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Episode 03

Ben Green is the author of The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future (Cambridge, MA: MIT Press, 2019). He is an Affiliate at the Berkman Klein Center for Internet & Society at Harvard and a Research Fellow at the AI Now Institute at NYU. Ben studies the social and policy impacts of data science with a focus on algorithmic fairness, municipal governments, and the criminal justice system. In this episode of The PFF Podcast, Ben and Jeffrey discuss the powers and limitations of the "smart city" approach to urban design, emphasizing what Ben calls "smart enough" alternatives that leverage the power of technologies in the service of a holistic vision of social justice and inclusion.

Transcript

Welcome to the Piaggio Fast Forward podcast. Join the conversation by subscribing to the PFF podcast at https://www.piaggiofastforward.com/podcast.

Jeffrey Schnapp

Welcome to the PFF podcast. I'm your host, Jeffrey Schnapp, Chief Visionary Officer at Piaggio Fast Forward, and it's my pleasure to welcome Ben Green. Ben is a PhD candidate in Applied Math at Harvard, where he's also pursuing a secondary field in Science, Technology, and Society. I first became aware of Ben's work, thanks to his affiliation with the Berkman Klein Center for Internet & Society. Ben studies the social and policy impacts of data science with a focus on algorithmic fairness, municipal governments, and the criminal justice system.

Jeffrey Schnapp

His book, The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future, was published in 2019, by MIT Press. Welcome to the PFF podcast, Ben.

Ben Green

Thanks so much. Excited to be able to chat with you today.

Jeffrey Schnapp

So a great place I think to start would be, particularly for people who don't follow the kinds of debates that have been going on in the urban design and urban planning and municipal government space, to say a little bit about what we understand when we evoke the term "smart city" and then maybe from there, we can move to the “smart enough city,” which is your critique and counter-proposal.

Ben Green

Yes, the smart city is an idea that has really emerged over roughly the past decade. And the way that I think of it as a heuristic is that, when we say smart city, what we mean is the same as what we say a smartphone or a smart home or a smart toaster or a smart toothbrush. The word smart is evoking this idea of taking an analog object or process, and providing or installing digital infrastructure, digital technology such as an internet connection, artificial intelligence, algorithms, apps into the structure.

Ben Green

So smart cities consist of a sort of, constellation of different technologies that different cities use within this idea of the smart city from self-driving cars to algorithms that predict outcomes such as crime, and public health outcomes to sensors on urban infrastructure such as trash cans and street poles that are trying to understand environmental conditions, understand the behavior of people that are within that city and apps that are connecting people to one another, or connecting people to their city government, providing information about conditions within the city.

Ben Green

So for all of these, the smart city embodies this idea that with new technology, we can solve long standing urban problems and create these sort of utopian optimized, efficient cities. And the project and the book is really to critique this vision. And I do that under this frame of the idea of the smart enough city. What I'm saying ultimately is that the point is not to reject technology, to simply throw it out and say all of the technology is bad, but to fundamentally reorient how we're approaching this process of improving cities with technology.

Ben Green

Rather than striving for a smart city where fundamentally the goal is to have technology and to view technology as the end in itself to a smart enough city where we are recognizing the role of technology but only in as much as it's enabling us to achieve other social goals.

Ben Green

So this idea of smart enough rather than being the end of the conversation where something like smart would be, you're prompting this question smart enough for what? What are we actually trying to accomplish and smart enough puts it towards this other end that technology is only in service of?

Jeffrey Schnapp

Given that your current work is in the field of Applied Math, which would seem more to align you with the smart city rather than the smart enough city, how did you come to this critical position vis-a-vis a kind of technocentric approach to the future design of cities?

Ben Green

It really was sort of a journey from starting out, not quite in a techno-utopian smart city space, but from the perspective of I'm a technologist, how can I apply my tech skills to urban problems? And I worked as a Data Scientist for a year. I was on staff in the City of Boston, but also worked on research projects and applied projects in Chicago, and with the city of Memphis, and with other cities I advise on some policy as well. And what I increasingly saw through these efforts was that the barrier to the success of actually achieving better social outcomes was not really about the technology. It wasn't about me coming in and developing the right algorithm, or if it was that was only a very small piece of the project.

Ben Green

There were questions of data governance. What sort of data is collected? Is it in a format that's actually usable? Is it managed and collected in a way that's considerate of public privacy? What sorts of policies are being implemented based on the insights from an algorithm? Are we using the predictions of a machine-learning algorithm to arrest people, or are we using the predictions to go provide help and prevent people from having a mental health crisis?

Ben Green

All of these broader questions ended up becoming really central, and it was really, I think the key for me being able to have those insights was in a sense just having a focus on the social impact. Really approaching my work from this question of “What is the impact of the work that I'm doing and how do my actions connect to impact and what are the barriers to impact?” And I think there could be a simplistic view among a lot of technologists that you develop the algorithm and you never really questioned whether or not it's going to be effective. And I think just by rigorously thinking about what are the impacts and how do we understand the problem I'm trying to help solve, and what are their causes of that problem, and is this technological work actually addressing those causes.

Ben Green

Just sort of doing that thought process increasingly led me to a point of realizing that the technology on its own was going to accomplish very little and might actually make things worse in certain ways.

Jeffrey Schnapp

What I find particularly compelling about the point you're making, and the scope of the argument that you make in the book is the attention to complexity, the way in which these solutions flatten things out, simplify, abstract. And much of what you just I think underscored in your response seems to draw our attention instead towards the specificity of a given landscape, of a given history, a given community, a given city, a series of political or ethical ideals rather than imposing upon all cities a uniform set of solutions that are equally applicable in Bangladesh as they are in the Island of Manhattan. And I find that appealing because it's also an invitation to think, again, about the question that you asked which is smart enough poses the issue of for whom? For what purpose? For what end?

Jeffrey Schnapp

And that seems to me like a powerful corrective to some of the patterns in the book you bring out the close connection between certain even architecturally-based ideas that belong to the earlier 20th-century history of urban planning, and these current ideas about smartness, about making the urban landscape smart.

Jeffrey Schnapp

How did that architectural backdrop enter into your own thought development process? Was that present from the beginning, or was that just a kind of extension of your immediate experience working in different municipal realities? Grappling with data and data solutions to urban problems?

Ben Green

It wasn't exactly the starting point. My background is in, I'm not an urban theorist or an urban scholar by my core background, but I did take a lot of urban planning courses in college. And so increasingly, as I read about sort of the perils of smart cities and really got into the mode of this smart city thinking, I began to have sort of flashbacks to the things I had learned about from Le Corbusier and others and saw a lot of really intricate parallels and interesting parallels between those two in the terms of the fundamental mode of thinking and a few other people such as Adam Greenfield have written before me that the connections between these different lines of thinking, within architectural history.

Ben Green

But it really does connect to that point you were making about complexity. And I think in many ways the parallel we can draw, and that I do pull out a little bit towards the end of the book between these different eras and urban planning, urban governance history is about simplicity. It's about, how do we flatten the urban ecosystem into something that can be understood scientifically from a very particular perspective. And I'm really drawn to how Le Corbusier was deeply inspired by this idea of viewing the city from above, from an airplane, which was the new technology of the day. And he actually wrote this short book, I think entitled Aircraft; it's a bunch of pictures of planes and of cities seen from planes. And there was this sense of how that led him to this sort of master narrative and vision of what a city could be. Today, we have a very similar narrative. But rather than being the perspective from a plane, it's the perspective of a data scientist analyzing a bunch of sensor data about the city.

Ben Green

So that lens itself is very different. But there's a sort of through-line of a technological approach to understanding cities. And that you know one of the core motifs I pull through the book is this idea of tech goggles, which is very much how does a technologist view society and is all about this flattening of taking a complex world or complex social problem and turning it into a relatively simple technological problem.

Ben Green

And this is actually something that my work, since the book has continued to think about specifically within algorithm design and how any mode of reasoning and epistemology requires some type of formalism and abstraction, and how do we grapple with the particular challenges of any of those methods and begin to recognize the limits of any form of abstraction to be able to grapple with or interrogate what we're choosing to leave out. What we're choosing to keep in and whether or not a particular mode is actually appropriate in a given context.

Ben Green

Algorithm design and other forms of smart city technology are perhaps just particularly unreflexive about these questions. Not, rather, than questioning these things sort of takes for granted that algorithms can be applied to every situation and can make that situation better rather than recognizing the many things that that can leave out. And whether or not we're thinking about technology, the idea of solving any problem within cities is almost nonsensical, right?

Ben Green

And the idea of solving requires you to oversimplify. You're not going to just solve poverty, or congestion, or inequality, and not from a fatalistic perspective that you can't remedy those problems, but you're never going to have a single tool that just solves that problem the way you might be able to have a... You can solve a picture falling off a wall by putting in a hammer, putting in the nail with a hammer, or solve a mathematical problem just by working through an individualized truth.

Ben Green

So whether it's thinking about a public policy intervention or a technological intervention on approach that starts from how do we solve X problem is almost guaranteed to fail because to solve complex problems requires oversimplifying them.

Jeffrey Schnapp

Indeed, and I think if you look at long-term patterns of urbanization and the projected growth of megacities over the next 50 years, what certainly strikes me as a cultural historian is a kind of asymmetry between the kinds of cities that we're going to have to grapple with. The Dhaka’s of the world which will present overwhelming infrastructure problems that we can hardly imagine today, but certainly not the kinds of smart city questions that have prevailed in the debate and the discussions around the kind of current major cities, many of them centered on transportation systems like self-driving cars.

Jeffrey Schnapp

I was wondering if you might say a few words about your view of the role of self-driving automobiles in the future urban landscape. I mean, certainly, a lot of the hype cycles over the last decade or so have been built around this expectation that somehow the automobile centered city of the 20th century will continue into the 21st century. But now minus the human agency of the driver behind the wheel. How do you feel about that narrative with respect to this larger critical engagement that you have with the smart city movement?

Ben Green

I think this question of self-driving cars and mobility is one of the most fascinating and maybe enlightening case studies that we can look to, to really understand what the smart city is and what the problems with this vision are. So right, we see a ton of excitement around self-driving cars today. And in some ways that excitement, I think, may have been more sharp three or four years ago when I was writing the book than it is right now. It seems to have tapered off a little bit in terms of our utopianism. And what was remarkable about it was that we'd see these self-driving cars, and there'd be stimulations, there'd be lots of hype and almost always it would show these traffic patterns of, we can reduce congestion. We can eliminate red lights, this idea that well now we can just have self-driving cars that zoom through downtowns, that don't have to stop for red lights, will reduce congestion and it'll be so much more efficient to get from A to B.

Ben Green

There are just so many flaws with this vision. There are sort of traffic engineering level flaws around just the actual dynamics of traffic from induced demand to this idea of cars that are driving around empty to pick people up and drop people off. So there's, first of all, a question of whether or not the city of ubiquitous self-driving cars could even reduce congestion to the extent that is promised. But then there's this larger question of like, "Why the heck are we suddenly having this vision of cities that's just around self-driving cars, getting us from A to B as conveniently as possible?"

Ben Green

We sort of slowly over the last few decades moved away from the very highway, automobile-centered model of urban design, and much more people are moving to down to city downtowns, people... A lot of cities are thinking much more holistically about urban design. And suddenly there's this moment of retrenchment of moving back to, "Oh, well, now we have this really convenient automobile technology. So we have to just follow that, and we have to implement that in all of these cities."

Ben Green

So there's almost this more fundamental danger around how smart city visions actually shape our imaginaries for the future. They shape what types of city we want to create and what we want to live in and what values we see as the core values, where suddenly we're viewing this idea of traffic flow efficiency as the goal. And in by doing so failing to ask the questions around how do we make livable cities where people don't need to get around by automobile? How do we make it so that people can walk so that we have denser urban design so that we can have efficient bus routes and train routes and invest in that infrastructure?

Ben Green

And so, one of the... and this is something that runs throughout smart city efforts and across a lot of domains, is that by optimizing existing systems, we fail to ask and actually completely ignore the broader structural questions about how did we get into this situation and what are the larger types of social and policy reforms that can get us out of it, or at least push us in a better direction. That's not just a more efficient version of what we have now but as a fundamentally re-imagined version of what we have now.

Ben Green

The other pieces that are really interesting about this self-driving car vision is also just how much it really highlights the stakes of corporate lobbying and privatization within city governments where all of this technology is developed by major tech companies like Google and Uber, and there's a huge amount of PR and lobbying to get those onto city streets even for testing. And there have been cities that in lieu of investing in public transit have made partnerships with Uber, for example, to provide rides to people as a new form of public transit in a sort of emaciated way.

Ben Green

And so rather than thinking about “how do we provide public infrastructure,” these cities are turning towards a public-private partnership model with a tech company that it should be noted is losing billions of dollars a year. And it's not even necessarily sustainable as a business, let alone all of the other flaws with it, and they're interesting historical parallels as well to the dawn of the motor age. So it's a great case study.

Jeffrey Schnapp

Yes. In that regard, I'm curious if you might share some of your thoughts about the Sidewalk Labs project in Toronto. Maybe not a failing company like some of the other ones you were alluding to a minute ago, but certainly a controversial project that imagines itself in a sense as going beyond some of the limits of the early smart city movement, but controversial nonetheless.

Ben Green

So this is a project where Sidewalk Labs, which is... It's essentially an Alphabet company, Alphabet being the parent company of Google, having this partnership with the city sort of a Toronto Municipal Agency to develop a waterfront neighborhood. This was announced, I want to say maybe 2017, around then, and has been really quite controversial from day one. The project has moved forward step by step and there's been very little genuine public engagement. The public engagement that has occurred has, by all the accounts I've heard, been sort of more of corporate PR than anything that would resemble deliberative democracy.

Ben Green

And I think of the Toronto case as sort of a bellwether case for what the future of smart city projects will look like and what the politics of smart city projects will look like. When you hear Google is trying to develop your city, the first concern obviously is about privacy, about How is Google... what data are they going to be collecting? Who has a right to shape that data collection? Or are you just by de facto consenting to pervasive data collection by living in this Google neighborhood? And those are absolutely correct concerns to have.

Ben Green

What I think is also really good though, is that over the last year the conversation has shifted to being one just about privacy to being one that's fundamentally about privatization, and about the privacy just being the tip of the iceberg of this question of What happens when Google, which is just the... Or Sidewalk Labs, but is a private company that is not in any way elected, has no public accountability, is making decisions about infrastructure, about who to work with, and what sorts of policies or infrastructure or designs will be in place?

Ben Green

So there are a number of efforts to block this project. There's a lawsuit from the CCLA, the Canadian Civil Liberties Association, and I'm an expert witness for them in that case against waterfront Toronto. There is a community advocacy group called Block Sidewalk that's been pushing to prevent this project from moving forward, in particular citing the lack of really a public mandate for this project to move forward. That there's never been enough broad public conversation and certainly not support from the community for the project. And it's very much up in the air. I think whether it will go forward and how much of the original plans will end up being implemented.

Ben Green

And the last thing that I'll say on it is that it's also an interesting case of What are the political... What's the political landscape around these projects? And I think that's such an important place here because a lot of smart city projects are, well, yes, there's a huge, where a lot of city managers and leaders are interested in efficiency and optimization and making their services work better, even if they're maybe have a misplaced faith in technology for that.

Ben Green

There's also a large component of this where the technology is a stand-in for a sense of progress and reform. Where a city mayor or a police chief can turn to technology and say, "Look, we are doing things better. Isn't this going to be great, vote for me or get off my back and stop scrutinizing me,” and all of that.

Ben Green

So what's particularly heartening to see about this case is that in Toronto is that the landscape is shifting where sort of getting into these poorly thoughts out projects, handing over huge amounts of data and power to massive company like Sidewalk Labs, is no longer going to have the types of easy political benefits that a lot of leaders would have expected it to have even three years ago.

Ben Green

And so I think even just that can put a lot of pressure to make people think differently about how cities move forward on this stuff.

Jeffrey Schnapp

So if you were to imagine a positive counterpart that comes to mind immediately of how to do things right, that gives us our listeners a sense of what a smart enough city approach would be. Is there one in particular that comes to mind, kind of exemplary project or endeavor that's ongoing or that for you as a kind of model of excellence?

Ben Green

Yes, and I pull out a couple through the book, and I think one thing that's notable about these examples is that none of them are at the scale of something like a Sidewalk Labs project in Toronto. None of them are these massive citywide efforts but are more targeted, then that's sort of by the nature of how these projects work, which is you're not going to have a single platform that's going to solve all their problems. It requires a much more detailed appreciation for the complexity of these problems.

Ben Green

So since we were talking about self-driving cars, I'll talk about the example, the case study that I talk about in the book and that chapter, which is about Columbus, Ohio, which in 2016, or so, won a grant about $40 million from the Department of Transportation, which is really a smart city's transportation grant. And what was notable about their application was that rather than focusing on self-driving cars and this sort of end of congestion type vision for the future of cities, it was their proposal for what they wanted to do with that money was really focused on, how do we address issues of social mobility through the lens of transportation mobility?

Ben Green

The city had long been focused on issues of lack of access to healthcare, particularly issues of prenatal healthcare and infant mortality in some of the lowest-income neighborhoods in the city. And so that was a major concern. And then the other piece was that Columbus had also undergone an urban sort of development visioning process to say, "What do we want to look like in 2030 and 2050," and fully realized they needed to move away from a sprawl centric automobile-centric vision of urban development.

Ben Green

So here we can see sort of this great example of what a smart enough approach looks like, where they already had long term plans from a design, urban planning perspective. They had particular problems that they were trying to address, and then thought to themselves, "Okay, well, here's an opportunity. How can we leverage technology to specifically focus on these goals?" And in doing so fully grappled with the complexity of these problems. Actually went out to these neighborhoods with high infant mortality rates and talked to the residents there to say, "What are the challenges that you face in accessing healthcare, accessing employment, and let's think holistically about how we can address that." And what they found was not the need for some super flashy fleet of self-driving cars, but were things that ranged from providing better WI-FI infrastructure to providing better access to information about public transit schedules that were accessible. There was an effort to improve on-demand ride accessibility.

Ben Green

But then they also talked about providing childcare to moms who needed to get to a job interview or a doctor's appointment for a newborn baby, for example. And so by doing that, they even reflected to me in interviews about how they were able to have this much more holistic understanding that would never have been possible if they had sat in a boardroom with a bunch of community leaders and thought, "What can we do with this technology?" So this starting point of understanding the real problems that real people face in their full complexity and then thinking about how you can engage with those, I think, is a really great model from both the design perspective and in this specific case, from a social welfare perspective.

Jeffrey Schnapp

The Columbus example is great because it crystallizes one of the strongest takeaways from the book that certainly I'm going to make use of in some of the things that I do, which is in your final chapter, you have these five essential principles, these five recommendations that are at the foundation of the smart enough city sort of counterargument, the smart city. And I'm wondering if you could just recapitulate those briefly because I think they're so valuable.

Ben Green

Yeah. So the first one is exactly that point of addressing complex problems rather than attempting to solve simple problems. And I've already talked about that. The need to start from a place of policy reform and social reform rather than viewing the technology as the reform in itself. Essentially prioritizing policy innovation over technological innovation. There's this sort of false idea that innovation is A, always good, and B, always involves technology. There's lots of technological innovation that is quite socially harmful, but there's also lots of great innovation that's not about a new algorithm or app, but is about a new way of bringing organizations within a city together or having a particular policy for how to respond to a social challenge so centering that type of reform.

Ben Green

One of the others is about centering democratic values in the design of technology. So a lot of what I was talking about, for example, in the Toronto case, is less about the explicit function of this algorithm does X, and that's bad. But the architecture of who owns technology, who controls that technology, who gets to have authority to govern that technology.

Ben Green

So these questions of democracy are absolutely central, not just in how do we apply technology to help our democracy? Or how do we worry about the implications of technology for our democracy? Even if you think about something like social media, but how do we actually ensure that our technology is democratically governed? So these questions about algorithms and transparency and privatization are absolutely central to understanding the shifts in power that are related to smart cities.

Ben Green

And the last one, which we haven't really touched on here, but is this focus on the operational aspects of really focusing on the internal infrastructure and mechanisms to make data use possible within cities. So one of the... a lot of my work when I was a data scientist for example, with the city of Boston and what has enabled a lot of cities from New York to San Francisco, to Chicago to actually use data effectively has been bringing in data scientists and developing a practice and a culture and an infrastructure for using data as part of their daily operations.

Ben Green

So having, moving from a process of totally disconnected paper sheets and Excel spreadsheets to an infrastructure of high-quality data that people can access. And then actually finding ways to get different departments to begin working with data and trusting data and using that both even relatively simple things as a guide for what they should be doing, but also then beginning to turn to data science to make better policies and have better behavior from preventing people from being unfairly evicted in their homes to improving the ability to identify unsafe conditions in restaurants, unsafe unsanitary food.

Ben Green

So actually achieving those outcomes requires not buying some off the shelf technology that does everything for you, but building a culture and an internal infrastructure to make all of this possible.

Jeffrey Schnapp

That's a really valuable synopsis of what you lay out in much greater in that final chapter of the book. As you probably know, Piaggio Fast Forward, we're a mobility company. We're trying to create the infrastructure for what we view as the model of future mobility that we feel should be at the foundation of the design of future cities. And this is a value judgment in our case, we think that walking along with bicycling along with other light mobility, micro-mobility vectors, is really essential to the quality of life. And therefore, we're engaged in a kind of critical role in a series of critical positions vis-a-vis the kind of automobile centered models of the future of urban development.

Jeffrey Schnapp

We're not data scientists, we're roboticists, but roboticists with a very strong urban design ethos as well as a deep set of beliefs in the importance of civic space. I guess I'm wondering if there's any particular advice you would have for people like ourselves who are trying to create vehicles that enable and support human behaviors that we believe are aligned with the pursuit of precisely some of those values you are articulating in your five essential principles, particularly the democratization of access to mobility, the freedom to move without being in a surveillance regime. The notion that citizens are the protagonists of the urban space not just passengers being moved around like cargo.

Jeffrey Schnapp

And I could go on, it's a long list, but I think we're in the domain of philosophy, ethics, social values not just in the domain of technology in any case. And I'm curious from a data science perspective, what advice you would give to people like ourselves.

Ben Green

Well, technology is philosophy and ethics and social values in and of itself. So, no need to distinguish those things. I mean, it sounds like obviously, you have a good approach to thinking about these things. I love this idea of the urban dwellers as protagonists and not passengers, and I think finding ways to really live that through in having, letting, providing ways for people to shape the designs of what you're doing, shape the visions of what you're doing and feel like they have some form of ability to co-create with you and not just consume whatever you're putting forward.

Ben Green

And I think the one other piece that I think is really important for any technological design that's connected to social change is to envision social and policy changes alongside the technological change. I think we often, one of the reasons that we get into this failure of optimizing to the status quo is precisely because technologists will treat the world as sort of this fixed constant thing, and then a new technology that can come in and intervene within that. Yet as I describe in the book and the Columbus example is a great case of this, that any type of effective reform, even one that does involve technology also has policy, and policy and other types of reforms happening alongside in lockstep or in conjunction with the technology.

Ben Green

So thinking not just about what type of vehicle is useful today, but how do we get to a place where the type of vehicle that might be desirable in five years is possible. And how do we think holistically about... it's not just about creating that physical piece of technology, but also creating other types of policy changes or other types of social values or norms that will push us towards that world where that type of vehicle is even the one that can be possible.

Ben Green

So thinking about how all of this is in flux is, it's sort of hard to grapple with all at once, but seeing the whole world and all of these dimensions are contingent and flexible. And we can get much further if we envision multiple movements along multiple dimensions at the same time.

Jeffrey Schnapp

I really welcome your conflation of the technological and the cultural and the cultural and the technological. Because I think so often we live in a culture where this kind of C. P. Snow, two culture's idea continues to justify a kind of false dichotomy, but a false dichotomy that informs a lot of reasoning that happens within public debates, over all kinds of aspects of civic life and even everyday life.

Jeffrey Schnapp

Ben Green, thank you so much for participating in this conversation. I want to remind our listeners that Ben's book, The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future, is out with MIT Press. It came out in 2019.

Ben Green

Yeah. Thank you so much. And I'll also just add the paperback just came out this month, and the book is also fully available online to read for free open access from MIT Press. So, it's readily out there in the world for any interested readers. But thank you so much. This was a really great conversation. I enjoyed it.

Jeffrey Schnapp

Thanks to you, Ben.

Thank you for listening to the Piaggio Fast Forward podcast and come back soon for further lively conversations about walking, light mobility, robots and the design of neighborhoods, cities, and towns. The PFF podcast is hosted by Jeffrey Schnapp, sound engineering by Robert Allen, narration by Ryan Harms, produced by Elizabeth Murphy, web designed by Jerry Ding. Intro music is Funkorama by Kevin MacLeod. End music is Your Call by Kevin MacLeod. Special thanks to Tory Leeming. To learn more about PFF and gita, please visit piaggiofastforward.com.