Hello, and welcome to another episode of the Odd Thoughts Podcast. I'm Tracy Alloway and I'm Joe. Joe. Do you remember when we had Gordon McGill on to talk about trucking. Yeah, that's what that's like an iconic. I mean, there's recent, but that's like a odd lots classic already and a bunch of people of reaching. That was a great episode.
It was he said, I mean, he said a bunch of things that were very interesting, but he said something in particular where he was talking about an upcoming book by a Cornell University professor called Data Driven, and the idea was to explore the role of technology in the trucking industry. Yeah. Absolutely, And you know, I think this is a really important area to explore because, of course, as we've discussed with Gored, but also other episodes that
we've done on trucking, truckers are monitored increasingly. They're these e l d s electronic logging devices, the track hours, things like that, and you know, obviously this affects truckers, but you know we may all be tracked by e l d s as workers were. Right, So there's two
interesting things here. So one you would expect that monitor monitoring technology UM like the e l D s that they're using would be sort of like anatama to a lot of the truck driving industry, Like a lot of truckers go into it thinking they're going to be independent, they have the freedom of the road, and then it turns out that they're like eye movements and brain waves are going to be tracked and monitored. So that's interesting.
And then secondly, given the shift towards work from home for a wide variety of workers, it does seem like
surveillance technology in general could become more of a thing. Well, and the other really important thing that I think maybe I don't know something profound about how business works or capitalism works, etcetera, is like there is this core problem right, like why does e l D exist in the first place, attempt to solve problems truckers on the road for too long that creates fatigue, that creates accidents, like some sort of impulse behind these rules that curtail how long someone
could be on the road, But rather than address why are they on the road to love, why is there truck or fatigue? Why has fatigue been part of trucking? And you know forever, rather than figuring out different ways to do that, let's just crow come up with a monitor system, rather than addressing the core issue that creates the need for these time constraints and monitoring systems in the first right. So the question is also whether or not technology is the right solution to the problem it's
trying to solve. Okay, well, I'm very happy to say we have the perfect guest because we are going to be speaking with the author of the book that was referenced by Gord. We are going to be speaking with Karen Leavy. She is an associate professor at Cornell University and also the author of Data Driven Truckers Technology and the New Workplace Surveillance, which just just came out. So, Karen, thank you so much for coming on all thoughts, Thanks
so much for having me. This is a really interesting topic and I'm glad we have the chance to dive into it further. Maybe just to begin with, you know, Joe kind of alluded to this in the intro, but what exactly is the problem that this workplace surveillance technology that's been mandatory in the trucking industry. I think since seen what exactly is it trying to solve Yeah, I mean the way you guys talked about it kind of in the lead up, I feel like perfectly encapsulates it.
So the e l D, the electronic logging device, as you mentioned, is federally mandated in the trucking industry. All long haul truckers have to buy and install and use them. And ostensibly the goal is related to safety, right, as you alluded to, we know that truckers are really tired. We know they're incredibly overworked and underslept, and obviously that has you know, that's high stakes, right. There are thousands of truck related accidents a year and fatalities from those accidents.
It's really cost billions of dollars every year. Um, So like nobody wants that, right, and including truckers, nobody wants the roads to be on safe. I don't want to be next to a tired trucker on the road, nobody, Like, we're all aligned on that. But what's interesting, as you point out, is not like is you know the way that we have sort of chosen to address that in
this case is via technology. So the electronic logging device is sort of, um the centerpiece of this effort to make truckers comply with the timekeeping regulations that they're subject to. I think this is something Gordon talked about two in the episode he was on right, Like, truckers for since the thirties have been bound to, you know, work no more than a certain number of hours every day and
every week, and that's for safety reasons. The problem, as I know, you know you'll have discussed, you know, on on Board show and on other shows, is that the way truckers are paid, like does not align with those incentives. Right.
They're paid by the mile. Truckers have the saying if the wheel ain't turn in, you ain't earnin right, Like, they're only paid for the time that they're actually moving down the highway, not to like sit around resting, right, or not to do all the other things that are an important, essential part of being a trucker but aren't compensated. So the result is that truck ers just want to stay on the road as much as they can because
that's how they make a living. They're in pretty dire economic straits to begin with, Like, it's not a mystery why they why they end up doing these things. And so the E L D is sort of scene is like an answer to this, right, a way to sort of police this behavior by making it ostensibly harder, although not impossible, for truckers to tamper with the log books that they used to keep. So they used to do this using paper and pencil um and that is like a really easy system to kind of falsify or make
it look like you're running legal when you're not. And so the e L the sort of scene as an answer to that. You know, I I always was a big fan of the song Convoy and there's a line of tearing up your swindle sheets, which I didn't really you realize the origin of that term until I read your book, and the swindle sheets was a nickname for the old physical pieces of paper that the truckers used to log their hours talk about like, you know, they had all different ways I guess of sort of swindle
lying on these cards. How long was that push to How long had that effort been in place to get truckers to give up the physical pieces of paper in favor of these e L D s. So ELD is like first start popping up in you know, discussion around regulation in the nineteen eighties, and there's a long history
of kind of how they eventually become mandatory. At first, the government starts to do things like, well, you know, maybe we'll make these mandatory for people who have like really bad safety records, right for some subset of the industry that we kind of think of as habitual VIL violators. Then there's a proposed mandate in the that goes nowhere right there, legal challenges. It's kind of like a long and rocky road to get to the e L demandate
that we eventually end up with in SEV. But we do eventually get there, right And you know, a lot of the kind of the research that's in for my book is trying to understand that transition looking at the arguments that get made on either side of the e L DE mandate. You know, from the nineteen eighties and even before right, there's some predecessor technologies to that that you know, I think set the stage for this up to you know, post mandate, looking at what the effects
have been on the industry. So we definitely want to dive into those various arguments. But before we do, can you talk little bit about the technology that goes into e L d s Because my understanding is. They sort of range from pretty basic models to more sophisticated things that actually, you know, can measure your brain waves to see how awake you are or how much attention you're paying to the road. So talk to us about the variety of e l d s that we have right now. Yeah,
this is really crucial. So the e l D itself captures some important data, but like, as you say, sometimes maybe not that much, like a fairly minimal amount. Basically where the truck is and how long it's been being driven, right, Like, those are basically the core requirements in the regulations. However, it's almost as though the government told everybody, like you have to buy a phone that makes phone calls or something, right, like you can. It's very hard to find a phone
that only makes phone calls. Right. If you're going to buy a phone that makes phone calls, you're also going to buy a phone that takes photos and connects to the internet and all this other stuff. Right, Because the tech tends to like bundle these things together, and the same thing happens in e l d s. So e l d s are actually more commonly like a module in what's sometimes called the fleet management system or FMS.
People sometimes call them like a qual calm because qual Calm used to be like have a big market share in this area. They're all kinds of names for him. But now what people think of is the E L D. Actually, it's kind of like, you know, it's almost like naming the part for the whole, Like it sort of stands in for this much broader range of data collection technologies. And as you point out, Tracy, those can include things.
You know, it commonly includes stuff like two way messaging or you know, alerting a back office about your fuel use or how hard you're breaking or how fast you're going, or you know, whether you're changing lanes without signaling, like all kinds of like pretty fine grain driving behavior data, which is just like very different from what trucking work
has look like for a long time. Right, Like, if you ask folks why they get into trucking, many of them say explicitly because they don't want that, right, they don't want someone looking over their shoulder kind of measuring how they do their work. And you know, some of the stuff that's coming up on the horizon more recently includes the types of stuff you allude to, right, things
like driver facing cameras have become much more common. Sometimes those are augmented by artificial intelligence that will do things like try to assess how fatigued a driver is, and they might do that by doing things like measuring, um, whether the dry driver's eyelids are fluttering, you know, as you know, like when you start to fall asleep, you're lets start to flutter your head nods. They can measure those kinds of things, and like you know, infer that
the driver is tired. UM. Some of them, you know, they are wearable devices that sometimes get sort of integrated into these systems or use kind of um in a complimentary way to these systems that do things like you said that measure a driver's brain waves, measure a driver's heart rate, you know, collecting these other kind of biometric signals to alert the back office or to alert you know, the driver's safety manager whoever kind of what state they're in.
So technically the law just require something the bare minimum of like okay, something track the truck, the hours on the road, etcetera. That needed an electronic version of the log book. But it's like the trojan Trojan horse atone, like once you get that electronic device in the truck itself, then why not add all these other things. Where is the impulse coming from to add these other features onto the field? Is it from the sort of like yeah,
who who's benefiting from this and who's making the decision? Yeah, we want to stick a camera in the face of the trucker and see their face at all time and start counting, uh, you know, eyelids opening and closing. Yeah, I think that's exactly right. It's like a scaffold, or it's like a you know, a Christmas tree, and once you have the Christmas tree, you can just pay more ornaments on the Christmas tree because you got the Christmas tree. Now.
So what has happened is that, yes, the government has you know, started to say like, we need to collect a certain sort of information digitally, and then a lot of the impetus for more data collection comes not necessarily
from the government per se, but from trekking companies. Right because those workplace analytics, as you alluded to right in the setup to the conversation, workplaces like across all kinds of industries and all kinds of professions are increasingly interested in using software, sensors or other technologies that are cheaper and easy to come by to measure stuff about what
their workers are doing. And so in some sense, truck like trucking companies are doing what all kinds of employers are doing, which is measuring more information about what their workers are doing on It Actually doesn't end there though, right Like on top of that, there are third parties that become very interested in this data too, right, So insurance companies become interested in it. Um companies that sell like parking space reservations to truckers other stuff like that, like,
they become interested in it. So the data becomes very valuable to many different parties. It's just not valuable to the trucker, right The trucker is kind of isolated against all these parties that are interested in gathering the stata about what he's doing. Can you talk a little bit more about the insurance angle, because this is sort of a a recent theme for us, this idea of insurers sort of incentivizing different types of behavior collecting more granular
data in order to do that. Does the installation of y l d s does that actually you know, reduce insurance rates for instance, for truck drivers or the truck driving companies yeah. So in what I have seen, um, it does or it can, and that some insurers insure, as I think at this point, are mostly just interested in getting the data rather than like really doing much with it beyond just like getting the data and integrating
it into their modeling. So what I've seen is is insurance companies offering what they sometimes call like a plug in discount. This is not so different from like what Progressive does with commercial or with passenger vehicles, right where you get some discount on your premia for just installing
the thing or like just giving data access. I haven't yet seen that it's actually had a measurable impact on like actual rates within the industry, but you can imagine right like this is this is the goal, right is to do something like that. So, I mean, we have had this mandate in effect for a few years now. Is there evident stead is making the road safer? No, there's not. There's not evidence that there's making the read safe.
Thank you for that set up. Um No. So what we have seen is that in the few years after the e l D mandate took effect, traffic like or truck crash fatalities went up. So they hit a thirty year high the year after the mandate. UM crash rates haven't gone down in some some segments of the industry, they've gone up. This is not based on my analysis. This is based on like quantitative analysis by some business
school professors that I talked about in the book. UM. But yeah, like if the goal is safety, right, like, there is no demonstration that even on its own terms, the e l D is succeeding in making the road safer. And if you think about why that is, there are
a couple of reasons that maybe happening. So one of them that's like really intuitive is if you tell people, like, hey, you know, you need to get from point A to point B in eleven hours, like about roughly, Like let me try to get home for Christmas in eleven hours, Like I will do that. But if it's eleven hours and five minutes or if it's twelve hours, like, it's
not the end of the world. And if I need to stop and get a cup of coffee, or if I need to like pull over and see if my tire looks weird or something like, I can do those things, right, I'm not going to like drive like about at a hell to do it because I know that that flexibility
is sort of built into the system. If I tell somebody like you have exactly eleven hours and you have no more because I'm like I'm tracking this, like I'm monitoring you, people will drive very differently, right, And that's very intuitive. So what we have seen is that like rates of speeding and reckless driving have gone up because people feel this extra rigidity in the rules and so, like not shockingly, they compensate for this lost productivity by trying to make up for that in the way that
they drive. So that's like one clear mechanism. Another thing that like we don't have as clear up data on this, but clearly seems to be happening based on my conversations with drivers. You know, trucking is kind of an aging workforce anyway, like the median trucker ages I think in the late forties, and a lot of folks if you talk to them, you know, like they are not interested in this, right, Veteran drivers who have been driving professionally
for me be decades, millions of miles without accidents. You tell them like, guess what, guess what we're putting in the truck now, Like they're not going to stick around for that. Trucking has this very high turnover rate anyway, people turn in and out of the industry all the time, And like, those are the drivers that are the safest. You want those drivers who are the most resistant in many ways to this kind of oversight. That's the guy
you want to be next to on the road. You don't want to be next to the eighteen year old who just got their CDL who like maybe it doesn't know any different, right, like, never grew up trucking any other way, It's hard to find a blue collar job that doesn't involve a lot of oversight and managerial surveillance. So those are the folks that will stomach this kind of thing, but they're not the safest drivers. Um. Actually, this reminds me. I want to ask you. You know
you studied this issue. I think when we spoke to Gored he mentioned a tenure study or something like that. I'm not sure if that time frame is entirely accurate, but talk to us about how you actually went about gathering data and anecdotes for your work. Yeah, so it has been cord is right. It has taken me a very long time to process the study but that's been good. Like I've spent like a quarter of my life thinking about trucking at this point, which you know, life comes
at a best. But um, I started the study inn I was a grad student. I was studying sociology um and I was a lawyer before that, so I was really interested in kind of thinking about law and how does it how does it function on the ground, and how do people respond to it? And especially I was really interested in kind of wine technology and what happens when we like surveil people, what happens when we collect a bunch of information about what people are doing to
kind of assess whether they're breaking the rules. And I was like sort of looking around for like where's a place where I can see this transition in action, Like I can really see that happening on the ground, so I can get a good sense for like how that unfolds or how it changes the way people relate to one another. And just by chance, it was like completely a fluke. I heard a story on the radio about trucking and how like truckers were upset because they were
dealing with this. But this was again twenty eleven, so the e l Demandate was being discussed, although it wasn't effective for several years after that, But about this mandate, and I thought like, well, that's maybe it. And I didn't know any truckers, like I have no truck truckers in my family, but I went that day to a truck stop just to see, like, what is it like to talk to a truck driver? Like is it easy? Will they talk to me? And I was like instantaneously hooked.
I found that truckers were like, they had such interesting stories, they were so forthcoming, they were incredibly generous, you know, in talking about the stuff that I admit I had never thought about. Right, it sounds like the origins of of odd lots interest in trucking as well. Yeah, so we keep doing trucking episodes. Obviously it's a fascinating, fascinating,
fascinating angle. You know what you mentioned, you know, the legal background, and this brings up something a point that I thought was really interesting in your book, which is that like society kind of depends on people being able to break the law a little bit, that you can't actually run a society on everywhere everyone always strictly hewing to the law and being punished if they don't you explain that a little bit more, because I think that's key when you talk about you know what the E
L D. You can't be ten minutes later, you can't drive an extra ten minutes. But what is this concept of like we need a little bit of loose areas? Yeah, no, I think this is exactly right. Right. It's very easy and intuitive to say, like, well, if we have a law, people should follow the law, and like therefore, you know, if we assume that the law is legitimate or has been reached in like a democratic way or whatever, like
people should just follow it. But like that doesn't really hold up too much scrutiny, right, And there's tons of places where we see that actually, like social life would kind of fall apart if people actually followed laws to
the letter. Um, you know, like one of the examples days in the book is just like speeding, right, Like I think if you were told that you were if you got a ticket for driving sixty six and a sixty five, not as a trucker but just as like a regular car driver, people like we would be like, what, that's not the law, and like it is technically, but
like nobody really expects that that's the law. Another thing I talked about in the book that kind of hits this home is um in in like labor actions and you know collective action, like a pretty common worker strategy is the work to rule labor action. I don't know if this is something it's familiar to odd lets listeners that we're in work to rule. What you do, it's it's like a work slowdown, and you achieve it by like suddenly you like really pay attention to all the
rules that are in like the cool books. You start track like spells out that you work this amount of hours every week, and you work exactly that amount of hours and you just do it right. And like the whole point is that by following the rules like that is not actually what we necessarily wanted people to do, because if you do it like, that's the slowdown. Right. The reason it's effective is because that's clearly not the expectation most of the time. And there's this happens just
all over the place. UM there was like a few years ago in New York City and in many cities right there are these big moves like um these vision zero kind of projects where they're like we should have
no jaywalking because jaywalking leads to traffic accidents. And then like when police start really cracking down on jaywalking, there's like some economics analysis where people say, like, you know, actually jaywalking is really efficient, and if we like we would lose like a good deal of economic efficiency if people actually follow these rules, because like we actually want people to bend the rules a lot of the time, right, We've built a society in which, like, following a bunch
of rules to the letter can be really inefficient or ineffective or can cause other harms. And that's definitely the case in trucking, right, Like, clearly a lot of problems
with the status quo and trucking. Like I'm not suggesting that everything is great and trucking and the labor conditions are wonderful and if we got rid of the E L D s everything would be fine, Like, I don't view it that way, but it is definitely the case that we have all sort of come to rely on the rules being more like guidelines in this context, right, and that people budge them in order to move stuff
at the pace at which we kind of all demand it. Um, So when we crack down on a rule without kind of considering that broader context, you end up with this weird situation where you know you haven't addressed the underlying reasons people are breaking the rule. You're just kind of policing them harder for it. You know. Joe mentioned the swindle books earlier, like the the analog log books that truck drivers used to keep. And I remember I used to, Um, I used to fly planes when I was like nine
years old. I don't know that you flew because my dad's out. Yeah, but I didn't know you were a pilot. Well not, but I had a pilot's log book and I was supposed to put in like my hours in my tiny little cessna, but like I was nine years old, and so I just used to pretend to fill it out all the time. I didn't know. So my question is, like, moving from the analog log books to the e l D S how infallible actually is that system? Can that
information be tampered with or falsified? Yeah, it is a great question, and I love that you yourself have falsified a log book. So yeah, right, So the whole idea writer, like the rhetoric around the e l D is like, oh, this is tamper This is a tamper proof version of the thing that people have been doing for a long time,
and certainly it is more difficult writer. It presents different kinds of challenges to falsify data and an e l D than it would be on a you know, using pencil and paper, where like anybody could do it with
five minutes of thought. Um, but it's not impossible, right, as you point out, um, in one of the chapters of the book, I go through, like all of these different strategies that truckers and other folks used to kind of still bend the rules sometimes, right, because like as I mentioned, right, you still sometimes need that, or like the economy depends on that, or they're expected to do
it by their managers or whatever it is. Um, Like one of the things people will do is what and they did this with paper lugs too, is what sometimes
called a ghost log. So like you sign in as Karen, right, if you're Karen, and you do your eleven hours, and then you sign in as Joe or as Tracy right using some other right, which is like that's not and then you have eleven more hours, right, And sometimes like some companies they often get like a demo account like a John Do kind of account when they sign up with the E l D vendor, and so they like have these kind of like slush you know, drivers that
they can use in some cases. I don't think like not everybody is doing this, but the strategy that was described to me, um other things folks will do. I once I was watching I was sitting with a safety or with a dispatcher at a trucking company and she was talking to this driver and the driver was like, well, I'm like four miles from where I need to be,
but I'm out of hours. What do I do? And she was like, well, pull over and then roll to the place you have to get to roll to the drop off point at less than fifteen miles an hour. And the reason was because the e l D s all have like a threshold which is usually set by the company, and that threshold is like, under fifteen miles an hour, it won't register is driving, right, So she
knew that like, it wouldn't register is driving. What's interesting and like both of these examples actually is that it's not necessarily the trucker that's like pushing this, right, it's oftentimes the company that's telling the driver like here's what you need to do. Right, Like it's kind of like a winky strategy because they kind of wanted both ways in some sense, right, Like they want the control that E. L D S afford them, but they also like just
want the stuff to move. So sometimes they kind of coerce or compel drivers to do these things. So, you know, one of the things, and I think this is a thing that's gonna matter for all workers who are especially you know, work from home. That's gonna we know that that's going to increase the amount of surveillance on workers like are you actually at your desk responding to customers, etcetera?
Whatever the job. But I think like one thing that all this data collection is going to affect everyone is like who who knows about how we're done? How who? Who? Where is the knowledge stored about how to do a
good job? And you know, so in the case of trucking, like at one point the idea is like, Okay, the truck drivers they really like know their area, they know the road, they know the warehouses that they go to, and there's some sort of like knowledge base that exists primarily in the head of the truck driver, that's difficult
to replicate. And then I imagine, you know, okay, now with e l D s, maybe a lot of that knowledge isn't at the level of the driver, but maybe at uh, you know, whatever, the fleet owner or some other entity. But I also have to imagine that even for the owner of the trucking fleet, they may be losing to some third party company that's building a black
box AI model that even the company can't access. And so like the locusts of like all this knowledge and you know, the power that one has with that knowledge gets sort of distributed. Can you talk a little bit about, like I guess I would say the shifting distribution of power and knowledge within the industry as these manufacturers E l D manufacturers, third party data providers, software companies that provide uh you know, become like, oh, we have we
have the database, we have the information. Yeah, no, I think that's exactly right, right, Like, so the information moves right in trucking like people used to talk about it, like you're the captain of your ship, right, you get to make all the calls because like you're there, nobody else is there, and you know what the conditions are, like and nobody else does because nobody else is there. But as you point out, right, like now more of that data is distributed to the firm or to a
third party. And what's important to recognize about that, I think is that like, not only does that change the game because somebody else has the data, but the data they have is like not quite the same as the data you have, right, Like they have some kind of abstracted guests about what things are like, Like they know what you're how many hours register on your eel D and they're going to use that to kind of assess whether you have the right to be tired, right, or
like whether you have the right to stop. Or they have some sense of what the weather is like because they can look at the weather channel. But that's not the same as being in the place and knowing what it's like, right. So as things get abstracted, a lot of times those you know, kind of more abstract data sources get used to challenge the accounts of workers on the ground because they're measurable, right, They're the kinds of things we can measure. And this happens again not just
in trucking but all over the place. So, like I have a study from a different contacts where I like looked at retail workers than kind of how technology is affecting them, and they're too, right, Like tail workers and some set in some settings do this practice that's called client telling, where you like keep a book of business and you kind of like know the sizes of your favorite customers and stuff, and you know when their birthdays are and so like that really is empowering exactly right,
Like sex stores, those workers like have at the work, they work on commission and they have like a really good relationship to certain customers. Increasingly, like now they're not allowed to keep their own books in business. They have to like input that data into some centralized system. And what that means is that when they it comes time for them to argue for a raise or something like, they don't have those bargaining chips because, as you said,
the data is not in their head. It's now owned by the company or it's owned by the software vendor or whatever, and so that reduces like they're more substitute herbal right, it's it reduces their bargaining power of easy the company. And I think you see this kind of thing happening just across the board really and a lot
of different labor contexts. So just on this topic, and this is kind of a Devil's Advocate question, but you know, our last trucking episode, we were talking a lot about how truck drivers end working more hours than they're actually paid for because they end up going to warehouses or depots or whatever and they have to wait hours and hours and hours to pick up or drop off a load.
If you have this kind of surveillance technology, could it not be used to measure, for instance, how much time you're idling and then maybe like used to avoid inefficient warehouses or make some of those problems, you know, try to ameliorate some of those problems. Yeah, definitely, I definitely think that can be. I don't think it like redeems the whole thing, but it is a silver lining, right that.
And and exactly those kinds of tools have been built using e l D data that kind of give you It's almost like the thing where Google will tell you like, is there a long wait at this restaurant? Right like it will do the same thing for truckers, being like, you know, is there a long detention period on average at a particular shipper and that potentially can be useful to you, right, like to the extent you get to control whether you know which which loads are going to
take to help you kind of control your business. So I agree that that kind of transparency can be useful, right And it's one example of where you know, it's kind of like a more labor friendly way of using this data to actually help truckers out. I don't think it like redeems the whole because it's like a nice thing to kind of put on top of all of this additional control. There would be like other ways we could ensure that truckers don't lose a bunch of time
to detention that would be much more direct. But I'm in agreement with you that that is like kind of a bright spot. Well, although it also seems like, look, we just had these two years of like terrible supply chain disruptions, Like we're why didn't all this data help us? Then? I mean maybe because this is like a once in
a hundred year crisis we just experienced. But you figured, like, well, if all this data was so great at improving supply chains, you know, it didn't exactly step up to the plate.
There's so many things I fascinating angles of this something I I wanna again something else in your book that really struck me, the social that you mentioned, Like, Okay, in many of the cases, the truckers you really want on the road are the ones who might be most repelled by having this electronic monitor device staring them in the face all day. Can you talk a little bit about these efforts that UM, the E l D makers and companies have put forth to sort of like get
people comfortable at them. Yeah. So one thing that companies sometimes will do, and I've talked to E l D vendors that have talked about these strategies and to trucking companies themselves that will use them, is that, like in rolling out an E l D system or a fleet management system, you know, a lot does depend on kind of the messaging around that or like what kind of
culture the company builds around that. UM, And there's a bunch of obviously, like the tools can be used in all kinds of different ways, and there's a bunch of variation and how companies roll them out. One kind of interesting thing I saw happening is that, you know, because there's now all this data on like like their scorecards, that can be generated for each driver based on fuel efficiency and how many safety incidents they have, and that
kind of thing like that becomes really easy. And then that also facilitates like not only measuring the driver, but comparing the driver against other workers, right, or incentivizing the driver kind of like making a like gamifying it, right, making it a game about like, well, who can have the lowest fuel efficiency. That's a big one, right, because that's a big cost driver for trucking firms. And so companies will do all kinds of stuff to sort of
incentivize drivers to sort of comply. Um, you know, like a really basic thing is just putting up a list of who's the most fuel efficient driver, which they of course now have that data, like putting that up you know in the central office or something. I've there's some pictures in the book of um you know some of these what these charts look like they might attach like
a small financial incentive to it. So, like I talked to a company that it was like they drove for restaurants and they're like, oh, well, we'll give you a gittu divigate to the restaurant that you drive to, which doesn't cost them very much, but I guess it's nice
for the driver. My favorite one is, um where a company they were interested in kind of um the drivers driving efficiently, and so what they decided to do was issue these like small bonuses two drivers wives in the wives names when their husbands like met whatever the fuel efficiency goal was. And the thinking I asked like, well, why the wives, and like, well, you know, once you get the wife fund board. Funny, I'm so proud of your efficient driving. I'm so proud of your e l
D compliance fuel efficient driver. Thrilled what people want to here when they get home. I know that's what I say to my husband every night. No, I mean like you have to sort of admire the antinuity. But it is an interesting strategy, right to like yeah, exactly like you said, to sort of bring the family dynamic into this kind of datification of the work. Incredible. Um, well, Karen, one of the reasons we wanted to have you on is I mean, a, we're fascinated by the trucking industry
in general. But be we mentioned this in the intro. As the world sort of shifts to work from home, or at least as there's a little bit more work from home than there was before the pandemic. It does feel like there is an opportunity for more of this kind of workplace surveillance technology to be deployed to a broader um workforce. Can you talk to us a little bit about what your research tells us about the application
of this tech to the rest of the labor market. Yeah, I definitely agree that workplace surveillance has a very long history, right,
and the motivations behind it are like not new. So companies have always wanted more productivity, more efficiency, and watching your workers to kind of get at that is something that like you know, get dates back to at least the Industrial Revolution, probably before that, right, Like, this is not a new strategy in some ways, but it is changing in some important respects, right, And one of those that I talked about in the book is like, well,
first just that you can integrate these things into new workplaces. So truck cabs, for a long time, we're pretty immune to the kinds of workplace oversight that you saw like in warehouses or in factories or even in offices, right, just because of the nature of the work and like, in some ways they're like a lagging indicator, right, Like they're they're catching up with some other types of blue collar work. Um, but there are other things I think
about kind of what the trucking case tells us. And as you mentioned right, like post pandemic, there's a lot more concern from managers about workers kind of not given it they're roll or shirking or not paying attention or doing those kinds of things. And so these types of data like data tracking, whether that's like um, you know, location tracking where your workers are, or detecting what they're looking at on a screen right when they're supposed to
be working, or what windows they have open. Um. You see the stuff in school sittings to like the same kind of like procting software that you sometimes see for taking remote exams. Functionally is not so different from some
of this workplace technology tracking like productivity monitoring. More and more kind of back end workplace systems like Microsoft three sixty five include these capabilities that will like report back to a manager about whether the like how many you know, minutes you spend in power Point or whatever stuff like that. So this kind of like measuring work, this is just happening all over the place, and I really don't see
that going away anytime soon, you know. One of the tricks here, one of the problems is that when you measure stuff, you like inherently lose a lot of contexts, and oftentimes the things you can measure, like how many emails somebody said or whatever, is like not an amazing
indicator of whether they're doing like meaningful work. And so workers a lot of times, you know, still have to do the meaningful work, but they also are sort of burdened with making themselves legible to these systems that are like sort of incentivizing or gamifying these things that may or may not be all that meaningful. So I do think that those those dynamics are just popping up, like across a lot of blue collar work, but also like what we think of as kind of more white color
professionalized industries like medicine and law and other contexts. Um. There was this really great article in The New York Times a few months ago that maybe folks saw um by Jodie Cantor and Aria Sundaram, where they talk about this kind of productivity monitoring that's happening, and like one of the examples that they use is of a hospice chaplain like it gets some certain number of points from her employer based on how many visits she makes to
like dying people. I mean, it's like just super super dystopiated. But it's like they talk about a range of different industries and it's clear that this is just sort of coming for everybody in its own Alright, Well, I look forward to our dystopian future where Joe and I are just sending each other to word emails, constantly productive game the algorithm you're prepping for a podcast. Yeah, all right, Karen,
we're going to have to leave it there. Thank you so much for coming on all thoughts and talking about your work. Absolutely fascinating. Oh it's my pleasure. Thanks for having me, Joe. That was interesting. That was so interesting. There's so many I feel like we've gould have talked to Karen for a long time, so many different threads about how like business worked, where power is the appoint the purpose of like you know, letter of the law,
a letter of the rules, so many interesting things. Yeah, I do think that point about how we have rules in place, but actually flexibility to work outside of the rules is really important, like both because it kind of lubricates just what we're doing, like living in New York would be really really difficult if we actually never j walked, for instance. Um, but also there's there's an element of
power to it. And you mentioned this, but if you have a manager in a workplace and they say like, oh, you know, don't worry about this deadline, or you're supposed to work from nine to five, but actually I don't mind if you come in slightly late. That's also a bargaining chip for workplace relationships. Absolutely, And then you think like, Okay, all these businesses like, oh yeah, we love the idea of having this software that allows us to track our
workers and track our worker productivity. But then the software maker then itself becomes a source of power because then they see the equivalent data for fifty other companies that they service, and then they can aggregate that data, and then they know things about how your employees benchmark against employees from other companies that you, as a business owner don't have, and then they sell you things on top
of that. So I think that like, as more jobs are sort of under this surveillance, like again, it seems like it's gonna be this sort of like fascinating power dynamic.
Who is the information about how stuff really works. Yeah, and also the thorny issue of measuring productivity in quality right, and this is something not to get really naval gay zy here, but in the media industry, this is something that's been going on for years where you know, we can look at pure traffic conumbers and say, like, this article generated a lot of traffic, but you can compare it with something that maybe didn't get as much traffic
and say, well, this is objectively a better article like this one has more nuance and more detail, but maybe it wasn't as popular. That's always been a sort of issue in journalists. But Tracy, you and I we've always been good at traffic on two both, like I always liked those rules because I usually like to pretty good at that. We do quality and quantity here. But the gamification of a place absolutely is an interesting one. Tons of stuff to talk about that was fasting. Shall we
leave it there, Let's leave it there, all right. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway and I'm Joe wi Isn't Though. You can follow me on Twitter at the Stalwart Follow our guest Karen Leavy.
She's at Karen Underscore, ec Underscore Levy. Follow our producer Carmen Rodriguez at Carmen armand and check out all of our podcasts Bloomberg under the handle at podcasts, and for more Odd Lots content, go to Bloomberg dot com slash odd Lots, where we push transcripts. Tracy and I blog, and we have a weekly newsletter that you can go to and subscribe to. Thanks for listening to