The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future with Ben Green

hello everyone and Welcome to our first Tech in the city webinar of the spring series today's guest Ben green will discuss points made about his recent book the smart enough City putting technology in its place to reclaim our Urban future my name is Jericho Logan and I am the Outreach coordinator at the Center for Urban and Regional analysis otherwise known as Cura I will be your host for this event if you require closed captioning you will find a box at the bottom of the screen called CC click on the box and select show subtitles this will allow you to see subtitles during the presentation please feel free to submit questions at any time during the webinar in the Q a box we will ask as many of your questions as we can in the last portion of the presentation and if we do not get to your question we do apologize if you have any additional questions following this event please feel free to email me at logan.433 osu.edu this event is approved for one aicp cm credit to claim your CM credits log into your my APA account on the APA website and enter and in to the event log there is also going to be a brief survey at the end of the web webinar if you have time please provide your feedback I am now going to pass it over to our director Harvey Miller okay thanks Jericho and welcome everyone to cura's webinar series for spring 2023 uh this this year this Academic Year we've been following the theme of tech in the city looking at the upsides and downsides of technology to help us understand and manage an Urban Planet and we're very pleased to invite Ben green today but I wanted also before we get into his talk I want to talk about our next event in this series and this will be a a webinar on February 10 2023 same time at noon and this will be by Jeff Boeing from the University of Southern California and he will talk about measuring built environments around the world new insights into urban sustainability and health so it should be a really exciting talk he's a real big data guy looking at global scale comparisons among cities and I'm looking forward to that myself but I'm also looking forward to today's talk by Ben green Ben green is currently a postdoctoral scholar in the Michigan Society of fellows and then the Gerald R Ford School of public policy at the University of Michigan he starting next year he will be a tenure track assistant professor at the same institution in the school of information congratulations on that Ben he has a PHD in Applied Mathematics with a secondary field in science technology and Society from Harvard University Ben studies the ethics of government algorithm of algorithms with a focus on algorithmic fairness human algorithmics interactions and AI regulation his book the smart enough City putting technology in its place to reclaim our Urban future was published in 2019 by MIT press and it's a very good book it certainly resonated with some of my thinking about smart cities and I'm looking forward to hearing his comments today Ben please all right uh thank you so much Harvey for the introduction and Erica for all of your work organizing this event and thanks everyone for for coming out it's a great deal to speak to you all I have my uh Jenny's ice cream mug in honor of the occasion um so yeah I'm excited to talk to you about my book the smart enough City so I will present some of the core themes from the book and some of the more recent events that have happened since the book was published uh and then yeah turn things over to questions um so I think it's you know also helpful to add a little bit of context of how I came to writing this book um you know I was I was working on my PhD in applied math and I was interested in the role of Technology uh in helping to address Urban challenges but encountered a lot of frustration with the types of solutions and ways of thinking about improving society that I was seeing from my department and my colleagues and my field so I sort of felt like a need to get away from the very Tech focused computer science world that I was in and I left and spent a year working for the city of Boston as a data scientist and there I was not working on Research I was working on you know very applied projects trying to uh really help the city manage data and make better use of data to improve uh various operations and performance and Equity concerns and so that really led me then after that back to research but uh to this book specifically really thinking about what is the gap between the ways of thinking about Urban challenges that I was encountering in the technology world and then what was actually happening and what was actually needed and working inside the real world environment of City Halls both in Boston as well as many other places around the country so so that's really the focus of how I came to this book thinking about where what is the proper role for technology in the future of cities so we can start with a definition of what is a smart city what are we actually talking about so this definition uh that I'll pull is from the company Cisco who writes by definition smart cities are those that integrate information Communications technology across three or more functional areas more simply put a smart city is one that combines traditional infrastructure roads buildings and so on with technology to enrich the lives of its citizens so there are a couple of elements to this definition that I want to highlight the first is that it is really centering the role of Technology um and we can see the usage of the word smart here in much the way that we see it across a number of other areas um from our smartphone to the smart house to a Smart toaster or a smart toothbrush where smart means taking some traditional object or process and connecting it in some way to and digitizing that thing uh connecting it to the internet adding Big Data algorithms and so on in the interest of efficiency and convenience and the second thing to note about this definition is that it is a definition provided by a technology company not say a city or a mayor or a group of academics and I think that's useful for framing this conversation because it's important to keep in mind when we're talking about smart cities that this entire realm this entire term really is one that is heavily influenced by the technology industry arguably the term smart city is a marketing term developed by technology companies trying to create markets for uh new software new sensors uh and new avenues for data collection and so we want to keep both of these elements the centrality of technology and the influence of technology companies front and center when we're thinking about uh what smart cities are um as that prior definition suggested the actual uh Technologies of the Smart City are somewhat uh they're somewhat broad there's a number of different technologies that we see this can range from sensors on Municipal infrastructure that will collect information about uh what's going on around the city weather patterns traffic patterns pedestrian counts and so on uh self-driving cars or autonomous vehicles are a central facet of uh of uh smart cities we have uh various types of Big Data softwares and algorithms and machine learning systems that are trying to pick out patterns of what's going on in the city and make predictions about what Will Go On in the future and then various types of digital connectivity Services most notably 311 apps that provide a way for residents of a city to connect with the municipal staff of that City say the sanitation department and so on by providing reports an easy way to provide reports about issues such as trash that needs pickup or potholes or broken sidewalks and so on and so within a given City different versions of these types of Technologies different combinations of these technologies will be brought to bear and in much of my work I am specifically focused on the role of machine learning algorithms and some of the political and normative tensions that these algorithms raise where on the one hand machine learning algorithms present uh excitement where many policy makers and Engineers are excited about the ability of algorithms to promote more accurate fair and consistent decision making and this has led to the use of algorithms across a wide range of contexts from uh the criminal justice system to child welfare services to Public Health and yet at the same time uh the use of these algorithms has uh been a site of significant controversy with concerns about incorrect predictions racially biased predictions and an inability of algorithms to be flexible and to account for the particular context of use and so thinking about uh smart cities then uh you know the smart city has emerged as a and a particularly emerged in the the early and mid-2010s as a very widespread popular vision for the future of Municipal governance and we can see just a sample here of different organizations and companies and government bodies that were interested in exploring smart cities and viewed the smart city as Central to its development plan or economic plan and you know we had many cities across the United States that were deploying or exploring Smart City projects and often using that as a way of branding themselves um I'm not sure if these cities still use these labels but at one point Kansas City described itself as the world's most connected Smart City San Diego described itself as having the world's largest Smart City platform and so uh for many cities around the world and especially in the United States the smart city was a way of viewing or thinking about and organizing a vision for where are we going in the future uh how do we want to Define what this city will look like as we uh enter the the later sort of midpoint of the 21st Century as we encounter these utopian Visions what we want to do is scratch beneath the surface of what's promised and begin to ask questions such as are these systems actually possible who is Behind These systems who is driving these narratives and are these Technology Solutions actually something that we want to be implemented and I argue in my book that the answer to these questions is generally uh no that the Smart City presents Visions full of false promises and hidden dangers and uh we want to it's necessary to think about uh to move away from Smart cities and think about an alternative organizing set of principles for what the role of Technology should be for improving urban life so one of the core uh aspects that I uh see in rhetoric about smart cities is a particular lens on the world that I call Tech goggles which uh views every ailment of urban life as a technology problem and selectively diagnoses issues that technology can solve so looking through at the world through Tech goggles prompts one to really pull out or see every aspect of the world as a technology problem or to think about the role of Technology uh as the solution to these problems and it's particularly uh a Viewpoint that is taught within engineering education across computer science and other disciplines and is also uh you know disseminated by technology companies as they try to create larger markets for the Technology Solutions that they provide and Tech goggles rest on two particular myths the first is that technology uh drives social change uh and the second is that technology provides neutral and objective solutions to social problems so the first myth really assumes that we can simply apply technology and whatever the expectations are or the goals are for that technology are what will actually happen in practice and how the how Society will actually be affected and this overlooks the many social factors and institutional complexities that alter and shape the impacts that technology actually has in practice and the Assumption of neutrality overlooks the uh the politics of these systems we have uh there's a quote from the IBM president or the former IBM president at this point uh describing how if the leaders of smarter City systems do share an ideology it is this we believe in a smarter way to get things done so there's this assumption that simply doing things smart is an apolitical and neutral way to solve Urban challenges um and much of what uh we see when these Technologies actually get rolled out is the false promises of these myths and how technology does have impacts but doesn't necessarily have the impacts that are often hoped for or expected and more importantly how technology embeds politics and enables certain actors or groups to gain power at the expense of others so what does it mean to look at the world through technology goggles what we see here is a simulation from a group of researchers of what a city street could look like if you got rid of uh you got you had autonomous vehicles and got rid of traffic lights and so this is presenting a somewhat utopian vision of how we could get rid of traffic lights which is you know sort of the scourge of every driver in a city everyone is frustrated about traffic and congestion and this this great simulation of how self-driving cars could uh sort of weave with across one another without having to pause because they could uh you know communicate across one another wirelessly and manage their driving that way and on first plants this looks like a really interesting and novel proposal but uh when you think about it a little more I think you can start to ask some questions about well what is actually going on on this street how is is this even a real City street at all so what is happening is here is that the tech goggles lens is prompting a starting point of taking a city street and optimizing it into a very simple uh problem where all that we have to care about is the flow of cars through a given interception was particularly notable about this simulation is that it's actually a simulation of a very specific intersection not just the generic street but actually a particular intersection in Boston one that uh is not just a home to cars it's not just at some freeway you know high-speed interchange but is an intersection with you know constant uh pedestrian use there are many cyclists going through in both directions you can see a partial bike lane in this image this is also along one of the busiest bus lanes or bus routes in the city um and then there's of course the broader context of uh sort of where this location is within the city and the social conditions here of how this location is actually at the center of uh where Boston's opioid epidemic is taking place and there are many people in this part of the city who are suffering from drug addiction homelessness and mental illness but of course all of that has been erased the city this complex streetscape with many people different types of people and many different types of uses has been abstracted into a traffic efficiency problem and so by doing that what we've created is a artificial representation of the city where we actually can create these effective technological solutions the autonomous vehicle solution does seem like it would work uh within the realm of this simulation but that only seems so neat and easy because we've erased all of these other elements from the picture and so more broadly then we have a process of distortion where through Tech goggles we're taking a city street and viewing it through the lens of Technology this image on the right here is an image from one of the vision statements put forward by Sidewalk Labs which is a Google Affiliated company in its vision for Toronto which I'll get to and talk about in a little bit but we can sort of see how uh this smart City Vision is taking a streetscape and then rendering it digital as you know how do we view a city street as a set of computable objects foreign ly uh there's a sort of interesting through line of History here as this sense of distortion that we see today uh in some ways Echoes back to modes of distortion that were present in 20th century Urban Visions such as uh design for Brasilia or the Futurama exhibit by General Motors where we've shifted the mode of how we're creating a highly regimented order or what type of lens we are focusing on but the underlying uh effort of taking a complex City and trying to render it into discrete highly ordered structure uh is is definitely carrying through so what actually happens with these smart City Visions um I'll talk about a couple of different harms that these that these attempts to create smart cities bring out the first is how smart cities can reshape Urban power and politics um I uh so to the extent that the smart city is revolutionizing urban life as it's often promised it will not be through you know whiz-bang technological solutions but by transforming the landscape of politics and who has Authority uh and governance power over the city city resources and public decision making two particular elements here that are important are surveillance and privatization so to start with surveillance much of the Smart City rests on data collection and uh one of the major interests for technology companies in developing Smart City uh tools and software is in the ability to collect data about the city collect data about people in the new environment and so almost every smart city project involves new types of data collection and this is true not just for projects that are explicitly about surveillance uh but also even projects that seem to have a more benevolent application often go down the road of becoming tools for surveillance so in San Diego several years ago the city partnered with a major technology company to develop a smart street light system where sensors would be embedded into the street lights to create new data that could improve traffic patterns we should not get much use for the purpose of traffic but the data ended up being used as a tool for the police department which is often the case here where police departments are gaining access to data and using it to surveil the public particularly minorities and protesters and low-income communities even when the Tool may have or the data collection system may have been implemented under a different expectation and so in San Diego they were using the the video camera and the sensors on these street lights to spy on protests including some of the protests in 2020 as part of the black lives matter uh protests that were that were going on following the murder of George Floyd um so surveillance remains a very pressing issue that is really present in all of these implementations another key element another key concern really about smart cities is privatization where uh it's not just that the technology is being developed by by companies by that technology companies are really attempting to gain more authority over what types of Visions are even promoted uh what types of decisions are actually made about public resources and so on the most notable example of this was the partnership between the city of Toronto and sidewalk Labs which is a company of alphabet the parent company of Google and so what they came up with was a plan for sidewalk labs to really be in control of the development of a neighborhood on the Toronto Waterfront and so sidewalk was not just given you know a contract to develop some technology but was given a contract really to become the Visionary for what this neighborhood should look like how it should be developed and so on and as the project uh moved forward it became clear that sidewalks intentions were much grander they were expecting to expand to a much larger region of the city they made claims even to be granted much of the the tax income that would be generated from this neighborhood sidewalk Labs expecting that they could have access to those resources and to the extent that they did community outreach it was relatively superficial uh you know Public public meetings where they would invite people in but really people were invited to talk about relatively superficial aspects of the program uh not making not being able to inform some of the larger decisions about you know who's even involved in this project how much data is collected what is it used for what are the goals and so on um and so one of the interesting outcomes there was actually that in Toronto local organizers were able to uh develop a pretty large Gathering of folks who were quite opposed to this project and in I think it was May of 2020 or 2021 sidewalk Labs actually backed out of this project um ending it and so there's a lot that we could say perhaps we'll talk about it in the Q a about what this project augers for the future of smart cities uh and the power as well of public resistance to these projects which is a really important angle to be capturing here is how is the public responding to these impositions of private control and new surveillance the other major concern that comes up with smart cities is how it promotes narrow approaches to reforming to attempting to solve deep structural entrenched problems uh where what often happens is that you know cities are facing concerns about racist and abusive police departments or the need to develop a better public transit system and then technology companies and technologists swoop in with a promise that their tools can solve these problems and sort of remove the need for more systemic reform so police departments have adopted various types of algorithms most notably predictive policing algorithms that attempt to respond to concerns about uh abusive police departments and racially discriminatory police departments with algorithms that can predict where crime will occur and supposedly take the human bias and discretion out of the decision making process and so often what these Technologies do is they provide an outlet where a certain amount of Reform can be promised but we've actually or the agencies and the municipalities are neglecting the need for more systemic reforms to their police departments or to the development and Improvement of their public transit system under the expectation that technology provides a relatively straightforward solution so what is the alternative that we can that we can hope for here what I call for is a need to shift towards uh smart enough cities and what the shift is really about is moving technology into a More instrumental role in thinking about how do we improve cities because I the the terminology of smart cities presents a very technology focused uh lens really to become a smart city or a smarter city is centrally about technology so talk about smart enough cities is to think about how can technology become an instrumental tool how can we use it how smart do we actually need to be to improve real world issues around Equity Transportation criminal justice and so on and so what this entails is a shift in some of the core principles of how we are actually approaching uh smart cities with smart cities as I've described we have assumptions of political neutrality we have assumptions that technology can provide a solution to all of our social problems and we evaluate these tools based on their technical capacities whereas in smart enough cities we move from an assumption of neutrality to a recognition of the politics of doing this type of work a practice of technological agnosticism recognizing that whether or not we use technology doesn't have value in and of itself what we should care about is is the technology actually beneficial or not and if it is that's that's great we can use it but if it's not we should be perfectly okay stepping away from it and our evaluations should shift from being focused on the technical capacities of the tools themselves to being really grounded in the real world outcomes that we actually care about so some of the key principles that this uh leads to um I tried to summarize this down so three key principles that I think are particularly important uh for doing this type of work number one is to address complex problems rather than solve artificially simple ones as the example of the the traffic light simulation showed it's very easy once we've artificially simplified a problem to create a really neat solution but in reality the real problems are much more complex and so we can't be expecting to have you know Perfect Solutions what we're really looking for is how can we help to address these problems and how can we do that recognizing all of their complexity the second uh principle is to implement technology to address social needs and Advance policy so really thinking about how do we put social and policy goals at the Forefront putting technology into more of a as more of a tool not the answer itself and then prioritizing Innovative policy and program reforms above Innovative technology uh and really here trying to decouple the link between Innovation and Technology when thinking about Municipal governance where we shouldn't be assuming that simply because a reform involves technology that it's Innovative and we shouldn't assume that just because of Reform is changing some policy that it's not Innovative we should be sort of decoupling those so I'll talk about uh if we had more time I would talk about an example from uh some of my own work in Boston with the Emergency Medical Services Division um really using data to improve how that department was actually responding to issues on the street uh shifting away from just assuming that the answer needed to be an algorithm or some sort of data Centric solution but instead using data to help to inform some policy reforms um but I won't go too deep into that for the sake of time make sure we get the discussion another example that is particularly pertinent uh in this talk is the example of the smart city challenge that Columbus uh went through over the past several years and this is one that I think exemplifies both the promises of these types of principles and also some of the challenges of moving this forward in practice so the story here is that the Department of Transportation launched a smart city challenge in 2015 with a promise of 40 million dollars to create a first of its kind smart transportation system and the winner of this challenge was Columbus and I'm sure many of you have encountered this and may know more about this than I do so uh and so you know definitely interested in talking about more of this in the Q a as well but what really struck me about Columbus uh the the plan that won was the novelty of it in terms of really embodying many of these smart enough principles unlike many of the other cities Columbus was not proposing a futuristic plant and traffic with autonomous vehicles but was really focusing on the connection between Transportation mobility and social mobility and more importantly building on work the city had already been doing uh where this already working towards how how to shift towards more dense development and mixed-use development rather than sprawl and how to improve conditions for low-income neighborhoods with high infant mortality where Health Care is often inaccessible and so the goal and the novelty of this this proposal was to really integrate technology into those plans that were already in place and then further as the as the team worked on this project they didn't just jump immediately to technological solutions even for those problems but actually went out and talked to the community to better understand their challenges and needs moving away from simplistic Tech Solutions towards other types of approaches that integrate technology reforms with other types of policy and programs that ranged from promoting better wi-fi in in low-income communities providing child care for uh these communities for so or for mothers to access jobs and Healthcare appointments on-demand rides for pregnant mothers and so on and so what what really struck me here is how the best way to avoid the simplistic and solutionist mindset fostered by Tech goggles is to really learn what barriers and challenges people actually face and to integrate communities as much as possible into that visioning process and that scoping process as uh as many of you may be familiar with the implementation of this program uh was really hard and faced a number of significant barriers that point to the the Gap and the tension between the Revolutionary tech-centric rhetoric of smart cities and the reality of how to make technology useful in practice some of the retrospective reports suggested that much of the initial technology uh proposals that was planned didn't end up getting as much use as was hoped for and the focus on marginalized communities was difficult to maintain in the face of flashier projects that also attracted uh private investment the when Columbus won this proposal there was a flood of new interest and new proposals from technology companies that may have overwhelmed some of the some of the planning as one of the individuals who led smart Columbus and the Smart City Vision described in a in an article it's not supposed to be a competition for who has more sensors or anything like that and I think we got a little distracted at a certain point and so there certainly was some movement on some of the more Justice and Equity oriented projects improve it including a pilot program to help pregnant women get on-demand rides to medical appointments as well as uh access to you know shopping and other things that they would need to do access grocery stores and so on but I think what we can see here uh or what I take away from this is both you know there was a lot of really exciting uh thoughtfulness and uh that embodies much of what I think of as a smart enough City Vision here but then also actually the the road from a great vision to implementation is really difficult and the pressures of the label of the smart city which inflates expectations and the uh the flashiness of the projects that will get more attention and particularly attract a lot of uh proposals and engagement from the private sector often detract and distract from uh some of these from some of these goals that really should remain front and center and really require the most uh the most development and the most active work to move forward because they are so hard and require getting across all of these barriers so happy to dig more into this uh in the Q a I think there'd be a lot more to unpack here um but to talk about the last two principles number four is to ensure that Technology's design and implementation promote Democratic Values number five is to develop capacities and processes for using data within Municipal departments so a few quick examples of what I mean by these uh one of the major developments in smart cities over the last few years and even really since I was working on the book has been more and more public backlash and public interest in uh creating better regulation for these Technologies not just allowing them to be used or embracing them wholeheartedly but putting in checks so that there would be public control over how this technology was used and really what technology would be allowed in the first place uh the ACLU has been a major player in developing what's known as surveillance oversight ordinances through its c-comps program community control over police surveillance uh and that that those have passed in many different cities and other some of these cities as well have also played fans on Police use of facial recognition technology and then for City infrastructure um you know I think one of the major things that all of the rhetoric on Smart cities completely misses is how the essential importance of basic data infrastructure and capacity it's very easy to talk about you know the the new City operating system and Big Data Solutions and sensors all over the place but what really actually matters is basic uh as a as a ground level for doing any work in cities is having the capacity through data management and access as well as actual staff within cities who are know how to work with data and know how to uh use data and to solve novel types of problems one really interesting project that I write about is in New York City they developed a practice of data drill so if you think about the fire drill from when you were a kid in school this is like a fire drill for how do we use data in an emergency and so the city would gather a bunch of different leaders together and say something like you know there's a blackout across Brooklyn and we need to figure out who to you know where to send the emergency vehicles who we should help first and they practice you know we don't have an explicit data set that just tells us exactly what the answer is instead we need to look across different data sets we need to bring together the information that we have that may be quite disparate across many different departments bring in the expertise of agency leaders as well as workers on the ground firefighters EMTs and so on and so they would do these practice exercises so that they would be able in an emergency uh or and just more generally for day-to-day projects to be able to uh you know solve novel types of problems for which it wasn't simple to just say here's our data set here's our answer because uh that's how many real projects actually go and in doing that they've built up much more capacity to move towards data science projects and analytics projects but at the foundation of that is data management and staff capacity to work with data so just to wrap up um you know I think that I see the the path towards smart cities as being at an interesting Crossroads I won't dig into each of these different areas but we've seen both significant pushback of smart City projects uh as well as you know efforts at governance um and efforts at regulation and I think really a central question now is where do where do we go where are the Smart City teams going where does a team like smart Columbus go from here and then more broadly where do smart enough City Visions go from here what is the sustainable role of technology in cities and City governance now that we've moved past some of that first phase of over hype and rejection of that um where do we go next so that's that's a really central question that I think about a lot and informs a lot of my work specifically with algorithms um and I think there's a lot for for all of us to discuss there so I'm going to wrap up there thank you all so much and I look forward to the discussion okay thank you very much Dr Green that was a very thought-provoking uh presentation and I want to encourage people in the audience to please submit your questions in the Q a box and we'll get to them in just a few minutes I think I'll start off with a couple questions Taking My Prerogative as Senator director and yeah so one thing I want to talk I want to talk about is you touched upon smart Columbus and I appreciate that kind of nuanced um view of it that you kind of resonates with my experience with smart Columbus one of the things about smart Columbus was that we we it was a public-private partnership and you know we talk about the Columbus way here in Columbus the way we have this unique collaboration among businesses and community and government and and Academia um does Tech does this smart City Tech approach is that kind of upset the delicate balance of that type of collaborative approach or is there something fundamentally wrong in these or fundamental tension in these public-private Partnerships yeah I mean I think that yeah technology really shifts the the bounds or the Dynamics within those Partnerships I think it can really you know it it's quite natural to for the technologists in those Partnerships and the technology companies to be able to have more leverage because they're the ones who who at least seemingly get to Define well here's what's possible here's what we can do here's what's on the table um and I think that you know it can be very hard for uh the non-technologists in those spaces to recognize what's Real Recognize what's not I mean if you think about self-driving cars pretty much at any point over the 2010s people were saying you know the self-driving car is going to be ubiquitous five years from now well we're well past that five-year window and it's not at all true and maybe the people at those companies believed that maybe they were just saying that as a as a matter of hype I won't try to you know parse that out but what the what the companies are promising is often not real or not not actually valid but it can be very difficult for uh you know organization City staff uh to to Really critique those and recognize uh sort of pull the center of gravity away from the tech centricness of it and I think it becomes especially easy for the broader Community to be left out of that conversation when you're thinking about technology at the start it sort of feels like well the technologist will tell us here's what we can do here's what's available and then we'll go from there rather than starting somewhere else that's ground found it in you know what do we want to accomplish in our city what are our goals and then you know we'll see if there's any interesting role for technology within that but subordinating the tech Focus so I think that you know I think these Dynamics are probably true across many different areas but I do think technology just shifts the balance a little bit okay good um I want to ask you know I'm glad you showed that a Thomas field called traffic simulation I use that in some of my talks and lectures right well because it is a very good example of abstract creating a simple problem for a more complex problem but I know if I remember correctly that's from MIT media lab so that came out of a science that came out of Academia so I want to ask about you you talk about tech goggles um where does that come from I mean for for the last century of urban science we've been talking about these Grand models and talking about how to optimize cities and how to make cities more efficient you know is some of the some of the fault here with are there are there science goggles I guess is what I'm saying that where the tech goggles come from and what do we do in Academia as Educators and researchers to kind of get Beyond these uh these science goggles in which we approach cities yeah I think I mean this is this is a huge question I mean the history of it I I I I can't totally pull out but I think it is really I mean I think it's it's worth looking both at the the pedagogy side and the industry side uh I mean in pedagogy yeah I mean computer science for instance it's very much the way that we're taught to just focus on models to describe how technology can solve all of the problems I mean engineering is very much a discipline that teaches its its students to solve all problems with technology there's very little practice of humility recognition of limits and so on um and then of course the technology industry you know wants us to view the world through that way through that lens because that you know makes it easier for them then suddenly the products that they uh will provide you know some big data solution appears like a more natural way of dealing with things but you know this is not a view that is uh you know unique to even modern technology one of the interesting things and I briefly touched on some of the those earlier 20 20th century Visions I mean in uh you know Laker busier writes about how you know being up in the air on a plane provides a new lens on cities and you can sort of see that how it led to this very uh a type of Urban Design that would have a very neat organized top-down structure if literally viewed from a plane but obviously had lots of problems when that was actually developed in practice so I think there's always on some level you know some hype around science or technology as providing a way to solve social problems because as we you know within the Natural Sciences it is so nice to be able to you know look within a particular lens and you can come up with these Solutions and I think it's just very it feels very natural to then want to say well why can't we do this for social problems why can't we move that into the the sociological or the political realm um and and I think that's a real a real issue I mean in terms of pedagogy one of the real shifts that that I think is important is really grounding our assumptions about what makes a good technology say a good algorithm be grounded in real world impacts um I think it's so easy for technology you know in computer science you learn how to develop an algorithm and you evaluate that algorithm based on its you know formal technical characteristics and so computer scientists will then go to cities and say you know you should develop this algorithm that will provide advice to a welfare agent and here's all of its great properties but they've never tested what it actually does in practice they've never tested well how does the human collaborate with this algorithm how does it actually affect decision making in practice they just assume that they can sort of take formal evaluations and those will work in practice so I think grounding the uh practice and sort of forcing students to work on more real world cases and recognize that what makes it good if you're developing an algorithm to improve child welfare what makes it effective is not that it makes accurate predictions but that it actually improves child welfare decisions and there's often a very large gap between a good model that makes good predictions and a model that will actually improve the decision-making process in practice and so I think grappling with that provides a way to a way into starting to to move away from this lens where you know you're forced to confront the gap between the Simplicity of the tech goggles View and the complexity of the real world right very good um I want to ask one more question then I'm going to turn it over to Jericho Logan who's going to field some of the audience questions but one of the things you hear about you know smart cities and really these uh public-private Partnerships and bringing Tech firms and other firms into into um into into our governance and how we up how we run cities is we hear you know that government is very slow and hard to innovate meanwhile we have tent companies that basically can can try things and see what works and what doesn't work um I want to talk about a bit about that tension or it's asked about that tension between the Silicon Valley View which is to move fast and break things versus the need for us to be um you know you know safe keeping our responsibility to the community just recently here in Columbus we had a Tesla go into the side of our convention center and caused uh six hundred thousand dollars worth of damage and we were very very lucky there weren't lots of people killed and you know we we know that Tesla's notorious for shipping buggy driving software and then collecting data on our city street so I mean one argument we can make and is that well you know um you have to break a few eggs to make an omelette so maybe we should allow some of these things to occur um what do you think about the utilitarian argument that somebody might push back and say well these things are going to happen but eventually things will work out better well I think that's a very big assumption to say well eventually things will work out better right um I think you know Tesla is a great example where yeah we're always promised these these cars uh whether Tesla or other companies will be ubiquitous and we'll be driving everywhere and everyone no one will own a car anymore and everyone will just you know ride share on autonomous Ubers things like that um you know the those those projects are very far away from being possible and I think one of the the issues is I think even through a utilitarian lens you could start to say well we don't actually know that this will be safer or you know the point in time when this will be safer is so far down the road we shouldn't stop doing other things because of it I mean a number of cities were disinvesting in their bus systems and saying well we're just going to start doing a public-private partnership where we pay Uber to uh you know to provide rides um you know we can obviously you could talk more about the labor conditions of you know some of these companies and how they operate but uh you know I think it was also like we're now actually in a moment right now where these companies are not doing well you know Google and Microsoft and Amazon are not are doing Mass layoffs they're not hiring at well and you know what one thing that uh folks in cities would often say when I would talk to them about some of these issues they're like you know a city can't fail like a city or I mean it can't but it's like this is the stakes of a city failing or going bankrupt or much higher you know we think of it's easy to see a company as uh persistent but you know many of these company Ubers losing tons of money right like it's not actually a sustainable company and so we need to be mindful of the there is a real commitment to a long-term trajectory or long-term sustainability that cities need to need to have and I also think that type of uh you know assumption I think discounts the ability of governments to innovate again in ways that aren't just about technology I mean certainly I think there are ways to improve that and make cities more able to try out new types of Pilots around programs and services and all of that but yeah I you know I don't think that there's sort of uh you know I think we should resist a binary of you know the technology industry is providing productive Innovation and if you're in a city all you're doing is you know boring stagnation okay I'm gonna turn over to Jerrica now is going to field some questions from the audience so we have our first one here um what are your thoughts about community members contributing to the smartness being additional sensors helping with the interpretation of the analysis or of the of the data and they're able to access with the data streams so what would a community member's role be yeah I mean I think I I sort of think about community members role in a couple of different ways I mean I sort of push against the uh you know the idea that okay smartness just means you know getting more community members involved in becoming smart or sort of being smart citizens because I think as we Center these even if we try to do these pivots we're still centering an idea of smartness as technology that you know we can have uh you know that we're yeah we're assuming that the technology is the answer and well maybe we bring more of the community into that um and you know I think there maybe are are some Partnerships where that that becomes possible but there are a lot of challenges too um you know one of the uh things that uh you know one of the Realms where this comes up is around 311 apps which is a way of really trying to leverage the public as uh sensors that are collecting data about the city but there are a couple of challenges that come up with that data actually in practice um so in Boston we worked on uh analyzing some of this data and for for sidewalk uh complaints and what we found were two issues one the number of complaints that were coming and about sidewalks on the 311 app where uh far too many for the city to actually deal with it was kind of an overwhelming amount the distribution was quite heavily biased and this is often what happens when you uh you know hope to rely on the public to provide this type of information uh there's far more input coming from uh well-off neighborhoods primarily white neighborhoods and far less input coming from the lower income and more minority neighborhoods but then also we found that the data was actually not super reliable that the the reports of where the city needed to be going and repairing sidewalks did not align at all with some of the more the other types of Assessments that the city had done at a more you know Global level on that so we found that actually you know although this approach has a lot of theoretical promise in practice it's it can be very misleading and can sort of create a strategy where or create a an outcome where you don't really have any thoughtful strategy of you know how you're balancing the priority of streets based on their location their neighborhood Equity concerns and so on um and so for me I I'm more I'm really interested in the role of community members in shaping these projects more broadly you know I mean one of the more one of the most interesting sets of developments in smart cities has been driven by communities in Toronto and San Diego and Seattle and other places organizing together and demanding that they have more control uh and say in what types of projects are pursued how technology is used and so on and I think that in a way more than anything has uh shifted a lot of the expectations and next steps around where smart cities go um but unfortunately those those Visions all had to be or those those efforts all had to be a matter of resistance you know not uh being able having to revolt essentially or maybe that's a little strong but object to having been excluded and being so upset about facial recognition plans or sidewalk Labs taking over a neighborhood that you push back and I think the real question is how do we ensure that these processes are inclusive and Democratic from the smart from the start uh and that's really the role that I want to see for community members here thank you um I think we have a couple more minutes left so we'll get to have one more um the next one is going to be um thank you for your uh presenting what are your thoughts on public ownership of these smart tools um yeah um I think there's there's a lot of uh yeah I mean I think that generally I I am interested in how to increase public control over these tools and I think public ownership is a model that could be quite interesting one of the there's a partnership in uh you know one of the interesting types of smart City programs that that I can trust is between so in New York there was an effort to develop sensors uh with a link NYC program that was developed uh again sidewalk Labs comes up again uh very involved in that Chicago had a program that uh for sensors for environmental conditions and so on that was a joint project between Argonne National Lab and NSF and uh and other other uh organizations in the city of Chicago and so on and so that really was a combination of you know Municipal ownership and sort of the scientific community of the NSF and so on um and I think in that program what we were what what was able to see was because there wasn't as much incentive for the program being grounded by you know advertising and data collection about the public there was much more ability to a focus on important questions around environmental equity and so on and also to actually engage the community in a much more inclusive way around privacy to be able to actually take data minimization steps and so on because there was the goals were more about uh you know Community acceptance and Community benefit and so you know there are obviously a lot of challenges around I think the real challenge here is around investment right how do we make sure that if we are going to move more in that direction of public control that there are sufficient funding and resources to actually push forward on these projects and that's often where there's a sense of well the only way forward is to work with private companies so I think there are you know deep questions here um and sort of a lot of what we could characterize as dynamics of the Smart City are dynamics of austerity where cities are operating and trying to make the best of what they can under a situation where they're very low resource and that provides the leverage for technology companies to come in and say you know we have a solution to spread your staff a little bit further because you're so limited or we'll provide you a free trial of all of our facial recognition sensors if you just let us deploy them and we'll provide you some insight so I think the the resource issues uh again are something that really shift that balance really disempower municipalities from being able to take considerations like equity and privacy into account as they pursue these projects foreign okay I think we're at the top of the hour now so I'll have to call it an end but uh thank you very much for the thought-provoking talk and the uh any and the answers to our questions and um people in the audience please uh keep in touch with Kira go to kira.osu.edu follow us on Facebook follow us on Twitter I think we're also looking at Mastodon right now uh but but you cannot there's many ways to keep in touch with us to hear more about our events and activities including on February 10th when we'll have uh Jeff Boeing show us some amazing things he's doing on an urban on a global scale with comparing cities with big data so take care have a good weekend and um be well thank you all very much really appreciate it

2023-02-02 18:32

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