In this episode we chat to Karen Levy, Associate Professor of Information Science at Cornell University and author of Data Driven: Truckers, Technology, and the New Workplace Surveillance. Karen is an expert in the changing face of long distance driving - she spent ten years doing research with truck drivers. So she’s been looking at how surveillance and automation are changing what it means to be a trucker in the USA. We talk about how truckers are responding to new AI technologies monitoring their behaviour, and what the future holds for the trucking industry. We recorded this a while ago so it’s an audio-only episode.
Karen Levy is an assistant professor in the Department of Information Science at Cornell University, and associate member of the faculty of Cornell Law School. She researches how law and technology interact to regulate social life, with particular focus on social and organizational aspects of surveillance. Much of Dr. Levy's research analyzes the uses of monitoring for social control in various contexts, from long-haul trucking to intimate relationships. She is also interested in how data collection uniquely impacts, and is contested by, marginalized populations.
Dr. Levy is also a fellow at the Data and Society Research Institute in New York City. She holds a Ph.D. in Sociology from Princeton University and a J.D. from Indiana University Maurer School of Law. Dr. Levy previously served as a law clerk in the United States Federal Courts.
Reading List
Levy, K. (2022). Data Driven : Truckers, Technology, and the New Workplace Surveillance.
Levy, Karen E.C. 2015. “Intimate Surveillance.” Idaho Law Review 50: 679-93.
Proactive Moderation of Online Discussions: Existing Practices and the Potential for Algorithmic Support
Charlotte Schluger, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil, and Karen Levy
Proceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW) 2022
Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles A. Feder Cooper and Karen Levy Colorado Technology Law Journal 20: 249–281 (2022)
Chilling Effects and Unequal Subjects: A Response to Jonathon Penney’s Understanding Chilling Effects Karen Levy Minnesota Law Review Headnotes 106: 392–399 (2022)
An Uncommon Task: Participatory Design in Legal AI Fernando A. Delgado, Solon Barocas, and Karen Levy Proceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW) 2022
Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems A. Feder Cooper, Karen Levy, and Christopher De Sa Proceedings of the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) 2021
Algorithmic Auditing and Social Justice: Lessons from the History of Audit Studies Briana Vecchione, Solon Barocas, and Karen Levy Proceedings of the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) 2021
Transcript
KERRY MCINERNEY:
Hi! I’m Dr Kerry McInerney. Dr Eleanor Drage and I are the hosts of The Good Robot podcast. Join us as we ask the experts: what is good technology? Is it even possible? And how can feminism help us work towards it? If you want to learn more about today's topic, head over to our website, www.thegoodrobot.co.uk, where we've got a full transcript of the episode and a specially curated reading list by every guest. We love hearing from listeners, so feel free to tweet or email us, and we’d also so appreciate you leaving us a review on the podcast app. But until then, sit back, relax, and enjoy the episode!
ELEANOR DRAGE:
In this episode we chat to Karen Levy, Associate Professor of Information Science at Cornell University and author of Data Driven: Truckers, Technology, and the New Workplace Surveillance. Karen is an expert in the changing face of long distance driving - she spent ten years doing research with truck drivers. So she’s been looking at how surveillance and automation are changing what it means to be a trucker in the USA. We talk about how truckers are responding to new AI technologies monitoring their behaviour, and what the future holds for the trucking industry. It’s a fascinating insight into what Uber is trying to do. We recorded this a while ago so it’s an audio-only episode. We hope you enjoy the show.
KERRY MCINERNEY:
Brilliant. So thank you so much for joining us here today. So just to kick us off, could you tell us a bit about who you are, what you do? And what's brought you to thinking about gender, feminism and technology?
KAREN LEVY:
Yeah, I'm so glad to join you both today. Thank you so much for having me. My name is Karen Levy. I'm an Associate Professor of Information Science at Cornell University, where I also have an affiliation with the Law School. I'm a sociologist and a lawyer by training. And I study social and ethical dimensions of new technologies. And oftentimes, you know, as you might expect, many of the issues that are looked at the way new technologies are deployed in the world intersect with questions around inequality, or different axis axes of difference. So I've always kind of centred feminist perspectives in my work. And that's, that's how I came to be. That's how I came to be here and to work on these topics.
ELEANOR DRAGE:
Amazing. So where the good robot so our triptych of priceless questions is, what is good technology is even possible, and how can feminist work help us work towards it?
KAREN LEVY:
Don't start with a softball question or anything - Right to the heart of it right away. What is good technology? I think that's such a good question. Um, you know, my feeling is that, you know, if we were to try to define good technology, I would say good technology is technology that's aligned with with human values, right technology that helps people to live with dignity, or with opportunity, or with happiness, or with other things that help people kind of flourish and achieve opportunities. And I think in practice, you know, that can look like a lot of different things, right, it can look like tools that help us communicate with our friends and family or access information that we need or stay safe. And I think the really complicated question, as you put it, right is, is is it possible to even have such technology? And I think, in my view, technology can never be entirely good or entirely bad? Right? I think good technology is sort of a goal that we know that we'll never achieve, technology is always a complicated set of trade offs. And I think there are a lot of reasons for this. I mean, one basic one is that people don't always agree, right, people can reasonably disagree on what values we should even be striving for in different contexts. We might think safety's most important, or we might think connection is most important, or democracy or access to information. But we won't all agree on that. And we can't have all those things at the same time. And then even if we did agree, the way people use technology, like people use technology, and all different kinds of ways that shape the outcomes that result from them. So every technology that, for example, can be used to keep someone safe can also be used to abuse and control someone or every technology that gives someone access to information can also be used to spread propaganda. And this is not news to anyone who pays attention to technology news, where we see these harms emerge over time. So I think the answer isn't to say, well, you know, technology isn't perfect. So like, let's throw up our hands and just give up? The answer is that I think there's this kind of constant balancing act right, of refining our technologies and refining our policies around them to sort of achieve the delicate balance between harms and benefits.
KERRY MCINERNEY:
But it's really interesting. And I think the points you bring up around tensions and conflicts over, you know, what do we even think is good? What do we think is worth pursuing? What trade offs are worth it, were also really interesting to Eleanor and I, as feminist theorists as feminist scholars, because if we look at the histories of feminism, right, and how different feminism is, is so deeply in conflict with one another. And there's so much tension of like, what does a good feminist future look like? You know, these are questions which I think we've been grappling with for such a long time. And I want to extend my congratulations to you because you have a new book coming out called Data Driven, which is based on a decade of research with truck drivers, and specifically, how new technologies are changing and affecting the cultures of long haul truck driving. So to kick us off, could you talk a little bit about how gender shapes the cultures and the identities of long haul truck drivers?
KAREN LEVY:
Yeah, I'd be happy to. I mean, you point out that I've been working on this book for about a decade. It's a good like, cautionary tale, that you should never embark on a research project that you don't want to spend like a substantial component of your life thinking about. But I really enjoyed learning about truck drivers and kind of getting to know folks in the trucking community. So it's been really rewarding for me personally. As to this, this question about kind of the relationship between gender and the identity, occupational identity of truckers. So there's a couple of different ways I think, in which this plays out. One is that is kind of just the centrality of masculinity to the occupation of truck driving. There's some really, really wonderful work by gender scholars and historians on kind of the connection between masculinity and occupational stamina and machinery. So the idea that, you know, driving this big piece of equipment for a very long period of time in a way that is really taxing for your body, and it's really, you know, it's essential work, right, that that, you know, that construct often is sort of intertwined with notions of masculinity, especially for folks, you know, who often are coming from blue collar work environments. So it's a very masculine coded job, I think, by the numbers, the most recent stats I've seen put the numbers in the United States at about 96% male. So the introduction of technology into a context like that is really fraught, because just the occupational identity itself is so closely connected to that notion of identity here and it kind of plays out in a few different ways. One is, so the technologies that are being introduced into truck driving kind of implicitly question whether someone is like “man” enough to do the work, right, someone has the stamina to do the work, someone has the bodily self knowledge to know when they're too tired to drive a lot of these these technologies, not exclusively, but many of them focus on fatigue, right. So knowing whether someone is kind of sort of fit to be driving. So that idea of stamina, of saying like, No, you know, you're not, your body isn't strong enough to do this, you know, it's obviously very closely tied with this kind of idea of masculine stamina. And then, you know, tied to that is economic provision. Right. So a lot of truckers that I talked to, you know, really see themselves as supporting, you know, children and family through their labour right through, you know, like very, very difficult essentially, sweatshop labour. There's a really wonderful book by an economist named Michael H. Belzer called Sweatshops on Wheels, where he sort of compares trucking labour to sweatshop labour, if you look at kind of the bodily risk that's entailed, the number of hours people drive, and the wages they receive for that work. It's basically not so different from working in a sweatshop, just one that's mobile. So economic provision, right. So if you impinge on someone's economic provision by saying like, actually, you should stop driving, which in the United States means that you'll stop making money because truckers are paid by the mile that they drive, you know, that also is an impingement on kind of this understanding of the self as being a support for family. So those are some of the ways in which masculinity and technology are intertwined in this context. But it's also really important to note that there are particular consequences for women, and for non-binary drivers to and here I've always liked to highlight this really, really wonderful oral history by a writer named Anne Balay. She's a scholar of labour and gender and sexuality. And she has this wonderful book called Semi Queer, which is about, you know, gay, lesbian, transgender drivers, as well as women, drivers and Black drivers. And she gives like many really wonderful examples in this history of ways in which technology, you know, uniquely affect folks who have these marginalised identities and in driving one really visceral example that she uses in the book that that I think really hits the point home is that, you know, for a lot of women and non-binary drivers going into a truck stop to use a bathroom is like a fairly dangerous endeavour, right? Like, it's not one in which someone's safety is necessarily guaranteed. So one thing that some of those drivers have started to do is to like have their own kind of bathroom space in the truck, right to kind of carry a mobile toilet with them. Now that, you know, maybe works unless your boss puts a camera in the cab that records everything that's going on in the cab, which is increasingly common in a trucking context, right, then the idea of going to the bathroom in this in this video recorded space, like takes on this different quality, right, and it's one that that not all drivers kind of evenly have to deal with. So we can see that, you know, gender obviously has kind of these multi-valent impacts in this context, that they're connected both to masculinity and to marginalised gender identities in the industry.
ELEANOR DRAGE:
You must have spoken to lots of incredibly interesting people, I can't even imagine the conversations that you've had, must have been incredible. The … you know, you've said that there's all these new digital technologies that are being implemented in the trucking space. Can you tell us a bit about them? You've said that Uber is getting involved in some way. So how are they changing the trucking industry? K
KAREN LEVY:
Yeah, no, I mean, to your to your point about the people that you talk to, I mean, I have to say, I kind of like wasn't prepared, when I started doing this work for kind of just how gratifying and humbling it would be to do ethnographic research with people who have like, really no good reason to talk to you, right? Like, they have things to do, you're kind of there bothering them, they're not necessarily going to benefit super directly from the work. But it was so humbling, I think is the only word I can think of to use to see like how openly people welcomed me into their lives and their homes and their trucks, and, you know, share their knowledge with me and their wisdom with me. And it really has been like one of the most wonderful experiences of my life to get to do that, in terms of the kinds of technologies that these folks are facing. So there's a huge variety of things. The kind of focus of my work has been actually on a government mandate of a technology called the electronic logging device, or ELD. So this is a technology that for the past few years in the United States, has been mandatory and all long haul trucks. And what it does is it records the time that truckers are driving and notes like where they are at different times of day. So this is designed to kind of - it's a regulatory technology, right? It's designed to keep tech to keep truckers from driving more than they're legally allowed to do. That is like…somewhat maybe sounds kind of minimal on its face. It's like not … doesn't seem …maybe all that invasive. It is really a big change in the way truckers have done their work and recorded their work hours. But I think what's important in this context is that that technology, which is made mandatory by the government, scaffolds a bunch more other types of surveillance, right. So including primarily private surveillance from truckers, employers, and those technologies kind of run the gamut. So there's a lot of what are sometimes called performance management systems or fleet management systems that will record many, many, many different aspects of drivers behaviour, like how fast they're going, how hard they're breaking, whether they're checking their mirrors regularly, how much fuel they're using - that's like a really big one, because fuel costs, obviously, you know, are a big cost driver in the industry, all kinds of different information about kind of just like the act of driving and the truckers body while they're doing and driving. So increasingly, these then are also integrated with camera systems, like the ones I mentioned that some face out and some face in, and are kind of focused on the driver’s face; biometrics, including like wearable technologies that detect things about a driver’s brainwaves, or driver’s heart rate, all kinds of different stuff. And of course, they're unevenly adopted in the industry. So some drivers deal with more of these than others. But all drivers have to deal with at least some of this. And then on top of the government surveillance and the private surveillance from firms, you see, third parties kind of getting into the mix, too, because if this data is being collected, probably there's some money to be made from it. So then we see things like insurance companies or companies that are selling or leasing, truck parking spaces, things like that. Also being really interested in, you know, getting kind of this gold, what is sometimes called this gold rush of data in trucking, right, just this incredible amount of data that's being collected about these drivers that previously were sort of immune from this kind of workplace surveillance because of the nature of their work. So it's really just a wholesale change for them.
KERRY MCINERNEY:
That's really fascinating. And something I'd be really interested to know is yeah, how are truck drivers themselves kind of mobilising, responding to these technologies. And this must be particularly interesting for you, because you've followed this now for 10 years. Do you feel like kind of the main targets or the political priorities of drivers have changed over this past 10 years? And if so, how? But yeah, I'd love to hear your reflections on that.
KAREN LEVY:
Yeah, it's a wonderful question. So certainly the way that drivers and others in the industry have responded to these changes has been kind of one of the central questions I've been asking. You know, it's a really big industry. So in the United States, there's like almost 2 million long haul drivers. So obviously, people have a wide variety of different reactions. Some drivers like some of these technologies, right, some of them find that it kind of levels the playing field between drivers who want to, you know, drive a whole lot and break the rules - it maybe makes it harder for them to break those rules. And that can sometimes be something that's welcome to some drivers. But on the whole, drivers have not responded super positively to these changes, for reasons that you can probably anticipate, especially given the kind of the very strong occupational identity that I alluded to. You know, trucking is an interesting industry, because, you know, it's not particularly well paid work. It's low wage work. As I mentioned, it's kind of, you know, akin to sweatshop labour, it's very risky, truckers have a very high - they have the eighth highest rate of occupational fatalities in the US, they incur all kinds of physical and mental health problems by nature of the work that they do. They get sleep apnea, like it's a really difficult, dirty job. But it's also a job that is really attended by like a very, very strong idea of pride in one's work. Like it's not a job, it's an identity, right? A truck driver is not just driving a truck, they are a truck driver. And so when you kind of like, intrude on that and you say this way that you've been doing your work, actually, we think your a cheat - like almost almost without fail truckers I've talked to about this, say that the technology treats them either as children or as criminals, right, and either says, we don't trust you, we don't think you like know when you're tired, we don't believe you can do this job, even though maybe you've been doing this job really well for 50 years, or we think you're basically like incapable of making these choices for yourself. So there's a good deal of resistance. And that manifests in different ways, right? To your point Kerry. Sometimes it's collective right, so sometimes it looks like truckers protesting in some way, sometimes it's individual, and it can be like very visceral, like, I've, you know, talked to lots of truckers who say like, yeah, I just broke the thing, like, I just smashed the thing when the company made me put it in the truck. Sometimes it looks like truckers are leaving the industry. So there's a huge, there's a very, very, very high rate of turnover in trucking as it is. But a lot of older truckers, the more experienced truckers that I've talked to, some of them say like, you know what, I'm just not going to do this job anymore. Like, this isn't the job I got into. And ironically, those are actually the drivers that you most want behind the wheel of the truck, because those are the experienced drivers. What you don't want is kind of the younger, like 18 year olds who just got their commercial driver's licence, who you know, like maybe it doesn't bother them quite so much because they haven't experienced it any other way. You know, surveillance is kind of just a feature of many low wage jobs at this point. So they don't maybe - they're maybe less resistant to it, but they're also the least safe drivers. So it maybe has this kind of paradoxical effect of driving out some of the people that you most want, you know behind the wheel of a truck.
ELEANOR DRAGE:
Are there any benefits to these new technologies, like the ports that you described - these autonomous truck ports in your lecture that I listened to, you said that there might be some benefits to the political economy of driving through Uber? Is that too utopian? Or is there something there?
KAREN LEVY:
Yeah, no, I know, you're definitely right. Right. So you know, kind of getting back to the beginning of our conversation. I don't think any technology is sort of necessarily bad in the way that, you know, just like, per se, evil, I think a lot depends on kind of how things are implemented. And in the book, I talk some about, you know, different ways in which different firms have implemented these technologies, in ways that, you know, maybe align more with kind of the culture of tracking or the goals that drivers have, you know, sometimes that looks like, you know, you pointed out kind of this new development where this isn't happening yet. But one kind of thing, one vision that's on the horizon is that we start to use autonomous vehicles more for long haul trucks or for long hauls, excuse me. And then we let people do some of the more local work, right, the work that lets them go home at night. Currently, that's not labour that's particularly well compensated in the industry. So currently, drivers make most of their money from the long haul, because they're paid by the mileage. But that could change. Right. So one thing that might happen, maybe is that the technology sort of occasions a shift in the political economy of the industry. And maybe we could envision, you know, a new world in which the technology plays a role in ensuring the truckers are safer and ensuring that they're paid for their labour, in ensuring that they can come home at night and ensuring that they're not basically driving themselves to death. The technology could be a part of that vision, right? It isn't currently being implemented in that way. And I think this is often kind of a feature of the way we use technology, right? Where we deploy technological solutions, we often kind of don't address the root causes of economic inequality or exploitation, right, which in the context of trucking has to do with kind of the wage structure of the way that these low wage workers are paid, right, the fact that much of their work is really uncompensated, because they're only kind of paid for the miles that they drive, like we could. And that that is what drives a lot of the fatigue in the industry, which the technology is then kind of being marshalled to try to address. But another way to do that might be to sort of use the technology as part of a suite of solutions, that also addresses these root problems, right, that helps drivers take care of themselves, right, and get their work done in a way that's more sustainable for everyone.
ELEANOR DRAGE:
Yeah, that's fascinating. I'm sure there'll be a lot of companies that will be trying to poach you to help them out, you know, it's good to be aware of what the trade offs are. And you know, what, at what price these benefits come, I think another thing that people are really interested in is, you know, people think a lot about autonomous vehicles as cars, but not really as trucks. And maybe it's slightly scarier, that there are these massive and incredibly heavy trucks on the road that are not driven by people. You talked a bit about the handover. So this is, you know, one of the biggest battles faced by people who try and develop autonomous vehicles is that moment of handover, when you have a driver that is not alert at all, and suddenly has to, you know, switch into alert mode. Can you tell us a little bit about those kinds of challenges in the context of trucking? You've talked about “vigilance detriments”, which is quite a nice phrase - hours of boredom and moments of terror. Will you tell us more about that?
KAREN LEVY:
Yeah, sure. And those phrases are not mine. Just those are phrases that other researchers have come up with. So right, so this has to do with kind of this question. So as I was kind of studying trucking, you know, which I've been doing for a while, something that's starting to come up in just the last few years, like the last maybe four years, is more than this question about autonomous vehicles. And what is the role that autonomous trucks will play in changing the trucking industry as well as just you know, the way we drive vehicles more generally? And I'll have I mean, I'll admit to you that at first, I thought, like, oh, well, that's like, not really, you know, if suddenly, we have autonomous vehicles, like maybe we don't have human truckers anymore. A lot of the media reports about autonomous vehicles and like robots taking our jobs sort of take, take this view. So I kind of felt like, Okay, well, does that mean that like, all these surveillance technologies I've been studying for the last several years are like maybe going to become moot, right, because we won't have human drivers to monitor anyway. As I looked into kind of, you know, more of the state of autonomous trucking, it became clear that that's not actually the case. Right. So what happens in autonomous trucking, as you alluded to Eleanor, is that we need to find a way for humans and vehicles or humans and machines to kind of work together right or integrate their labour together. Vehicles are nowhere near the stage where we can really, just deploy them without humans being involved in some way. Right. And the Society of Automotive Engineers has a variety of different ways that they categorise the capabilities of autonomous vehicles. But everybody pretty much agrees that we're still at the point where humans have to be there and have to be paying attention in order to take over from the machine. This is the handoff, right, or the handover that you alluded to. Now, the problem is, as many other people who are not me have written about, in which I traced some of their research in my book is that the handoff seems to be like a pretty intractable problem in the context of driving. So we know that people are really, really bad cognitively, at paying attention to a situation for a long time where nothing is happening. And then all of a sudden, kind of swooping into an emergency situation, they're really not very good at coming in and like suddenly acting quickly, in a safety critical situation, in driving those safety critical situations happen in like a matter of milliseconds. So if you're about to have an accident, you just don't have time you don't have time - it takes about 16 seconds for a person to kind of take over from an autonomous vehicle from a state of not paying any attention, and like you don't have anywhere near that amount of time. So we know that that's unlikely to be a solution. As a result, we've kind of turned to looking for other kinds of ways to sort of divide up the driving task between human and machine, there are a few different possibilities. And in this chapter of the book, I talk a bunch about different ones that have been envisioned, including this idea of autonomous truck ports, like Uber was working on before they shuttered that component of their business. Ultimately, though, where we sort of landed is that the way we've kind of dealt with the integration of humans and machines in autonomous trucks, looks actually a whole lot like the surveillance that I had been tracing, right in other contexts, right looks like Well, we know that the person is not going to be very good at paying attention to a context where nothing's going on. And so the way that we'll try to enforce them doing that is by monitoring their attention, right will do things like point a camera at their face, and have it buzz them or like flash a light in their eyes, if they stopped paying attention, or, you know, if they take their hands off the wheel, instead of you know, holding the wheel at 10 and 2 like they're supposed to, well, you know, jiggle their seat or something right, or like one company I read about in the book even had like this idea of delivering like a light electric shock to truckers if they stopped paying attention, things like that, right. So what you end up kind of seeing at the end of the day is not that automation kind of substitutes for the surveillance that we've seen in this industry for a long time, but rather that the two are complements, right? And that's because people are just always going to be an integral part of autonomous systems, right? Autonomous systems kind of need to make the person sort of fit as a cog into the machine, right? They need to have the person fulfil a role. And then in the interest of kind of making the human fill that role, what we often do is monitor them even more intensively than we did before.
KERRY MCINERNEY:
Absolutely. One of our other fantastic podcast guests, Maya Indira Ganesh has a piece called ‘The ironies of autonomy’.
KAREN LEVY:
Yeah, that's a wonderful piece.
KERRY MCINERNEY:
Yeah, exactly. Yeah. And she's absolutely wonderful, and yet kind of speaks to this fantasy of the autonomous entity in particular, I think your work is such a testament to how important these kinds of long term ethnographic projects are, and gauging sort of how these technologies emerge, become embedded and change these particular fields of work. And so if you'd like to share, you don't have to - do you have any particular stories from this research in particular people interactions that really shaped or helped crystallise some of the key arguments, conclusions that you draw out in your book?
KAREN LEVY:
Oh, what a good question. I mean, yeah, I mean, I just I, like I said earlier, I've been so honoured to get to know the people that I've gotten to know through this work, it really has been just a, just a wonderful window into an area of life that I hate to admit, I had just kind of ignored, right, like, I had not thought much about the work that truckers do, even though the work that they do is incredibly essential to the way we all live our lives, right? Like basically everything that you have in front of you, or that you're wearing on your body or anything like that was at some point on a truck being driven by a truck driver. We depend on them more now than we ever did, because we expect much faster delivery times we want to know where Amazon packages, but it's very, very, very easy to ignore these workers, right, and to ignore the work that they're doing until something goes wrong, right, until there's, you know, delays at the ports are until there's you know, the need for delivery of, you know, equipment in a pandemic or something like that. But, but obviously, they've been essential for a very long time, they continue to be essential. I mean, in terms of like, individual stories, I think there's one that really sticks out for me, which I talked about in the book, which is that, you know, I alluded to this idea of kind of, you know, masculinity and the independence that's kind of inherent in the trucking profession, and which has been for a long time. So like, if you look back at kind of the 1970s, where the trucking kind of cultural heyday where we got a bunch of trucker movies like Smokey and the Bandit, and, you know, all just like all these songs, like a bunch of really great trucker country music anthems and stuff. And a lot of it kind of paints the trucker as like a cowboy, right? So the idea is like, you know, the truck Er really knows what they're doing. The state is bureaucratic and doesn't know what it's doing. The trucker is just like doing what needs to get done without regard for rules, right? That's like kind of this notion of the cowboy trucker. And it's easy to kind of buy into that, right? Like, it's, it's kind of like a fun character. It's easy to sort of think like, yeah, you know, these guys are just out there doing their job. And like, they don't care what anybody says about it. Like, it's a very kind of appealing kind of independent idea. So I remember talking to this one - this is a long winded way of what I’m trying to say. Sorry. I remember talking to this one driver, who about kind of this kind of idea of the cowboy mentality. And I was kind of like, being a little light hearted about it. Right? I was kind of like saying, like, yeah, you know how it is out there, right. And at the end of the interview, like we stopped the interview, and he stopped me and he said, like, listen, I just need you to know - like, he kind of corrected me. And he was absolutely right to do it. He was like, I just want you to know, like, Yes, we all like talk a big game. Yes, we like, make this sound like it's really fun. Like, yes, we kind of, you know, make fun of people who try to like put constraints on our work. But at the end of the day, like, this is not a fucking party, right? Like, you would not be able to - like you can't keep the lights on at home if you don't do this work. Nobody wants to be out there driving 24 hours in a row. Like, that's not fun, right? We act like it's fun. But it's not fun, right? Like, that is a cultural gloss that's necessitated by the economic position in which these worker workers find themselves. And that's huge, right? Like, you know, he, I mean, he was very gracious about it, but he kind of was like, don't forget, right, that these are real people who like really die doing this job. And the fact that we like make it sound like we're cowboys, is kind of like what we have to do to like, do this with dignity. And that, to me, was like such a good check. And to your point, right, Kerry about kind of the importance of ethnographic research, I think, like I needed to hear that, like, I needed to, like have this conversation with a human being who was doing this job in order to like, really see, you know, what, what that work is even somebody you know, even though I talked to, you know, dozens of truckers at that point, I kind of like let the story run away with me a little bit, right. And it was a good check for me that like, you know, the narratives about the narratives that we might have externally about people's lives are almost never really the full picture. And it's really important to understand the range of constraints that people find themselves in to really, really see why they do what they do, and to appreciate the dignity of their work.
KERRY MCINERNEY:
Thank you so much for sharing that. I think that's an incredibly important story. And the critically important watershed moment, I guess, in your own research, but I think also kind of speaks to some of the points we're talking about the beginning of this episode around the all the inherent tensions and how we use technology, but also how we think about feminism, how we think about justice, and how we grapple with these interlocking, complex power relations that constitute the world that we live in. And thank you so much for sharing with us so graciously about your work to our lovely listeners, please go out and read data driven. And thank you so much again, Karen, for appearing on the podcast. It's been a real delight to talk to you.
KAREN LEVY:
Well, thank you so much for having me. It's been a pleasure to join you both.
ELEANOR DRAGE:
This episode was made possible thanks to our generous funder, Christina Gaw. It was written and produced by Dr Eleanor Drage and Dr Kerry Mackereth, and edited by Laura Samulionyte.