I first want to thank everyone for coming today to the Disparity Seminar organized by the McLean Center and the Urban Health Initiative along with the Global Health Initiative and the RWJ program on finding answers. We have a group of distinguished visitors and guests from the University of Abaddon in Nigeria, and we're so glad to welcome you. Welcome to Chicago. Our speaker today will be Dr. Stacy Lindau who's in the Department of Obstetrics and Gynecology, the Department of Medicine, McLean Center, and in the Urban Health Initiative. Dr. Lindau is the principal investigator of the Southside Health and Vitality Studies and directs the population-based biosocial and health technology research using a community-engaged minimally invasive approach. Dr. Lindau also directs the Chicago Corps on biomarkers in population-based health and aging research. She does many other things leading the population-based integrated biology research corps at the University of Chicago's Institute for Translational Medicine.  It's really a tremendous pleasure. I know how busy you can hear how busy Stacy is in her many activities. Stacy will speak today on asset-based approaches to urban health. Please join me in welcoming Stacy. Thank you. Good afternoon. Thank you, Mark, for inviting me to speak. It's an honor and really I'm speaking on behalf of a whole lot of people, many of whom are staring at my back, unfortunately, and many of whom are in this room who work together on the South Side Health and Vitality Studies. I want to compliment the McLean Center and your work. There's an excellent website that has all of the talks in this lecture series beautifully produced. Kudos to the cameraman. I'm sure nobody's acknowledged you before, right? Which I really appreciate because for personal reasons I've not been able to participate as much as I would have liked in this conference series this year and it's been very helpful for me to be able to follow those talks online and I encourage those of you who haven't seen them to see them. I want to mention, for example, Rob Samson's work, Kathleen Cagney's work, Marge Cohen. These are all people whose work has been an inspiration to me in my own work. These are all people who've spoken in this conference over the last year and it's just an incredible series and I want to thank you for doing it. Thank Eric Whitaker. I know the Urban Health Initiative and Bumi Olapati and the Global Health Initiative and Marshall Chin's group also have supported this excellent series. I want to start by telling a story and it's kind of a microcosm of what I hope the South Side Health and Vitality Studies will be. The story starts with a conversation actually between myself and Dorian Miller, one of my partners in crime. Dorian had talked with Reverend Hutt. This is Reverend Hutt. I don't think she's here today. This is Reverend Hutt, who's one of the Reverend chaplains at the Comer Children's Hospital. I'm a gynecologist so I don't spend a lot of time there but Dorian told me one day shortly after she'd come back to the University of Chicago, having been here as a student, a medical student, she told me that Reverend Hutt had observed hungry parents at the bedside of their children in Comer Hospital and that the Reverend had observed a parent being hungry enough to ask the resident whether the resident could get her a sandwich or some food. And essentially, of course, it's a little bit of a game of telephone but the response was no, I don't have a way of doing that. And it raised the question about hunger in our children's hospital, hunger among parents trying to care for their sick children and make important decisions about their sick children while being hungry. And it just so happened that a couple days later I'd been invited by Dr. Monica Vella to give a talk to the incoming medical students during their summer immersion course about the physician's responsibility to the poor and underserved. So at the end of my talk, because this conversation with Dorian had been really bothering me, I said to the students, you know, if you want to take your energy and do something good, why don't you help us solve this problem? Reverend Hyde over at the Children's Hospital knows that there are parents who are hungry at their bedside and she needs a way to help provide them food with dignity. So a couple students, and here they are here, including from left to right if you can see them, Dan Thorngren, Robert Stern, Kevin Heaton, Avram Kaplan, these were first year medical students who sat in the lecture hall, heard the story and decided they were going to do something about it. Rob Stern called me up or emailed me and said, I want to do something to help solve this problem. What can I do? And we connected him up with Reverend Hyde and over time using some of the institutional resources from the Urban Health Initiative that had allowed me to hire some research staff like Jennifer Makalarski, who was just at that time hadn't even completed her PhD, got together and very quickly solved this problem. They didn't solve it alone. Part of the question was where do we get food and how can a rich institution like ours not be able to provide a meal for a hungry parent? There just wasn't a way to do it.  One of the trustees from the Medical Center was serving on the advisory board to the Urban Health Initiative. And she was also on the board at the Greater Chicago Food Depository and had connected us up to a really great research team at that organization. So we called them up and said, hey, we have this problem. We feel embarrassed to call and ask you to provide food to us given our riches, but maybe it's an opportunity for you to expand your services. And they were thrilled with the idea and through the sheer will of the medical students working with Reverend Hutt, working with the researchers here, working with a strong community-based organization, we've set up a food pantry. I should really say they've set up a food pantry, a closet in the chaplain's space that provides food to hungry parents in the children's hospital. And so since February 2010, when this pantry came into being, we distributed 3,000 pounds of food purchased for $1,058 or $1.75 per bag, distributed to, as I understand, more than 300, more than 450 families, some of whom were grateful enough that they continued to work with the program to help us distribute our food or load up the pantry. And nurses and the chaplains and others, residents have noted how the food, the gift of food and the appreciation and the trust for parents has really helped engage parents more in their child's care and has improved interactions between the nursing staff and the parents. So why do I tell you this story? This isn't a product necessarily of research. This is the product of a need and putting our heads together to solve a really terrible problem but with a pretty simple solution. And then we hang research around it to figure out how much does it cost? How do we give out? How do we keep this sustainable and how do we replicate it elsewhere? So this to me, the story of the Comer Food Pantry is really the ideal for what I hope the South Side Health and Vitality Studies will be. I came to the South Side Health and Vitality Studies because Eric Whitaker called me up and said, I have a dream. And so when someone like Eric Whitaker says I have a dream, someone like me responds, I've been primarily a sexuality researcher but working in the population health arena. And this was an opportunity to take what I learned about population health and how to study it and translate it to something I care a lot about which is the communities that we serve by virtue of working here at the University of Chicago. So the objectives of my talk today are first to help you understand the aims and scope of the South Side Health and Vitality Studies to become familiar with the asset-based community-engaged research approach. And hopefully most importantly I'd like to spark new ideas in this group about how your work and skills can benefit and be stimulated by the local community. And just a note on that, I've had a few notable experiences here with faculty outside the medical school who have said, you know, I'm interested in working with you because you are giving me an opportunity to see that my work has meaning in the human context. One was a chemist, Rustamiz Magaloff.  He was motivated to work with us because he thought maybe these tubes he was designing could be a benefit to the health of the local population. Another person is someone named Charlie Catlett. He's a computationist. He's a senior person at Argonne National Laboratories who's motivated to work with us because, again, we're providing an outlet for him to feel that his work is an opportunity of working at an institution like the University of Chicago that's situated on the south side of Chicago. I just start by way of transparency to disclose the funding sources. We are fortunate to have first and foremost really seed funding from the University of Chicago through the Urban Health Initiative. Without that, it would have been a very, very big risk for me to kind of stop or add on to what I was doing to take on this work and that's true for many of the other people who've been directly supported by the Urban Health Initiative. Many others have not been directly supported and we keep writing grants to bring support on more and more for the people who are involved. We've had individual philanthropy. We've had major foundation funding. We have corporate funding from PepsiCo an interesting story that I'm happy to answer questions about if people want to know more. And we have funding from the National Institutes of Health. This is two years worth of... we started two years ago when the funding for this project reflects the tremendous diversity of people involved and this asset-based community-engaged approach which I think is quite novel and has really gotten the attention of funders including ranging from PepsiCo to Chicago Community Trust to the National Institutes of Health. This will be hard for you to see if you're in the back but this is our organizational chart and I think what I just want you to walk away knowing is that the South Side Health and Vitality Studies is within Dorian Miller Center for Community Health and Vitality and the Center for Community Health and Vitality is sitting within the Urban Health Initiative led by Dr. Eric Whitaker both of whom are in the room today and have been tremendous champions not only champions of the South Side Health and Vitality Studies but really my entree into the community. My touch with community has been as a practicing physician here. I started my practice at the Friend Family Health Center. I worked in student care. Really the kinds of relationships that I need in order to do research in the community have been forged through the tremendous amount of street credibility and courage and friendships that Eric and Dorian bring to this work. It would be simply we would there's no way we would be where we were if that weren't the case. And we also have a broad variety of community partners working with us. This just highlights the logos of the community partners working on something called asset mapping. I'll tell you about that. We have the Greater Auburn Gresham Development Corporation Kenzie and Kenzie Communications New Ways Learning Health Literacy Organization Quad Communities Development Corporation Washington Park Consortium These organizations have been at the table with us now for a good two years heavily kept together on the project by Daniel Johnson in Pediatrics Colleen Grogan from SSA who helped to lead this asset mapping project. And again you won't be able to see a lot here but this is just one example of one of our several working groups for the studies. Southside Health and Vitality Studies is organized by working groups working on various aspects. This is the community engagement and ethics and human subjects working group members. So there are about 25 individuals here some from university many from community and a really diverse range of community members Merkin Company a pharmaceutical company big international company to you know youth and family services or Chicago State University to individuals who are interested in what we're doing. The studies are open to anyone who wants to be involved we welcome you and it can be coming once in a while to our monthly meetings or it can be real active involvement. The mission of the studies is very closely aligned with the mission of the Urban Health Initiative that is to create and share knowledge with our community to produce and sustain excellent health and vitality on Chicago Southside and beyond. What do we mean by health? We adopt a World Health Organization definition of health which is not just the absence of disease or infirmity but health more broadly and vitality refers to the health at the community level the health of our community organizations and the ability of our communities to continue to develop in a positive way. The vision is that the Southside of Chicago is a model of exemplary Urban Health by 2025 there's not a lot of time there's a lot of work to be done but that's the vision that keeps us moving there's certainly a lot of opportunity for improvement. So what are the research aims? The reason we're called the studies plural is that we are many interrelated efforts and I'm going to try to walk you through those the Comer food pantry I think of as one of the Southside health and vitality studies but that's why we're plural it's a little bit awkward and therefore the studies has its own specific aims these are the broad aims of the Southside health and vitality studies so in a low income urban area with a fragmented heterogeneous healthcare infrastructure one what is the duration and quality of assets I'm sorry what is the distribution and quality of assets in the region and are these being optimized to promote health and manage disease it's a very simple question before we start building new systems and new programs what do we have to work with what are the assets out there what are all the assets available to us secondly what is the status of population health and how does it change in relation to designed and natural experiments what's a designed experiment providing food at the Comer food pantry there's a designed experiment what's the impact of that experiment on health of people and then thirdly because technology is an area of high interest to the community we're starting to explore how technology services cell phones internet other sorts of services can be optimized for health healthcare and social connectedness these aims have evolved over time we didn't just start with these aims they've come out of close conversation and collaboration with many many community members and frankly they've also been shaped in part by what we think is fundable and I think we have to be honest about that without funding we won't be able to do the work at all each of the aims indicates which organization is funding the work and there are some organizations we're in process with in terms of pursuing funding this is one example of the breadth of our collaboration these are university faculty and senior research staff we're actively involved in aspects of the studies there are many many others but the dean for example is quite interested to see how many different departments and divisions across the institution are working on the project and we'd love to see your name up there too I want to just take a moment to put the work we're doing in context of what's going on with health reform so one question we have as we work with the urban health initiative is what's our health system on the south side of Chicago and while that hasn't been my primary focus with the urban health initiative Kim Hobson has been working on the work started by Laura Dirks and working with many many healthcare organizations on the south side of Chicago in the auspices of something called the south side healthcare collaborative the south side healthcare collaborative I understand includes now more than 30 federally qualified health center 34 federally qualified health centers located on the south side of Chicago in all of the major hospitals including the University of Chicago Medical Center so probably close to 40 partners now inside that organization which was seated here at the University of Chicago but which has now evolved into what will become its own 501C3 organization and one of the FQHC leaders that south side healthcare collaborative as far as I know is really the first serious attempt to get a handle on what is the healthcare system on the south side of Chicago frankly we've never had a system we had a whole bunch of players not talking to each other and we had a population whose health wasn't I don't think up to par for how many players we had the south side healthcare collaborative as far as we can tell is really unique as we go around the country talking to other academics and other policy leaders about healthcare reform it seems to us that having a collaborative that's talking about building a health system in an urban area like ours that involves so many different players I think the FQHCs are distributed across eight different independent corporations and of course the hospitals are also owned independently is a really unique entity and that's what I mean by a heterogeneous environment if we can figure out how to build an integrated smooth efficient system of healthcare on the south side of Chicago given the heterogeneous environment of health players we've solved a problem that will be salient for lots of other urban environments where we don't have a Kaiser Permanente or a Mayo clinic that's taking care of 90% of the health of the population so the fact that we are diverse and that we are complex is an opportunity for us rather than a problem so we're thinking about whether there's a health system and how do we create a health system and others are thinking about this too the Institute of Medicine and the World Health Organization are talking about the health system as an intersectoral health system it's a word that when we put it on the screen at our last meeting with our Board of Trustees they all said we have no idea what that even means the point is that leading world organizations are saying that the health system goes beyond those providing medical care it requires and here specifically it comprises the government public health agencies and various partners including communities, the clinical care delivery system like the University of Chicago Medical Center, employers in business, the mass media and academe who's not part of the health system is what I want to know and this definition is one that was published in a 2010 Institute of Medicine report funded by the Robert Wood Johnson Foundation and one that's being echoed very in using the exact same terminology by the World Health Organization. Okay so let's adopt that definition of the health system has anyone ever described anywhere all the components of the intersectoral health system and how they're working together has it ever been empirically evaluated or studied the answer is no but where are we starting to do this here on the south side of Chicago mapping every single built asset in the primary service area of the University of Chicago which includes 34 community areas of the entire 77 community areas of Chicago and trying to understand if everybody's in the health system well then what's everybody's role in the health system that's one part of what we're doing now in talking about the health systems we have a definition of intersectoral and we have a definition of the health system also coming from the Institute of Medicine in describing and using the term the health system the committee seeks to reinstate the proper evidence based understanding of health is not merely the result of medical or clinical care but the result of the sum of what we do as a society to create the conditions in which people can be healthy and this is why we are called the south side health and vitality studies we need vital communities we need a vital region urban area so that people can be healthy so these are we're working with these concepts and in a proposal we just wrote to NIH aim one was to empirically describe for the first time the intersectoral health system I get that's our definition let's take it seriously and see what it really means so this is a figure from the proposal we just submitted and because we're so nascent I can really only talk about the proposals we submitted less so the papers we've published or the problems we've fully solved that's why I started with the food pantry we actually did something there but to give you those aims those research aims in another format I want you to start here first of all what are the assets in the community what is the availability of assets are people aware of these assets are people using the assets why or why not and we're starting to get a little bit of handle on that already second of all how are the assets in our community related to people's perceived and evaluated health what we mean by evaluated health this is where my experience collecting biological measures using minimally invasive methods and population research is helpful we ask people what they think their health is but we can also measure from a few drops of blood from the tip of the finger somebody's hemoglobin a1c level to determine whether or not they have diabetes or prediabetes somebody's blood count to see if they're anemic and a whole variety of other factors that help us give an objective evaluated measure of health and over time I imagine I'm hoping that our colleagues at the University of Chicago have more measures so we can get a more robust assessment of population health without having to bring people into the clinical setting for really expensive evaluation thirdly you know I told you people we have learned from community members that there's a real high interest in digital communication technology high uptake a sense that we're on the wrong side of the digital divide and the data that are available would corroborate that and a feeling that if only we had better access to internet higher speed internet network phones that we could really make up a lot of ground and some of the disparities in health in the south side so to what degree is digital communication technology related to people's awareness and use of the assets in our community which places in the community are offering people free wifi or terminals where they can get their work done if they don't have access to these things at home and then finally our question is does digital communication technology help drive help through more use of our community assets or does digital communication technology potentially substitute for needing local assets places you can go in order for people to be healthy can people diagnose themselves by getting on the internet or figure out how to treat some first aid problems with internet access and therefore don't need to go to an emergency department or don't need to go to a Walgreens clinic maybe in some cases they do we want to understand where we can substitute and be more efficient and where digital communication technology drives health giving you I hope some insight to what we mean by asset based community engaged research but here's just a little bit more information to share with you a paper that we recently published in the journal preventive medicine Michelle Obama as many of you know preceded Eric Whitaker here at the medical center and as I understand it was active in recruiting him as she went on to take her position as first lady she was involved with something called the asset based community development institute at Northwestern she's a faculty member there and that work the work of that institute has influenced our approach to community engaged research I really appreciate this quote from her we can't do well serving these communities if we the givers are the only ones that are half full and if everybody we're serving is half empty there are assets and gifts out there in the communities and our job is good servants and good leaders is not just being humble but it's having the ability to recognize those gifts and others and help them put those gifts into action communities are filled with assets that we need to better recognize and mobilize if we're really going to make a difference now I'd like to say that I heard her say this or I saw this quote before we went full steam down the path of an asset based approach but in fact it was only about maybe six months ago that I came across this quote from her it's not a surprise because Leif was in the back of the room worked with Michelle Obama and it was Leif who really introduced me and to the others with the South Side Health and Vitality Studies to the idea of asset based community development so building on the work of John Kretsman and John McKnight at the Northwestern and soon I've actually never met them personally and I'd like to and I think we should maybe invite them to come here sometime we've developed this graphic schematic of an asset based approach for our research and what this schematic says is that our work begins and never ends with respect to community engagement and relationship building that turns the wheel we start with identifying community priorities we define the aims for the South Side Health and Vitality Studies both by what talents and skills we had among the university researchers who came to the table and by the areas of highest interest to community members did we just survey people once know every time we interact in our research meetings with community members we ask are we on to the right thing are we asking the right questions are the data we're showing you salient to the work you're doing and if not what do we need to do differently we just came from a meeting like that today once we've identified priorities we start to identify the assets in the community we have under the leadership as I mentioned before of Daniel Johnson and Colleen Grogan and many others working on the asset census project have been literally deploying teams of people walking up and down every single street in now 11 communities of 34 on the South Side of Chicago to identify every single asset we're not mapping private homes but every business establishment any public place or even private place where people could potentially go to get services once we know where all the assets are we can then begin to leverage those assets towards our goal of exemplary health in this urban area by 2025 we're building assets too I think the South Side Health Care Collaborative is an example of an asset that we're building at the same time as we're measuring and identifying assets we leverage these assets in part to help us conduct research in part to inform our day-to-day activities and importantly to generate new knowledge when we generate new knowledge that has to be fed back to the community for priority setting so hopefully over time our priorities change because we're checking some things off the list okay we solved that problem now the next one can come to the top I'm just going to share some pictures with you these are of our large interactions with community this was our first retreat in December 2008 the Little Black Pearl I think we had about 50 or 60 people there more university than community people our second retreat was on October 2009 the DeSable Museum at this retreat we had closer to 100 people and closer to a 50-50 distribution it was between that first retreat and the second retreat December 2009 where we had six communities mapped with asset data we brought the data back to the retreat people broke out into small groups and had computer screens to work with people told us what they liked, what else they needed and people said we need to know what services are being offered in all these places not just good enough to know there's a church I need to know is there day care there can I get diabetes screening there what kinds of services are available so between October 2009 and our next retreat we wrote several grants to get that service mapping off the ground this is critical this is what community-engaged part of asset-based community-engaged research is it's bringing the ideas to the table and the table includes community and university people working together hearing people's ideas and then executing on them and that's critical for building trust and then this is our recent retreat December 2010 at the South Shore Cultural Center Rebecca Holbrook who's up here has been actively involved for a long time and is involved with our ethics and human subjects working group I think that might be Shane with New Pathways Learning who looks like he has a headache he's also been with us he's a veteran with us since the beginning we had how many people 200 and about 60% were community members representing as far as we know at least 30 or 40 different community organizations it was a tremendous growth in our participation we had the Illinois Commissioner for the Department of Health with us as well as Chicago's Commissioner for the Department of Health there we had these amazing graphic artists who summarized everything that happened during the course of the day graphically on these giant white boards that evolved they just appeared during the day and bringing the humanities to the work that we're doing I think is a really interesting opportunity because the work we're doing is very humanistic and sometimes it's much better summed up in something like this than in a paper in preventive medicine so what assets do we have to work with to achieve this vision of healthiest urban area by 2025 this is one of the earliest maps that we generated when we were thinking about how to build the Southside Health and Vitality Studies we contracted with an organization called the Metro Chicago Information Center we paid them money to take 2000 census data and impute it so that it was relevant for 2008-2009 and they helped us generate maps to summarize the socio-demographic and health conditions in the region of interest so what you see here is a black foundry showing in fact one day I just gerrymandered the border so Chicago Long is now part of the Southside of Chicago but at this point in time they weren't I also included I added the near Southside to the Southside of Chicago too so right here is the only 32 community areas it was that was what the heck I was like you know what these two communities need to be in the Southside and we just put them in there so nobody objected I was transparent nobody said they should be so in any case this chart shows you the gradations in income and this is communities of the percent households in each community with an annual income less than $25,000 that's not a lot of income what does it cost an undergrad a year to go to the University of Chicago anyone know $56,000 okay it was in the newspaper sounds good to me that's not a lot of money less than $25,000 a year the darkest blue shaded areas mean that 48-65% households are living at less than $25,000 in 2008 this is Hyde Park here's the University of Chicago we are surrounded by a horse shoe or some other metaphor of communities living in extreme poverty now this is a call to action it wasn't a terrible surprise unfortunately but it's not exactly an asset-based way of looking at things so if we only think about the south side of Chicago by the prevalence of poverty and if I put up the map of diabetes deaths or cardiovascular disease deaths or infant mortality it would look really very much the same as this map okay to the best of our ability to tell an accurate view of things the data are quite limited do you know we haven't had any population health estimates of people living on the south side of Chicago since 2004 and those data were really based on course measures of health so if a community organization is working on HIV AIDS or working on diabetes how do they write a grant justifying their mission we don't even have current data about the prevalence of disease Dr. Miller is giving a talk in or did you already in Hyde Park she gave a talk in Hyde Park on diabetes and so we said okay well can we get some maps together for Dorian about the prevalence of diabetes in Hyde Park so she has some salient data no we had diabetes deaths in Hyde Park with a lot of variance around the estimates from 2004 based on not great data but we didn't have diabetes prevalence or diabetes risk we don't have these data for the south side of Chicago and we really desperately need them to do this work this is I'm sorry this is a terrible chart that people like Marshall Chin and others in the room who have mentored me as a research will you know I really slapped my hand after the talk for putting it up here but it's really important and so I just want to make a couple points about it this summarizes socio-demographic and health characteristics using those old 2004 data in our study region first row national data Chicago south side the south side of Chicago has current estimates somewhere around 870,000 people best data we have available looks like somewhere between a 4 and 7% population loss since the 2000 census will know better in June or July when those data become available so 870,000 people these are the 11 communities where we've done asset mapping mapping all the built assets in the community let's just look at a couple comparisons here average African American population 12.3% national 33.6% Chicago 71.4% south side and many of our communities are almost 100% Anglewood 98.8% Washington Park 98.7% Auburn Gresham 98.6% African American the south side of Chicago has one of the largest contiguous African American populations in the United States which again is an opportunity it puts a great deal of I want to say pressure on us to learn as much as we can about the health of African American population because we have such a large population here that both we are serving and can tell us something about health of African American urban populations in other cities around the country Hispanic percent Hispanic most think of more the west side of Chicago is being where the Hispanic population is concentrated national 12.5% Chicago 27.3% south side a little bit higher than national but we have a few community areas with large Hispanic populations Chicago on east side and south Chicago east side 77.6% Hispanic with a strong federally qualified health center the leader of which is heading that south side health care collaborative I mentioned before and is actively involved in this asset mapping project that we've been doing I want you to take a quick look at percent living at less than two times the federal poverty level national 31.4% at 49.5% look at how many communities are living look at this Washington park 74.2% living this community is on our border seven people come here and work do we realize 74% three quarters of the population are living at less than two times the federal poverty level what does that mean for our responsibility when we come to work and do our research here the medical center a couple things on the death side these are the health indicators from those 2004 Chicago public health data if you're interested you can get them from the website yourself death rates Chicago as a city overall has lower annual death rates per 10k population than nationally let's look at some of the death rates here our benchmark is 73 123 in grand crossing 200 in wood lawn where by the way 65% of the population is between the ages of 35 and 49 cancer rates they all follow the same pattern there's nothing here that really jumps out as not making sense but it's also a call to action so these are some of the people we call to action and these are the people who are doing the asset mapping project in the first year of July 2009 we had teams of university students working with teams of students hired from the community managed by the University of Chicago survey lab which has been a phenomenal partner in this work these were the first people to go out and start documenting every built asset in the community they had PDA phones the phones were pre-programmed with purchased lists of asset data we paid good money for those lists done in brad street they make a lot of money from selling these lists 40% on average of the assets we found were not on the most recent purchase done in brad street list and several, I think it was also close to 40% 30 to 40% of the things on their list we didn't find so guess what we now have the criterion standard asset data for this region we have to figure out how to sell it so we can keep this project going but we should be competing with done in brad street yes there's something like that Far I'm going to help you negotiate that so and the students I mean we had beautiful essays from the students on our blog who came to the meeting and said I've been living in these communities all my life I had no idea how much there was there so it was really exciting and within six weeks of them completing their data collection all of these data were on a brand new website or an expanded actually website that urban health initiative already started called southsidehealth.org and available to the community 10 months later people had this website to look at and could make use of the data themselves in 2010 we expanded the asset mapping to include several communities Auburn Gresham actually came to our group and said hey we hear you're doing this and we want to be part of this asset mapping and we've got a bunch of high school students working for an after schools matters program who need a good summer activity could they do the work we thought ooh high school students and I think to some degree community members and business owners were a little bit even more sympathetic to the high school students and we're welcoming of them and again we heard the same thing I learned about things in my community I'd never seen before and this was just part of the team that was doing some of the mapping last summer so these are the blue lines shows you the communities where we have now built asset census data 11 of 34 communities really in two summers of mapping we've got to get to all 34 communities and we're in the meantime trying to figure out how to keep these data updated we have updated six of these communities and we're going to show you some data from that here are the six community pilot from the first summer these are some of the data that we collected this is the number of built assets per 1,000 population so for example Hyde Park 28 assets per 1,000 population Kenwood 9 is that because Kenwood is a impoverished area we've been talking about this meeting before so there are a lot of large single family homes in Kenwood and we can see that even in Kenwood which most of us regard as a wealthy community 40% living at less than two times federal poverty level but still among the lower rates of poverty as compared to some of our other communities and this is a map that is an example of what we can generate now for the communities that have been mapped here's a map of select diabetes related assets in Grand Boulevard you go on to southsidehealth.org you can generate this map for yourself in two seconds it's really easy and it's available to everybody but here for example we mapped health clinics, grocery stores and the rare fitness facility you can't do this on Yelp or Google you can only map a certain place you can't map places by disease or by need so we think we have something really special here it takes a lot of human effort to get to it we got to figure out how to make it efficient, sustainable and always up to date imagine though I just want to go back for one second imagine if we intersected the asset mapping data with the electronic medical records and you hit diabetes as a diagnosis an epic the wizard behind epic somehow queries this database and sees the patients address and the patients diagnosis and spits this out at the end of the visit and the patient leaves not just with a diagnosis but a place where they can improve their wellness despite their diagnosis or maybe even turn the course of their disease around so we're working on that idea a lot of people are involved in that I don't think it's certainly very doable it's a matter of resources but would be quite exciting here shows you the additional communities where we have started to do the service mapping we're trying to get it under the skin of the organizations to understand what they're offering and we're very much in process with that Washington Park which has fewer total number of assets but should be commended because they're close to 36% of all of their assets having its service data in the system and here this just shows that we have a get on the map campaign working with SurveyLab and our community partners to get all the asset data the service data for every place into the SouthsideHealth.org system this is a picture of SouthsideHealth.org we also recently bought, I think this is really exciting can you believe nobody owned Dondeasta.org Whereis.org I'm the proud owner of Dondeasta this is how I'm going to get rich and it's all going to go back into SouthsideHealth.org but we have now translated the website into Spanish especially for the population on Eastside which has been working very hard on this project it has a large primary Spanish speaking population we also bought ChicagoHealth.org can you believe no one owned that one so once we expand to the whole city we're all set quickly this is a map of the asset data showing gains and losses over one year this generated a lot of discussion in our last large group meeting for the studies we meet every month, second Wednesday of the month 11 to 12.30 everybody's welcome and we have been now having the great experience of being able to share back the data and get people's reaction to it so now you've had a chance to look at this for a minute these are one year gains losses of community assets across all sectors in the six communities that have been mapped twice these data were not nobody has these data they've never been available I guess you could buy the Don and Brad Street data and do it but most organizations don't have access to that so all sectors if you just looked at all sectors it would look like things stayed the same we had 1976 assets then we have 1976 now the economy's gone to hell but it doesn't seem like anything's changed we're all good and okay when we put these data up several community members said you're finally with a University of Chicago stamp we know but now we can take these data with the University of Chicago logo on it and maybe the policy makers will pay a little bit more attention so just to give you some examples Jennifer McElarski by hand weighted the area the square area of these bars to the number of services so the fatter ones have more service you know financial insurance real estate and legal had 235 so it's really fat versus industrial where we lost two or three industrial sites so it's really skinny so there's a lot of fluctuation over one year and what does this mean for the health of our population I'm interested in this 50 public service organizations police fire postal government a little more than 10% so five gone in six communities we need to understand where the five police stations gone those could have real implications for the health of our population how do people find places and services for health so this is this is really the critical issue once we were classifying all these assets we're finding all the assets we're describing all the assets and we know where they all are maybe we know what their value is we know which ones are good and bad the next question is how do people get to these assets is it true that the reason why people don't get access to health care is because we don't have enough appointment slots to get preventive care or the reason why people don't get a shelter a homeless shelter at night on a freezing cold night because we don't have enough slots or spaces or beds in our homeless shelters that's the going theory and in some places that is true there's over demand for high quality services we still have a sense though that there probably is some underutilization or there's some mismatch we don't have people's demand for high quality services available so we made this argument to the national institutes of health and they awarded us a grant to try to figure this thing out and this is called the Chicago health and aging services exchange we asked for a million dollars we got a hundred thousand dollars but we got the stamp of approval of NIH so we can design the thing in our minds and then we have to get more resources to build it there are a broad variety of organizations involved with this some of them are represented here and across the community we have Mitch Katz who's the immediate past commissioner of public health for the city of San Francisco just took over LA County as part of our team John Skinner who's a phenomenal health economist from Dartmouth as part of our team and it's a really exciting project if you want to get involved what we're trying to figure out is how do we make it so that a person almost like buying an airline ticket can get on the website enter their special needs for the services they need not only that, but we're interested in tracking the activity in this marketplace how many people demanded HIV aid services how many people demanded food support services what was the geographic distribution of that demand how does it relate to the location of food distribution sites in our community how does it change over time which places have the most demand with the longest waiting list of people who want to get in because if I'm a volunteer I want to go work at that clinic or if I'm a philanthropist I want to send my money there because the long waiting lists are probably a decent indicator assuming there's more than one option of quality we don't know that for sure, but these are the kinds of questions we want to be asking and as quickly as possible we want to have a web-based solution where people in need of services can get matched services and we can start to bring some transparency of the health and human services system so we can see how people are using or not using what's available and then finally we have the functioning technology so I mean I'm a gynecologist I am extremely humbled by all of the work we're doing on a given day I have to understand how aromatase inhibitors affect the anatomy of a woman's vulva and how people are using their cell phones to find food support in the city of Chicago it is overwhelming but it's so exciting to have an opportunity to really make an impact so we have the capability, everyone in this room to learn, whatever it is you need to learn substantively to help solve these big problems how can we use technology to achieve our vision, why am I interested in this because community members have said we think technology is part of the solution okay, so let's go figure out technology together here are some estimates from a pilot study we did on the south side using Urban Health Initiative resources initially with some additional support from other small foundations these give us estimates probability sample of our population digital communication technology used in the population Jen Makularski did all the data analysis and deserves a great deal of credit for this work it just came out in the Journal of Urban Health if you're interested in the paper it's online now so these data speak for themselves I think what's interesting I've had a lot of interest in older adult health we have a national tendency to look at things stratified by age we see relatively high overall digital communication technology used on the south side of Chicago comparable to national estimates for the African American population which actually says I think that given the degree of poverty on the south side of Chicago that there's a real hunger for the technology people are figuring out a way to get access and make use of technology even though they can't afford a lot of other stuff older adults are at an extreme disadvantage older adults living in our urban area are really disconnected and that's a problem because we know how important social connectedness is for healthy aging and wellness as people get older and it's a place where we can really make an impact look at the proportions of older adults who are text messaging using internet at home have ever used internet a lot of older adults have cell phones almost 70 percent and Monica peak made the point that there's a relatively easy way to make up this gap just show people how to use the text messaging feature on their phone and people catch on pretty quickly so we're working with several of the aging advocacy organizations on the south side and have a real interest in how technology can be used to decrease social isolation and increase connection to the health care system and I am wrapping up I've been talking for a long time I'm really thirsty I was just telling Mark I gave a talk yesterday for Mark to the medical students and I wrote him an email after saying it does not suit me well so here I am talking nonstop for 45 minutes but this is where we're hoping to go this was one of the figures from the the R01 proposal that we just submitted to NIH and I want to acknowledge there are several people in this room who really helped to make this proposal possible including Eric Whitaker and Marshall Chin all of the people sitting back here who literally worked Christmas New Year's January 6th deadline going Dorian Miller George Smith Leif helped us out raise your hand if you helped raise your hand if you were working for us on Christmas but really a tremendous collaborative effort in many many community organizations writing in support of this proposal what we want to do now is leverage this amazing unique asset data we have and start a population health everybody in the communities we've mapped to understand whether whether the assets in the community and which assets in the community relate to individual health and how do those changes in time does loss of five police stations in this region move with health trajectories in the population or does it not matter do we not need police stations for health but we really need our fitness centers it's extremely practical questions that we're trying to ask these that will be involved that were proposed to be involved in this study are shaded here, these are the ones where we've done asset mapping and a few additional to give us a bigger contiguous area who agreed to work with us toward this proposal what's nice about this geographic region is that while we have many communities that are predominantly African American we have three that have those three communities that have larger Hispanic populations which just expands the relevance of our work for other communities we have clinical sites that are using southsidehealth.org in their lobbies to help connect people to care so it gives us something of an opportunity to follow those people and the impact of those activities on health and we have several communities that are considered Chicago smart communities communities that have received funding from the federal government to promote community literacy around technology so again we're leveraging that opportunity to see whether those smart communities are healthier over time than the ones that don't get that intervention so finally how your work and skills can benefit and be stimulated by the local community alright so just make me feel good how many of you sitting here have had some idea about how your work might relate to what we're doing or feel somewhat inspired about how your work might be might help advance the aims and vision of the southside health vitality studies anyone? oh good thank you so I told you the story about the Comer food pantry which I just think I hope you walk away with that because that's the kind of thing it's a simple but devastating problem with a simple and very feel good solution here's another example of how the data we've been collecting the work we've been doing has benefited a community one of our closest neighbors the wood lawn community as many of you may know the wood lawn community is interested in competing for or building something like the Harlem children's zone they call it the wood lawn children's promise community they've been working on this for a couple of years we went to the health and wellness committee meaning we were invited we were part of their community engagement strategy in fact it was so interesting to hear the community organization talk about how their challenges in engaging the community to help them with their work in this case we as university people were the community they were trying to engage so here we went to the community health and wellness committee we're talking about kids and where do they get their health care so we anticipated that might be of interest so we went to our asset mapping data to query where are all the places for kids to get health care in the community of wood lawn well turned out these were all the places that had anything to do with health including curves of wood lawn doesn't cater to kids the only things we could find were labra beta which is for pretty sick kids a tertiary care center for kids and Dr. Chao Chen who does never answer his phone at least all the times I've called but if it's providing child care it's very hard to get an appointment so we said to them look we thought this might be of interest to you these are the data we just collected with people from your community about wood lawn there's no where in wood lawn for kids to get health care so where are the kids getting their health care so they said let's go to the schools and see what they know and they had health forms from the schools one school worked with us gave us 100 health forms that said the address of the doctor we got back and asked Todd Schuble who we have a little bit of money to pay in our social sciences division to map those places out so this is the whole not just the city of Chicago but goes down to Indiana and up to Wisconsin and the big circles are where the most kids are getting care and the little circles are only a few kids in wood lawn are getting their care all over the city of Chicago including Indiana and north of the city so this was really interesting information for them they think about building a health system for kids in wood lawn this is the community of people they need to talk to because these are the people who have been providing care for their kids so it's just another example of how the infrastructure we're building can be used not only to advance the big aims but to help quickly solve smaller questions so with that I'd be happy to take some questions if there's time I want to encourage you if I haven't already to get involved we all have our own individual fiefdoms of research and that's good but for those of you who are looking for an outlet to take your talent and skills and the things you're discovering and make them really salient and beneficial to the local community that sustains us frankly and our jobs then please get involved with us all of our meetings are open we won't kidnap you and make you come back forever just come to one and see how you like it or pop in whenever you can contact Natalie Watson that raise your hand if you'd like to join one of our working groups Lisa she's still here Lisa oh she's a lovely person she's not here right now but contact Lisa if you want to receive our monthly e-newsletter check us out on our website everybody welcome and needed so I'll end there thank you very much for listening to me talk for so long yes I'm happy to take a couple questions so you see how far are you planning to take some of the outcomes measures that you're looking at I mentioned at the very beginning getting a few drops of blood and perhaps checking what the hemoglobin A1C is for people do you have a vision of having a map in which you can tell what the mean hemoglobin A1C is in a neighborhood and can tell whether somebody's intervention for increasing exercise or decreasing high sugar content drinks in a community would change the average mean hemoglobin for anyone seeing a community if that's true that sounds really wonderful I don't think there's anything like that anywhere on the planet our idea thank you for asking that question I don't know if the people in the back would hear but it was really what's the scope of ambition around the kinds of population health data we would collect the scope of ambition is limitless high on ambition and we'll have to get there incrementally according to funding so we have to be strategic I told us that there are some high priority areas diabetes, obesity fitness is really important safe outdoor space really important to communities cardiovascular disease kind of fits in with that community members use the phrase metabolic syndrome and say what are you doing about it I mean there's a lot of concern there there's concern about cancer and cancer risk there's concern about things like teen pregnancy and wellness and aging part of what we have to do is align community disease priorities with our best areas of expertise to start because those are the places where we have the most credibility for a funder we'd have to ask for several million dollars really to get this thing off and once we get started then I really believe just based on the response of the asset data the data will be so compelling that we will find a way to grow and be sustainable yes the ambition is 34 community areas probabilistic samples so that we can make community by community comparisons the data collection would be a home based survey unless somebody didn't want to be interviewed at home face to face self report biological measures environmental data like NHANES but NHANES is a serial cross section and I think at this point in an ideal world we would have both serial cross section and a longitudinal cohort for different reasons I think we're going to start trying to build a longitudinal cohort so the conversation around obtaining blood for any purpose for many people evokes feelings of mistrust you know rooted in Tuskegee and other unethical ways in which we've conducted research in the past and I say we being part of the research community it's interesting how the dialogue has shift we've had some training sessions where community members could come and see how this methodology works for obtaining blood we had a major we have a regular conversation about what's on the table what's not at the retreat we had a couple breakout sessions simply around the collection of biological measures and for the most part people said is we understand why you want to collect these data my organization could use these kinds of data to advance its mission it's not whether to do it it's how you do it it's got to be done right and there is no room for error in terms of protection of confidentiality respect for individual integrity and making the data getting the data back to people in a way that they can use it to improve their health and so I think the conversation has largely shifted from why or why not to how are you going to do it Stacy it's remarkable work it's dizzying how many components you have to it I'd love to hear your thoughts at two or three years in about the role that you think the University of Chicago is probably the biggest built asset the biggest the richest institution on the south side would have ideally as this thing goes forward and I would it be do you think these are the right instruments the urban health initiative SS you know that thing and so on or do you are there other ideas that have come up about how the University of Chicago could serve the community better while continuing to serve its its goals of being a world-class research institution thank you I mean I think there are a couple ways to answer that question in my ideal world I would lead this thing for only a few more years and then would hand it off to a strong community lead organization that would be that would take this this project over a generation of time and we would be the technical partners we would be the ones with the technical skills to execute the data collection help ensure the validity and reliability of the findings but that it would be a community led endeavor that would be my ideal maybe somewhere between you know where I stand now and that moment there's a junior faculty member maybe an African-American MD PhD top of his or her game who we can recruit to the University of Chicago with this incredible opportunity and let them grow their career one stage there's a real need to develop people minority people in academic medicine as leaders and then hand it off to the community so and that's my honest feeling about it with respect to my feeling about the urban health initiative I will say that you know you know in 11 years of working here there was no opportunity like this until the urban health initiative came with Eric and his leadership and frankly at the way I see the history it was a big part Michelle Obama and her vision and Jim Madera and his vision and you know there are parts of the vision that were very business driven and I really believe bigger parts of the vision that were about it's just not right what's going on here and we can do a lot better we do believe that and whether it was or wasn't that that's what it is now the University of Chicago has a very core focus on it's product it's business product which is world class scholarship and so what we're doing here has to be done as world class scholarship or it will not be sustainable within the institution it's part of my challenge has been and it has been to sell this what we're doing to the board of trustees to the dean to the provost to the president as a tremendous research and development opportunity the 21st century research development opportunity for the University of Chicago and the at the same time bringing it to the community as a tremendous research and development opportunity for each one of those important organizations that helps sustain the region it's tricky it's challenging it's incredible incredible career opportunity to be able to figure help figure these challenges out with the other incredible people working on it but I you know the University of Chicago has a tremendous responsibility and I think it it's tricky to fulfill it's social mission at the same time as it fills it's business mission let's take one more question and that's all going to be on tape on the website can we edit that part out it's all true oh my god I can just see it now is there one more pressing final question for Dr. Lindo if not why don't you all maybe he was going to compliment me thank you


You quickly find that it falls apart. So the other thing that's big these days is chatbots, right? I think you see a lot of chatbots, a lot of frameworks, a lot of things with them. But there is a difference between what we do, which we call agents or assistants, and chatbots. And for the particular case that we've chosen to solve, here's the difference. So imagine you're busy excited, you're trying to get a meeting together. And if you were to use a chatbot, you want to say something like, hey, it's getting a meeting for us next week, right? And what a chatbot will say is, well, what day would you like me to organize that meeting? So if you try this with Siri, it will do exactly this. Then you say, well, maybe Monday or Tuesday. And then, okay, really in a quicker. And it can't decide, right? You have to give it very specific instructions. So you say Monday, and then it'll say, well, what time? And at this point, you're like, I just want you to get the meeting together, right? And that's the difference. When a real agent or a real assistant would do for you, you just take it off your hands, right? Take that ambiguous instruction of schedule a meeting next week, sometime next week. Figure out what's good, right? Confirm it, put it on your calendar, and send an invite to make sure that everything's done. Yeah. And that's the real difference between chatbots and agents that we see. Okay, so let me just quickly introduce Evie. She's an intelligent assistant, schedules your meetings, and how does she do this? She reads and writes emails, interacts like a real person, right? So it's like a CEO's assistant, follows up, books, meeting rooms, learns your preferences. Exactly what you expect from a real human assistant, right? That's really the bar that we're trying to hit. And did you know only 45% of your work day is spent doing your job, right? A lot of it is spent on admin tasks, and this is really the broader picture that we're trying to address and starting with scheduling meetings, yeah? And if you're a mid-level manager in a big corporation, easily six weeks a year, it's spent scheduling meetings, and that's what we're getting back for you, right? Is it a quick video, I think? No, let's get that, okay. So let's talk about speaking human now, right? So this is Evie, this is her assistant, it reads and writes, doesn't sound too difficult, we do it every day, right? But let's take a quick look at why it's such a hard engineering problem, lunch. I mean, think about the word lunch, you and I have a shared experience of what that means, right? A shared common understanding of what the word lunch means. It's a meeting, right? We typically involve a face-to-face meeting, you can't have a lunch call really, I mean, to extend more of a call, there's an actual face-to-face lunch. It's got a certain time range, right? Typically between 11.30 to maybe, and then the latest time you would end your lunch is maybe about 2.30, right? Anything later than that, you probably do a coffee instead. And it needs a venue, right? And there's typically food involved. So from that one word that you and I share, there's actually a whole deep level of understanding that the machine doesn't know about, right? And the machine needs to be taught about. And this is just one word. Imagine all the words that we use in the context of scheduling. So that's the first reason why it's hard. Then there's the whole syntax. Sorry, got it the wrong way. Syntax versus semantics. So 3 at 5, I have to run at 6. So again, it comes to the meaning of the words today. You've got 3 at 5, I have to run at 6, right? And implicitly, that means I want to end the meeting at 6. Then a very similar sentence. I'm busy at 5, but I'm available at 6. And to the machine, and if you throw this into something like word2vec, which is one of the vector space learning models, these are going to look very, very similar to a machine. Because in tactically, if you look at the structure of the sentence, they're very, very similar. But the meanings are almost completely reversed because of the particular meanings of the words themselves. So these are some of the things that make things difficult. A lot of neural nets and big data learning approaches focus on structure. And if the structures are similar, those are things that kind of tend to match, right? But in this case, the specific word, the detail really, really matters. Here's another one. That's me, Thursday or Friday afternoon words. Really simple sentence, right? But if you really break it down, there's a whole lot of processing that you do very automatically. Friday afternoon, pretty straightforward, right? But you know what, try to decide that afternoon applies to Thursday as well, right? And so you're going to have to multiply that afternoon now between Thursday and Friday. And then the other thing is, you got to treat Thursday or Friday afternoon as one element and apply that to the word works, right? And these are things that machines don't know. And these are things that you need to teach them or put in place a structure that you can use in order to get the right result, right? But ultimately, it's about people. One last example. Let's do coffee at Holland Village. Let's say Starbucks at Yapun, right? So first of all, relatively easy to pick out coffee, HV, Starbucks, Yapun, right? But again, you have a bit of this interesting context that's happening, right? In the context of Singapore, it probably means Holland Village. But someone in San Francisco would probably mean something else altogether, right? And then on top of that, you then need to graph the fact that Starbucks and Yapun are very specific places within a region called Holland Village, right? So it's not just the aim to look at the words in isolation, but you need to have this whole model of the world behind you in order to get the right meaning from the text, right? So you have to look a lot deeper. So that's some of the reasons why it's hard. And let's say you do get the complete understanding of the sentence, right? Let's say I'm in Hong Kong next week. Fairly straightforward, it's a fact, right? This person is saying that he will be in Hong Kong over this period of time, start time and end time. Fairly straightforward. But in the context of scheduling a meeting, you don't really know, this isn't like saying, no, I'm not free, or yes, I'm free, right? It's kind of an orthogonal kind of statement, just a statement of a fact. And you need to actually bring in some context around what is it that you're trying to do before you can decide what it is. And this, again, makes it difficult to apply very standard, simplistic mapping model to text, right? So where's the meeting? If the meeting I'm trying to organize is actually in Hong Kong, then next week's a good time. But if it's in Singapore, then maybe it's not a good time, right? Or was I trying to organize a call in which case I don't care, except I just have to adjust for the time zone. And did I have any other personalization parameters? And only then can I choose from a model that kind of sets a decision, right? Whether I prefer the time next week, I find another time, change the meeting to a call, yeah? So, literally, once you have the surface level understanding, you still need to go deeper, bringing the context around the task that you're trying to do, and actually reason from it to get to kind of the right set of possible decisions, yeah? Yeah, and so, you know, if you're ever curious about natural language and what a natural language pipeline looks like, this is a very high-level view of it. It starts with a whole bunch of preprocessing. So from an email, you take an email, you got to figure out, like, what is the actual text that comes out of it versus the five previous emails that were quoted. You've got to separate that part of it, then you have to take that and you have to go and find the signature and extract that because there's some interesting things you need to do with the signature versus the actual text. But then you get the text, right? So you do all that preprocessing, you get your text, and now you put it through this pipeline and you say, well, the first thing you need to do is to tokenize, right? So fairly standard, well-understood task, great things, and the machine just sees this whole line of text, right? You need to break it down into individual words, right? Not as easy as you might think, as you might expect. Then we tag it, parts of speech. Is this a verb, is this a noun, is it preposition, is it past tense, present tense? Is this a plural form of a base word? Then we enrich it with an oncology. That's really a fancy way of taking the word lunch and adding all the information we know about lunch into the pipeline. And then, so now we have these atomized words, now we start building it up again in order to get some meaning out of it, right? And so we take a semantic chakra, the meaning of the word. We talk about the Thursday and Friday afternoon, grouping those things together, figuring out Starbucks and Yakun and Holland Village, and then we start building that into a craft and then, since life is information, rout it to the right tasks, is this a response to an existing meeting on Friday schedule, is this a new meeting? Is someone starting a new email thread but asking me to reschedule another meeting? Do another round of contextual enrichment and then outcomes, structured language representation, yeah? So this is really the core pipeline for the natural language processing. And at a very high level, it's probably consistent with most of the NLP processing pipelines out there. And that's just understanding the language, right? So it turns out to do scheduling well like a real assistant, there's a whole bunch of other things you need to do, right? You actually need to figure out what a good slot is.  We talked a little bit about the location modeling, Google Office, again, like HB, very, very context specific. In this case, it's personal, right? Or you could say Starbucks, and Starbucks to you means this Starbucks, and Starbucks to someone else means another Starbucks. Dynamic workflows. So we've seen meetings that were organized and started out as a lunch, and then someone had rescheduled, turned into coffee, a lot of companies that. How about we meet in another time and it just ends up in a call. So if you're an engineer, you know that you usually want to build for a spec, right? Say, well, my spec says A, B, C, D, E, and I'm going to build so it does A, B, C, D, E. But in the real world stuff is a lot more fluid, right? So another engineering challenge is how do you support that level of fluidity at scale without kind of just getting yourself tied up or not? And of course, at the end, you also need to output something, right? Not only does E.B. read emails, she also needs to write emails, and to write emails, you need to be able to talk like a real person. And a lot of it is actually being responsive to what just happened before or what happened right at the start. And so that when you then take an action, you're able to explain why you did something. And that's another pretty important thing that is critical for machines to be able to talk like people, right? I mean, we respond so naturally to events that we build that into the words we use in such a dynamic manner that it's hard for machines, right? So, yeah. So these are all the fun challenges. And if you enjoy hard problems, come talk to me later, software engineers and specialist data science experts. And now it's question and answer time. Because we have a broad audience. It's really open. What can I tell you guys about? All right. So my question is, how is E.B.'s understanding of language different from, say, plug into something that, I don't know, like Siri, right? Yeah. How is it different? How is it different? I think with Siri and with Trapbox in general, they tend to deal with one line at a time. And they really focus on, at the moment, more information, right? Show me the spot spot, or what's the time, or the actions that will be treated to voice actions, which is, do this. Play this song, turn on my music, and set my alarm. And these are very, I think it's not so much the understanding of language, as much as it's the scope of the task that they do, right? And with Siri, it's nice that if it doesn't understand and doesn't know what you want to do, it just throws you back to a website. That's the default, the fallback. Is that it? I'll ask you a question. How does E.B. deal with typos, or algorithms? So in case you want to hear, the question was how does E.B. deal with typos, or colloquialism? So if you notice, Google has a pretty good spelling in everything, in everything, right? I mean, it's probabilistic in some ways. Colloquialisms are hard, because simply because the surface meaning of the word is kind of different. And that, there's really no way around to say about very specific things. Oh, no, no, no. I mean, I think other than E.B. to be able to handle typos, reasonable typos, right? I don't think you can do it in an isolated state, because whether something is a typo or not, it's very difficult to handle typos. It's also got language, it's an active subject. It's based on the content. So that's what we're doing. Okay. Alright, Chris. Did you meet your own NMP system, or did you go with something a little bit longer? Like with AI or something else? So we built our own on top of open source departments, right? So the two problems that are fairly well solved are speech tagging, tokenization, and there's no reason to reinvent the wheel on that. Those are actually machine learning models. You can train them on your own corpus if you want. They come to you trained model. But beyond that, we built our own stack, right? And there was, I mean, there's one of the things I didn't call out there is that one of the things we do is we don't know single lines of text or combination. We have to read an entire email that's addressed not only to us, but to multiple people. So there might be a conversation going, and at the end, it's literally a line that says, Evie, do this, right? Just set up the name. But in all that text, there was a conversation, there was context around when, where, and who that we need to extract a lot of information from. Given the level of complexity, it's like we have to build our own stack. I'm wondering how much it is. Right. Or whether you have to build it on your own and also when you have to build it on your own. So I think it depends very much on what you want to do with it. I mean, if you want to build a chatbot, there are a zillion different chatbot frameworks right now, I think. I'm not sure if WIT or AI has a full chatbot interface, but API.ai is just a Google equivalent. Certainly a lot of basic natural language processing is there for you. But, yeah, I mean, it depends. If you wanted to build something like Evie, I think that's something you have to build yourself. What for? That's a problem for us right now. I mean, it's a question of, we're building a, we're not trying to build something that only does that. So it's trying to build it in a general way as possible. So being able to detect, you just need to be back where they write back to you and say, no, you got it wrong. It's relatively straightforward, right? You use the same foundation of the engine that you have to understand what you're trying to do. But that's, you know, it's just a lot of work. Does anyone else have something that I miss? Can I ask you, do you see that there's a specific difference between chatbots and new slides, right? I wonder how do you address the fact that it's learning? How is your, how is Evie learning? Because chatbot, you know, there's a different way it learns, right? Is it different roughly around the same program? So I'll repeat the question. The question was, does Evie learn any differently from chatbots? Is that a fair paraphrase of the question? You know, with maybe one or two exceptions, I don't know how much actual learning happens in the way that you and I think about learning, right? Any machine learning experts here? No, so I can say what I can, I want to say. Yeah, I mean, I think some of the deep learning machine learning stuff really has been categorized more accurately and we'll strip away the marketing as applied statistics, right? A lot of times that's what it is. They learn certain things within the framework that you have set up for them. So if you phrase the problem in a particular way, if you frame the problem such as it's a machine learning problem, within those bounds it learns, right? More likely it just waits to get to match your data set. But I'm not aware of anything that really is able to integrate new concepts today to actually take an unknown situation and apply reasoning to it. That's, I think, beyond what the state of the art is today. So when you talk about learning, I think it needs to be, are you talking about getting better at picking out certain parts of the text versus getting, being able to handle unknown scenarios that it's not been programmed for and that last bit definitely doesn't exist anyway. So I've got a question from a marketing perspective. Yeah. So this is something that's relatively new, you know, hasn't quite existed before, at least in Singapore. Yeah. What was your approach to going to market and after that, because I know you guys been live last year, in the last year. Yeah. And then after that, capturing market share, what were your approaches? I think what's interesting, one of the things we learned is that this isn't a product for everyone.  So it turns out there's a fairly specific group of people who it appeals to. One of the earliest groups of users who really got into this, into EB, was people who used to have assistants. So they used to work in a big company and they used like a consulting company that had assistants, or at least a shared assistant. So they came out, they did a startup or they had a consulting firm. And then when they hear about this, they kick the tires, they schedule two or three test meetings. You get it and then like, I love it, right? And then they're off to the races. And it turns out like having an assistant takes some getting used to, right? You need to be able to instruct, give the right instructions within reason, right? Because even human assistants don't read your mind. So I think to answer, come back to your question around going to market, I think a lot of it has been finding the right groups of users. People who schedule a lot of meetings, recruiters, startups, resource-contrained startups, BD guys, salespeople. The other thing is virality, right? As EV schedules meetings with other people, they say, hey, what's this? And then they get curious and they can check it out. So it's still early days. There's one question about, we call it, the way EV learns, right? Does it learn from a one-on-one basis? Like, say, for example, it's actually worth talking with one particular person versus you have an entire organization which is actually using EV. Does it learn what you call phonetics or whatever the context of all the different people together? Or it's always a one-on-one basis? Or can it apply this learning from this person to a different person? Can you repeat the question? Yeah, actually, why don't you repeat the question? Because I'd like to hear it again. So what I'm saying is, does it have the capability to learn from different people in one organization and then apply that learning in multiple ways? I think there are things that you, I'd say you acquire information as the process of scheduling. And if you say, in the process of scheduling one meeting, you say, I'm going to be away next week in Hong Kong, whatever. That's something that EV will pick up and say, okay, this person's going to be in Hong Kong next week. Right? And we'll use that for future scheduling or other meetings, right? Certainly, that piece is, yeah. I think there's a lot of interesting work around figuring out, if you're sent an email and you ask to schedule a meeting, are there multiple organizations involved? What's the power dynamic? Is one a client, one a vendor? I think these are things that work in progress. There's a lot of subtlety, a lot of things that kind of happen immediately, but sorry, that happen naturally for humans. That for machines, they don't move. Probably doesn't quite address the question, but also because I'm not quite sure what, could you give me an example of what group learning versus individual learning would mean? So obviously, I come from more of a recruitment. It's a recruitment organization, we have like 100 recruiters continuously scheduling meetings all the time. Everyone has their own personal system who's basically scheduling all these meetings for them. Do you want to kind of share everything? Hong Kong could mean a room, Hong Kong could mean actual Hong Kong. So there are different contexts and there are different ways that these guys speak or there's standard terminology of these people who use all these different people. So does it understand from one person and has the capability to apply that understanding to a different person when he is scheduling his meeting? Yeah, so I think it depends very much on the link. So the link between the people, right? So if it understands Hong Kong is a meeting room within an organization, then if people within that organization speak about Hong Kong, then that's definitely, it's a probabilistic kind of thing you have candidates, right? Is this a meeting room? Is this a place? And then you have to figure out what the use other contextual clues to figure that out. Is Evee smart enough right now? So if I use a model that you should can she figure out a meeting? If I just say we're competing with me and Joe and get us a meeting room and she figure out a meeting room as well right now or do I need to specify a meeting room? No, she can pick a meeting room. If you're on a team plan. Yeah, if I'm on a team plan. So she knows the meeting rooms and she can just assign one to me. Yeah, so sure. So I made that caveat around first getting the meeting room integration set up with the organization for 10 years will be a choosing a room for you. Can you book her cell? I think that's fine. Not yet. Are you the process of identifying some other use cases? Yeah, I think we have the use cases I think we're waiting for the tech to catch up. The team based in Singapore right now we're about 8 people but we're looking into a problem. So are we just creating the team? Is it mostly that I say it is? Is it engineers or is it... Engineers. Mainly engineers. So it turns out like a lot of this is software engineering as opposed to data science or machine learning. And it's probably also I guess the phase of growth. We're building something from nothing. A lot of this infrastructure and plumbing and software engineering and then probably as we evolve and grow that mix will shift towards okay, let's look at the data as we find the models.


A manufacturer might be ready to try a new agency if working with their agency just gets hard. Working with an agency should not be stressful for a manufacturer. If they are, you might be outgrowing them. With my clients, our whole team is excited to work with them. We see ourselves as an extension of their team. And if we ever feel like we are being a drain on the clients, we make sure that we shift our processes and that we come in to support them fully. If you are in a position where leaving your agency meetings has you feeling drained or feel like you have twice as much work as you had before you walked into that meeting, it might be time for a switch. So one pain point that we frequently see with new customers is that they don't own their own data. You should own your website. You should own your Google Analytics. You should own your ads account. If you don't, this is a red flag and something that you should get addressed. Venvio's position is that any platform, any system, you own.    We don't want you staying with Venvio because we own too much of your data for you to move. We want you to stay with us because we produce great results. A few common things we see with manufacturers who become frustrated with their agency and are making a change is, first of all, lack of transparency into reporting. So we have a personal goal internally of if you can't measure it, you can't do it. Basically, that means that we need to have objective goals that we're aiming towards and if your agency isn't able to provide you clear and transparent data that indicates this was a success or this was not a success, not just vanity markers of the number of impressions that a specific campaign got but true leads that came from it. That's typically an indicator that something's going on in the background that could potentially not really be giving you the success that you were expecting. Another thing that we see is the owning of data. So if you don't own your ads account or what a website is developed for you but you don't have access to it and every little change has to be done through the agency or something like that, that's concerning because this is your work and you're putting a lot of work into it even though you're partnering with an agency to get that work done. So we would really recommend any opportunity you have to own everything. Your ads account, your website, you're frankly even down to like an individual design file that really needs to sit with you at the end of the day in an editable version and not with whatever agency you're working with. I think the gaps that you look out for is in your data. If you're working with another agency or even an internal resource and they can't show you the data behind what they're doing, they probably shouldn't be doing it. Back up, even if you have to stop the tactic for a little while, back up, make sure you can measure it, get that data in place and then move forward. It can't be a gut feel, it can't be, you know, this person said that it might be working or this person thought they saw good results in this region so it's probably working. Get the data in place, then move forward.