WEBVTT - What Truckers Already Know About the Future of Electronic Worker Surveillance

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<v Speaker 1>Hello, and welcome to another episode of the Odd Thoughts Podcast.

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<v Speaker 1>I'm Tracy Alloway and I'm Joe. Joe. Do you remember

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<v Speaker 1>when we had Gordon McGill on to talk about trucking. Yeah,

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<v Speaker 1>that's what that's like an iconic. I mean, there's recent,

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<v Speaker 1>but that's like a odd lots classic already and a

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<v Speaker 1>bunch of people of reaching. That was a great episode.

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<v Speaker 1>It was he said, I mean, he said a bunch

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<v Speaker 1>of things that were very interesting, but he said something

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<v Speaker 1>in particular where he was talking about an upcoming book

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<v Speaker 1>by a Cornell University professor called Data Driven, and the

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<v Speaker 1>idea was to explore the role of technology in the

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<v Speaker 1>trucking industry. Yeah. Absolutely, And you know, I think this

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<v Speaker 1>is a really important area to explore because, of course,

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<v Speaker 1>as we've discussed with Gored, but also other episodes that

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<v Speaker 1>we've done on trucking, truckers are monitored increasingly. They're these

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<v Speaker 1>e l d s electronic logging devices, the track hours,

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<v Speaker 1>things like that, and you know, obviously this affects truckers,

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<v Speaker 1>but you know we may all be tracked by e

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<v Speaker 1>l d s as workers were. Right, So there's two

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<v Speaker 1>interesting things here. So one you would expect that monitor

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<v Speaker 1>monitoring technology UM like the e l D s that

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<v Speaker 1>they're using would be sort of like anatama to a

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<v Speaker 1>lot of the truck driving industry, Like a lot of

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<v Speaker 1>truckers go into it thinking they're going to be independent,

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<v Speaker 1>they have the freedom of the road, and then it

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<v Speaker 1>turns out that they're like eye movements and brain waves

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<v Speaker 1>are going to be tracked and monitored. So that's interesting.

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<v Speaker 1>And then secondly, given the shift towards work from home

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<v Speaker 1>for a wide variety of workers, it does seem like

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<v Speaker 1>surveillance technology in general could become more of a thing. Well,

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<v Speaker 1>and the other really important thing that I think maybe

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<v Speaker 1>I don't know something profound about how business works or

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<v Speaker 1>capitalism works, etcetera, is like there is this core problem right,

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<v Speaker 1>like why does e l D exist in the first place,

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<v Speaker 1>attempt to solve problems truckers on the road for too

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<v Speaker 1>long that creates fatigue, that creates accidents, like some sort

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<v Speaker 1>of impulse behind these rules that curtail how long someone

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<v Speaker 1>could be on the road, But rather than address why

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<v Speaker 1>are they on the road to love, why is there

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<v Speaker 1>truck or fatigue? Why has fatigue been part of trucking?

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<v Speaker 1>And you know forever, rather than figuring out different ways

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<v Speaker 1>to do that, let's just crow come up with a

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<v Speaker 1>monitor system, rather than addressing the core issue that creates

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<v Speaker 1>the need for these time constraints and monitoring systems in

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<v Speaker 1>the first right. So the question is also whether or

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<v Speaker 1>not technology is the right solution to the problem it's

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<v Speaker 1>trying to solve. Okay, well, I'm very happy to say

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<v Speaker 1>we have the perfect guest because we are going to

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<v Speaker 1>be speaking with the author of the book that was

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<v Speaker 1>referenced by Gord. We are going to be speaking with

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<v Speaker 1>Karen Leavy. She is an associate professor at Cornell University

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<v Speaker 1>and also the author of Data Driven Truckers Technology and

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<v Speaker 1>the New Workplace Surveillance, which just just came out. So, Karen,

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<v Speaker 1>thank you so much for coming on all thoughts, Thanks

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<v Speaker 1>so much for having me. This is a really interesting

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<v Speaker 1>topic and I'm glad we have the chance to dive

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<v Speaker 1>into it further. Maybe just to begin with, you know,

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<v Speaker 1>Joe kind of alluded to this in the intro, but

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<v Speaker 1>what exactly is the problem that this workplace surveillance technology

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<v Speaker 1>that's been mandatory in the trucking industry. I think since

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<v Speaker 1>seen what exactly is it trying to solve Yeah, I

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<v Speaker 1>mean the way you guys talked about it kind of

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<v Speaker 1>in the lead up, I feel like perfectly encapsulates it.

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<v Speaker 1>So the e l D, the electronic logging device, as

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<v Speaker 1>you mentioned, is federally mandated in the trucking industry. All

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<v Speaker 1>long haul truckers have to buy and install and use them.

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<v Speaker 1>And ostensibly the goal is related to safety, right, as

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<v Speaker 1>you alluded to, we know that truckers are really tired.

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<v Speaker 1>We know they're incredibly overworked and underslept, and obviously that

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<v Speaker 1>has you know, that's high stakes, right. There are thousands

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<v Speaker 1>of truck related accidents a year and fatalities from those accidents.

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<v Speaker 1>It's really cost billions of dollars every year. Um, So

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<v Speaker 1>like nobody wants that, right, and including truckers, nobody wants

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<v Speaker 1>the roads to be on safe. I don't want to

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<v Speaker 1>be next to a tired trucker on the road, nobody, Like,

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<v Speaker 1>we're all aligned on that. But what's interesting, as you

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<v Speaker 1>point out, is not like is you know the way

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<v Speaker 1>that we have sort of chosen to address that in

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<v Speaker 1>this case is via technology. So the electronic logging device

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<v Speaker 1>is sort of, um the centerpiece of this effort to

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<v Speaker 1>make truckers comply with the timekeeping regulations that they're subject to.

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<v Speaker 1>I think this is something Gordon talked about two in

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<v Speaker 1>the episode he was on right, Like, truckers for since

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<v Speaker 1>the thirties have been bound to, you know, work no

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<v Speaker 1>more than a certain number of hours every day and

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<v Speaker 1>every week, and that's for safety reasons. The problem, as

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<v Speaker 1>I know, you know you'll have discussed, you know, on

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<v Speaker 1>on Board show and on other shows, is that the

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<v Speaker 1>way truckers are paid, like does not align with those incentives. Right.

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<v Speaker 1>They're paid by the mile. Truckers have the saying if

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<v Speaker 1>the wheel ain't turn in, you ain't earnin right, Like,

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<v Speaker 1>they're only paid for the time that they're actually moving

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<v Speaker 1>down the highway, not to like sit around resting, right,

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<v Speaker 1>or not to do all the other things that are

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<v Speaker 1>an important, essential part of being a trucker but aren't compensated.

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<v Speaker 1>So the result is that truck ers just want to

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<v Speaker 1>stay on the road as much as they can because

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<v Speaker 1>that's how they make a living. They're in pretty dire

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<v Speaker 1>economic straits to begin with, Like, it's not a mystery

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<v Speaker 1>why they why they end up doing these things. And

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<v Speaker 1>so the E L D is sort of scene is

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<v Speaker 1>like an answer to this, right, a way to sort

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<v Speaker 1>of police this behavior by making it ostensibly harder, although

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<v Speaker 1>not impossible, for truckers to tamper with the log books

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<v Speaker 1>that they used to keep. So they used to do

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<v Speaker 1>this using paper and pencil um and that is like

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<v Speaker 1>a really easy system to kind of falsify or make

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<v Speaker 1>it look like you're running legal when you're not. And

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<v Speaker 1>so the e L the sort of scene as an

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<v Speaker 1>answer to that. You know, I I always was a

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<v Speaker 1>big fan of the song Convoy and there's a line

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<v Speaker 1>of tearing up your swindle sheets, which I didn't really

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<v Speaker 1>you realize the origin of that term until I read

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<v Speaker 1>your book, and the swindle sheets was a nickname for

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<v Speaker 1>the old physical pieces of paper that the truckers used

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<v Speaker 1>to log their hours talk about like, you know, they

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<v Speaker 1>had all different ways I guess of sort of swindle

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<v Speaker 1>lying on these cards. How long was that push to

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<v Speaker 1>How long had that effort been in place to get

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<v Speaker 1>truckers to give up the physical pieces of paper in

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<v Speaker 1>favor of these e L D s. So ELD is

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<v Speaker 1>like first start popping up in you know, discussion around

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<v Speaker 1>regulation in the nineteen eighties, and there's a long history

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<v Speaker 1>of kind of how they eventually become mandatory. At first,

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<v Speaker 1>the government starts to do things like, well, you know,

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<v Speaker 1>maybe we'll make these mandatory for people who have like

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<v Speaker 1>really bad safety records, right for some subset of the

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<v Speaker 1>industry that we kind of think of as habitual VIL violators.

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<v Speaker 1>Then there's a proposed mandate in the that goes nowhere

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<v Speaker 1>right there, legal challenges. It's kind of like a long

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<v Speaker 1>and rocky road to get to the e L demandate

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<v Speaker 1>that we eventually end up with in SEV. But we

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<v Speaker 1>do eventually get there, right And you know, a lot

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<v Speaker 1>of the kind of the research that's in for my

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<v Speaker 1>book is trying to understand that transition looking at the

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<v Speaker 1>arguments that get made on either side of the e

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<v Speaker 1>L DE mandate. You know, from the nineteen eighties and

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<v Speaker 1>even before right, there's some predecessor technologies to that that

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<v Speaker 1>you know, I think set the stage for this up

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<v Speaker 1>to you know, post mandate, looking at what the effects

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<v Speaker 1>have been on the industry. So we definitely want to

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<v Speaker 1>dive into those various arguments. But before we do, can

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<v Speaker 1>you talk little bit about the technology that goes into

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<v Speaker 1>e L d s Because my understanding is. They sort

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<v Speaker 1>of range from pretty basic models to more sophisticated things

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<v Speaker 1>that actually, you know, can measure your brain waves to

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<v Speaker 1>see how awake you are or how much attention you're

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<v Speaker 1>paying to the road. So talk to us about the

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<v Speaker 1>variety of e l d s that we have right now. Yeah,

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<v Speaker 1>this is really crucial. So the e l D itself

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<v Speaker 1>captures some important data, but like, as you say, sometimes

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<v Speaker 1>maybe not that much, like a fairly minimal amount. Basically

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<v Speaker 1>where the truck is and how long it's been being driven, right, Like,

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<v Speaker 1>those are basically the core requirements in the regulations. However,

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<v Speaker 1>it's almost as though the government told everybody, like you

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<v Speaker 1>have to buy a phone that makes phone calls or something, right,

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<v Speaker 1>like you can. It's very hard to find a phone

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<v Speaker 1>that only makes phone calls. Right. If you're going to

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<v Speaker 1>buy a phone that makes phone calls, you're also going

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<v Speaker 1>to buy a phone that takes photos and connects to

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<v Speaker 1>the internet and all this other stuff. Right, Because the

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<v Speaker 1>tech tends to like bundle these things together, and the

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<v Speaker 1>same thing happens in e l d s. So e

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<v Speaker 1>l d s are actually more commonly like a module

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<v Speaker 1>in what's sometimes called the fleet management system or FMS.

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<v Speaker 1>People sometimes call them like a qual calm because qual

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<v Speaker 1>Calm used to be like have a big market share

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<v Speaker 1>in this area. They're all kinds of names for him.

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<v Speaker 1>But now what people think of is the E L D. Actually,

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<v Speaker 1>it's kind of like, you know, it's almost like naming

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<v Speaker 1>the part for the whole, Like it sort of stands

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<v Speaker 1>in for this much broader range of data collection technologies.

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<v Speaker 1>And as you point out, Tracy, those can include things.

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<v Speaker 1>You know, it commonly includes stuff like two way messaging

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<v Speaker 1>or you know, alerting a back office about your fuel

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<v Speaker 1>use or how hard you're breaking or how fast you're going,

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<v Speaker 1>or you know, whether you're changing lanes without signaling, like

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<v Speaker 1>all kinds of like pretty fine grain driving behavior data,

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<v Speaker 1>which is just like very different from what trucking work

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<v Speaker 1>has look like for a long time. Right, Like, if

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<v Speaker 1>you ask folks why they get into trucking, many of

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<v Speaker 1>them say explicitly because they don't want that, right, they

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<v Speaker 1>don't want someone looking over their shoulder kind of measuring

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<v Speaker 1>how they do their work. And you know, some of

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<v Speaker 1>the stuff that's coming up on the horizon more recently

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<v Speaker 1>includes the types of stuff you allude to, right, things

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<v Speaker 1>like driver facing cameras have become much more common. Sometimes

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<v Speaker 1>those are augmented by artificial intelligence that will do things

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<v Speaker 1>like try to assess how fatigued a driver is, and

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<v Speaker 1>they might do that by doing things like measuring, um,

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<v Speaker 1>whether the dry driver's eyelids are fluttering, you know, as

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<v Speaker 1>you know, like when you start to fall asleep, you're

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<v Speaker 1>lets start to flutter your head nods. They can measure

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<v Speaker 1>those kinds of things, and like you know, infer that

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<v Speaker 1>the driver is tired. UM. Some of them, you know,

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<v Speaker 1>they are wearable devices that sometimes get sort of integrated

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<v Speaker 1>into these systems or use kind of um in a

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<v Speaker 1>complimentary way to these systems that do things like you

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<v Speaker 1>said that measure a driver's brain waves, measure a driver's

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<v Speaker 1>heart rate, you know, collecting these other kind of biometric

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<v Speaker 1>signals to alert the back office or to alert you know,

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<v Speaker 1>the driver's safety manager whoever kind of what state they're in.

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<v Speaker 1>So technically the law just require something the bare minimum

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<v Speaker 1>of like okay, something track the truck, the hours on

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<v Speaker 1>the road, etcetera. That needed an electronic version of the

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<v Speaker 1>log book. But it's like the trojan Trojan horse atone,

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<v Speaker 1>like once you get that electronic device in the truck itself,

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<v Speaker 1>then why not add all these other things. Where is

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<v Speaker 1>the impulse coming from to add these other features onto

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<v Speaker 1>the field? Is it from the sort of like yeah,

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<v Speaker 1>who who's benefiting from this and who's making the decision? Yeah,

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<v Speaker 1>we want to stick a camera in the face of

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<v Speaker 1>the trucker and see their face at all time and

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<v Speaker 1>start counting, uh, you know, eyelids opening and closing. Yeah,

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<v Speaker 1>I think that's exactly right. It's like a scaffold, or

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<v Speaker 1>it's like a you know, a Christmas tree, and once

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<v Speaker 1>you have the Christmas tree, you can just pay more

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<v Speaker 1>ornaments on the Christmas tree because you got the Christmas tree. Now.

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<v Speaker 1>So what has happened is that, yes, the government has

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<v Speaker 1>you know, started to say like, we need to collect

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<v Speaker 1>a certain sort of information digitally, and then a lot

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<v Speaker 1>of the impetus for more data collection comes not necessarily

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<v Speaker 1>from the government per se, but from trekking companies. Right

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<v Speaker 1>because those workplace analytics, as you alluded to right in

0:10:48.760 --> 0:10:52.160
<v Speaker 1>the setup to the conversation, workplaces like across all kinds

0:10:52.160 --> 0:10:55.840
<v Speaker 1>of industries and all kinds of professions are increasingly interested

0:10:55.960 --> 0:10:59.640
<v Speaker 1>in using software, sensors or other technologies that are cheaper

0:10:59.640 --> 0:11:02.120
<v Speaker 1>and easy to come by to measure stuff about what

0:11:02.160 --> 0:11:04.600
<v Speaker 1>their workers are doing. And so in some sense, truck

0:11:04.679 --> 0:11:06.800
<v Speaker 1>like trucking companies are doing what all kinds of employers

0:11:06.840 --> 0:11:09.760
<v Speaker 1>are doing, which is measuring more information about what their

0:11:09.800 --> 0:11:12.319
<v Speaker 1>workers are doing on It Actually doesn't end there though,

0:11:12.440 --> 0:11:15.240
<v Speaker 1>right Like on top of that, there are third parties

0:11:15.280 --> 0:11:17.520
<v Speaker 1>that become very interested in this data too, right, So

0:11:17.559 --> 0:11:21.160
<v Speaker 1>insurance companies become interested in it. Um companies that sell

0:11:21.280 --> 0:11:24.160
<v Speaker 1>like parking space reservations to truckers other stuff like that, like,

0:11:24.200 --> 0:11:26.720
<v Speaker 1>they become interested in it. So the data becomes very

0:11:26.760 --> 0:11:29.800
<v Speaker 1>valuable to many different parties. It's just not valuable to

0:11:29.840 --> 0:11:32.600
<v Speaker 1>the trucker, right The trucker is kind of isolated against

0:11:32.640 --> 0:11:35.720
<v Speaker 1>all these parties that are interested in gathering the stata

0:11:35.720 --> 0:11:48.880
<v Speaker 1>about what he's doing. Can you talk a little bit

0:11:48.880 --> 0:11:51.400
<v Speaker 1>more about the insurance angle, because this is sort of

0:11:51.440 --> 0:11:55.559
<v Speaker 1>a a recent theme for us, this idea of insurers

0:11:55.600 --> 0:11:59.120
<v Speaker 1>sort of incentivizing different types of behavior collecting more granular

0:11:59.200 --> 0:12:03.200
<v Speaker 1>data in order to do that. Does the installation of

0:12:03.360 --> 0:12:06.560
<v Speaker 1>y l d s does that actually you know, reduce

0:12:06.640 --> 0:12:09.720
<v Speaker 1>insurance rates for instance, for truck drivers or the truck

0:12:09.800 --> 0:12:15.320
<v Speaker 1>driving companies yeah. So in what I have seen, um,

0:12:15.360 --> 0:12:18.480
<v Speaker 1>it does or it can, and that some insurers insure,

0:12:18.480 --> 0:12:20.200
<v Speaker 1>as I think at this point, are mostly just interested

0:12:20.200 --> 0:12:23.079
<v Speaker 1>in getting the data rather than like really doing much

0:12:23.080 --> 0:12:25.240
<v Speaker 1>with it beyond just like getting the data and integrating

0:12:25.240 --> 0:12:27.720
<v Speaker 1>it into their modeling. So what I've seen is is

0:12:28.080 --> 0:12:30.679
<v Speaker 1>insurance companies offering what they sometimes call like a plug

0:12:30.720 --> 0:12:32.840
<v Speaker 1>in discount. This is not so different from like what

0:12:32.880 --> 0:12:36.600
<v Speaker 1>Progressive does with commercial or with passenger vehicles, right where

0:12:36.600 --> 0:12:39.760
<v Speaker 1>you get some discount on your premia for just installing

0:12:39.760 --> 0:12:43.440
<v Speaker 1>the thing or like just giving data access. I haven't

0:12:43.480 --> 0:12:45.920
<v Speaker 1>yet seen that it's actually had a measurable impact on

0:12:46.640 --> 0:12:49.079
<v Speaker 1>like actual rates within the industry, but you can imagine

0:12:49.160 --> 0:12:51.040
<v Speaker 1>right like this is this is the goal, right is

0:12:51.080 --> 0:12:54.880
<v Speaker 1>to do something like that. So, I mean, we have

0:12:55.040 --> 0:12:58.520
<v Speaker 1>had this mandate in effect for a few years now.

0:12:59.360 --> 0:13:02.360
<v Speaker 1>Is there evident stead is making the road safer? No,

0:13:02.760 --> 0:13:05.800
<v Speaker 1>there's not. There's not evidence that there's making the read safe.

0:13:05.800 --> 0:13:08.720
<v Speaker 1>Thank you for that set up. Um No. So what

0:13:08.760 --> 0:13:11.600
<v Speaker 1>we have seen is that in the few years after

0:13:11.720 --> 0:13:15.520
<v Speaker 1>the e l D mandate took effect, traffic like or

0:13:16.120 --> 0:13:18.839
<v Speaker 1>truck crash fatalities went up. So they hit a thirty

0:13:18.920 --> 0:13:22.640
<v Speaker 1>year high the year after the mandate. UM crash rates

0:13:22.640 --> 0:13:24.920
<v Speaker 1>haven't gone down in some some segments of the industry,

0:13:24.920 --> 0:13:26.840
<v Speaker 1>they've gone up. This is not based on my analysis.

0:13:26.840 --> 0:13:29.720
<v Speaker 1>This is based on like quantitative analysis by some business

0:13:29.720 --> 0:13:33.000
<v Speaker 1>school professors that I talked about in the book. UM.

0:13:33.040 --> 0:13:35.640
<v Speaker 1>But yeah, like if the goal is safety, right, like,

0:13:35.679 --> 0:13:38.320
<v Speaker 1>there is no demonstration that even on its own terms,

0:13:38.320 --> 0:13:40.240
<v Speaker 1>the e l D is succeeding in making the road safer.

0:13:40.280 --> 0:13:41.640
<v Speaker 1>And if you think about why that is, there are

0:13:41.640 --> 0:13:44.000
<v Speaker 1>a couple of reasons that maybe happening. So one of

0:13:44.040 --> 0:13:47.760
<v Speaker 1>them that's like really intuitive is if you tell people, like, hey,

0:13:47.840 --> 0:13:50.000
<v Speaker 1>you know, you need to get from point A to

0:13:50.080 --> 0:13:53.800
<v Speaker 1>point B in eleven hours, like about roughly, Like let

0:13:53.800 --> 0:13:55.640
<v Speaker 1>me try to get home for Christmas in eleven hours,

0:13:55.679 --> 0:13:58.240
<v Speaker 1>Like I will do that. But if it's eleven hours

0:13:58.240 --> 0:14:00.480
<v Speaker 1>and five minutes or if it's twelve hours, like, it's

0:14:00.480 --> 0:14:02.280
<v Speaker 1>not the end of the world. And if I need

0:14:02.280 --> 0:14:04.200
<v Speaker 1>to stop and get a cup of coffee, or if

0:14:04.200 --> 0:14:06.040
<v Speaker 1>I need to like pull over and see if my

0:14:06.120 --> 0:14:08.679
<v Speaker 1>tire looks weird or something like, I can do those things, right,

0:14:08.679 --> 0:14:10.800
<v Speaker 1>I'm not going to like drive like about at a

0:14:10.840 --> 0:14:13.040
<v Speaker 1>hell to do it because I know that that flexibility

0:14:13.160 --> 0:14:15.640
<v Speaker 1>is sort of built into the system. If I tell

0:14:15.679 --> 0:14:18.400
<v Speaker 1>somebody like you have exactly eleven hours and you have

0:14:18.440 --> 0:14:20.880
<v Speaker 1>no more because I'm like I'm tracking this, like I'm

0:14:20.880 --> 0:14:23.800
<v Speaker 1>monitoring you, people will drive very differently, right, And that's

0:14:23.880 --> 0:14:26.000
<v Speaker 1>very intuitive. So what we have seen is that like

0:14:26.080 --> 0:14:29.400
<v Speaker 1>rates of speeding and reckless driving have gone up because

0:14:29.520 --> 0:14:32.960
<v Speaker 1>people feel this extra rigidity in the rules and so,

0:14:33.080 --> 0:14:36.720
<v Speaker 1>like not shockingly, they compensate for this lost productivity by

0:14:36.720 --> 0:14:38.560
<v Speaker 1>trying to make up for that in the way that

0:14:38.600 --> 0:14:41.960
<v Speaker 1>they drive. So that's like one clear mechanism. Another thing

0:14:42.000 --> 0:14:44.080
<v Speaker 1>that like we don't have as clear up data on this,

0:14:44.200 --> 0:14:46.760
<v Speaker 1>but clearly seems to be happening based on my conversations

0:14:46.760 --> 0:14:48.920
<v Speaker 1>with drivers. You know, trucking is kind of an aging

0:14:48.920 --> 0:14:51.480
<v Speaker 1>workforce anyway, like the median trucker ages I think in

0:14:51.520 --> 0:14:53.640
<v Speaker 1>the late forties, and a lot of folks if you

0:14:53.680 --> 0:14:56.480
<v Speaker 1>talk to them, you know, like they are not interested

0:14:56.520 --> 0:14:59.359
<v Speaker 1>in this, right, Veteran drivers who have been driving professionally

0:14:59.440 --> 0:15:03.120
<v Speaker 1>for me be decades, millions of miles without accidents. You

0:15:03.200 --> 0:15:05.320
<v Speaker 1>tell them like, guess what, guess what we're putting in

0:15:05.360 --> 0:15:07.640
<v Speaker 1>the truck now, Like they're not going to stick around

0:15:07.640 --> 0:15:10.120
<v Speaker 1>for that. Trucking has this very high turnover rate anyway,

0:15:10.240 --> 0:15:12.160
<v Speaker 1>people turn in and out of the industry all the time,

0:15:12.360 --> 0:15:14.280
<v Speaker 1>And like, those are the drivers that are the safest.

0:15:14.320 --> 0:15:17.080
<v Speaker 1>You want those drivers who are the most resistant in

0:15:17.120 --> 0:15:19.640
<v Speaker 1>many ways to this kind of oversight. That's the guy

0:15:19.640 --> 0:15:21.000
<v Speaker 1>you want to be next to on the road. You

0:15:21.040 --> 0:15:22.680
<v Speaker 1>don't want to be next to the eighteen year old

0:15:22.720 --> 0:15:25.640
<v Speaker 1>who just got their CDL who like maybe it doesn't

0:15:25.640 --> 0:15:28.320
<v Speaker 1>know any different, right, like, never grew up trucking any

0:15:28.400 --> 0:15:31.000
<v Speaker 1>other way, It's hard to find a blue collar job

0:15:31.040 --> 0:15:34.400
<v Speaker 1>that doesn't involve a lot of oversight and managerial surveillance.

0:15:34.640 --> 0:15:36.320
<v Speaker 1>So those are the folks that will stomach this kind

0:15:36.320 --> 0:15:39.640
<v Speaker 1>of thing, but they're not the safest drivers. Um. Actually,

0:15:39.720 --> 0:15:41.720
<v Speaker 1>this reminds me. I want to ask you. You know

0:15:41.880 --> 0:15:44.600
<v Speaker 1>you studied this issue. I think when we spoke to

0:15:44.720 --> 0:15:47.520
<v Speaker 1>Gored he mentioned a tenure study or something like that.

0:15:47.560 --> 0:15:49.920
<v Speaker 1>I'm not sure if that time frame is entirely accurate,

0:15:49.960 --> 0:15:52.720
<v Speaker 1>but talk to us about how you actually went about

0:15:52.920 --> 0:15:57.600
<v Speaker 1>gathering data and anecdotes for your work. Yeah, so it

0:15:57.640 --> 0:16:00.120
<v Speaker 1>has been cord is right. It has taken me a

0:16:00.240 --> 0:16:03.080
<v Speaker 1>very long time to process the study but that's been good.

0:16:03.120 --> 0:16:05.120
<v Speaker 1>Like I've spent like a quarter of my life thinking

0:16:05.120 --> 0:16:07.840
<v Speaker 1>about trucking at this point, which you know, life comes

0:16:07.840 --> 0:16:11.120
<v Speaker 1>at a best. But um, I started the study inn

0:16:11.120 --> 0:16:14.000
<v Speaker 1>I was a grad student. I was studying sociology um

0:16:14.040 --> 0:16:15.640
<v Speaker 1>and I was a lawyer before that, so I was

0:16:15.680 --> 0:16:19.000
<v Speaker 1>really interested in kind of thinking about law and how

0:16:19.040 --> 0:16:21.040
<v Speaker 1>does it how does it function on the ground, and

0:16:21.040 --> 0:16:22.800
<v Speaker 1>how do people respond to it? And especially I was

0:16:22.840 --> 0:16:26.320
<v Speaker 1>really interested in kind of wine technology and what happens

0:16:26.320 --> 0:16:28.840
<v Speaker 1>when we like surveil people, what happens when we collect

0:16:28.840 --> 0:16:31.280
<v Speaker 1>a bunch of information about what people are doing to

0:16:31.680 --> 0:16:34.040
<v Speaker 1>kind of assess whether they're breaking the rules. And I

0:16:34.080 --> 0:16:35.880
<v Speaker 1>was like sort of looking around for like where's a

0:16:35.920 --> 0:16:38.600
<v Speaker 1>place where I can see this transition in action, Like

0:16:38.640 --> 0:16:40.520
<v Speaker 1>I can really see that happening on the ground, so

0:16:40.560 --> 0:16:43.120
<v Speaker 1>I can get a good sense for like how that

0:16:43.200 --> 0:16:44.960
<v Speaker 1>unfolds or how it changes the way people relate to

0:16:45.000 --> 0:16:47.720
<v Speaker 1>one another. And just by chance, it was like completely

0:16:47.760 --> 0:16:50.920
<v Speaker 1>a fluke. I heard a story on the radio about

0:16:51.440 --> 0:16:54.560
<v Speaker 1>trucking and how like truckers were upset because they were

0:16:54.760 --> 0:16:56.840
<v Speaker 1>dealing with this. But this was again twenty eleven, so

0:16:56.880 --> 0:16:59.000
<v Speaker 1>the e l Demandate was being discussed, although it wasn't

0:16:59.040 --> 0:17:02.240
<v Speaker 1>effective for several years after that, But about this mandate,

0:17:02.280 --> 0:17:05.080
<v Speaker 1>and I thought like, well, that's maybe it. And I

0:17:05.119 --> 0:17:07.679
<v Speaker 1>didn't know any truckers, like I have no truck truckers

0:17:07.680 --> 0:17:10.040
<v Speaker 1>in my family, but I went that day to a

0:17:10.119 --> 0:17:12.760
<v Speaker 1>truck stop just to see, like, what is it like

0:17:12.840 --> 0:17:14.919
<v Speaker 1>to talk to a truck driver? Like is it easy?

0:17:15.080 --> 0:17:18.560
<v Speaker 1>Will they talk to me? And I was like instantaneously hooked.

0:17:18.600 --> 0:17:21.520
<v Speaker 1>I found that truckers were like, they had such interesting stories,

0:17:21.560 --> 0:17:24.800
<v Speaker 1>they were so forthcoming, they were incredibly generous, you know,

0:17:24.880 --> 0:17:27.520
<v Speaker 1>in talking about the stuff that I admit I had

0:17:27.600 --> 0:17:30.439
<v Speaker 1>never thought about. Right, it sounds like the origins of

0:17:30.440 --> 0:17:34.399
<v Speaker 1>of odd lots interest in trucking as well. Yeah, so

0:17:34.440 --> 0:17:39.160
<v Speaker 1>we keep doing trucking episodes. Obviously it's a fascinating, fascinating,

0:17:40.119 --> 0:17:42.200
<v Speaker 1>fascinating angle. You know what you mentioned, you know, the

0:17:42.320 --> 0:17:45.119
<v Speaker 1>legal background, and this brings up something a point that

0:17:45.119 --> 0:17:47.600
<v Speaker 1>I thought was really interesting in your book, which is

0:17:47.640 --> 0:17:51.120
<v Speaker 1>that like society kind of depends on people being able

0:17:51.160 --> 0:17:53.400
<v Speaker 1>to break the law a little bit, that you can't

0:17:53.440 --> 0:17:58.160
<v Speaker 1>actually run a society on everywhere everyone always strictly hewing

0:17:58.240 --> 0:18:00.159
<v Speaker 1>to the law and being punished if they don't you

0:18:00.200 --> 0:18:01.960
<v Speaker 1>explain that a little bit more, because I think that's

0:18:02.040 --> 0:18:03.560
<v Speaker 1>key when you talk about you know what the E

0:18:03.680 --> 0:18:06.320
<v Speaker 1>L D. You can't be ten minutes later, you can't

0:18:06.359 --> 0:18:08.960
<v Speaker 1>drive an extra ten minutes. But what is this concept

0:18:08.960 --> 0:18:12.359
<v Speaker 1>of like we need a little bit of loose areas? Yeah, no,

0:18:12.480 --> 0:18:15.040
<v Speaker 1>I think this is exactly right. Right. It's very easy

0:18:15.160 --> 0:18:18.080
<v Speaker 1>and intuitive to say, like, well, if we have a law,

0:18:18.160 --> 0:18:21.080
<v Speaker 1>people should follow the law, and like therefore, you know,

0:18:21.240 --> 0:18:23.560
<v Speaker 1>if we assume that the law is legitimate or has

0:18:23.600 --> 0:18:25.720
<v Speaker 1>been reached in like a democratic way or whatever, like

0:18:25.720 --> 0:18:28.480
<v Speaker 1>people should just follow it. But like that doesn't really

0:18:28.520 --> 0:18:30.600
<v Speaker 1>hold up too much scrutiny, right, And there's tons of

0:18:30.640 --> 0:18:34.080
<v Speaker 1>places where we see that actually, like social life would

0:18:34.119 --> 0:18:36.679
<v Speaker 1>kind of fall apart if people actually followed laws to

0:18:36.720 --> 0:18:39.879
<v Speaker 1>the letter. Um, you know, like one of the examples

0:18:39.920 --> 0:18:41.560
<v Speaker 1>days in the book is just like speeding, right, Like

0:18:41.600 --> 0:18:44.000
<v Speaker 1>I think if you were told that you were if

0:18:44.000 --> 0:18:45.720
<v Speaker 1>you got a ticket for driving sixty six and a

0:18:45.760 --> 0:18:47.399
<v Speaker 1>sixty five, not as a trucker but just as like

0:18:47.440 --> 0:18:50.359
<v Speaker 1>a regular car driver, people like we would be like, what,

0:18:50.480 --> 0:18:53.560
<v Speaker 1>that's not the law, and like it is technically, but

0:18:53.640 --> 0:18:57.000
<v Speaker 1>like nobody really expects that that's the law. Another thing

0:18:57.000 --> 0:18:58.480
<v Speaker 1>I talked about in the book that kind of hits

0:18:58.480 --> 0:19:01.320
<v Speaker 1>this home is um in in like labor actions and

0:19:01.440 --> 0:19:05.040
<v Speaker 1>you know collective action, like a pretty common worker strategy

0:19:05.160 --> 0:19:07.080
<v Speaker 1>is the work to rule labor action. I don't know

0:19:07.080 --> 0:19:10.040
<v Speaker 1>if this is something it's familiar to odd lets listeners

0:19:10.040 --> 0:19:11.760
<v Speaker 1>that we're in work to rule. What you do, it's

0:19:11.840 --> 0:19:14.760
<v Speaker 1>it's like a work slowdown, and you achieve it by

0:19:14.800 --> 0:19:17.000
<v Speaker 1>like suddenly you like really pay attention to all the

0:19:17.080 --> 0:19:19.960
<v Speaker 1>rules that are in like the cool books. You start

0:19:19.680 --> 0:19:22.119
<v Speaker 1>track like spells out that you work this amount of

0:19:22.119 --> 0:19:24.600
<v Speaker 1>hours every week, and you work exactly that amount of

0:19:24.600 --> 0:19:27.679
<v Speaker 1>hours and you just do it right. And like the

0:19:27.720 --> 0:19:30.760
<v Speaker 1>whole point is that by following the rules like that

0:19:30.880 --> 0:19:33.920
<v Speaker 1>is not actually what we necessarily wanted people to do,

0:19:34.080 --> 0:19:36.600
<v Speaker 1>because if you do it like, that's the slowdown. Right.

0:19:36.640 --> 0:19:38.520
<v Speaker 1>The reason it's effective is because that's clearly not the

0:19:38.560 --> 0:19:41.040
<v Speaker 1>expectation most of the time. And there's this happens just

0:19:41.080 --> 0:19:44.080
<v Speaker 1>all over the place. UM there was like a few

0:19:44.160 --> 0:19:46.159
<v Speaker 1>years ago in New York City and in many cities

0:19:46.280 --> 0:19:48.840
<v Speaker 1>right there are these big moves like um these vision

0:19:48.920 --> 0:19:50.959
<v Speaker 1>zero kind of projects where they're like we should have

0:19:51.000 --> 0:19:55.840
<v Speaker 1>no jaywalking because jaywalking leads to traffic accidents. And then

0:19:55.920 --> 0:19:58.640
<v Speaker 1>like when police start really cracking down on jaywalking, there's

0:19:58.680 --> 0:20:01.399
<v Speaker 1>like some economics analysis where people say, like, you know,

0:20:01.440 --> 0:20:04.560
<v Speaker 1>actually jaywalking is really efficient, and if we like we

0:20:04.560 --> 0:20:07.040
<v Speaker 1>would lose like a good deal of economic efficiency if

0:20:07.040 --> 0:20:09.600
<v Speaker 1>people actually follow these rules, because like we actually want

0:20:09.600 --> 0:20:11.199
<v Speaker 1>people to bend the rules a lot of the time, right,

0:20:11.240 --> 0:20:14.240
<v Speaker 1>We've built a society in which, like, following a bunch

0:20:14.240 --> 0:20:17.040
<v Speaker 1>of rules to the letter can be really inefficient or

0:20:17.040 --> 0:20:19.679
<v Speaker 1>ineffective or can cause other harms. And that's definitely the

0:20:19.720 --> 0:20:22.240
<v Speaker 1>case in trucking, right, Like, clearly a lot of problems

0:20:22.240 --> 0:20:24.760
<v Speaker 1>with the status quo and trucking. Like I'm not suggesting

0:20:24.800 --> 0:20:27.080
<v Speaker 1>that everything is great and trucking and the labor conditions

0:20:27.080 --> 0:20:28.560
<v Speaker 1>are wonderful and if we got rid of the E

0:20:28.640 --> 0:20:30.720
<v Speaker 1>L D s everything would be fine, Like, I don't

0:20:30.840 --> 0:20:33.640
<v Speaker 1>view it that way, but it is definitely the case

0:20:33.720 --> 0:20:36.000
<v Speaker 1>that we have all sort of come to rely on

0:20:36.440 --> 0:20:39.320
<v Speaker 1>the rules being more like guidelines in this context, right,

0:20:39.359 --> 0:20:43.000
<v Speaker 1>and that people budge them in order to move stuff

0:20:43.040 --> 0:20:46.000
<v Speaker 1>at the pace at which we kind of all demand it. Um,

0:20:46.080 --> 0:20:47.879
<v Speaker 1>So when we crack down on a rule without kind

0:20:47.880 --> 0:20:50.080
<v Speaker 1>of considering that broader context, you end up with this

0:20:50.119 --> 0:20:53.280
<v Speaker 1>weird situation where you know you haven't addressed the underlying

0:20:53.320 --> 0:20:55.439
<v Speaker 1>reasons people are breaking the rule. You're just kind of

0:20:55.440 --> 0:20:58.280
<v Speaker 1>policing them harder for it. You know. Joe mentioned the

0:20:58.359 --> 0:21:02.439
<v Speaker 1>swindle books earlier, like the the analog log books that

0:21:02.440 --> 0:21:06.400
<v Speaker 1>truck drivers used to keep. And I remember I used to, Um,

0:21:06.440 --> 0:21:08.360
<v Speaker 1>I used to fly planes when I was like nine

0:21:08.440 --> 0:21:10.480
<v Speaker 1>years old. I don't know that you flew because my

0:21:10.520 --> 0:21:12.840
<v Speaker 1>dad's out. Yeah, but I didn't know you were a pilot.

0:21:12.960 --> 0:21:15.720
<v Speaker 1>Well not, but I had a pilot's log book and

0:21:15.920 --> 0:21:17.840
<v Speaker 1>I was supposed to put in like my hours in

0:21:17.880 --> 0:21:21.080
<v Speaker 1>my tiny little cessna, but like I was nine years old,

0:21:21.080 --> 0:21:23.159
<v Speaker 1>and so I just used to pretend to fill it

0:21:23.200 --> 0:21:27.520
<v Speaker 1>out all the time. I didn't know. So my question is, like,

0:21:27.840 --> 0:21:31.480
<v Speaker 1>moving from the analog log books to the e l

0:21:31.560 --> 0:21:35.679
<v Speaker 1>D S how infallible actually is that system? Can that

0:21:35.800 --> 0:21:39.840
<v Speaker 1>information be tampered with or falsified? Yeah, it is a

0:21:39.840 --> 0:21:42.480
<v Speaker 1>great question, and I love that you yourself have falsified

0:21:42.480 --> 0:21:47.680
<v Speaker 1>a log book. So yeah, right, So the whole idea writer,

0:21:47.840 --> 0:21:49.640
<v Speaker 1>like the rhetoric around the e l D is like, oh,

0:21:49.640 --> 0:21:51.520
<v Speaker 1>this is tamper This is a tamper proof version of

0:21:51.520 --> 0:21:53.120
<v Speaker 1>the thing that people have been doing for a long time,

0:21:53.200 --> 0:21:56.160
<v Speaker 1>and certainly it is more difficult writer. It presents different

0:21:56.200 --> 0:21:58.840
<v Speaker 1>kinds of challenges to falsify data and an e l

0:21:58.880 --> 0:22:01.080
<v Speaker 1>D than it would be on a you know, using

0:22:01.119 --> 0:22:03.280
<v Speaker 1>pencil and paper, where like anybody could do it with

0:22:03.440 --> 0:22:06.159
<v Speaker 1>five minutes of thought. Um, but it's not impossible, right,

0:22:06.200 --> 0:22:08.560
<v Speaker 1>as you point out, um, in one of the chapters

0:22:08.560 --> 0:22:10.080
<v Speaker 1>of the book, I go through, like all of these

0:22:10.080 --> 0:22:13.240
<v Speaker 1>different strategies that truckers and other folks used to kind

0:22:13.280 --> 0:22:16.800
<v Speaker 1>of still bend the rules sometimes, right, because like as

0:22:16.840 --> 0:22:18.919
<v Speaker 1>I mentioned, right, you still sometimes need that, or like

0:22:18.960 --> 0:22:21.919
<v Speaker 1>the economy depends on that, or they're expected to do

0:22:21.960 --> 0:22:24.639
<v Speaker 1>it by their managers or whatever it is. Um, Like

0:22:24.680 --> 0:22:27.679
<v Speaker 1>one of the things people will do is what and

0:22:27.720 --> 0:22:29.879
<v Speaker 1>they did this with paper lugs too, is what sometimes

0:22:29.920 --> 0:22:33.720
<v Speaker 1>called a ghost log. So like you sign in as Karen, right,

0:22:33.800 --> 0:22:36.800
<v Speaker 1>if you're Karen, and you do your eleven hours, and

0:22:36.840 --> 0:22:39.399
<v Speaker 1>then you sign in as Joe or as Tracy right

0:22:39.520 --> 0:22:41.960
<v Speaker 1>using some other right, which is like that's not and

0:22:42.000 --> 0:22:44.359
<v Speaker 1>then you have eleven more hours, right, And sometimes like

0:22:44.440 --> 0:22:48.280
<v Speaker 1>some companies they often get like a demo account like

0:22:48.280 --> 0:22:50.560
<v Speaker 1>a John Do kind of account when they sign up

0:22:50.600 --> 0:22:53.119
<v Speaker 1>with the E l D vendor, and so they like

0:22:53.240 --> 0:22:56.480
<v Speaker 1>have these kind of like slush you know, drivers that

0:22:56.520 --> 0:22:58.760
<v Speaker 1>they can use in some cases. I don't think like

0:22:58.800 --> 0:23:00.840
<v Speaker 1>not everybody is doing this, but the strategy that was

0:23:00.880 --> 0:23:04.439
<v Speaker 1>described to me, um other things folks will do. I

0:23:05.000 --> 0:23:07.080
<v Speaker 1>once I was watching I was sitting with a safety

0:23:07.280 --> 0:23:09.600
<v Speaker 1>or with a dispatcher at a trucking company and she

0:23:09.680 --> 0:23:11.600
<v Speaker 1>was talking to this driver and the driver was like, well,

0:23:11.640 --> 0:23:13.320
<v Speaker 1>I'm like four miles from where I need to be,

0:23:13.760 --> 0:23:16.239
<v Speaker 1>but I'm out of hours. What do I do? And

0:23:16.280 --> 0:23:20.159
<v Speaker 1>she was like, well, pull over and then roll to

0:23:20.280 --> 0:23:21.960
<v Speaker 1>the place you have to get to roll to the

0:23:22.000 --> 0:23:25.320
<v Speaker 1>drop off point at less than fifteen miles an hour.

0:23:25.880 --> 0:23:27.680
<v Speaker 1>And the reason was because the e l D s

0:23:27.720 --> 0:23:29.840
<v Speaker 1>all have like a threshold which is usually set by

0:23:29.840 --> 0:23:33.080
<v Speaker 1>the company, and that threshold is like, under fifteen miles

0:23:33.080 --> 0:23:34.960
<v Speaker 1>an hour, it won't register is driving, right, So she

0:23:35.040 --> 0:23:37.400
<v Speaker 1>knew that like, it wouldn't register is driving. What's interesting

0:23:37.440 --> 0:23:40.520
<v Speaker 1>and like both of these examples actually is that it's

0:23:40.560 --> 0:23:43.200
<v Speaker 1>not necessarily the trucker that's like pushing this, right, it's

0:23:43.240 --> 0:23:46.679
<v Speaker 1>oftentimes the company that's telling the driver like here's what

0:23:46.760 --> 0:23:48.200
<v Speaker 1>you need to do. Right, Like it's kind of like

0:23:48.240 --> 0:23:50.960
<v Speaker 1>a winky strategy because they kind of wanted both ways

0:23:50.960 --> 0:23:53.800
<v Speaker 1>in some sense, right, Like they want the control that E.

0:23:53.880 --> 0:23:56.119
<v Speaker 1>L D S afford them, but they also like just

0:23:56.160 --> 0:23:59.040
<v Speaker 1>want the stuff to move. So sometimes they kind of

0:23:59.160 --> 0:24:13.679
<v Speaker 1>coerce or compel drivers to do these things. So, you know,

0:24:13.760 --> 0:24:15.520
<v Speaker 1>one of the things, and I think this is a

0:24:15.600 --> 0:24:18.760
<v Speaker 1>thing that's gonna matter for all workers who are especially

0:24:18.840 --> 0:24:20.920
<v Speaker 1>you know, work from home. That's gonna we know that

0:24:20.920 --> 0:24:23.760
<v Speaker 1>that's going to increase the amount of surveillance on workers

0:24:23.760 --> 0:24:26.919
<v Speaker 1>like are you actually at your desk responding to customers, etcetera?

0:24:26.960 --> 0:24:28.840
<v Speaker 1>Whatever the job. But I think like one thing that

0:24:28.880 --> 0:24:31.760
<v Speaker 1>all this data collection is going to affect everyone is

0:24:31.760 --> 0:24:36.600
<v Speaker 1>like who who knows about how we're done? How who? Who?

0:24:36.640 --> 0:24:39.320
<v Speaker 1>Where is the knowledge stored about how to do a

0:24:39.359 --> 0:24:41.680
<v Speaker 1>good job? And you know, so in the case of trucking,

0:24:41.680 --> 0:24:44.159
<v Speaker 1>like at one point the idea is like, Okay, the

0:24:44.160 --> 0:24:46.720
<v Speaker 1>truck drivers they really like know their area, they know

0:24:46.880 --> 0:24:49.119
<v Speaker 1>the road, they know the warehouses that they go to,

0:24:49.240 --> 0:24:52.320
<v Speaker 1>and there's some sort of like knowledge base that exists

0:24:52.359 --> 0:24:55.560
<v Speaker 1>primarily in the head of the truck driver, that's difficult

0:24:55.560 --> 0:24:58.160
<v Speaker 1>to replicate. And then I imagine, you know, okay, now

0:24:58.320 --> 0:25:00.879
<v Speaker 1>with e l D s, maybe a lot of that

0:25:00.960 --> 0:25:03.240
<v Speaker 1>knowledge isn't at the level of the driver, but maybe

0:25:03.440 --> 0:25:06.119
<v Speaker 1>at uh, you know, whatever, the fleet owner or some

0:25:06.200 --> 0:25:08.560
<v Speaker 1>other entity. But I also have to imagine that even

0:25:08.600 --> 0:25:11.720
<v Speaker 1>for the owner of the trucking fleet, they may be

0:25:11.960 --> 0:25:14.639
<v Speaker 1>losing to some third party company that's building a black

0:25:14.680 --> 0:25:18.239
<v Speaker 1>box AI model that even the company can't access. And

0:25:18.320 --> 0:25:20.719
<v Speaker 1>so like the locusts of like all this knowledge and

0:25:20.840 --> 0:25:23.360
<v Speaker 1>you know, the power that one has with that knowledge

0:25:23.400 --> 0:25:26.520
<v Speaker 1>gets sort of distributed. Can you talk a little bit about,

0:25:26.560 --> 0:25:29.520
<v Speaker 1>like I guess I would say the shifting distribution of

0:25:29.600 --> 0:25:33.679
<v Speaker 1>power and knowledge within the industry as these manufacturers E

0:25:33.760 --> 0:25:38.480
<v Speaker 1>l D manufacturers, third party data providers, software companies that

0:25:38.560 --> 0:25:41.960
<v Speaker 1>provide uh you know, become like, oh, we have we

0:25:42.000 --> 0:25:44.680
<v Speaker 1>have the database, we have the information. Yeah, no, I

0:25:44.720 --> 0:25:47.960
<v Speaker 1>think that's exactly right, right, Like, so the information moves

0:25:48.040 --> 0:25:50.679
<v Speaker 1>right in trucking like people used to talk about it,

0:25:50.720 --> 0:25:52.640
<v Speaker 1>like you're the captain of your ship, right, you get

0:25:52.680 --> 0:25:54.840
<v Speaker 1>to make all the calls because like you're there, nobody

0:25:54.840 --> 0:25:57.240
<v Speaker 1>else is there, and you know what the conditions are,

0:25:57.280 --> 0:25:59.320
<v Speaker 1>like and nobody else does because nobody else is there.

0:26:00.080 --> 0:26:02.199
<v Speaker 1>But as you point out, right, like now more of

0:26:02.240 --> 0:26:05.080
<v Speaker 1>that data is distributed to the firm or to a

0:26:05.160 --> 0:26:08.679
<v Speaker 1>third party. And what's important to recognize about that, I

0:26:08.680 --> 0:26:11.159
<v Speaker 1>think is that like, not only does that change the

0:26:11.200 --> 0:26:13.320
<v Speaker 1>game because somebody else has the data, but the data

0:26:13.359 --> 0:26:14.840
<v Speaker 1>they have is like not quite the same as the

0:26:14.920 --> 0:26:16.879
<v Speaker 1>data you have, right, Like they have some kind of

0:26:16.920 --> 0:26:21.640
<v Speaker 1>abstracted guests about what things are like, Like they know

0:26:21.800 --> 0:26:24.040
<v Speaker 1>what you're how many hours register on your eel D

0:26:24.160 --> 0:26:26.000
<v Speaker 1>and they're going to use that to kind of assess

0:26:26.040 --> 0:26:28.439
<v Speaker 1>whether you have the right to be tired, right, or

0:26:28.440 --> 0:26:29.880
<v Speaker 1>like whether you have the right to stop. Or they

0:26:29.920 --> 0:26:32.800
<v Speaker 1>have some sense of what the weather is like because

0:26:32.800 --> 0:26:35.439
<v Speaker 1>they can look at the weather channel. But that's not

0:26:35.480 --> 0:26:37.119
<v Speaker 1>the same as being in the place and knowing what

0:26:37.160 --> 0:26:40.000
<v Speaker 1>it's like, right. So as things get abstracted, a lot

0:26:40.000 --> 0:26:42.720
<v Speaker 1>of times those you know, kind of more abstract data

0:26:42.760 --> 0:26:45.119
<v Speaker 1>sources get used to challenge the accounts of workers on

0:26:45.160 --> 0:26:47.439
<v Speaker 1>the ground because they're measurable, right, They're the kinds of

0:26:47.440 --> 0:26:49.679
<v Speaker 1>things we can measure. And this happens again not just

0:26:49.760 --> 0:26:52.480
<v Speaker 1>in trucking but all over the place. So, like I

0:26:52.520 --> 0:26:55.240
<v Speaker 1>have a study from a different contacts where I like

0:26:55.240 --> 0:26:57.720
<v Speaker 1>looked at retail workers than kind of how technology is

0:26:57.720 --> 0:27:00.679
<v Speaker 1>affecting them, and they're too, right, Like tail workers and

0:27:00.760 --> 0:27:03.160
<v Speaker 1>some set in some settings do this practice that's called

0:27:03.200 --> 0:27:06.080
<v Speaker 1>client telling, where you like keep a book of business

0:27:06.080 --> 0:27:08.000
<v Speaker 1>and you kind of like know the sizes of your

0:27:08.040 --> 0:27:10.240
<v Speaker 1>favorite customers and stuff, and you know when their birthdays

0:27:10.240 --> 0:27:13.960
<v Speaker 1>are and so like that really is empowering exactly right,

0:27:14.000 --> 0:27:17.480
<v Speaker 1>Like sex stores, those workers like have at the work,

0:27:17.520 --> 0:27:19.160
<v Speaker 1>they work on commission and they have like a really

0:27:19.160 --> 0:27:23.320
<v Speaker 1>good relationship to certain customers. Increasingly, like now they're not

0:27:23.400 --> 0:27:26.080
<v Speaker 1>allowed to keep their own books in business. They have

0:27:26.160 --> 0:27:29.560
<v Speaker 1>to like input that data into some centralized system. And

0:27:29.600 --> 0:27:32.000
<v Speaker 1>what that means is that when they it comes time

0:27:32.000 --> 0:27:34.159
<v Speaker 1>for them to argue for a raise or something like,

0:27:34.200 --> 0:27:36.160
<v Speaker 1>they don't have those bargaining chips because, as you said,

0:27:36.200 --> 0:27:38.440
<v Speaker 1>the data is not in their head. It's now owned

0:27:38.440 --> 0:27:40.200
<v Speaker 1>by the company or it's owned by the software vendor

0:27:40.280 --> 0:27:43.600
<v Speaker 1>or whatever, and so that reduces like they're more substitute

0:27:43.600 --> 0:27:45.920
<v Speaker 1>herbal right, it's it reduces their bargaining power of easy

0:27:46.359 --> 0:27:47.960
<v Speaker 1>the company. And I think you see this kind of

0:27:47.960 --> 0:27:50.640
<v Speaker 1>thing happening just across the board really and a lot

0:27:50.640 --> 0:27:53.359
<v Speaker 1>of different labor contexts. So just on this topic, and

0:27:53.440 --> 0:27:56.439
<v Speaker 1>this is kind of a Devil's Advocate question, but you know,

0:27:56.520 --> 0:27:58.960
<v Speaker 1>our last trucking episode, we were talking a lot about

0:27:59.000 --> 0:28:02.080
<v Speaker 1>how truck drivers end working more hours than they're actually

0:28:02.119 --> 0:28:04.960
<v Speaker 1>paid for because they end up going to warehouses or

0:28:05.000 --> 0:28:07.240
<v Speaker 1>depots or whatever and they have to wait hours and

0:28:07.280 --> 0:28:09.400
<v Speaker 1>hours and hours to pick up or drop off a load.

0:28:10.000 --> 0:28:13.119
<v Speaker 1>If you have this kind of surveillance technology, could it

0:28:13.440 --> 0:28:17.680
<v Speaker 1>not be used to measure, for instance, how much time

0:28:17.680 --> 0:28:22.800
<v Speaker 1>you're idling and then maybe like used to avoid inefficient

0:28:22.920 --> 0:28:26.200
<v Speaker 1>warehouses or make some of those problems, you know, try

0:28:26.240 --> 0:28:30.439
<v Speaker 1>to ameliorate some of those problems. Yeah, definitely, I definitely

0:28:30.440 --> 0:28:32.880
<v Speaker 1>think that can be. I don't think it like redeems

0:28:32.920 --> 0:28:34.840
<v Speaker 1>the whole thing, but it is a silver lining, right that.

0:28:34.960 --> 0:28:37.000
<v Speaker 1>And and exactly those kinds of tools have been built

0:28:37.080 --> 0:28:38.920
<v Speaker 1>using e l D data that kind of give you

0:28:39.200 --> 0:28:41.240
<v Speaker 1>It's almost like the thing where Google will tell you like,

0:28:41.360 --> 0:28:43.040
<v Speaker 1>is there a long wait at this restaurant? Right like

0:28:43.080 --> 0:28:44.760
<v Speaker 1>it will do the same thing for truckers, being like,

0:28:45.360 --> 0:28:47.880
<v Speaker 1>you know, is there a long detention period on average

0:28:47.880 --> 0:28:50.880
<v Speaker 1>at a particular shipper and that potentially can be useful

0:28:50.880 --> 0:28:52.640
<v Speaker 1>to you, right, like to the extent you get to

0:28:52.720 --> 0:28:54.840
<v Speaker 1>control whether you know which which loads are going to

0:28:54.920 --> 0:28:57.040
<v Speaker 1>take to help you kind of control your business. So

0:28:57.080 --> 0:29:00.400
<v Speaker 1>I agree that that kind of transparency can be useful,

0:29:00.480 --> 0:29:03.400
<v Speaker 1>right And it's one example of where you know, it's

0:29:03.480 --> 0:29:05.840
<v Speaker 1>kind of like a more labor friendly way of using

0:29:05.840 --> 0:29:08.840
<v Speaker 1>this data to actually help truckers out. I don't think

0:29:08.840 --> 0:29:11.520
<v Speaker 1>it like redeems the whole because it's like a nice

0:29:11.520 --> 0:29:12.840
<v Speaker 1>thing to kind of put on top of all of

0:29:12.880 --> 0:29:15.000
<v Speaker 1>this additional control. There would be like other ways we

0:29:15.040 --> 0:29:17.680
<v Speaker 1>could ensure that truckers don't lose a bunch of time

0:29:17.720 --> 0:29:20.720
<v Speaker 1>to detention that would be much more direct. But I'm

0:29:20.720 --> 0:29:22.680
<v Speaker 1>in agreement with you that that is like kind of

0:29:22.720 --> 0:29:25.520
<v Speaker 1>a bright spot. Well, although it also seems like, look,

0:29:25.560 --> 0:29:27.959
<v Speaker 1>we just had these two years of like terrible supply

0:29:28.040 --> 0:29:31.760
<v Speaker 1>chain disruptions, Like we're why didn't all this data help us? Then?

0:29:31.800 --> 0:29:33.440
<v Speaker 1>I mean maybe because this is like a once in

0:29:33.480 --> 0:29:37.560
<v Speaker 1>a hundred year crisis we just experienced. But you figured, like, well,

0:29:37.960 --> 0:29:40.920
<v Speaker 1>if all this data was so great at improving supply chains,

0:29:41.440 --> 0:29:43.360
<v Speaker 1>you know, it didn't exactly step up to the plate.

0:29:44.200 --> 0:29:47.480
<v Speaker 1>There's so many things I fascinating angles of this something

0:29:47.480 --> 0:29:50.240
<v Speaker 1>I I wanna again something else in your book that

0:29:50.280 --> 0:29:53.280
<v Speaker 1>really struck me, the social that you mentioned, Like, Okay,

0:29:53.600 --> 0:29:55.640
<v Speaker 1>in many of the cases, the truckers you really want

0:29:55.680 --> 0:29:57.840
<v Speaker 1>on the road are the ones who might be most

0:29:57.880 --> 0:30:01.240
<v Speaker 1>repelled by having this electronic monitor device staring them in

0:30:01.320 --> 0:30:03.600
<v Speaker 1>the face all day. Can you talk a little bit

0:30:03.600 --> 0:30:07.440
<v Speaker 1>about these efforts that UM, the E l D makers

0:30:07.480 --> 0:30:10.000
<v Speaker 1>and companies have put forth to sort of like get

0:30:10.000 --> 0:30:13.720
<v Speaker 1>people comfortable at them. Yeah. So one thing that companies

0:30:13.760 --> 0:30:15.920
<v Speaker 1>sometimes will do, and I've talked to E l D

0:30:16.040 --> 0:30:18.800
<v Speaker 1>vendors that have talked about these strategies and to trucking

0:30:18.800 --> 0:30:22.120
<v Speaker 1>companies themselves that will use them, is that, like in

0:30:22.320 --> 0:30:25.080
<v Speaker 1>rolling out an E l D system or a fleet

0:30:25.080 --> 0:30:28.040
<v Speaker 1>management system, you know, a lot does depend on kind

0:30:28.040 --> 0:30:31.400
<v Speaker 1>of the messaging around that or like what kind of

0:30:31.560 --> 0:30:34.040
<v Speaker 1>culture the company builds around that. UM, And there's a

0:30:34.040 --> 0:30:35.800
<v Speaker 1>bunch of obviously, like the tools can be used in

0:30:35.840 --> 0:30:37.440
<v Speaker 1>all kinds of different ways, and there's a bunch of

0:30:37.560 --> 0:30:40.320
<v Speaker 1>variation and how companies roll them out. One kind of

0:30:40.320 --> 0:30:43.440
<v Speaker 1>interesting thing I saw happening is that, you know, because

0:30:43.480 --> 0:30:46.760
<v Speaker 1>there's now all this data on like like their scorecards,

0:30:46.840 --> 0:30:50.000
<v Speaker 1>that can be generated for each driver based on fuel

0:30:50.040 --> 0:30:52.800
<v Speaker 1>efficiency and how many safety incidents they have, and that

0:30:52.880 --> 0:30:56.040
<v Speaker 1>kind of thing like that becomes really easy. And then

0:30:56.080 --> 0:30:59.440
<v Speaker 1>that also facilitates like not only measuring the driver, but

0:30:59.520 --> 0:31:03.200
<v Speaker 1>comparing the driver against other workers, right, or incentivizing the

0:31:03.280 --> 0:31:05.520
<v Speaker 1>driver kind of like making a like gamifying it, right,

0:31:05.560 --> 0:31:07.160
<v Speaker 1>making it a game about like, well, who can have

0:31:07.160 --> 0:31:09.400
<v Speaker 1>the lowest fuel efficiency. That's a big one, right, because

0:31:09.400 --> 0:31:12.440
<v Speaker 1>that's a big cost driver for trucking firms. And so

0:31:12.560 --> 0:31:14.280
<v Speaker 1>companies will do all kinds of stuff to sort of

0:31:14.280 --> 0:31:18.600
<v Speaker 1>incentivize drivers to sort of comply. Um, you know, like

0:31:18.640 --> 0:31:20.520
<v Speaker 1>a really basic thing is just putting up a list

0:31:20.920 --> 0:31:23.520
<v Speaker 1>of who's the most fuel efficient driver, which they of

0:31:23.560 --> 0:31:26.240
<v Speaker 1>course now have that data, like putting that up you

0:31:26.240 --> 0:31:28.719
<v Speaker 1>know in the central office or something. I've there's some

0:31:28.760 --> 0:31:31.680
<v Speaker 1>pictures in the book of um you know some of

0:31:31.680 --> 0:31:34.080
<v Speaker 1>these what these charts look like they might attach like

0:31:34.160 --> 0:31:37.520
<v Speaker 1>a small financial incentive to it. So, like I talked

0:31:37.520 --> 0:31:39.680
<v Speaker 1>to a company that it was like they drove for

0:31:39.760 --> 0:31:41.320
<v Speaker 1>restaurants and they're like, oh, well, we'll give you a

0:31:41.320 --> 0:31:43.840
<v Speaker 1>gittu divigate to the restaurant that you drive to, which

0:31:43.840 --> 0:31:46.200
<v Speaker 1>doesn't cost them very much, but I guess it's nice

0:31:46.200 --> 0:31:50.360
<v Speaker 1>for the driver. My favorite one is, um where a

0:31:50.360 --> 0:31:53.719
<v Speaker 1>company they were interested in kind of um the drivers

0:31:53.800 --> 0:31:56.760
<v Speaker 1>driving efficiently, and so what they decided to do was

0:31:56.880 --> 0:32:00.760
<v Speaker 1>issue these like small bonuses two drivers wives in the

0:32:00.800 --> 0:32:05.000
<v Speaker 1>wives names when their husbands like met whatever the fuel

0:32:05.040 --> 0:32:07.200
<v Speaker 1>efficiency goal was. And the thinking I asked like, well,

0:32:07.200 --> 0:32:09.040
<v Speaker 1>why the wives, and like, well, you know, once you

0:32:09.160 --> 0:32:11.480
<v Speaker 1>get the wife fund board. Funny, I'm so proud of

0:32:11.480 --> 0:32:15.960
<v Speaker 1>your efficient driving. I'm so proud of your e l

0:32:16.040 --> 0:32:20.040
<v Speaker 1>D compliance fuel efficient driver. Thrilled what people want to

0:32:20.040 --> 0:32:21.960
<v Speaker 1>here when they get home. I know that's what I

0:32:21.960 --> 0:32:25.240
<v Speaker 1>say to my husband every night. No, I mean like

0:32:25.280 --> 0:32:27.080
<v Speaker 1>you have to sort of admire the antinuity. But it

0:32:27.160 --> 0:32:30.520
<v Speaker 1>is an interesting strategy, right to like yeah, exactly like

0:32:30.560 --> 0:32:32.960
<v Speaker 1>you said, to sort of bring the family dynamic into

0:32:33.680 --> 0:32:37.960
<v Speaker 1>this kind of datification of the work. Incredible. Um, well, Karen,

0:32:38.080 --> 0:32:39.840
<v Speaker 1>one of the reasons we wanted to have you on

0:32:40.040 --> 0:32:43.640
<v Speaker 1>is I mean, a, we're fascinated by the trucking industry

0:32:43.640 --> 0:32:47.000
<v Speaker 1>in general. But be we mentioned this in the intro.

0:32:47.400 --> 0:32:50.560
<v Speaker 1>As the world sort of shifts to work from home,

0:32:50.760 --> 0:32:53.160
<v Speaker 1>or at least as there's a little bit more work

0:32:53.160 --> 0:32:55.640
<v Speaker 1>from home than there was before the pandemic. It does

0:32:55.800 --> 0:32:58.000
<v Speaker 1>feel like there is an opportunity for more of this

0:32:58.120 --> 0:33:01.400
<v Speaker 1>kind of workplace surveillance technology to be deployed to a

0:33:01.520 --> 0:33:05.440
<v Speaker 1>broader um workforce. Can you talk to us a little

0:33:05.480 --> 0:33:09.040
<v Speaker 1>bit about what your research tells us about the application

0:33:09.240 --> 0:33:13.160
<v Speaker 1>of this tech to the rest of the labor market. Yeah,

0:33:13.240 --> 0:33:17.480
<v Speaker 1>I definitely agree that workplace surveillance has a very long history, right,

0:33:17.560 --> 0:33:20.719
<v Speaker 1>and the motivations behind it are like not new. So

0:33:20.840 --> 0:33:26.600
<v Speaker 1>companies have always wanted more productivity, more efficiency, and watching

0:33:26.640 --> 0:33:28.720
<v Speaker 1>your workers to kind of get at that is something

0:33:28.760 --> 0:33:31.520
<v Speaker 1>that like you know, get dates back to at least

0:33:31.560 --> 0:33:34.360
<v Speaker 1>the Industrial Revolution, probably before that, right, Like, this is

0:33:34.360 --> 0:33:36.760
<v Speaker 1>not a new strategy in some ways, but it is

0:33:36.880 --> 0:33:40.240
<v Speaker 1>changing in some important respects, right, And one of those

0:33:40.280 --> 0:33:41.760
<v Speaker 1>that I talked about in the book is like, well,

0:33:41.840 --> 0:33:44.680
<v Speaker 1>first just that you can integrate these things into new workplaces.

0:33:44.760 --> 0:33:47.960
<v Speaker 1>So truck cabs, for a long time, we're pretty immune

0:33:48.400 --> 0:33:50.760
<v Speaker 1>to the kinds of workplace oversight that you saw like

0:33:50.880 --> 0:33:54.840
<v Speaker 1>in warehouses or in factories or even in offices, right,

0:33:54.920 --> 0:33:57.200
<v Speaker 1>just because of the nature of the work and like,

0:33:57.240 --> 0:33:59.320
<v Speaker 1>in some ways they're like a lagging indicator, right, Like

0:33:59.360 --> 0:34:02.080
<v Speaker 1>they're they're catching up with some other types of blue

0:34:02.120 --> 0:34:05.200
<v Speaker 1>collar work. Um, but there are other things I think

0:34:05.240 --> 0:34:07.480
<v Speaker 1>about kind of what the trucking case tells us. And

0:34:07.800 --> 0:34:11.080
<v Speaker 1>as you mentioned right, like post pandemic, there's a lot

0:34:11.120 --> 0:34:14.279
<v Speaker 1>more concern from managers about workers kind of not given

0:34:14.320 --> 0:34:17.000
<v Speaker 1>it they're roll or shirking or not paying attention or

0:34:17.040 --> 0:34:19.160
<v Speaker 1>doing those kinds of things. And so these types of

0:34:19.960 --> 0:34:23.680
<v Speaker 1>data like data tracking, whether that's like um, you know,

0:34:23.800 --> 0:34:27.040
<v Speaker 1>location tracking where your workers are, or detecting what they're

0:34:27.040 --> 0:34:29.000
<v Speaker 1>looking at on a screen right when they're supposed to

0:34:29.040 --> 0:34:31.680
<v Speaker 1>be working, or what windows they have open. Um. You

0:34:31.719 --> 0:34:33.919
<v Speaker 1>see the stuff in school sittings to like the same

0:34:34.000 --> 0:34:36.239
<v Speaker 1>kind of like procting software that you sometimes see for

0:34:36.320 --> 0:34:39.799
<v Speaker 1>taking remote exams. Functionally is not so different from some

0:34:39.840 --> 0:34:43.719
<v Speaker 1>of this workplace technology tracking like productivity monitoring. More and

0:34:43.760 --> 0:34:47.200
<v Speaker 1>more kind of back end workplace systems like Microsoft three

0:34:47.239 --> 0:34:51.359
<v Speaker 1>sixty five include these capabilities that will like report back

0:34:51.440 --> 0:34:54.920
<v Speaker 1>to a manager about whether the like how many you know,

0:34:55.000 --> 0:34:57.799
<v Speaker 1>minutes you spend in power Point or whatever stuff like that.

0:34:58.040 --> 0:35:00.880
<v Speaker 1>So this kind of like measuring work, this is just

0:35:00.960 --> 0:35:02.879
<v Speaker 1>happening all over the place, and I really don't see

0:35:02.920 --> 0:35:06.040
<v Speaker 1>that going away anytime soon, you know. One of the

0:35:06.120 --> 0:35:08.279
<v Speaker 1>tricks here, one of the problems is that when you

0:35:08.320 --> 0:35:10.960
<v Speaker 1>measure stuff, you like inherently lose a lot of contexts,

0:35:10.960 --> 0:35:13.120
<v Speaker 1>and oftentimes the things you can measure, like how many

0:35:13.200 --> 0:35:16.520
<v Speaker 1>emails somebody said or whatever, is like not an amazing

0:35:16.560 --> 0:35:20.439
<v Speaker 1>indicator of whether they're doing like meaningful work. And so

0:35:20.920 --> 0:35:23.000
<v Speaker 1>workers a lot of times, you know, still have to

0:35:23.000 --> 0:35:24.719
<v Speaker 1>do the meaningful work, but they also are sort of

0:35:24.800 --> 0:35:28.399
<v Speaker 1>burdened with making themselves legible to these systems that are

0:35:28.400 --> 0:35:30.719
<v Speaker 1>like sort of incentivizing or gamifying these things that may

0:35:30.760 --> 0:35:33.040
<v Speaker 1>or may not be all that meaningful. So I do

0:35:33.120 --> 0:35:35.960
<v Speaker 1>think that those those dynamics are just popping up, like

0:35:36.040 --> 0:35:38.359
<v Speaker 1>across a lot of blue collar work, but also like

0:35:38.360 --> 0:35:40.200
<v Speaker 1>what we think of as kind of more white color

0:35:40.280 --> 0:35:44.480
<v Speaker 1>professionalized industries like medicine and law and other contexts. Um.

0:35:44.520 --> 0:35:46.560
<v Speaker 1>There was this really great article in The New York

0:35:46.600 --> 0:35:50.280
<v Speaker 1>Times a few months ago that maybe folks saw um

0:35:50.320 --> 0:35:53.400
<v Speaker 1>by Jodie Cantor and Aria Sundaram, where they talk about

0:35:53.400 --> 0:35:56.560
<v Speaker 1>this kind of productivity monitoring that's happening, and like one

0:35:56.560 --> 0:35:58.680
<v Speaker 1>of the examples that they use is of a hospice

0:35:58.760 --> 0:36:02.680
<v Speaker 1>chaplain like it gets some certain number of points from

0:36:02.680 --> 0:36:05.600
<v Speaker 1>her employer based on how many visits she makes to

0:36:05.680 --> 0:36:08.759
<v Speaker 1>like dying people. I mean, it's like just super super dystopiated.

0:36:08.760 --> 0:36:11.760
<v Speaker 1>But it's like they talk about a range of different

0:36:11.760 --> 0:36:13.360
<v Speaker 1>industries and it's clear that this is just sort of

0:36:13.400 --> 0:36:16.640
<v Speaker 1>coming for everybody in its own Alright, Well, I look

0:36:16.680 --> 0:36:19.399
<v Speaker 1>forward to our dystopian future where Joe and I are

0:36:19.440 --> 0:36:24.319
<v Speaker 1>just sending each other to word emails, constantly productive game

0:36:24.360 --> 0:36:28.320
<v Speaker 1>the algorithm you're prepping for a podcast. Yeah, all right, Karen,

0:36:28.360 --> 0:36:30.319
<v Speaker 1>we're going to have to leave it there. Thank you

0:36:30.360 --> 0:36:32.839
<v Speaker 1>so much for coming on all thoughts and talking about

0:36:32.880 --> 0:36:36.520
<v Speaker 1>your work. Absolutely fascinating. Oh it's my pleasure. Thanks for

0:36:36.560 --> 0:36:52.759
<v Speaker 1>having me, Joe. That was interesting. That was so interesting.

0:36:52.880 --> 0:36:55.680
<v Speaker 1>There's so many I feel like we've gould have talked

0:36:55.719 --> 0:36:58.440
<v Speaker 1>to Karen for a long time, so many different threads

0:36:58.440 --> 0:37:02.280
<v Speaker 1>about how like business worked, where power is the appoint

0:37:02.360 --> 0:37:05.279
<v Speaker 1>the purpose of like you know, letter of the law,

0:37:05.320 --> 0:37:07.239
<v Speaker 1>a letter of the rules, so many interesting things. Yeah,

0:37:07.239 --> 0:37:10.120
<v Speaker 1>I do think that point about how we have rules

0:37:10.160 --> 0:37:13.759
<v Speaker 1>in place, but actually flexibility to work outside of the

0:37:13.800 --> 0:37:16.680
<v Speaker 1>rules is really important, like both because it kind of

0:37:16.760 --> 0:37:19.719
<v Speaker 1>lubricates just what we're doing, like living in New York

0:37:19.760 --> 0:37:24.000
<v Speaker 1>would be really really difficult if we actually never j walked,

0:37:24.040 --> 0:37:28.080
<v Speaker 1>for instance. Um, but also there's there's an element of

0:37:28.120 --> 0:37:30.560
<v Speaker 1>power to it. And you mentioned this, but if you

0:37:30.600 --> 0:37:33.560
<v Speaker 1>have a manager in a workplace and they say like, oh,

0:37:33.600 --> 0:37:36.720
<v Speaker 1>you know, don't worry about this deadline, or you're supposed

0:37:36.760 --> 0:37:39.279
<v Speaker 1>to work from nine to five, but actually I don't

0:37:39.280 --> 0:37:42.080
<v Speaker 1>mind if you come in slightly late. That's also a

0:37:42.080 --> 0:37:47.240
<v Speaker 1>bargaining chip for workplace relationships. Absolutely, And then you think like, Okay,

0:37:47.280 --> 0:37:49.839
<v Speaker 1>all these businesses like, oh yeah, we love the idea

0:37:49.840 --> 0:37:52.640
<v Speaker 1>of having this software that allows us to track our

0:37:52.680 --> 0:37:56.120
<v Speaker 1>workers and track our worker productivity. But then the software

0:37:56.400 --> 0:37:59.600
<v Speaker 1>maker then itself becomes a source of power because then

0:37:59.640 --> 0:38:02.759
<v Speaker 1>they see the equivalent data for fifty other companies that

0:38:02.800 --> 0:38:05.160
<v Speaker 1>they service, and then they can aggregate that data, and

0:38:05.160 --> 0:38:08.440
<v Speaker 1>then they know things about how your employees benchmark against

0:38:08.480 --> 0:38:12.000
<v Speaker 1>employees from other companies that you, as a business owner

0:38:12.160 --> 0:38:14.200
<v Speaker 1>don't have, and then they sell you things on top

0:38:14.239 --> 0:38:17.320
<v Speaker 1>of that. So I think that like, as more jobs

0:38:17.320 --> 0:38:20.240
<v Speaker 1>are sort of under this surveillance, like again, it seems

0:38:20.280 --> 0:38:23.160
<v Speaker 1>like it's gonna be this sort of like fascinating power dynamic.

0:38:23.200 --> 0:38:25.560
<v Speaker 1>Who is the information about how stuff really works. Yeah,

0:38:25.600 --> 0:38:30.759
<v Speaker 1>and also the thorny issue of measuring productivity in quality right,

0:38:30.800 --> 0:38:33.399
<v Speaker 1>and this is something not to get really naval gay

0:38:33.480 --> 0:38:35.759
<v Speaker 1>zy here, but in the media industry, this is something

0:38:35.800 --> 0:38:38.080
<v Speaker 1>that's been going on for years where you know, we

0:38:38.120 --> 0:38:40.719
<v Speaker 1>can look at pure traffic conumbers and say, like, this

0:38:40.880 --> 0:38:43.480
<v Speaker 1>article generated a lot of traffic, but you can compare

0:38:43.520 --> 0:38:46.360
<v Speaker 1>it with something that maybe didn't get as much traffic

0:38:46.360 --> 0:38:49.360
<v Speaker 1>and say, well, this is objectively a better article like

0:38:49.400 --> 0:38:51.479
<v Speaker 1>this one has more nuance and more detail, but maybe

0:38:51.480 --> 0:38:54.480
<v Speaker 1>it wasn't as popular. That's always been a sort of

0:38:54.520 --> 0:38:57.480
<v Speaker 1>issue in journalists. But Tracy, you and I we've always

0:38:57.480 --> 0:39:00.880
<v Speaker 1>been good at traffic on two both, like I always

0:39:00.920 --> 0:39:03.080
<v Speaker 1>liked those rules because I usually like to pretty good

0:39:03.080 --> 0:39:06.840
<v Speaker 1>at that. We do quality and quantity here. But the

0:39:06.920 --> 0:39:11.560
<v Speaker 1>gamification of a place absolutely is an interesting one. Tons

0:39:11.560 --> 0:39:13.680
<v Speaker 1>of stuff to talk about that was fasting. Shall we

0:39:13.719 --> 0:39:15.360
<v Speaker 1>leave it there, Let's leave it there, all right. This

0:39:15.440 --> 0:39:18.160
<v Speaker 1>has been another episode of the All Thoughts podcast. I'm

0:39:18.160 --> 0:39:20.640
<v Speaker 1>Tracy Alloway. You can follow me on Twitter at Tracy

0:39:20.680 --> 0:39:23.000
<v Speaker 1>Alloway and I'm Joe wi Isn't Though. You can follow

0:39:23.040 --> 0:39:26.760
<v Speaker 1>me on Twitter at the Stalwart Follow our guest Karen Leavy.

0:39:26.880 --> 0:39:32.560
<v Speaker 1>She's at Karen Underscore, ec Underscore Levy. Follow our producer

0:39:32.640 --> 0:39:36.400
<v Speaker 1>Carmen Rodriguez at Carmen armand and check out all of

0:39:36.400 --> 0:39:40.600
<v Speaker 1>our podcasts Bloomberg under the handle at podcasts, and for

0:39:40.680 --> 0:39:43.280
<v Speaker 1>more Odd Lots content, go to Bloomberg dot com slash

0:39:43.320 --> 0:39:46.040
<v Speaker 1>odd Lots, where we push transcripts. Tracy and I blog,

0:39:46.360 --> 0:39:48.080
<v Speaker 1>and we have a weekly newsletter that you can go

0:39:48.160 --> 0:40:04.239
<v Speaker 1>to and subscribe to. Thanks for listening to