 And good morning or good afternoon wherever you might be. I'm Pete Peterson, the very grateful Dean of Pepperdine's Graduate School of Public Policy coming to you live here from the Dean's Conference Room here on campus in Malibu, California. And I'm delighted to welcome you here to today's webinar, COVID Tech and Local Government Making an Impact at the City Level. This webinar is, of course, hosted by the Public Interest Technology University Network, of which the School of Public Policy is a very excited and grateful member of. PittUN, as it's affectionately known, is a network of 30-plus academic institutions throughout the country that are exploring a variety of issues at the intersection of tech, policy, politics, and public interest. Delighted to host this specific webinar as we're focusing on the efforts taken by three particular institutions to support local governments in their COVID response through technology. Joining me for today's webinar are Andrea Christel. Andrea is the Good Systems Network Relationship Manager in the Office of the Vice President for Research at the University of Texas at Austin, one of the PittUN members. Professor Jim Featherstone joins me here as the Executive Director of the Homeland Security Advisory Council, an adjunct faculty here at Pepperdine's School of Public Policy. And Professor Rai Ghani is the Distinguished Career Professor in the Machine Learning Department and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University, again another one of the PittUN members. The format for today's conversation is we're going to begin with a brief four or five minute intros and overviews from each of our panelists, describing the work that they're doing in their regions, again, supporting COVID response through technology. I'll have some slide backdrops to further illustrate the work that they're doing. Then we'll move into a period of conversation with me as we explore not only the work that they do, but also some of the challenges in these very unique town-gown relationships as these academic institutions seek to support local government efforts, in this case around COVID, and then we'll open it up to questions from you all. And so I invite those questions through either the chat feature or the Q&A feature here in Zoom. It would be hard to believe that any of us are unfamiliar with the Zoom platform, but if you are, just take a look down there at the bottom of the screen. And again, either in the chat icon or the Q&A icon, you can type your questions in as we're proceeding through this conversation. And again, we'll get to your questions towards the end of our time together. Again, thank you so much for joining us here this morning or this afternoon. I hope that you're inspired by these conversations. I know that of our attendees, we have many who are working not only in academia, but also in local government, and I know it's really one of our parts of our vision here at Pitt UN that we build in deep in the relationships between academic institutions and local and regional governments. And so I'm delighted to look at these great examples here today. And so, Andrea, why don't we begin with you? Tell us about some of the great work that you're doing there in Austin and elsewhere. And as you do, I'm going to share the screen and pull up the slides for your presentation. Sure. Thanks, Pete. Hello, everyone. My name is Andrea Christel, and I'm the Network Relationship Manager for Good Systems at the University of Texas at Austin. And Good Systems is one of three grand challenges in bridging barriers, which is a presidential initiative that is funded by the Office of the Executive Vice President and Provost and supported by the Office of the Vice President for Research. The way we define grand challenges at UT is that they are moonshot goals that address major societal challenges. And the goal of Good Systems is to design AI technologies that benefit and do not harm society. Grand challenges are by design, interdisciplinary and transdisciplinary. And as the Network Relationship Manager, I facilitate connections among the faculty and researchers from several colleges, schools and units, as well as with industry partners, community organizations and government. In particular, I work closely with the City of Austin, and Good Systems currently has 21 projects overall, and seven of those are collaborations with the City of Austin. Our projects are organized around eight research focus areas, and you can see those here. And I'm going to tell you about just some of the projects that have addressed COVID-19 and describe the teams briefly to give you a sense of the range of our intern and transdisciplinarity. Like universities everywhere, our faculty and researchers pivoted their efforts starting in March of this year to help citizens and society cope with the pandemic. One of the first things, and we can go to the next slide now, please. One of the first, let's see, realized, I don't think these are the slides, but that's okay. I'm going to talk about a project realized by Ken Fleischman. He is a professor of information in the Good Systems Founding Chair. And he realized that a health crisis is also an information crisis. Ken just recently stepped down as the Chair of Good Systems, but he remains a leader and is actively working on a project that is supported by an NSF rapid grant. And his team has already published in the Journal of the Association for Information Science and Technology. That team includes Bojee, who is a faculty member with a joint appointment in nursing and information, and Mike Macker, the director for the Center for Health Communication at the Dell Medical School. Smart Cities Should Be Good Cities, AI, Equity, and Homelessness is a project that's led by Sherry Greenberg, who is a professor of practice in the LBJ School of Public Affairs and the research director for Good Systems Future of Work. Sherry's team includes Min Koon Lee, Steven Slota, and Ken Fleischman, all faculty in the School of Information. And from the city of Austinside, James Snow and Khalil Balot from the Department of Public Works, Divya Rathenlal from Communications and Technology Management, and Jonathan Tomko from the Neighborhood Housing and Community Development. This project has already won Metro Labs Innovation of the Month, which is an award that was created to highlight impactful tech, data, and innovation projects between cities and universities. SMADS, and this is the slide you can see here projected. This is the Small to Medium Term Automatic Delivery System. And this project developed autonomous robots that interface with an iOS app to perform contactless and thus more hygienic deliveries. This project is led by the current Good Systems Executive team chair, Zhen Feng Zhao, who's an associate professor in the School of Architecture and the founder of UT's Urban Information Lab, and he also coined the term transportation desert. This team also includes Louise Sentis from Aerospace Engineering, and Joy Deep Visas, and Justin Hart from Computer Science. And then I think we can move to the next slide, please. Great, there are several transportation and GIS mapping projects that Zhen Feng Zhao has led, and some of his team members include Valerie Dinesh from Nursing and Katie Pierce Meyer from UT Libraries. As a response to COVID, these teams completed and analyzed the New York City public transportation systems to track COVID's spread and also completed an urban health risk mapping project for five of Texas's largest urban areas. And he also developed a Vehicles Mile Travel Interactive app, which you can see displayed here. And that shows Vehicle Miles traveled for every county in the US. And you can see one of the early findings was that there was a 39% decrease in vehicular travel as a result of COVID. Now, this is not a comprehensive report of Good Systems projects that address COVID-19, but it gives you a sense of our range. And for all of you joining us now, in February, we have some exciting programming coming up with the World Economic Forum. And I'll talk more about that later in the program and explain why it will be especially relevant to folks, not only at universities, but also joining us from the ICMA and the National League of Cities. So I want to thank you and it's really a pleasure to be here with Public Interest Technology University Network. Thanks so much, Andrea. Really appreciate that. And look forward to exploring those other topics in this conversation. Jim Featherstone, I want to come to you next. We're here together in Los Angeles and you head up something called the Homeland Security Advisory Council at SPP. Your background is as a practitioner, former interim fire chief for the City of Los Angeles, as well as the director of the Emergency Management Department here for the City of Los Angeles. And the work that you've done through this HAC and SPP initiative has been supporting COVID response through technology, looking at both GIS maps as well as digital dashboards. And so as you lead in, I'll pull up your presentation. Thanks Pete. Thanks to everyone for joining the event this morning, wherever you are in the world. As Pete says, I've been in the crisis management business for over three decades now. In fact, this is the first fire season I haven't been somewhat involved in since 1985. And as horrendous as this fire season is, I'm actually glad to not be a part of this. Anyway, so we actually started to address COVID-19 issues with technology as part of our greater effort. We addressed what we call for probably the last seven, eight years, the Magnificent Seven. Those were the seven most probable and most significant threats and hazards to impact the Greater Los Angeles area in Southern California. The Magnificent Seven being of number one, coincidentally, which we've talked about for years, was pandemic, then violent actors, catastrophic wildfire, catastrophic earthquake, a cyber event, adverse weather and large public assemblages. Unfortunately, the year 2020 has seen us touch on several of the Magnificent Seven. So when the COVID-19 crisis struck, we had already been watching it because we had been watching through the Christmas holidays, just as part of our global scan, what at that time was called the Wuhan virus. We actually went on our Christmas break, our holiday break with a team meeting. We were looking at, we always have a horizon brief. We were actually watching things like air pollution in China. It normally drops off during the Lunar New Year and then it comes back up when people go back to work and we were seeing coming into early January that the pollution was still down. So working with some of our analysts, we began to tie that in with things that were happening in some of our public health briefs were saying that there was a really bad virus in China, et cetera, et cetera. So, you know, and the rest is history. But what we started to do, we had been applying technology to the other Magnificent Seven events here in Los Angeles, probably for the last five or six years. And we looked at GIS, the GIS capability, GIS and data analytics. We wanted to take it out of the hands of the subject matter experts and make those capabilities available and usable to and with the actual practitioner communities, both private sector and public sector. So our thing was to take GIS capabilities and tools and data analytics and make them the tagline was make everything no more than three clicks away. And we wanted to democratize GIS capabilities. So what you see there on the screen is one of the screen capture from COVID testing. This is part of what we call, it's an Esri platform called StoryMap where we made this available, the ability to the average citizen in Los Angeles could put their address in, their kid's school, their workplace and they could bring up multiple data sets that were relative to their geo position. So we used the capability of GIS and we made that the common language that became because graphics and data supported GIS interfaces that's what everybody was into. Certainly since the COVID-19 event. Last October, we had tremendous fire issues in California and we were probably one of a dozen capability, dozen entities that were using this capability. And of course, now with COVID-19 and the Johns Hopkins dashboards, we've become just another straw in the broom which shows the evolution of capabilities like this and making every person much more participatory in their crisis management decision-making processes. Next slide, Pete. So here we have the mayor. This is one of the, you can tell how early this was because nobody had a face mask on. They're doing social distancing but no face mask. This is the mayor, the chief of police, the fire chief, the city's current emergency manager and a sign language interpreter in the background on the 40 foot screen there in the city's EOC is actually one of the early salas dashboards. So we actually supported over 20 city agencies using technology to actually visualize the evolution of the COVID situations throughout the city during the early days and actually up to right now. So the dashboard became a very, very well-utilized tool and we made it so that this technology could be developed, implemented and updated by non-GIS or non-data science professionals. May I visit the last one, Pete? That's right. So anyway, just wanted to say that we found that what we did is we took tools that were out there and we made them, overused the term, we made them user-friendly so that the response and the first supporter community weren't so dependent on GIS and data science professionals. So we put the tools and the capability in anyone's hands and enormously successful, the city's story map, the COVID-19 story map to date has close to three million views. So that just shows that we also got the Greater Los Angeles community involved in using technology to give themselves better situational awareness and effective decision-making. The meals, the feeding centers, you just put your address in or your kids school in, you can see the closest feeding center. We also use the technology to make better awareness of supply chain resiliency. As we've started to experience more and more food distresses, we made grocery stores available. And then also on the other side of that, for the private sector, we showed routing and we overlaid census data with economic data so that the health, social services agencies could see where the impact would most likely occur in terms of food disparities. And so they were actually making data-informed decisions. Anyway, I get on a tangent about that. So I'll back up. We've got some time here to get into that, Jim. Thank you. Ray, let's come to you in Pittsburgh or at least Western Pennsylvania. Tell us a little bit about the work that you've been doing through Carnegie Mellon with data analytics. Yeah, so every university, every organization has lots of massive efforts going on responding to COVID. So I'm not gonna be able to cover everything CMU is doing and we'll probably don't even know everything CMU is doing. So I'll mention a few things that highlight sort of work, both, we sort of take local geography broadly, we live in the world, so we should be better world citizen's geography is at least Earth. And we're not going beyond that for COVID, hopefully. So the initial work that we started was with the state of Pennsylvania and the idea there was trying to help them, so we can engage with them at the point where things were shutting down. And the idea was how do we help the state eventually figure out how to reopen and recover in a way that's equitable. And there were sort of a few different goals of overall sort of policy goals, right? One was we wanted to make sure that we could help reduce or minimize the diffusion of COVID, but we also wanted to balance that with returning to work and reopening industries, while sort of again this long-term health and economic possible trade-offs, we don't actually even know their trade-offs there in a way that leads to equitable outcomes, especially for vulnerable residents, right? I think that's one piece that there are enough articles right now on this disparate impact. It's not a surprise to anyone, but again, these reopening decisions, the idea was how do we take data that the state has? And one thing about sort of administrative data is the state has data on unemployment situation. It's relatively complete in the formal job sector, but it doesn't, it's not real time. It takes a few weeks for this data to get processed because these systems are not designed for as real-time sensors, they are sensors, but they're designed to be administrative systems that we're now using as sensors. So how do we take data across the economic impact from unemployment filings from revenue, revenue, look, combine that with human service impact, so SNAP, TANF, Medicare, and combine that with the health data that's coming in through where are tests happening, who's testing positive, what is the situation in the hospital capacity? And so trying to look at all the data to figure out what the current state is, which is a lot of what Jim was talking about is just understanding what's going on right now, which is much, much more difficult than it seems. Like, well, should you be able to just look at the data and figure out what's going on? Like, well, no, data is just an artifact of these different sensors that are being used to collect this information. That's not the truth. It's never been the truth. And it's not in context, yeah. Exactly, exactly. If your data is your unemployment insurance filings, you're gonna, by definition, miss the people who are not in jobs where they have unemployment benefits. And so what does that mean? How do you augment that? So the second, so one piece was really this, can we take this not perfect data and help the state figure out where things are, who's being impacted in terms of health, human services and economic impact? Two is can we then project forward? Can we predict who will be impacted or who will not be able to recover once things open up easily? The recovery is gonna take different, some people, again, there's a lot of studies on that of different occupations being able to work remotely and again, disparate impact there on people, lower wage occupations tend not to be conducive to remote work and will not be able to go back. Even things like, if you look at the official top down view of the economy, a lot of restaurants work open except that doesn't mean that the people there have jobs and they're getting earnings. So there was kind of the policy top down view of here are the sectors that are open but then what's happening on the ground who's the impacted today? What the recovery will be in the future? And then try to understand how do we evaluate the impact of different policy interventions along these different dimensions? So that was kind of phase one of that. Finding some of these issues around, how real time the data is, how long does it take to capture this? How fine grain is it? We then sort of also started talking to the private sector to see, can we augment the administrative state level data with data coming in from private sector from banks or utility companies? Because if you look at them, that data or a lot of this call cell phone location data while making sure that the key there was is to make sure we protect the privacy of the individuals there but then still be able to help the state make these decisions. And there the private sector data is, it has less coverage, right? It doesn't cover everybody. So if you're looking at a bank, no single bank has enough coverage but also not representative coverage. It depends on who they want as customers but they have a lot of data about those individuals. And so for example, some of the banks we're working with, they could they had they could tell when somebody's paycheck was if it was coming into a direct deposit when it was disrupted. That's a much, much, much earlier sensor for unemployment. Whereas the state might know the same thing four weeks later once they file the paperwork it's been verified by civil security administration it then comes back, it's four, six, eight weeks. Whereas the bank can know for a small subset of people that is probably extremely biased. Same for if their paycheck got disrupted then they started getting unemployment direct deposits in. So then we know what they're getting. And then when the economy started reopening did they get their paycheck restored? So for a subset of the clients of these banks we could tell in a much more real time granular way their spending patterns, their economic situation same for looking at some of the utility data. And so that kind of gives us this combination of how do we combine all of that to provide the state with decision-making tools that both sort of help them achieve some of these balancing these goals but then trying to figure out how do we do it in a way that that's equitable. And then just to mention a couple of the nice thing about this work is I'm the one talking about it but this sort of I live in the computer science school and the policy school. And so this work was that people from other people from policy school people from the business school coming in and really trying to figure out how do we build these types of analyses in a way that because these require disciplines that don't typically work together. So I think that was another piece of trying to bring in our colleagues and collaborating with people across the university. We had a team at CMU working on this COVID cast that's looking at their partnering with Facebook on doing these massive surveys on symptoms and what's going on and getting health claims data to assess again just simply what the current state is because we don't have good data on that. Let alone do any analysis. Just trying to figure out what's going on today. We've got another colleague in the math department was looking at some, they built an app called Novid that's tracking contact between people but doing it in a way that's preserving the privacy of individuals but also being more accurate than just using Bluetooth by using ultrasound. We've got a lot of other people working locally with the city, with the county here and different community groups. So one of the things we've been working with some community groups and talking to them about is how do we allocate testing resources? Because that's one thing when a policy is made where they'll say, well, we'll make sure that there's at least one testing facility within 30 miles of somebody. That's not enough to get to equity just because a facility exists doesn't mean you're gonna get tested and our job is to make sure not just availability of resources but actual consumption of those resources. Inequities, and so one of the things we've been collaborating with some groups locally is thinking about how do we allocate testing resources to maximize equity. And so if we had to- No, this theme here around the lens of inclusion and the importance of technology specifically through this time of COVID in reaching underserved populations is something that I wanna explore in this conversation but that's very good, right? Andrea, I wanted to come back to you. I know that in our audience right now we have a variety of people. We have folks, as I said, on the government side we have folks on the academic side. We have nonprofit leaders as well. Tell us a little bit about the connections that you've made either through good systems or separately with the city of Austin. How was that relationship developed in the first place? Sure, I would say that the relationship was really developed very intentionally. And I think when we're addressing these challenges it really will take research innovation but working with the actual public agencies that are on the ground. And so in February of last year we hosted a workshop for city of Austin staff and they came to campus. And we just asked them to tell us about their problems and issues they were facing. And then we had our researchers share things that they were working on and then just invited these teams to form. And it was really through the conversations that happened that day that many teams formed. There were also some pre-existing relationships but a lot of it was very intentionally facilitated. And then we had a competition for projects and we ended up with seven out of our 11 funded projects for the upcoming academic year being collaborations with the city of Austin. And I meet every other week with Sarah Smith who's a senior business analyst at the city of Austin who works in the area of community outreach. And we just talk about various team members. If someone needs something, if we're trying to build a certain bridge because of course the city of Austin is a large and complex organization in the University of Texas that Huston is a large and complex organization. And so it really takes support from senior leadership to empower people like Sarah and I to come together and to work with those teams. And we're actually going to have another workshop for them in November. I just want to pick up on something that Jim talked about about the democratization of this technology because that's something that certainly both our researchers and the city really want as AI technologies are being developed. We really want people to understand how this affects their personal interest and hence the public interest in the common good and to be able to advocate and to weigh in on certain policies. So we're actively working on that angle of it too. Not only how we can bring researchers and city officials together and city employees together but how we can all work together to then communicate what's happening to citizens. That's a great point, Andrea. And I hope it is one of the takeaways from all of the audience members that, and again, this is really a promotion of the public interest technology university network. The commitment of these 30 plus academic institutions is essentially, although we don't use this phrase but we're now going to steal it from Jim if he doesn't put it on t-shirts first, is to democratize the technology that we have access to. And I think what's so important about this particular conversation is that one of the great ways that you can in fact democratize technology whether it's AI, whether it's data analytics, whether it's GIS is to do it at the local level where you have access to both data and decision makers in such a way that you're not trying to reach some immense federal department or even in some of our state's immense state level departments. The local and regional level is really a place where you can build those one-on-one relationships and I think that's really so great, Andrea. I mean, essentially stepping forward as you've done to invite local government, in this case city of Austin, folks to say, hey, let's have a round table. Let's have the conversation about what we're doing, what may be some of your needs around technology, how can we support you? Because this really is a completely different way of thinking about the town-gown relationship, right? One, frankly, that may not have been available to us 15 years ago when we weren't really thinking about GIS and analytics and AI for that matter or IoT in such a way that cities are really beginning to wrestle with and we have such great learning and understanding in our universities. I continue to be so encouraged about the work that these institutes can do in serving local government and at the local level. Jim, I wanted to come to you next just on this conversation, again, about how we develop these relationships in the first place. I mean, your career trajectory is really quite interesting in that you worked in government for most of your career and as you say, you're really terrible at retiring. You were sensibly retired from local government service but then headed up what was first a nonprofit and then now integrated now within the work of the policy school here at Pepperdine. But tell us about the thinking when you left local government and the need for organizations from the outside, whether nonprofit or in this case, academic, to serve back into local government that there were some challenges to inventing or sustaining technology in local government. In this case, it actually took stepping outside of government to bring this great GIS technology back in. Well, now that I'm no longer in government, government doesn't do technology well. It's not the government doesn't want or need it but just because of procurement processes and transparency guidelines, which are important. Government tends to lag behind on technology and so it kind of, in a lot of instances, stunts the, or dampens the innovation spark. Yes. So we kind of put the aspirin in the milkshake. We built events that we built it and they came but we kind of, we slipped in little technological nuggets that our government partners began to bite on. One of the things that we did is quarterly and we held what we called the Salis Symposium. Right. Which was kind of like- And just to be clear that for the listeners, Salis is the Roman goddess of safety. The Roman goddess of public safety and welfare. And so that's the name given to the GIS mapping platforms for crisis management that you've created. But tell us again, because it's reminiscent of what Andrea said about these Salis workshops and how they provided a non-ramp relationship building opportunities with local government. So it allowed us to introduce capabilities and why don't yous. But we also, it was the knife cuts in both directions but we also got feedback from the users. And we were very open about the feedback we got from them. So everyone wants to be heard. So if they wanted a button put here as opposed to here, we did that, if it didn't destroy or kill something or somebody, we did that. And we showed them that their input was valuable. So they became more participatory in these Salis Symposiums. And of course we built it around the working lunch. Food is always a good common denominator. And we set up, it looked like a computer showroom. We had computers and monitors and we had our users. We also celebrated the super users with an award and an open recognition. And we put a lot on the user experience. We made that really important. And so because we worked with some pretty powerful applications, but when we found it, and I found this in government, working with the tech companies, they said, well, all you have to do is, and that phrase was absolutely forbidden in the ASAC workspace. We had a jar. Anytime you say, well, all you have to do is you had to put a dollar in the jar. And we used it to buy coffee and cookies for the office, but we never wanted to be in that situation. So we made it very inviting and we made it very inclusive. And we also, our government partners, we made it very obvious to them that we were listening to their feedback as to why it mattered. The symposiums were about introducing things, fine tuning skills were already there, but also for new thought. If the, one of our super users was the Los Angeles City Department of Recreation and Parks. Yeah. They had, so all 200 plus rec centers, each manager actually became an expert on how to use this GIS and data analytics tool. Yeah. So, like I said, we made it work for everyone. And then of course, we had police fire, the usual public safety agencies. So when COVID hit, we had developed a familiarity and an awareness of this, essentially it was a pretty basic technological capability. They just shifted the hazard framework from earthquake and wildfire to pandemic. I mean, I said that and I'm not oversimplifying, I try not to oversimplify, but they had the familiarity with the technology. And we, our board mandated five years ago, we gifted the basic technology to all public agencies in the greater LA area. Right. It wasn't cheap, but what it did is it made the greater LA area very comfortable with using technology in their crisis decision-making process. Well, and I wanna come back to that in a second with you, Andrea, because this purchasing piece is something, is an area that we don't often talk about. I know that when ATSAC was created as a 501C3, the reason it was philanthropically supported and essentially this technology was then given back to the region of Los Angeles was in a way to get around some of these purchasing challenges and even giving it back for free wasn't easy, but I'll come to that in a second, but right, I wanna come to you. Obviously at Carnegie Mellon, you're really a flagship university for the city of Pittsburgh and for Western Pennsylvania. Tell us a bit about how the relationship was built with Pittsburgh and the state government. Yeah, it's an interesting question to me because I'm kind of in a different situation. So I just moved to Pittsburgh about a year ago. I spent the last 20 years in Chicago. I was at the University of Chicago for some of those years and as both Andrea and Jim were saying that the local relationship is what matters. Everything else is totally secondary. The data, the tech, everything else is, it's all useless if nobody's gonna use it and if you're not gonna focus it on real problems. We've seen enough people building these epidemic curves, right? They're mostly useless because nobody changes a decision based on something you built and put it out. So I think for me, to be honest, it's been a challenge because I'm new here and I didn't have that relationship with the city, with the county, with the state, which I did in many other places. And so some of the work that we've been doing has been outside Pittsburgh, primarily because of that preexisting relationships and working with Illinois, for example, and some work in California and work in Mexico. But coming back to sort of the local, I didn't have the personal relationship, but CMU did. And that sort of important is what sort of, I often get this question of like, you are working with an organization in some country or some city, how do we do that? How does the university will come in? And as Jim, I mean, I loved Andrea's workshop of coming in and telling us what your problems are, so few universities actually ask the local or government they're working with think, what are your problems? Most of the times we go in and say, here's what we're doing. Can you use any of this as opposed to tell me about your problems and I will solve it. And more importantly, I will commit to solving it because if you don't commit to solving it, then you're just perceived as an academic who wants to try something that they've built and if it works, wonderful. If it doesn't work, too bad and we'll move on to our next problem. And so I think something that when I was considering coming to CMU, that was the kind of conversation that I was having is I wanna make sure that when we go to an organization and agency that we can commit to giving them something back that it's not just an exercise we're doing to the community doesn't exist to test our research on. That's not their purpose and we'll often use these test beds and I think they're horrible words because that's not the community's role. They're not our test beds for our research. They're not a Petri dish, right? Exactly, exactly. But I think it's going in and saying, tell us about your problems. And if you invest that time, we promise we will help you and that commitment is hard for universities because we're not incentivized and we're not set up to do that. Even with Jim, you're talking about like I have several systems I've developed that are implemented and deployed at different government agencies. The problem is universities aren't designed to maintain and support these things. Like if you're a consulting company, that's your job. You wanna get in there and never get out. If you're a university, you wanna get in but then teach them how to maintain it themselves because that's the long-term business model, right? It's we want to transfer. So I think it's what we've got to do with the local community of the state and the city of the state is really sort of say, what are you struggling with? What are your problems? Very similar. And then we'll commit to helping you. And there are, I think some universities have better, more experience doing it and some universities don't. And I think part of it is if we can help each other, things like the example contracts, data use agreements and all these things that end up being one-offs. And then having, what was really tough for me personally was not having that, not being able to just go talk to people and understand where they're coming from in this situation which in a pre-existing relationship is much, much easier to have to rely on my colleagues who've done that and built that relationship. And then borrow that. You're basically saying, can you lend me your trust? And I will make sure I, if I don't produce anything, then you can take it back but then I'll borrow it to kind of build my own and then share it with the rest of the community which is actually something that last, something we've been doing and we're building at CMU is trying to create these relationships with different government agencies and nonprofits not in a kind of one-on-one faculty organization but if we have it then we can make it accessible to the entire university and then put the onus in them to, well, now you have this access, can you do something to help the people? So yeah, I think it's sort of, it's interesting to hear about different models that the universities are using to build these relationships and then- But I think you raised really the operative question, right? I mean, we can talk about methods but there's also a perspective here. And that perspective is not to come to a city and say, here's what we're doing, can you make this fit? It is, here are our capabilities, how can we support, improve the work that you're doing? And that- I would not even start with here are capabilities. If you're a university, you clearly have capabilities. Every university has skills that can be used to solve problems that local government is facing, right? So I think I would, like we do these in Chicago, I used to do these workshops, we call scoping workshops, where we would get government agencies in and we would just, we wouldn't, it would be called the scope of thought, right? And we would just spend the day scoping problems, not having anything, not writing any code, not doing any data analysis, but just showing them, here come on the problem and we'll help you scope it. And that's beneficial for the agency, but it's equally beneficial to the university because now you have access to these problems, you have access to people who care about those problems and then you have access to data that can be used to help solve those problems. And then on us to develop expertise, resources to help solve those problems. Yeah. No, I like that. I wanna come back to the data piece in a second, just a time check here before coming back to you, Andrea, we're about 10 minutes before the top of the hour, we're gonna run about 15 minutes past. And so we've got some great time here for any of your questions. Again, you can enter them through the chat feature or through Q&A and we'll make sure to get to them shortly. Andrea, I wanted to come back to you on this question of purchasing. Again, if there's a mundane area of government services, it's this, but it's one that really can present a challenge in these town-gown relationships, whether it's in consulting or providing technology specifically. I know that you've been working on this issue and it's one that's even raised to the interest level of the World Economic Forum. Tell us a little bit about the work that you're doing there and some news that we're gonna see breaking in the months ahead. Hey, thanks, Pete. And if I could, before I talk about procurement, which I think is much more exciting than anyone realizes, I just wanna follow up on Raeid's point about the importance of learning from each other at other institutions and the great network that PIT-UN provides. And I know right now two of our researchers that I mentioned earlier, Ken Fleischman and Sherry Greenberg are working in the PIT-UN accelerator, right? Getting ready, developing ideas to be implemented in the community. And so I really think like the convening power of this organization and giving people an opportunity to learn from each other is so important. And something else Raeid said that really struck me was just communicating this across your university and the resources you had. You know, one of the things we accomplished at this workshop was we had an assistant professor of mathematics, Naq Tran, who came in and she had worked in disaster response but didn't have any contacts at the city. She met people working in EMS response and is now modeling how to improve that during extreme events. And then we were also able to connect her with Kerri Stevens who is the co-director of the Technology Information and Policy Institute who also works in extreme events from a different angle. So really having support from leadership, I think at the university is so important to facilitate these kinds of interactions, both on campus and then make the long-term commitments with the communities to see how these skills can be deployed and operationalized. But now to talk about procurement, which is one of my favorite topics. Please. Kayford Butterfield is the head of AI and ML at the World Economic Forum's Center for the Fourth Industrial Revolution. And they developed a set of procurement guidelines that were designed for national governments. And these were actually adopted by the UK in early July. But of course there are many more state and local governments than national governments. And so we believe that these procurement guidelines can be adopted. And smart cities is one of our research focused areas. A lot of people are looking at smart cities but the way cities are going to become smart in large part is when cities actually purchase these technologies and deploy them. So how does that happen? And one of the challenges with AI technologies or maybe any technology generally as Jim was pointing out is that it can be difficult to regulate them when they're developing so quickly that people don't understand them. And often a faster way, sort of soft law approach to affect that is through procurement guidelines, right? To say something like, you know, here's where we need a human in the loop or this is an area where we're really concerned about bias in the algorithms and we want someone to look at this. And so procurement guidelines can actually be a very effective way if you're thinking about ethical AI to make sure that those ethical considerations are reviewed and considered at the time of purchase. And so in February, just a little teaser for some programming we have coming up, we'll be partnering with the World Economic Forum and we'll have a week of programming, February 15th through 19th. We're gonna look at how these procurement guidelines can be adapted to state and local governments. So we again hope to see some of these ICMA and League of Cities folks there. And then we'll also be talking to industry and saying now that you know that governments who are big customers when it comes to technology purchasing have procurement guidelines in place, how is that going to affect the way that you are developing technologies and will that maybe motivate them in a way that they might not have been previously to incorporate some of these ethical considerations. So I think that, you know, procurement might seem like a dull word, but once you think about what is involved with that and what happens when that is deployed, it's really an important issue. And it's really that nexus, right, of where you really do need to source out that government expertise with the expertise that you all bring on the academic side as well. Because frankly, government procurement processes are not something that many people in academia have a real clear sense of. It really is its own world. And so it's so great that you're involved in this work, again, starting at the national level, but work that can be extrapolated to the state local level. Because Andrea, as we discussed in our prep call, you know, if we're just looking at the market size, I mean, the numbers of cities versus nations versus states, counties, I mean, it really, the action, if you will, is really at the state, county and local level. And I mean that internationally, much less here in the United States. And if I could, just another angle that we've been looking at that is working between the University of Texas at Austin and the city of Austin recently established a 7.5 million master service agreement. And that's just an approval, right, to make contracts between the city and the university much easier and smoother. So there's nothing actually moving forward from that yet, but we've got it in place so that if those opportunities arise, now like the, you know, the bureaucracy that's necessary to move those contracts forward has been largely eliminated because we have a trusted relationship and we're trusted partners and we can move more quickly. You know, as COVID has forced us to do, as you know, there are often exigent matters. And we've now, through our partnership with the city, positioned ourselves to work more effectively. Andrea, just as a side note, I know that our Pitt UN members would love to see if there's some template or example that can be shared around this relationship. I know that we have a lot of interested people because that, again, it's one of those things that seems so mundane, but prepares the ground for so much deeper relationships and engagement. So that's terrific news. That's terrific news. Right, I wanna come back to you because as we're alluding to here in this conversation around the challenges around procurement and the difficulties and even giving things for free to cities, you've talked a little bit on our prep call just about the perspective around data and the different perspective that many, although I believe this is changing, I know we're certainly seeing this at the policy school, that we're preparing local government leaders that are much more familiar with the possibilities in the data that they have access to. But some of the work that we all can provide on the academic side is just helping municipal governments and state governments to understand the goldmine, if you will, of data that they have access to and how it really can help enable them to make much more data informed decisions. Tell us a little bit about your work there. Yeah, I mean, I think it's a balance, right? So today, and you talk to cities or counties, you sort of, you know, there's a spectrum, right? There's one side of it, which is one extreme, which is they're thinking of any sort of data driven tools as magic, right? You put data in and magic comes out and you make decisions, of course they're better because they're based on data. And then you've got the other extreme, which is, oh, this is too complicated, this is too hard for us, we don't have infrastructure, we don't have people, so let's not do anything. And there's a lot of, in the middle, but I think, you know, what we've sort of tried to do over the last several years, it's been kind of take specific problems. Again, start with what problems do you have, right? So one of my earlier projects that we started actually five, six, seven years ago was Chicago looking at lead poisoning in children. And that being an issue in pretty much, you know, most sort of older cities where homes have been built before 1977 lead paint. And using sort of that project as can we be preventative, can we be proactive about reducing lead poisoning is, yes, we were able to build something, it took a while and get data agreements through. But I think more importantly, it gave the health department there a template for how would you use data and what can it be used for? I think that being said, the challenge becomes, and again, as we're saying, is that the data that cities are collecting is not for the purposes of policy making, of our analysis. It's their administrative purpose, right? To take like three-in-one data and nine-in-one data. I can't believe how many times I'll sort of hear, oh, you know, I was doing some analysis with the crime data. What crime data do you have? Like, oh, it's on the portal. Well, that's just reported crime data. What's the difference? Like, ah, how much time do you have? Right? So I think sort of there is this- They're going to get a copy. Exactly. But I think the assumption is that, you know, as cities are collecting this data, the danger is that they take as ground truth. The danger is also they don't use it, right? So I think that's where people like us who can take kind of a little bit of a broader view and are not trying to, you know, get the next election one, which the mayor's office is, obviously, right? A lot of the mayor's offices are busy with getting a press release out, and then they're done. Because as far as they're concerned, the project is over once the press release is done. That should accomplish, yes. Exactly. So I think what we've tried to do is kind of take chunks of use cases, work with agencies that have more continuity and sort of, you know, build something, trial it, implement it, and then evaluate. So right now, for example, we're doing a project for everything going on for a couple of years in Kansas with a county called Johnson County, which is reducing jail recidivism through mental health outreach programs. And that started off as we want to sort of see, can be understood, and we predict which people like to come back to jail. And that acquired them to go and build data yet sharing agreements. Because just because you're, you know, your county or a state or a city doesn't mean you can connect your data together today. Every agency lives in their own silo because they think they're so special and they need to be separate and everything. And it turns out, you know, you can't do these types of things if you treat them completely separately. And so we were to kind of connect mental health data with jail data, with police data, with other medical data to one predict who's likely to come back to jail, but who cares if we can help them and reduce that risk? So then last year, we started a trial where they started doing, you know, we'd give them a list of people that go out and do proactive outreach with mental health services to the high risk. And now we're getting that data back to see if it reduced their recidivism rate. And we'll find out over the next nine months or so. But what that required was one, the each agency internally to have data sharing agreements. And then two agreements with us that allowed us to use this data to help them with this specific task. And that was one of the easier cases because the county is amazingly good at kind of doing this, but they also had a very distinct use case. It wasn't, oh, we're gonna get this data and we're gonna put it together and we'll think about what to do, right? It's like, here's a critical problem we're facing. How do we, in order to solve it well, we need and kind of showing this. And what's happened based on that is that they've started, they hired an internal data analysis person, we helped them hire that person, we trained that person, we've given that system so they're now building internal capacity and identifying other problems that they can replicate this approach in. So I think that's kind of the model we've been trying to do is build capacity. The part that we haven't, I think which the PICUIN network can really help with in one way is a lot of these projects, you know, there's a hundred projects, right? And that we've been doing with different cities, they're not unique to that city. Most cities have very similar problems. And but most cities also think that they're so special that their problem is so different they just couldn't replicate somebody else's solution. And so I wonder if there's a role we can play. I'm curious what people here think, you know, Pete and Andrea, is to sort of say, you know, can we take something that's been successfully applied in one or two cities and through the partnership, work with, have this local connection that tries to replicate these things across instead of all of us starting from scratch. No, I think that's, there is a, I happen to head up the governance committee here for PICUIN, but we do have a communications committee as well that is really focused on getting the word out about these projects. I would say in this space, and I think it's fair to just, you know, frame the work of PICUIN is that working with local governments is only part of the work that the entire network is doing. There are others that are working on, particular ethics issues around particular areas of technology, for example, but specifically for this, and that's why Andrea, I'm so glad to hear about the outreach and something that I'm looking to do here as well towards these local government associations like ICMA, the International City County Management Association, like the National League of Cities. Jim's work has been so great in promoting the work of GIS among IAEM, the International Association of Emergency Managers. I mean, if there's a field of associations, local government is it? I mean, you could take it at the big screen or in specific disciplines. And so I think those are great contact points for PICUIN to get the word out about the work that you're doing. Again, to encourage these town-gown relationships, exploring that in new ways. Jim, I wanted to come back to you on this question around equality and equal treatment and serving underserved populations. I think maybe in the eyes of some that this field of public interest technology has seen us kind of an elitist Silicon Valley saturated kind of focused way of approaching technology and serving the well to do first and then seeing kind of what trickles down. But in the work that you've done, and I know obviously the work that Andrew is doing and Raeid is doing, actually the use of this technology, whether it's data analytics or AI or GIS, to serve those who need it most is really remarkable. And I know that you've done a lot of this through the Salis platform, not only for COVID response and making sure that people are aware of government services, especially those who need them the most, but also in the use of GIS for wildfire mapping and so forth. Tell us a little bit about how GIS is being used really for the benefit of those who need it most. So one, the public facing application, we made it as accessible and I don't wanna say simple in the sense of we didn't dumb it down, but we made it more user friendly, the public facing version. But we also gave the folks behind the curtain the ability to use like the social vulnerability indexing, we did a whole thing on food and pharma deserts, evacuation in one of the fires a year or so ago, the folks were in the ready set go area. And so we talked to PD and fire and so Reckon Parks, who's responsible for mass care, they said, so worst case scenario, how many people should we be expecting to shelter if this area becomes at risk? And so PD and fire who've worked there for years says about 250,000 people. So we coached them into using the tool. So we said, let's use the tool. So it was actually 150,000 people. We had them overlay the latest census data, but also we helped them prioritize the evacuation by overlaying something as simple as the median income layer. So households with the median income was $30,000 a year. There's a different evacuation lift and responsibility compared to a household where the median income is $130,000 a year. So we got the people behind the curtain to actually begin to use the data to look at, well, as we talked about now, social vulnerabilities or people who needed more assistance direction or guidance in a crisis situation. We didn't put that on the public facing side because we didn't want the appearance of us prioritizing evacuation or public efforts based on income, so to speak. But we thought that that was a factor that the public safety and first supporter agencies should use in terms of thinking through their evacuation efforts. But on the public facing side, getting the school, LAUSD is one of the largest school districts, probably in the world. It's certainly, I think it's number two behind New York, New York City in the nation, but by giving them the public facing tools, like I said, the simple story map and they could direct families to go there and see where's the closest feeding center? What's your evacuation route? What's your vulnerability, regardless of which one of the Magnificent Seven was impacting them? And we've done that over a series of crises and near crises because the other thing with the technology, people have to be familiar and comfortable with it. Because I think during the Boston bombing, it was said, we don't necessarily rise to the occasion. We sink to the height of our training and familiarity. And we saw a big uptick between the public facing use of technology from last October to this spring with COVID. Last October, we wetted the appetite for a lot of the population in Greater Los Angeles for these public facing tech tools. And we saw, they were just inundated with them during COVID. So people, they developed more of it. The other side of that, the flip side of that is that you have to actually keep up with it and you have to have the latest, greatest tool because it's like television. You know, I grew up watching black and white TV with 30 minute programming. My 30 year old daughter says black and white TV in a show less than an hour or 90 minutes. So, you know, there's a self-fulfilling and self-feeding concept. So I want to be mindful of time or we're into our last few minutes. There is a question from one of the viewer's participants here about COVID testing and the understanding that we're becoming increasingly aware that COVID is airborne. Is anyone hearing anything about supporting municipal governments or businesses through sensors, maybe CO2 sensors or other sensors looking at airborne particles or air quality to look at the presence of COVID? I don't know, can CO sensors pick up a bio? Particle, I think. They can't in and of themselves, but just as an example of the kind of sensors that are focusing on airborne, either particulates or broader air quality. Yeah, I'm not sure about sensors, but one of our sister grand challenges, whole communities, whole health did develop an app called Protect Texas Together. And we're using that to track where students are, where people are on campus, which buildings they've been in. And so then if someone gets tested or reports symptoms, we can see where they've been and who's been in those places as well. Well, I know, Rae, you had mentioned something similar as well, if I remember with an app that is helping with this tracing, it really is such an essential use of that technology. Jim, were you gonna say something? I was gonna say that, it's interesting. I never thought about the sensing, but coming from the fire service, I watched how smoke alarms change the dynamic of residential fires, smoke alarms and seat belts. The things that we take for granted now, basically change the public safety landscape. Yeah, well, I think we're gonna see this after COVID as well, right? I mean, certainly I often compare to our graduate students, this world with the 9-11 world, the post 9-11 world. And when we look at the application of technologies, especially in places like airports, and there's a lot of technology that we don't see that is happening at airports and other places of large populations, I think it's fair to say we're going to see some of that happen again. And it's gonna come out of institutes like the ones who are part of this, a public interest technology university network. So I wanna close this. I'll go ahead, Jim. Ray mentioned something about sharing, that the data, so one of the things with Sal is that the team actually built a sharing wizard. So across all 40 departments in the city of LA, they could share or not share the data that they either had on hand or that they had developed. And that was a huge game changer to be able to share because normally each department or discipline is siloed, which is a good thing and a bad thing because these cylinders of excellence, there's a plus to them, but there's also the downside of being siloed, but the sharing wizard actually was a big game changer in terms of having everybody be participatory in the data analysis and the GIS capability across the city. Yeah, yeah. Well, let's close just with a vision. I'd love to get your thoughts and this can really just be kind of a one minute proposition. Where would you like to see the relationship between academic institutes like the ones that you all are a part of and cities go by this time next year when hopefully we're actually doing things like this in person and not just on Zoom, right? I'll start with you and then come to you, Andrea and finish with you, Jim, right? Where would you like to see those relationships go? I mean, I guess I'd rephrase what I said earlier, which is I want universities to be the R&D lab for cities, not the cities to be the R&D lab for universities. That's kind of my hope is that we can help them try things out, learn, share, and then implement policies. So we want to be policy partners and be the R&D lab. That's brilliant. I also don't want to lose that interesting point that you made with the Kansas County. I think it was at Jefferson County, you said? Johnson, yeah. Johnson County, where you were actually played a role in helping to recruit a tech person for the government itself. I mean, that's an amazing teaching how to fish kind of a virtuous circle there. Yeah, we interviewed people, we looked at resumes because it's hard for them. Sorry, it's, you know, with all the tech buzzwords that come around, right? It's hard to figure out what's real, what's, and so I think it's a role that we can play and it's in everybody's best interest. Very good. Andrea, your thoughts, we're in a year from now, you're doing such great work in Austin, but I also know other cities through good systems. What's your hope? Well, I think, you know, as a grand challenge, we really want to take on these societal problems and have a meaningful and lasting impact. And so we've just launched seven of these collaborative projects with the city of Austin. And then I think that, you know, these researchers and our city partners are really looking forward to seeing this operationalized so that, you know, we can meet some of the city's greatest challenges. So it'll be, you know, seeing how the research evolves and seeing how the partnerships evolve and then really seeing it implemented. And I just want to echo what Raeed said too. I think it's so important that these aren't experimental labs for us, these are partnerships and these are the places where we live too. So, you know, we really want to do something that serves the public interest. Doing good in the neighborhood is a phrase we like to use around here. Jim, your focus has been on the intersection of technology and public safety disaster response, but the work of ATAC has also been in the homelessness space as well, working with the city's Homelessness Response Center. Where would you like to see things a year from now? Homelessness. I'd like to see the County of Los Angeles stop doing pencil and paper counts of homeless folks. There is technology that can do that. It's laughable, but we did a whole study on that. Try to convince them. Anyway, I just, one is it was really great hearing what Andrea and Raeed are saying because it lets me, lets us know that where we're pointed, and the three of us are pointing in slightly different directions, but we're still pointed in the same general direction and the concept of inclusiveness and listening to the end users and the thing of the labs, being the labs for the city and the relationships. I mean, the huge, we had great relationships because most of us had just come out of government. So every meeting was taken, every phone call was returned. It took us two years to actually get to the point where we felt we had traction, but the relationships are huge and to hear that you all have similar challenges, but they can be managed, that's very energizing. I just, I just have to echo what Raeed said about the labs, being the labs for the city. That's, that and also I think the institution of higher learning can be a kind of a buffer, take some of the edge off of the direct contact with the tech companies. Because I think the institutions of higher learning, higher education could actually be a buffer and a conduit for bringing in big tech to make it usable capability for our cities. Well, thank you all for participating in this great conversation. And thanks to all of our participants, attendees for joining. I think there's been a remarkable conversation. One that I know that my guess is that we'll be sending along a link to the recording of this session just as a way of continuing to promote this important work. I ask all the attendees to share it with their networks, because again, I think this is really evidence of where we can democratize technology, which is one of the phrases I'll take away from today, as well as that we're serving as the labs for the cities and not the other way around. And of course, putting aspirin in milkshakes is another one that I'm gonna take away from Jim, I always get a new fray from Jim. So thank you to New America. Thank you to all of you for joining us. Thank you, Andrea, Raid, Jim, for the incredible work that you're doing in connecting and using technology to make our cities more transparent and responsive and to make our public decisions better. And if there was ever a time that needed evidence that we were making better public decisions, now is that time. So thank you all for your work and look forward to joining you all on a future Public Interest Technology University Network webinar.