it would be really easy just to make this one map and then we were going to be done and that would be our project what we wanted to do was figure out who was behind all the different evictions and figure out if there were serial victors that maybe were enacting multiple evictions at the same time we did make this map that shows these are all this is one particular type of eviction in California should back up there but they're they're two major types of evictions that that take place generally fault evictions and no fault evictions particularly in renters event stabilized rent controlled cities such as new york also san francisco rent control in san francisco and a lot of cities that have rent control in the us achieved rent control after a lot of tenant organizing in the late 70s so 1979 in san francisco 1983 in oakland and rent stabilization or rent control means that rents can't go up more than a certain increment every year but the real estate industry didn't like this and pushed back and so in california we have these two statewide laws the a la soft and costa hawkins they only pertain to california but what that means is that landlords can bypass particular protections offered by rent control to tenants and affect tenants for no fault of their own so what we began to see was a surge of ls f evictions in particular in 2011 2012 and many of them were being enacted by LLCs and shell companies not the actual names of the victors or the owners of those shell companies so what we began to see was that like surrounding tech infrastructure but also in neighborhoods where there were a lot of google buses which are these private tech luxury buses that facilitate reverse canines to silicon valley from san francisco we began to see a lot of evictions accumulated in those particular areas and so we really just wanted to know who was behind these evictions so we could better organize right so you can see here like the sizes of these dots correlate with how many units were evicted but many many of these are not actual names but what's the pure names but there are many that are just LLCs like yeah so it's hard to figure it out so that question of who's who's evicting whom and who the serial victors are has continued to animate our project and although we made this map and thought it was great we realized that there was so much more we needed to do and that the question we were trying to answer wasn't fully addressed with this this one map that we made which was you know nevertheless helpful but still there was much more we could do and and try to understand so we soon started making maps that that are correlated for instance google bus stops tech bus stops with evictions we found that 69 percent of no fault evictions occurred within four blocks of tech bus stops we also realized that by producing the kinds of maps we began producing we were we were missing a lot of nuance in terms of stories of resistance and also just stories of displacement so we began this this narrative wing of our project that we call the narratives of displacement and resistance in which we produce oral histories and video pieces with people who have been displaced or who are fighting displacement to better understand what's going on in particular neighborhoods and with particular struggles so this has continued to date and I think what's been really nice about this narrative component to our project was that it brought in a lot of folks who weren't necessarily drawn to data analysis or cartography but were more oriented towards the humanities and social sciences and so our project is not we're not affiliated with the university some of us are academics many of us are not but those of us who are academics are coming from a lot of different fields which has been I think really the result of us opening up this narrative component to that project and producing for instance murals we made this mural in collaboration with a bunch of tenants whose stories we've collected in the very first iteration of our oral history project and invited them to participate in creating a mural and I think this dedication for the mural in this alley which is a very kind of famous mural alley in San Francisco we began doing work that involved projecting narratives on buildings and creating sort of feedback loops in urban space so that we could we could be in dialogue again offline online and kind of create these hybrid spaces between the two um yeah we also began working with housing clinics that collect different kinds of data than the data that we had we had previously been able to access so that first map that I showed you it has rent for data and so the cities with rent control often have rent boards some rent boards are more forthcoming with their data than others um so just for example San Francisco and Oakland both have rent controls San Francisco's rent board did give us their eviction data which we were able to analyze Oakland refused for two or three years and we had to write a number of record requests and actually threatened to sue the county until they finally give us their data but whether we get data from the county courts or from the rent boards it is it's pretty bare bones maybe it will be the date of an eviction and an address possibly the type of eviction but that's it so we don't get any information about who's being displaced and we don't want to have any information about anything that could be used to identify a tenant but we did want to understand the demography of displacement and where people were ending up after they were displaced so we began partnering with groups such as the eviction defense collaborative which represents about 90 percent of all tenants whose evictions go to court in San Francisco to um to understand client intake data uh so here we can this is the map we made to figure out where people ended up after being evicted in 2012 we followed up with them in 2015 um we were able to reach about 500 people so it's just a small sample set but as you can see it shows us um movement within the city we can also understand um the demography of who's being displaced we found with this map that 300 percent of of um sorry that the black tenants in San Francisco are overrepresented by 300 percent when it comes to who's being evicted which is huge um and so that that is really important in understanding the racist nature of the displacement crisis um but we were also able to figure out where where folks were going um when they were kicked out of of San Francisco and even um who ended up homeless and and who passed away as a result of eviction so this is a different kind of data than the data we'd previously been getting um yeah after a couple years of pressuring Oakland and Alameda county which is the county that contains Oakland Fort it's eviction data we were finally able to get some and so we produced this very lengthy interactive report with a number of community partners um to to kind of display that data in a way that we thought made sense and to entangle that data with other data sets so um this is Alameda county um so we have video pieces um we have uh data that different um uh students collected in their their schools um we have narrative space or narrative work we have maps about public spaces that have been lost um we even have a community power map which we produced with a local um art gallery in which tenants could come in and put on the map spaces of power and spaces of um that they consider to be community assets so that we could start thinking about space not just in this negative way but also as a site of power and resistance um and then we digitized it which is where this map is but it's this this huge like online interactive report that we made um that I think really gets I think this sort of report really highlights the ways that we we work with community partners and we don't really make reports for sure alone we're always working with other groups and really trying to maintain some sort of um horizontal approach when we do that um yeah we began to also analyze um we wanted to still better understand who is benefiting and and who was kind of taking advantage of of the displacement crisis if you want to call it crisis obviously it's it's more than that um so we started for instance looking at the loss of single residency occupancy or SRO hotels in Oakland and um one of the really I don't know how to describe this but um do folks know what SROs are generally right they're they're yeah a lot of tenants who are in pretty precarious situations live in them but in in Oakland a lot of them have been flipped and converted into what are now being called like tech dorms or um or just fancy hostels with German beer gardens on the roofs so we began this project to really investigate what's going on with them um and both Oakland and San Francisco have experienced a surge of houselessness as of late for a variety of reasons but one of them is that a lot of SROs are being shut down and really after being kicked out of an SRO there's nowhere else to generally go so we started looking at that and the increase of houselessness as part of this project as well um yeah and it was around this time that we began new work in Los Angeles and New York so each of those chapters operates relatively independently they're they're autonomous chapters um but we do share platforms and tools and technology so in LA folks began this new narrative project which they call tenants in common that they they made in collaboration with a few tenant groups there which features various forms of oral history work um and they also began doing a lot of work to understand the implications of sweeps as they're they're being used to target houseless folks in LA um because we have this LA chapter we've been able to do more statewide work and and really examine what's going on across the state in terms of struggles for rent control um really it's been although we've had a lot of uphill battles that often feel like they're losing battles in San Francisco because we're fighting these two big real estate well the real estate industry and the tech industry statewide there's been a lot of organizing and a lot of tenants uniting and rent control actually being passed so we've been doing a lot of work with statewide groups such as tenants together and homes for all to really understand what's going on across the state and how we can better gain and control in particular cities um yeah I'm just going through a lot of our work right now but and there's we have a sub project in San Francisco that I haven't been a part of but other folks have um that's called dislocation black exodus that's been really documenting black experiences of gentrification in the city and their goal was to produce a zine but it ended up being 147 pages which is now online um and you're welcome to take a look later but we just released this um two months ago and recently made a um an interactive digital humanity platform that highlights all of that work too so that's been an exciting kind of new addition um but most of what I've been working on has again been trying to continue to identify who these serial ventures are and make that more accessible and palpable for for tenant organizers on the ground um so in addition so this is a map we made of all the wall street landlords in California which includes blackstone and invitation homes um blackstones recently merged with these other huge wall street companies like colony and waypoint um and again they're the largest landlord nationwide um so yeah they operate through a number of LLCs but what we found was it's actually not so hard to figure out where their properties are because often they use the same mailing addresses to register their properties so this was a huge thing for us to realize and we're like oh we could implement this to kind of figure out um to better analyze the real victors that are not maybe blackstone scale but still large serial victors um in San Francisco and Oakland um so for instance this guy William Rosetti um he's currently Oakland's top serial victor uh he has a number of LLCs which you can see here um much like one of these blackstone kind of companies um and of those all of these on the left have issued addiction notices making him uh Oakland's top of victor with over 4 000 notices um eviction notices um yeah since 2008 and this is excluding a couple years that we couldn't get data for from the report um so we we began making pages like this um Veritas is currently San Francisco's largest landlord and becoming uh quite a serial victor and you can see on the right again all of their their LLCs um and yeah they've been behind only 20 units evicted but they've been harassing a lot of tenants out at their buildings unofficially um so we're also able to figure out who's funding them um there's a group in California called first or say called the California Reinvestment Coalition who's been able to put pressure on some of the banks that have been behind eviction such as First Republic which we identified as disproportionately funding evictors so that information has been useful. Do you know if this is true how you hide LLCs from the big money lord? Yeah so so we do a few different things for one we we look at where owners so they're okay they're like three different data sets that we're trying to merge all the time um one is the eviction data we're able to get from various cities or counties the other is just property parcel information right like who owns what parcel but then the third is um business registry data so we look at different states California mainly to understand um what businesses register what names with the state um that data is often very hard to to parse through um there's there are tools like corporation wiki that um are basically funneling that data into a more interactive platform so sometimes we use that um but we're currently in the process of I guess I'll just get skip ahead slightly um did it that we're trying to automate this process with our this new tool that doesn't exist online yet so you're you're seeing our like very data version right here where we're trying to um merge these different data sets um through what's called a relational graph database um so that one of the problems is that the corporation data is so weird and complex there could be an LLC that owns an LLC that owns I don't know that that is the manager of a different LLC it's very strange um so we wanted to be able to relate these different data sets but if you think of a traditional um relational database they're basically these more I don't know like just tables right that we we merge different columns or different data um through unique identifiers etc etc but what we're able to do with a graph database is really understand um the the weird connections so that's what we're trying to automate right now but when we began doing this work we weren't using a graph database we were simply looking at where um the the businesses registered their um their mailing address and then group properties together like that which is exactly what um just fix nyc which is another really amazing repair the part our new york chapter partners with that's how they um have been able to create their their tool that identifies owners by just looking at owner mailing addresses one thing we were finding was that while that works a lot of the time it definitely works with the um the wall street landlords there are some landlords such as veritas who might share a po box with somebody else and so we didn't want to falsely accuse somebody else of the victim if they didn't and so that's been one of the things that's been hardest for us to parse through and that's one of the reasons why we wanted to not only look at mailing addresses but um also kind of use this this graph database structure to look at different relationships between LLCs um this is not my I'm not a graph database person there are other people in their project who are even learning um but it's a really there's this um library called neo4j that we've been using if anybody's really into databases or wants to geek out on that later but um but yeah so for instance like I could look up um let me just let this up like a an address here I don't have to look at the answer um um so there's this um company called 55 Dolores street LLC that uh evicted 55 Dolores street in um 2013 they're the shell company of a bigger company called urban green which I mapped out here once when I threw out my back and couldn't move for a week I I used little sys which is um and a great open source project that allows you to look at corporate connections I use their tool to create this kind of web of relationships to better understand urban green so um so to just show you here uh urban greens and investment company in San Francisco they're a subsidiary of a bigger company in Colorado called cornerstone holdings the CEO of urban green is this guy David McCloskey the CEO of cornerstone holdings is his father but um all of these purple darker purple circles are properties that a particular LLC such as 55 Dolores street LLC um purchased and evicted the more magenta I don't know you can quite see but the magenta circles are properties that they have purchased that they have not yet evicted but perhaps they will um you can see that they're getting some of them are getting funding from first republic bank um I I sort of dorked out on this and wanted to follow um political contributions and was able to figure out all these connections to both the democrat and republican parties mostly republican and the ascan institute which is this republican thing in Colorado um and was even able to make weird connections to like the new york city police department which and you know all the way up to David Koch and Trump if you if you go far enough but um but what's useful for some what was useful for me in doing this was to identify points of pressure that we could apply in fighting some of these evictions so for instance um after 55 Dolores street got their eviction notice one of the women who was being evicted was at the time 97 years old um she's since passed away but it became a sort of national story because we were able to apply pressure and and kind of create this campaign that the McCloskey's were evicting a 97-year-old woman but we were able to get some some friends in Colorado to go and also you know um hang billboards and petition outside of the offices of cornerstone holdings and we could have worked up the web even further but eventually um they decided to withdraw the eviction and give her a lifetime at least but she only lived a couple more years while all her neighbors got evicted including her caretaker so it wasn't like an ultimate success but um but that's sort of the the point that's kind of what we're going for with identifying these webs of connection but the thing was it took me um probably about a week to build this from hand by just looking up all of these different LLCs um all of the parcel information I could find the eviction notices so what we've been trying to do is find a way to automate this and we're not quite there yet but that's what our victor book tool is trying to do um with our graph database um and it's not fully working yet so look out for it I think we're going to probably release it to the public early next year um but it shows you all of the parcels that are related through the the various corporate connections um but what's one of my favorite parts of it is that it also shows you kind of the web of connections and lets you play around this isn't fully this doesn't have the complete data set yet which is why it doesn't look like the one that I made but the goal is that it will and it will let users um kind of yeah play around and better understand all of these weird connections um so that they can organize accordingly so um that's our victor book tool which is by far the most complex thing we've tried to build so far and it's required the most work um we're considering like how it would be really great to model this out in other cities but this kind of gets back to the the ethics question that I want to sort of end on um so it's um when we began there weren't many groups doing this now there are a lot of groups doing this some of them are totally amazing but we've had some trouble with some bigger groups trying to kind of scoop up and absorb our data and use our work in a way that is maybe not as ethical as it could be um so the eviction lab Matthew Desmond's eviction lab in Princeton um tried multiple times to get our data from us without any sort of yeah any sort of conversation around data ethics how our data would be protected what he was going to do with it um as we found out he was doing this not just him but his team was doing this to some other groups across the country too I mean we've had conversations since then and I'm not just trying to make him like the enemy here but it's kind of become this weird landscape in which eviction data itself has become this commodity as these groups have kind of populated and gotten a lot of funding um we we are not funded so that's not really our concern the eviction lab is massively funded by I don't know MacArthur money forward money Facebook money and with that comes a lot of incentives to grow and expand and now become I think an international mapping project that they're trying to do but what we found was that because they're not rooted in like on the ground struggles and they're not rooted in community the eviction lab produced this map of evictions in California that really undermined the problem and didn't include the data that we had um because we wouldn't give it to them because we weren't quite sure about them yet but what they were able to use was one of these data broker companies these prop tech companies to get their data and and um it really undermined the scope of what was going on but of course their project has a lot more validity than ours because of just I don't know Princeton big money did it that so it becomes this weird kind of conundrum rate um there's this this project in Detroit currently called land group they've changed their names multiple times they used to be called love land but I think before that they were called like we should own that and they um they're also proprietary and offer parcel data for anybody who wants to buy it but they really position themselves as like there to help um I don't know fight displacement in Detroit but really they're when they started they were they started this guy started them um with this idea that this tool would help people just buy up parcels really quickly and that if they could better map parcel than they could people like this guy could buy parcels and take advantage of what he called like the urban blight problem of Detroit and now they're themselves very proprietary and offering like again if you want to pay like a hundred thousand dollars you can get access to their national data set um which kind of goes back to the prop tech like core logic right and all of that stuff but there are these groups now that are positioning positioning themselves as on the sides of housing advocates but really I don't know it becomes this this kind of strange conundrum um and it's it's strange that it's so hard for us or hard for just fix or any of these other groups to actually produce data that just simply connects a parcel with an eviction and a landlord like that's really again like going back to our very first not that's all that we're really trying to do um but yeah the data is expensive the data is proprietary now and these corporations know that it's strategic by um that by using all these shell companies and LLCs they can maintain anonymity which makes it harder to to protest them um so yeah I think that's that's kind of where I wanted to to lead us into having a more dynamic conversation um and kind of what we've been struggling with as a project I always say that our end goal for the project is to just become an archive of a problem that is no more but the problem persists um and I think there are these other projects that are out there really to um promote themselves that are driven by capital ego etc um that are now suddenly sort of undermining the work that we're doing and that other groups are doing too um yeah and just I mean when we began there weren't so many um web mapping platforms that are so prolific now like Cardo and Mapbox and um I mean there was ArcGIS but there's also this proliferation of of web mapping softwares too that are proprietary now that a lot of people think that they need in order to make maps like this um and so they're also kind of they're supplying the landlords with mapping technologies and tools they're also sometimes supplying us with mapping technologies and tools um but it gets kind of tricky and it gets hard to figure out where to draw the line and producing the most sort of ethical nothing project that that one can um yeah so I want to I want to leave it there and open it up does that sound good yeah any any thoughts or questions I know I just threw a lot of information at you all um I mean really our website is where we're trying to make everything that we've made that's for the public available um we recently reorganized it so you can filter by topic and location now as we've added more locations um yeah and again like in thinking about scaling out that tool it's like we're we're kind of coming up against that like we don't want to just pretend that this tool is going to work for everywhere um we are now like rooted and on the ground in these three different locales LA the Bay Area and New York so we are hoping that that tool will be able to um to roll out in those three different cities by really understanding the landscape and understanding the data landscape and the housing landscape which can be a messy and there are lots of groups and relationships and organizations um yeah um yeah people who work in tech I mean we're in an interesting moment where there's a lot of organizing happening in tech right now in a way that I've never seen before um most of it of course is being done to kind of think about text relationships with ICE with sexism with with climate injustice etc I feel like there's still a lot of work to be done within the big tech companies to to make folks aware of the gentrifying impacts that their companies produce and that they themselves often are implicated in um and so I mean often what we tell people is there are so many housing organizations that already exist that need more support and need people to plug into I think there's this idea in tech that we always have to create something new and often these groups just need people to join and show up and and be bodies or people on the street so that's often what we tell folks um and there are so many groups to plug into including in slow pambali itself um yeah yeah I'm sure you're listening about uh if you have any demands uh coming from your community or about what type of data should be made more available um some people are redlining where you know the part of the organizing was to get that piece more shared yeah many data so if you have something so I mean we are often demanding that LLCs like have to register their their entire ownership system with particular cities not just with the state um and that when they do they have to be much more transparent often they're just registering a managing officer and not the actual owner right now um I think having more transparency around that would be huge as it really is mostly right now LLCs that are buying up properties um yeah and then just I mean evictions in general we can get eviction data like I said in cities with remuneration in California which are less than 20 cities in like a state with I should know but hundreds of cities that's not thousands of cities right um so right now there's no mandate that that eviction data be be made public or available anywhere and often you have to have a lawyer that you're you know writing record requests with in order to get that and da da da um so that's that's another data set that we would love to see made available um I mean really what we're trying to produce with this evictor book tool we would just love that to be to be made available and accessible by different municipalities so that we're not the ones having to do it but that's not about to happen any day soon but yeah yeah yeah yeah yeah so we ourselves are not policy advocates and we do make policy recommendations when we work with community partners so in some of these reports that we've made for instance we often will have policy recommendations but we're always careful that we're not the only ones leading those recommendations because that's not really our expertise per se but in our Alameda report we definitely have recommendations that we produced with tenants together which again is the statewide group in California that does do policy advocacy um we do write academic articles that wasn't our goal originally but what happened was some academics started writing articles about us and we were like no you got it wrong so um so we did start doing that I've done quite a bit about myself um often in collaboration with one or two other folks um and then we write a lot of more just like public press type of articles and work that does not exist behind paywalls and that's for us that's really important um yeah so there are different platforms um we have now two zines that we've made one is that black exit a scene we have another one we made back in 2015 um which is smaller though it's still kind of cumbersome and next year we're going to be releasing our first ever book which I didn't talk about but um it's going to come out with p.m. press it's called counterpoints we've been working on it for like four years um but it will have seven chapters each chapter is edited by a team of different people in that project um I've been involved in two of the chapters and that book has been a way for us to also challenge ourselves to to build new relationships um because we wanted to think more broadly around displacement and resistance so we've been working with some uh indigenous organizers for the past three or four years and we're going to have a chapter in that book on indigenous geographies um and resistance and we have a chapter on environmental racism that we've been producing with some folks involved in public health struggles and environmental racism and justice struggles um there's a chapter on like policing and state violence and gentrification so it's kind of interesting because um generally we make maps that are digital uh and not for print and not necessarily like graphic design based mapping but for this book we've had to kind of change modalities and bring in some folks with that sort of expertise and turns out it's a lot harder than I thought to convert a digital like online interactive mapping to something for print um because we it's hard to compress the kind of well the interactivity but also the temporality um so that's been it's been exciting but also a lot of work but hopefully we're in the process of doing a lot of fundraising for that because we want it to be affordable um so we need to raise a lot of money by next year so we can keep it at around the maximum $20 range and we'll have a good free online version too. I mean really so there are different ways so for instance in that mural that I showed you um we made sure to highlight narratives they're just five minute clips so there's a call the wall feature on this mural there's a phone number you can call when you go by it and hear these these narratives um they're just five minute clips um in English and Spanish um and again the idea is to distill what's otherwise an hour long oral history to something shorter and most of them are stories around ways that tenants have successfully thought back in one um we also include the story of Alex Nieto who was killed by the San Francisco police um in 2014 and these are his parents here uh actually these are his parents um Elvira and Refugio who um who painted his portrait which is right here um but we wanted to include him because he was killed after a few gender fires in San Francisco racially profiled him when he was on his lunch break and called the cops to um fired 72 bullets within a couple minutes and killed him instantly um and the police department um the the particular branch of that police department is across the street from this alley but anyway so we wanted to really make that palpable and know too so that when anybody walks by this and calls that number they hear immediately um about his story um yeah I think like with the the tenants in common um let's see this this platform it's a little bit more digestible maybe than our um kind of more geospatial map uh which this one you really have to search through there's not a great way to be like oh I want to hear a story about x y and z you we kind of intentionally wanted it to be something that people had to to traverse themselves and get lost in um but we wanted with with the tenants in common project to make that a little bit um easier for the york and just to to show you guys you know we've got the stories in LA um but we are now gathering stories in New York um there's a separate URL for the New York one so you don't have to do this but um there aren't as many stories yet but we're slowly um producing them with some some tenant orgs that we've been working in community with here in New York um and speaking of which we've also produced this worst a victor list um of of New York so you're welcome to check that out um we were able to to break down the worst of victors um by a vibero um but also um look at them NYCY um and so you you can see here here those kind of worst players are like the the sort of equivalent of Veritas and urban green in San Francisco or are these people here in New York um and just uh several weeks ago um we had an victor tribunal um with the right to council network which has been kind of acting as a way to kind of bring together a lot of groups throughout the city to put on a mock trial um to hold these evictors accountable we're all the tenants who have been um subject to harassment and eviction by them we're able to testify um and again it would the actual evictors weren't there and the judges were um or really friends of the housing movement um including one judge who was part of a similar tribunal that took place in 1970 put on by the young lords so yeah this isn't the first time that something like this has been done um but yeah and I recently realized too just because there's been this kind of looking back at the the sort of decades after the world um the WTO protest in Seattle in 1999 but that you know indie media came out of that movement right and the indie bay is the bay area version of of indie media but one of the very first things that indie media did when it formed in the early 2000s was to put together a list of the 45 worst fun lords in San Francisco so so yeah we're definitely not like the first to do this um and it's cool to kind of learn about this histories and try to make sure that we don't forget them and that we we stay in conversation with the people who really were doing this decades before um yeah it's really hard I mean it's great generally it's very organic but um we have in New York for instance we have monthly meetings um or maybe we have about 12 or so folks who show up um and talk about the various projects that are going on here in New York um and make decisions together through a consensus model um we were so it's interesting like in the whole reason really that the New York and LA chapter started was that we had folks in the bay area who were from New York and LA and or who were moving to New York and LA so everybody who kind of started those chapters was already plugged into the bay area chapter before so they were able to transmit kind of like organizational knowledge and politics and ethics really um but they were both also very intentional when they started those chapters not to just like go in and start a chapter but like spend at least a year just supporting and showing up to um the work that other groups were doing so I think that kind of gets at how we've approached um being really slow to produce work um and really not wanting to step on toes because obviously there are a lot of groups in New York doing amazing work um and the same in LA so it's been yeah it's been a slow moving process that's really prioritized the relationships and not the the work that's being produced um and in the bay area I think because we kind of emerged out of the tenants union which has been around since the 70s and it's part of various coalition there's a coalition called the anti-displacement coalition in San Francisco and then the regional tenant organizing network that kind of unites groups regionally throughout um this sort of bay area broadly speaking um I think it's been that's made it a little bit we're one of the groups in a network that generally um is comprised of housing non-profits and like legal organizations um so really even though we're not a nonprofit um I think our allies are generally people who do like base building work with tenants and not necessarily like funded tech projects so it's it's kind of a different yeah a different affiliation with with funded organizations but um yeah we have gotten funding sometimes to produce specific projects so it's not that we're opposed to getting funding we just don't have paid staff and we haven't prioritized like making that our model so at times we've gotten funding to um to do particular projects and we'll often divvy that funding up amongst the people working on those projects and yeah we're always talking about maybe we do need to to restructure it to have some more cohesion in terms of um I don't know just like some of the behind the scenes work that kind of it takes to keep their project going but that's just never been really the priority and it seems to work without that but it's I don't know it's it's an experiment um for sure yeah yeah yeah yeah it is a lot of work and I think that's one of the things I've been really realizing as we've been growing is um for every map we make you know if there's a time stamp on it and within a few months it's not going to be completely up to date anymore or or as relevant as it could be in terms of updating it with eviction data um so we're trying to find a better way to to make that happen um in the three different cities right now it's a lot of just kind of this whole list of record requests we have to do on a like monthly or quarterly basis and then kind of updating the various maps with that data um yeah it took us quite a bit to we restructure the websites that that things were searchable um by theme and location as we realized suddenly we didn't want the new New York and LA work to get lost in the sea of San Francisco based maps um that was pretty hard too because we didn't want to lose existent URLs because so many of them are in various articles or reports and so we had to um the restructuring was a lot harder than we thought but I think we have a more sustainable way to do that going forward um but yeah it's it's a lot of work and um yeah it's it's an experiment for sure questions or thoughts or oh yeah two oh no okay yeah I guess so this is kind of like this first two like um I'm wondering about you talk about like creating a dataset for like for different kinds of people is share with certain people so don't share with other people can you talk about like how do you kind of make decisions for the collective yeah particularly if you're going to discuss to like prevent the dataset if you are just worried about how are you going to deal with like these other kinds of like hard work that you're going to do yeah that's been a really that's been one of the hardest questions for us um so there are a few things for one um with this victor book tool we've been having a lot of conversations like do we want it to just be protected and only distributed to other people within our sort of lake and I displacement network um or do we want it to be made available to the general public and the fear that people in the network we've we've been having conversations with other organizers and they're like well we don't want this to get into the hands of the real estate industry but then on the other hand the real estate industry has a much more robust set of tools and data sets than than what we have like they basically already have this we're just trying to um to kind of shift the the presentation of it to to shine light on them rather than on speculatable um property so I think that's going to be okay for us to make public but in terms of like the ability to download eviction data sets that's that's something that we've been struggling with too because we want that to be available we've been worried about that getting into the hands of the landlords but the more that we realize that they already have it the less worried we are but we definitely don't want any identifiable information about tenants to be used against them that's been a really important thing to us and that was what we wanted to have conversations with Desmond about initially that we never were able to have um for instance our oral history map um right now the the stories that pop up on it are um they're not archived anywhere other than on our site and unfortunately with SoundCloud which is what we're using right now but um but we have access to that and we can we can take a story down or put a story up when we first launched the oral history project um we learned that one of the tenants who we've been working with he was a friend of one of the other people in our collective we had a whole narrative that was about their fight their eviction struggle um we found out that the landlord um their landlord had a lawyer that found that oral history and decided to use that in a court case that was ongoing against them which horrified us because it was like the last thing we wanted to do was to produce um narrative work that would be used against a tenant right so we we have right now this double consent process that we've designed with tenants that they consent to their story going online um and we before we even put it up we need them to consent again that it's okay that they're not in the middle of any sort of ongoing court case or investigation and that they know that at any moment they can write to us and we will take it down instantly um so that's been like an important thing for us to design and a reason why we've not archived oral histories with um a more formal archive that we wouldn't have as much control over although now I know there are some really radical archival projects that would let us have that control but yeah that maybe that's something we'll do in the future um but yeah it's sort of like an ongoing learning process um because a lot of the data is really sensitive and yet some of it when it's um abstracted slightly and kind of without the identifiable information can be really important to make publicly available um but yeah it's it's weird it's a weird question and problem to try to figure out yeah is anybody working on any sort of similar project here or like is it I mean similar in terms of identifying landlords or nothing evictions or yeah I know that there are lots in New York and it's still learning okay oh yeah yeah okay you'll learn a lot more about pop tech from her she's she's more than expert than me but it's been fun working with her so yeah I've been working with a colleague on um trying to map um yeah yeah yeah I'm sure so that's a little bit of yeah but that's not totally important yeah yeah it's interesting these different municipal governing bodies and the data that they have or they don't have um with the the prop tech stuff like we've been asking that the city what we the tenants and the in Atlantic Plaza terrorists have asked for a moratorium or a ban on facial recognition altogether um some policy makers have been pushing for a policy that would require the city to at least have a registry of all the deployments of fish recognition and automated decision-making and yeah um like the technology branch of the city do it has claimed that they don't have the capacity and that maybe it should be dbi and dbi is like no maybe it should be hd and and and it's it's kind of this ongoing like nobody wants to to create that very I think not so difficult to to produce or maintain um data so it's really interesting how you can do that um like you've kind of created a policy that was installed in the very high and like residential areas and then also the under the poor opposite the like the public housing yeah horrible housing units yeah are also getting into the and like one is a like a voluntary or the wanted item yeah exactly they're being different right right and I and I wonder like what are the what are the incentives for installing these is the main incentive for installing these like easier ways to evict um to evict residents so that they may be friends or they just kind of like like police surveillance yeah I mean so the landlords say that like their their incentive is to increase safety but right so but in for instance Atlanta Plaza towers there are currently seven different cameras that tenants have to walk through already before they get into their apartments and that's even before the facial recognition because public housing has so much surveillance already right and so much policing and the tenants will say that they have a lot of complaints that they raise in their tenant association meetings um like broken heaters or infestations or whatnot but safety is not their concern it's it's I think often used um discursively used by landlords in order to kind of speculate on the tenants that they hope to have in the future so that's what a lot of the tenants in Atlanta Plaza towers have said like this is not for me this is to kick me out so that new people will show up um who want this technology who aren't threatened by this technology um yeah with team in and the gate guard I mean his his the letter he's been sending us to landlords explicitly states like if you install this you'll be able to better um surveil your tenants and evict tenants and raise rents and da da da so I think I think that is up in the incentive of the landlord um know about these technologies before you get installed or there's like a plan like what how does the decision it's yeah it's different all the time so the Atlanta Plaza towers first like a this really weird survey went out in the mail to a lot of tenants about like check this if you like this or that and that was supposed to be around like whether or not they wanted this installed but it was not transparent that that's what was coming um and I've got some tenants worried um that mailing only went into some tenants mail mail boxes because already the landlord have implemented a system that for tenants have access to their mailboxes they had to send a photo of themselves in so it's like again this isn't the the stone log would be new but there was already this very robust surveillance regime in place that involved cameras um but yeah so when the tenants got that weird mailing they were like this is strange and they started organizing because they already have monthly tenant association meetings and doing research they began working with brooklyn legal services um which is now um representing a few different buildings that that have been fighting this um and yeah just they started working with some of the researchers that I know but other other organizations as well to to kind of understand what you know I don't know he scanned facial recognition even is the guide I had no idea that that even existed and so yeah but they're very well informed and they've already been organizing around other issues in the building so I think that made them really good um organizers and yeah um but they've been amazing those tenants and that particular case reached the national level um you've got Clark um you know proposed a policy amendment that would prohibit facial recognition in public housing in the U.S. but it's unlikely that's gonna pass but that came out of their organizing um so yeah but yeah I don't know I think in a lot of the team and properties they're more high-end and people might might like them whether they're too specific but I'm interested in my questions around facial recognition you know if the um the residents used to be from high-end properties same facial recognition you know they're different and they aren't the same little things in here because like that ritual um you mean like even the same algorithm or the same like like yeah I think that they're relatively standard based on the companies there so they're different companies right so this is the gate guard one that um our team and made and I think they're all relatively similar with like you know landlords can maybe alter some some sort of specific ways that it's used but it's the same kind of piece of hardware I think of the same with this fst-21 which is already being deployed um and this is the stone lock one um which is called a stone lock true frictionless solution frictionless solution yeah um and that it's funny actually a lot of the language around this is around safety but also frictionlessness which is like the new buzzword at these project conferences which is so strange because it's actually really hard to say but uh but people are often talking about how this is going to create a sort of frictionless future um but yeah I think that this is already being deployed I believe in another building in the Bronx um and the only reason we knew about that was that somebody living in that building was friends with one of the people in Atlantic Plaza towers and let them know and then the Atlantic Plaza tower tenants have been doing a lot of work to kind of educate the folks where this has already been deployed so even though it's this big victory with Atlantic Plaza towers it's like already out there in the world elsewhere um but yeah this particular technology is very different than this one which is different than this one but um and this is the one that's being used in some of the more high-end places but um yeah as far as I know but yeah I I know that according to Taman this is being deployed in 700 locations in New York but he could just be saying that I I haven't figured out where those locations are yet that's what I'm trying to now figure out but there's no incentive that he disclosed that because there's no requirement or anything like that um and the same with all of these companies or even that weird poo prints thing it's like um poo prints has said that they're being used in 100 buildings but at this moment there's been it's been impossible to find which buildings they are um but hopefully that will be easier with more research but that's kind of what what I'm trying to do now no I mean we just know like generally if we look at the algorithms that official recognition use like I mean they're being trained with these sort of labeling systems that we now prioritize the faces of white men um but with I don't know how that works with heat mapping or motion detecting per se um that's kind of like that's going to require some more research but um but you know scholars like Ruha Benjamin have said like the point is not to suddenly train these algorithms with more like women of color faces the point is to like abolish these these systems um but at the moment it's it's not lost on the tenants that it's not designed with their faces in mind or with them even living in those buildings in the future in mind yeah and if anybody wants to get involved with the mapping project please let me know and you're welcome to join I'm sorry if you've covered this but how much is this technology do you think can it be used to sort of like because for whatever you did like tenants they have to partner with them more than half a year and things like that yeah do you foresee sort of the use of this technology to sort of like trap tenants or people in here or or just sort of use data that might not be just using data against yeah protected yeah that's what it seems like the idea is that like if they can if particular violations can be detected um then that's grounds for distancing so I think a lot of it's looking for like oh they brought a friend and then they weren't supposed to bring in or they like um I don't know