ODSC WEST 2015 | Jonathan Reichental - "Creating Data Driven Cities"

Thank you for that lovely introduction. You read it like I wrote it. Thank you for that. I want to take you on a journey to India. This is Chennai. Some of you may have visited or grown up there. And if you look at what's going on in this picture, I think you'll see there are some considerable issues. There's some considerable issues around transportation. Look at that. If you're in the car at the bottom of this picture trying to get to the airport, you're not feeling pretty good right now. Look at the potential impact these cars and all these people are having on our planet. And look at that infrastructure. And while this is maybe the extreme case, everywhere in the world might get to see this personally is in some shape similar to this. This is the world when over half the amount of people live in cities. So we're at the sort of 3.5 billion mark now. And then the next 20, 30 years, another 2 billion people will move into cities. And so the vast majority of humans will live and play and have their lives in a city or an urban context. You look at a picture like this and basically what we're saying is over the next 20 to 30 years, this picture's going to double in the amount of people. And I would say to you, if we double this picture, we're going to have some issues. This is going to break. And so let's make it really personal. What are we looking at here? We're in San Francisco, in the San Francisco Bay area. Right now, you're sitting in that very area. And this is actually looking down at the city of San Francisco. And it is showing here. You can see in the top left you have the Golden Gate Bridge. On the bottom right you have downtown. And so what are we looking at? We're looking at the potential for water rise over some period of time. So the area in blue, that light blue is going to be flooded. And so I look at the bottom right and I say, wow, that's the western Wall Street. That's what we call it. That's downtown San Francisco. And it's going to be flooded. And many people look at this picture and say, well, that's 200 years from now. You know, we'll try our best to fix it, but it doesn't really impact us. Well, depending who you believe and what scientific study you read, it's not that far away. When I do this type of presentation to children or young teenagers and I say, this could be in your lifetime, they sort of get angry. They soon as they wait, what that's crazy. And so I say, I'm really glad that you don't like this because you'll be motivated and potentially provoked into fixing it. So these are some very serious risks that impact us all. Impact us all is as humans who live in an urban context, I think what I'm trying to do is to tell you that our future belongs in cities. But as we look at the issues, I'm ready to say, and I have first hand experience because this is what I do for a living. We're not ready for the cities of the future and our lives to be in cities. What we really need, what we've got to do is create a new operating system. We have to create an operating system where we are applying 21st century solutions to 21st century problems. What we're doing right now is applying 20th century solutions to 21st century problems. Really. That's the challenge that I have to ask you and to tell you about today is how do we help and how do we participate in this? What you're going to learn is that data is going to play an enormous role in helping us prepare our cities, create the kinds of environments, the kind of urban environments that we all want to live in. Now I always say to people when I make this presentation, you may have two motivations for getting involved and I hope that you fall into either one of them or both of them. The first motivation is, well, you want cities that you live in to be really nice, safe. I think that's timely. You want your cities to be places where there's opportunity and jobs that's healthy and where there's great transportation. So you might have a personal interest if that doesn't really bother you and perhaps you're saying, well, somebody else can deal with that. The second thing I would say is there's an economic opportunity for everyone in this room. What I mean by that is when you think about America and our job market, you look across the world, the job market is changing significantly. We're not too sure what everyone's going to do in the next 20, 30 years. That's just reality. I mean, the robots are coming, you know, artificial intelligence is coming. And so we got to figure out what we're going to do. And the opportunity, the economic opportunity to have to be data scientists in a city context is a real high paying opportunity. And I say, if you're not interested just in the social piece of it, which I am, you may be interested in the trillion dollar opportunity that technologists are going to contribute to and be part of over the next 10 years. Now there's something really interesting happening. Who knows this app, Waze? Almost everybody here, of course, this is the Bay Area. I give this presentation in different countries and I get maybe one person sometimes who puts their hand up. But everybody kind of gets the concept of what you're looking at. And I always ask the question, how come Waze only exists now? I think this is a tremendous application, the ability to see traffic that you can't see what the issue is ahead of you, or to get a better route to go home or to go to a friend's house. Well, you need a few things. You need amazing connectivity. We're getting there. You need social computing, really a brand new phenomenon in our world, less than 10 years old in the form we know it now. You need, of course, an enormous amount of data to make this work. Like everything here is driven by external data, by user generated data. The ubiquity of smartphones, right? The biggest, most prolific type of technology we're probably ever going to be seen in history so far. Billions of people getting the entire universal knowledge on one little device in their pocket. And of course, you can get access to this data and information anywhere at any time. It's very useful. When you're in your car, your car using a smartphone, you can get access to this data. So take any one of those things and you don't get Waze, maybe take two of them, you don't get Waze. You kind of have to have all of them to get this completely new type of capability. And that's a great place to be, it's great to live in 2015. It's going to be even more amazing in 2016 and 2017 as even more technology comes online that lets us do even more amazing things than waves. And that's why I'm an optimist, because I think we will begin to solve really tough problems like transport and transportation when we have an intersection of technology, smart people and data, of course. And that's our topic today. That's why you're here, hopefully. What is the role of data? Data scientists, data analysts, People are just passionate about the space to make amazing cities where we can all live and enjoy ourselves. So sometimes when you're talking about a topic, you don't get to say this, that in fact the topic of data is about life and death. That's something you don't always get to say. Why do I say that? Well, let's take a look at this picture. This is Haiti after the devastating earthquake. They had a Few years ago looks pretty, pretty bad. I mean, it was devastating. One interesting fact about the Haiti earthquake is that SMS messaging worked. Afterwards, a basic communication service actually worked. And we're afraid of that. If we have a mass when we have a massive earthquake here in the Bay Area, will our cellular network work in any form? We're hoping there's sufficient redundancy or something can be spun up pretty fast. But in Haiti, it actually worked. And so for the first time what happened was a non for profit organization stepped in and said using texting, tell us about what you're seeing on the ground. Tell us when you see the state of a collapse, building other injured people there, tell us if there's a road that's blocked and use a mechanism of texting. And we will aggregate it and put it on a visualization so that first responders actually know where to go to save the most amount of people. It was really the first time that we changed the game in terms of how we could get people to the right place at the right time and save lives. So data and telecommunications here saves lives. This really is a topic about life and death. That's also a topic about you being informed and me being informed about what our elected officials are doing. For the first time, we have very deep visibility to what happens, or at least we perceive to happen behind closed doors. Here in the United States. You can go to USA spending.gov and click on any state and drill down and drill down it. You might find right to the point of the decision maker how money's been spent. You know, when we started to do this type of work in the city of Palo Alto, we asked our community, what are you interested in seeing? Number one thing they wanted to see was how is our money spent? It's a good thing to know. It's your money and we're taxpayers. You want to know how money's been spent. And for the first time we have really deep visibility to that which helps us be more formed. A more formed electrode gives people power, not people in power, power. You follow that? I want to show you this picture. Okay? It's a heat map in Durham. The red area signifies something. It signifies where there's a density of crime happening. And as you go out to the green and the less green areas, there's less crime that's occurring. And you might say, well that's interesting. Okay, you've taken some crime data and the volume of crime data you've simply mapped against picture. Well, that's cool. But I wouldn't just show that to you, I wouldn't have any credibility then this is a picture of crime that hasn't yet happened. This is what we call predictive policing. This is looking at crime in the future. For the first time we have the ability to look into the future, a week, two weeks ahead and know what might happen. Think of the benefits of that. If we know there's going to be more crime in that red, the purple zone in the center, we might pre position public safety. We might do outreach. In fact, in communities that are experimenting with predictive policing, crime is falling by double digits. This is very promising, I always have to say, is just a disclaimer. Predictive policing is wildly controversial, as you can imagine. Right, Right, right, controversial. That's my point. Thank you. Thank you for sharing that. But we'll get better at it. We'll have to have the debate as a society. Right. But it's really interesting to see what might be possible. So let's just take this down to a local level. I want to talk about Palo Alto. It's only about if the traffic's good, it's only about 20 minutes from here. On a bad morning, it can be an hour from here, not so good. And it's the birthplace of Silicon Valley. It's a small city, but it's got an incredible footprint in the world that I recognize and privilege to be part of it every day because of that. So here's some of the stuff we're looking at, really practical applications, how data might change the game for us and has changed the game. So what are you looking at here? You're looking at the typical government set of data, like columns and rows of data. What we're looking at here, you wouldn't believe. I didn't believe this. This is the condition of every street in Palo Alto. It's a thing called the Pavement Condition Index, the pci. This is really gripping stuff. Right. But if your road, if your road is crappy, you might be interested in this. Palo Alto happens to have decent roads, but you've got some bad roads too. And it's an index from 0 to 100. 100 means the road is great. 0 means that the road is not a road, it's just gravel. So we want to get most roads to 70, I think it was. 80 is our index. And so what we would have historically done is looked at a picture like this and said, let's make some choices. And you show that this is like, this is only a few streets. There's 25 square miles of streets in Palo Alto. This is quite a big document. It's really difficult to make decisions. So in true Silicon Valley fashion, on a napkin, I drew this picture because you have to do that here. And so I said, why can't we, instead of this nonsense, why don't we have a nice interface where you can type in your own address and see the condition of your street? So went up to Stanford with the mayor. It's really useful when you have a mayor. You can get really cool stuff then. And said to the students in the computer science department, would you be able to take this, make it into this? And they said, yeah, we'll give it a shot. And in basically 24 hours, in a hackathon, they created this. Really cool. The question is, how did they create all the pictures? They got them from Google Maps for free. And now you could just take the data which has the condition. This case 83 is the condition here. It's on 250 Hamilton. And here's a picture of the street. Now this, I think you'd agree, is a much better way to make decisions about streets. Now you can upload photographs here, too. This was one of the first experiments. We tried to change the game using a traditional way of using data and then thinking about it in a more contemporary way. So the question is not so much, well, that's kind of cool, but I can't go up to Stanford every time I need a little app built, right? That's not scalable. And the question to me was, well, how can we do this over and over again? How can we actually build solutions that we really need? So that's the challenge. Now, if we went and continued in the traditional fashion is what a lot of cities still continue to do. There's all these things we want to do. They all cost money and they all have to be privatized. That solution I just showed you might have caused, I don't know, I just guessed with you, maybe $50,000 for developers to come in for a few months. And it would take, based on the procurement cycle and everything else, maybe a year to produce, if we were lucky. Well, we did it in 24 hours, and it didn't cost anything. In this case, my question was, well, how do we scale that? Not for everything. Not for everything, but some of the things. So the first thing is really what we did is we built an application, or the software developers at Stanford did, based on data that we already have. One of the things about government that I discovered having moved from the private sector was in government, there's never Enough money, there's never enough time. There's too much bureaucracy. It's all about these incredible constraints. And then I said, well, wait a minute, we've got these constraints, but one thing we have is data in abundance. We have data in abundance. Every public agency, and there's about 89,000 public agencies in America has data in abundance. And it's not typically used. It's not typically used to solve the problems that we already care about. So I looked at Palo Alto, a small little city, and I said, wow, we have a lot of data. Let's just make that data available. And in fact, all new data that we create, just let it, liberate it by default, make it available, make our data open by default. Now, we weren't the first to do this. I don't take credit for innovating in this area, but we were the first of a small city, and we're still among a very elite group. I don't know why that is. I mean, I still struggle with it a little bit. We're a small group of cities of the hundred thousand person number that makes their data available. And in this case, a very small group. It's a real elite group club that does open data by default. And you may be interested in some of that. So one of the things I'd like to give you is this link, and you can then play with our data. And maybe if you live in Silicon Valley or even if you live in Palo Alto, perhaps you'd be willing to participate in problem solving. Of course, I shared with you this idea that the number one thing that our community wanted to see was budget information. And so today we give away five years. If I say give it away, it's yours, it belongs to us. We make available five years of data, budget information, and actual information. Let me tell you a little story. So one of the things that people are really interested in are government worker salaries. People are very interested in what I earn, for example. We're just curious, right? And so, yes, because I work in government, because we have to conform with certain laws, my salary is open and available to any one of you. And each year prior to this, there was this kind of tug of war between the media, who loved to publish it, of course, and the government, city hall that said, okay, we can get it to you, but we're working on some other things and people don't want to be embarrassed. And there's all sorts of things that maybe just created that tension. Ultimately, of course, we gave it. We're obligated to do that. But when it was given, maybe by Palo Alto, but other cities, perhaps it's a PDF, as data scientists, you love that. Or here's even better, a jpeg, how about that? For data analysis. And in some instances, government agencies, not Palo Alto, shipped boxes of documents rather than doing it digitally, because there's no obligation to give it digitally, just have to make it available. So we went ahead and, and after many, many years, when I came along, we said, I'm going to put salaries on open data and everyone in the world can see what I'm earning, what my benefits are, my vacation, whatever. We'll do that for everybody, all staff. So if you want that, you can go to our API or just download a text file and see all the detail you want. The day after we did it, I met a guy from one of the journalists from a local newspaper and I said, what do you think about that? And he said, jonathan, it's like, I don't know, it's really crazy. He said, you know, I thought you were going to do sort of incremental change, whatever, but overnight you gave everything away. We're overwhelmed. We didn't think there would be that type of transformation. And that was, that felt really good. And if you can surprise the media in a positive way, and this was a real positive story, that's a good thing. That reduces the tension between city hall and community and, and media in a world where there's enormous tension between those stakeholders. Now, what does it look like when other people start to build community solutions based on our data? Now lots of people do it because it's just interesting and they do it because I want to be a contributor. Remember I talked about, you do it either for social good or for profit. Well, we're very encouraging of companies that want to make a profit because it creates jobs, it creates good economic activity. So if you can make a solution that uses our data and we as a community benefit, but you also profit. Wow. It's a win, win for everybody. Here we have a solution called Civic Insight, recently purchased by a very big tech company. So it's a great success story where they simply took our permit data, which we made available on open data, and they built this really nice interface that allows people to know exactly what's happening in their neighborhood or any part of the city. Because like I said before, people are curious. Right now I have to tell you about our trees. Why? Because Palo Alto is a tree. In fact, El Palo Alto is Spanish for tall trees. And the actual tree that the city is named after still exists, you can go and see it if you'd like. So we really revere trees. This is open data. This is a visualization of every tree in the city of Palo Alto. You can get to it with the web link I gave prior and in fact, if you click on any one of these green dots, you can see the type of tree, the age of the tree, any disease the tree has had. Anything else you want to know about the trees? Amazing amount of stuff about trees. I never knew so many people were interested in our trees. And they are. We even have an urban forester on staff. People really love trees in this area. And so we helped people who typically would have used a probably a clipboard and pen to walk to every tree and note stuff. We kind of changed the game by digitizing the whole thing and making it available. Now making data available in cities is, is not a case of if you build it, they will come. There are over 500 cities in America that make their data available and most people don't know that. Now you do. So we have to create environments and situations where people can be aware of the opportunity and do stuff with the data. So last year we did this thing called the Palo Alto Apps Challenge. We designed it after the big Apps Challenge in New York City, but we did it for our city size and we kind of made it in a way that was kind of cool for our community. It was sort of an American Idol style six month challenge. I played Ryan Seacrest very convincingly. And so we got lots of people to participate to create apps based on our data. And yes, there was a number of solutions that were created. And you could say, and I could say that's fantastic. You know, it's fantastic that we got a solution built and you could end there. That actually wasn't what was interesting to me. It wasn't the most exciting data point about the Palo Alto Apps Challenge and what it is might surprise you. Of all the entrants of which there was about 100 active participants, 30% of the participants were under the age of 18. 30% of the entrance to the Palo Alto Challenge were under the age of 18, which is amazing. I'll tell you why. First of all, young people do want a voice in government. They don't know how to get one and they're disenfranchised. And it's sort of like just for the grown ups and we have no say in our community. They get a say here. They can build solutions, they can do analytics, they can actually be part of the conversation. The second component is young people aren't necessarily attracted to civic life and public life. And we do need smart, educated, motivated people to be interested in the future of their communities and their cities. So 30% of entrants have this visibility. And, you know, they're not all going to go on and do stuff, but they might. We may have created through this interest enough that the next mayor or senator or congressperson might be somebody who is exposed to a new way of thinking in government because of an Apps Challenge that we held. And that's what I'm really hoping. People will be excited in a way that they weren't able to prior to this. And here's just one picture of an actual meeting during the Palo Alto Apps Challenge. Now, I want to talk about other applications getting more specific to Palo Alto and how it might manifest, how you might make real the things I'm talking about to each of you today. And so I want to talk about this app that you can all get for free. I want to actually go back, I want to give you something for free today. Sorry, I just went past it too fast. A lot of people ask, how did you do this? Right. I just want to go back to this because you get something from sitting here, just beyond the knowledge and insights. And so I thought to myself, wow, I'm getting so many questions about how we did this, I can't possibly get on the phone and kind of explain it to everybody. Why not go ahead and write a book? Why not actually write the book on the panel outlets challenge? So I did that and I have a copy for everybody in the audience today. So it's yours free. Now, before you guys applaud, it's an ebook. I don't have a pile of books behind here just to say it's better. It's no carbon footprint, it's totally virtual. You can use it on your Kindle so no trees impacted, really in style of our city. So you're all, I'd love you all to use it, download it, distribute it. It's open source, it's free. Just have that and enjoy it. Just do a search for the Palo World Apps Challenge Playbook or some variant of that. Okay, so I want to talk about the app, this particular one. Now, having a reporting app in the community isn't necessarily that innovative or interesting. So in San Francisco, yes, there's an awesome app for reporting potholes and abandoned bicycles and all sorts of things. Communities all over the country, all over the world, have solutions that are like this. And in panoalto we have one too. It's free. You can download this from any of the App Store, from the Google Play Store, and you can use it if you enter the city of Palo Alto for something that you don't like. So you take a picture, the picture goes to an engineer at City Hall. They dispatch an engineer to look at the problem. You get notified, the problem is solved. You get notified, and then you're asked to rate it. It's a tremendous way of holding us accountable. It's a great way of holding cities and public officials accountable. Now this is just a good thing to do and I hope all communities will pursue this. It's a great use of, of technology and community to make a difference. And so I could have ended there. And you might have said, well done, Jonathan. Cool stuff. We didn't end there because if you think about what's happening, we're capturing incredible data. Every time somebody takes a picture or reports an issue, we're learning something about our community. In fact, we're learning about the invisible the very first time. We're learning about the, the rhythm, what I call the cadence of Palo Alto. And so we take all those reports and in near real time map the begets of the city of Palo Alto. So you can double click on any one of these items here and see what's happening in Palo Alto right now. In fact, you can do that right now or over lunch. Do it over lunch. And so you can see, for example, that perhaps we have a increased volume in something in one certain part of the city. So I'm just going to make this up. This is not real. But in the east part of the city, there has, we're seeing now in near real time, an increase in graffiti. For some reason, starting last Tuesday to today, there's an increase in graffiti. Why might that be? Now the fact that we can ask that question is really a product of data science. Why might there be more graffiti on the east the city? And so you drill in, maybe you have conversations, maybe you do some analysis. Turns out that the time in which students were released from school has changed. It changed on Monday night or Monday. On a Tuesday, something different happened. So now we track a consequence with a potential change, you know, an impact to a change. It really gives government officials and cities completely new ways to, of seeing the invisible. So we've had a lot of fun today. I want to end on a little story to kind of bring this all together. Now what you're looking at is a fire hydrant. You all knew that this is around 2010. And there is significant snowstorms in Boston. And I know some of you from Boston here, you probably remember this well, weeks and weeks of snow. Turns out, almost unintuitively, there are more fires during snowstorms than other times. And I think you can probably figure that out. It's because people are making fires in the house because they're cold and the houses go on fire sometimes. And so it's important to know where the fire hydrant is. Right? It's important to know that now if your house is on fire, fire's engine comes out, can't find the hydrant, or it takes a while to find it because it's covered in snow, the house might burn down. And so it's really important to know where that is and get easy access. The quicker you can get access to a fire hydrant, the quicker the solution, the water, can be applied to the fire. So a programmer, a software developer, no less, saw this as a big issue, went to Boston, and over the course, actually of just a few days, built a solution called Adopt a Fire Hydrant. And Adopt a Fire Hydrant basically allowed people in their neighborhood to say, I want to be responsible for that hydrant outside my house in the event of snow. And you could then register. And it said, the fire hydrant on this street belongs to this individual. And it had some cache to. Has so much cache that if you didn't check in on a periodic basis, somebody could take over the fire hydrant and be the adopter and you would lose it, essentially gamifying the process. It's been a really big success. So if it snows and you are the adoptor, you have to go outside and dig around the hydrant. So it's available to the fire service. And over the course of Several winters since 2010, Boston has used this, and it's been quite a deep benefit. Now, think about what's going on. Well, there's a software engineer that's motivated, there is a lot of data, there's app technology. We're really bringing together a lot of things I've been talking about today in order to create a solution that really is meaningful, low cost and doesn't cost government anything because it's just done by the community. Now, that's not the end of the story. The end of the story goes a little bit like this. Public officials in Hawaii saw this and called the Boston team, or the Boston mayor and said, we're interested in your Adopt a hydrant app. Now, there's something wrong with this picture. I wonder what that is okay. So for those of you who haven't got it yet, there's no snow in Hawaii. Never has been, other than high up in the mountains for sure. Someone later will tell me that. I go there quite often, so I know that. And so there's typically no snow. So the question is, what on earth are government officials doing in Hawaii? Calling the folks in Boston about a fire hydrant solution that has everything to do with snow. Well, they have a similar solution. They have a similar problem in Hawaii. There's always a potential for tsunamis, tidal waves. So if you're on the beach or near to the water in the tsunami, you want to be warned in advance. So there's tsunami warning horns that are all around the coast of all the islands. Now, tsunamis don't happen often, so these warning horns often get neglected and you know, weeds grow up them and you know, animals chew in wires. But mostly actually people steal the batteries. That's what they really do. So what the Hawaiian government, having seen the success of the Boston adopt the fire hydrant program, said, why don't we adopt a tsunami horn program where people then have an affinity adopt a particular horn, they can make sure the wires are working, they can test it, they can put batteries in it. And that makes a lot of sense. Now what you have are scalable solutions. This is really cool. They took it, they modified it, making slight modifications now the solution can be applied in Hawaii. It's a very different way of thinking about the future. It's a very meaningful sort of near to us solution among the complexity of solutions and problems that we all face. So what I want to share with you and I want to get you excited about it, we're not in the middle of this phenomenon, this trillion dollar ten year phenomena that's ahead of us to make better cities, smarter cities. We're just at the very beginning. The opportunity is massive. Not only massive for social good, but massive for economic benefit. We need data scientists and developers and engineers, entrepreneurs. We need artists, people who do great art. We need all the steam, the science, technology, engineering, art, math, we can get in government. And I want to ask you to consider being a part of it. Either work directly in government, just for a couple of years, you don't have to work there for a lifetime. You might be amazed how much it touches a part of you you didn't know, could be touched in your heart or in your mind in a way that's very different from the work you probably do today. And so that's one thing. But I want to also share. If you want to be on the outside, you want to create a business that serves government, the money is sitting there waiting for you. And it's money that when we spend it in the right way, will create a real difference in how our community works, how we consume energy, how we impact the planet, how our transportation options will change, how our cities will become healthier. These are all components of the things that you can directly do. And this is just the beginning. Ten years from now, if I'm up here, I won't have the benefit of telling you that we have 10 years of opportunity ahead or because people will have stepped up. But now we're at the beginning. We have the opportunity for each of you to be part of it. And so my request, my ask is it might not be you could be a colleague, a family member, a friend, but there is amazing opportunity. I want you to be part of it. So I'll end on this question. I'll ask each of you, are you ready to help create a new operating system for data driven cities? And with that, thank you so much for your attention.