Transcript
00:00:00 The following is a conversation with Steve Vasile,
00:00:02 formerly a truck driver and now a sociologist
00:00:06 at the University of Pennsylvania
00:00:07 who studies freight transportation.
00:00:10 His first book, The Big Rig,
00:00:12 Trucking and the Decline of the American Dream,
00:00:15 explains how long haul trucking
00:00:17 went from being one of the best blue collar jobs
00:00:20 to one of the toughest.
00:00:22 His current ongoing book project,
00:00:24 Driverless, Autonomous Trucks
00:00:26 and the Future of the American Trucker,
00:00:28 explores self driving trucks
00:00:30 and their potential impacts on labor and on society.
00:00:34 This is the Lex Friedman podcast.
00:00:36 To support it, please check out our sponsors
00:00:38 in the description.
00:00:39 And now, here’s my conversation with Steve Vasile.
00:00:45 You wrote a book about trucking
00:00:47 called The Big Rig, Trucking and the Decline
00:00:49 of the American Dream,
00:00:51 and you’re currently working on a book
00:00:53 about autonomous trucking called Driverless,
00:00:56 Autonomous Trucks and the Future of the American Trucker.
00:01:00 I have to bring up some Johnny Cash to you
00:01:02 because I was just listening to this song.
00:01:03 He has a ton of songs about trucking,
00:01:06 but one of them I was just listening to,
00:01:08 it’s called All I Do is Drive,
00:01:11 where he’s talking to an old truck driver.
00:01:13 It goes, I asked them if those trucking songs
00:01:17 tell about a life like his.
00:01:19 He said, if you want to know the truth about it,
00:01:22 here’s the way it is.
00:01:24 All I do is drive, drive, drive,
00:01:27 try to stay alive, that’s the chorus,
00:01:29 and keep my mind on my load,
00:01:30 keep my eye upon the road.
00:01:32 I got nothing in common with any man
00:01:34 who’s home every day at five.
00:01:36 All I do is drive, drive, drive,
00:01:39 drive, drive, drive, drive.
00:01:41 So I got to ask you,
00:01:43 same thing that he asked the trucker.
00:01:45 You worked as a trucker for six months
00:01:48 while working on the previous book.
00:01:50 What’s it like to be a truck driver?
00:01:54 I think that captures it.
00:01:57 It really does.
00:01:59 Can you take me through the whole experience,
00:02:01 what it takes to become a trucker,
00:02:03 what actual day to day life was on day one,
00:02:06 week one, and then over time how that changed?
00:02:09 Yeah.
00:02:10 Well, the book is really about how that changed over time.
00:02:14 So my experience, and I’m an ethnographer, right?
00:02:17 So I go in, I live with people,
00:02:21 I work with people, I talk to them,
00:02:23 try to understand their world.
00:02:26 Ethnographer, by the way, what is that?
00:02:29 The science and art of capturing the spirit of a people?
00:02:35 Yeah, life ways.
00:02:36 I think that would be a good way to capture it,
00:02:38 try to understand what makes them unique as a society,
00:02:43 maybe as a subculture, what kind of makes them tick,
00:02:47 that might be different than the way you and I are wired.
00:02:52 And really sort of thickly describe it
00:02:54 would be at least one component of it.
00:02:56 That’s sort of the basic essential.
00:02:59 And then for me, I want to exercise what C. Wright Mills
00:03:04 called the sociological imagination,
00:03:07 which is to put that individual biography
00:03:11 into the long historical sweep of humanity,
00:03:15 if at all possible.
00:03:17 My goals are typically more modest than C. Wright Mills’s.
00:03:21 And to then put that biography in the larger social structure
00:03:26 to try to understand that person’s life
00:03:29 and the way they see the world,
00:03:31 their decisions in light of their interests
00:03:34 relative to others and conflict and power
00:03:36 and all these things that I find interesting.
00:03:38 And conflict and power.
00:03:40 And interesting.
00:03:41 In the context of society and in the context of history.
00:03:43 Yeah.
00:03:44 And the small tangent, what does it take to do that,
00:03:47 to capture this particular group, the spirit, the music,
00:03:54 the full landscape of experiences
00:03:56 that a particular group goes through
00:03:58 in the context of everything else?
00:04:00 You only have a limited amount of time
00:04:02 and you come to the table probably with preconceived notions
00:04:06 that are then quickly destroyed, all that whole process.
00:04:08 So I don’t know if it’s more art or science,
00:04:11 but what does it take to be great at this?
00:04:14 I do think my first book was a success
00:04:18 relative to my goals of trying to really get at the heart
00:04:22 of sort of the central issues
00:04:25 and the lives being led by people.
00:04:28 If I have a resource, a talent,
00:04:32 it’s that I’m a good listener.
00:04:34 I can talk with anybody.
00:04:38 My wife loves to remark on this
00:04:41 that I can sort of sit down with anyone.
00:04:45 I think I learned that from my dad who worked at a factory
00:04:49 and actually had a lot of truckers go through
00:04:51 the gate that he operated.
00:04:53 And he always had a story, a joke for everybody,
00:04:57 kind of got to know everyone individually.
00:04:59 And he just taught me that essentially
00:05:02 everyone has something to teach you.
00:05:04 And I try to embody that.
00:05:06 Like that’s the rule is for me is every single person
00:05:11 I interact with can teach me something.
00:05:14 I gotta ask you, I’m sorry to interrupt
00:05:16 because I’m clearly of the two of us, the poorer listener.
00:05:19 I think you’re a great listener.
00:05:23 Thank you.
00:05:23 I’ve been listening to the podcast.
00:05:24 I think you’re a great listener.
00:05:26 I really appreciate that.
00:05:28 You’ve done a large number of interviews,
00:05:30 like you said, of truckers for this book.
00:05:33 I’m just curious, what are some lessons you’ve learned
00:05:38 about what it takes to listen to a person enough,
00:05:43 maybe guide the conversation enough
00:05:46 to get to the core of the person, the idea,
00:05:49 again, the ethnographer goal to get to the core?
00:05:54 Yeah, I think it doesn’t happen in the moment, right?
00:05:58 So I’m a ruminator.
00:06:01 I just sit with the data for years.
00:06:05 I sat with the trucking data for almost 10 full years
00:06:10 and just thought about the problems and the questions
00:06:13 using everything that I possibly could.
00:06:16 And so in the moment, my ideal interview is I open up
00:06:22 and I say, tell me about your life as a trucker.
00:06:24 And they never shut up.
00:06:26 And they keep telling me the things that I’m interested in.
00:06:29 Now, it never works out that way
00:06:32 because they don’t know what you’re interested in, right?
00:06:34 And so a lot of it is the, as you know,
00:06:38 I think you’re a great interviewer, prep, right?
00:06:41 So you try to get to know a little bit about the person
00:06:45 and sort of understand kind of the central questions
00:06:48 you’re interested in that they can help you explore.
00:06:52 And so I’ve done hundreds of interviews with truck drivers
00:06:56 at this point and I should really go back
00:06:59 and read the original ones.
00:07:01 They were probably terrible.
00:07:02 What’s the process like?
00:07:03 You’re sitting down, do you have an audio recorder
00:07:05 and also taking notes or do you do no audio, just notes or?
00:07:08 Yeah, audio recorder and social scientists
00:07:11 always have to struggle with sampling, right?
00:07:13 Like who do you interview?
00:07:15 Where do you find them?
00:07:15 How do you recruit them?
00:07:17 I just happened to have a sort of natural place to go
00:07:21 that gave me essentially the population
00:07:23 that I was interested in.
00:07:24 So all these long haul truck drivers that I was interested in
00:07:27 they have to stop and get fuel
00:07:29 and get services at truck stops.
00:07:31 So I picked a truck stop at the juncture
00:07:35 of a couple of major interstates,
00:07:36 went into the lounge that drivers have to walk through
00:07:40 with my clipboard and everybody who came through,
00:07:44 I said, hey, are you on break?
00:07:46 And that was sort of the first criteria was,
00:07:49 do you have time, right?
00:07:51 And if they said, yes, I said,
00:07:53 I’d say, I’m a graduate student at Indiana University.
00:07:57 I’m doing a study,
00:07:59 trying to understand more about truck drivers.
00:08:01 Will you sit down with me?
00:08:02 And I think the first,
00:08:04 I think I probably asked like 104 or 103 people
00:08:08 to get the first 100 interviews.
00:08:10 That’s pretty good odds.
00:08:11 It’s amazing, right?
00:08:13 For any response rate like that for interviewing,
00:08:16 these are people who sat down and gave me an hour
00:08:19 or sometimes more of their time,
00:08:21 just randomly at a truck stop.
00:08:23 And it just tells you something about like,
00:08:26 truckers have something to say.
00:08:28 They’re alone a lot.
00:08:30 And so I had to figure out how to kind of
00:08:33 turn the spigot on, you know?
00:08:35 And I got pretty good at it, I think, yeah.
00:08:38 So they have good stories to tell
00:08:40 and they have an active life in the mind
00:08:41 because they spend so much time on the road
00:08:43 just basically thinking.
00:08:45 Yeah, there’s a lot of reflection,
00:08:49 a lot of struggles, you know?
00:08:50 And they take different forms.
00:08:53 One of the things that they talk about
00:08:55 is the impact on their families.
00:08:56 They say truckers have the same rate of divorce
00:08:59 as everybody else.
00:09:00 And that’s because trucking saves so many marriages
00:09:03 because you’re not around and ruins so many.
00:09:05 And so it ends up being a wash.
00:09:08 So I had this experience.
00:09:12 I met another person and he recognized me from a podcast.
00:09:16 And he said, you know, I’m a fan of yours
00:09:18 and a fan of Joe Rogan, but you guys never talk.
00:09:22 You always talk to people with Nobel Prizes.
00:09:24 You always talk to these kinds of people.
00:09:27 You never talk to us regular folk.
00:09:31 And that guy really stuck with me.
00:09:33 First of all, the idea of regular folk is a silly notion.
00:09:36 I think people that win Nobel Prizes
00:09:39 are often more boring than the people, these regular folks
00:09:42 in terms of stories, in terms of richness of experience,
00:09:45 in terms of the ups and downs of life.
00:09:48 And, you know, that really stuck with me
00:09:51 because I set that as a goal for myself
00:09:53 to make sure I talked to regular folk.
00:09:57 And you did just this talking, again, regular folk.
00:10:03 It’s human beings.
00:10:05 All of them have experiences.
00:10:08 If you were to recommend to talk some of these folks
00:10:14 with stories, how would you find them?
00:10:16 Yeah, so I do do this sometimes for journalists
00:10:19 who will come and they want to write about
00:10:21 sort of what’s happening right now in trucking, you know.
00:10:25 And I send them to truck stops.
00:10:26 I say, you know, yeah, there’s a town
00:10:29 called Effingham, Illinois.
00:10:31 And it’s just this place where, you know,
00:10:34 bunch of huge truck stops, tons of trucks
00:10:36 and really nothing else out there.
00:10:38 You know, it’s in the middle of corn country.
00:10:41 And, you know, again, truckers in this, you know,
00:10:44 sadly, I think, you know, the politics of the day,
00:10:48 it’s changing a little bit.
00:10:50 I think there’s a little, the polarization is getting
00:10:54 to the trucking industry in ways that, you know,
00:10:57 maybe we’re seeing in other parts of our social world.
00:11:02 But truckers are generally, you know,
00:11:04 real open sort of friendly folks.
00:11:07 Some of them ultimately like to work alone and be alone.
00:11:11 That’s a relatively small subset, I think.
00:11:15 But all of them are generally, you know,
00:11:17 kind of open, you know, trusting,
00:11:20 willing to have a conversation.
00:11:21 And so, you know, you go to the truck stop
00:11:23 and you go in the lounge and they’re usually,
00:11:26 there’s usually a booth down there
00:11:27 and somebody is sitting at their laptop
00:11:28 or on their phone and willing to strike up a conversation.
00:11:32 You should try that.
00:11:32 You should, you know.
00:11:33 That 100% will try this.
00:11:35 Yeah.
00:11:36 Just again, we’re just going from tangent to tangent.
00:11:38 We’ll return to the main question,
00:11:40 but what do they listen to?
00:11:43 Do they listen to talk radio?
00:11:45 Do they listen to podcasts, audio books?
00:11:47 Do they listen to music?
00:11:48 Do they listen to silence?
00:11:50 Everything.
00:11:51 Everything.
00:11:52 Everything.
00:11:53 Some, I mean, and some still listen to the CB,
00:11:55 which, you know, it’s a ever dwindling group.
00:11:59 They’ll call it the Original Internet Citizens Band.
00:12:02 You know, back in the 70s,
00:12:03 they thought it was going to be the medium of democracy.
00:12:07 And they love to just get on there
00:12:08 and, you know, cruise along one truck after the other
00:12:13 and chat away.
00:12:13 Usually, you know, it’s guys who know each other
00:12:15 from the same company or happen to run into each other.
00:12:18 But other than that, it’s everything under the sun.
00:12:21 You know, and that’s, it’s probably one of the stereotypes
00:12:24 and it’s, I think it was more true in the past, you know,
00:12:28 about the sort of heterogeneity of truck drivers.
00:12:32 They’re a really diverse group now.
00:12:33 You know, there’s definitely a large,
00:12:37 still a large component of rural white guys
00:12:40 who work in the industry,
00:12:42 but there’s a huge growing chunk of the industry
00:12:45 that’s immigrants, people of color, and even some women.
00:12:50 Still huge barriers to women entering it,
00:12:52 but it’s a much more diverse place than most people think.
00:12:57 So let’s return to your journey as a truck driver.
00:13:00 What did it take to become a truck driver?
00:13:03 What were the early days like?
00:13:05 Yeah, so this is, I mean, this is a central part
00:13:07 of the story, right, that I uncovered.
00:13:09 And the good part was that I went in
00:13:12 without knowing what was gonna happen.
00:13:14 So I was able to experience it as a new truck driver would.
00:13:19 It’s one of the important stories in the book
00:13:20 is how that experience is constructed by employers
00:13:24 to sort of, you know, help you think the way
00:13:28 that they would like you to think about the job
00:13:29 and about the industry and about the social relations of it.
00:13:32 So it’s super intimidating.
00:13:37 I say in the book, you know, pretty handy guy,
00:13:40 you know, familiar with tools, machines,
00:13:41 like, you know, comfortable operating stuff,
00:13:44 like from time I was a kid.
00:13:46 The truck was just like a whole nother experience.
00:13:50 I mean, as I think most people think about it,
00:13:52 it’s this big, huge vehicle, right?
00:13:55 It’s really long, it’s 70 feet long,
00:13:58 it can weigh 80,000 pounds.
00:14:00 You know, it does not stop like a car.
00:14:02 It does not turn like a car.
00:14:05 But at least when I started, and this has changed
00:14:10 and it’s part of the technology story of trucking,
00:14:13 the first thing you had to do was learn how to shift it.
00:14:15 And it doesn’t shift like a manual car.
00:14:19 The clutch isn’t synchronized.
00:14:21 So you have to do what’s called double clutch.
00:14:24 And it’s basically the foundational skill
00:14:26 that a truck driver used to have to learn.
00:14:29 So you would, you know, accelerate, say you’re in first gear,
00:14:33 you push in the clutch,
00:14:35 you pull the shifter out of first gear,
00:14:37 you let the clutch out,
00:14:39 and then you let the RPMs of the engine drop an exact amount.
00:14:44 Then you push the clutch back in
00:14:46 and you put it in second gear.
00:14:48 If your timing is off,
00:14:50 those gears aren’t gonna go together.
00:14:52 So if you’re in an intersection,
00:14:54 you’re just gonna get this horrible grinding sound
00:14:57 as you coast, you know, to a dead stop in the,
00:15:00 you know, underneath the stoplight or whatever it is.
00:15:03 So the first thing you have to do is learn to shift it.
00:15:06 And so at least for me and a lot of drivers
00:15:09 who are going to private company CDL schools,
00:15:12 what happens is it’s kind of like a bootcamp.
00:15:14 They ship me three states away from home,
00:15:17 send you a bus ticket and say,
00:15:19 ‘‘Hey, we’ll put you up for two weeks.’’
00:15:21 You sit in a classroom,
00:15:22 you sort of learn the theory of shifting,
00:15:25 the theory of kind of how you fill out your log book,
00:15:29 rules of the road, you know, you do that maybe half the day.
00:15:32 And then the other half you’re in this giant parking lot
00:15:35 with one of these old trucks and just like, you know,
00:15:38 destroying what’s left of the thing, you know,
00:15:41 and it’s lurching and belching smoke
00:15:43 and just making horrible noises and like rattling.
00:15:45 I mean, in these things, like there’s a lot of torque.
00:15:48 And so if you do manage to get it into gear,
00:15:51 but the engine’s lugging,
00:15:52 I mean, it can throw you right out of the seat, right?
00:15:54 So it’s this, it’s like, you know, it’s bull,
00:15:56 you’re trying to ride and it’s super intimidating.
00:16:00 And the thing about it is that for everybody there,
00:16:04 it’s almost everybody there, it’s super high stakes.
00:16:07 So trucking has become a job of last resort
00:16:11 for a lot of people.
00:16:12 And so they, you know, they lose a job in manufacturing,
00:16:16 they get too old to do construction any longer, right?
00:16:20 The knees can no longer handle it.
00:16:22 And they get replaced by a machine,
00:16:25 their job gets, you know, offshored
00:16:27 and they end up going to trucking because it’s a place
00:16:30 where they can maintain their income.
00:16:31 And so it’s super high stress.
00:16:34 Like they’ve left their family behind,
00:16:36 maybe they quit another job.
00:16:38 They’re typically being charged a lot of money.
00:16:40 So that first couple of weeks,
00:16:41 like you might get charged $8,000 by the company
00:16:45 that you have to pay back if you don’t get hired.
00:16:47 And so the stakes are high and this machine is huge
00:16:50 and it’s intimidating.
00:16:52 And so it’s super stressful.
00:16:53 I mean, I watched, you know, grown men break down crying
00:16:57 about like how they couldn’t go home and tell their son
00:17:00 that they had been telling they were gonna, you know,
00:17:02 go become a long haul truck driver that they’d failed.
00:17:05 And it’s kind of this super high stress system.
00:17:08 And it’s designed that way partly
00:17:09 because as one of my trainers later told me,
00:17:11 it’s basically a two week job interview.
00:17:14 Like they’re testing you, they’re seeing like, you know,
00:17:16 how’s this person gonna respond when it’s tough, you know,
00:17:19 when they have to do the right thing and it’s slow
00:17:22 and, you know, they need to learn something,
00:17:24 are they gonna rush, you know,
00:17:26 or are they gonna kind of stay calm, figure it out,
00:17:29 you know, nose to the grindstone.
00:17:31 Cause when you’re a new truck driver, you’re unsupervised,
00:17:34 you know, and that’s what they’re really looking for
00:17:35 is that kind of quality of conscientious work
00:17:39 that’s gonna carry through to the job.
00:17:41 Well, so the truck is such an imposing part
00:17:43 of a traffic scenario.
00:17:45 So you said like turning, it stresses me out every time
00:17:49 I look at a truck cause they, I mean,
00:17:51 the geometry of the problem is so tricky.
00:17:53 And so if you combine the fact that they have to,
00:17:56 like everybody, basically all the cars in the scene
00:17:58 are staring at the truck and they’re waiting,
00:17:59 often in frustration.
00:18:02 And in that mode, you have to then shift gears perfectly
00:18:06 and move perfectly.
00:18:08 And if, when you’re new, especially,
00:18:11 like you’ll probably, for somebody like me,
00:18:12 it feels like it would take years to become calm
00:18:15 and comfortable in that situation
00:18:17 as opposed to be exceptionally stressed under the eyes
00:18:20 of the road, everybody looking at you, waiting for you.
00:18:24 Is that the psychological pressure of that?
00:18:27 Is that something that was really difficult?
00:18:28 Yeah, absolutely.
00:18:30 Again, just, I saw people freeze up, you know,
00:18:33 in that intersection as, you know, horns are blaring
00:18:36 and the truck’s grinding, you know, gears
00:18:38 and you just can’t, you know, and they just shut down.
00:18:40 They’re like, this isn’t for me, I can’t do it.
00:18:42 You’re right, it takes years.
00:18:45 If, you know, trucking is not considered
00:18:47 a skilled occupation, but, you know, my six months there,
00:18:52 and I was a pretty good rookie, but when I finished,
00:18:54 I was still a rookie, even shifting, definitely backing,
00:18:59 tight corners and situations, you know,
00:19:02 I could drive competently, but the difference between me
00:19:05 and someone who had, you know, two, three years
00:19:08 of experience was, it was a giant gulf between us.
00:19:13 And between that and the really skilled drivers
00:19:16 who’ve been doing it for 20 years, you know,
00:19:19 it’s still another step beyond that.
00:19:21 So it is highly skilled.
00:19:22 Would it be fair to break trucking into the task
00:19:25 of driving a truck into two categories?
00:19:28 One is like the local stuff, getting out of the parking lot,
00:19:31 getting into, you know, driving down local streets
00:19:35 and then highway driving, those two tasks.
00:19:38 What are the challenges associated with each task?
00:19:41 You kind of emphasized the first one.
00:19:43 What about the actual like long haul highway driving?
00:19:48 Yeah, so, I mean, and they are very different, right?
00:19:51 And the key with the long haul driving is really a set of,
00:19:58 the way I came to understand it was a set of habits, right?
00:20:03 We have a sense of driving, particularly men, I think,
00:20:07 have a sense of driving as like being really skilled,
00:20:10 is like the goal and you can kind of maneuver yourself
00:20:13 out of in and out of tight spaces with great speed
00:20:16 and breaking and acceleration, you know.
00:20:20 For a really good truck driver,
00:20:22 it’s about understanding traffic and traffic patterns
00:20:26 and making good decisions
00:20:28 so you never have to use those skills.
00:20:30 And the really good drivers, you know,
00:20:33 the mantra is always leave yourself an out, right?
00:20:37 So always have that safe place that you can put that truck
00:20:40 in case that four wheeler in front of you
00:20:43 who’s texting loses control.
00:20:46 You know, what are you gonna do in that situation?
00:20:50 And what really good truck drivers do on the highway
00:20:54 is they just keep themselves
00:20:56 out of those situations entirely.
00:20:59 They see it, they slow down, you know, they avoid it.
00:21:04 And then the local driving is really something
00:21:06 that takes just practice and routine to learn.
00:21:10 You know, this quarter turn,
00:21:12 it feels like the back of the truck sometimes is on delay
00:21:15 when you’re backing it up.
00:21:16 So it’s like, all right, I’m gonna do a quarter turn
00:21:18 of the wheel now to get the effect that I want
00:21:22 like five seconds from now
00:21:24 in where that tail of that trailer is gonna be.
00:21:26 And there’s just no,
00:21:28 I mean, some people have a natural talent for that,
00:21:30 you know, spatial visualization
00:21:32 and kind of calculating those angles and everything,
00:21:35 but there’s really no escaping the fact
00:21:37 that you’ve gotta just do it over and over again
00:21:40 before you’re gonna learn how to do it well.
00:21:42 Do you mind sharing how much you were getting paid,
00:21:46 how much you were making as a truck driver
00:21:48 in your time as a truck driver?
00:21:50 Yeah, I started out at 25 cents a mile
00:21:54 and then I got bumped up to 26 cents a mile.
00:21:56 So we had a minimum pay,
00:22:01 which was sort of a new pay scheme
00:22:03 that the industry had started to introduce to, you know,
00:22:07 because there’s lots of unpaid work and time.
00:22:10 And so we had a minimum pay of $500 a week
00:22:12 that you would get
00:22:13 if you didn’t drive enough miles to exceed that.
00:22:17 You get paid in sort of,
00:22:19 so you get paid when you turn the bills in,
00:22:21 which is the paperwork that goes with the load.
00:22:24 So, you know, you have to get that back to your company
00:22:28 and then that’s how they bill the customer.
00:22:30 And so you might get a bunch of those bills
00:22:32 that kind of bunch up in one week.
00:22:34 So, you know, I might get a paycheck for, you know, $1,200.
00:22:38 And I mean, I was a poor graduate student.
00:22:40 So this was real, real money to me.
00:22:44 And so I had this sort of natural incentive to,
00:22:47 you know, earn a lot or to maximize my pay.
00:22:51 Some weeks were that minimum, 500, very few.
00:22:54 And then some I’d get 1200, 1300 bucks.
00:22:58 Pay has gone up, you know,
00:23:00 typical drivers now starting in the 30s, you know,
00:23:03 in the kind of job that I was in.
00:23:05 30 cents per mile, 30 to 35.
00:23:09 So can we try to reverse engineer that math,
00:23:12 how that maps to the actual hours?
00:23:14 So the hours connected to driving are so widely dispersed,
00:23:19 as you said, some of them don’t count as actual work,
00:23:21 some of it does.
00:23:22 That’s a very interesting discussion
00:23:24 that we’ll then continue
00:23:25 when we start talking about autonomous trucking.
00:23:28 But, you know, you’re saying all these cents per mile
00:23:31 kind of thing.
00:23:31 What, how does that map to like average hourly wage?
00:23:38 Yeah, so, I mean, and this is kind of the,
00:23:41 this is also an interesting technology story in the end.
00:23:44 And it’s the technology story that didn’t happen.
00:23:46 So pay per mile was, you know,
00:23:49 invented by companies when you couldn’t surveil drivers,
00:23:52 you didn’t know what they were doing, right?
00:23:53 And you wanted them to have some skin in the game.
00:23:56 And so you’d say, you know, here’s the load,
00:23:58 it’s going from, you know, for me,
00:24:00 I might start in, you know, the Northeast,
00:24:03 maybe in upstate New York with a load of beer,
00:24:05 and say, here’s this load of beer,
00:24:07 bring it to this address in Michigan,
00:24:09 we’re gonna pay you by the mile, right?
00:24:11 If I was being paid by the hour,
00:24:12 I might just pull over at the diner and have breakfast.
00:24:16 So you’re paid by the mile,
00:24:19 but increasingly over time,
00:24:22 the typical driver is spending more and more time
00:24:26 doing non driving tasks.
00:24:28 There’s lots of reasons for that.
00:24:30 One of which is railroads captured a lot of freight
00:24:32 that goes long distances now.
00:24:34 Another one is traffic congestion.
00:24:37 And the other one is that drivers are pretty cheap.
00:24:39 And they’re almost always the low people
00:24:41 on the totem pole in some segments.
00:24:44 And so their time is used really inefficiently.
00:24:48 So I might go to that brewery
00:24:51 to pick up that load of Bud Light.
00:24:54 And, you know, their dock staff may be busy
00:24:58 loading up five other trucks.
00:25:00 And they’ll say, you know, go over there and sit and wait,
00:25:03 and we’ll call you on the CB when the dock’s ready.
00:25:05 So you wait there a couple hours, they bring you in,
00:25:08 you know, you never know what’s happening in the truck.
00:25:10 Sometimes they’re loading it with a forklift,
00:25:12 maybe they’re throwing 14 pallets on there full of kegs.
00:25:16 But sometimes it’ll take them hours, you know,
00:25:18 and you’re sitting in that truck.
00:25:19 And you’re essentially unpaid.
00:25:22 You know, then you pull out, you’ve got control
00:25:26 over what you’re gonna get paid
00:25:27 based on how you drive that load.
00:25:29 And then on the other end,
00:25:31 you got a similar situation of kind of waiting, so.
00:25:34 So if that’s the way truck drivers are paid,
00:25:37 then there’s a low incentive for the optimization
00:25:40 of the supply chain to make them more efficient, right?
00:25:43 To utilize truck labor more efficiently.
00:25:46 Absolutely.
00:25:48 So that’s a technology problem that,
00:25:51 one of several technology problems that could be addressed.
00:25:57 I mean, so what did, if we just linger on it,
00:26:01 what are we talking about in terms of dollars per hour?
00:26:06 Is it close to minimum wage?
00:26:08 Is it, you know, there’s something you talk about,
00:26:10 there was a conception or a misconception
00:26:15 that truckers get paid a lot for their work.
00:26:19 Do they get paid a lot for their work?
00:26:21 Some do.
00:26:23 And I think that’s part of the complexity.
00:26:26 So, you know, what interested me as an ethnographer
00:26:28 about this was, you know, I’m interested
00:26:31 in the kind of economic conceptions
00:26:32 that people have in their heads
00:26:34 and how they lead to certain decisions in labor markets.
00:26:38 You know, why some people become an entrepreneur
00:26:40 and other people become a wage laborer,
00:26:43 or, you know, why some people wanna be doctors
00:26:45 and other people wanna be truck drivers.
00:26:47 That conception, right, is getting shaped
00:26:50 in these labor markets is the argument of the book.
00:26:53 And the fact that drivers can hear,
00:26:57 or potential drivers can hear about these, you know,
00:26:59 workers who make $100,000 plus,
00:27:01 which happens regularly in the trucking industry.
00:27:04 There are many truck drivers who make more
00:27:06 than $100,000 a year, you know, is an attraction.
00:27:10 But the industry is highly segmented.
00:27:13 And so the entry level segment,
00:27:16 and we can probably get into this,
00:27:18 but, you know, the industry is dominated
00:27:20 by a few dozen really large companies
00:27:24 that are self insured and can train new drivers.
00:27:28 So if you want those good jobs,
00:27:30 you’ve gotta have several years,
00:27:32 up until recently, now the labor market’s becoming tighter,
00:27:35 but you had to have several years of accident free,
00:27:38 you know, perfectly clean record driving
00:27:40 to get into them.
00:27:42 The other part of the segment, you know,
00:27:44 those drivers often don’t make minimum wage.
00:27:47 But this leads to one of the sort of central issues
00:27:50 that has been in the courts,
00:27:52 and in the legislature, in some states,
00:27:56 is, you know, what should truck drivers get paid for?
00:27:59 Right, the industry, you know,
00:28:01 for the last 30 years or so has said, essentially,
00:28:04 it’s the hours that they log for safety reasons
00:28:07 for the Department of Transportation, right?
00:28:11 Now, since the drivers are paid by the mile,
00:28:14 they try to minimize those,
00:28:15 because those hours are limited by the federal government.
00:28:19 So the federal government says,
00:28:19 you can’t drive more than 60 hours in a week
00:28:22 as a long haul truck driver.
00:28:24 And so you wanna drive as many miles as you can
00:28:26 in those 60 hours, and so you under report them, right?
00:28:31 And so what happens is the companies say,
00:28:34 well, that guy, you know, he only said he logged 45 hours
00:28:38 of work that week, or 50 hours of work.
00:28:40 That’s all we have to pay him minimum wage for.
00:28:43 When in fact, typical truck driver in these jobs will work,
00:28:47 according to most people, would sort of define it as like,
00:28:49 okay, I’m at the customer location, I’m waiting to load,
00:28:51 I’m doing some paperwork, you know,
00:28:53 inspecting the truck, I’m fueling it,
00:28:55 just waiting to, you know, get put in the dock,
00:28:58 80 to 90 hours would be sort of a typical work week
00:29:01 for one of these drivers.
00:29:04 And just when you look at that,
00:29:05 they don’t make minimum wage oftentimes.
00:29:07 Right, just to be clear, what we’re dancing around here
00:29:10 is that a little bit over, a little bit under minimum wage
00:29:14 is nevertheless most truck drivers seem to be making
00:29:17 close to minimum wage.
00:29:19 Like this is the, so like we maybe haven’t made that clear.
00:29:23 There’s a few that make quite a bit of money,
00:29:27 but like you’re as an entry and for years,
00:29:31 you’re operating essentially minimum wage
00:29:35 and potentially far less than minimum wage
00:29:37 if you actually count the number of hours
00:29:40 that are taken out of your life
00:29:42 due to your dedication to trucking.
00:29:45 Well, if you count like the hours taken out of your life,
00:29:49 then you gotta go, you know, maybe a full 24.
00:29:52 That’s right, yeah, from family,
00:29:54 from the high quality of life parts of your life.
00:29:59 Yeah, and there’s a whole nother set of rules
00:30:01 that the Department of Labor has,
00:30:03 which basically say that a truck driver
00:30:06 who’s dispatched away from home for more than a day
00:30:09 should get minimum wage 24 hours a day.
00:30:13 And that could be a state minimum wage,
00:30:16 but typically what it would work out to for most drivers
00:30:19 is that, you know, the minimum wage for a truck driver
00:30:22 should be 50s of thousands, you know, 55, $60,000
00:30:26 should be the minimum wage of a truck driver.
00:30:28 And you’ve probably heard about the truck driver shortage.
00:30:31 If, you know, which I hope we can talk about,
00:30:35 if the minimum wage for truck drivers
00:30:37 is as it should be on the books at, you know,
00:30:40 around $60,000, we wouldn’t have a shortage of truck drivers.
00:30:44 Oh, wow.
00:30:46 And to me, 60,000 is not a lot of money
00:30:49 for this kind of job.
00:30:51 Cause you’re, this isn’t, this is essentially two jobs
00:30:56 and two jobs where you don’t get to sleep
00:30:58 with your wife or see your kids at night.
00:31:03 That’s 60,000 is a very little money for that.
00:31:06 But you’re saying if it was 60,000,
00:31:09 you wouldn’t even have the shortage.
00:31:11 If that was the minimum.
00:31:12 If that was the minimum.
00:31:13 And I think that’s what,
00:31:14 now we have drivers who start in the 30s.
00:31:18 Wow, but yeah.
00:31:19 And I mean, so we’re talking two, three jobs really,
00:31:22 when you look at the total hours
00:31:23 that people are working at, you know,
00:31:25 they can work over a hundred.
00:31:26 If they’re a trainer, you know,
00:31:28 training other truck drivers,
00:31:29 well over a hundred hours a week.
00:31:31 So a job of last resort.
00:31:34 Maybe you can jump around from tangent to tangent.
00:31:37 This is such a fascinating and difficult topic.
00:31:41 I heard that there’s a shortage of truck drivers.
00:31:46 So there’s more jobs than truck drivers
00:31:48 willing to take on the job.
00:31:49 Is that the state of affairs currently?
00:31:53 I mean, I think the way that you just put that is right.
00:31:57 We don’t have a shortage of people
00:31:59 who are currently licensed to do the jobs.
00:32:02 So I’m working on a project for the state of California
00:32:05 to look at the shortage of agricultural drivers.
00:32:07 And the first thing that the DMV commissioner of the state
00:32:11 wanted to look at was, you know,
00:32:13 is there actually a shortage of licensed drivers?
00:32:15 He’s like, I’ve got a database here
00:32:17 of all the people who have a commercial driver’s license
00:32:20 who could potentially have the credential to do this.
00:32:24 There are about 145,000 jobs in California
00:32:28 that require a class A CDL,
00:32:31 which would be that commercial driver’s license
00:32:33 that you need for the big trucks.
00:32:36 About 145,000 jobs.
00:32:37 The industry in their, you know,
00:32:39 regular promotion of the idea that there’s a shortage
00:32:43 is always projecting forward and says,
00:32:45 you know, we’re gonna need 165,000 or so
00:32:48 in the next 10 years.
00:32:50 They’re currently like 435,000 people licensed
00:32:53 in the state of California to drive one of these big trucks.
00:32:57 So it is not at all an absence of people who,
00:33:01 I mean, and again, going back
00:33:03 to what we were talking about before,
00:33:05 getting that license is not something
00:33:07 that you just walk down to the DMV and take the test.
00:33:10 Like this is somebody who probably quit another job,
00:33:13 was unemployed, and took months to go to a training school,
00:33:19 paid for that training school oftentimes,
00:33:22 left their family for months,
00:33:24 invested in what they thought was gonna be
00:33:26 a long term career, and then said,
00:33:28 you know what, forget it, I can’t, I can’t do it.
00:33:33 So yeah, so it’s not just skill,
00:33:35 it’s like they were psychologically invested
00:33:37 potentially for months, if not years,
00:33:39 into this kinds of position as perhaps a position
00:33:42 that if they lose their current job, they could fall too.
00:33:46 Okay, so that’s an indication
00:33:47 that there’s something deeply wrong with the job,
00:33:50 if so many licensed people are not willing to take it.
00:33:53 What are the biggest problems
00:33:55 of the job of truck driver currently?
00:33:59 Yeah, the job, the problems with the job
00:34:01 and the labor market, right?
00:34:02 But let’s start with the job, which is, you know, again,
00:34:07 just so much time that’s not compensated directly
00:34:11 for the amount of time.
00:34:12 And that’s just psychologically,
00:34:15 and this was a big part of what I studied
00:34:17 for the first book was, you know,
00:34:20 that conception of like, what’s my time worth, right?
00:34:24 And like, what truck drivers love is oftentimes,
00:34:28 is that tangible outcome based compensation.
00:34:32 So they say, you know what, you know, honest days work,
00:34:37 I work hard, I get paid for what I do,
00:34:38 I drive 500 miles today,
00:34:40 that’s what I’m gonna get paid for.
00:34:42 And then you get to that dock,
00:34:44 and they tell you, sorry, the load’s not ready,
00:34:46 go sit over there, and you stew.
00:34:49 And that weight can break you psychologically
00:34:51 because your time every second becomes more worthless.
00:34:57 Yeah.
00:34:58 Or worth less.
00:35:00 Yeah, and again, the industry is gonna say, for instance,
00:35:04 okay, well, you know, they’ve got skin in the game, right?
00:35:06 That argument about sort of compensation
00:35:08 based on sort of output, right?
00:35:10 But that’s a holdover from when you couldn’t
00:35:12 observe truckers.
00:35:13 Now they all have, you know, satellite linked computers
00:35:15 in the trucks that tell these large companies,
00:35:18 this driver was, you know, at this GPS location
00:35:21 for four and a half hours, right?
00:35:22 So if you wanted to compensate them for that time directly,
00:35:25 and the trucker can’t control what’s happening
00:35:28 on that customer location, you know,
00:35:29 they’re waiting for that, you know, firm,
00:35:31 that customer to tell them, hey, pull in there.
00:35:35 And so what it becomes is just a way to shift
00:35:38 the inefficiencies and the cost of that onto that driver.
00:35:43 Now it’s competitive for customers.
00:35:45 So if you’re Walmart, you might have your choice
00:35:48 of a dozen different trucking companies
00:35:50 that could move your stuff.
00:35:52 And if one of them tells you, hey, you’re not moving
00:35:54 our trucks in and out of your docks fast enough,
00:35:57 we’re gonna charge you for how long our truck
00:35:59 is sitting on your lot.
00:36:01 If you’re Walmart, you’re gonna say,
00:36:02 I’ll go see what the other guy says, right?
00:36:04 And so companies are gonna allow that customer
00:36:08 to essentially waste that driver’s time, you know,
00:36:11 in order to keep that business.
00:36:14 Can you try to describe the economics,
00:36:16 the labor market of the situation?
00:36:18 You mentioned freight and railroad.
00:36:20 What is the sort of the dynamic financials,
00:36:27 the economics of this that allow for such low salaries
00:36:32 to be paid to truckers?
00:36:35 Like what’s the competition?
00:36:37 What’s the alternative to transporting goods via trucks?
00:36:41 Like what seems to be broken here
00:36:43 from an economics perspective?
00:36:44 Yeah, so it’s, well, nothing.
00:36:47 It’s a perfect market, right?
00:36:50 I mean, so for economists, this is how it should work, right?
00:36:53 But the inefficiencies, like you said,
00:36:55 sorry to interrupt, are pushed to the truck driver.
00:36:59 Doesn’t that like spiral, doesn’t that lead to
00:37:02 a poor performance on the part of the truck driver
00:37:04 and just like make the whole thing more and more inefficient
00:37:08 and it results in lower payment
00:37:10 to the truck driver and so on.
00:37:12 It just feels like in capitalism,
00:37:17 you should have a competing solution
00:37:19 in terms of truck drivers.
00:37:21 Like another company that provides transportation via trucks
00:37:25 that creates a much better experience for truck drivers,
00:37:28 making them more efficient, all those kinds of things.
00:37:32 How is the competition being suppressed here?
00:37:34 Yeah, so it is, the competition is based on who’s cheaper.
00:37:39 And this is the cheapest way to move the freight.
00:37:42 Now, there are externalities, right?
00:37:44 I mean, so this is the explanation
00:37:46 that I think is obvious for this, right?
00:37:49 There are lots of costs that,
00:37:53 whether it’s that driver’s time,
00:37:55 whether it’s the time without their family,
00:37:57 whether it’s the fact that they drive through congestion
00:38:02 and spew lots of diesel particulates into cities
00:38:06 where kids have asthma and make our commutes longer
00:38:09 rather than more efficiently use their time
00:38:11 by sort of routing them around congestion
00:38:14 and rush hour and things like that.
00:38:17 This is the cheapest way to move freight.
00:38:21 And so it’s the most competitive.
00:38:23 A big part of this is public subsidy of training.
00:38:26 So when those workers are not paying for the training,
00:38:31 you and I often are.
00:38:32 So if you lose your job because of foreign trade
00:38:38 or you’re a veteran using your GI benefits,
00:38:44 you may very well be offered training,
00:38:48 publicly subsidized training to become a truck driver.
00:38:50 And so all of these are externalities
00:38:53 that the companies don’t have to pay for.
00:38:55 And so this makes it the most profitable way to move freight.
00:38:58 So trucks is way cheaper than trains?
00:39:02 Well, over the long,
00:39:03 so one of the big stories for these companies
00:39:07 is that the average length of haul,
00:39:10 which becomes very important for self driving trucks,
00:39:12 the average length of haul has been steadily declining.
00:39:17 Over the last 15 years or so,
00:39:19 and this is industry collected data
00:39:21 from sort of the big firms that report it,
00:39:23 but roughly been cut in half from typically
00:39:26 about a thousand miles to under 500.
00:39:30 And under 500 is what a driver can move in a day, right?
00:39:36 So you can get loaded, drive and unload,
00:39:40 around 400 miles or something like that.
00:39:44 I wanna steal a good question from the Penn Gazette
00:39:48 interview you did, which people should read.
00:39:49 It’s a great interview.
00:39:51 Was there a golden age for long haul truckers in America?
00:39:55 And if so, this is just a journalistic question.
00:39:58 And if so, what enabled it and what brought it to an end?
00:40:02 Wow, I might have to have you read my answer to that.
00:40:05 That was a few years ago,
00:40:07 be interesting to compare what I’ll say, but.
00:40:10 I mean, one bigger question to ask, I guess,
00:40:12 is like Johnny Cash wrote a lot of songs about truckers.
00:40:17 There used to be a time when perhaps falsely,
00:40:22 perhaps it’s part of the kind of perception
00:40:24 that you study with the labor markets and so on.
00:40:26 There was a perception of truckers being,
00:40:28 first of all, a lucrative job
00:40:30 and second of all, a job to be desired.
00:40:34 Yeah, so I mean, this is,
00:40:37 the trucking industry to me is fascinating,
00:40:40 but I think it should be fascinating to a lot of people.
00:40:43 So the golden age was really two different kinds
00:40:47 of markets as well, right?
00:40:51 Today we have really good jobs and some really bad jobs.
00:40:54 We had the Teamsters Union
00:40:55 that controlled the vast majority of employee jobs.
00:41:01 And even where they had something called
00:41:03 the National Master Freight Agreement.
00:41:05 And this was Jimmy Hoffa who led the union
00:41:10 through its sort of critical period by the mid 60s
00:41:15 had unified essentially the entire nation’s
00:41:19 trucking labor force under one contract.
00:41:22 Now you were either covered by that contract
00:41:26 or your employer paid a lot of attention to it.
00:41:29 And so by the end of the 1970s,
00:41:32 the typical truck driver was making
00:41:34 well more than $100,000,
00:41:36 typical truck driver was making more than $100,000
00:41:39 in today’s dollars and was home every night.
00:41:41 That was without a doubt and even more
00:41:46 than unionized auto workers, steel workers,
00:41:49 10, 20% more than those workers made.
00:41:53 That was the golden age for sort of job quality,
00:41:56 wages, teamster power.
00:41:57 They were without a doubt the most powerful union
00:42:00 in the United States at that time.
00:42:03 At the same time in the 1970s,
00:42:05 you had the mythic long haul trucker.
00:42:09 And these were the guys who were kind of on the margins
00:42:13 of the regulated market,
00:42:15 which is what the teamsters controlled.
00:42:16 A lot of them were in agriculture,
00:42:17 which was never regulated.
00:42:19 So in the new deal, when they decided to regulate trucking,
00:42:22 they didn’t regulate agriculture
00:42:23 because they didn’t wanna drive up food prices,
00:42:25 which would hurt workers in urban areas.
00:42:28 So they essentially left agricultural truckers out of it.
00:42:32 And that’s where a lot of the kind of outlaw,
00:42:34 you know, asphalt cowboy imagery that we get.
00:42:40 And I grew up, I know you didn’t grow up in the US
00:42:44 at this sort of, you know, as a young child.
00:42:47 And I’m a bit older than you, but in the late 70s,
00:42:51 there were movies and TV shows and CBs were a craze.
00:42:54 And it was all these kind of outlaw truckers
00:42:57 who were out there hauling some unregulated freight.
00:43:00 They weren’t supposed to be trying to avoid the bears,
00:43:02 you know, who are the cops.
00:43:03 And, you know, with all this salty language
00:43:07 and these like, you know, terms that only they understood
00:43:10 and, you know, the partying at diners and popping pills,
00:43:13 you know, the California turnarounds.
00:43:15 So asphalt cowboys, truly.
00:43:17 So it’s like another form of cowboy movies.
00:43:20 Oh, absolutely, absolutely.
00:43:22 And I think that sort of masculine ethos of like,
00:43:27 you got 40,000 pounds of something you care about,
00:43:30 I’m your guy, you know,
00:43:31 you needed to go from New York to California,
00:43:33 don’t worry about it, I got it.
00:43:34 That’s appealing and it’s tangible, right?
00:43:37 And you think about people who don’t wanna be paper pusher
00:43:39 and sit in the, I deal with office politics,
00:43:41 like just give me what you care about
00:43:42 and I’ll take care of it, you know, just pay me fair,
00:43:44 you know, and that appeals.
00:43:46 You mentioned unions, Teamsters, Jimmy Hoffa.
00:43:51 Big question, maybe difficult question.
00:43:53 What are some pros and cons of unions historically
00:43:56 and today in the trucking space?
00:43:58 Yeah, well, if you’re a worker, there are a lot of pros.
00:44:03 And I don’t, you know,
00:44:04 and this was one of the things I talked to truckers about
00:44:06 a lot.
00:44:07 Yeah, what’s their perception of Jimmy Hoffa,
00:44:09 for example, of unions?
00:44:11 Yeah, so, and this was probably one of the central
00:44:15 hypotheses that I had going in there.
00:44:16 And it may sound, you know,
00:44:19 someone who does hard science, right?
00:44:21 You may hear a social scientist, you know,
00:44:23 sort of use that terminology,
00:44:24 even other social scientists.
00:44:26 Hypothesis?
00:44:26 Yeah, you know, they don’t like it,
00:44:28 but I do like to think that way.
00:44:31 And my initial hypothesis was that, you know,
00:44:33 and it’s very simple,
00:44:35 that, you know, the tenure of the driver in the industry
00:44:39 would have a strong effect on how they viewed unions.
00:44:43 That, you know, somebody who had experienced unions
00:44:45 would be more favorable
00:44:48 and someone who had not would not be, right?
00:44:51 And that turned out to be the case without a doubt.
00:44:55 But in an interesting way,
00:44:57 which was that even the drivers
00:44:59 who were not part of the union,
00:45:02 who in the kind of public debate of deregulation
00:45:09 were portrayed as these kind of small business truckers
00:45:12 who were getting shut out by the big regulated monopolies
00:45:16 and the Teamsters Union, you know,
00:45:17 the corrupt Teamsters Union.
00:45:19 Even those drivers longed for the days of the Teamsters
00:45:22 because they recognized the overall market impact
00:45:27 that they had.
00:45:27 That trucking just naturally
00:45:31 tended toward excessive competition
00:45:33 that meant that there was no profit to be made
00:45:36 and oftentimes you’d be operating at a loss.
00:45:39 And so even these, you know,
00:45:41 the asphalt cowboy owner operators from back in the day
00:45:44 would tell me when the Teamsters were in power,
00:45:47 I made a lot more money.
00:45:48 And, you know, this is, you know, unions,
00:45:51 at least those kinds of unions, like the Teamsters,
00:45:55 you know, there’s, I think a lot of misconceptions today
00:45:58 sort of popularly about what unions did back then.
00:46:01 They tied wages to productivity.
00:46:04 Like that was the central thing that the Teamsters Union did.
00:46:08 And, you know, there were great accounts
00:46:11 of sort of Jimmy Hoffa’s perspective
00:46:13 for all his portrayal as sort of corrupt
00:46:17 and criminal, and there’s, you know, I’m not disputing that.
00:46:19 He broke a lot of laws.
00:46:22 He was remarkably open about who he was and what he did.
00:46:27 He actually invited a pair, a husband and wife team
00:46:30 of Harvard economists to follow him around
00:46:34 and like opened up the Teamsters books to them
00:46:37 so that they could see how he was, you know,
00:46:40 thinking about negotiating with the employers.
00:46:43 And the Teamsters, and this goes back to the beginning,
00:46:46 and this goes back well before Hoffa,
00:46:48 back to the, you know, 1800s,
00:46:52 they understood that workers did better
00:46:55 if their employers did better.
00:46:57 And the only way the employers would do better
00:46:59 was if they controlled the market.
00:47:01 And so oftentimes the corruption in trucking
00:47:04 was initiated by employers who wanted to limit competition
00:47:07 and they knew they couldn’t limit competition
00:47:09 without the support of labor.
00:47:10 And so you’d get these collusive arrangements
00:47:12 between employers and labor to say no new trucking companies.
00:47:17 There are 10 of us, that’s enough.
00:47:19 We control Seattle, we’re gonna set the price
00:47:21 and we’re not gonna be undercut.
00:47:24 When there’s a shortage of trucks around, it’s great,
00:47:27 rates go up, but you get too many trucks.
00:47:30 It’s very often that you end up operating at a loss
00:47:33 just to keep the doors open.
00:47:35 You know, you don’t have any choice.
00:47:36 You can’t, it’s what economists called derived demand.
00:47:39 You can’t like make up a bunch of trucking services
00:47:41 and store it in a warehouse, right?
00:47:43 You gotta keep those trucks moving to pay the bills.
00:47:47 Can we also lay out the kind of jobs that are in trucking?
00:47:50 What are the best jobs in trucking?
00:47:52 What are the worst jobs in trucking?
00:47:53 What are we, how many jobs are we talking about today?
00:47:56 Yeah.
00:47:57 And what kind of jobs are there?
00:48:00 So there are a number of different segments
00:48:04 and the first part would be, you know, are you offering,
00:48:08 the first question would be,
00:48:08 are you offering services to the public
00:48:11 or are you moving your own freight, right?
00:48:13 So are you a retailer, say Walmart or, you know,
00:48:17 a paper company or something like that
00:48:19 that’s operating your own fleet of trucks?
00:48:22 That’s private trucking.
00:48:25 For hire are the folks who, you know,
00:48:28 offer their services out to other customers.
00:48:31 So you have private and for hire.
00:48:33 In general, for hire pays less.
00:48:37 Is that because of the, something you talk about
00:48:40 with employee versus contractor situation
00:48:43 or are they all tricked or led to become contractors?
00:48:48 That can become a part of it as a strategy,
00:48:52 but the fundamental reason is competition.
00:48:54 So those private carriers aren’t in competition
00:48:58 with other trucking fleets, right?
00:49:00 For their own in house services.
00:49:02 So, you know, they tend to, and this, you know,
00:49:05 the question of why private versus for hire
00:49:07 because for hire is cheaper, right?
00:49:09 And so if you need that, if that trucking service
00:49:14 is central to what you do and you cannot afford disruptions
00:49:17 or volatility in the price of it, you keep it in house.
00:49:19 You should be willing to pay more for that
00:49:21 because it’s more valuable too
00:49:22 and you keep it in house and that.
00:49:23 So that’s an interesting distinction.
00:49:25 What about, and this is kind of moving towards
00:49:27 our conversation of what can and can’t be automated.
00:49:31 How else does it divide the different trucking jobs?
00:49:36 So the next big chunk is kind of
00:49:38 how much stuff are you moving, right?
00:49:40 And so we have what’s called truckload
00:49:43 and truckload means, you know, you can fill up a trailer
00:49:45 either by volume or by weight and then less than truckload.
00:49:50 Less than truckload, the official definition
00:49:52 is like less than 10,000 pounds.
00:49:55 You know, this is gonna be a couple of pallets of this,
00:49:57 a couple of pallets of that.
00:49:58 The process looks really different, right?
00:50:00 So that truckload is, you know, point A to point B,
00:50:04 I’m buying, you know, a truckload of bounty paper towels,
00:50:08 I’m bringing it into, you know, my distribution center,
00:50:11 go pick it up at the bounty plant,
00:50:13 bring it to my distribution center, right?
00:50:15 Nowhere in between do you stop.
00:50:18 At least process that freight.
00:50:19 Less than truckload, what you’ve got is terminal systems.
00:50:22 And this is what you had under regulation too.
00:50:26 And so these terminal systems, what you do is you do
00:50:27 a bunch of local pickup and delivery,
00:50:29 maybe with smaller trucks,
00:50:32 and you pick up two pallets of this here,
00:50:33 four pallets of this there, you bring it to the terminal,
00:50:36 you combine it based on the destination,
00:50:38 you then create a full truckload, you know, trailer,
00:50:43 and you send it to another terminal
00:50:44 where it gets broken back down,
00:50:46 and then out for local delivery.
00:50:47 That’s gonna look a lot like if you send a package by UPS,
00:50:52 right, they pick all these parcels, right,
00:50:54 figure out where they’re all going,
00:50:55 put them on planes or in trailers
00:50:57 going to the same destination,
00:50:58 then break them out to put them
00:50:59 in what they call package cars.
00:51:01 So, before I ask you about autonomous trucks,
00:51:06 let’s just pause for your experience as a trucker.
00:51:11 Did it get lonely?
00:51:12 Like, can you talk about some of your experiences
00:51:15 of what it was actually like?
00:51:16 Did it get lonely?
00:51:17 Yeah, no, I mean, it was, I didn’t have kids at the time.
00:51:21 Now I have kids, I can’t even imagine it.
00:51:25 You know, I’ve been married for five years at the time.
00:51:29 My wife hated it, I hated it.
00:51:31 You know, I describe in the book
00:51:34 the experience of being stuck,
00:51:37 if I remember correctly, it was like Ohio
00:51:40 at this truck stop in the middle of nowhere
00:51:42 and like, you know, sitting on this concrete barrier
00:51:46 and just watching fireworks in the distance
00:51:48 and like eating Chinese food on the 4th of July.
00:51:51 And you know, my wife calls me from like the family barbecue
00:51:55 and our anniversary is July 8th.
00:51:57 And she’s like, are you gonna be home?
00:51:59 And I’m like, I don’t know, you know.
00:52:03 I have a cousin whose husband drove truck
00:52:09 as a truck driver would say, drove truck for a while.
00:52:13 And he told me before I went into it,
00:52:15 he was like, the advantage you have is that you know
00:52:18 that you’re not gonna be doing this long term.
00:52:21 Like, and Lex, I can’t even like,
00:52:24 the emotional content of some of these interviews,
00:52:27 I mean, I would sit down at a truck stop with somebody
00:52:30 I had never met before and you know, you open the spicket
00:52:33 and the last question I would ask drivers
00:52:37 was that by the time I really sort of figured out
00:52:40 how to do it, the last question I would ask them is,
00:52:43 you know, what advice would you give to somebody,
00:52:45 like your nephew, you know, a family friend asks you
00:52:50 about what it’s like to be a driver and should they do it?
00:52:52 What advice would you give them?
00:52:54 And this question, some of these, you know,
00:52:57 grizzled old drivers, you know, tough, tough guys,
00:53:00 would that question would like, some of them would break down
00:53:04 and they would say, I would say to them,
00:53:06 you better have everything
00:53:08 that you ever wanted in life already.
00:53:11 Because I’ve had a car that I’ve had for 10 years,
00:53:15 it’s got 7,000 miles on it.
00:53:17 I own a boat that hasn’t seen the water in five years.
00:53:21 My kids, I didn’t raise them.
00:53:24 Like I’d be out for two weeks at a time,
00:53:27 I’d come home, my wife would give me two kids to punish,
00:53:31 a list of things to do, you know, on Saturday night
00:53:34 and I might leave out Sunday night or Monday morning.
00:53:37 You know, I come home dead tired,
00:53:39 my kids don’t know who I am.
00:53:41 And you know, it was just like,
00:53:44 it was heartbreaking to hear those stories.
00:53:46 And then before you know it, you know,
00:53:49 life is short and just the years run away.
00:53:52 Yeah.
00:53:54 Hard question to ask in that context,
00:53:56 but what’s the best,
00:53:58 what was the best part of being a truck driver?
00:54:04 Was there moments that you truly enjoyed on the road?
00:54:08 Oh, absolutely.
00:54:09 There was, there’s definitely a pride and mastery of,
00:54:13 you know, even basic competence
00:54:14 of sort of piloting this thing safely.
00:54:17 There’s a lot of responsibility to it.
00:54:18 That thing’s dangerous and you know it.
00:54:21 So there’s some pride there.
00:54:23 For me personally, and I know for a lot of other drivers,
00:54:26 it’s just like seeing these behind the scenes places
00:54:29 that you know exist in our economy.
00:54:32 And I think we’re all much more aware of them now
00:54:35 after COVID and supply chain mess that we have.
00:54:38 I don’t know if we’ll talk about that,
00:54:40 but you know, you get to see those places.
00:54:42 You know, you get to see those ports.
00:54:44 You get to see the place where they make the cardboard boxes
00:54:47 that the Huggies diapers go in.
00:54:49 Or the warehouse full of Bud Light.
00:54:52 I moved Bud Light from like upstate New York
00:54:55 and the first load like went to Atlanta, you know?
00:54:58 And then a couple months later,
00:55:00 I circled back through that same brewery
00:55:02 and I brought a load of Bud Light out to Michigan.
00:55:07 And I was like, holy shit, all the Bud Light,
00:55:09 like, you know, for this whole giant swath
00:55:12 of the United States comes from this one plant,
00:55:14 this cavernous plant with like kegs of beer.
00:55:16 And you see that part of the economy
00:55:18 and it’s like, you’re almost like you’re an economic tourist.
00:55:22 And I think all, everybody kind of appreciates that.
00:55:25 Like kind of, it’s almost like a behind the scenes tour.
00:55:29 That wears off after a few months, you know?
00:55:31 You start to see new things less and less frequently.
00:55:34 At first, everything’s novel and sort of life on the road.
00:55:37 And then it becomes just endless miles of white lines
00:55:40 and yellow lines and truck stops.
00:55:43 And the days just blur together.
00:55:46 You know, it’s one loading dock.
00:55:47 It’s one loading dock after another.
00:55:49 So you lose the magic of being on the road.
00:55:52 Yeah, it’s very rare the driver that doesn’t.
00:55:58 You mentioned COVID and supply chain.
00:56:01 While being this, for a brief time,
00:56:04 this member of the supply chain,
00:56:06 what have you come to understand about our supply chain,
00:56:11 United States and global and its resilience
00:56:14 against strategies, catastrophic in the world?
00:56:18 Like COVID, for example.
00:56:20 Yeah, I mean, we have built really long,
00:56:24 really lean supply chains.
00:56:26 And just by definition, they’re fragile.
00:56:31 You know, the current mess that we have,
00:56:34 it’s not gonna clear by Christmas.
00:56:37 It will be lucky if it clears by next Christmas.
00:56:39 Can you describe the current mess in supply chain
00:56:42 that you’re referring to?
00:56:43 Yeah, so we’ve got pile ups of ships
00:56:46 off the coast of California, Long Beach,
00:56:50 and LA in particular, in bad shape.
00:56:54 You know, last I checked, it was around 60 ships,
00:56:56 all of which are holding thousands of containers
00:57:00 full of stuff that retailers were hoping
00:57:02 was gonna be on shelves for the holiday season.
00:57:07 Meanwhile, the port itself has stacks and stacks
00:57:10 of containers that they can’t get rid of.
00:57:12 The truckers aren’t showing up to pick up
00:57:15 the containers that are there,
00:57:17 so they can’t offload the ships that are waiting.
00:57:22 And why aren’t the truckers picking it up?
00:57:26 Partly because there’s a long history of inefficiency
00:57:28 in making them wait,
00:57:29 but it’s because the warehouses are full.
00:57:31 So we’ve had all these perverse outcomes
00:57:36 that no one really expected.
00:57:38 Like in the middle of all these shortages,
00:57:40 people are stockpiling stuff.
00:57:43 So there are suppliers who used to keep two months
00:57:47 of supply of bottled water on hand.
00:57:50 And after going through COVID and not having supply
00:57:53 to send to their customers,
00:57:55 they’re like, we need three months.
00:57:58 Well, our system is not designed for major storage of goods
00:58:02 to go up 50% in a category.
00:58:04 It’s lean.
00:58:05 If you’re a warehouse operator,
00:58:07 you know, you wanna be 90% plus.
00:58:08 You don’t want a lot of open bays sitting around.
00:58:10 So we don’t have 10% extra capacity in warehouses.
00:58:16 We don’t have 10% of them.
00:58:18 Trucking capacity can fluctuate a bit,
00:58:19 but you don’t have that kind of slack.
00:58:23 And now, I mean, and we saw this
00:58:26 right when people shifted consumption.
00:58:28 And I get a little mad when people talk about panic buying
00:58:32 as kind of the reason that we had all these shortages.
00:58:36 It really, like it’s preventing us from understanding,
00:58:40 you know, the real problem there,
00:58:42 which is that lean supply chain.
00:58:44 Sure, there was some panic buying, you know,
00:58:46 no doubt about it,
00:58:47 but we had an enormous shift in people’s behavior.
00:58:51 So with my sister and brother in law,
00:58:55 I own a couple of small businesses and we serve food, right?
00:58:58 So we get, you know, food from Cisco.
00:59:02 Cisco couldn’t get rid of food, right?
00:59:04 Because nobody’s eating out.
00:59:05 So they’ve got, you know, 50 pounds sacks of flour,
00:59:09 you know, sitting in their warehouse
00:59:11 that they can’t get rid of.
00:59:11 They’ve got cases of lettuce and meat and everything else
00:59:14 that’s just gonna go bad.
00:59:17 So that panic buying certainly exacerbated some things
00:59:20 like toilet paper and whatever,
00:59:22 but we saw just a massive change in demand.
00:59:25 And our supply chains are based on historical data, right?
00:59:28 So, you know, that stuff leaves Asia,
00:59:31 you know, months before you wanna have it on the shelves
00:59:34 and you’re predicting based on last year, you know,
00:59:37 what you want on that shelf.
00:59:39 And so it’s a, you know, I guess at its best,
00:59:43 it’s a beautiful symphony of lots of moving parts,
00:59:48 but now everyone can’t get on the same page of music.
00:59:52 But it’s not resilient to changes
00:59:54 in on mass human behavior.
00:59:59 So even like I read somewhere,
01:00:03 maybe you can tell me if it’s true in relation to food,
01:00:06 it’s just the change of human behavior
01:00:08 between going out to restaurants versus eating at home.
01:00:11 As a species, we consume a lot less food that way.
01:00:15 Apparently what I read in restaurants,
01:00:18 like there’s a lot of food just thrown out.
01:00:20 It’s part of the business model.
01:00:23 And so like you then have to move a lot more food
01:00:26 through the whole supply chain.
01:00:28 And now because you’re consuming, you know,
01:00:31 there’s leftovers at home,
01:00:32 you’re consuming much more of the food you’re getting
01:00:37 when you’re eating at home,
01:00:38 that’s creating these bottleneck situations,
01:00:41 problems as you’re referring to,
01:00:42 too much in a certain place, not enough in another place.
01:00:45 And it’s just the supply chain is not robust
01:00:47 those kinds of dynamic shifts in who gets what where.
01:00:53 Yeah.
01:00:54 Yeah, I mean, so, and I have worked in agriculture a bit
01:00:57 on sort of the supply side, you know,
01:01:01 and there are product categories, right?
01:01:03 Where 30% of the crop raised does not get used, right?
01:01:07 Just gets plowed under or wasted.
01:01:09 But here’s the importance of this
01:01:12 in sort of getting this right, you know, like that,
01:01:14 not that like panic buying, you know,
01:01:16 blame the irrational consumer, you know,
01:01:18 look at the hard sort of truth
01:01:21 of the way we’ve set up our economy.
01:01:24 And I’ll ask you this, Lex, I know you’re a hopeful,
01:01:29 optimistic person.
01:01:30 100%, yes.
01:01:31 Yeah, I am too.
01:01:32 I mean, I write about problems all the time.
01:01:34 And so people think I’m sort of like a,
01:01:36 just a Debbie Downer, you know, pessimist,
01:01:39 but I’m a glass half full kind of guy.
01:01:43 Like I want to identify problems so we can solve them.
01:01:47 So let me ask you this,
01:01:48 we’ve got these long lean supply chains.
01:01:52 In the future, do you see more environmental problems
01:01:57 that could disrupt them,
01:02:00 more geopolitical problems that could disrupt trade
01:02:05 from Asia, you know, other institutional failures?
01:02:10 Do those things seem, you know,
01:02:13 potentially more likely in the future
01:02:16 than they have been in say the last 20 years?
01:02:18 Yeah, it almost absolutely seems to be the case.
01:02:21 So you then have to ask the question of
01:02:24 how do we change our supply chains?
01:02:28 Whether it’s making more resilient
01:02:31 or make them less densely connected,
01:02:35 you know, building a, it’s like a, what is it?
01:02:38 You know, the Tesla model for in the automotive sector
01:02:43 of like trying to build everything,
01:02:45 like trying to get the factory to do as much as possible
01:02:48 with as little reliance on widely distributed sources
01:02:53 of the supply chain as possible.
01:02:55 So maybe like rethinking how much we rely
01:02:58 on the infrastructure of the supply chain.
01:03:01 Yeah, I mean, you know, there’s some basic,
01:03:03 and I assume, right, that there are a lot of folks
01:03:08 in corporate boardrooms looking at risk
01:03:10 and saying that didn’t go well,
01:03:13 and maybe it could have even gone worse.
01:03:16 Maybe we need to think about reshoring, right?
01:03:20 At the very least, one of the things
01:03:22 that I’m hearing about anecdotally
01:03:24 is that they’re starting stuff up, you know,
01:03:26 when they can, right?
01:03:28 Which is, that’s probably not sustainable, right?
01:03:31 I mean, at some point, somebody in that corporate boardroom
01:03:34 is gonna say, you know, guys, inventory is getting
01:03:36 kind of heavy and the cost of that is like,
01:03:38 do we, can we really justify that much longer
01:03:40 to the shareholders, right?
01:03:41 We can back off and start, you know,
01:03:43 back, things are back to normal, let’s lean out.
01:03:45 Well, my hope is that there’s a technology solution
01:03:48 to a lot of aspects of this.
01:03:49 So one of them on the supply chain side
01:03:51 is collecting a lot more data,
01:03:53 like having much more integrated
01:03:57 and accurate representation of the inventory
01:03:59 all over the place,
01:04:00 and the available transportation mechanisms,
01:04:03 the trucks, the all kinds of freight,
01:04:06 and how in the different models
01:04:08 of the possible catastrophes that can happen,
01:04:14 like how will the system respond?
01:04:15 So having a really solid model that you’re operating under
01:04:19 as opposed to just kind of being in emergency response mode
01:04:23 under poor, incomplete information,
01:04:26 which is what seems like is more commonly the case,
01:04:30 except for things like you said, Walmart and Amazon,
01:04:34 they’re trying to internally get their stuff together
01:04:36 on that front, but that doesn’t help
01:04:38 the rest of the economy.
01:04:40 So another exciting technological development
01:04:44 as you write about, as you think about is autonomous trucks.
01:04:48 So these are often brought up in different contexts
01:04:52 as the examples of AI and robots taking our jobs.
01:04:57 How true is this?
01:04:58 Should we be concerned?
01:05:01 I think they’ve really come to epitomize
01:05:03 this anxiety over automation, right?
01:05:06 It’s such a simple idea, right?
01:05:09 Truck that drives itself,
01:05:11 classic blue collar job that pays well,
01:05:15 guy maybe with not a lot of other good options, right?
01:05:20 To sort of make that same income easily,
01:05:23 and you build a robot to take his job away, right?
01:05:28 So I think 2016 or so,
01:05:32 that was the sort of big question out there,
01:05:35 and that’s actually how I started studying it, right?
01:05:38 I just wrapped up the book,
01:05:40 just so happened that somebody was working at Uber,
01:05:43 Uber had just bought auto, saw the book and was like,
01:05:45 hey, can you come out and talk to our engineering teams
01:05:48 about what life is like for truck drivers
01:05:51 and maybe how our technology could make it better.
01:05:54 And at that time, there were a lot of different ideas
01:05:58 about how they were gonna play out, right?
01:06:00 So while the press was saying,
01:06:03 all truckers are gonna lose their jobs,
01:06:05 there were a lot of people in these engineering teams
01:06:08 who thought, okay, if we’ve got an individual owner operator
01:06:11 and they can only drive eight or 10 hours a day,
01:06:17 they hop in the back, they get their rest,
01:06:19 and the asset that they own works for them, right?
01:06:23 Sort of perfect, right?
01:06:25 And at that time, there were a bunch of reports
01:06:28 that came out and sort of basically what people did
01:06:30 was they took the category of truck driver.
01:06:33 Some people took a larger category from BLS
01:06:35 of sales and delivery workers
01:06:37 that was about three and a half million workers
01:06:40 and others took the heavy duty truck driver category,
01:06:43 which was at the time about 1.8 million or so.
01:06:46 And they picked a start date and a slope
01:06:49 and said, let’s assume that all these jobs
01:06:52 are just gonna disappear.
01:06:53 And really smart researcher, Annette Bernhardt
01:06:57 at the Labor Center at UC Berkeley
01:07:00 was sort of looking around for people
01:07:03 who were sort of deeply into industries
01:07:06 to complicate those analyses, right?
01:07:10 And reached out to me and was like,
01:07:11 what do you think of this?
01:07:12 And I said, the industry is super diverse.
01:07:15 I haven’t given a ton of thought, but it can’t be that.
01:07:17 It’s not that simple, it never is.
01:07:21 And so she was like, will you do this?
01:07:23 And I was like ready to move on to another topic.
01:07:26 I had like been in trucking for 10 years
01:07:28 and that’s how I started looking at it.
01:07:31 And it is, it’s a lot more complicated.
01:07:33 And the initial impacts, and here’s the challenge I think,
01:07:38 and it’s not just a research challenge,
01:07:40 it’s the fundamental public policy challenge
01:07:43 is we look at the existing industry
01:07:46 and the impacts, the potential impacts,
01:07:50 they’re not, you know, nothing.
01:07:53 For some communities and some kinds of drivers,
01:07:56 they’re gonna be hard.
01:07:57 And there are a significant number of them.
01:07:59 Nowhere near what people thought.
01:08:00 You know, I estimate it’s like around 300,000,
01:08:04 but that’s a static picture of the existing industry.
01:08:08 And here’s the key with this is, at least in my conclusion
01:08:13 is this is a transformative technology.
01:08:17 We are not going to swap in self driving trucks
01:08:20 for human driven trucks and all else stays the same.
01:08:24 This is gonna reshape our supply chains.
01:08:27 It’s gonna reshape landscapes.
01:08:29 It’s gonna affect our ability to fight climate change.
01:08:33 This is a really important technology in this space.
01:08:37 Do you think it’s possible to predict the future
01:08:41 of the kind of opportunities it will create,
01:08:44 how it will change the world?
01:08:46 So like when you have the internet,
01:08:50 you can start saying like all the kinds of ways
01:08:53 that office work, all jobs will be lost
01:08:55 because it’s easy to network.
01:08:57 And then software engineering allows you to automate
01:08:59 a lot of the tasks like Microsoft Excel does, you know.
01:09:04 But it opened up so many opportunities,
01:09:08 even with things that are difficult to imagine,
01:09:10 like with the internet, I don’t know, Wikipedia,
01:09:12 which is widely making accessible information.
01:09:15 And that increased the general education globally by a lot,
01:09:21 all those kinds of things.
01:09:22 And then the ripple effects of that
01:09:25 in terms of your ability to find other jobs
01:09:29 is probably immeasurable.
01:09:31 So is it just a hopeless pursuit to try to predict
01:09:37 if you talk about these six different trajectories
01:09:40 that we might take in automating trucks,
01:09:44 but like as a result of taking those trajectories,
01:09:47 is it a hopeless pursuit to predict
01:09:49 what the future will result in?
01:09:50 Yeah, it is.
01:09:52 It absolutely is.
01:09:54 Because it’s the wrong question.
01:09:56 The question is, what do we want the future to be
01:09:59 and let’s shape it, right?
01:10:01 And I think this is, and this is the only point
01:10:06 that I really wanna make in my work
01:10:08 for the foreseeable future,
01:10:10 is that we have got to get out of this mindset
01:10:16 that we’re just gonna let technology kind of go
01:10:20 and it’s a natural process and whatever pops out
01:10:22 will fix the problems on the backside.
01:10:24 And we’ve got to recognize that one,
01:10:28 that’s not what we do, right?
01:10:30 You know, and self driving vehicles
01:10:33 is just such a perfect example, right?
01:10:35 We would not be sitting here today
01:10:37 if the Defense Department, right?
01:10:38 If Congress in 2000 had not written into legislation
01:10:44 funding for the DARPA challenges,
01:10:46 which followed, actually I think the funding came
01:10:49 a couple of years later,
01:10:50 but the priority that they wrote in 2000
01:10:52 was let’s get a third of all ground vehicles
01:10:55 in our military forces unmanned, right?
01:10:58 And this was before aerial unmanned vehicles
01:11:01 had really sort of proven their worth.
01:11:02 They would come to be incredibly,
01:11:04 like, you know, just blow people’s minds
01:11:07 in terms of their additional capabilities,
01:11:09 the lower costs, you know,
01:11:10 keeping soldiers out of harm’s way.
01:11:13 Now, of course they raised other problems
01:11:15 and considerations that I think we’re still wrestling with,
01:11:17 but that was even before that they had this priority.
01:11:21 We would not be sitting here today
01:11:22 if Congress in 2000 had not said, let’s bring this about.
01:11:27 So they already had that vision, actually.
01:11:29 I didn’t know about that.
01:11:30 So for people who don’t know the DARPA challenges
01:11:32 is the events that were just kind of like
01:11:36 these seemingly small scale challenges
01:11:39 that brought together some of the smartest roboticists
01:11:41 in the world, and that somehow created enough of a magic
01:11:45 where ideas flourished,
01:11:49 both engineering and scientific,
01:11:51 that eventually then was the catalyst
01:11:54 for creating all these different companies
01:11:56 that took on the challenge.
01:11:57 Some failed, some succeeded,
01:11:58 some are still fighting the good fight.
01:12:01 And that somehow just that little bit of challenge
01:12:03 was the essential spark of progress
01:12:07 that now resulted in this beautiful up and down wave
01:12:10 of hype and profit and all this kind of weird dance
01:12:15 where the B word, billions of dollars
01:12:18 have been thrown around and we still don’t know.
01:12:21 And the T word, trillions of dollars
01:12:23 in terms of transformative effects of autonomous vehicles.
01:12:25 And all that started from DARPA
01:12:27 and that initial vision of, I guess, as you’re saying,
01:12:31 of automating part of the military supply chain.
01:12:35 I did not know that.
01:12:36 That’s interesting.
01:12:37 So they had the same kind of vision for the military
01:12:39 as we’re not talking about a vision for the civilian,
01:12:43 whether it’s trucking or whether it’s autonomous vehicle,
01:12:45 sort of a ride sharing kind of application.
01:12:48 Yeah, I mean, what an incredible spark, right?
01:12:53 And just the story of what it produced, right?
01:12:57 I mean, your own work on self driving, right?
01:13:01 I mean, you’ve studied it as an academic, right?
01:13:04 How many great researchers and minds have been harnessed
01:13:08 by this outcome of that spark, right?
01:13:11 And I think this is sort of theoretically about technology,
01:13:14 right, this is what makes it sort of so great
01:13:15 is that this is what makes us human, in my opinion, right?
01:13:18 Is that you conceive of something in your mind
01:13:21 and then you bring it into reality, right?
01:13:23 I mean, that’s what is so great about it.
01:13:27 Sometimes you’re too dumb to realize how difficult it is
01:13:29 so you take it.
01:13:30 Right.
01:13:31 And then eventually you’re in too deep.
01:13:36 You might as well solve the problem.
01:13:38 Well, and maybe we’re in that situation right now
01:13:41 with self driving.
01:13:42 But, you know, and so let me throw this out there.
01:13:44 I’d be curious to hear your thoughts on it.
01:13:46 But truck drivers always ask me, like, is this for real?
01:13:50 Like, is this really, like, it’s harder than they think,
01:13:52 like, right, and they can’t really do this.
01:13:55 And, you know, at first I was like, look, you know,
01:13:59 this is like the defense department
01:14:01 and like basically the top computer science
01:14:04 and robotics departments in the world.
01:14:07 And now Silicon Valley with billions of dollars in funding
01:14:14 and just, you know, some of the smartest, hardest working,
01:14:17 most visionary people focused on what is clearly,
01:14:21 you know, a gigantic market, right?
01:14:24 And what I tell them is like,
01:14:26 if self driving vehicles don’t happen,
01:14:31 I think this will be the biggest technology failure story
01:14:34 in human history.
01:14:35 I don’t know of anything else that is just galvanized.
01:14:39 I mean, you’ve had people in garages or weird inventors
01:14:42 work on things their whole lives and come really close
01:14:44 and it never happens and it’s a great failure story, right?
01:14:48 But never have we had like whole,
01:14:50 I mean, we’re talking about GM, right?
01:14:53 And these are not, you know, these are not tech companies,
01:14:55 right, these are industrial giants, right?
01:14:58 What were in the 20th century,
01:15:00 the pinnacle of industrial production in the world
01:15:03 in human history, right?
01:15:05 And they’re focused on it now.
01:15:07 So if we don’t pull this off, it’s like, wow.
01:15:11 It’s fascinating to think about.
01:15:12 I’ve never thought of it that way.
01:15:14 There was a mass hysteria on a level
01:15:18 in terms of excitement and hype
01:15:20 on a level that’s probably unparalleled in technology space.
01:15:23 Like I’ve seen that kind of hysteria just studying history
01:15:26 when you talk about military conflict.
01:15:28 So we often wage war with a dream of making a better world
01:15:32 and then realize it costs trillions of dollars
01:15:34 and then we step back and like, and go, wait a minute,
01:15:37 what do we actually get for this?
01:15:40 But in the space of technology,
01:15:41 it seems like all these kinds of large efforts
01:15:44 have paid off.
01:15:45 This, you’re right.
01:15:47 It seems like, it seems like even GM and Ford
01:15:51 and all these companies now are a little bit like,
01:15:54 hey, or Toyota and even Tesla,
01:15:58 like, are we sure about this?
01:16:01 Yeah.
01:16:02 And it’s fascinating to think about
01:16:04 when you tell the story of this,
01:16:06 this could be one of the big first, perhaps,
01:16:10 but by far the biggest failures of the dream
01:16:14 in the space of technology.
01:16:16 That’s really interesting to think about.
01:16:17 I was a skeptic for a long time
01:16:20 because of the human factor.
01:16:22 Because for business to work in the space,
01:16:25 you have to work with humans
01:16:26 and you have to work with humans at every level.
01:16:29 So in the truck driving space,
01:16:30 you have to work with the truck driver,
01:16:32 but you also have to work with the society
01:16:34 that has a certain conception of what driving means.
01:16:37 And also you have to have work with businesses
01:16:38 that are not used to this extreme level of technology,
01:16:44 you know, in the basic operation of their business.
01:16:48 So I thought it would be really difficult
01:16:50 to move to autonomous vehicles in that way.
01:16:53 But then I realized that there’s certain companies
01:16:56 that are just willing to take big risks
01:16:58 and really innovate.
01:17:00 I think the first impressive company to me was Waymo
01:17:04 or what was used to be the Google self driving car.
01:17:07 And I saw, okay, here’s a company
01:17:11 that’s willing to really think longterm
01:17:13 and really try to solve this problem, hire great engineers.
01:17:18 Then I saw Tesla with Mobileye when they first had.
01:17:22 I thought, actually Mobileye is the thing that impressed me.
01:17:25 When I sat down, I thought,
01:17:27 because I’m a computer vision person,
01:17:28 I thought there’s no way a system could keep me in lane
01:17:33 long enough for it to be a pleasant experience for me.
01:17:36 So from a computer vision perspective,
01:17:38 I thought there’d be too many failures.
01:17:39 It’d be really annoying.
01:17:40 It’d be a gimmick, a toy.
01:17:42 It wouldn’t actually create a pleasant experience.
01:17:44 And when I first was gotten Tesla with Mobileye,
01:17:47 the initial Mobileye system,
01:17:49 it actually held to lane for quite a long time
01:17:52 to where I could relax a little bit.
01:17:54 And it was a really pleasant experience.
01:17:56 I couldn’t exactly explain why it’s pleasant
01:17:58 because it’s not like I still have to really pay attention,
01:18:01 but I can relax my shoulders a little bit.
01:18:05 I can look around a little bit more.
01:18:07 And for some reason that was really reducing the stress.
01:18:10 And then over time, Tesla with a lot of the revolutionary
01:18:15 stuff they’re doing on the machine learning space
01:18:17 made me believe that there’s opportunities here to innovate,
01:18:22 to come up with totally new ideas.
01:18:23 Another very sad story that I was really excited about
01:18:27 is Cadillac SuperCruise system.
01:18:29 It is a sad story because I think I vaguely read in the news
01:18:32 they just said they’re discontinuing SuperCruise,
01:18:36 but it’s a nice innovative way
01:18:39 of doing driver attention monitoring
01:18:41 and also doing lane keeping.
01:18:43 And it just innovation could solve this
01:18:45 in ways we don’t predict.
01:18:47 And same with in the trucking space,
01:18:49 it might not be as simple as like journalists envision
01:18:52 a few years ago, where everything’s just automated.
01:18:55 It might be gradually helping out the truck driver
01:19:00 in some ways that make their life more efficient,
01:19:03 more effective, more pleasant,
01:19:07 remove some of the inefficiencies
01:19:09 that we’ve been talking about in totally innovative ways.
01:19:12 And that I still have that dream
01:19:14 that I believe to solve the fully autonomous driving problem
01:19:18 we’re still many years away,
01:19:20 but on the way to solving that problem,
01:19:22 it feels like there could be,
01:19:25 if there’s bold risk takers and innovators in this space,
01:19:29 there’s an opportunity to come up
01:19:30 with like subtle technologies that make all the difference.
01:19:36 That’s actually just what I realized
01:19:38 is sometimes little design decisions
01:19:41 make all the difference.
01:19:42 It’s the Blackberry versus the iPhone.
01:19:45 Why is it that you have a glass and you’re using your finger
01:19:50 for all of the work versus the buttons
01:19:52 makes all the difference.
01:19:54 This idea that now that you have a giant screen
01:19:57 so that every part of the experience
01:20:00 is now a digital experience.
01:20:01 So you can have things like apps that change everything.
01:20:05 You can’t, when you first thinking about
01:20:07 do I want a keyboard or not on a smartphone,
01:20:10 you think it’s just the keyboard decision.
01:20:13 But then you later realize by removing the keyboard,
01:20:17 you’re enabling a whole ecosystem of technologies
01:20:21 that are inside the phone.
01:20:23 And now you’re making the smartphone into a computer.
01:20:25 And that same way,
01:20:27 who knows how you can transform trucks, right?
01:20:30 By like automating some parts of it,
01:20:32 maybe adding some displays,
01:20:36 maybe allows you to,
01:20:37 maybe giving the truck driver some control
01:20:40 in the supply chain to make decisions
01:20:43 all those kinds of things.
01:20:44 Yeah.
01:20:45 So, I don’t know.
01:20:46 So where are you on the spectrum of hope
01:20:51 for the role of automation in trucking?
01:20:56 I think automation is inevitable.
01:20:59 And again, I think this is really going to be transformative
01:21:04 and it’s gonna be,
01:21:06 I’ve studied the history of trucking technology
01:21:09 as much as I can.
01:21:11 There’s not a lot of great stuff written
01:21:12 and you kind of have to,
01:21:14 there isn’t a lot of data and places to know
01:21:16 sort of volumes of stuff and how they’re changing, et cetera.
01:21:19 But the big revolutionary changes in trucking
01:21:24 are because of constellations of factors.
01:21:27 It’s not just one thing, right?
01:21:29 So Daimler builds a motorized truck
01:21:32 and I think it’s 1896, right?
01:21:35 Intercity trucking.
01:21:37 So basically what they use that truck for
01:21:39 is just to swap out horses, right?
01:21:41 They basically do the same thing.
01:21:42 The service doesn’t really change, you know?
01:21:45 And then World War I really spurs the development
01:21:48 of sort of bigger, larger trucks,
01:21:50 like spreads air filled tires.
01:21:54 And then we start paving roads, right?
01:21:57 And paved roads, right?
01:22:00 Air filled tires and the internal combustion engine.
01:22:04 Now you got a winning mix.
01:22:05 Now it met with demand for people who wanted to get out
01:22:09 from under the thumb of the railroads, right?
01:22:12 So there was all of this pent up demand
01:22:14 to get cheaper freight from the countryside
01:22:18 into cities and between cities
01:22:20 that typically had to go by rail.
01:22:22 And so now, you know, 40 years
01:22:25 after that internal combustion engine,
01:22:28 it becomes this absolutely essential, right?
01:22:30 This necessary but not sufficient piece of technology
01:22:34 to create the modern trucking industry in the 1930s.
01:22:38 And I think self driving is gonna be,
01:22:41 self driving trucks are gonna be part of that.
01:22:43 And the idea, I guess we credit Jeff Bezos.
01:22:47 The idea is, you know, okay, so Sam Walton,
01:22:52 if we can do it like a slight tangent
01:22:54 on sort of the importance of trucking to business strategy
01:22:57 and sort of how it has transformed our world.
01:23:00 The central insight that Sam Walton had
01:23:03 that made him the giant that he was
01:23:06 in influencing the way that so many people get stuff
01:23:10 was a trucking insight.
01:23:12 And so if you look at the way that he developed his system,
01:23:17 you build a distribution center
01:23:19 and then you ring it with stores.
01:23:22 Those stores are never further out
01:23:24 from that distribution center
01:23:26 than a human driven truck
01:23:28 can drive back and forth in one day.
01:23:31 And so rather than the way all of his competitors
01:23:34 were doing it with sending trucks all over the place
01:23:37 and having people sleep overnight
01:23:39 and sort of making the trucking service fit
01:23:43 where they had stores,
01:23:45 he designed the layout of the stores
01:23:49 to fit what trucks could do.
01:23:51 And so transportation and logistics
01:23:53 become Walmart’s edge
01:23:57 and allows them to dominate the space.
01:23:59 That’s the challenge that Amazon has now.
01:24:02 They’ve mastered the digital part of it.
01:24:05 And now they got to figure out
01:24:07 how do we dominate the actual physical movement
01:24:11 that complements that.
01:24:14 Others are obviously gonna follow.
01:24:16 But the capabilities of these trucks
01:24:18 is completely different
01:24:20 than the capability of a human driven truck.
01:24:22 So if you’re Smith packing
01:24:25 and you’ve got a bunch of meat in a warehouse
01:24:30 and it’s going to grocery distribution centers,
01:24:33 you have that trucker probably come in the night before
01:24:37 and you make him wait
01:24:38 so that he has a full 10 hour break,
01:24:41 which is what the law requires
01:24:42 so that he can get to the furthest reaches
01:24:45 that he can of one of those stores.
01:24:48 So he can drive his full 11 hours
01:24:50 and bring that meat
01:24:51 so it doesn’t have to sit overnight
01:24:53 in that refrigerated trailer.
01:24:55 And so their system is based on that.
01:24:57 Now, what happens when that truck
01:25:00 can now travel two times as far, right?
01:25:04 Three times as far.
01:25:05 Now you don’t need the warehouses where they were.
01:25:08 Now you can go super lean with your inventory.
01:25:11 Instead of having meat here, meat there, meat there,
01:25:14 you can put it all right here.
01:25:16 And if it’s cheap enough,
01:25:18 substitute those transportation costs
01:25:20 for all that warehousing costs, right?
01:25:22 So this is gonna remake landscapes
01:25:24 in the same way that big box supply chains did, right?
01:25:29 And then of course, the further compliment of that is,
01:25:32 how do you then get it to two people at their door, right?
01:25:37 And the big box supply chain,
01:25:39 it moves very few items in really large quantities
01:25:44 to very few locations pretty slowly, right?
01:25:49 Ecommerce aspires to do something completely different,
01:25:53 move huge varieties of things in small quantities,
01:25:57 virtually everywhere as fast as possible, right?
01:26:01 And so that is like that intercity trucking
01:26:05 under the, in the era of railroad monopolies, right?
01:26:10 The demand for that is potentially enormous, right?
01:26:14 And so there’s such a,
01:26:16 so right now I think a lot of the business plans
01:26:20 for sort of automated trucks, right?
01:26:22 And sort of the way that the journalistic accounts portray it
01:26:24 is like, okay, if we swap out a human for a computer,
01:26:28 what are the labor costs per mile?
01:26:30 And like, oh, here’s the profitability
01:26:31 of self driving trucks, uh uh.
01:26:34 Like this is transformative technology.
01:26:36 We’re gonna change the way we get stuff.
01:26:39 So we could actually get a lot more trucks period
01:26:41 with like with autonomous trucks
01:26:43 because they would enable a very different kind
01:26:45 of transportation networks you think.
01:26:47 Yeah, here’s, and this is where it’s like, uh oh.
01:26:50 Like, yeah, so we really thought
01:26:54 we were gonna be electrifying trucks.
01:26:57 If they’re going twice as far,
01:26:59 if they’re moving three times as much,
01:27:01 if they’re going three times as far, right?
01:27:03 What does that mean for how far we are
01:27:05 behind on batteries, right?
01:27:06 We’ve got sort of these, you know, ideas about like, man,
01:27:09 we, you know, here’s how far,
01:27:10 how close we could get to meet this demand.
01:27:12 That demand is gonna radically change, right?
01:27:15 These trucks are, you know, so then we’ve got to think
01:27:17 about, all right, if it’s not batteries, you know,
01:27:20 how are we powering these things?
01:27:22 And how many of them are they’re gonna be?
01:27:25 Like right now we’ve got 5 million containers
01:27:28 that move from LA and Long Beach to Chicago on rail.
01:27:34 Rail is three or four times at least more efficient
01:27:38 than trucks in terms of greenhouse gas emissions.
01:27:42 And on that lane, it varies a lot depending on demand,
01:27:45 but maybe rail has a 20% advantage in cost, maybe 25%,
01:27:50 but it’s a couple of days slower.
01:27:52 So now you cut the cost of that truck,
01:27:54 transportation per mile by 30%.
01:27:57 Now it’s cheaper than rail and it gets the stuff there
01:28:00 five days faster than rail.
01:28:02 How many millions of containers are gonna leave LA
01:28:05 and Long Beach on self driving trucks and go to Chicago?
01:28:08 And it might look very much like a train
01:28:10 if we go with the platooning solution,
01:28:14 where you have these rows of like,
01:28:18 imagine like rows of like 10, like dozens of trucks
01:28:21 or like hundreds of trucks, like some absurd situation.
01:28:25 Just going from LA to Chicago, just this train,
01:28:29 but taking up a highway.
01:28:31 I mean, this is probably a good place
01:28:34 to talk about various scenarios.
01:28:37 Well, before we get there,
01:28:39 can I just make one interesting observation
01:28:41 that I made as a driver?
01:28:44 When you’re in a truck, you’re up higher.
01:28:46 So you can see further and you can see the traffic patterns
01:28:50 and cars move in packs.
01:28:54 I’m sure there’s academic research on this, right?
01:28:56 But they move in packs.
01:28:57 They kind of bunch up behind a slower car
01:28:59 and then a bunch of them break free.
01:29:01 And this is sort of on almost free flowing highways.
01:29:03 They kind of move in packs
01:29:05 and you can kind of see them in the truck.
01:29:07 So, rather than platoons,
01:29:09 we might have like hives of trucks, right?
01:29:11 So you have like 20 trucks moving
01:29:13 in some coordinated fashion, right?
01:29:15 And then maybe the self driving cars are,
01:29:18 cause people don’t like to be around them
01:29:19 or whatever it is, right?
01:29:21 You might have a pod of 20 self driving cars
01:29:24 sort of moving in a packet behind them.
01:29:26 This is what, if the aliens came down
01:29:28 or we’re just observing cars,
01:29:30 which is one of the sort of prevalent characteristics
01:29:34 of human civilization is there seems to be these cars
01:29:37 like moving around that would do this kind of analysis
01:29:40 of like, huh, what’s the interesting clustering
01:29:42 of situations here,
01:29:46 especially with autonomous vehicles, I like this.
01:29:48 Okay, so what technologically speaking
01:29:52 do you see are the different scenarios
01:29:55 of increasing automation in trucks?
01:29:58 What are some ideas that you think about?
01:30:00 For the most part, I have no influence
01:30:04 on sort of what these ideas were.
01:30:06 So what the project was that I did was I said,
01:30:11 technology is created by people, they solve for X
01:30:14 and they have some conception of what they wanna do.
01:30:17 And that’s where we should start in sort of thinking
01:30:19 about what the impacts might be.
01:30:22 So I went and I talked to everybody I could find
01:30:25 who was thinking about developing a self driving truck.
01:30:28 And the question was essentially,
01:30:31 what are you trying to build?
01:30:32 Like, what do you envision this thing doing?
01:30:35 It turned out that that for a lot of them
01:30:39 was an afterthought.
01:30:40 They knew the sort of technological capabilities
01:30:43 that a self driving vehicle would have.
01:30:45 And those were the problems that they were tackling.
01:30:48 They were engineers and computer scientists and…
01:30:50 Oh, robotics people, I love you so much.
01:30:53 This is, I could talk forever about this,
01:30:56 but yes, there’s a technology problem,
01:30:58 let’s focus on that and we’ll figure out
01:30:59 the actual impact on society,
01:31:02 how it’s actually going to be applied,
01:31:03 how it’s actually going to be integrated
01:31:05 from a policy and from a human perspective,
01:31:08 from a business perspective later.
01:31:09 First, let’s solve the technology problem.
01:31:11 That’s not how life works, friends, but okay, I’m sorry.
01:31:14 Yeah, yeah, so I mean,
01:31:16 I’m sure you know the division of labor
01:31:18 in these companies, right?
01:31:18 There’s sort of a business development side,
01:31:21 you know, and then there’s the engineering side, right?
01:31:22 And the engineers are like, oh my God,
01:31:24 what are these business development people, you know,
01:31:26 why are they involved in this process?
01:31:30 So I ended up sort of coming up with a few different ideas
01:31:34 that people seem to be batting around
01:31:36 and then really tried to zero in
01:31:39 on a layman’s understanding of the limitations, right?
01:31:42 And it turns out that’s really obvious and quite simple.
01:31:47 Highway driving’s a lot simpler, right?
01:31:49 So, you know, the plan is simplify the problem, right?
01:31:53 And focus on highways because city driving
01:31:56 is so much more complicated.
01:31:59 So from that, I came up with basically six scenarios,
01:32:04 actually I came up with five
01:32:06 that the developers were talking about.
01:32:08 And then one that I thought was a good idea
01:32:11 that I had read about, I think in like 2013 or 2014,
01:32:16 which was actually something
01:32:18 that the US military was looking at.
01:32:20 I actually first heard about the idea
01:32:23 of this kind of automation, at least in sketched out form
01:32:27 in like 2011, I guess it was with Peloton,
01:32:30 which was this sort of early technology entrant
01:32:33 into the trucking industry,
01:32:35 which was working on platooning trucks.
01:32:39 And all they were doing was, you know,
01:32:41 a cooperative adaptive cruise control
01:32:43 as they came to call it.
01:32:45 And we ended up on a panel together.
01:32:48 And it’s kind of interesting because I was on that panel
01:32:52 because I was thinking about how we got the best return
01:32:55 on investment for fuel efficient technologies.
01:32:58 And if it’s cool, I’ll sort of set this up
01:33:01 because it does, it comes into sort of the story
01:33:03 of some of these scenarios.
01:33:05 So when I studied the drivers,
01:33:09 you had this like complete difference in the driving tasks,
01:33:15 like we were talking about before
01:33:16 with long haul and city, right?
01:33:18 And you’re not paid in the city,
01:33:21 you’ve got congestion, the turns are tight.
01:33:25 There’s lots of, you know, pedestrians, you know,
01:33:27 all the things that self driving trucks don’t like,
01:33:29 truckers don’t like, right?
01:33:31 And they’re not paid, there’s lots of waiting time.
01:33:35 And then in the highway, they get to cruise,
01:33:37 they’re getting paid, they have control,
01:33:39 they go at their own pace,
01:33:41 they’re making money, they’re happy.
01:33:43 Well, it turned out, I guess it was around 2010,
01:33:45 this is still when we were thinking
01:33:47 about regenerative braking, you know,
01:33:48 and hybrid trucks being sort of like the solution.
01:33:53 The problems with them sort of,
01:33:56 and the advantages, you know,
01:33:57 also split on what I was thinking of
01:33:59 as kind of the rural urban divide at that time, right?
01:34:01 So, like you got the regenerative braking, right?
01:34:05 You can make the truck lighter,
01:34:06 you can keep it local, right?
01:34:08 You don’t get any benefit from that, you know,
01:34:10 hybrid electric on the rural highway,
01:34:15 you want aerodynamics, right?
01:34:17 There, you want low rolling resistance tires
01:34:20 and these super aerodynamic sleek trucks, right?
01:34:23 Where we know with off the shelf technology today,
01:34:26 we could double the fuel economy,
01:34:27 more than double the fuel economy of the typical truck
01:34:30 in that highway segment,
01:34:32 if we segmented the duty cycle, right?
01:34:34 And so in the urban environment,
01:34:36 you want a clean burning truck,
01:34:37 so you’re not giving kids asthma,
01:34:39 you want it lighter,
01:34:40 so it’s not destroying those less strong pavements, right?
01:34:45 You’re not, you can make tighter turns,
01:34:47 you don’t need a sleeper cab,
01:34:48 because the driver, you know,
01:34:49 hopefully is getting home at night, right?
01:34:51 In the long haul, you want that super aerodynamic stuff.
01:34:54 Now that doesn’t get you anything in the city,
01:34:55 and in fact, it causes all kinds of problems,
01:34:57 because you turn too tight,
01:34:58 you crunch up all the aerodynamics
01:35:00 that connect the tractor and the trailer.
01:35:02 So the idea that I had was like, okay,
01:35:05 what if we deliberately segmented it?
01:35:08 Like, what if we created these droplets outside cities,
01:35:12 where, you know, a local city driver who’s paid by the hour
01:35:16 kind of runs these trailers out once they’re loaded,
01:35:18 you know, doesn’t sit there and wait while it’s being loaded,
01:35:20 they drop off a trailer, they go pick up one that’s loaded,
01:35:23 they run it out, when it’s loaded, they call them,
01:35:25 and they just run them out there and stage them.
01:35:27 It’s like an Uber driver, but for truckloads.
01:35:30 Yeah, and we have like intermodal.
01:35:32 We have like, basically this would be the equivalent
01:35:34 of like rail to truck intermodal, right?
01:35:37 So you put it on the rail, and then, you know,
01:35:38 a trucker picks it up and delivers it, right?
01:35:40 So instead of having the rail,
01:35:42 you’d have these super aerodynamic, hopefully platoons,
01:35:44 or what at the time was called long combination vehicles,
01:35:48 which is basically two trailers connected together, right?
01:35:51 Because this is like a huge productivity gain, right?
01:35:54 And then instead of that driver like me,
01:35:56 I would pick up something in upstate New York,
01:35:57 drive to Michigan, drive to Alabama, you know,
01:35:59 drive to Wisconsin, drive to Florida, you know,
01:36:01 I’d get home every two weeks.
01:36:03 If I’m just running that, you know, that double trailer,
01:36:08 I might be able to go back and forth
01:36:09 from Chicago to Detroit, right?
01:36:11 Take two trailers there, pick up two trailers going back,
01:36:14 right, and be home every night.
01:36:16 Now, the problem with that at the time,
01:36:17 or one of them was, you know, bridge weights.
01:36:20 So you can’t, not all bridges can handle
01:36:23 that much weight on them.
01:36:25 They can’t handle these doubles, right?
01:36:26 And some places can, some places can’t.
01:36:28 And so this platooning idea was happening at the same time,
01:36:31 and we ended up on the same panel,
01:36:33 and the founders were like,
01:36:35 hey, so what’s it like to follow
01:36:37 really close behind another truck?
01:36:39 Which was kind of the stage that they were at was like,
01:36:41 you know, what’s that experience gonna be like?
01:36:43 And I was like, truckers aren’t gonna like it, you know?
01:36:46 I mean, that’s just like the cardinal rule
01:36:48 is following distance.
01:36:49 Like that’s the one you really shouldn’t violate, right?
01:36:52 And when you’re out on the road,
01:36:54 like you have that trucker like right on your ass,
01:36:56 you know, people remember that.
01:36:58 They don’t remember the 99.9% of truckers
01:37:01 that are not on their ass, you know?
01:37:03 Like they’re very careful about that.
01:37:05 But when the trucks are really close together,
01:37:07 there’s benefits in terms of aerodynamics.
01:37:10 So that’s the idea.
01:37:11 So like if you want to get some benefits of a platoon,
01:37:16 you want them to be close together,
01:37:17 but you’re saying that’s very uncomfortable for truckers.
01:37:20 Yeah, so I mean, I think that ended up at the,
01:37:22 I mean, Peloton I think is sort of winding down
01:37:25 their work on this.
01:37:27 And I think that ended up being still an open question.
01:37:31 Like, and I had a chance to interview a couple drivers
01:37:33 who at least one, maybe two of which
01:37:36 had actually driven in their platoons.
01:37:38 And I got completely different experiences.
01:37:41 Some of them were like, it’s really cool.
01:37:43 You know, I’m like in communication with that other driver.
01:37:46 You know, I can see on a screen what’s out,
01:37:49 you know, the front of his truck.
01:37:51 And then some were like, it’s too close.
01:37:53 And it might be one of those things that’s just,
01:37:55 you know, it takes an adjustment to sort of get there.
01:37:57 So you get the aerodynamic advantage,
01:37:59 which, you know, saves fuel.
01:38:01 There’s some problems though, right?
01:38:03 So, you know, you’re getting that aerodynamic advantage
01:38:07 because there’s a low pressure system
01:38:08 in front of that following truck.
01:38:10 But the engine is designed with higher pressure
01:38:14 feeding that engine, right?
01:38:15 So there are sort of adjustments that you need to make
01:38:18 and, you know, still the benefits are there.
01:38:21 That’s one scenario.
01:38:22 And that’s just the automation
01:38:24 of that acceleration and braking.
01:38:26 Starsky, which, you know,
01:38:29 probably a lot of your listeners heard about,
01:38:33 was working on another scenario,
01:38:34 which was, you know, to solve that local problem
01:38:38 was gonna do teleoperation, right?
01:38:40 Sort of remote piloting.
01:38:42 I had the chance to, you know,
01:38:44 sort of watch them do that.
01:38:46 You know, they drove a truck in Florida
01:38:49 from San Francisco in one of their offices.
01:38:53 That was really interesting.
01:38:54 And then…
01:38:55 In case it’s not clear,
01:38:56 teleoperation means you’re controlling the truck remotely,
01:38:59 like it’s a video game.
01:39:01 So you’ve gotten the chance to witness it.
01:39:05 Does it actually work?
01:39:06 Yeah, I mean, so it’s a…
01:39:08 What are the pros and cons?
01:39:10 You know, one of the problems with doing research like this
01:39:12 with all these Silicon Valley folks is the NDAs.
01:39:16 Oh, right.
01:39:17 So, you know, I don’t know what I’m able to say
01:39:20 about sort of watching it,
01:39:21 but obviously they’re public statements
01:39:24 about sort of what the challenges are, right?
01:39:25 And it’s about the latency
01:39:27 and the ability to sort of in real time.
01:39:31 There’s challenges there.
01:39:32 Let me say one thing.
01:39:33 So I’m talking to the…
01:39:36 You know, I’ve talked to the Waymo CTO.
01:39:38 I’m in conversations with them.
01:39:39 I’m talking to the head of trucking, Boris Softman,
01:39:43 in next month, actually.
01:39:45 I’m a huge fan of his because he was,
01:39:48 I think the founder of Anki,
01:39:49 which is a toy robotics company.
01:39:52 So I love human robot interaction.
01:39:55 And he created one of the most effective
01:39:58 and beautiful toy robots.
01:40:03 Anyway, I keep complaining to them on email privately
01:40:07 that there’s way too much marketing in these conversations
01:40:11 and not enough showing off both the challenge
01:40:14 and the beauty of the engineering efforts.
01:40:16 And that seems to be the case
01:40:18 for a lot of these Silicon Valley tech companies.
01:40:21 They put up this, you’re talking about NDAs.
01:40:26 For some reason, rightfully or wrongfully,
01:40:29 because there’s been so much hype
01:40:31 and so much money being made,
01:40:33 they don’t see the upside in being transparent
01:40:39 and educating the public about how difficult the problem is.
01:40:43 It’s much more effective for them to say,
01:40:45 we have everything solved.
01:40:46 This will change everything.
01:40:47 This will change society as we know it.
01:40:49 And just kind of wave their hands
01:40:51 as opposed to exploring together
01:40:53 like these different scenarios.
01:40:54 What are the pros and cons?
01:40:55 Why is it really difficult?
01:40:57 You know, what are the gray areas
01:41:00 of where it works and doesn’t?
01:41:01 What’s the role of the human in this picture
01:41:03 of the both sort of the operators
01:41:06 and the other humans on the road?
01:41:08 All of that, which are fascinating human problems,
01:41:11 fascinating engineering problems
01:41:12 that I wish we could have a conversation about
01:41:15 as opposed to always feeling like it’s just marketing talk.
01:41:19 Because a lot of what we’re talking about now,
01:41:22 even you with having private conversations under NDA,
01:41:26 you still don’t have the full picture of everything,
01:41:29 of how difficult this problem is.
01:41:31 One of the big questions I’ve had,
01:41:34 still have is how difficult is driving?
01:41:37 I disagree with Elon Musk and Jim Keller on this point.
01:41:41 I have a sense that driving is really difficult.
01:41:45 You know, the task of driving, just broadly.
01:41:47 This is like philosophy talk.
01:41:49 How much intelligence is required to drive a car?
01:41:55 So from like a Jim Keller,
01:41:58 who used to be the head of autopilot,
01:42:00 the idea is that it’s just a collision avoidance problem.
01:42:03 It’s like billiard balls.
01:42:05 It’s like you have to convert the drive.
01:42:06 You have to do some basic perception,
01:42:08 a computer vision to convert driving into a game of pool.
01:42:13 And then you just have to get everything into a pocket.
01:42:15 To me, there just seems to be some game theoretic dance
01:42:19 combined with the fact that people’s life is at stake.
01:42:21 And then when people die at the hands of a robot,
01:42:24 the reaction is going to be much more complicated.
01:42:26 So all of that, but that’s still an open question.
01:42:28 And the cool thing is all of these companies
01:42:31 are struggling with this question
01:42:34 of how difficult is it to solve this problem sufficiently
01:42:38 such that we can build a business on top of it
01:42:39 and have a product that’s going to make
01:42:41 a huge amount of money
01:42:42 and compete with the manually driven vehicles.
01:42:46 And so their teleoperation from Starsky’s
01:42:49 is really interesting idea.
01:42:50 How much can, I mean,
01:42:53 there’s a few autonomous vehicle companies
01:42:55 that tried to integrate teleoperation in the picture.
01:42:59 Can we reduce some of the costs
01:43:02 while still having reliability,
01:43:04 like catch when the vehicle fails
01:43:10 by having teleoperation?
01:43:11 It’s an open question.
01:43:13 So that’s for you scenario number two
01:43:17 is to use teleoperation as part of the picture.
01:43:20 Yeah, let me follow up on that question
01:43:22 of how hard driving is,
01:43:23 because this becomes a big question for researchers
01:43:26 who are thinking about labor market impacts,
01:43:28 because we start from a perspective
01:43:31 of what’s hard or easy for humans.
01:43:34 And so if you were to look at truck driving prior to a lot,
01:43:39 I mean, there’s been a lot of thinking and debate
01:43:41 in academic research circles
01:43:45 around sort of how you estimate labor impacts,
01:43:47 what these models look like.
01:43:49 And a lot of it is about how automatable is a job,
01:43:52 object recognition, really easy for people, right?
01:43:54 Really hard for computers.
01:43:56 And so there’s a whole bunch of things
01:43:58 that truck drivers do that we see as super easy
01:44:03 and as it would have been characterized 10 years ago,
01:44:07 routine, and it’s not for a computer, right?
01:44:10 It turns out to be something that we do naturally
01:44:13 that is sort of cutting edge, right?
01:44:16 Computer science.
01:44:17 So on the teleoperation question,
01:44:20 I think this is a more interesting one
01:44:23 than people would like to sort of let on, I think, publicly.
01:44:29 There are gonna be problems, right?
01:44:32 And this is one of the complexities
01:44:33 of sort of putting these things out in the world.
01:44:35 And if you see the real world of trucking,
01:44:37 you realize, wow, it’s rough.
01:44:40 There are dirt lots, there’s gravel,
01:44:42 there’s salt and ice and cold weather,
01:44:44 and there’s equipment that just gets left out
01:44:46 in the middle of nowhere,
01:44:47 and the brakes don’t get maintained,
01:44:49 and somebody was supposed to service something
01:44:51 and they didn’t, you know?
01:44:53 And so you imagine, okay, we’ve got this vehicle
01:44:56 that can drive itself,
01:44:57 which is gonna require a whole lot of sensors
01:44:59 to tell it that the doors are still closed
01:45:02 and the trailer’s still hooked up
01:45:03 and each of the tires has adequate pressure,
01:45:05 and any number of, probably hundreds of sensors
01:45:09 that are gonna be sort of relaying information.
01:45:11 And one of them, after 500,000 miles or whatever,
01:45:15 it goes out.
01:45:17 Now, do we have some fleet of technicians
01:45:20 sort of continually cruising the highways
01:45:22 and sort of servicing these things as they do what?
01:45:25 Pull themselves off to the side of the road
01:45:27 and say, I’ve got a sensor fault, I’m pulling over,
01:45:30 or maybe there’s some level of safety critical faults
01:45:32 or whatever it might be.
01:45:36 So that suggests that there might be a role
01:45:40 for teleoperation even with self driving.
01:45:43 And when I push people on it in the conversations,
01:45:47 they all are like, yeah, we kind of have that
01:45:50 on the bottom of the list,
01:45:52 figure out how to rescue truck, you know?
01:45:54 I guess on the to do list, right?
01:45:56 After solving the self driving question is like,
01:46:00 yeah, what do we do with the problems, right?
01:46:02 I mean, no, we could imagine like, all right,
01:46:04 we have some protocol that the truck is not,
01:46:08 realizes the system says not safe for operation,
01:46:11 pull to the side.
01:46:13 Good, you have a crash, but now you got a truck stranded
01:46:15 on the side of the road.
01:46:17 You’re gonna send out somebody to like calibrate things
01:46:19 and check out what’s going on,
01:46:21 or that sounds like expensive labor,
01:46:23 it sounds like downtime, it sounds like the kind of things
01:46:26 that shippers don’t like to happen to their freight,
01:46:28 you know, in a just in time world.
01:46:30 And so wouldn’t it be great if you could just sort of,
01:46:33 you know, loop your way into the controls of that truck
01:46:36 and say, all right, we’ve got a sensor out,
01:46:38 says that the tire is bad,
01:46:40 but I can see visually from the camera, looks fine,
01:46:43 I’m gonna drive it to our next depot,
01:46:45 you know, maybe the next rider or Penske location, right?
01:46:48 Sort of all these service locations around
01:46:50 and have a technician take a look at it.
01:46:52 So teleoperation often gets this, you know,
01:46:57 so dismissive, you know, commentary from other folks
01:47:02 working on other scenarios.
01:47:04 But I think it’s potentially more relevant
01:47:07 than we hear publicly.
01:47:09 But it’s a hard problem.
01:47:11 And, you know, for me, I’ve gotten a chance
01:47:17 to interact with people that take on hard problems
01:47:19 and solve them and they’re rare.
01:47:21 What Tesla has done with their data engine.
01:47:25 So I thought autonomous driving cannot be solved
01:47:29 without collecting a huge amount of data
01:47:31 and organizing it well,
01:47:32 not just collecting, but organizing it.
01:47:34 And exactly what Tesla is doing now
01:47:37 is what I thought it would be,
01:47:38 like I couldn’t see car companies doing that,
01:47:40 including Tesla.
01:47:42 And now that they’re doing that, it’s like, oh, okay.
01:47:44 So it’s possible to take on this huge effort seriously.
01:47:48 To me, teleoperation is another huge effort like that.
01:47:51 It’s like taking seriously what happens when it fails.
01:47:56 What’s the, in the case of Waymo for the consumer,
01:48:00 like ride sharing, what’s the customer experience like?
01:48:04 There’s a bunch of videos online now
01:48:06 where people are like the car fails and it pulls off
01:48:09 to the side and you call like customer service
01:48:11 and you’re basically sitting there for a long time
01:48:13 and there’s confusion.
01:48:15 And then there’s a rescue that comes
01:48:17 and they start to drive.
01:48:17 I mean, just the whole experience is a mess
01:48:19 that has a ripple effect to how you trust
01:48:23 in the entirety of the experience.
01:48:25 But like actually taking on the problem
01:48:27 of that failure case and revolutionizing that experience,
01:48:32 both for trucking and for ride sharing,
01:48:34 that’s an amazing opportunity there
01:48:35 because that feels like it would change everything.
01:48:40 If you can reliably know when the failures happen,
01:48:42 which they will, you have a clear plan
01:48:45 that doesn’t significantly affect the efficiency
01:48:47 of the whole process, that could be the game changer.
01:48:51 And if teleoperation is part of that,
01:48:53 it could be just like you’re saying,
01:48:54 it could be teleoperation or it could be like a fleet
01:48:57 of rescuers that can come in, which is a similar idea.
01:49:01 But teleoperation, obviously that allows you
01:49:04 to just have a network of monitors
01:49:07 of people monitoring this giant fleet of trucks
01:49:10 and taking over when needed.
01:49:12 And it’s a beautiful vision of the future
01:49:14 where there’s millions of robots
01:49:18 and only thousands of humans monitoring
01:49:20 those millions of robots.
01:49:22 That seems like a perfect dance
01:49:27 of allowing humans to do what they do best
01:49:29 and allowing robots to do what they do best.
01:49:31 Yeah, yeah, so I mean, I think there are,
01:49:34 and we just applied for an NSF we didn’t get,
01:49:37 anybody’s watching, but with some folks from Wisconsin
01:49:41 who do teleoperation, right?
01:49:43 And some of this is used for like rovers
01:49:46 and I mean, really high stakes, difficult problems.
01:49:50 But one of the things we wanted to study
01:49:52 were these mines, these Rio Tinto mines in Australia
01:49:55 where they remotely pilot the trucks.
01:49:59 And there’s some autonomy, I guess,
01:50:01 but it’s overseen by a remote operator
01:50:05 and it’s near Perth and it’s quite remote
01:50:09 and they retrained the truck drivers
01:50:13 to be the remote operators, right?
01:50:15 There’s autonomy in the port of Rotterdam
01:50:18 and places like that where there are jobs there.
01:50:21 And so I think, and maybe we’ll get to this later,
01:50:24 but there’s a real policy question
01:50:25 about sort of who’s gonna lose and what we do about it
01:50:28 and whether or not there are opportunities there
01:50:31 that maybe we need to put our thumb on the scale
01:50:33 a little bit to make sure that there’s some give back
01:50:38 to the community that’s taking the hit.
01:50:41 So for instance, if there were teleoperation centers,
01:50:45 maybe they go in these communities
01:50:46 that we disproportionately source truck drivers from today.
01:50:50 Now, I mean, what does that mean?
01:50:52 It may not be the cheapest place to do it
01:50:53 if they don’t have great connectivity
01:50:55 and it may not be where the upper level managers wanna be
01:50:58 and places like that, issues like that, right?
01:51:01 So I do think it’s an interesting question,
01:51:04 both from sort of a practical scenario situation
01:51:09 of how it’s gonna work, but also from a policy perspective.
01:51:13 So there’s platoons, there’s teleoperation,
01:51:16 and this is taking care of some of the highway driving
01:51:20 that we’re talking about.
01:51:21 Is there other ideas like,
01:51:24 is there other ideas, scenarios
01:51:26 that you have for autonomous trucks?
01:51:28 Yeah, so I mean, the most obvious one actually
01:51:31 is just facility to facility, right?
01:51:34 The sort of, it can’t go everywhere,
01:51:37 but a lot of logistics facilities
01:51:40 are very close to interstates
01:51:42 and they’re on big commercial roads
01:51:45 without bikes and parked cars and all that stuff.
01:51:48 And some of the jobs that I think are really first
01:51:51 on the chopping block are these LTL,
01:51:54 that less than truckload, what’s called line haul, right?
01:51:57 So these are the drivers who go from terminal to terminal
01:51:59 with those full trailers.
01:52:02 And those facilities are often located strategically
01:52:05 to avoid congestion, right?
01:52:07 And to be in big industrial facilities.
01:52:10 So you could imagine that being the first place
01:52:14 you see a Waymo self driving truck rollout
01:52:17 might be sort of direct facility to facility
01:52:21 for UPS or FedEx or less than truckload care.
01:52:25 And the idea there is fully driverless,
01:52:27 so potentially not even a driver in the truck,
01:52:30 it’s just going from facility to facility empty,
01:52:33 zero occupancy.
01:52:34 Yeah, and those, because that labor is expensive,
01:52:38 they don’t keep those drivers out overnight,
01:52:39 those drivers do a run back and forth typically,
01:52:42 or in a team go back and forth in one day.
01:52:47 So from the people you’ve spoken with so far,
01:52:49 what’s your sense?
01:52:50 How far are we away from, which scenario is closest
01:52:53 and how far away are we from that scenario
01:52:56 of autonomy being a big part of our trucking fleet?
01:53:02 Most folks are focused on another scenario,
01:53:05 which is the exit to exit, right?
01:53:07 Which looks like that urban truck ports thing
01:53:10 that I laid out earlier.
01:53:12 So you have a human driven truck
01:53:14 that comes out to a drop lot,
01:53:16 it meets up with an autonomous truck,
01:53:19 that truck then drives it on the interstate to another lot,
01:53:23 and then a human driver picks it up.
01:53:27 There are a couple variations maybe on that.
01:53:32 So, or let me just run through the last two scenarios.
01:53:36 Sure.
01:53:37 The other thing you could do, right,
01:53:39 is to say, all right, I’ve got a truck that can drive itself,
01:53:43 and I refer to this one as autopilot,
01:53:46 but you have a human drive it out to the interstate,
01:53:49 but rather than have that transaction
01:53:52 where the human driven truck detaches the trailer
01:53:55 and it gets coupled up to a self driving truck,
01:53:58 they just, that human driver just hops on the interstate
01:54:01 with that truck and goes in back and goes off duty
01:54:05 while the truck drives itself.
01:54:07 And so you have a self driving truck
01:54:09 that’s not driverless, right?
01:54:11 And just to clarify,
01:54:12 because Tesla uses the term autopilot instead of airplanes,
01:54:15 and so everybody uses the word autopilot,
01:54:17 we’re referring to essentially full autonomy,
01:54:20 but because it’s exit to exit,
01:54:22 the truck driver is onboard the truck,
01:54:24 but they’re sleeping in the back or whatever.
01:54:26 Yeah, and this gets to the really weedy policy questions,
01:54:30 right?
01:54:31 So basically for the Department of Transportation,
01:54:34 for you to be off duty for safety reasons,
01:54:36 you have to be completely relieved of all responsibility.
01:54:39 So that truck has to not encounter a construction site
01:54:44 or inclement weather or whatever it might be,
01:54:47 and call to you and say, hey, you know,
01:54:49 or I mean, obviously, right,
01:54:51 we’re imagining connected vehicles as well, right?
01:54:53 So you’re in a self driving truck,
01:54:55 you’re in the back and trucks 20 miles ahead
01:54:58 experience some problem, right?
01:55:01 That may require teleoperation or whatever it is, right?
01:55:04 And it signals to your truck,
01:55:05 hey, you know, tell the driver 20 miles ahead,
01:55:08 he’s got to hop in the seat.
01:55:10 That would mean that they’re on duty
01:55:12 according to the way that the current rules are written,
01:55:14 they have some responsibility.
01:55:15 And part of that is, you know,
01:55:17 we need them to get rest, right?
01:55:19 They need to have uninterrupted sleep.
01:55:22 So that’s what I call autopilot.
01:55:25 The final scenario is one that I thought was actually
01:55:30 the one scenario that was good for labor, you know,
01:55:34 which I proposed is I was like, well, here’s an idea,
01:55:38 you know, that would be like, actually good for workers.
01:55:41 And just another brief aside here.
01:55:46 The history of trucking over the last, you know, 40 years,
01:55:51 there’s been a lot of technological change.
01:55:53 So when I learned to drive the truck,
01:55:55 I had to learn to manually shift it like I was describing,
01:55:57 you had to read these fairly complicated, you know,
01:56:00 big sets of laminated maps to figure out
01:56:02 where the truck can go and where it couldn’t,
01:56:04 which is a big deal, you know,
01:56:06 I mean, you take these trucks on the wrong road
01:56:07 and you’re destroying a bridge
01:56:09 or you’re doing a can opener,
01:56:10 which is where you try to drive it under a bridge too low.
01:56:12 You’ve probably seen that on YouTube,
01:56:14 if not, you know, check it out, you know, truck can opener.
01:56:18 You know, there’s some bridges that are famous for it,
01:56:20 right, and there’s one I think called the can opener
01:56:23 and you can find on YouTube.
01:56:26 And, you know, you had to log those hours like manually
01:56:30 and sort of do the math and plan your work routine.
01:56:34 And I would do this every day.
01:56:35 I’d say like, okay, I’m gonna get up at five.
01:56:37 I’ve got to think about Buffalo and there’s traffic there.
01:56:40 So I wanna be through Buffalo by 6.30, you know,
01:56:43 and then that’ll put me, you know, in Cleveland at,
01:56:47 you know, 9.30, which means I’ll miss that rush hour, right,
01:56:51 which is gonna put me in Chicago, you know,
01:56:53 and so you do this and now today, you know,
01:56:57 15 years later, truck drivers don’t have to do any of that.
01:57:01 You know, you don’t have to shift the truck,
01:57:03 you don’t have to map, you know,
01:57:05 you can figure out the least congested route
01:57:09 to go on and your hours of service are recorded
01:57:12 or a good portion of them are reported automatically.
01:57:17 All of that has been a substantial de skilling
01:57:19 that has, you know, put downward pressure on wages
01:57:23 and allowed companies to kind of speed up, monitor
01:57:26 and direct, I mean, the key technology, you know,
01:57:29 that I did work under is satellite linked computers.
01:57:32 So before you could kind of go out and plan your own work
01:57:34 and the boss really couldn’t see what you were doing
01:57:36 and push you and say, you know, you’ve been on break
01:57:39 for 10 hours, why aren’t you moving?
01:57:41 You know, and you might tell them, you know,
01:57:43 cause I’m tired, you know, like I didn’t sleep well,
01:57:45 I’ve got to get a couple more hours, you know,
01:57:48 they’re only gonna accept that so many times
01:57:50 or at least some of those dispatchers are.
01:57:51 So all this technology has made the job sort of, you know,
01:57:56 de skilled the job, you know, hurt drivers
01:57:58 in the labor market, made the work worse.
01:58:01 So I think the burden it’s really on the technologists
01:58:07 who are like, oh, this will make truck driver jobs better
01:58:09 and sort of envision ways that it would.
01:58:11 It’s like, the burden’s really, a proof is really on you
01:58:14 to sort of really clearly lay out what that
01:58:17 is gonna look like because it’s 30 or 40 years of history
01:58:21 suggests that that technology into labor markets
01:58:25 where workers are really weak and cheap is what wins
01:58:29 that new technology doesn’t help workers
01:58:31 or raise their wages.
01:58:33 So it lowers the bar of entry in terms of skill.
01:58:36 Yeah.
01:58:38 So that’s really, that’s tough.
01:58:43 That’s tough to know what to do with because yeah,
01:58:46 from a technology perspective, you wanna make the life
01:58:48 of the people doing the job today easier.
01:58:51 Is it?
01:58:52 Is that what you want?
01:58:54 No, but that like, when you think about like what exactly,
01:58:58 because the reality is you will make their life
01:59:01 potentially a little bit easier,
01:59:04 but that will allow the companies to then hire people
01:59:07 that are less skilled, get those people
01:59:10 that were previously working there fired or lower wages.
01:59:13 And so the result of this easier is a lower quality of life.
01:59:19 Yeah.
01:59:20 That’s dark actually.
01:59:21 I know, I’m sorry.
01:59:23 But you were saying that was for you initially the hopeful.
01:59:27 Oh no, so I’ll get to that.
01:59:28 But one more thing, cause this is not stopping.
01:59:31 And this is another interesting question
01:59:32 about the sort of automation.
01:59:34 And I think Uber is an interesting example here
01:59:38 where it’s like, okay, if we had self driving trucks
01:59:40 or self driving cars, we could automate
01:59:43 what used to be taxi service.
01:59:46 There’s a whole bunch of stuff
01:59:46 that’s already been automated, like the dispatching.
01:59:49 So the dispatchers are already out of work in rideshare
01:59:52 and the payment is already automated.
01:59:55 So you have to automate steps like this.
01:59:57 So you have to have that initial link to dispatch the truck.
02:00:00 You have to have the automated mapping.
02:00:04 So we’re sort of done all this incremental automation
02:00:07 that could make the truck completely driverless.
02:00:11 There’s some important things happening right now
02:00:13 with the remaining good jobs.
02:00:15 So what you’re really paying for
02:00:17 when you get a good truck driver is, like I said,
02:00:20 you get those kind of local skills
02:00:22 of like backing and congested traffic.
02:00:26 Those, it’s really impressive to watch
02:00:28 and there’s some value on it certainly,
02:00:30 but it’s relatively low value
02:00:33 in the actual driving technique, right?
02:00:35 So you bump something backing into the dock,
02:00:39 it might be a couple of thousand dollars
02:00:41 because you ruin a canopy or something over a dock
02:00:43 or tear up a trailer.
02:00:45 What you really want,
02:00:46 those highly skilled conscientious drivers,
02:00:50 and that’s really what it is.
02:00:52 And that’s what computers are really good at
02:00:53 is about being conscientious, right?
02:00:55 In the sense of like, they pay attention continually, right?
02:00:59 And how I was describing those long haul segments
02:01:02 where the driver just keeps out of the situations
02:01:06 that could become problematic
02:01:08 and just, they don’t look at their phone.
02:01:10 I mean, they take the job seriously and they’re safe
02:01:13 and you can give somebody a skills test, right?
02:01:16 As a CDL examiner, you could take them out and say,
02:01:19 all right, I need you to go around these cones
02:01:20 and drive safely through this school zone.
02:01:24 But what really proves that you’re a safe driver
02:01:27 is two years without an accident, right?
02:01:29 Because that means that day after day,
02:01:31 hour after hour, mile after mile,
02:01:34 you did the right thing, right?
02:01:36 And not when it was like, oh, some situations emerging,
02:01:39 but just consistently over time
02:01:41 kept yourself out of accident situations.
02:01:43 And you can see this with drivers who are a million
02:01:46 or 2 million safe miles.
02:01:47 The value of those drivers for Walmart
02:01:50 is they don’t run over minivans.
02:01:52 The company I worked for,
02:01:54 they ran over minivans on a regular basis.
02:01:57 So when I was trained, they said, we kill 20 people a year.
02:02:03 We send someone to the funeral,
02:02:04 there’s a big check involved, don’t be that.
02:02:08 We don’t wanna go to your funeral
02:02:10 and you don’t wanna be the person who caused that funeral.
02:02:15 Okay, so they just write that off.
02:02:18 Okay, that’s just part of the business model.
02:02:20 Now, forward collision avoidance
02:02:25 can basically eliminate the vast majority
02:02:29 of those accidents.
02:02:30 That’s what the value of a really expensive
02:02:33 conscientious driver is based on.
02:02:35 They don’t run over minivans.
02:02:37 So as soon as you have that forward collision avoidance,
02:02:40 what’s gonna happen to the wages of those drivers?
02:02:43 By way of a therapy session, help me understand,
02:02:48 is a collision avoidance,
02:02:52 automated collision avoidance systems,
02:02:55 are they good or bad for society?
02:02:57 Yeah, I mean, this is, they’re good.
02:03:02 Right. They’re good.
02:03:03 But what do we do about the pain of a workforce
02:03:08 in the short term because their wages are gonna go down
02:03:13 because the job starts requiring less and less skill?
02:03:18 Is there a hopeful message here
02:03:20 where other jobs are created?
02:03:22 So I’m a sociologist, right?
02:03:24 So I’m gonna think about what’s the structure behind that
02:03:28 that creates that pain, right?
02:03:30 And it’s ownership, right?
02:03:32 We don’t call it capitalism for nothing.
02:03:35 What capitalists do is they figure out cheaper,
02:03:39 more efficient ways to do stuff.
02:03:40 And they use technology to do that oftentimes, right?
02:03:43 This is the remarkable history of the last couple centuries
02:03:47 and all the productivity gains is,
02:03:50 people who were in a competitive market saying,
02:03:54 if I have to do it, right?
02:03:56 I don’t have a choice.
02:03:57 Cause like my competitor over there is gonna eat my lunch
02:04:00 if I’m not on my game.
02:04:03 I don’t have a choice.
02:04:04 I’ve got to invest in this technology
02:04:06 to make it more efficient, to make it cheaper.
02:04:10 And what do you look for?
02:04:12 You look for oftentimes, you look for labor costs, right?
02:04:16 You look for high value labor.
02:04:17 If I can take a hundred and,
02:04:19 a lot of these truck drivers make good money,
02:04:21 a hundred thousand dollars, good benefits,
02:04:22 vacation, retirement.
02:04:25 If I can replace them with a $35,000 worker
02:04:28 when I’m competing with maybe a low wage retail employer
02:04:32 rather than some other more expensive employers
02:04:34 for skilled blue collar workers, I’m gonna do that.
02:04:39 And that’s just, that’s what we do.
02:04:41 And so I think those are the bigger questions
02:04:45 around this technology, right?
02:04:46 Is like, are workers gonna get screwed by this?
02:04:50 Like, yeah, most likely.
02:04:51 Like that’s what we do.
02:04:54 So one of the things you say is,
02:04:55 I mean, first of all, the numbers of workers
02:04:56 that will feel this pain is not perhaps as large
02:05:00 as the journalists kind of articulate,
02:05:02 but nevertheless, the pain is real.
02:05:05 And I guess my question here is,
02:05:11 do you have an optimistic vision
02:05:12 about the transformative effects
02:05:14 of autonomous trucks on society?
02:05:17 Like if you look 20 years from now
02:05:21 and perhaps see maybe 30 years from now,
02:05:24 perhaps see these autonomous trucks
02:05:26 doing the various parts of the scenarios you listed.
02:05:30 And there’s just hundreds of thousands of them,
02:05:33 just like veins, like blood flowing through veins
02:05:38 on the interstate system.
02:05:43 What kind of world do you see that’s a better world
02:05:46 than today that involves such trucks?
02:05:48 Yeah, can I defend myself first?
02:05:51 Because I’m reading the comments right now
02:05:53 of people, of the economists who are telling me.
02:05:56 Another commenter, dear PhD in economics.
02:05:59 Yes, yes, dear PhD in economics,
02:06:02 I know that higher skilled jobs
02:06:05 are created by technological advancement, right?
02:06:09 I mean, there are big questions about how many of them,
02:06:11 right, so the idea that we would create
02:06:14 more expensive labor positions, right,
02:06:19 with a new technology, right?
02:06:20 You better check your business plan
02:06:22 if your idea is to take a bunch of low wage labor
02:06:26 and replace it with the same amount of high wage labor,
02:06:28 right, so there’s a question about how many of those jobs.
02:06:31 And there’s the really important social
02:06:34 and political question of are they the same people, right?
02:06:38 And do they live in the same places?
02:06:39 And I think that kind of geography
02:06:42 is a huge issue here with the impacts, right?
02:06:45 Lots of rural workers.
02:06:47 Interesting politically, lots of red state workers, right?
02:06:50 Lots of blue state, maybe union folks
02:06:51 who are gonna try to slow autonomy
02:06:53 and lots of red state representatives in the house maybe
02:06:57 who wanna stand up for their trucker constituents.
02:07:01 So just to defend myself.
02:07:03 Yeah, and to elaborate, I think economics as a field
02:07:06 is not good at measuring the landscape
02:07:08 of human pain and suffering.
02:07:10 So sometimes you can forget in the numbers
02:07:13 that it’s real lives that are at stake.
02:07:15 That’s what I suppose sociology is better at doing.
02:07:18 So we try sometimes, sometimes.
02:07:20 Well, the problem with, I mean,
02:07:22 I’m somebody who loves psychology and psychiatry
02:07:25 and a little bit, I guess, of sociology.
02:07:28 I realize how little, how tragically flawed the field is,
02:07:33 not because of lack of trying,
02:07:34 but just how difficult the problems are.
02:07:37 To do really thorough studies
02:07:39 that understand the fundamentals of human behavior
02:07:42 and this, yes, landscape of human suffering,
02:07:45 it’s almost an impossible task without the data.
02:07:48 And we currently don’t, not everybody’s richly integrated
02:07:53 to where they’re fully connected
02:07:54 and all their information is being recorded
02:07:58 for sociologists to study.
02:08:00 So you have to make a lot of inferences.
02:08:02 You have to talk to people.
02:08:03 You have to do the interviews as you’re doing.
02:08:05 And through that really difficult work,
02:08:07 try to understand, hear the music
02:08:11 that nobody else is hearing,
02:08:13 the music of what people are feeling,
02:08:15 their hopes, their dreams, and the crushing of their dreams
02:08:19 due to some kind of economic forces.
02:08:22 Yeah, I mean, we’ve just lived that
02:08:24 for four and a half years of probably elites,
02:08:28 let me just go out on a limb and say,
02:08:30 not understanding the sort of emotional
02:08:33 and psychological currents
02:08:35 of a large portion of the population, right?
02:08:37 And just being stunned by it and confused, right?
02:08:41 It wasn’t confusing for me after having talked to truckers.
02:08:46 Again, trucking is a job of last resort.
02:08:48 These are people who’ve already lost
02:08:50 that manufacturing job oftentimes,
02:08:52 already lost that construction job to just aging, right?
02:08:57 So what can we do, right?
02:08:59 What’s sort of the positive vision?
02:09:01 Because like, we’ve got tons of highway deaths.
02:09:04 We’ve got, and just the big picture is,
02:09:09 and this is the opportunity, I guess, for investors,
02:09:13 it’s a hugely inefficient system.
02:09:15 So we buy this truck,
02:09:17 there’s this low wage worker in it oftentimes.
02:09:19 And again, I’m setting aside those really good
02:09:21 line haul jobs in LTL, those are a different case.
02:09:26 That low wage worker is driving a truck that they might,
02:09:30 the wheels might roll seven to eight hours a day.
02:09:32 That’s what the truck is designed to do
02:09:33 and that’s what makes the money for the company.
02:09:36 In other seven, eight hours a day,
02:09:37 the driver’s doing other kinds of work
02:09:39 that is not driving.
02:09:41 And then the rest of the day,
02:09:42 they’re basically living out of the truck.
02:09:45 You really can’t find a more inefficient use of an asset
02:09:49 than that, right?
02:09:51 Now, a big part of that is we pay for the roads
02:09:53 and we pay for the rest areas and all this other stuff.
02:09:55 So the way that I work and the way that I think
02:09:59 about these problems is I try to find analogies, right?
02:10:01 Sort of labor processes and things that make economic sense
02:10:04 that seem in the same area of the economy,
02:10:11 but have some different characteristics for workers, right?
02:10:15 And sort of try to figure out
02:10:17 why does the economics work there, right?
02:10:19 And so if you look at those really good jobs,
02:10:24 the most likely way that you as a passenger car driver
02:10:29 would know that it’s one of those drivers
02:10:30 is that there are multiple trailers, right?
02:10:33 So you see these, like maybe it’s three small trailers,
02:10:35 maybe it’s two sort of medium sized trailers.
02:10:37 Some places you might even see
02:10:39 two really big trailers together.
02:10:42 You do that because labor is expensive, right?
02:10:44 And it’s highly skilled.
02:10:45 And so you use it efficiently and you say, all right,
02:10:48 rather than having you haul that little trailer
02:10:51 out of the ports, that sort of half size container,
02:10:54 we’re gonna wait till we get three
02:10:55 or we’re gonna coordinate the movement
02:10:56 so that they’re three ready.
02:10:57 You go do what truckers call make a set,
02:11:00 put them together, right, and you go.
02:11:04 That’s a massive productivity gain, right?
02:11:06 Because you’re hauling two, three times as much freight.
02:11:09 So the positive scenario that I threw out in 2018
02:11:13 was why not have a human driven truck
02:11:18 with a self driving truck that follows it, right?
02:11:20 Just a drone unit.
02:11:23 And to me, this seemed as a non computer scientist,
02:11:28 a non computer scientist, a sociologist, right?
02:11:31 This made a lot of sense because when I got done talking
02:11:33 to the computer scientists and the engineers,
02:11:36 they were like, well, it’s like object recognition,
02:11:38 decision making algorithm, all this stuff.
02:11:40 It’s like, all right, so why don’t you leave
02:11:43 the human brain in the lead vehicle, right?
02:11:46 You got all that processing and then all that following.
02:11:50 Now, again, this is sort of me being a lay person.
02:11:54 I said, why don’t, then that following truck, right,
02:11:57 makes direction from the front.
02:11:58 It uses the rear of the trailer as a reference point.
02:12:01 It maintains the lane.
02:12:02 You’ve got cooperative adaptive cruise control
02:12:04 and that you double the productivity of that driver.
02:12:08 You solve that problem that I hated
02:12:11 in my urban truck ports thing about the bridge weight.
02:12:15 Cause when you get to the bridges,
02:12:17 the two trucks can just spread out just enough
02:12:20 to make the bridge weight, right?
02:12:21 And you can just program that in
02:12:22 and they’re 50 feet further apart,
02:12:24 100 feet further apart.
02:12:28 So interesting sort of, I think, story about this
02:12:32 that leads to kind of, I think, the policy questions.
02:12:36 In, I guess, 2017, Jack Reed and Susan Collins
02:12:42 and requested from the Senate,
02:12:44 the Senate requested research on what the impacts
02:12:47 of self driving trucks would be.
02:12:48 And the first stage of that was for the GAO
02:12:51 to do a report, sort of looking at the lay of the land,
02:12:56 talking to some experts.
02:12:59 And I was working on my 2018 report,
02:13:03 help contribute to that GAO report.
02:13:06 And I had the six scenarios, right?
02:13:08 I’m like, okay, here’s what Starsky’s doing.
02:13:12 Here’s what Embark and Uber are doing.
02:13:16 Here’s what Waymo might be doing.
02:13:18 Nobody really knows, right?
02:13:20 Here’s what Peloton’s doing.
02:13:23 Here’s the autopilot scenario.
02:13:25 And then here’s this one that I think
02:13:27 actually could be good for drivers.
02:13:29 So now you’ve got that driver who’s got
02:13:31 two times the freight.
02:13:34 Their decisions are more important.
02:13:35 They’re managing a more complex system, right?
02:13:37 They’re probably gonna have to have
02:13:38 some global understanding of how to,
02:13:40 the environments in which it can operate safely, right?
02:13:42 Now we’re talking upskilling, right?
02:13:44 And so the GAO sort of writes up these different scenarios
02:13:52 and the idea is that it’s gonna prepare
02:13:54 for this Department of Transportation,
02:13:56 Department of Labor set of processes
02:13:58 to engage stakeholders and sort of get industry perspectives
02:14:05 and then do a study on the labor impacts.
02:14:07 So that DOT, DOL process starts to happen
02:14:12 and I get to the workshop and a friend was sitting
02:14:18 at the table next to me and he holds up the scenarios
02:14:22 that they’re gonna have us discuss at this workshop.
02:14:24 And he’s like, hey, these look really familiar, right?
02:14:27 They were the scenarios from the report,
02:14:30 but there were only five instead of six.
02:14:33 Interesting.
02:14:34 The sixth scenario, which was the upskilling labor,
02:14:37 good for workers scenario, wasn’t discussed.
02:14:42 So to clarify that the integral piece of technology
02:14:45 there is platooning.
02:14:47 Yeah, I mean, in a sense it’s platooning,
02:14:50 but, and in fairness, right, as I pitched that idea
02:14:54 or sort of ran that idea by the computer scientists
02:14:58 and engineers and product managers that I would talk to,
02:15:01 they would say, we thought about that,
02:15:05 but that following truck, it’s not that simple.
02:15:09 That thing, basically we had to engineer that
02:15:12 to be capable of independent self driving,
02:15:15 because what if there was a cut in
02:15:17 or any number of scenarios in which it lost
02:15:21 that connection to the lead truck for whatever reason.
02:15:25 Now, I mean, I don’t know.
02:15:26 Boo hoo, platooning is hard.
02:15:29 There’s edge cases.
02:15:30 I guarantee the number of edge cases in platooning
02:15:33 is orders of magnitude lower than the number of edge cases
02:15:37 in the general solo full self drive.
02:15:40 You do not need to solve the full self driving problem.
02:15:43 I mean, if you’re talking about
02:15:46 probability of dangerous events,
02:15:49 it just seems with platooning,
02:15:50 then like you can deal with cut ins.
02:15:54 Yeah, so this is beyond,
02:15:56 this is one of the challenge obviously of being a researcher
02:15:59 who doesn’t really have any background
02:16:02 in the technology, right?
02:16:04 So I can dream this up.
02:16:05 I don’t, you know, I have no idea if it’s feasible.
02:16:08 Well, let me speak, you spoke to the PhDs in economics.
02:16:10 Let me speak to the PhDs in computer science.
02:16:12 If you think platooning is as hard
02:16:14 as the full self driving problem,
02:16:17 we need to talk, because I think that’s ridiculous.
02:16:20 I think platooning, and in fact,
02:16:22 I think platooning is an interesting idea
02:16:24 for ride sharing as well,
02:16:26 for the general autonomous driving problem,
02:16:28 not just trucking, but obviously trucking
02:16:30 is the big, big benefit,
02:16:32 because the number of A to B points in trucking
02:16:35 is much, much lower than the general ride sharing problem.
02:16:38 But anyway, I think that’s a great idea,
02:16:40 but you’re saying it was removed.
02:16:42 Yeah, and so you can go, you know,
02:16:44 and listeners could go to these reports.
02:16:47 They’re publicly available.
02:16:48 And they explain why in the footnote.
02:16:51 And they note that there was this other scenario
02:16:54 suggested by at least me,
02:16:56 and I can’t remember if they said someone else did too.
02:16:58 But they said, you know, we didn’t include it
02:17:01 because no developers were working on it.
02:17:04 Interesting.
02:17:05 Full disclosure,
02:17:07 that was the approach that I took in my research, right?
02:17:11 Which was to go to the developers and say,
02:17:13 what’s your vision, right?
02:17:14 What are you trying to develop?
02:17:17 That’s what I was trying to do.
02:17:19 And maybe, you know,
02:17:20 and then I tried to think outside the box at the end
02:17:22 by adding that one, right?
02:17:23 Like, here’s one that I have, you know,
02:17:24 people aren’t talking about that could be cool.
02:17:25 Now, again, it had been proposed in like 2014
02:17:29 for like fuel convoys.
02:17:31 So you could just have like one super armored lead fuel
02:17:35 truck, right?
02:17:35 In a, you know, bringing fuel to forward operating bases
02:17:38 in Afghanistan.
02:17:39 And then you wouldn’t need, you know, the super heavy,
02:17:41 you know, you wouldn’t have to protect the human life
02:17:43 in the following truck.
02:17:44 So that’s interesting.
02:17:44 You’re saying like, when you talk to Waymo,
02:17:46 when you talk to these kinds of companies,
02:17:48 they weren’t at least openly saying they’re working on this.
02:17:52 So then it doesn’t make sense to include in the list.
02:17:56 Yeah.
02:17:56 And so, but here’s the thing, right?
02:17:58 This is the Department of Transportation, right?
02:18:01 And the Department of Labor.
02:18:03 Maybe they could consider some scenarios.
02:18:04 Like maybe we could say, you know, this, we,
02:18:07 this technology has got a lot of potential.
02:18:08 Here’s what we’d like it to do.
02:18:10 You know, we’d like it to reduce highway deaths,
02:18:12 help us fight climate change, reduce congestion,
02:18:14 you know, all these other, other things.
02:18:16 But that’s not how our policy conversation
02:18:19 around technology is happening.
02:18:20 We’re not, and people don’t think that we should.
02:18:24 And I think that’s the fundamental shift
02:18:26 that we need to have, right?
02:18:27 I’ve been involved with this a little bit like NHTSA and DOT.
02:18:31 The approach they took is saying,
02:18:33 we don’t know what the heck we’re doing.
02:18:34 So we’re going to just let the innovators do their thing
02:18:38 and not regulate it for a while, just to see.
02:18:41 You don’t, you think that’s,
02:18:43 you think DOT should provide ideas themselves.
02:18:46 Well, so this is the, this is the great trick
02:18:49 in policy of private actors,
02:18:53 is you get narrow mandates for government agencies, right?
02:18:58 So, you know, the safety case will be handled
02:19:01 by organizations whose mandate is safety.
02:19:04 So the Federal Motor Carrier Safety Administration,
02:19:07 who is, you know, going to be a key player,
02:19:11 I argue in an article that I wrote, you know,
02:19:13 they’re going to be a key player in actually determining
02:19:15 which scenario is most profitable
02:19:17 by setting the rules for truck drivers.
02:19:20 Their mandate is safety, right?
02:19:22 Now they have lots of good people there who want,
02:19:25 you know, who care about truck drivers
02:19:26 and who wish truck drivers jobs were better,
02:19:29 but they don’t have the authority to say,
02:19:32 hey, we’re going to write this rule
02:19:34 because it’s good for truck drivers, right?
02:19:35 And so when you, you know, we need to say,
02:19:40 you know, as a society, we need to not restrict technology,
02:19:44 not stand in the way of things.
02:19:45 We need to harness it towards the goals that matter, right?
02:19:48 Not whatever comes out the end of the pipeline
02:19:52 because it’s the easiest thing to develop
02:19:53 or whatever is most profitable for the first actor
02:19:57 or whatever, but, you know, and we do,
02:19:58 the thing is we do that, right?
02:20:00 I mean, like when we sent people to the moon,
02:20:04 you know, we did that,
02:20:06 and there were tremendous benefits
02:20:07 that followed from it, right?
02:20:09 And we do this all the time in, you know,
02:20:11 trying to cure cancer or whatever it is, right?
02:20:13 I mean, we can do this, right?
02:20:17 Now the interesting sort of epilogue to that story is,
02:20:21 you know, six months or so, I don’t know how long it was,
02:20:25 after those meetings in which that sixth scenario
02:20:28 was not considered, a company called Locomation,
02:20:33 you know, ends up using that,
02:20:36 essentially that basic scenario with a slight variation.
02:20:39 So they leave the human driver in both trucks
02:20:43 and then that following driver goes off duty.
02:20:46 And then, you know, I’ve been trying to think
02:20:50 of what the term is, they kind of,
02:20:50 I think of it as like slingshotting,
02:20:52 they sort of, when one runs out of hours,
02:20:54 you know, the one who’s off duty goes in front and,
02:20:56 you know, and so, you know, if only they had been,
02:21:01 you know, around six months earlier,
02:21:04 that might’ve been considered by the OT,
02:21:06 but it just says, you know, who has the authority
02:21:08 to propose what these visions of the future are?
02:21:10 Well, some of it is also just the company stepping up
02:21:13 and just doing it, screw the authority,
02:21:16 and showing that it’s possible,
02:21:18 and then the authority follows.
02:21:19 So that’s why I really love innovators in the space.
02:21:24 The criticism I have, the very sort of real,
02:21:29 I don’t know, harsh criticism I have
02:21:31 towards autonomous vehicle companies in the space
02:21:34 is they’ve gotten culturally,
02:21:38 they’ve, it’s become acceptable somehow
02:21:42 to do demos and videos,
02:21:46 as opposed to the old school American way
02:21:48 of solving problems.
02:21:50 There’s a culture in Silicon Valley
02:21:53 where you’re talking to VCs
02:21:56 that have lost that kind of love of solving problems.
02:22:01 They kind of like envision,
02:22:03 if the story you told me in your PowerPoint presentation
02:22:07 is true, how many trillions of dollars
02:22:09 might I be able to make?
02:22:10 There’s something lost in that conversation
02:22:13 where you’re not really taking on like the problem
02:22:16 in a real way, so these autonomous vehicle companies
02:22:19 realize we don’t need to,
02:22:21 we just need to make nice PowerPoint presentations
02:22:24 and not actually deliver products
02:22:26 that like everybody looks outside and says,
02:22:29 holy shit, this is life changing.
02:22:31 This is where I have to give props to Waymo
02:22:34 is they put driverless cars on the road
02:22:37 and like forget PowerPoint slide presentations,
02:22:41 actual cars on the road.
02:22:42 Then you can criticize like,
02:22:43 is that actually going to work?
02:22:45 Who knows, but the thing is they have cars on the road
02:22:48 and that’s why I have to give props to Tesla.
02:22:49 They have whatever you want to say about risk
02:22:52 and all those kinds of things,
02:22:54 they have cars on the road
02:22:55 that have some level of automation
02:22:57 and soon they have trucks on the road as well.
02:23:00 And that kind of, that component,
02:23:03 I think is important part of the policy conversation
02:23:06 because you start getting data from these companies
02:23:10 that are willing to take the big risks
02:23:12 as opposed to making slide decks,
02:23:14 they’re actually putting cars on the road
02:23:16 and like real lives are at stake.
02:23:19 They could be lost and they could bankrupt the company
02:23:21 if they make the wrong decisions.
02:23:23 And that’s deeply admirable to me.
02:23:25 Speaking of which I have to ask Waymo trucks,
02:23:28 I think it’s called Waymo Via.
02:23:31 So I’m talking to the head of trucking at Waymo.
02:23:34 I don’t know if you’ve gotten a chance
02:23:35 to interact with them.
02:23:37 What’s a good question to ask the guy?
02:23:39 What’s a good question of Waymo?
02:23:41 Because they seem to be one of the leaders in the space.
02:23:45 They have the zen like calm
02:23:47 of like being willing to stick with it for the longterm
02:23:51 in order to solve the problem.
02:23:53 Yeah, and I guess they have that luxury, right?
02:23:56 Which I don’t think I,
02:23:59 if I had another life as a researcher,
02:24:01 I would love to just study the business strategies
02:24:05 of startups and Silicon Valley sort of structure.
02:24:10 Would you consider Waymo a startup?
02:24:12 No.
02:24:13 No.
02:24:13 No, right?
02:24:14 I mean, it’s at least not in the things
02:24:16 that seem to matter in this self driving space.
02:24:18 So you mentioned the demos,
02:24:21 and I don’t have enough data as a sociologist
02:24:24 to really say like, oh, this is why they do what they do.
02:24:27 But my hypothesis is,
02:24:30 there’s a real scarcity of talent and money for this.
02:24:33 And there certainly was a scarcity of like partnerships
02:24:36 with OEMs and the big trucking companies.
02:24:39 And there was a race for it, right?
02:24:42 And the way that if you don’t have the backing of Alphabet,
02:24:47 you do a demo, right?
02:24:49 And you get a few more good engineers who say,
02:24:52 hey, look, they did that cool thing.
02:24:54 Like Anthony Levandowski did with Otto
02:24:56 and that resulted in the Uber purchase of that program.
02:25:01 So what would I ask?
02:25:03 I mean, I think I would ask a lot of questions,
02:25:06 but I think the markets.
02:25:07 Well, there’s also on record and off record conversations
02:25:09 which unfortunately,
02:25:11 I’m asking for an on record conversation.
02:25:14 And that I don’t know if these companies
02:25:18 are willing to have interesting on record conversations.
02:25:21 Yeah, I mean, I assume that like there are questions
02:25:24 that I don’t think you’d have to ask.
02:25:26 Like I assume they’re gonna be actually driverless, right?
02:25:28 They’re not gonna like keep the driver in there.
02:25:31 So I mean, for the industry,
02:25:33 I think it would be interesting to know
02:25:36 where they see that first adopter, right?
02:25:39 Oh, you mean from like the scenarios that laid out
02:25:42 which one are they going to take on?
02:25:44 Yeah, I mean, cause that’s gonna,
02:25:45 again, it’s those really expensive good jobs, right?
02:25:48 So those LTL jobs, the like UPS jobs.
02:25:51 Now that’s gonna be, that’s where labor is too, right?
02:25:54 That’s where the teamsters are.
02:25:54 That’s the only place they are left, right?
02:25:57 So that’s gonna be the big fight on the hill
02:26:00 and if labor can muster it, right?
02:26:03 I don’t know.
02:26:04 There’s a really cool,
02:26:06 like one thing I would recommend to you and your listeners,
02:26:10 if you really wanna see some like a remarkable page
02:26:13 in sort of the history of labor and automation,
02:26:15 there’s a report that Harry Bridges,
02:26:18 who was the socialist leader of the Longshoremen
02:26:23 on the West Coast and just, you know, galvanize that union
02:26:26 and they still control the ports today
02:26:28 because of the sort of vision that he laid down.
02:26:31 In the 1960s, he put out a photo journal report
02:26:35 called Men and Machines and basically what it was,
02:26:39 was it was an internal education campaign
02:26:42 to convince the membership
02:26:44 that they had to go along with automation.
02:26:46 Machines were coming for their jobs
02:26:48 and what the photo journal,
02:26:49 it’s almost like a hundred pages or something like that
02:26:51 is like, here’s how we used to do it.
02:26:54 Some of you old timers remember it.
02:26:56 Like we used to take the barrels of olive oil
02:26:58 and we’d stack them in the hold and we’d roll them by hand
02:27:01 and we’d put the timber in and we’d, you know,
02:27:03 stack the crates tight, you know,
02:27:05 and that was the pride of the Longshoremen,
02:27:07 was a tight stow.
02:27:09 And now you all know, you know,
02:27:12 there are cranes that come down
02:27:13 and there’s no longer any, you know, rope slings
02:27:15 and we’re loading bulldozers into the hold
02:27:17 to push the ore up into piles
02:27:19 and then clamshells are coming down
02:27:21 and he made this case to them and he said,
02:27:25 this is why we’re signing this agreement
02:27:27 to basically allow the employer to automate
02:27:33 and we’re gonna lose jobs,
02:27:34 but we’re gonna get a share of the benefits.
02:27:37 And so our wages are gonna go up.
02:27:39 We’re gonna continue to control the hiring
02:27:41 and training of workers.
02:27:42 Our numbers are gonna go down,
02:27:44 but you know, basically that last son of a bitch
02:27:46 who’s working at the ports,
02:27:48 he’s gonna be one really well paid son of a bitch,
02:27:51 you know, he may just be one standing,
02:27:53 but he’s gonna love his job.
02:27:56 You should check out that report.
02:27:57 That’s an interesting vision of a future
02:27:59 that probably still holds.
02:28:01 That is, I mean, there is some level
02:28:04 to which you have to embrace the automation.
02:28:07 Yeah, I mean, and who gets, you know,
02:28:08 it’s the benefits, right?
02:28:09 It’s like, I mean, think of the public dollars
02:28:12 that went into developing self driving vehicles
02:28:14 in the early days, right?
02:28:14 Not just the vision of it, right?
02:28:16 Which was a public vision to, you know,
02:28:18 take soldiers out of harm’s way,
02:28:21 but you know, a lot of money.
02:28:24 And there’s some way if you are a business
02:28:27 that’s leveraging the technology
02:28:29 from a broad historical ethical perspective,
02:28:33 you do owe it to the bigger community to pay back,
02:28:41 like for all the investment that was paid
02:28:44 to make that technology a reality.
02:28:47 In some sense, I don’t know how to make that right, right?
02:28:50 On one, there’s this pure capitalism
02:28:54 and then there’s communism and I’m not sure,
02:28:57 I’m not sure how to get that balance right.
02:29:04 You know, I don’t have all the answers in here,
02:29:06 you know, and I wouldn’t expect, you know,
02:29:09 individual private companies to kind of kick back, right?
02:29:11 That’s, capitalism doesn’t allow that, right?
02:29:14 Unless you have a huge monopoly, right?
02:29:15 And then you can on the backside,
02:29:17 create music halls and libraries and things like that.
02:29:21 But you know, here’s what I think, you know,
02:29:23 the basic obligation is, is, you know, come to the table,
02:29:28 like, and have an honest conversation
02:29:31 with the policymakers, with the truck drivers, you know,
02:29:35 with the communities that are at risk.
02:29:37 Like, at least let’s talk about these things, you know,
02:29:41 in a way that doesn’t look like
02:29:43 the way lobbying works right now.
02:29:45 Where you send a well paid lobbyist to the Hill
02:29:49 to, you know, convince some representative or Senator
02:29:52 to stick a sentence or two in that favors you into the,
02:29:55 like, let’s have a real conversation.
02:29:57 Real human conversation.
02:29:58 Can we just do that?
02:29:59 Yeah, don’t play games.
02:30:01 Real, real human conversation.
02:30:03 Let me ask you, mention Autopilot.
02:30:06 Gotta ask you about Tesla, this renegade little company
02:30:10 that seems to be, from my perspective,
02:30:12 revolutionizing autonomous driving
02:30:13 or semi autonomous driving,
02:30:15 or at least the problem of perception and control.
02:30:19 They’ve got a semi on the way.
02:30:22 They got a truck on the way.
02:30:24 What are your thoughts about Tesla Semi?
02:30:26 You know, I, and I did have
02:30:29 some very preliminary conversations
02:30:31 with, you know, policy folks there.
02:30:35 You know, nothing really in the tech
02:30:37 or business side of it too much.
02:30:39 And here’s why.
02:30:40 I think because electrification and autonomy
02:30:43 run in opposite directions.
02:30:46 And I just, you know, I don’t see the application,
02:30:49 the value in self driving for the truck
02:30:52 that Tesla’s gonna produce in the near term.
02:30:55 You know, they’re just, you’re not gonna have the battery.
02:30:58 And now you could have wonderful safety systems
02:31:01 and, you know, reinforcing, you know, the auto,
02:31:03 you know, self driving features supporting a skilled driver,
02:31:08 but you’re not gonna be able to pull that driver out
02:31:11 for long stretches the way that you are
02:31:12 with driverless trucks.
02:31:14 So do you think, I mean, the reason,
02:31:18 so yeah, the electrification
02:31:22 is not obviously coupled with the automation.
02:31:27 They have a very interesting approach
02:31:29 to semi autonomous pushing towards autonomous driving.
02:31:35 All right, it’s very unique.
02:31:37 No LIDAR, now no radar.
02:31:41 It’s computer vision alone from a large,
02:31:44 they’re collecting huge amounts of data from a large fleet.
02:31:47 It’s an interesting, unique approach,
02:31:49 bold and fearless in this direction.
02:31:51 If I were to guess whether this approach would work,
02:31:55 I would say, no, it started.
02:31:59 One, you would need a lot of data
02:32:01 and two, because you have actual cars deployed on the road
02:32:05 using a beta version of this product,
02:32:07 you’re going to have a system that’s far less safe
02:32:11 and you’re going to run into trouble.
02:32:13 It’s horrible PR, like it just seems like a nightmare,
02:32:17 but it seems to not be the case, at least up to this point.
02:32:20 It seems to be not, you know, on par, if not safer
02:32:26 and it seems to work really well
02:32:27 and the human factor somehow manages,
02:32:32 like drivers still pay attention.
02:32:33 Now there’s a selection of who is inside
02:32:36 the Tesla autopilot user base, right?
02:32:39 There could be a self selection mechanism there,
02:32:42 but however it works,
02:32:43 these things are not running off the road all the time.
02:32:47 So it’s very interesting whether that can sort of creep
02:32:50 into the trucking space.
02:32:52 Yes, at first the long haul problem is not solved.
02:32:57 They need to charge, but maybe you can solve, you know,
02:33:01 a lot of your scenarios involved small distances
02:33:06 and you know, that last mile aspect,
02:33:10 which is exactly what Tesla is trying to solve
02:33:12 for the regular passenger vehicle space
02:33:18 is the city driving.
02:33:20 It’s possible that you have these trucks.
02:33:22 It’s almost like, yeah, you solved the last mile delivery
02:33:28 part of some of the scenarios that you mentioned
02:33:31 in autonomous driving space.
02:33:32 Is that, do you think that’s from the people you’ve spoken
02:33:35 with too difficult of a problem?
02:33:37 The thing that, you know, keeps me so interested
02:33:41 in this space and thinking that it’s so important,
02:33:43 you know, is again, that efficiency question,
02:33:46 that safety question and the way that these economics
02:33:50 can push us potentially, you know,
02:33:53 toward a more efficient system.
02:33:54 So I wanna see those Tesla electric trucks running out
02:33:58 to those truck ports where you’ve got those two,
02:34:01 you know, two trucks with a human driver in front, right?
02:34:05 You know, I think that’s now what’s powering those
02:34:08 is that hydrogen, you know, I mean, I don’t, you know,
02:34:11 again, it’s very interesting as a researcher
02:34:13 who does not have a background in technology
02:34:14 and doesn’t have a horse, you know, in this race.
02:34:18 I mean, you know, for all I know,
02:34:20 self driving trucks will ultimately be achieved
02:34:22 by some biomechanical sensor that uses echolocation
02:34:26 because we took stem cells of bats.
02:34:28 And you know, I mean, I don’t, I don’t,
02:34:30 I am completely unable to assess who’s, you know,
02:34:35 who’s the head or who’s behind or who makes sense.
02:34:37 But I think one key component there,
02:34:39 and this is what I see with Tesla often,
02:34:42 and it’s quite sad to me that other companies
02:34:45 don’t do this enough, is that first principles thinking,
02:34:49 like, wait, wait, wait, okay.
02:34:51 It’s looking at the inefficiencies as opposed to,
02:34:54 I’ve worked with quite a few car companies
02:34:57 and they basically have a lot of meetings.
02:35:00 There’s a lot of meetings.
02:35:01 And the discussion is like,
02:35:03 how can we make this cheaper, this cheaper, this cheaper,
02:35:05 this component cheaper, this cheaper,
02:35:07 the cheapification of everything, just like you said,
02:35:10 as opposed to saying, wait a minute, let’s step back.
02:35:13 Let’s look at the entirety of the inefficiencies
02:35:15 in the system.
02:35:17 Like, why have we been doing this like this
02:35:19 for the last few decades?
02:35:20 Like, start from scratch.
02:35:22 Can this be 10X, 100X cheaper?
02:35:25 Like, if we not just decrease the cost
02:35:29 of one component here or this component here
02:35:32 or this component here,
02:35:33 but like, let’s like redesign everything.
02:35:37 Let’s infrastructure, let’s have special lanes
02:35:42 or in terms of truck ports,
02:35:45 as opposed to having regular human control truck ports,
02:35:47 have some kind of weird like sensors,
02:35:51 like where everything about the truck connecting
02:35:56 at that final destination is automated fully
02:35:58 from the ground up.
02:35:59 You build the facility from the ground up
02:36:01 for the autonomous truck.
02:36:03 All those kinds of sort of questions are platooning.
02:36:06 Let’s say, wait a minute.
02:36:08 Okay, I know we think platooning is hard,
02:36:11 but can we think through exactly why it’s hard
02:36:14 and can we actually solve it?
02:36:15 Like if we collect a huge amount of data, can we solve it?
02:36:20 And then teleoperation, like, okay, yeah, yeah.
02:36:23 It’s difficult to have good signal,
02:36:25 but can we actually, can we have,
02:36:27 can we consider the probability of those edge cases
02:36:31 and what to do in the edge cases
02:36:32 when the teleoperation fails?
02:36:34 Like how difficult is this?
02:36:35 What are the costs?
02:36:36 How do we actually construct a teleoperation center
02:36:39 full of humans that are able to pay attention
02:36:41 to a large fleet where the average number of vehicles
02:36:44 per human is like 10 or a hundred?
02:36:47 Like having that conversation as opposed to kind of having,
02:36:52 you show up to work and say, all right,
02:36:55 it seems like because of COVID,
02:36:58 we are not making as much money.
02:37:00 Can we have a cheaper,
02:37:02 can we give less salary to the trucker?
02:37:04 And can we build like decrease the cost
02:37:11 or decrease the frequency at which we buy new trucks?
02:37:14 And when we do buy new trucks,
02:37:16 make them cheaper by making them crappier,
02:37:18 like this kind of discussion.
02:37:20 This is why, to me, it’s like Tesla is like rare on this.
02:37:23 And there’s some sectors in which innovation
02:37:26 is part of the culture.
02:37:27 In the automotive sector, for some reason,
02:37:29 it’s not as much.
02:37:31 This is obviously the problem that Ford and GM
02:37:33 are struggling with.
02:37:34 It’s like, they’re really good at making cars at scale cheap.
02:37:39 And they’re like legit good.
02:37:41 Like Toyota at this,
02:37:42 they’re some of the greatest manufacturing people
02:37:44 in the world, right?
02:37:45 That’s incredible.
02:37:46 But then when it comes to hiring software people,
02:37:48 they’re horrible.
02:37:49 So it’s culture.
02:37:52 And then it’s such a difficult thing
02:37:55 for them to sort of embrace,
02:37:57 but greatness requires that they embrace this,
02:38:01 embrace whatever is required
02:38:03 to remove the inefficiencies in the system.
02:38:04 And that may require you to do things very differently
02:38:07 than you’ve done in the past.
02:38:09 Yeah, I mean, there are certain things
02:38:12 that the market can do well.
02:38:13 And this is how I see the world, right?
02:38:17 That’s the best way to organize certain kinds of activities
02:38:21 is the market and private interest.
02:38:24 But I think we go too far in some areas.
02:38:28 Transportation is,
02:38:30 if we can’t have a public debate about the roads
02:38:35 that we all pay for,
02:38:39 forget about it.
02:38:39 Private factories and all these other,
02:38:41 healthcare and other places,
02:38:43 it’s gonna be way harder there.
02:38:45 Healthcare I guess has some direct contact
02:38:49 with the consumer where we’re probably gonna have lots of
02:38:52 sort of hands on public policy
02:38:54 about concerns around patient rights and things like that.
02:38:57 But if we can’t figure out
02:39:00 how to have a public policy conversation
02:39:02 around how technology is gonna reform our public roadways
02:39:06 and our transportation system,
02:39:10 we’re really leaving way too much to private companies.
02:39:13 And it’s just, it’s not in there.
02:39:17 I get asked this question, like, what should companies do?
02:39:19 And I’m like, just go about doing what you’re doing.
02:39:22 I mean, please come to the table and talk about it,
02:39:24 but it’s not their role.
02:39:26 I mean, I appreciate Ilan’s attempts
02:39:29 to have species level goals,
02:39:34 like, we’re gonna go to Mars.
02:39:36 I mean, that’s amazing.
02:39:37 And that’s incredible that someone can realize that,
02:39:42 have a chance at realizing that vision.
02:39:44 It’s amazing.
02:39:46 But when it comes to so many areas of our economy,
02:39:50 we can’t wait for a hero.
02:39:52 We have to have,
02:39:53 and there are way too many interests involved.
02:39:56 It’s who builds the roads.
02:39:58 I mean, the money that sloshes around on Capitol Hill
02:40:02 to decide what happens in these infrastructure bills
02:40:05 and the transportation bill is just obscene, right?
02:40:09 See, I think it’s an interesting view of markets.
02:40:12 Correct me if I’m wrong, let me propose a theory to you.
02:40:16 That progress in the world is made by heroes
02:40:22 and the markets remove the inefficiencies
02:40:24 from the work the heroes did.
02:40:26 So going to Mars from the perspective of markets
02:40:30 probably has no value.
02:40:32 Maybe you can argue it’s good for hiring
02:40:34 to have a vision or something like that,
02:40:35 but like those big projects
02:40:37 don’t seem to have an obvious value,
02:40:40 but our world progresses by those big leaps.
02:40:45 And then after the leaps are taken,
02:40:48 then the markets are very good
02:40:50 at removing sort of inefficiencies.
02:40:52 But it just feels like the autonomous vehicle space
02:40:55 and the autonomous trucking space requires leaps.
02:40:59 It doesn’t feel like we can sneak up into a good solution
02:41:03 that is ultimately good for labor,
02:41:05 like for human beings in the system.
02:41:07 It feels like some, like probably a bad example,
02:41:12 but like a Henry Ford type of character steps in
02:41:15 and say like, we need to do stuff completely differently.
02:41:20 Yeah, and you said we can’t hope for a hero,
02:41:24 but it’s like, no, but we can say we need a hero.
02:41:27 We need more heroes.
02:41:29 So if you’re a young kid right now listening to this,
02:41:31 we need you to be a hero.
02:41:33 It’s not like we need you to start a company
02:41:34 that makes a lot of money, no.
02:41:36 You need to start a company that makes a lot of money
02:41:38 so that you can feed your family
02:41:41 as you become a hero and take huge risks
02:41:43 and potentially go bankrupt.
02:41:45 Those risks is how we move society forward, I think.
02:41:49 Maybe that’s a romantic view, I don’t know.
02:41:51 I totally disagree.
02:41:52 You disagree, goddammit.
02:41:53 I mean, I…
02:41:54 And out of the two of us, you’re the knowledgeable one.
02:41:57 No, no.
02:41:58 No, no, I think it’s a matter of like,
02:42:01 do we need those heroes?
02:42:02 Absolutely.
02:42:04 I mean, I saw the boosters come down from space,
02:42:09 boosters come down from SpaceX’s rockets
02:42:12 and land nearly simultaneously with my kids
02:42:18 after school one day.
02:42:19 And I thought, oh my god,
02:42:21 like science fiction has been made real.
02:42:25 It’s incredible.
02:42:26 And it’s a pinnacle of human achievement, right?
02:42:29 It’s like, this is what we’re capable of.
02:42:32 But we need to have those heroes oriented.
02:42:37 We need to allow them to orient toward the goals, right?
02:42:42 We gotta…
02:42:43 Climate change, you know?
02:42:45 I mean, all the heroes out there, right?
02:42:48 I mean, it’s time.
02:42:50 The clock is ticking.
02:42:52 It’s past time.
02:42:53 I’ve been working on climate change issues
02:42:55 since the mid 90s.
02:42:59 I still remember the first time in 2010
02:43:04 when I got a grant that was completely focused
02:43:08 on adaptation rather than prevention.
02:43:12 And just when it hit me, that like, wow.
02:43:18 So adaptation versus prevention is like acceptance
02:43:22 that there’s going to be catastrophic impact.
02:43:25 We need to figure out how do we at least live with that.
02:43:28 Yeah.
02:43:29 And you know, the grant was like,
02:43:30 okay, our agriculture system is gonna move,
02:43:32 our breadbasket is no longer gonna be California,
02:43:34 it’s gonna be Illinois.
02:43:36 What does that mean for truck transportation?
02:43:38 So it’s like, so in terms of a big philosophical
02:43:42 societal level, that’s kind of like giving up.
02:43:44 Yeah.
02:43:45 In terms of the big heroic actions.
02:43:47 Yeah.
02:43:47 You know, failures in human history, yeah.
02:43:51 That’s gonna be, let’s hope not the biggest, but could be.
02:43:56 Do you…
02:43:57 So let me say why I disagree, right?
02:43:59 Henry Ford, amazing, right?
02:44:02 To sort of mass produce cars, right?
02:44:04 Daimler to put that first truck on the road
02:44:07 without the roads, right?
02:44:09 So there’s like, we need that innovation.
02:44:11 There’s no doubt about it.
02:44:12 And there are rules for that,
02:44:14 but there’s big public stuff that sets the stage.
02:44:19 It’s critical.
02:44:20 And you know, and what it really is,
02:44:22 it’s a sociological problem, right?
02:44:25 It’s a political problem.
02:44:26 It’s a social problem.
02:44:26 We have to say, and we have these screwed up ideas, right?
02:44:29 So we have this politics right now
02:44:31 where like everybody feels like they’re getting screwed
02:44:34 and someone undeserving is benefiting.
02:44:37 When in fact, like, you know, at least in the middle, right?
02:44:40 They’re huge.
02:44:41 I used to teach this course in rich and poor,
02:44:43 you know, in economic inequality.
02:44:45 And I would go through public housing subsidies
02:44:49 in Philadelphia, you know, section eight subsidies,
02:44:53 you know, and then I would go through my housing subsidies
02:44:57 for my mortgage interest deduction.
02:45:00 And it worked out to basically the average payment
02:45:02 for a section eight housing voucher in my neighborhood.
02:45:06 I’m not a welfare recipient
02:45:08 according to the dominant discourse.
02:45:10 And so we have this completely screwed up sense
02:45:13 of like where our dollars go and you know,
02:45:15 who benefits from the investment.
02:45:17 And you know, we need to, you know,
02:45:20 I don’t know that we can do it,
02:45:21 but you know, if we’re gonna survive,
02:45:24 we need to figure out how to have honest conversations
02:45:28 where private interest is where we need it to be
02:45:32 in fostering innovation and, you know,
02:45:35 and rewarding the people who do incredible things.
02:45:37 Please, you know, we don’t wanna squash that,
02:45:41 but we need to harness that power
02:45:42 to solve what I think are some pretty big,
02:45:45 you know, existential problems.
02:45:47 So you think there’s a like government level,
02:45:50 national level collaboration required
02:45:53 for infrastructure project.
02:45:54 Like there’s, we should really have large moonshot projects
02:46:01 that are funded by our governments.
02:46:04 At least guided by, I mean,
02:46:06 I think there are ways to finance them
02:46:08 and you know, other things,
02:46:08 but we gotta be careful, right?
02:46:10 Cause that’s where you get all these sort of perverse,
02:46:13 you know, unintended consequences and whatnot.
02:46:15 But if you look at transportation in the United States
02:46:18 and it is the foundation of the, you know,
02:46:21 manifest destiny, economic growth, right?
02:46:24 That built the United States into the world superpower
02:46:29 that it became and the industrial power that it became.
02:46:30 It rested on transportation, right?
02:46:33 It was like, you know, the Erie Canal,
02:46:35 I grew up a few miles from where they dug
02:46:38 the first shovel full of the Erie Canal
02:46:40 and everyone thought it was, you know, crazy, right?
02:46:44 But those public infrastructure projects,
02:46:46 the canals, right, the railroads, yeah,
02:46:49 they were privately built,
02:46:50 but they wouldn’t have been privately built without,
02:46:52 you know, Lincoln funding them essentially
02:46:55 and giving, you know, the railroads, you know, land
02:46:59 in exchange for building them.
02:47:01 The highway system, the Eisenhower,
02:47:03 the payback that the US economy got
02:47:06 from the Dwight D. Eisenhower interstate system
02:47:09 is phenomenal, right?
02:47:12 No private entity was gonna do that.
02:47:14 Electrification, dams, water, you know,
02:47:17 we need to do these infrastructure, infrastructure.
02:47:21 And now more than ever, it’s been really upsetting to me
02:47:24 on the COVID front.
02:47:27 There’s one of the solutions to COVID,
02:47:29 which seems obvious to me from the very beginning
02:47:32 that nobody’s opposed to.
02:47:34 It’s one of the only bipartisan things is at home testing,
02:47:39 rapid at home testing.
02:47:41 There’s no reason why at the government level,
02:47:45 we couldn’t manufacture hundreds of millions of tests
02:47:47 a month.
02:47:48 There’s no reason starting in May, 2020.
02:47:51 And that gives power to a country that values freedom,
02:47:55 that gives power information to each individual
02:47:57 to know whether they have COVID or not.
02:47:59 So it’s possible to manufacture them for under a dollar.
02:48:04 It’s like an obvious thing.
02:48:05 It’s kind of like the roads.
02:48:07 It’s like, everybody’s invested.
02:48:08 Let’s put countless tests in the hands
02:48:11 of every single American citizen,
02:48:13 maybe every citizen of the world.
02:48:16 The fact that we haven’t done that today
02:48:19 and there’s some regulation stuff with the FDA,
02:48:21 all the kind of dragging of feet,
02:48:24 but there’s not actually a good explanation
02:48:26 except our leaders and culturally,
02:48:31 we’ve lost the sort of, not lost,
02:48:35 but it’s a little bit dormant.
02:48:38 The will to do these big projects that better the world.
02:48:43 I still have the hope that when faced
02:48:45 with catastrophic events, the more dramatic,
02:48:51 the more damaging, the more painful they are,
02:48:53 the higher we will rise to meet those.
02:48:56 And that’s where the infrastructure style projects
02:48:58 are really important.
02:48:59 But it’s certainly a little bit challenging
02:49:03 to remain an optimist in the times of COVID
02:49:06 because the response of our leaders has not been as great
02:49:10 and as historic as I would have hoped.
02:49:14 I would hope that the actions of leaders
02:49:17 in the past few years in response to COVID
02:49:20 would be ones that are written in the history books.
02:49:23 And we talk about it as we talk about FDR,
02:49:25 but sadly, I don’t know.
02:49:27 I think the history books will forget
02:49:30 the actions of our leaders.
02:49:32 So let me just, to wrap up autonomy,
02:49:42 when you look into the future,
02:49:45 are you excited about automation in the space of trucking?
02:49:52 Is it, when you go to bed at night,
02:49:57 do you see a beautiful world in your vision
02:50:01 that involves autonomous trucks?
02:50:03 Like all of the truckers you’ve become close with,
02:50:07 you’ve talked to, do you see a better world for them
02:50:10 because of autonomous trucks?
02:50:13 Damn you, Alex.
02:50:15 You know why?
02:50:15 Because I mean, I want to be an optimist,
02:50:19 and I want to think of myself, I guess,
02:50:21 as a half glass bowl kind of person.
02:50:23 But when you ask it like that,
02:50:25 and I think about like,
02:50:27 when I look at the challenges to harnessing that for,
02:50:36 just let’s take just labor and climate, right?
02:50:40 There are other issues,
02:50:41 congestion, et cetera, infrastructure,
02:50:43 that are gonna be affected by this,
02:50:45 again, those big transformational issues.
02:50:50 I think it’s gonna take the best of us.
02:50:53 Like it’s gonna take the best of our policy approaches.
02:50:59 We need to start investing in building those,
02:51:03 rebuilding those institutions.
02:51:05 I mean, that’s what we’ve seen in the last four years, right?
02:51:07 And the erosion of that was so clear
02:51:11 among these truck drivers.
02:51:12 Like when Trump came in and said like,
02:51:17 free trades, good for workers, like, yeah, right.
02:51:20 I grew up in the Rust Belt.
02:51:23 I watched factory after factory close.
02:51:25 All of my ancestors worked at the same factory.
02:51:28 It’s still holding on by a thread.
02:51:30 Like, the Democratic Party told blue collar workers
02:51:35 for years, I don’t worry about free trade.
02:51:38 It’s not bad for you.
02:51:39 And I know the economists will probably
02:51:40 get in the comment box now.
02:51:44 We’ll look forward to your comments.
02:51:45 Look forward to your comments
02:51:46 about how free trade benefits everybody.
02:51:48 But, you know, immigration, you know, you go,
02:51:54 and I think immigration is great.
02:51:56 The United States benefits from it tremendously, right?
02:51:59 But there are costs, right?
02:52:01 Go down to South Philadelphia and find a drywaller
02:52:05 and tell him that immigration hasn’t hurt him, right?
02:52:08 You know, go to these places where there’s competition,
02:52:12 right?
02:52:13 And yes, we benefit overall,
02:52:15 but we have a system that allows some people
02:52:19 to pay really high costs.
02:52:21 And Trump tapped into that, you know?
02:52:24 And there was no, you know,
02:52:26 there’s more than that too, obviously.
02:52:28 And there’s lots of really dark stuff
02:52:30 that goes along with it, you know,
02:52:32 the sort of racialization of others and things like that.
02:52:35 But he hit on those core, you know, issues that, you know,
02:52:40 if you were to go back over my trucking interviews
02:52:42 for 15 years, you would have heard those stories
02:52:44 over and over and over again, that sense of voicelessness,
02:52:47 that sense of powerlessness,
02:52:49 that sense that there’s no difference
02:52:50 between the Democrats and the Republicans
02:52:52 because they’re all gonna screw us over.
02:52:54 And that was there, you know?
02:52:56 And you just ignore it as long as you want
02:52:58 and tell people, don’t worry, trade’s good for you.
02:53:00 Don’t worry, immigration’s good for you.
02:53:01 As their communities lose factories.
02:53:04 And I mean, a lot of them were lost to the South
02:53:05 before they were lost to overseas, whatever,
02:53:07 but tapped into that, you know?
02:53:10 And there’s a fundamental distrust of,
02:53:13 you know, you look at these like pupils on like,
02:53:16 you know, whether people trust the media, right?
02:53:17 But whether or not they trust higher education, you know,
02:53:21 these institutions that I find magical, right?
02:53:24 I mean, you look at the vaccine research and stuff,
02:53:27 that, you know, just, you know, brilliant, you know,
02:53:30 people doing incredible things for humanity.
02:53:33 Like, you know, the idea that like, you know,
02:53:36 we can take these viruses that, you know,
02:53:39 used to ravage through the human population
02:53:42 that we had to be terrified of.
02:53:44 And, you know, we’ve suffered, but, you know,
02:53:47 we have such power now to defend ourselves, right?
02:53:52 Behind these programs, right?
02:53:54 And to see those, people would be like,
02:53:56 eh, I’m not sure if higher education’s good
02:53:58 for the country or not, you know, it’s like,
02:54:00 where are we, you know?
02:54:02 So we need to rebuild the faith and trust
02:54:04 in those institutions and have these,
02:54:05 but we need to have honest conversations
02:54:07 before people are gonna buy it, you know?
02:54:09 Do you have ideas for rebuilding the trust
02:54:11 and giving a voice to the voices?
02:54:13 So is the, many of the things we’ve been talking about
02:54:18 is so sort of deeply integrated.
02:54:21 You think like, this is the trouble I have
02:54:24 with people that work on AI and autonomous vehicles
02:54:27 and so on, it’s not just a technology problem.
02:54:30 It’s this human pain problem.
02:54:36 It’s the robot essentially silencing the voice
02:54:39 of a human being because it’s lowering their wage,
02:54:43 making them suffer more and giving them no tools
02:54:46 of how to escape that suffering.
02:54:48 Is there something, I mean, it even gets
02:54:53 into the question of meaning, you know?
02:54:55 So if money is one thing, but it’s also
02:54:59 what makes us happy in life.
02:55:01 You know, a lot of those truckers,
02:55:06 the set of jobs they’ve had in their life
02:55:08 were defining to them as human beings.
02:55:12 And so, and the question with automation
02:55:14 is not just how do we have a job that gives you money
02:55:21 to feed your family, but also a job that gives you meaning,
02:55:24 that gives you pride.
02:55:26 Yeah.
02:55:27 And for me, the hope is that AI and automation
02:55:32 will provide other jobs that will be a source of meaning.
02:55:43 But coupled with that hope is that there will not
02:55:47 be too much suffering in the transition.
02:55:49 And that’s not obvious from the people you’ve spoken with.
02:55:53 I mean, I think we need to differentiate
02:55:55 between the effects of technology
02:55:57 and the effects of capitalism, right?
02:55:58 And they are, you know, the fact that workers
02:56:02 don’t have a lot of power, right, in the system matters.
02:56:06 Now, we had a system, right?
02:56:08 And that’s why I would say, you know,
02:56:09 go to that, you know, Harry Bridges report.
02:56:12 And, you know, those were workers who had a sense of power.
02:56:16 They said, you know what, we can demand
02:56:18 some of the benefits, like, yeah, automate our jobs away,
02:56:21 but, you know, kick a little down to us, right?
02:56:24 And we had, in the golden era of American industrialism
02:56:28 in post World War II, that was the contract.
02:56:32 The contract was employers can do what they want
02:56:35 in automation and all these things.
02:56:37 Yeah, sure, there’s some union rules
02:56:38 that make things less efficient in places,
02:56:40 but the key compromise is tie wages to productivity.
02:56:45 That’s what we did.
02:56:46 We tied, that’s what unions did.
02:56:47 They tied wages to productivity, kept demand up, right?
02:56:50 It was good for the economy, some economists think, right?
02:56:54 And that’s what, you know, we need to,
02:56:57 I think we need to acknowledge that.
02:56:59 We need to acknowledge the fact
02:57:02 that it’s not just technology,
02:57:04 it’s technology in a social context
02:57:08 in which some people have a lot of power
02:57:10 to determine what happens.
02:57:12 For me, I don’t have all the answers,
02:57:14 but I know what my answer is.
02:57:15 And my answer is, and I think I started with this, you know,
02:57:19 I can learn from every single person, you know?
02:57:24 Did I have to talk to the 200th truck driver?
02:57:27 In my opinion, yes, because I was gonna learn something
02:57:31 from that 200th truck driver.
02:57:33 Now, people with more power might talk to none,
02:57:39 or they might talk to five and say, okay, I got it.
02:57:41 You know, people are amazing
02:57:47 and every one of them has a life experience
02:57:49 and concerns and, you know, can teach us something.
02:57:53 And they’re not in the conversation, you know?
02:57:57 And I know this because I’m the expert, you know?
02:58:00 So I get pulled in to these conversations
02:58:02 and people wanna know, you know,
02:58:04 what’s gonna happen to labor, you know?
02:58:06 It’s like, well, so I try to be a sounding board
02:58:10 and I feel a tremendous weight of responsibility,
02:58:14 you know, for that.
02:58:16 So, but I’m not those workers, you know?
02:58:21 And they may listen to this or, you know,
02:58:24 walk in the door sometime, it’s about to be like,
02:58:27 that guy’s full of shit, that’s not what I think at all.
02:58:29 You know?
02:58:31 And they don’t get heard over and over and over.
02:58:34 But in a small way, you are providing a voice to them
02:58:36 and that’s kind of the, if at scale,
02:58:40 we apply that empathy and listening,
02:58:43 that we could provide the voice to the voiceless
02:58:46 through our votes, through our money, through,
02:58:47 I mean, that’s one way to make capitalism work
02:58:50 at not making the powerless more powerless,
02:58:56 is by all of us being a community
02:58:58 that listens to the pain of others
02:58:59 and tries to minimize that,
02:59:01 to try to give a voice to the voiceless,
02:59:03 to give power to the powerless.
02:59:05 I have to ask you on, by way of advice,
02:59:09 young people, high school students, college students,
02:59:12 entering this world full of automation,
02:59:17 full of these complex labor markets and markets period,
02:59:23 what would you, what kind of advice would you give
02:59:25 to that person about how to have a career?
02:59:28 How to have a life they can be proud of?
02:59:32 Yeah, I think, you know, this is such a great question.
02:59:35 I don’t, it’s okay to quote Steve Jobs, right?
02:59:42 Always.
02:59:45 Yeah, I mean, so, and I just heard this recently.
02:59:49 It was a commencement speech that he gave
02:59:51 and I can’t remember where it was.
02:59:53 And he was talking about, you know,
02:59:55 he had famously dropped out of school,
02:59:56 but continued to take classes, right?
02:59:59 And he took a calligraphy class
03:00:02 that influenced the design of the Mac and sort of fonts.
03:00:06 And, you know, just was something that he had no,
03:00:09 you know, sense of what it was gonna be useful for.
03:00:11 And his lesson was, you know,
03:00:13 you can’t connect the dots looking forward.
03:00:16 You know, looking back, you can see all the pieces
03:00:19 that sort of led you to where you ended up.
03:00:22 And for me, studying truck driving,
03:00:24 like, I mean, I literally went to graduate school
03:00:27 because I was worried about climate change.
03:00:28 And like, you know, I had a whole other dissertation plan
03:00:31 and then was like driving home.
03:00:32 And like, I had read about all this management literature
03:00:35 and sort of like how you get workers to work hard
03:00:37 for my qualifying exams.
03:00:39 And then read a popular article
03:00:41 on satellite linked computers.
03:00:44 And the story in the literature was,
03:00:45 you know, a sense of autonomy.
03:00:47 And I was like, well,
03:00:48 that monitoring must affect the sense of autonomy.
03:00:51 And it’s just this question that I found interesting.
03:00:54 And it never in a million years
03:00:55 that I ever thought I was gonna like study, you know,
03:00:57 spend 15 years of my life studying truck driving.
03:01:02 And it was like, if you were to map out a career path
03:01:07 in academia or research, like, you know,
03:01:10 you would do none of the things that I did
03:01:14 that many people advise me against.
03:01:15 Where like, you can’t like go spend a year
03:01:17 working as a truck driver, you know, like that’s crazy.
03:01:20 Or, you know, you can’t, you know, spend all this time
03:01:23 trying to write like one huge book and, you know.
03:01:26 But by the way, if I could just interrupt,
03:01:28 what was the fire that got you to take the leap
03:01:32 and go and work as a truck driver
03:01:34 and go interview truck drivers?
03:01:36 This is what a lot of people would be incapable of doing,
03:01:39 just took that leap.
03:01:41 What the heck is up with your mind
03:01:43 that allowed you to take that big leap?
03:01:46 So I think it’s probably like Tolkien.
03:01:50 And Lord of the Rings, you know.
03:01:51 I mean, I think as a teenager, you know,
03:01:54 I sort of adopted some sense of needing to, you know,
03:01:58 heroically go out in the world and, you know,
03:02:01 which I’ve done at various points in my life
03:02:03 and like looking back in absolutely stupid ways
03:02:07 that, you know, where I could have completely,
03:02:08 I ended up dead and traumatized my family,
03:02:11 including like, I took a couple week trip in the Pacific,
03:02:14 like a solo trip on a kayak.
03:02:16 And basically my kayak experience up till that, you know,
03:02:19 point had been, you know, on a fairly calm lake
03:02:21 and like class one rapids on a river.
03:02:22 Solo trip on a kayak in the Pacific.
03:02:24 Yeah, yeah.
03:02:25 So I was working on forestry issues
03:02:28 and we were starting a campaign
03:02:30 up in really remote British Columbia.
03:02:33 And I was like, okay, if I’m gonna work on this,
03:02:35 I’ve got to actually go there myself
03:02:36 and see what this is all about
03:02:38 and see whether it’s worth like devoting my sort of,
03:02:40 you know, life right now too.
03:02:42 And just drove up there with this kayak
03:02:45 and, you know, put into the Pacific and it was insane.
03:02:49 You know, like the tides are huge
03:02:52 and, you know, there was one point
03:02:54 in which I was going down a fjord
03:02:56 and two fjords kind of came up and there was a cross channel
03:03:00 and I had hit the timing completely wrong
03:03:03 and the tide was sort of rushing up like, you know,
03:03:05 rivers in these, you know, two fjords
03:03:08 and then coming through this cross channel and met
03:03:11 and created this giant standing wave
03:03:14 that I had to paddle through.
03:03:16 And now actually very recently,
03:03:18 I’ve gone out on whitewater with some people
03:03:20 who know what the hell they’re doing
03:03:21 and I realized like just how absolutely stupid
03:03:26 and, you know, ill fit I was,
03:03:28 but that’s just, I think I’ve always had that.
03:03:31 Were you afraid when you had that wave before you?
03:03:33 That wave scared the shit out of me, yeah.
03:03:35 Okay, what about taking a leap and becoming a trucker?
03:03:39 Yeah, there was some nervousness for sure.
03:03:41 I mean, and, you know, I guess my advantage
03:03:44 as an ethnographer is I grew up in a blue collar environment.
03:03:48 You know, again, all my ancestors were factory workers.
03:03:52 So I can move through spaces.
03:03:56 I’m really, I feel, I can become comfortable
03:04:01 in lots and lots of places, you know, not everywhere,
03:04:03 but, you know, along class lines for sort of white,
03:04:07 you know, even white ethnic workers,
03:04:09 like that’s, you know,
03:04:10 I can move in those spaces fairly easily.
03:04:13 I mean, not entirely, there was one time
03:04:16 where I was like, okay, you know,
03:04:17 and I grew up around people who worked on cars.
03:04:19 I’d been to drag races in NASCAR
03:04:21 and I’d been to, you know, Colgate University.
03:04:24 And so I’d, and I think that was probably
03:04:26 my initial training was, you know,
03:04:28 being this just working class kid who ends up in this,
03:04:32 you know, sort of blue blood, small liberal arts college
03:04:36 and just feeling like, you know,
03:04:39 both having the entire world opened up to me,
03:04:41 like philosophy and Buddhism
03:04:43 and things that I had never heard of, you know,
03:04:46 and just became totally obsessed with
03:04:48 and just like, you know, just following my interests.
03:04:52 But also culturally perhaps didn’t feel like you fit in.
03:04:55 Feeling like just a fish out of water.
03:04:57 I just, you know, but, and at the same time
03:04:59 that sort of drove me in the sense
03:05:02 that it drove an opening of my mind
03:05:04 because I couldn’t understand it.
03:05:06 You know, I was like, I didn’t know that this world existed.
03:05:09 I don’t understand.
03:05:11 And I think maybe that’s where my real first step
03:05:14 in trying to understand other people
03:05:17 because they were my friends, you know?
03:05:18 I mean, they were my teammates.
03:05:19 I played lacrosse in college.
03:05:21 So like, you know, I was close to people
03:05:22 who came from such different backgrounds than I did.
03:05:25 And I just, I was so confused, you know?
03:05:29 And so I think I learned to learn
03:05:31 and then, you know, sort of went from there.
03:05:34 And then develop your fascination with people.
03:05:36 And the funny thing is you went from trucking now
03:05:38 to autonomous trucks.
03:05:40 I mean, this is speaking of not being able
03:05:41 to connect the dots and, you know,
03:05:44 your life in the next 10 years
03:05:46 could take very interesting directions
03:05:48 that are very difficult to,
03:05:50 first of all, us meeting is a funny little thing
03:05:53 given the things I’m working on with robots currently.
03:05:57 But, you know, it may not relate to trucks at all.
03:06:00 There’s a, at a certain point,
03:06:03 autonomous trucks are just robots.
03:06:06 And then it starts getting into a conversation
03:06:08 about the roles of robots in society.
03:06:11 Yeah, and the roles of humans and robots.
03:06:15 And that interplay is right up your alley.
03:06:19 Yeah.
03:06:20 As somebody who deeply cares about humans
03:06:21 and have somehow found themselves studying robots.
03:06:25 Yeah, no, it’s crazy.
03:06:26 I mean, even four or five years ago,
03:06:28 I would, if you had asked me
03:06:30 if I was gonna be studying trucking still,
03:06:32 I would have said no.
03:06:33 And so my advice is, I think if I was gonna give advice,
03:06:36 you know, is, you know,
03:06:38 you can’t connect the dots looking forward.
03:06:40 You just gotta follow what interests you, you know?
03:06:43 And I think we downplay, right,
03:06:47 that when we talk to, you know, kids,
03:06:50 especially, you know, if you have some bright gifted kid
03:06:52 that gets identified as like, oh, you could go somewhere.
03:06:54 Then we’re like, we feed them stuff.
03:06:55 You’re like, we’ll learn the piano
03:06:57 and learn another language, right?
03:06:58 Or learn robotics.
03:07:00 And then we tell other kids like,
03:07:02 oh, learn a trade, you know,
03:07:04 like figure out what’s gonna pay well.
03:07:05 And not that there’s anything against trades.
03:07:06 I think everyone should learn like manual skills
03:07:10 to make things.
03:07:10 I think it’s incredibly satisfying and wonderful,
03:07:13 and we need more of that.
03:07:15 But also, you know, tell, you know, all kids,
03:07:18 it’s okay to like take a class in something random
03:07:20 that you don’t think you’re gonna get
03:07:22 any economic return on.
03:07:23 Well, because maybe you will end up going into a trade,
03:07:26 but that class that you took in studio art
03:07:30 is gonna mean that, you know,
03:07:31 you look at buildings differently, right?
03:07:33 Or you end up sort of putting your own stamp on,
03:07:36 you know, woodworking, you know?
03:07:38 It just, I think that’s the key is like,
03:07:40 follow, you know, it’s cheesy
03:07:43 because everybody says, follow your passion.
03:07:44 But you know, we say that, and then we just, you know,
03:07:48 the 90% of what people hear is, you know,
03:07:51 what’s the return on investment for that, you know?
03:07:54 It’s like, you’re a human being.
03:07:55 Like things interest you, music interests you,
03:07:58 literature interests you, video games interests you,
03:08:00 like follow it, you know?
03:08:02 Go grab a kayak and go into the pool.
03:08:04 Go do something really, no, don’t do that.
03:08:07 Go do something stupid and something you’ll regret
03:08:10 a lot later.
03:08:11 My poor mother, thank God she didn’t know.
03:08:13 Well, let me ask, because for a lot of people work,
03:08:16 for me it is, quote unquote, work is a source of meaning.
03:08:20 And at the core of something we’ve been talking about
03:08:24 with jobs is meaning.
03:08:27 So the big ridiculous question,
03:08:28 what do you think is the meaning of life?
03:08:31 Do you think work for us humans in modern society
03:08:36 is as core to that meaning?
03:08:38 Is that something you think about in your work?
03:08:42 So the deeper question of meaning,
03:08:43 not just financial wellbeing and the quality of life,
03:08:46 but the deeper search for meaning.
03:08:50 Yeah, the meaning of life is love
03:08:53 and you can find love in your work.
03:08:57 Now, and I don’t think everybody can.
03:09:00 There are a lot of jobs out there that just, you know,
03:09:02 you do it for a paycheck.
03:09:04 And I think we do have to be honest about that.
03:09:08 There are a lot of people who don’t love their jobs
03:09:11 and we don’t have jobs that they’re gonna love.
03:09:15 And maybe that’s not a sort of realistic,
03:09:18 that’s a utopia, right?
03:09:20 But for those of us that have the luxury,
03:09:23 I mean, I think you love what you do that people say that.
03:09:28 I think the key for real happiness
03:09:34 is to love what you’re trying to achieve
03:09:36 and maybe love trying to build a company
03:09:39 and make a lot of money just for the sake of doing that.
03:09:41 But I think the people who are really happy
03:09:44 and have great impacts, they love what they do
03:09:47 because it has an impact on the world
03:09:49 that they think is, it expresses that love, right?
03:09:52 And that could be at a counseling center,
03:09:56 that could be in your community,
03:09:59 that could be sending people to Mars, you know.
03:10:03 Well, I also think it doesn’t necessarily,
03:10:05 the expression of love isn’t necessary
03:10:06 about helping other people directly.
03:10:09 There’s something about craftsmanship and skill
03:10:11 as we’ve talked about,
03:10:12 that’s almost like you’re celebrating humanity
03:10:15 by like searching for mastery in the task,
03:10:21 in the simple, like, especially tasks that people outside me
03:10:25 see as menial, as not important.
03:10:30 Nevertheless, searching for mastery,
03:10:33 for excellence in that task.
03:10:34 There’s something deeply human to that
03:10:36 and also fulfilling that just like driving a truck
03:10:40 and getting damn good at it.
03:10:42 Like, you know, the best who’s ever lived
03:10:45 and driving the truck and taking pride in that,
03:10:48 that’s deeply meaningful.
03:10:50 And also like a real celebration of humanity
03:10:55 and a real show of love, I think, for humanity.
03:10:59 Yeah.
03:11:00 Yeah, I just had my floors redone
03:11:01 and the guy who did it was an artist.
03:11:04 You know, he sanded these old 100 year old floors
03:11:06 and made them look gorgeous and this is craft.
03:11:08 That’s love right there.
03:11:10 Yeah, I mean, he showed us some love.
03:11:12 The product was just like, is enriching our lives.
03:11:17 Steve, this was an amazing conversation.
03:11:19 We’ve covered a lot of ground, your work,
03:11:21 just like you said, impossible to connect the dots,
03:11:24 but I’m glad you did all the amazing work you did.
03:11:28 You’re exploring human nature at the core
03:11:31 of what America is, the blue collar America.
03:11:35 So thank you for your work.
03:11:36 Thank you for the care and the love you put in your work.
03:11:38 And thank you so much for spending
03:11:40 your valuable time with me.
03:11:42 I appreciate it, Lex.
03:11:43 I’m a big fan, so it’s just been great to be on.
03:11:47 Thanks for listening to this conversation
03:11:49 with Steve Vasile.
03:11:50 To support this podcast,
03:11:52 please check out our sponsors in the description.
03:11:54 And now let me leave you with some words
03:11:56 from Napoleon Hill.
03:11:58 If you cannot do great things,
03:12:00 do small things in a great way.
03:12:03 Thank you for listening and hope to see you next time.