 Good afternoon and good evening to the students, the panelists, the attendees, grantees, and funders who are taking time out of their busy schedules to attend this virtual event. And thank you so much for joining us. This is our second annual public interest technology university network convening. In 2019, our public interest technology university network the network challenge, which is a grant program designed to seed and support initiatives that grow public interest technology at the university level. The network and the challenge grants are funded through the support of the Ford Foundation, Hewlett Foundation, Mastercard Impact Fund, with support from the Mastercard Center for Inclusive Growth, Patrick J. McGovern Foundation, the Ragus Foundation, Schmidt Futures, and the Segal Family Endowment. So we thank them so much for their help with and their commitment to this important endeavor. It's been an amazing first year for our first cohort. We've seen projects that address racial, environmental, and societal issues, and those that are lifting up the work of public interest technologists, creating a well lit path forward for students and teachers. The second cohort promises more of the same. We're so excited and honored to welcome them to our fold. And so with that, let me introduce the second annual 2020 network challenge grantees. Each day, policymakers, technologists, academics, philanthropists, and concerned citizens are making decisions about how technology will shape our future. Imagine a movement to create a better world, one with more fair and humane systems. This is public interest technology, or PIT. It's the work that members of the Public Interest Technology University Network are undertaking, whose students are more committed than ever to changing the world for people in need. We are building community cellular networks in urban Tacoma to provide inexpensive access to marginalized people. Inclusive Tech Anti-Connection Program will be an integrated career development program for students with disabilities and students from underrepresented minorities who are interested in becoming PIT entrepreneurs. We're going to be able to build a community of practice around what it means to do social justice informatics. We have a collaboration between the University of Texas at Austin, a major research university, Houston Tillitson University, a historically black college or university, and two nonprofits, Measure and Capacity Catalyst and the City of Austin. They're opening a dialogue talking about what our experiences are and what we're going through to make sure that when we innovate, data information and technology can be leveraged for societal good. All of the project is really focused on how do we enhance educational experiences for students in the ways in which they understand emerging technologies, but also develop a deeper understanding of society and humanity through partnerships between social workers and computer scientists, for instance, so that we're able to bridge and develop those knowledge gaps through experiential learning. And I think that this award and this particular network of individuals allows us to explain that even greater and the contribution that we bring is that an important partner in all of this work are the community members, the people in which these technologies are built for, but are oftentimes left out of the conversation. One need that our project is really focused on is the experiential learning courses, particularly as social entrepreneurs, who work in the public interest. You know, the public interest, you know, has oftentimes not been aligned with, you know, communities of color. And what we're finding is that for us to move forward as a community, as a society, there's many challenges that people who actually live through those challenges, you know, are once on the front line who can create, you know, solutions. Too often native students they leave their their home communities and they often are made to feel like they kind of have to give up their own unique cultural identities. When I wrote the proposal for Pitt UN, I had that in mind, that this would be a fantastic opportunity to bridge that gap between tribal communities and university faculty and students. We've learned that Pitt collaboration cuts across sectors and it starts and grows most naturally at our colleges and universities. That's because students are more committed than ever to making the world a better place. In support of this important work, New America is proud to introduce the winners of the 2020 Network Challenge. Representing projects across the network with grants totaling over 3.7 million. This is possible through the generous support of the Ford Foundation, Hewlett Foundation, MasterCard Impact Fund, Patrick J. McEvern Foundation, Rakes Foundation, Schmidt Futures, and Siegel Family Endowment. Learn more about how the Pitt University Network is building the field of public interest technology. Join the Pitt Network today. Again, thank you to our funders and congratulations to the 40 projects from across 25 universities that were awarded grants this year. We'll be bringing you their stories during the next 24 hours of this meeting. In addition, if you'd like to learn more right now, you can go to our website and check out the entire list of grantees and dig a little deeper. The URL will be in the chat box. With that, let's get started with this evening's panel. I'm very happy to help guide us through a discussion this evening on public interest technology in a time of COVID with a racial equity lens. I'm Elizabeth Garlow. I direct the new practice lab at New America. We are a hands-on lab that's operating within the public interest technology division of New America. We bring together teams of public interest technologies to work with governments and NGOs on the design and delivery of programs and policies that are focused on family economic security. Over the course of eight weeks this summer, our new practice lab interviewed Black and Latinx workers that lost their job or income due to COVID-19 about their experiences navigating our unemployment insurance system. And this work has really led us on a journey of exploring more deeply how we can center racial equity in our practice of public interest technology, not just in unemployment insurance, but holistically across programs and policies. Our work led us to find that unemployment insurance is rife with compounding inequities as our other critical government programs. Decision makers and subject matter experts would do well to really cross pollinate with experts in other areas, even and especially when they seem unrelated, because odds are they're not unrelated. It may have been that the system was designed that way. So we believe that whether automated or manual, racism and bias must be rooted out of all processes, especially when they're being used to determine someone's ability to receive critical benefits. Marginalized communities and communities of color have so often had to navigate a system that not only was not designed for them, but is also designed often to penalize them. So we will explore some of these themes further in the panel of practitioners that we have this evening who are doing such important work to design and advocate for systems that are accessible and equitable. I'm going to have each of our panelists introduce themselves by providing an overview of the work that they're doing to first increase access to unemployment insurance and beyond and how specifically they're centering racial equity in that work. And I'd like to start with Monet Fields White, who was a fellow with our new practice lab over the summer, and actually has a background as a journalist. So Monet, I'll start with you. I'd love to have you tell us a little bit more about the work you did this summer on UI and also your work more broadly transitioning from the work of journalism to the work of public interest technology. And I think we need you to unmute. Hello. Can you hear me? Hello. Good job. Yes. Hello. As you mentioned, Liz, I was a research fellow with the new practice lab at New America. I was part of an amazing team, myself, our fearless leader, Vivian Grobert, who couldn't be with us tonight, as well as Alberto Alvarez and Nikki Zivner. And I'd also like to acknowledge one of the authors of our 55 page report, author, Cassandra Robertson, and essentially looking at the work that we set out to do. I've been a journalist for many decades now, working in business and economics, but went freelance about 10 years ago and still pushing for telling stories and telling stories about the people who are infected by social inequities I've done. I've written for the root.com. I've written for American Banker and a variety of other publications. And then was granted and offered this opportunity to join this amazing team, setting out to understanding experiences of Latinx workers, applying for unemployment insurance amid this health crisis, and really just pulling back the layers on what you spoke so eloquently about in regards to looking at systemic racism within the system. But pretty much all of my work, looking at the economy, looking at our financial markets is really just delving into how Black, Latinx, BIPOC communities across the board are affected by these various crises. Thank you so much, Monique. Matt, I'd like to turn to you next. We have Matt Morrison with us, who's the Executive Director of Working America. Well, thank you much and thank you for having me. And really inspiring to see all of the participants' fellows in the setup video for this. It really puts a human touch to what can really be a particularly important way to connect bridges. So I'm Matt Morrison, I'm the Director of Working America. For those of you who don't know us, we're the community organizing arm of the AFL-CIO. What that means is that we go out and we organize working class people. We don't have the benefit of a union on the job. What's unexpected about the way we do the work is how we bring analytics into the analysis targeting impacts. Our mission, broadly speaking, is to try to close the wealth disparity that working people have been on the wrong side of for far too long in this country by empowering them through strength in numbers. And one of the unfortunate patterns that we see no matter where we do this work is that there are certain communities, particularly communities of color, black communities, most especially, where the structural disadvantages are so robust that they compound upon themselves, upon themselves, upon themselves. We've come to this project more recently, focusing on trying to answer this really simple question. And the last major recession back in 2007, eight, nine, black workers who were otherwise eligible for unemployment insurance, only 27, only 26% of them filed and collected those benefits. So a community that over hundreds of years has found itself dispossessed and without in the moment of greatest need was going without critical earned benefits. We cannot allow that to replicate itself. What we've done is try to bring all of our organizing skill, all of our observation skill, all of our analytics skill to bear. And that's why is this happening? People need the income in their lives. Why aren't they applying? What are the impediments? How do we help build community that moves them past that in a specific way that is measurable and therefore replicable in other contexts? Matt, would you like to say a little bit more about the report you all recently issued around increasing uptake, UI uptake among black workers? I would love to, yeah. So we've built this program around three phases. First, we wanted to do a bit of exploratory analysis where we wanted to get a large scale qualitative feedback that we can integrate with quantitative data, understand who is and isn't applying, why aren't they applying, and what are some of the impediments they face. The first thing that we could tell right away is that it's remarkably hard to find unemployed people when you're going outreach. You would think it'd be relatively easy, but one of the systems or biases that's built into our data systems, into our observation systems is that they are optimized for finding people who are already invested and have a stake in society. So if you don't have a stake, if you are not a homeowner, if you are not stable in your residence or in your credit accounts, then you are one more vulnerable and more likely to be displaced, but to a lot harder to find and help. Two, we found that there's a huge community interest in helping each other. And so this was really distinct when we did a large-scale survey in our phase two of this work of some 14,000 working class voters. What you could see very clearly is that around two out of three black workers, including people who were not directly affected by job loss, wanted to see how they could assist others in their community. And that's actually something about that. There's a bit of a stark difference there. When we asked white workers the exact same question, only around 46 percent, yes, they wanted to help others in their community with this action. And so there's a dimension here that's worth unpacking. There's something communal happening. I mean, thirdly, we saw that the level of knowledge about what the benefit structure was, how one could access it was lacking. And that was across the board. But at the same time, it's not that hard to change. In a series of really short clinical tests, we just delivered a couple of text messages and you could see that knowledge of access qualifications increased by 10 to 12 percentage points just off of receiving a single text message. So if we're trying to solve these kind of big and intractable problems, then there's a road that we can pave each step along the way by constantly probing, testing, assessing. But we also need to be clear about what our limitations are and how we overcome those. Thank you, Matt. I'd like to turn to Umbreen Koreshi who's a designer with Sevilla. Next, Umbreen, you've been doing some pretty deep user research with individuals filing for unemployment in the state of Michigan. Tell us a little bit about you and the work of Sevilla and more specifically the work you've been doing on unemployment insurance. Absolutely. So I work with Sevilla, which is a non-profit human centered design studio based at Detroit. And our belief is that the best way to center equity in anything is to really give people a voice so that they might have influence on the decisions that are being made on the systems that are impacting them most. And we obviously know that unemployment is a system that's impacting a lot of people right now. And the way that we're approaching this is through deep user centered design and our actual previous knowledge from working in another system, kind of a sister system, which is DHS. And the work that Sevilla does is we align ourselves with institutions such as the Department of State or Health and Human Services and now looking into unemployment to really understand what is the user need and experience. And I know that in unpacking inequities, you guys discussed how Black and Latinx communities pointed to difficulty navigating applications as one of the biggest barriers to entry of unemployment. And what Sevilla has been doing over the past four years is really understanding what is the basis of these applications and how are they affecting people's access to benefits. So what we've been looking at recently with unemployment is how are these communities gaining access to unemployment and how is it different? How are communities of color different than white communities that are accessing this benefit? And for some people, gaining an employment is actually quite simple. You have stable employment for over 18 months with a boss who will check all the boxes and send what you need. But what we've also found, and this is something that I know you touched on in your report, is that a large percentage of Black and Latinx communities are actually in the gig economy. And gig economy is things like Uber and Handyman or people who work at a grocery store or people who just have multiple jobs. I know we talked to a user today who said, I have had a full-time job for years, but no matter what, when I have a full-time job, I also have a part-time job. And so what we've noticed is that for people who are in the gig economy, one of the biggest barriers is that they have to go back 18 months and find every single piece of information for each of the jobs that they've worked. So when they started, when they ended, they need to know their employer information, their EAN and FEIN numbers, which often isn't given to them. They have to find it on a W2, which is again another burden going around finding all these documents. And once they do that, they need access to their employer who has to approve these for them. And what we're finding is that this becomes this massive complicated web people are having to navigate on their own. And this system isn't built for them. And again, it's not that these people aren't eligible for benefits. It's simply that they have so many hurdles to pass before they can gain access to this. And we have seen people who have been eligible for full benefits have to wait 20, 30 weeks before they can gain their actual full amount. And it's just like you said, it's compounding. So someone has owed benefits for a month or two months. As soon as those two months are up and they are about to be paid out, their threshold is now beyond the 15 or 1800 dollars. And they need a manager at UIA, which is already, I mean, a system that's overloaded. They need them to approve that. So there's just all of these different things that we're finding in these user research that are, I mean, honestly, an incredible, I guess, lens into these communities and how they're affected differently in so many other communities. Thank you for sharing that. Monet, I'd like to come back to you and bring mentioned a couple of things about the report that you worked on unpacking inequities and unemployment insurance. And you did some deep user research yourself as part of that. I wonder if you could share a couple of themes or stories that really stand out to you months later now, having done that research that help also to illustrate what Umbreen was just sharing about a system feeling like it's not designed or built for the communities it's supposed to serve and what how that manifests in people's daily lives. One of the quotes that we have in our story and when we added it, I smiled big, which is from Malcolm X that everyone in Harlem needed some kind of hustle to survive. And essentially, I think about Helen from Kentucky, she's a hairdresser, she's been doing this for 35 years. And she's the one who essentially we quoted in our how we started our report, which is not designed for us navigating through a system that doesn't serve you. And for her, as she states, we pay our taxes, we do what we need to do, and we contribute to this economy. Why not have the system be there for us? Because we do contribute the gig economy, especially when you think about the percentage of black and brown workers who are now joining and working as working in DoorDash, working for DoorDash, working for Uber, working for Lyft, working for all of these app based companies. Because again, it's about survival and it's also about that hustle and and not to say that none of them have dreams to have like that stable or standard idea of a job. But this is what they are doing to either reach that goal, or this is what they're doing just to survive within our current economy and shift with our economy. Because that's the other aspect of this that we need to think about. Our economy has changed so dramatically. It's not like you the same format of what we have, right, what we used to be used. I grew up in Eastern Kentucky. So it was you, you went to high school, maybe go to a few years of college, and then you went and worked in our steel mill. That doesn't exist anymore. I think about my hometown, that steel mill doesn't exist anymore. That idea of the standard job of going to work in this factory, going to work for this factory, that doesn't, they exist, but not to the level of when I was growing up. So at the same time, what we found as we were pulling, I talked about the layers, as we were pulling back the layers, systems like unemployment insurance, insurance need to shift as well. And that's what's not really happening. I hope that answered your question. It does. It does. It's, it really helps drive home the fact that the systems that are supposed to be serving people during vulnerable times have not evolved or not kept pace or were never designed to meet the lived realities of those that are intended to serve. And the skills that you all are bringing to this work around human centered design and user research help to bring to light the lived experiences of people in such critical and important ways. So I think what I'd like to do next is shift then to a discussion around the role of public interest technology broadly in leveraging those insights and those stories in order to improve access to critical services and benefits and redesigning policy. And specifically to sort of maintain this focus on our collective responsibility to do this work in a way that centers equity. So Matt, I'm going to start with you because you bring an advocate's lens to this work. So I'm really curious to hear you reflect on how Pitt public interest technology specifically helps you in your practice of advocacy, like as the executive director of working America, thinking about the application of public interest technology in your work and in accomplishing your goals. How does that play out? Can we have you unmute? Thank you. Thank you. Sorry about that. We all do it at least once a day. Yeah, no, you can't. It's not a zoom if you don't do it. I wanted to speak to an observation from the report and it was really commendable work. There was one story or a couple of stories of how interviewers, claim reviewers were looking at names of applicants and making determinations that, you know, this person has a funny sounding name. Maybe they should be subjected to deeper scrutiny. Those biases exist throughout every decision that gets made, not just in terms of whether or not someone is eligible for claims, but whether or not they get a callback for a job interview in the first place, these types of compounding inequities, or how we make design choices on where the unemployment claiming assistance should be focused, should it be focused on factory workers who have employers that file on their behalf, or should it be focused on gig workers, or what we found often was that there were sectors that were really quite at the healthcare sector, the healthcare sector, the restaurant, retail sectors were really ineffective at helping their laid off staff members access the system. And it's not for any particular reason, except the system does not speak to them. So when we think about where the public interest technology community can go, one, we have to remember everything is a choice. Just as those reviewers were making choices that they probably didn't intend to discriminate, but that was the large scale outcome and disadvantage in people who were already behind April to what we prioritize when we're looking at data systems for observation. The things that I would most want to see come out of a revised UI system is the ability for us to query quite quickly on the application status of any individual. If I can find out whether or not you voted last week, or if you've tracked your vote by mail application, or know how close the vehicle delivering my food order is, I should also be able to understand how far through the system have folks matriculated where the geographic clusters where they are not actually matriculating through the system. What are the report outs on the recent state aren't matriculating through the system so that us as advocates know exactly where the pressure points are and can orient our organizing and advocacy capacity in that direction. Secondly, we need the ability to have insight that can then help fortify the communities that we're organizing in. You've talked about others have talked about you have applicants waiting 30 weeks. We talked about this earlier, they kind of trip past this threshold. It was a common experience for us that folks would just say, I give up in some places for worse than others. North Carolina is one of the worst places in America to file unemployment insurance if you need it. Michigan, I'll say, is considerably better. I think some folks in civilian probably have, I should take a good bit of credit for credit for that. But what you're finding is that if I'm eligible for the extra $600 a week that was in the federal stimulus earlier, but I have to file for three months and by the time I'm done, I'm back at work, then I just give up and I leave all of that money on the table. And so how do we how do we make sure that we have the ability to account for and fortify those folks so that they keep persisting through that and that income that calls them to go without groceries to lose their apartment to actually have long term life consequences comes back to them and they're able to be made whole. Thank you, Matt. Your emphasis on real time data instrumentation and the importance of the kind of insights that can generate for organizations like yours are critical. And our team worked this past summer with the Century Foundation to build a UI data dashboard to try and bring some visibility to a wide array of indicators like wheat times for UI claims in order to try and bring some transparency to this because as you pointed out, this system was created the historical context around this is quite interesting. And for those who'd like to dig deeper our report that Monet and others co-authored goes into this that there were compromises made at the outset that gave states quite a bit of autonomy and how their unemployment insurance systems were structured. And in many cases, states have intentionally made it difficult to access UI. And as you mentioned, these choices matter. And so bringing some transparency and accountability to that is at least a step in the right direction. I'm going to go to you then just to think about, you know, Matt's points around how choices matter. And you at the outset mentioned the importance of user centered design and the work that you all have been doing, not just on UI, but also with the Department of Health and Human Services. Can you share a little bit more about how you're leveraging public interest technology and the work that civil is doing across many different public benefits and social service programs in the state? Sure. So I think one of the things that anyone at Sevilla could tell you is kind of hard to describe because we do have a hand in so many different sectors. But I think at the end of the day that is why how we consider ourselves strong enough to build these relationships between these sectors. So one of the ways that we leverage ourselves in these different sectors, especially public interest technology, is that we're positioning ourselves alongside leaders at the moments when they need us, when they need the user voice to come in most. So we're going and we're talking to advocacy groups like Matt and we're going and we're talking to institutions like the Department of Health and Human Services, and we're understanding both sides, the needs and the challenges, and then bridging the communication and coming up with a resolution for both. And I think that the main way that Sevilla has been able to leverage ourselves is by deeply rooting in the user need at every step of the way. I wish we were in person that I could ask everyone to raise their hand, but how many people have done a project where there have been designers and executive and experts throughout the process of funding and ideation and design and production. And you get through this whole process and all of a sudden you realize that through it all you haven't talked to a single user. There's all these experts in the room. They're all talking about the data that they have, but no one is gone and asks someone what they need. If the technology you're building is the thing that they really need, that's going to be the most useful for them. And I definitely have been on those projects where needs assumptions were made on behalf of the user and thousands or millions of dollars have been spent developing a tech or product that don't actually meet the root of the need. And what Sevilla brings is the user voice to every step of the way and it's really encouraging leaders through this relationship we're building of trust and respect to say, hey, you know, the person who should be driving a lot of these strategies is actually this person right here who's going to be impacted by the system most. And there's a story that comes to mind is actually recently we're working with the state to look into COVID messaging. So we were looking into testing. How do we get people tested? How do we get them the information they need making sure that they understand who should be getting tested, when, how often. And we were working with them for a while and they gave us some messaging that they wanted to test out. And we went through with a lot of these user groups that we would normally speak to and the messaging we tweaked it here, we tweaked it there. And eventually we ended up reaching out to a broader network because one of the things that Sevilla really has to do is recruit from communities outside of the ones that you would normally interact with. And we do that actually by partnering with community organizations that have like deep roots in Hispanic communities or Arab communities. And after talking to one of these community organizations, they told us that one of the biggest trigger words for a lot of communities of immigrants is the word trace. And trace was a part of this messaging that we were using. And so all of a sudden we have this messaging that's now isolating this entire group of marginalized individuals. And had we not gone and really talked to them, we wouldn't have been able to understand what should we be doing and how are we going to be able to bring that voice to this design process and communicate with them so that they understand this information. And it's coming from a trusted source. I mean, there's countless stories of that with Sevilla, but I really think that that's the main goal of our work. Really helpful stories there. You mentioned two things that I want to pick up on. One is user voice. The other is actually talent recruitment and building out a team to do this work. And Monet, I'm going to kick it over to you on both these points because I remember when you joined our new practice lab, you were like, am I a public interest technologist? Do I have the skills to do it? And your skills as a journalist really played out in such a powerful way in that user research and in the work you did to get close to those stories and understand them. So I just wondered if you could share a little bit about that journey for you and also what it was like to move into that work. I was nervous as ever in the beginning. Very nervous in terms of understanding and exactly what I could bring to the table. I mean unemployment insurance, the actual unemployment insurance report was my first story as a journalist back in the day. And so to then come in to play and work with the team that I had, which was great to work with. And understanding my role was, you know, you talk about bringing in the voices, but also understanding the nuance within those voices and within the communities. I'm a child of the South, so also understanding the nuance of the South and how the South works, understanding the nuance within Black communities and understanding like just all of those things. And then as we were pulling back, I keep going back to those layers as we were pulling back those layers as a writer and storyteller, making sure that in our research we knew the through line and that we still kept the thread going through each story we were weaving together. And making sure that as we were putting each layer on and as we were pulling out these stories that we captured the nuance of the stories that we had within our pieces and just the other thing is just learning from others. And that's the beauty of when you're coming together as a team within this world and trying to make a difference through technologies. And, you know, many newsrooms I would say have already been doing this, Matt brought up the elections if we can understand where somebody has voted. But if you look at what newsrooms are doing in terms of just bringing in like who are the people who are out there voting, a lot of those knowledge is that a lot of those expertise are coming into newsrooms. And I think for organizations like within this field, it's beauty. There's a beauty in the diversity of the voices that come in to make a difference in the work that we do. Thank you for that. It really goes to show me too that there's no one size fits all in terms of who a public interest technology is and how this this is practiced. And I think that's really worth. So thank you for your good work. Okay, let's shift and go a layer deeper here. Since the start of the pandemic, more than 50 million people have lost work. And unemployment rates have reached levels not seen since the Great Depression. And we know that the economic devastation experience has not been colorblind. Neither are the financial support systems that are meant to buoy workers. And so we are seeing disproportionate impacts across the board with Black and Latinx communities, not just with UI, but in terms of food insecurity, the food insecurity rate of food insecurity among Black households has doubled since the start of the pandemic. So with this in mind, we know and I think everyone on the webinar tonight knows that there are many opportunities for technology to be helpful in increasing access to critical benefits. At the same time, I think part of what we want to unpack here is that the role of technology and government related work is increasingly and rightfully being scrutinized and critiqued. Technology is a tool, right? It's not a solution unto itself. And so my question for you all that I'd love to unpack next is really around how you see the role of data design and technology in this work and how we harness that responsibly. So moving forward for specifically what sort of opportunities do you see to center racial equity and your practice of public interest technology? And what are the dangers or the risks if we don't do that? Matt, I'm going to start with you and we'll see where we go. Well, thank you for the question. And, you know, the dangers, the risk, what's at stake if we don't do that? If any of us think about our tax burdens and our economic vitality, the economic vitality of the communities that we live and work in, does anyone really think that we are better off by having millions of people who are in need of public assistance but locked out of the system? In fact, what that does is it makes it contracts the GDP in a given region. It makes us poorer people. It puts greater pressure on our overall public budgets because there's a group of people who could be making more cost efficient personal financial choices. It is a whole lot cheaper, for example, for someone to get preventative health care than to show about the emergency room. We've heard this story a million times. Where technology has the potential to really help close the gap is to close, it is to help us realize the potential profit, if you will, from these type of socialized cost. That is, we're all going to pay one way or another. There's an old saying, you can take the window, you can take the stairs, but you're going to go. If we can help by defining the coloring in the blank spaces, by defining where is the revenue circle for connecting the dots more effectively, then we're all going to be better off. I'll go back to the electoral context. We work on a lot of elections and this is just a useful metaphor. It is much easier to find people who are already registered voters and turn them out to vote than it is to find people who are not registered voters. Our systems are built to find the people who have already signaled engagement, and so as a space where the public interest technology community could go quite a long way is help us all find the spaces where people are not signaling interest. I have no doubt that Facebook knows more about me than I know about myself, but there are millions of other people just like me, or people who are not just like me, I should say, people who are not stably employed, people who do not have the benefit of a home that they've lived in for an extended period of time, or don't have the type of consistent employment record. It would be a huge service for that level of technological observation to be able to help us point to where the people who aren't otherwise connected. Now that gets creepy real quick, and how you govern those instincts is a real, there's a moral dilemma here that I don't pretend to have all those solutions survived. I do think it's incumbent upon us to at least try. Lastly, I would say in this space, innovation matters, but the type of innovation that Embryne talked about, where you really take the 360 view of the participants, there's expertise all around us, and you come up with a brand new idea. That's how you start to color in those blank spaces. That's how you start to realize the revenue recapture from shifting socialized cost to other parts of the system, and returning profitability. It's a bit of a kind of murky space, but it requires some exploration. I think that this team can do it. Thanks, Matt. Your point around innovation, but through responsible governance, in particular, governance of data is a big one. We might want to come back to that. Let's just put a pin in that. Monet, what I remember also when you were doing the work on the unpacking and equities and unemployment insurance this summer is that many individuals shared with you their struggles with access to broadband, and I think there's something really critical to unpack there, because in many instances, our first instinct when we see a website that is overwhelmed by claims and breaks down, or we see people struggling to get access to timely information about the status of their application, our first instinct often is to build a new technological solution, and in many ways that could unintentionally end up hardwiring discriminatory practices inherent within a system that might be harder to access from someone who is in a low broadband community or does not have access to reliable internet services. I wonder if you could share a little bit with us about some of the things that were coming forth in your research and in your work about the spectrum of responsible technology interventions from high tech to low tech interventions and how you would think about that. Well, the one thing I remember when we were working on a story separate from the report, realizing that this system is broken by design and that you can fix websites, you can add staff to deal with the volume of calls, but at the end of the day, the system itself is still broken by design when you look at the work search requirements, when you look at African-Americans being the ones who spend, who have the longest duration of being on unemployment, those things start to come into play, and then you throw in the digital divide where Black and Latinx families are less likely to have Wi-Fi or a computer at home, and if they are accessing these websites, they're accessing them via their mobile phones, and most of those sites are not mobile friendly. So it gets down to we can fix websites and we can fix, we can bring in more folks, but if you're not dealing with the actual systems and the external factors that impact that system, you're not really making much change. You're just putting more band-aids on to a problem and you're not actually dealing with the damage that's been done. I would also, I think about one of the folks we talked to, her name was Loretta, excuse me, I had to remember, and Loretta had a phone, she had a smartphone, but she didn't know how to navigate the website and navigate through the barriers of the actual application and had to rely on a friend to help her through that process. Then she spends about a month trying to access the unemployment office in Wisconsin via her phone, calling in, she gets someone in and it's like, you know, she has to talk to this person who then takes her to this person, so there's all these barriers that she's facing, they finally get her in the system and she finds out that because of a prior time, she has to pay punitive fees because of a prior time that she had applied and they said that she was overpaid. So it's just so many other barriers that come into play that it's not just about websites and call centers and people being able to fill out these applications at this time. There are so many other things that come into play which is what we hope that our report would bear out. Yes, and what you're sharing is reminding me of one of our new practice lab team mantras, which is to design for the 10%. So design for the 10% of folks that are hardest to reach, right? It matters who you're designing for, absolutely. And the work that you did through this report too has been really foundational for our new practice lab in terms of laying the groundwork for a new racial equity framework that we are baking into our design sprint methodology to help us identify and unpack and provide recommendations to rectify inequality in policies and programs moving forward. You have to understand the origins of policies, who they were designed to serve, and the way in which racism has emerged either by design or through implementation over time within these systems. And we feel like that's really crucial to designing an equitable safety net that would actually serve the needs of all Americans. Ambreen, I would love to turn to you next. When I was first connecting with your team about the work you're doing on unemployment insurance in Michigan, I was really struck, speaking of historical context, although it's recent history, really struck by the ways in which you were sort of encountering some of the emotional scars of a recent sort of challenge with implementation of a system in Michigan that was used to determine unemployment eligibility and track case files that flagged nearly 40,000 workers for fraud in which I think 93% were inaccurate. And it led to a series of lawsuits and a series of new decisions that are being made at the state level to really think about appropriate systems moving forward for system governance. But in your user research, I think some of these themes around fraud and some of these myths or ideas around fraud were perpetuating themselves, not just with unemployment insurance, but with other systems as well. I wondered if you could share about some of what you're hearing and also your thoughts on what we incentivize for matters. Are we incentivizing for minimizing fraud or are we incentivizing for maximizing access for those who need it? Yeah, absolutely. And I mean, building upon what Monet said as well, this system is, I mean, if you look at what technology is, it's just codifying rules in a different format, right? It's taking administrative policy and it's translating it. And what this administrative policy is at its core right now, it's fraud prevention. And so much of the work that we've been looking into comes down to how many people can we make sure aren't hurting the system, not how many people can we help through the system. And we've seen that in our work with DHS, we've seen that in our work across the board. And users understand that. And users know that at the end of the day, like if you're caught for fraud, what Monet was just saying about the penalties, I was just talking to someone today who was telling me a story about how her god sister went through this whole process. And I think she answered something wrong. And if you answer something wrong in your recertification of unemployment, you could be flagged for fraud. And then you have to pay back 1.5 times the amount that you were given retroactively for all of the weeks that you were given payment. And oftentimes, the amount of fraud that's being flagged is an actual fraud. It's people answering the wrong question. It's employers not filling out the right the reason for something. One of the stories we heard is on the application, you have to state why you were separated from your work, right? And the reason that the employee gave was I was laid off due to COVID and due to COVID because of a shutdown. And the reason the employer gave was laid off because of a shutdown. But simply because the word COVID wasn't in there, this person had to wait weeks, weeks to get their money. And they were flagged as fraudulent. And this is happening all the time. And being flagged for fraud isn't just the tax of not having enough money to feed your kids or not having enough money to pay your rent and having to borrow money or take a second job. It's the most important as well. It's pulled over and over again, biased and that's supposed to be taken care of you that we don't believe you. We don't think you're worthy of this money. And we hear this every day from our users. And it's this deep, deep fear of being caught for something. And it's very discouraging. And exactly like Matt said, people will just give up, they'll give up on trying to work with the system and do whatever they can to work around it. We heard a story about a woman who was flagged for fraud because she was owed a ton of back pay because an ID verification that didn't go through. While she was waiting, she had to borrow money for rent. And then when that ran out, she had to go get a job at a factory nearby. That was actually producing medical products. While she was at this factory, she noticed that they weren't really being very safe in the factory. She noticed that people were looking like they were getting kind of sick. They weren't cleaning the factory very often. People were being a little bit sketchy. And she was like, I don't know if I can risk my life for this. I have asthma. And if I get COVID, that's it. I don't know what I'm going to do. And now she doesn't have health care either because that was something that was provided by her job. So now this woman has to make a decision between her life and the amount of money she'll need to pay her rent. And she eventually quit this. And two weeks later, this factory shut down because there was a massive COVID outbreak. And these are the decisions that our claimants are having to make every single day. And it's because someone behind the desk is saying, I just don't believe you. Yeah. Well, we have 10 minutes left on the clock. I'm going to invite our audience members to share any questions that you'd like to share with our panelists today. And we'll see those come in. And in the meantime, while we wait for those, I want to ask each panelist to give one call to action for those participating this evening this afternoon on pertaining to how they might go deeper in practicing racial equity in their practice of public interest technology. So just one call to action, whether it's something that you've, that's been really influential for you and your journey in this work, or something you've come across recently or you want to invite the audience into. Simone, can I start with you? Practice empathy. I think in this work, we must practice empathy. And therefore, when you empathize for others, you will then be able to acknowledge the variety of things that are happening. You'll be able to acknowledge, as we have in our report, that systemic racism is real. And that when you look at it through the lens of UI, which you talked about the history of it, 1935 New Deal plan that excluded 65% of its workforce, which were Black workers, agriculture and domestic. I'd also say, know your history too, because that's where the power comes. Thank you, Monet. How about you, Matt? Yeah, that's a great point, Monet. I will extend that strategic request. Make assumptions that are in the best interest of those most in need and building power that they have agency for themselves. The more someone who is in a vulnerable position has to rely on the whims of someone who's behind the desk, the more exposed they are and the more likely they are to give up. If we built tools and systems, or we built tools that push power in, decisioning into the hands of the affected individual, and suddenly, they're more resilient, they're able to weather and navigate the system a lot more effectively. Thank you. I'm green. I would say that what needs to be done as much as possible is bringing a strong and undeniable influence of the user voice on the decision-making process throughout every element of what you're creating, what you're designing. It's understanding that the user is actually the expert. It's not the person with the most data. It's not the person with the most research as the user. It's their need. At the end of the day, you are creating something that they will be using. Understand that those are the people who should be at the forefront of every decision and allow them to lift their own voices and be heard in these rooms full of experts and executives and designers. Thank you. I had a question come in around, I think it was a comment made earlier about technology being a tool, not a solution and how that shows up. I think this is an interesting point because it's quite clear that certainly in unemployment insurance and that system that our technology systems are woefully underfunded and inadequate. Certainly it's a part of the solution, but I wonder if any of you would like to expand a little bit on that. What is the danger potentially of thinking of technology as the solution? Since we talked about the digital divide that everyone is connected, not everyone is utilizing all of the technologies that are out there. I think that's one of the biggest assumptions that are made that everyone is connected. I mentioned Loretta. She has just her smartphone, but she has no tablet, no computer, no access to the internet. She's relying on mobile access and she's relying on a friend who has a tablet to help her to navigate these websites, so we can't assume that everyone is connected. How does this show up for you in your work, particularly on the advocacy realm? I think that one of the areas where we see people most in need of technology as a tool, not as a solution, is in how they understand where they are in the system. I've talked about this a little bit earlier, but the lack of visibility into the decision process means that it's not because your smartphone didn't cinch an update, it's because the technology doesn't necessarily exist or the bureaucratic decision maker can automatically note what's going wrong, what's going right, and that you are therefore informed and able to solve the problem. That would be an example of where if what we solve for is the beneficiary, the potential beneficiary having greater insight into the process of using technology, then technology winds up being the tool that is the solution. That makes sense. Thank you. We have a question coming around the relevance of the learning from UI for other systems, other public benefits systems, other social systems. Marina, I might look to you first on this one, especially because the work you're doing around cross-enrollment in Michigan might be really interesting for folks on this call. How is what you're learning through UI maybe enhancing some of the other work Seville has done on health and human services and vice versa? Sure. I think the thing to recognize is all of these systems, all of these institutions are connected in some way or another. Sometimes they're right down the street, oftentimes the same people are overseeing these or at least in communication. What I think is really important is leveraging the learnings from one project, one organization, one team, and bringing it over into these different areas as well. What we've learned in our work with Department of Health and Human Services is simple solutions are often the most important. A lot of that is what we're bringing into our UI work as well. I think that goes back to the previous question of how are we using technology as a tool? Technology is in a solution. It is just a tool. One of the ways we can use it as a tool is to bring these very simple solutions into some of these systems that have been overly complicated. It's using simple language. It's making sure it's clear and it's readable at a seventh grade reading level. It's using icons and white space. It's all of these very simple things that we can learn from research of one application and bring over to research of another application. I think that the more these larger organizations are speaking to one another, the more consistently we can help fix all of them. So in just a couple of minutes we have left, I want to pick up on this question of what you see as next steps for this work and how students by participating doing this kind of work. Does anyone have any ideas for the students in the work? I mean I've got some crazy radical stuff I can throw at you and students are impressionable. So there you go. Let's start with this. Let's have every State Department of Revenue actually itemize by EIN the wage rates based on gender of their employees. To the extent those states also track race data, particularly on the voter file side and that's in a lot of voting rights states, you can pretty quickly match up who's seeing disparate income, disparate levels of displacement. States are massive data sets that could be exploited to the benefit of working people and no one's asking the question or pulling the data in that way. There's so many different ways that we can help solve these problems and I'm bringing that type of out of the box creative rigor to it would be getting changing. Anyone else want to chime in on that? I would say if you want to make a big difference in technology, look at the underlying policy. Understand all of the systems that it is working with. Understand every piece that's connected because you can't change you can't change one without looking at everything else and understanding the relationship between each of these things is going to be key in actually creating change and making the impact that you want to make and I would just oh please go ahead my and I was only going to add just to piggyback off for what I'm being said is that and if you want to share those stories bring in the diverse voices who can help you share those stories who can help you to understand that nuance and understand sort of like that through line in your work be it if it's through video audio journey mapping whatever that is to make that change. Thank you. There was another question that came in that we probably don't have as much time to dig in on but it's around whether this moment of COVID which we feel is making as more accountable or really emphasizing accountability around technology for those who are using it whether that's like something that's going to stick around or go away and I will say that I think that the common the collective shared experience of trying to be more reliant upon certain technological tools and services does seem like a window of opportunity to have these conversations and does seem to be opening up some really deep kind of robust analysis around where we go from here in terms of designing for the 10%. So thank you everyone and now you're welcome to join our celebration hour. Take care. Thank you.