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


Good afternoon ladies and gentlemen and welcome to the February, 6th of February, not the 6th, it's the 3rd, isn't it? I'm already wishing the Friday away. Welcome to this non-farm payrolls webinar on Friday the 3rd of February with me, Michael Hueson and my colleague Colin Sizinski where we will take you through the non-farm payrolls number, the January non-farm payrolls report and certainly I think expectations are fairly high while I work through the risk warnings. I think expectations are high that we will get a fairly decent number as I think there's a number of factors at play with respect to our thinking on this and I know Colin and myself have basically laid out our thinking in our morning notes which can be found on the news and analysis section of the CMC Markets website. We post them there. We post them there every morning when we come in just to sort of give you an indication of our thoughts for the day. So just get rid of that risk warning. We're now ready to go. So basically looking at the last non-farm payrolls report of the Obama era, January and yes, I know Donald Trump became president on the 20th of January but I think we can pretty much call it the last Obama payrolls report and the big question is whether or not we're going to see a similar sort of bump in the official payrolls numbers that we saw in the ADP number and this is something that Colin and I would like to sort of kick around before the numbers. This is a spreadsheet of the ADP payrolls report and the non-farm payrolls report next to each other here and here. So obviously that's the January report earlier this week and then we had the December report in November but look how closely correlated they are to the non-farms on a month-to-month basis. There's never really that much of a difference between the two over the course of the last 12 months. Apart from here in July when there was a 38,000 difference and here in March when there was a 30,000 difference, for the past 12 months we haven't really seen more than a 30,000 difference between the non-farm payrolls report and the ADP report. Now obviously that's not to say that this one will be similar but based on historical precedence and I'm big on those sorts of things being a technical analyst, I look for patterns and the pattern here would appear to suggest that non-farm payrolls if the pattern is going to be repeated is going to be pretty close to the ADP number which is why I've gone fairly high at 210 from the consensus which is 180. Colin on the other hand doesn't appear to want to play things by half so he's gone all in, haven't you, mate? I have. I've gone to 225 which I actually split my calls between the revision and the headline number. I've gone for 225 for the headline number plus I'm thinking a 20,000 upward revision to September which is 245 or gives you pretty much in line with the ADP number. My thinking is that December was a little bit late and the reason I felt that was that we had this huge amount of pent-up hiring demand heading into the U.S. election. Some of that showed up in November where people stepped in, started hiring right away and then we had to drop off in December and I think what happened was that some jobs you can fill fairly rapidly, you can just go out and hire somebody within a couple of weeks and a certain number of jobs sometimes the hiring process will take six weeks to two months or two weeks of holidays in there and I suspect that some of the hirings that you might normally, had we not had Christmas, had it not been December and it had been in the summer say or in October or something you would have had two months of strong hirings but instead because of the holidays you went soft in December and I think you made that back in the first couple of weeks in January where people came back from the holidays ready to make their hiring decisions and I think that's what happened there. The other thing Michael and I have been kicking around this morning is the government hiring. It doesn't matter. There's about 4,000 jobs that turn over during an inauguration month and then of course Donald Trump came in and also announced a hiring freeze so government jobs could play a bit of a factor in this month. We were just debating before the call whether the 4,000 people quitting their jobs and being replaced by 4,000 other people doesn't really matter because it's not really net out to zero at the end and do you get this where people leave and maybe they show up in the numbers and then the next group of people get hired and they show up in the next month or how does that work? We're not totally sure. Again it's about 4,000 or 5,000 people that we're talking about anyways. Yeah so it's not a particularly high number but nonetheless it could constitute a skew one way or the other. So for me it's still a factor just not a particularly large one. Certainly not when you're talking in the context of say 30,000 jobs and then that's really what we're talking about in terms of differentials when we're talking about today's payrolls report. I think it's really interesting Michael you've put up manufacturing payrolls there because it's something that I was thinking about but forgot to mention in my notes do you want to speak to that? We have seen a particularly big pickup on the ISM manufacturing component earlier this week. There was a big jump in jobs there. The big question is will they get included in the January numbers or will they actually get rolled into the February because sometimes there isn't a decent correlation between the ISM and the actual official payrolls numbers. Sometimes there's a bit of a lag and what I was struck by actually was how there was such a big difference in terms of the Chicago PMI and the disappointing number that we saw there and the ISM manufacturing and the fairly decent number that we saw there. So certainly in terms of manufacturing I think that's going to be a fairly decent indicator as to whether or not we're going to get a good number. One other thing that I did notice on the ADP payrolls number was the fact that of all those jobs that were added 246,201 of them were services jobs. So that's which is quite big. So it does beg the question the quality of the jobs relative to the rising wages. One other thing, rig counts have risen quite substantially. Now obviously if rig counts have risen that means the jobs that man those rigs have basically come back online. So will that be? Those are good high paying jobs. So that could feed through into wages to the average early earnings. And I also wanted to note on the manufacturing with all the talk we've had lately about the Trump administration about currencies, trade, tariffs, walls, you name it. It's all going to focus in on the big thing they're going to be trying to goose for the next several months is manufacturing payrolls. So that's another thing. If that comes in at a low number again you'll probably hear some squawking out of the political side this morning. I think that's going to be an area that's going to be particular. I get a lot of focus from Trump in the next while. There's quite a few people now on my Twitter timeline going quite high on NFP guesses. So I've obviously set a trend. Now they're starting to kick in. We've set a trend, mate. We need to be careful about that. So basically the key numbers I'm looking for because I think the big question is for me is if this is a good number what effect will it have on the dollar? Given Peter Navarro's comments this week and given Donald Trump's comments recently it's quite apparent to me that the new administration does not want a stronger dollar and agreed Mr. Trump broke with convention by actually specifically saying that the strong dollar was killing us. I think that was the exact phraseology that he used. Presidents aren't normally in the habit of talking about the currency for the very simple reason it's just not the done thing whether it's weak or whether it's strong. So for me I think there's been a little bit of a sell-off in the dollar index as a result of that and certainly the dollar is actually very strong today. If we look at this currency ranking today for all the currencies against the dollar we can see that pretty much the biggest fall is the Swedish Krona then it's followed by the pound and we'll cover the pound in a minute I think there's a good chance we could test 124.20 later today that's a really really big level for me on the cable but again also 50 day average there? Yeah the 50 day moving average and obviously the previous peaks on the move higher so that's a big level and what's more important I think is if we look at the dollar index and we look at a graph and the reason I'm showing the Bloomberg chart this suggests to me it's a real key inflection point here around about this 100 level it's actually just support there it's actually just support there it's been below it it's now trying to get back above it so the big question for me I think is whether or not we can actually break below this 100 day moving average which is on the dollar index more importantly I talks in my weekly video about the importance of dollar Swiss and the chart there because there is a decent correlation between dollar Swiss and the dollar index if I look at this chart here I can show it to you look at this here again it's the big big support area through here also the the 200 day moving average it's broken below this 99.70 area it's now trying to get back above it and it's also in a significant downtrend so there is some evidence that potentially we're at a very very key level for the US dollar if we're to break lower we need to break below the 200 day moving average on the swissie and we also need to break below the 112 level on dollar yen and obviously held overnight we've made marginal new lows on the dollar yen at 112.10 around about that sort of level from 12.55 to the dollar swiss level here because we've been in a nice little downtrend in the dollar swiss we've been in a nice little downtrend in the dollar index and I'm just surprised at how well they match up the moving averages are quite different but certainly the trend gradient is actually quite something that's pretty steady and solid distribution one other thing I was going to mention there's no easy talking about the currency but he stopped putting pressure on the Fed to raise rates hasn't he, he's gone very quiet on that and I think we're back to looking at well I'm still at 2 and I think you're still at 1 I'm sort of one and a half I mean if you can call it that I think we'll definitely get 1 but we could get 2 I think it really depends on what other central banks do because ultimately I think Mark Carney was very dovish yesterday with respect to his inflation forecast and quite frankly I think he's wrong I think inflation is going to be much more of an issue as we head into 2017 than people currently think I get the impression he doesn't want to raise rates because if he raises rates he might as well admit he was wrong to cut them in August and I don't think he wants to do that let's quickly look at the key levels even though he was wrong everyone knows he was wrong the big big it's a real problem the big big levels, S&P 2290 it's held pretty much since we broke below it we've got a nice little gap there so between 2290 and 2295 you're going to get a fairly decent bit of resistance through there decent support around about 2270 I don't think we're going to break significantly above that over the course of the next few sessions because I just think if we come out of Trump and his cohorts this week I think people are a little bit nervous of protectionism and a trade war again here 20,000 level on the Dow big big level again will it be resistance on the way back up we gaped lower we may well have another go at it if we get a fairly decent number let's quickly look at the cable because I think this is important this 50 day moving average sorry 100 day moving average here and it's 12420 it's this level here, the blue line and also these peaks here that for me I think is key what's worrying me a little bit is we saw a key reversal day yesterday which could suggest that maybe we'll come back to 12250 but it's come so close after this key reversal week the other way suggests that we're probably going to get a bit of a bumpy ride on the pound against the dollar to move higher but we could actually get a very sharp correction lower first towards around around about 124 dollar again let's quickly look at that big big support as you can see around between 1205 and 12010 big resistance at 114 so I think that's really going to be the extent of it decent number, decent wage growth wage growth keep an eye on that I think that's the big one if anything in excess of 2.9 then I think you're going to go and see the dollar go for a bit of a tear and that's what we're expecting on the annualized number 0.3 this number here on the monthly number that's not so much of a that's not so much of a number I'm looking at the annualized number and I will now be quiet and we will digest the numbers as they come through so here we go 2.7 and a 175 upgrade unemployment is slightly higher 4.8 and average hourly earnings 2.5 that is a really weak number on the average hourly earnings so that is probably going to move the dollar the average hourly earnings number because Cable it's not really done anything let's have a look at this well that tells you all you need to know really I think there's a dollar I think there's a fairly dollar bearish view I think weak average hourly earnings I think they're going to pay more attention to that than the payrolls number it was a good payrolls number don't get me wrong 2.27 but that also suggests to me that there's not an awful lot of slack or there's more slack in the US labor market than maybe people currently think which is what the Fed was kind of hinting at on Wednesday something that struck me about the statement from the Fed was how much they were talking about the inflation and the lack of inflation inflation is below our target we don't see it getting to our target they were really dovish on inflation and this will add to that dovish inflation case at the Fed yeah I think I'll keep them on hold probably through mid-year well to be quite honest Colin I always thought March was a non-starter this pretty much takes March off the table I think and you're really sort of talking you're really sort of talking June at the earliest I think yeah I thought March was pushing it the only way they'd go in March is if they were serious about 4 which I never figured since I've been saying 2 so yeah I'm with you on this one it's definitely it keeps inflation soft because wage pressures are the sticky ones that's the one you've got to worry about and down wages are the one that you've got to focus on along with the core inflation there is another one the dollar index is still dropping here it's now down to $99.75 and heading lower that actually becomes a technical confirmation of $100 as resistance you've had the reversal of polarity $100 with support it's now become resistance so this is a quite a significant retest here for the dollar index $125 back above $125 for cable yeah to recap let's look at the key levels because I think now that the dollar is probably going to weaken I think we're going to get a retest of the lows so certainly keep an eye on this dollar Swiss chart that I was talking about earlier I think we're probably going to come back down to a test around about $99.20 also look at the dolly yen the dolly yen is obviously the big mover that is really the responsive one in terms of wow that pretty much tells you all you need to know so for me I think for this downward momentum to really be maintained we need to stay below this $113.20 area that we saw earlier we're getting a little bit of a pullback at the moment but ultimately it's not going to be paid to any potential dollar rebound today and that's probably going to be reflected I think in my dollar page here there we go so the commodity currencies are obviously taking up the slack a little bit Australian dollar not altogether surprising probably going to see a bit of a higher in gold prices as a result of that let's have a quick look at gold because that's again near a key resistance level for me on gold if you have any questions by the way ladies and gentlemen feel free to sling them over more than happy to there is some resistance around $1218.1220 on the upside if you look at this here you've got a big big level through here $1220.240 I think it's ranging gold we we tested $1180 in the early part in the late part of January we haven't been able to get back below that I don't think this will be enough to send us through $1220.240 maybe Peter Navarro will come out and basically spook somebody or spook investors or Donald Trump himself by saying I think the dollar is too high I want it to go lower obviously I don't think you will do that I've lost it given some of the stuff he's come out with in recent days let's face it threatening to invade Mexico isn't wouldn't be on top of my list of things to make friends and influence people and then hanging up on the Australian Prime Minister I couldn't believe they picked a fight with Australia that seems strange well the stock market likes the numbers even if the dollar doesn't so stock markets retesting that 20,000 level on the Dow be interested to see whether or not we get back above that and obviously again we'll look at the S&P we talked about that earlier between 2290 I would doubt that we get back above there but I've been wrong before but I'm going to put it out there I think it will be pretty tough to get above there and actually if we look at the FTSE 100 in particular I think the FTSE is going to struggle to get back much above 7,200 yes it's oversold on the daily RSI let's zoom this in and look at it on a 4 hour chart we can see that through 7,200 we've got a series of lows through here and then some peaks through here we have found a little bit of support just below 71 7,110 71,27 was the previous highs but the thing that makes me doubt that the FTSE has significant upside in it is really this chart here this key reversal week on the FTSE 100 now that would suggest to me that it's going to be very difficult for the FTSE to get much above 7,200 we weren't able to do it last week we weren't able to do it last week so the big question for me is what's going to take us back above there certainly on the RSI we are starting or the slow stochastic rather we're starting to roll over and that weekly reversal there also coincided with the weekly reversal that we saw on cable on the cable chart so the big question for me is what's been the biggest driver of pushing the FTSE up here it's been sterling weakness if you longer have that then what's going to drive the FTSE 100 higher in the absence of sterling weakness I think you've still got the same relationship between the FTSE and sterling that you've got between the Nikkei and the Yen right now and they're just basically trading opposite to each other and I guess US dollar and gold but those are kind of those opposing relationships and I think that's what you're really looking at with the FTSE and cable here and with cable back above 125 I don't see how you're going to get the FTSE back above 7200 in the near term especially when you're overbought and rolling over I noticed someone I think is trying to ask a couple of questions you need to reply to the chat that I've just put reply to the chat message that I just sent out about a minute ago so questions here if you reply to this message here we can then respond to your question I'm afraid I can't see any other messages unless you actually reply to this message that I've just sent out to everybody here just what we're stopping for I just wanted to mention we aren't covering Canadian jobs this morning because they're not out this morning the Canada jobs are out next Friday this sometimes happens when the first Friday falls in the first couple of days of the month it's not unusual but I just wanted to mention that it's not unusual I've been asked how would the non-farm figures affect the FTSE 100 they affect the FTSE 100 in terms of the way the dollar reacts on the exchange rate so certainly that's the way they've been reacting at the moment so if it sends the pound higher it's going to weigh on the FTSE 100 because predominantly that's why the FTSE 100 is really rallying generally equity markets tend to move in lockstep with each other so what's generally good for one equity market is good for the other so I certainly think there's potential for the FTSE 100 to move higher but I don't think there's potential for it to move much above where we are now so maybe another 20 points and I think that for me is how equity markets affected global equity markets are affected by one set of numbers in this case the non-farm payrolls numbers it's basically everything is interlinked being asked what we see is the next key level of resistance for cable there's a huge resistance intermediate is probably a little above 125 I think it was 12540 but the huge resistance for cable was in and around where we saw it top out earlier in the week in this 127 to 12730 area about 12730 there's actually a cluster of Fibonacci resistance levels that kind of contained the recent rally in cable here just below 127 so what's that first line Michael if we look at this we've got a potential double bottom at 120 and we've got the first reaction high which is 12795 now we've come all the way back here to around about<PHONE_NUMBER>30 here basically the next resistance level minor resistance level is around about 12545 if I take this out to a four hour chart we can see that there which is a series of peaks and that low there but ultimately I expect I would expect the pound to try and retest the highs that we saw earlier this week earlier this week around about 127 and ultimately retest this peak here from November 12795 which is also support so it's potentially carving out a base the cable interim resistance around about 125.5 but ultimately we're looking 12795 128 what I wouldn't want to say in the context of this up move is for us to go below 124.20 so hopefully that makes sense what I really like about this up move is not only did you have that strong green candle up off the double bottom but since then the 50 day moving average rated by 124 has come in this really nice support on these last two weekly candles and that's really encouraging to me that each time you've seen the bears try and pound cable back down it's getting contained by the 50 day moving average it almost looks like a cup with handle patterns starting to form which is like a larger saucer bottom and then a smaller one starting to form here and that could be quite bullish as well for cable in the long term it really does look like there's a pretty big base forming here. What we've also got though ladies if you look at the 50 day moving average over the past six months very often it's acted as support and resistance resistance resistance resistance resistance a little bit of support broke below resistance resistance support support again so when you see that sort of when you see that sort of sequencing you can't ignore it it's going to give you a trading signal and ultimately if you're looking to play that then it gives you a fairly decent risk-reward ratio because essentially what you'd be doing is you're buying the pound as close to that moving average as possible but your stop-loss is going to be just below it by 30 or 40 points and that really keeps your stop-loss tight while at the same time and minimizing your risk at the same time in the hope of a decent rebound so for me the next key level of resistance on the cable for me at the moment is 125.5 simply because that was the series of peaks that we saw earlier this week I'm also being asked is the 0.2% difference on average earnings a large difference or just classed as a slight difference are we talking on the monthly or the, yeah we are talking on the monthly it isn't it isn't the bigger number which obviously I don't have up here is the annualized number the annualized number posted a drop from 2.9% to 2.5% that's a big drop everyone was expecting just a modest drop to 2.8% they weren't expecting a big drop down to 2.5% so when you look at it through that sort of prism in terms of what markets were expecting it's quite a big drop particularly on an annualized basis when you consider that inflation is actually rising very very quickly so inflation is rising quickly but wages are stalling out and at the moment central banks will not raise rates if they perceive that wages are not rising in line with inflation because all that will do is exacerbate an income squeeze on those people who are being squeezed by inflation so hopefully that makes sense does anyone else have any other questions on any of this I can see someone else I'll just highlight here I think someone else has tried to ask a question but again I can't see it I just wanted to note while we're waiting for questions that we still have some more data coming out in the United States this morning so we could see some other announcements the market service PMI is at 5 a.m. that's 245 in London the big one is 3 o'clock in London 10 a.m. here in the east coast is ISM non-manufacturing composite streets expecting 57 and US factory orders street is expecting a rebound to 0.5% after a 2.4% drop 2.4% drop again that could have gotten distorted by the holidays so we could get a rebound and we also have the rig count at 1 o'clock this afternoon and Michael was right and something I wanted to mention on the rig count it's two things, one it is increasing as we normally see seasonally but on top of that a couple of weeks ago we finally had the crossover where drill rigs are running higher than they were in the same week a year ago so we're definitely starting to see that the higher oil prices which are basically running double what they were this time a year ago is starting to have a positive impact on spending, on exploration and that's a good thing because those are good high paying jobs that are going to be starting to come back and help a lot of the US economy in kind of the middle of the country let's call it that center piece that runs from North Dakota down through Texas right through the heart of the United States will definitely be helpful I've just been asked about dollar Turkish lira you're brave whoever you are yes it has broken through support and it looks as if it's going to head lower so certainly on the basis of this four hour chart that I've got in front of me here certainly a decent break lower the next area of support is probably quite a little bit lower certainly in the context of that I must admit it's not something that I'd be particularly brave enough to trade but yeah it does look as if it's broken through a fairly key support level on the four hour chart could have been asked about dollar CAD Colin affected by the oil price yeah of course it is it is affected by the oil price but ultimately the oil price is not really doing anything at the moment so any move on dollar CAD today is likely to be driven by the dollar the US dollar and not the oil price though we are seeing oil prices at their at multi-month highs if the oil price does continue to push higher then obviously it will have a double effect on the weakness of the dollar because it will cause the Canadian dollar to appreciate yeah on that on the on dollar CAD there's a big support zone for it between 129.75 and 130 129 is a Fibonacci level and 130 even of course is a round number if you break then we've seen a couple of times here recently really since September as Michael's showing in the chart here this zone is held as support for quite a long time now if you look though you've also got a trend of lower highs heading into this you've got a really nice ascending triangle that's telling you distribution and that the Canadian dollar has been recovering so if the oil price and the same thing we're actually seeing a nice little ascending triangle in the oil price itself showing accumulation so if the oil price continues to trend upward and eventually breaks out of this 50 to 54 range it's stuck in on WTI that would be bullish for CAD if we start to and the other piece that we're seeing though with the Looney is it is getting a little bit of a boost and that people are starting to come around to the idea that Trump's probably not going after Canada in trade talks I mean if NAFTA goes we still have an existing bilateral free trade agreement with the United States that can go back into force because it didn't have to basically built on that anyways and so basically although so primarily I mean Trump has a lot of other countries in his sights even the Mexican peso to be honest has rebounded a little bit over the last week or so as as he's kind of starting to turn his sights elsewhere away from NAFTA it looks like he wants to fight a lot of battles of once rather than picking people off one at a time which is a dangerous thing to do could you put up a dollar Mexican Michael just so I can point that out sure that it actually has been quietly recovering for the last week or you can see there it actually peaked right about inauguration day to be honest and it's actually been that the peso surprisingly has actually been recovering it surprised me I thought it would blast through but it hasn't it's actually starting to to turn back down with so with so many things going on heading into the inauguration people were really worried Trump was going to go full force on NAFTA and that depressed the loony and it depressed the peso they've now come off and had a relief rally now I do think that support level there which is 20 and what 20 40 that'll probably contain it I don't see the peso busting 20 I think and for sure I think they're not yet anyways I think that that'll kind of contain it for now just because there's still risk out there of that one day he turned it around and refocuses on Mexico and that could turn the whole thing right around again so this is likely to be a volatile pair to be trading over the next well year at least I think it will continue to see some big swings in a lot of if Trump lost that long sort of their relations yeah Donald Trump lost that long yeah that too alright ladies and gents I think we're pretty much done for this week as I say I have recorded this so I will be posting it on YouTube at some point over the course of the next hour or so but thank you very much for your attendance today hope you found hope you found our two-ing and fro-ing useful and please feel free to log into my weekly webinar which is on a Monday at 12.15 otherwise both Colin and myself will see you again same time next month for the February payrolls report sounds great have a great day trading everybody