Lex Fridman Podcast - #237 – Steve Viscelli: Trucking and the Decline of the American Dream
Episode Date: November 4, 2021Steve Viscelli is a former truck driver and now an economic sociologist at University of Pennsylvania studying freight transportation, including autonomous trucks. Please support this podcast by check...ing out our sponsors: - Shopify: https://shopify.com/lex to get 14-day free trial - ROKA: https://roka.com/ and use code LEX to get 20% off your first order - Sunbasket: https://sunbasket.com/lex and use code LEX to get $35 off - Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium - BetterHelp: https://betterhelp.com/lex to get 10% off EPISODE LINKS: Steve's Website: https://www.steveviscelli.com/ Big Rig (book): https://amzn.to/3EbaofP Will Robotic Trucks Be "Sweatshops on Wheels?" (article): https://bit.ly/3vGGgpO Johnny Cash - All I Do Is Drive (song): https://www.youtube.com/watch?v=DEHoagHlqrE Steve's Penn Gazette Interview: https://bit.ly/3nkRPyV More Information on Automated Trucking: http://www.driverlessreport.org/ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (07:36) - Ethnography (19:49) - Challenges of driving a truck (38:28) - Trucking industry: State of affairs (1:11:33) - Future of autonomous trucks (1:37:49) - Solving the automated truck dilemma (2:09:44) - Role of society in automated trucking (2:36:53) - Tesla and revolutionizing the trucking industry (2:56:33) - Hope and final thoughts
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The following is a conversation with Steve Vaseli, formerly a truck driver and now a sociologist
at the University of Pennsylvania, whose studies freight transportation.
His first book, The Big Rig, trucking in a decline of the American dream explains how long
haul trucking went from being one of the best blue collar jobs to one of the toughest.
His current ongoing book project, Driverless, Autonomous Trucks, and the future of the toughest. His current ongoing book project, Driverless,
Autonomous Trucks, and the future of the American Trucker, explores self-driving trucks and
their potential impacts on labor and on society. And now a quick few seconds summary of the sponsors.
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This is the Lex Friedman Podcast, and here is my conversation with Steve Vassali. You wrote a book about trucking called The Big Rig Trucking in the Decline of the American
Dream and you're currently working on a book about autonomous
trucking called Driverless, autonomous trucks in the future of the American trucker. I have to bring
up some Johnny Cash to you because I was just listening to this song. He has a ton of songs about
trucking, but one of them I was just listening to is called All I Do Is Drive drive where he's talking to an old truck driver. It goes I
Asked them if those trucking songs tell a bottle life like his he said if you want to know the truth about it
Here's the way it is all I do is drive drive drive
Try to stay alive. That's the course and keep my mind on my load keep my eye upon the road
I got nothing in common with any man whose home every day at five all I do is drive drive drive
Drive drive drive drive drive
So I got to ask you
Same thing that he asked the trucker you worked as a trucker for six months and and now while working on the previous book
What's it like to be a truck driver?
I think that captures it.
It really does.
Can you take me through the whole experience,
what it takes to become a trucker,
what actual day-to-day life was on day one, week one,
and then over time how that changed?
Yeah.
Well, the book is really about how that changed over time. So my experience,
and I'm an ethnographer, right? So I go in, I live with people, I work with people, I talk to them,
try to understand, you know, their world. Ethnographer, by the way, what is it? The science and art of capturing a
The spirit of a people. Yeah, life ways, you know, I think that would be a good way to capture it, you know, try to understand
What makes them unique um as a as a society
Maybe as a subculture, right what and it makes them tick that might be different than the way you and I are
sort of wired and to are sort of wired.
And really sort of thickly describe it, would be at least one component of it.
That's sort of the basic essential.
And then for me, I want to, you know, exercise what C-Write Mills called the Sociological Imagination,
which is to, you know, put that individual biography into the long historical sweep of
humanity, if at all possible.
My goals are typically more modest than see-right mills, and to then put that biography in the
larger social structure, to try to understand that person's life and the way they see the world,
their decisions in light of their interests, their relative to others and conflict and power
and all these things that I find interesting.
In a context of society and in the context of history.
Yeah.
And a small tangent, what does it take to do that to capture this particular group, the spirit, the music, the full landscape of experiences
that a particular group goes through in the context of everything else.
You only have limited amount of time and you come to the table probably with preconceived
notions that are then quickly destroyed all that whole process.
So I don't know if it's more art or science, but what does it take to be great at this?
I do think the, my first book was a success, you know, relative to my goals of trying to really, you know,
get at the heart of, of sort of the central issues and, and the lives being led by people. If I have a,
If I have a resource, a talent, it's that I'm a good listener.
I can talk with anybody.
My wife's loves to remark on this that I can sit down with anyone.
I think I learned that from my dad who worked at a factory and actually had a lot of truckers go through the gate that he operated.
And he always had a story, you know, a joke for everybody kind of got to know everyone individually.
And he just kind of taught me that like essentially everyone has something to teach you.
And I try to embody that.
Like that's the rule is for me is every single person I interact with can teach me something.
I gotta ask you, I'm sorry to interrupt because I'm clearly of the two of us, the poor listener.
I think you're a great listener.
Thank you.
I've been listening to the podcast.
I think you're a great listener.
I really appreciate that.
You've done a large number of interviews, like you said, of truckers for this book.
I'm just curious, what are some lessons you've learned about what it takes to listen to
a person enough, maybe guide the conversation enough to get to the core of the person, the
idea, again, the ethnographer goal to get to the core.
Yeah, I think it doesn't happen in the moment, right?
So I'm a ruminator.
I just sit with the data for years.
I sat with the trucking data for almost 10 full years
and just thought about the problems and the questions using everything
that I possibly could.
And so in the moment, my ideal interview is, I open up and I say, tell me about your life
as a trucker and they never shut up and they keep telling me the things that I'm interested
in.
Now, it never works out that way because they don't know what you're interested in. Right? And so it's a lot of it is the, as you know, as a, I think,
you're a great interviewer, you know, prep, right? I mean, so you try to get to know a little bit
about the person and sort of understand, you know, kind of the central questions you're interested in
that they can help you explore. And so, I've done hundreds of interviews with truck drivers at this point and I should
really go back and read the original ones.
They're probably terrible.
What's the process like?
You're sitting down, do you have an audio recorder and also taking notes or do you
do no audio recording?
Just notes, or?
Yeah, audio recorder and social scientists always have to struggle with sampling right like who do you interview where do you find them
how do you recruit them I just happen to have a sort of natural place to go
that gave me essentially the population that I was interested in you know so
all these long haul truck drivers that I was interested in they have to stop
and get fuel and get services at truck stops. So I picked a truck stop at the juncture
of a couple major interstates, went into the lounge
that drivers have to walk through with my clipboard
and everybody who came through, I said,
hey, are you on break?
That was sort of the first criteria was,
do you have time, right?
And if they said yes, I said, you know, I'd say,
I'm a graduate student at Indiana University,
I'm doing a study, I'm trying to understand more
about truck drivers, you know, will you sit down with me?
And I think the first, I think I probably asked like
104 or 103 people to get the first 100 interviews.
That was pretty good odds.
It's amazing, right?
Wow.
For any response rate like that,
for I mean, these are people who sat down and gave me
an hour or sometimes more of their time,
just randomly at a truck stop.
And it just tells you something about,
like, truckers have something to say.
They're alone a lot.
And so I had to figure out how to kind of turn the spiket on, you know.
And I got pretty good at it, I think, yeah.
So they have good stories to tell
and they have an active life in the mind
because they spend so much time on the road just basically thinking.
Yeah. There's a lot of reflection,
a lot of struggles, you know.
And they take different forms, you know, one of the
things that they talk about is the impact on their families.
They say truckers have the same rate of divorce as everybody else, and that's because trucking
saves so many marriages because you're not around and ruin so many.
And so it ends up being a wash.
So you know, I had this experience.
I met another person and he recognized me from a podcast.
And he said, you know, I'm a fan of yours and a fan of Joe Rogan.
But you guys never talk.
You always talk to people with no bull prizes.
You always talk to these kind of people.
You never talk to us regular folk.
And that guy really stuck with me.
First of all, the idea of regular folk is a silly notion.
I think people that win Nobel Prizes
are often more boring than the people of these regular folks
in terms of stories, in terms of richness of experience,
in terms of the ups and downs of life.
And that really stuck with me,
because I said that as a goal for myself to make sure I
talk to regular folk.
And you did just this talking, again, regular folk, it's human beings, all of them have experiences.
If you were to recommend to talk to, to talk some of these folks with stories, how would
you find them?
Yeah, so I do do this sometimes for journalists who, you know, will come and they want to
write about sort of what's happening right now in trucking, you know.
And I send them to truck stops, you know, I say, you know, yeah, there's a town called
Effingham, Illinois.
And it's just this place where you know,
a bunch of huge truck stops, tons of trucks, and really nothing else out there. You know, it's in the
middle of corn country. And you know, again, truckers in this, you know, sadly, I think you
know, the politics of the day, it's changing a little bit. I think there's a little, the polarization is getting to the
trucking industry in ways that, you know, maybe we're seeing in other parts of our social world.
But truckers are generally, you know, real open, sort of friendly folks. Now, some of them
ultimately like to work alone and be alone. That's a relatively small subset, I think,
but all of them are generally kind of open, you know, trusting willing to have a conversation.
And so, you go to the truck stop and you go in the lounge and there's usually a booth
down there and somebody's sitting at their laptop around their phone and will indistricate
up a conversation. You should try that. You should
know that 100% will try this. Just again, we're just going
from tangent to tangent, we'll return to the main question.
But what do they listen to? Do they listen to talk radio?
Do they listen to podcasts, audio books? Do they listen
to music? Do they listen to silence? Everything.
Everything. Everything. Everything.
I mean, and some still listen to the CB, which, you know, it's a, it's a ever dwindling
group.
They'll call it the original internet, Citizens Band, you know, they, they, back in the 70s,
they thought it was going to be the, the medium of democracy.
And they love to just get on there and, you know, cruise along, one truck after the other
and chat away.
Usually, guys who know each other from the same company are happy to run into each other.
But other than that, it's everything under the sun.
And that's probably one of the stereotypes.
And it's, I think it was more true in the past about the sort of heterogeneity of truck
drivers.
They're a really diverse group now.
There's definitely a still a large component
of rural white guys who work in the industry,
but there's a huge growing chunk of the industry
that's immigrants, people of color,
and even some women, still huge barriers
to women entering it, but it's a much more diverse place than most
people think.
So let's return to your journey as a truck driver.
What did it take to become a truck driver?
What were the early days like?
Yeah, so this is, I mean, this is a central part of the
story, right, that I uncovered.
And the good part was that I went in without knowing what was gonna happen.
So I was able to experience it as a new truck driver would.
So one of the important stories in the book is how
that experience is constructed by employers to sort of
help you think of the way that they would like you to think
about the job and about the industry
and about the social relations of it.
It's super intimidating.
I say in the book, you know, pretty handy guy, you know, familiar with tools, machines,
like, you know, comfortable operating stuff, like from time I was a kid, the truck was
just like a whole nother experience.
I mean, as I think most people think about it, it's this big, huge vehicle, right?
It's really long, it's 70 feet long,
it can weigh 80,000 pounds.
You know, it does not stop like a car,
it does not turn like a car.
But at least when I started,
and this is changing, it's part of the technology story
of trucking.
The first thing you had to do was learn how to shift it.
And it doesn't shift like a manual car.
The clutch isn't synchronized.
So you have to, what's called double clutch.
And it's basically the foundational skill
that a truck driver used to have to learn.
So you would, you know, accelerate,, say you're in first gear,
you push in the clutch, you pull the shifter out of first gear,
you let the clutch out, and then you let the RPMs
of the engine drop an exact amount,
then you push the clutch back in,
and you put it in second gear.
If your timing is off, those gears aren't going to go together.
And so if you're in an intersection,
you're just going to get this horrible grinding sound
as you coast to a dead stop underneath the stoplight
or whatever it is.
So the first thing you have to do is learn to shift it.
And so at least for me and a lot of drivers
who are going to private company, CDL schools,
what happens is it's
kind of like a boot camp. They ship me three states away from home, send you a bus ticket
and say, hey, we'll put you up for two weeks. You sit in a classroom, you sort of learn
the theory of shifting the theory of how you fill out your logbook, rules of the road,
you know, and do that maybe half the day. And then the other half, you're in this giant parking lot with one of these old trucks
and just like, you know, destroy what's left of the thing.
You know, and it's lurching and belching smoke and just making horrible noises and like
rattling. I mean, in these things, like, there's a lot of torque. And so if you do manage to
get it into gear, but the engine's lugging, I mean, it can throw you right out of the seat, right?
So it's like, you know, it's bull,
you're trying to ride, and it's super intimidating.
And the thing about it is that for everybody there,
it's almost everybody there, it's super high stakes.
So trucking has become a job of last resort
for a lot of people.
And so they, you know, they become a job of last resort for a lot of people. And so they lose a job in manufacturing.
They get too old to do construction any longer, right?
The knees can no longer handle it.
They get replaced by a machine, their job gets off short.
And they end up going to trucking
because it's a place where they can maintain their income.
And so it's super high stress.
Like, they've left their family behind.
Maybe they quit another job.
They're typically being charged a lot of money.
So that first couple of weeks, like, you might get charged $8,000 by the company that you
have to pay back if you don't get hired.
And so the stakes are high.
And this machine is huge and it's intimidating.
And so it's super stressful.
I mean, I watched, you know, men, grown men break down crying about like how they couldn't
go home and tell their son that they had been telling they were going to, you know, go
become a long-haul truck driver that they'd failed.
And it's kind of this super high-stress system.
It's designed that way partly because as one of my trainers later told me, it's basically
a two- week job interview.
Like they're testing you.
They're seeing like, you know, how's this person going to respond when it's tough, you
know, when they have to do the right thing and it's slow and, you know, they need to learn
something, are they going to rush, you know, or are they going to kind of stay calm, figure
it out, you know, nose to the grindstone because when you're in a truck driver, you're on supervised.
And that's what they're really looking for is that kind of quality of conscientious work
that's going to carry through to the job.
So the truck is such an imposing part of a traffic scenario.
So you said like turning, it stresses me out every time I look at a truck.
Because the geometry of the problem is so tricky.
And so if you combine the fact that they have to,
like everybody, basically all the cars in the scene
are staring at the truck and they're waiting,
often in frustration.
And in that mode, you have to then shift gears perfectly
and move perfectly.
And when you're new especially,
I give a probably for somebody like me,
it feels like it would take years to become calm and comfortable in that situation.
As opposed to be exceptionally stressed under the eyes of the road. Everybody looking and you waiting for you.
Is that the psychological pressure of that? Is that something that was really difficult. Yeah, absolutely. Again, just I saw people freeze up, you know, in
that intersection as, you know, horns are blaring and the trucks grinding, you know, gears,
and you just can't, you know, and they just shut down. They're like, this isn't for me.
I can't do it. You're right. It takes years. If, you know, trucking is not considered
a skilled occupation, but, you know, my six months there. And I was pretty good-rookie, but when I finished,
I was still a rookie, even shifting, definitely backing,
tight corners and situations.
I could drive competently, but the difference between me
and someone who had two, three years of experience
was a giant gulf between us. and between that and the really skilled drivers
who've been doing it for 20 years, you know, is still another step beyond that. So it is highly
skilled. Would it be fair to break trucking into the task of truck of driving a truck,
did two categories. One is like the local stuff getting out of the parking lot, getting into, you know,
driving down local streets and then highway driving, those two tasks. What are the challenges
associated with each task? You kind of emphasize the first one. What about the actual like
long haul highway driving? Yeah, so I mean, they are very different, right? And the key with the long haul driving
is really a set of, the way I came to understand it,
was a set of habits, right?
We have a sense of driving, particularly men,
I think, have a sense of driving as like being really skilled
as like the goal and you can kind of maneuver yourself out of,
in and out of tight spaces with great speed
and breaking and acceleration.
You know, for a really good truck driver,
it's about understanding traffic and traffic patterns
and making good decisions so you never have to use those skills.
And the really good drivers,
you know, the mantra is always leave yourself and out.
Right? So always have that safe place
that you can put that truck in case
that four wheeler in front of you
who's texting, loses control.
You know, what are you gonna do in that situation?
And what really good truck drivers do on the highway is they just keep
themselves out of those situations entirely.
They see it, they slow down, they avoid it.
And then the local driving is really something that takes just practice and routine to learn.
This quarter turn, it feels like the back of the
truck sometimes is on delay when you're backing it up. So it's like, all right, I'm going
to do a quarter turn of the wheel now, and to get the effect that I want, like five
seconds from now, and where that tail of that trailer is going to be. And there's just
no, I mean, some people have a natural talent for that, you know, spatial visualization
and kind of calculating those angles and everything,
but there's really no escaping the fact that you've got to just do it over and over again before you're going to learn how to do it well.
Do you mind sharing how much you were getting paid?
How much you were making as a truck driver in your time as a truck driver?
Yeah, I started out at 25 cents a mile,
and then I got bumped up to 26 cents a mile.
So we had a minimum pay, which was sort of a new pay scheme
that the industry had started to introduce to,
because there's lots of unpaid work and time.
And so we had a minimum pay of $500 a week
that you would get if you didn't drive enough miles
to exceed that.
You get paid in sort of,
so you get paid when you turn the bills in,
which is the paperwork that goes with the load.
So you have to get that back to your company
and then that's how they build a customer.
And so you might get a bunch of those bills
that kind of bunch up in one week.
So, you know, I might get a paycheck for, you know, $1,200.
And I mean, I was a poor graduate student.
So this was real, real money to me.
And so I had this sort of natural incentive to, you know, earn a lot or to maximize my pay. Some weeks were that minimum, 500, very few. And then
some I'd get 1,200, 1,300 bucks. Pay has gone up, you know, typical drivers now starting
in the 30s, you know, in the kind of job that I was in, 30s, you know, cents per mile,
30 to 35. So can we try to reverse engineer that math, how that maps the actual hours?
So there's the hours connected to driving are so widely dispersed.
As you said, some of them don't count as actual work.
Some of it does.
That's a very interesting discussion that will then continue when we start talking about autonomous trucking.
But you know, you're saying all these sense per mile kind of thing.
What, how does that map to like average hourly wage?
Yeah, so I mean, and this is kind of the,
this is also an interesting technology story in the end
and it's the technology story that didn't happen.
So pay per mile was invented by companies
when you couldn't surveil drivers.
You didn't know what they were doing, right?
And you wanted them to have some skin in the game.
And so you'd say, you know, here's the load.
It's going from, you know, for me,
I might start in, you know, the Northeast,
maybe in upstate New York with a load of beer.
It's a, here's this load of beer,
bring it to this address in Michigan.
We're gonna pay you by the mile, right?
If you have us being paid by the hour,
I might just pull over with the diner and have breakfast. So you're paid by the mile, but increasingly
over time, the typical driver is spending more and more time doing non-driving tasks. There's
lots of reasons for that. One of which is railroads captured a lot of freight that goes long distances now.
Another one is traffic congestion.
And the other one is that drivers are pretty cheap.
And they're almost always the low people on the totem pole in some segments.
And so their time is used really inefficiently.
So I might go to that brewery to pick up that load of Bud Light.
And, you know, their docks staff may be busy loading up five other trucks.
And they'll say, you know, go over there and sit and wait.
We'll call you on the CB when the docks are ready.
So you wait there a couple hours.
They bring in, you know, you never know what's happening in the truck.
Sometimes they're loading it with a fork lift. Maybe they're throwing
14 pallets on their full of kegs, but sometimes it'll take them hours, you know, and you're sitting in that truck and you're you're essentially unpaid, you know,
then you pull out, you've got control over what you're going to get paid based on how you drive that load. And then on the other end,
you got a similar situation of kind of waiting.
So if that's the way truck drivers are paid, then there's a low incentive for the optimization
of the supply chain to make them more efficient, right, to utilize truck labor more efficiently.
Absolutely.
So that's a technology problem that one of several technology problems that could be addressed.
I mean, so what did if we just linger on it, what are we talking about in terms of
dollars per hour? Is it close to minimum wage? Is it, you know, there's something you talk about.
There was a conception or a misconception that
chargers get paid a lot for their work.
Do they get paid a lot for their work?
Some do.
I think that's part of the complexity.
What interested me as an ethnographer about this was, I'm interested in the kind of economic conceptions that people
have in their heads and how they lead to certain decisions in labor markets.
Why some people become an entrepreneur and other people become a wage laborer or why some
people want to be doctors and other people want to be truck drivers.
That conception is getting shaped in these labor markets as the argument of the book.
And the fact that drivers can hear, or potential drivers, can hear about these workers who make
$100,000 plus, which happens regularly in the trucking industry.
There are many truck drivers who make more than $100,000 a year, is in attraction.
But the industry is highly segmented.
And so the entry level segment,
and we can probably get into this,
but the industry is dominated by a few dozen
really large companies that are self-insured
and can train new drivers.
So if you want those good jobs,
you've got to have several years up until recently,
now that labor market's becoming tighter, but you had to have several years of accident-free,
you know, perfectly clean record driving to get into them. The other part of this segment,
you know, those drivers often don't make minimum wage. But this leads to one of the sort of
central issues that has been in the courts and in the legislature
in some states is, what should truck drivers get paid for?
The industry for the last 30 years or so has said essentially,
it's the hours that they log for safety reasons
for the Department of Transportation.
Now, since the drivers are paid by the mile, they try to minimize those
because those hours are limited by the federal government. So the federal government says you can't
drive more than 60 hours in a week as a long haul truck driver. And so you want to drive as many
miles as you can in those 60 hours. And so you under-report them. Right. And so what happens is the company say, well, that guy, he only said he logged 45 hours
of work that week or 50 hours of work.
That's all we have to pay him minimum wage for.
When in fact, typical truck driver and these jobs will work according to most people,
what sort of define it as like, okay, I'm at the customer location, I'm waiting to
load and doing some paperwork, inspecting the truck, I'm feeling it, just waiting to,
you know, get put in the dock, 80 to 90 hours would be sort of a typical work week for one of these
these drivers. And just to look at that, they don't make minimum wage oftentimes.
Right, just to be clear, what we're dancing around here is that a little bit over, a little bit under minimum wage is nevertheless most truck drivers seem to be making close to minimum wage.
Like this is the, so like we maybe haven't made that clear.
There's a few that make quite a bit of money, but like you're as an entry and for years you're operating essentially minimum wage and potentially
far less than minimum wage if you actually count the number of hours that are taken out
of your life due to your dedication to trucking.
Well, if you count like the hours taken out of your life, then you got to go, you know,
maybe a full 24. That's right. Yeah.
From family, from the high quality of life parts of your life.
Yeah. And there's a whole another set of rules that the Department of
Labor has, which basically say that a truck driver who's dispatched away from
home for more than a day should get minimum wage 24 hours a day.
And that could be a state minimum wage,
but typically what it would work out to for most drivers
is that a minimum wage for a truck driver
should be 50s of thousands,
55, 60,000 dollars should be the minimum wage
of a truck driver.
And you probably heard about the truck driver shortage.
If, you know, which I hope we can talk about, if the minimum wage for truck drivers is as it should be
on the books at, you know, around $60,000, we wouldn't have a shortage of truck drivers.
Oh, wow. And to me, 60,000 is not a lot of money for this kind of job. Because you're, this isn't, this is essentially two jobs.
And two jobs where you don't get to sleep with your wife
or see your kids at night.
That's 60,000 is a very little money for that.
But you're saying if it was 60,000,
you wouldn't even have the shortage.
If that was the minimum.
If that was the minimum. If that was the minimum.
And I think that's what, now we have drivers
who start in the 30s.
Wow, but yeah, I mean, so we're talking to three jobs,
really, when you look at the total hours
that people are working at, you know,
they can work over 100.
If they're a trainer, you know,
training other truck drivers, well over 100 hours a week.
So a job of last resort, maybe you can jump around from tangent to tangent.
This is such a fascinating and difficult topic.
I heard that there is a shortage of truck drivers.
So there's more jobs than truck drivers willing to take on the job.
Is that the state of affairs currently?
I mean, I think the way that you just put that is right.
We don't have a shortage of people
who are currently licensed to do the jobs.
So I'm working on a project for the state of California
to look at the shortage of agricultural drivers.
And the first thing that the DMV commissioner
of a state wanted to look at was,
is there actually a shortage of licensed drivers?
He's like, I've got a database here
of all the people who have a commercial driver's license
who could potentially have the credential to do this.
There are about 145,000 jobs in California
that require a class A CDL,
which would be that commercial driver's license that you need for the big trucks.
About 145,000 jobs, the industry in their regular
promotion of the idea that there's a shortage is always projecting forward and says, you know, we're gonna need
165,000 or so in the next 10 years.
They're currently like
435,000 people licensed
in the state of California to drive one of these big trucks.
So it is not at all an absence of people who,
I mean, and again, going back to what we were talking
about before, getting that license is not something
that you just walk down to the DMV and take the test.
Like, this is somebody who probably quit another job, was unemployed and took months to go to
a training school, paid for that training school oftentimes, left their family for months,
invested in what they thought was going to be a long-term career.
And then said, you know what, Forget it. I can't. I can't do it. You know.
So yeah, so it's not just skill. It's like they were psychologically invested potentially for months, if not years into this kinds of position, as perhaps a position that if they lose their
current job, they can fall to. Okay, so that's in the indication that there's something deeply wrong
with the job. If so many licensed people are not willing to take it.
What are the biggest problems of the job of Trump's drive currently?
Yeah, the job, the problems with the job and the labor market, right? But let's start with the job,
which is, again, just so much time that's not compensated directly for the amount of time.
time that's not compensated directly for the amount of time. And that's just psychologically, and this was a big part of what I studied for the first
book was that conception of like, what's my time worth?
What truck drivers love is oftentimes, is that tangible outcome-based compensation. So they say, you know what, you know,
honest day's work, I work hard, I get paid for what I do, I drive 500 miles today, that's
what I'm going to get paid for, and then you get to that dock, and they tell you, sorry, the
load's not ready, go sit over there, and you stew. And that weight can break you psychologically because your your your time
Every second becomes more worthless. Yeah, or worth less
Yeah, and again the industry is gonna say for instance
Okay, well, you know, they've got skin in the game right that argument about sort of compensation based on sort of output
Right, but that's a holdover from when you couldn't observe truckers. Now they all have satellite linked computers in the trucks
that tell these large companies, this driver was,
you know, at this GPS location for four and a half hours, right?
So if you wanted to compensate them for that time directly
and the trucker can't control what's happening
on that customer location, you know,
they're waiting for that, you know,
firmed that customer to tell them, hey, pull in there.
And so what it becomes is just a way to shift the inefficiencies and the cost of that onto
that driver.
Now, it's competitive for customers.
So if you're Walmart, you might have your choice of a dozen different trucking companies
that could move your stuff.
And if one of them tells you, hey, you're not moving our trucks in and out of your docs
fast enough, we're going to charge you for how long our truck is sitting on your lot.
If you're Walmart, you're going to say, I'll go see what the other guy says, right?
And so companies are going to allow that customer to essentially waste that driver's time,
in order to keep that business.
Can you try to describe the economics, the labor market, or the situation?
You mentioned freight and railroad.
What is the dynamic financials, economics of this that allow for such low salaries to be paid to truckers. What's the competition? What's the alternative
to transporting goods via trucks? What seems to be broken here from an economics perspective?
Yeah, so it's, well, nothing. It's a perfect market.
Okay, right. I mean, so for economists, this is how it should work, right?
But the inefficiencies, like you said,
started to interrupt or push to the truck driver.
Doesn't that like spiral?
Doesn't that lead to poor performance
in the part of the truck driver
and just like make the whole thing more and more inefficient
and it results in lower payment to the truck driver
and so on.
It just feels like in capitalism,
you should have a competing solution
in terms of truck drivers.
Like another company that provides transportation via trucks
that creates a much better experience for truck drivers,
making them more efficient, all those kinds of things,
or how is the competition being suppressed here?
Yeah, so it is, the competition is based on who's cheaper.
And this is the cheapest way to move the freight.
Now, you know, they're externalities, right?
I mean, so this is the explanation that I think
is obvious for this, right?
There are lots of costs that, you know,
whether it's that driver's time,
whether it's the, you know, time without their family,
whether it's the, you know, the fact that they drive
through congestion and spew lots of diesel particulates
into cities where kids have asthma
and make our commutes longer,
rather than more efficiently use their time
by sort of routing them around congestion and rush hour and things like that. This is the cheapest way to move
freight, and so it's the most competitive. But big part of this is public subsidy of training.
So when those workers are not paying for the training, you and I often are.
So if you lose your job because of foreign trade or your veteran using your GI benefits,
you may very well be offered training, publicly subsidized training to become a truck driver.
And so all of these are externalities that the companies don't have to pay for.
And so this makes it the most profitable way to move freight.
So trucks is way cheaper than not trains?
Well, over the long, so one of the big stories for these companies is that the average length
of haul, which becomes very important for self-driving trucks. The average length of haul has been steadily declining.
Over the last 15 years or so,
I'll let this industry collect the data
from sort of the big firms that report it,
but it'll roughly been cut in half
from typically about 1,000 miles to under 500.
And under 500 is what a driver can move in a day, right?
So you can get loaded, drive, and unload, you know, around 400 miles or something like that.
I want to steal a good question from the pen gazette interview you did, which people should read. It's a great interview. Was there a golden age for
long haul truckers in America? And if so, this is just a journalist, the question. And if so,
what enabled it and what brought it to an end? Wow. I might have to have you read my answer to that.
That was a few years ago. We had to ask you to compare what I'll say. But I mean, one bigger question to ask, I guess, is like, you know, Johnny Cash wrote a
lot of songs about truckers.
There used to be a time when perhaps falsely, perhaps it's part of the kind of perception
that you study with the labor markets and so on.
There was a perception of truckers being, first of all, a lucrative job and second of
all, a job to be desired.
Yeah, so I mean, this is the tracking industry,
to me, is fascinating, but I think it should be
fascinating to a lot of people.
So the golden age was really two different kinds
of markets as well, right?
Today we have really good jobs and some really bad jobs.
We had the Teamsters Union that controlled
the vast majority of employee jobs,
and even where they had something called
the National Master Freight Agreement.
And this was Jimmy Hoffa who led the union
through its critical period by the mid-60s had unified essentially
the entire nation's trucking labor force under one contract.
Now you were either covered by that contract or your employer paid a lot of attention to
it.
And so by the end of the 1970s, the typical truck driver was making well more
than $100,000 typical truck driver was making more than $100,000 in today's dollars and
was home every night. That was without a doubt. And even more than unionized auto workers,
steel workers, 10, 20% more than those workers made.
That was the golden age force of job quality, wages, teamster power.
They were without a doubt the most powerful union in the United States at that time.
At the same time in the 1970s, you had the mythic long haul trucker.
These were the guys who were on the margins of the regulated market, which
is what the teamsters controlled. A lot of them were in agriculture, which was never regulated.
So in the New Deal, when they decided to regulate trucking, they didn't regulate agriculture
because they didn't want to drive up food prices, which would hurt workers in urban areas. So
they essentially left agricultural truckers out of it. And that's where a lot of the kind of outlaw, you know, asphalt cowboy imagery that we
get.
And I grew up, I know you didn't grow up in the US that this sort of, you know, as a young
child, and I'm a bit older than you, but in the late 70s, you know, there were movies
and TV shows and C.B.s were a craze,
and it was all these kind of outlaw truckers who were out there hauling some unregulated freight.
They weren't supposed to be trying to avoid the bears who are the cops and with all this salty
language and these terms that only they understood, the party and diners and popping pills,
you know, the California turn arounds.
So that's called Cowboys, truly.
So it's like another form of cowboy movies.
Oh, absolutely, yeah.
Absolutely.
And I think that sort of masculine ethos of like,
you got 40,000 pounds or something you care about,
I'm your guy, you know, you need it to go
from New York to California, don't worry about it, I got it. Yeah. That's appealing. And it's tangible.
Right. And you think about people who don't want to be paper pusher and sitting on deal with
office politics. Like, give me what you care about. I'll take care of it. You know, you just pay me
fair. You know, and that up that appeals. You mentioned unions, teamsters, Jimmy Hafa.
Big question, maybe difficult question.
What are some pros and cons of unions historically and today in the trucking space?
Yeah.
Well, if you're a worker, there are a lot of pros.
And I don't, you know, and this was one of the things I talked to truckers about a lot.
Yeah, what's their perception of Jimmy Hoffa, for example, and of unions?
Yeah.
So, and this was probably one of the central hypotheses that I had going in there.
And it may sound, you know, somebody who does hard science, right?
You may hear a social scientist, you know, sort of use that terminology, even other social
scientists.
Compothesis?
Yeah, you know, they don't like it.
But I do like to think that way.
And my initial hypothesis was that,
and it's very simple that the tenure of the driver
in the industry would have a strong effect
on how they viewed unions,
that somebody who had experienced unions
would be more favorable,
and someone who had not would not be.
Right?
And that turned out to be the case without a doubt,
but in an interesting way,
which was that even the drivers who were not part of the union,
who in the kind of public debate of deregulation
were portrayed as these kind of small business truckers
who were getting shut out by
the big regulated monopolies and the teamsters union, the corrupt teamsters union, even those drivers
longed for the days of the teamsters because they recognized the overall market impact that they had,
that that trucking just naturally tended toward excessive competition that meant that
you there was no profit to be made and oftentimes you'd be operating at a loss. And so even
these, you know, the asphalt cowboy owner operators from back in the day would tell me when
the teamsters were in power, I made a lot more money. And, you know, this is, you know, unions, at least those kinds of unions, like the teamsters.
You know, there's, I think a lot of misconceptions today sort of popularly about what unions did
back then.
They tied wages to productivity.
Like that was the central thing that the teamsters union did.
And, you know, there were great accounts of sort of Jimmy
Hoffa's perspective for all his portrayal as sort of corrupt and criminal and there's you know
I'm not disputing that he broke a lot of laws. He was remarkably open about who he was and what
he did. He actually invited a pair a husband and wife team of Harvard economist
to follow him around and opened up the teamsters' books to them so that they could see how he was
thinking about negotiating with the employers. And the teamsters, and this goes back well before Hafa,
back to the 1800s, they understood that workers did better if their employers did
better.
The only way the employers would do better was if they controlled the market.
Oftentimes, the corruption and trucking was initiated by employers who wanted to limit
competition, and they knew they couldn't limit competition without the supportive labor.
You'd get these collusive arrangements between employers and labor to say, no new
trucking companies.
They're 10 of us.
That's enough.
We control Seattle.
We're going to set the price and we're not going to be undercut.
When there's a shortage of trucks around, it's great rates go up, but you get too many
trucks.
It's very often that you end up operating at a loss
just to keep the doors open. You don't have any choice. It's what economists call
derived demand. You can't make up a bunch of trucking services and store it in a warehouse.
You got to keep those trucks moving to pay the bills.
Can we also lay out the kind of jobs that are in trucking? What are the best jobs in trucking?
What are the worst jobs in trucking? how many jobs we're talking about today?
What kind of jobs are there?
There are a number of different segments.
The first part would be, are you offering, the first question would be, are you offering
services to the public or are you moving your own freight? Right? So are you a retailer, say Walmart or a paper company or something like that that's
operating your own fleet of trucks? That's private trucking. Four hire are the folks who offer
their services out to other customers. So you have private and forehigher.
In general, forehigher pays less.
Is that because of the something you talk about
with employee versus contractor situation
or are they all tricked or led to become contractors?
That can become a part of it as a strategy,
but the fundamental reason is competition.
So those private carriers don't aren't in competition with other trucking fleets for
their own in-house services. So they tend to, and the question of why private versus
for hire, because for hire is cheaper, right? And so if you need that, if that trucking service is central to what you do,
and you cannot afford disruptions or volatility
in the price of it, you keep it in house.
You should be willing to pay more for that
because it's more valuable to you,
and you keep it in house and that.
So that's an interesting distinction.
What about, and this is kind of moving towards our conversation
what can and can't be automated.
How else does it divide the different trucking jobs?
So the next big chunk is kind of how much stuff are you moving?
And so we have what's called truck load.
And truck load means you can fill up a trailer either by volume or by weight
and then less than truck load.
Less than truck load, the official definition is like less than 10,000 pounds.
You know, this is gonna be a couple pallets of this,
a couple pallets of that.
The process looks really different, right?
So that truckload is, you know, point A to point B,
I'm buying, you know, a truckload of bounty paper towels.
I'm bringing it into, you know, my distribution center.
Go pick it up at the, at the bounty plant, bring it to my distribution center, like nowhere in
between.
Do you stop?
At least process that freight.
Less than truck load, what you've got is terminal systems.
This is what you had under regulation too.
These terminal systems, what you do is you do a bunch of local pickup and delivery, maybe
with smaller trucks.
You pick up two pallets of this here, four pallets of this there.
You bring it to the terminal, you combine it based on the destination.
You then create a full truckload trailer.
And you send it to another terminal where it gets broken back down
and then out for local delivery.
That's going to look a lot like if you send a package by UPS.
They pick all these parcels, right?
Figure out where they're all going, put them on planes or in trailers, going to the same
destination, then break them out to put them in what they call package cars.
Before I ask you about autonomous trucks, it's just paused for your experience as a trucker.
Did it get lonely?
Like can you talk about some of your experiences of what it was actually like? Did it get lonely? Like, can you talk about some of your experiences
of what it was actually like?
Did it get lonely?
Yeah, no, I mean, it was, I didn't have kids at the time.
Now, I have kids I can't even imagine it.
You know, I've been married for five years.
At the time, my wife hated it.
I hated it.
You know, I describe in the book the experience of being stuck,
if I remember correctly, it was like Ohio,
at this truck stop in the middle of nowhere
and like, you know, sitting on this concrete barrier
and just watching fireworks in the distance
and like eating Chinese food on the 4th of July.
And you know, my wife calls me from like the family barbecue
and our anniversary is July 8th.
And she's like, are you gonna be home?
And I'm like, I don't know, you know.
I have a cousin whose husband drove truck
as a truck driver would say, drove truck for a while.
And he told me, before I went into it, he was like, the advantage you have is that you know that you're not going to
be doing this long term. And Lex, I can't even like the emotional content of some of these
interviews. I mean, I would sit down at a truck stop with somebody I had never met before and you know you open the spiket and
The the the last question I would ask drivers was that by the time I really sort of figured out to do it the last question
I would ask them is you know, what advice would you give to somebody?
Your nephew, you know a family friend
Asked you about what it's like to be a driver and should they do it? What advice would you give them?
And this question, some of these grizzled old drivers,
tough guys, would that question,
some of them would break down and they would say,
I would say to them, you better have everything
that you ever wanted in life already.
Because I've had a car that I've had for 10 years,
it's got 7,000 miles on it.
I own a boat that hasn't seen the water in five years.
My kids, I didn't raise them.
Like, I'd be out for two weeks at a time.
I'd come home, my wife would give me two kids to punish,
a list of things to do on Saturday night,
and I might leave out Sunday night or Monday morning.
I come home dead tired,
my kids don't know who I am.
It was heartbreaking to hear those stories.
Before you know it, life is short,
and just the years run away.
Yeah.
Hard question to ask in that context, but what's the best, what was the best part of being
a truck driver?
Was there moments that you truly enjoyed on the road?
Oh, absolutely.
There was definitely a pride and mastery of even basic
competence of piloting this thing safely. There's a lot of responsibility to it.
That thing's dangerous, and you know it. So there's some pride there.
For me personally, and I know for a lot of other drivers, it's just like seeing
these behind the scenes places that you know exist in our economy.
I think we're all much more aware of them now
after COVID and supply chain mess that we have.
I don't know if we'll talk about that,
but you know, you get to see those places.
You know, you get to see those ports.
You get to see the place where they make the cardboard boxes
that the Huggy Dippers go in.
Huggy's Dippers going, Or the warehouse full of bud light.
I moved bud light from like upstate New York
and the first load like went to Atlanta.
You know, and then a couple months later,
I circled back through that same brewery
and I brought a load of bud light out to Michigan.
And I was like, holy shit, all the bud light.
Like, you know, for this whole giant swath
of the United States comes from this one plant,
this cavernous plant with like kegs of beer
and you see that part of the economy.
And it's like you're almost like you're an economic tourist.
And I think all everybody kind of appreciates that,
like kind of, it's almost like a behind the scenes tour.
That wears off after a few months, you know,
you start to see new things less and less frequently.
At first, everything's novel and sort of life on the road.
And then it becomes just endless miles of white lines and yellow lines and truck stops.
And the days just blur together.
It's one loading dock after another.
So you lose the magic of being on the road?
Yeah.
It's very rare the driver that doesn't.
You mentioned COVID and supply chain.
While being this, for a brief time,
this member of the supply chain,
what have you come to understand about
our supply chain, United States and global,
and its resilience against
strategies, scatters, troughs in the world,
like COVID, for example.
Yeah, I mean, we have built really long,
really lean supply chains.
And just by definition, they're fragile.
The current mess that we have, it's not going to clear
by Christmas. It will be lucky if it clears by next Christmas.
Can you describe the current mess and supply chain that you refer into?
Yeah, so we've got pile-ups of ships off the coast of California, Long Beach and LA in particular, and in bad shape. Last night, I checked, it was
around 60 ships, all of which are holding thousands of containers full of stuff that retailers were
hoping was going to be on shelves for the holiday season. Meanwhile, the port itself has stacks and
stacks of containers that they can't get rid of. The truckers aren't showing up to pick up
the containers that are there,
so they can't offload the ships that are waiting
and why aren't the truckers picking it up
partly because there's a long history of inefficiency
and making them wait,
but it's because the warehouses are full.
So we've had all these perverse, you know, outcomes that no one really
expected, like in the middle of all these shortages, people are stockpiling stuff.
So there are suppliers who used to keep two months of supply of bottled water on hand.
And after going through COVID and not having supplied to send to their customers,
they're like, we need three months.
Well, our system is not designed
for major storage of goods to go up 50% in a category.
It's lean.
If you're a warehouse operator,
you know, you want to be 90% plus.
You don't want a lot of open base sitting around.
So we don't have, you know have 10% extra capacity in warehouses.
We don't have 10% of them trucking capacity
can fluctuate a bit, but you don't have that kind of slack.
And now, I mean, we saw this right when people shifted consumption.
And I get a little mad when people talk about panic buying
as kind of the,
you know, the reason that we had all these shortages. And it really, like, it's preventing us from
understanding, you know, the real problem there, which is that, that lean supply chain. Sure,
there was some panic buying, you know, no doubt about it. But we had a enormous shift in people's
behavior. So I, with my sister and brother-in- law, I own a couple of small businesses and we serve food.
So we get food from Cisco.
Cisco couldn't get rid of food because nobody's eating out.
So they've got 50 pounds sacks of flour sitting in their warehouse that they can't get rid
of.
They've got cases of lettuce and meat and everything else that's just going to go bad.
That panic buying certainly exacerbated some things like toilet paper and whatever, but
we saw just a massive change in demand, and our supply chains are based on historical
data.
That stuff leaves Asia months before you want to have it on the shelves.
And you're predicting based on last year, you know, what you want on that shelf.
And so, it's a, you know, I guess at its best, it's a beautiful symphony of lots of moving parts.
But now, everyone can't get on the same page of music. But it's not resilient to changes in on mass human behavior.
So even like I read somewhere, maybe you can tell me if it's true in relation to food,
it's just the change of human behavior between going out to restaurants versus eating at home
as a species we consume a lot less food that way.
Apparently what I read in restaurants like there's a lot of food just thrown out. It's part of the
business model. And so like you then have to move a lot more food through the whole supply chain.
And now because you're consuming, you know, there's leftover at home, you're consuming much more of the food you're getting when you're eating at home.
That's creating these bottleneck situations, problems as you're referring to too much in a certain place, not enough in another place.
And it's just the supply chain is not robust, those kind of dynamic shifts in who gets what where.
Yeah.
Yeah, I mean, so I have worked in agriculture a bit
on sort of the supply side.
And there are product categories where 30% of the crop
raised does not get used, right?
Just gets plowed under or wasted.
But here's the importance of this.
And sort of getting this right,
not that panic buying, blame the irrational consumer,
look at the hard truth of the way we've set up our economy.
And I'll ask you this, Lex, I know you're a hopeful,
optimistic person.
100% yes.
Yeah, I am too.
I mean, I write about problems all the time
and so people think I'm sort of like a just a Debbie Downer,
you know, pessimist.
But I'm a glass half full kind of guy.
Like, I want to identify problems so we can solve them.
So let me ask you this, we've got these long,
lean supply chains.
In the future, do you see more environmental problems
that could disrupt them, more geopolitical problems
that could disrupt trade from Asia,
other institutional failures?
Do those things seem potentially more likely in the future
than they have been and say the last 20 years?
Yeah, it almost absolutely seems to be the case. So you then have to ask the question of how do we
change our supply chains? Whether it's making more resilient or make them
chains, whether it's making more resilient or make them less densely connected, you know, building a set, what is it, you know, the Tesla model for in the automotive sector of
like trying to build every, like trying to get the factory to do as much as possible
with as little reliance on widely distributed sources of the supply chain
is possible. So maybe like rethinking how much we rely on the infrastructure of the supply
chain.
Yeah, I mean, you know, there's some basic and I assume that there are a lot of folks
in corporate boardrooms looking at risk and saying that didn't go well and maybe it could have even gone worse.
Maybe we need to think about reshoring, right? At the very least, one of the things that I'm hearing about
anecdotally is that they're starting stuff up, you know, when they can, right? Which is, that's not,
that's probably not sustainable, right? I mean, at some point, somebody in that corporate board room is going to say,
you know, guys, inventory is getting kind of having the cost of that as like,
do we, can we really justify that much longer to the shareholders?
Right. We should, we can back off and start, you know, back things are back to normal.
Let's lean out. Well, my hope is that there's a technology solution to a lot of aspects of this.
So one of them on the supply chain side is collecting a lot more data.
solution to a lot of aspects of this. So one of them on the supply chain side is collecting a lot more data, like having much
more integrated and accurate representation of the inventory all over the place and the
available transportation mechanisms, the trucks, the all kinds of freight.
And how in the different models of the possible catastrophes that can happen, how will the system respond?
So, having a really solid model that you're operating under as opposed to just kind of being
in an emergency response mode under poor incomplete information, which is what seems
like is more commonly the case, except for things like you said, Walmart and Amazon, they're trying to
internally get their stuff together on that front, but that doesn't help the rest of the economy.
Another exciting technological development as you write about, as you think about,
is autonomous trucks. So these are often brought up in different contexts as the examples of AI and robots taking
our jobs.
How true is this?
Should we be concerned?
I think they've really come to epitomize this anxiety over automation, right?
It's such a simple idea, right?
Truck that drives itself, you know, classic blue collar job that pays well, you know,
guy maybe with not a lot of other good options, right? To sort of make that same income easily,
right? And you build a robot to take his job away, right? So I think 2016 or so, that was
that was the sort of big question out there.
And that's actually how I started studying it, right?
I just wrapped up the book.
Just so happened that somebody was working at Uber.
Uber, I just bought auto, saw the book, and was like, hey, can you come out and talk
to our engineering teams about what life is like for truck drivers and maybe how our
technology could make it better. engineering teams about what life is like for truck drivers and maybe how our technology
could make it better.
And at that time, there were a lot of different ideas about how they were going to play out.
So while the press was saying, all truckers are going to lose their jobs, there were a lot
of people in these engineering teams who thought, okay, if we've got an individual owner operator
who thought, okay, you know, if we've got an individual owner operator, you know, and they can only drive eight or 10 hours a day, you know, they hop in the back, they get their
rest, and the asset that they own works for them, right?
So, perfect, right?
And at that time, you know, there were a bunch of reports that came out and sort of basically
what people did was they took the category of truck driver. Some people took a larger category from BLS of sales and delivery workers that was about
three and a half million workers and others took the heavy-duty truck driver category which was
at the time about 1.8 million or so. And they picked a start date and a slope
let's assume that all these jobs are just going to disappear.
And really smart researcher and at a Bernhardt at the labor center at UC Berkeley was sort of looking
around for people who were sort of deeply into industries to complicate those analyses, right?
And reached out to me and was like, what do you think of this? And I said, the industry's super diverse.
You know, I haven't given a ton of thought,
but can't be that.
You know, it's not that simple.
You know, I mean, it never is.
And so she was like, well, you know,
well, you do this.
And I was like ready to move on to another topic.
You know, I had like been in trucking for 10 years.
And that's how it, I started looking at it.
And it is, it's a lot more complicated.
And the initial impacts, and here's the challenge, I think,
and it's not just a research challenge,
it's the fundamental public policy challenge,
is we look at the existing industry
and the impacts, the potential impacts,
they're not, you know, nothing.
For some communities and some kinds of drivers, they're going to be hard.
And there are a significant number of them.
No, we're near what people thought.
You know, I estimate it's like around 300,000.
But that's a static picture of the existing industry.
And here's the key with this is, at least in my conclusion,
is this is a transformative technology.
We are not going to swap in self-driving trucks
for human driven trucks, and all else stays the same.
This is gonna reshape our supply chains.
It's gonna reshape landscapes.
It's gonna affect our ability to fight climate change.
This is a really important technology in this space.
Do you think it's possible to predict the future of the kind of opportunities it will create,
how it will change the world?
So like when you have the internet, you can start saying like all the kind of ways that office work, all jobs will
be lost because it's easy to network and then software engineering allows you to automate
a lot of the tasks at Microsoft Excel does, you know.
But it opened up so many opportunities, even with things that are difficult to imagine,
like with the internet, I don't know, Wikipedia, which is widely making accessible information, and that increase the general education globally
by a lot, all those kinds of things.
And then the ripple effects of that in terms of your ability to find other jobs is probably
immeasurable. So is it just a hopeless pursuit to try to predict
if you talk about these six different trajectories
that we might take in automating trucks,
but like as a result of taking those trajectories,
is it a hopeless pursuit to predict
what the future will result in?
Yeah.
It is.
It had absolutely is. Because it future will result in. Yeah. It is.
It had absolutely is because it's the wrong question.
Yeah.
The question is, what do we want the future to be
and let's shape it?
Right?
And I think this is, and this is the only point
that I really want to make in my work for the foreseeable
future, is that we have got to get out of this mindset that we're just gonna
let technology kind of go and it's a natural process and
whatever pops out will fix the problems on the backside.
And we've got to recognize that one, that's not what we do.
Right. You know, and self-driving vehicles is just such a perfect example, right?
We would not be sitting here today if the Defense Department, if Congress in 2000 had not
written into legislation funding for the DARPA challenges, which followed,
actually, I think the funding came a couple years later, but the priority that they wrote in 2000 was,
I think the funding came a couple of years later, but the priority that they wrote in 2000 was,
let's get a third of all ground vehicles
in our military forces on manned, right?
And this was before aerial unmanned vehicles
had really sort of proven their worth.
They would come to be incredibly,
like, you know, just blow people out of them,
though blow people's minds in terms of their additional
capabilities, the lower costs, you know,
keeping, you know, soldiers out of
harm's way. And of course, they raised other problems and considerations that I think we're still
wrestling with. But that was even before that, they had this priority. We would not be sitting here
today if Congress in 2000 had not said, let's bring this about. So they already had that vision,
actually. I didn't know about that. So for people who don't know the dupour challenges,
had that vision, actually, I didn't know about that. So for people who don't know, the dupor challenges
is the events that were just kind of like
these seemingly small scale challenges
that brought together some of the smartest
roboticists in the world.
And that somehow created enough of a magic
where ideas flourished both engineering and scientific
that eventually then was a catalyst for creating all these different companies that took on the child some fail some succeeded some are still fighting the good fight.
And that somehow just that little bit of challenge was the was the essential spark of progress that now resulted in this beautiful up and down way of hype and profit and all this kind of weird
dance for the B-word, billions of dollars have been thrown around and we still don't
know.
And the T-word trillions of dollars in terms of transformative effects of autonomous vehicles
and all that started from DARPA and that initial vision of I guess as you're saying, of
automating part of the military supply chain.
Yeah, I did not know that.
That's interesting.
So they had the same kind of vision for the military
as we're not talking about a vision for the civilian,
whether it's trucking, or whether it's autonomous vehicle,
sort of a ride sharing kind of application.
Yeah, I mean, what an incredible spark, right?
And just the story of an incredible spark, right? And and it just the story of
What it produced right? I mean
Your own work on self-driving right? I mean you you you studied it as an academic, right?
How many great researchers and minds have been harnessed
By this outcome of that spark right and I think this is sort of theoretically about technology, this is what makes it so great is that,
this is what makes us human in my opinion, right?
Is that you conceive of something in your mind
and then you bring it into reality, right?
I mean, that's what is so great about it.
Sometimes your two dumb to realize how difficult it is
so you take care of it.
Right?
And then eventually your two, you take it. Right. And then eventually you're
you're too, you're in too deep. You might as well solve the problem. Well, and maybe we're in
that situation right now. Yeah. Self driving. But you know, so let me throw this out there. I'd
be curious to see your thoughts on it. But the truck driver's always always asked me like, is this
for real? Like, is this really do like, it's harder than they think, right?
And they can't really do this.
And, you know, at first I was like, look, you know,
this is like the defense department
and like, basically the top computer science
and robotics departments in the world.
And now Silicon Valley with billions of dollars in funding and just, you know, some of the smartest, hardest working, most visionary people focused on what is clearly, you know, a gigantic market.
Right. And what I tell them is like, if, if, if, if self-driving vehicles don't happen, I think this will be the biggest technology failure
story in human history.
I don't know of anything else that is just galvanized.
I mean, you've had people in garages or weird inventors work on things their whole lives
and come really close.
And it never happens and it's a great failure story, right?
But never have we had like whole, I mean, we're talking about GM, right?
And these are not, you know, these are not tech companies, right?
These are industrial giants, right?
What were in the 20th century the pinnacle of industrial production in the world in human history,
right?
And they're focused on it now.
So if we don't pull this off, it's like, wow.
Yeah.
It's fascinating to think about.
I've never thought of it that way.
I there was a mass hysteria on a level in terms of excitement and hype.
On a level that's probably unparalleled in technology space.
Like, I've seen that kind of hysteria just studying history when you talk about military conflict.
So we often wage war with a dream of making a better world and then realize it costs
trillion dollars.
And then we step back and go, wait a minute, what do we actually get for this?
But in the space of technology, it seems like all these kind of large efforts have paid
off.
This year right, it seems like it seems like giving GM and Ford and all these companies now are a little bit like,
hey, or Toyota and even Tesla, are we sure about this?
Yeah.
And it's fascinating to think about when you tell the story of this, this could be one
of the big first, perhaps, but by far the biggest failures of the dream in the space of technology.
That's really interesting to think about.
I was a skeptic for a long time because of the human factor.
Because for business to work in the space, you have to work with humans, you have to work
with humans at every level.
So in the truck driving space, you have to work with the truck driver, but you also have
to work with the society that has a certain conception of what driving means.
And also, you have to have work with businesses that are not used to this extreme level of
technology, you know, in the basic operation of their business. So I thought it would
be really difficult to move to autonomous vehicles in that way.
But then I realized that there are certain companies that are just willing to take big risks
and really innovate.
I think the first impressive company to me was Waymo or what was used to be the Google
self-driving car.
And I saw, okay, here's a company that's willing to really think long-term and really try
to solve this problem, hire great engineers.
Then I saw Tesla with mobile I when they first had, I thought, actually, mobilized the thing
that impressed me when I said, because I'm a computer vision person, I thought there's
no way a system could keep me in lane long enough for it to be a pleasant experience for me.
So from a computer vision perspective, I thought there'd be too many failures, it'd be really annoying, it'd be a gimmick a toy, it wouldn't actually create a pleasant experience.
And when I first got in a Tesla with a mobile eye, the initial mobile eye system, it actually held to lane for quite a long time to where I could relax a little bit.
It was a really pleasant experience. I couldn't exactly explain why it's pleasant because it's not like I still have to really pay attention,
but I can relax my shoulders a little bit. I can look around a little bit more. For some reason, I was really reducing his stress. And then over time, Tesla, with a lot of the revolution
and stuff they're doing on the machine learning space,
made me believe that there's opportunities here
to innovate, to come up with totally new ideas.
Another very sad story that I was really excited about
is Cadillac SuperCruise system.
It is a sad story because I think I vaguely read it
and used it just said they're discontinuing SuperCruise system. It is a sad story because I think I vaguely read it and used it,
just said they're discontinuing supercruise. But it's a nice, innovative way of doing driver
attention monitoring and also doing lane keeping. And just innovation could solve this in
ways we don't predict. And same with the trucking space, it might not be as simple as like
journalists in vision a few years ago
where everything's just automated. It might be gradually helping out the truck drivers some ways
that make their life more efficient, more effective, more pleasant, make the like remove some of the
inefficiencies that we've been talking about in totally innovative ways. And I still have that dream that I believe to solve the fully autonomous driving problem
was still many years away.
But on the way to solving that problem, it feels like there could be, if there's bold
risk takers and innovators in the space, there's an opportunity to come up with like subtle technologies
to make all the difference. That's actually just what I realized is sometimes little design
decisions make all the difference. It's the blackberry versus the iPhone. Why is it that
you have a glass and you're using your finger for all of the work versus the buttons makes all the
difference.
This idea that now that you have a giant screen so that every part of the experience is
not a digital experience.
So you can have things like apps that change everything.
You can't, you know, when you first think about do I want a keyboard or not on a smartphone,
you think it's just the keyboard decision. But then you
later realize by removing the keyboard, you're enabling a whole ecosystem of technologies
that are inside the phone. And now you're making a smartphone into a computer. And that
same way, who knows how you can transform trucks, right? But like automating some parts of it, maybe adding some displays,
maybe allows you to maybe giving the truck driver some control in the supply chain to make
decisions, all those kinds of things. So I don't know. So what's where are you on the spectrum of hope
Where are you on the spectrum of hope for the role of automation in trucking?
I think automation is inevitable. And again, I think the, this is really going to be transformative. And it's going to be, I studied the history of trucking technology as much as I can.
There's not a lot of great stuff written, then you kind of have to,
there isn't a lot of data and places to know
sort of volumes of stuff and how they're changing, et cetera.
But the big revolutionary changes in trucking
are because of constellations of factors.
It's not just one thing, right?
So, dimelar builds a motorized truck,
and I think it's 1896, right?
Intercity's trucking.
So basically what they use that truck for
is just to swap out horses, right?
They basically do the same thing.
The service doesn't really change.
And then World War I really spurs the development
of bigger larger trucks, like spreads air-filled tires.
And then we start paving roads, right?
And paved roads, right?
Air-filled tires and the internal combustion engine.
Now you got to win a mix.
Now it met with demand for people who wanted to get out from under the thumb of the rail
roads, right? for people who wanted to get out from under the thumb of the railroads. So there was all of this pent-up demand to get cheaper freight from the countryside
into cities and between cities that typically had to go by rail. And so now,
40 years after that internal combustion engine, it becomes this absolutely essential,
right, this necessary but not sufficient piece of technology
to create the modern trucking industry in the 1930s.
And I think self-driving is going to be,
self-driving trucks are going to be part of that.
And the idea, I don't know, I guess we credit Jeff Bezos.
The idea is, you know, okay, so Sam Walton,
if we can do it like a slight tangent on sort of,
the importance of trucking to business strategy
and sort of how it has transformed our world.
The central insight that Sam Walton had that made him,
the giant that he was in influencing the way
that so many people get stuff was a trucking insight.
And so if you look at the way that he developed
his system, you build a distribution center, and then you ring it with stores. Those stores
are never further out from that distribution center than a human driven truck can drive back
and forth in one day. And so rather than the way all of his competitors were doing it with
sending trucks all over the place and having people sleep overnight and sort of
making the trucking service fit where they had stores.
He designed the layout of the stores, right, to fit what trucks could do.
And so transportation and logistics, right,
become Wal-Mart's, you know, edge, right, and allows them to dominate the space.
That's the challenge that Amazon has. Now they've mastered the digital part of it,
right, and now they got to figure out like, how do we, you know, dominate the
actual physical movement that compliments that others are obviously going to follow.
But the capabilities of these trucks is completely different than the capability of human-driven
trucks. So if you're smith-packing, and you've got a bunch of meat in a warehouse, and it's going to
grocery distribution centers.
You have that trucker probably come in the night before and you make him wait so that he
has a full 10 hour break, which is what the law requires, so that he can get to the furthest
reaches that he can of one of those stores.
He can drive his full 11 hours and bring that meat so it doesn't have to sit overnight
in that refrigerated trailer.
So their system is based on that.
Now what happens when that truck can now travel two times as far, three times as far?
Now you don't need the warehouses where they were.
Now you can go super lean with your inventory.
Instead of having meat here, meat there, meat there,
you can put it all right here.
And if it's cheap enough, substitute those transportation costs
for all that warehousing costs.
So this is going to remake landscapes
in the same way that big box supply chains did.
And then, of course, the further complement of that is,
how do you then get it to two people at their door?
And the big box supply chain, it moves very few items
in really large quantities to very few locations,
pretty slowly.
E-commerce aspires to do something completely different, right?
We've moved huge varieties of things in small quantities, virtually everywhere as fast as possible.
Right? And so that is like that intercity trucking under the, you know, in the era of railroad
monopolies, right? The demand for that is potentially enormous.
And so right now, I think a lot of the business plans
for automated trucks, and the way that the journalistic
accounts portray it is like, okay, if we swap out
a human for a computer, one of the labor costs per mile
and like, oh, here's the profitability of self-driving trucks. Uh-uh.
Like, this is transformative technology.
We're gonna change the way we get stuff.
So we get actually get a lot more trucks period
with like, with the autonomous trucks,
because they would enable a very different kind
of transportation networks, you think.
Yeah, here's, and this is where it's like, uh-oh.
Like, yeah, so, like, we really thought we were gonna be electrifying trucks.
If they're going twice as far,
if they're moving three times as much,
if they're going three times as far, right?
What does that mean for how far we are behind on batteries,
right?
We've got sort of these ideas about like,
man, here's how close we could get to meet this demand.
That demand is gonna radically change, right? These trucks are, you know, ideas about like, man, you know, here's how close we could get to meet this demand. That demand is going to radically change, right?
These trucks are, you know, so then we've got to think about, all right, if it's not batteries,
you know, how are we powering these things?
And how many of them are they're going to be?
Like right now, we've got five million containers that move from LA and Long Beach to Chicago
on rail.
Rail is three or four times at least more efficient
than trucks in terms of greenhouse gas emissions.
And on that lane, it varies a lot depending on demand,
but maybe rail has a 20% advantage in cost, maybe 25%,
but it's a couple days slower.
So now you cut the cost of that truck, transportation per mile by 30%.
Now it's cheaper than rail, and it gets the stuff there five days faster than rail.
How many millions of containers are going to leave LA and Long Beach on self-driving trucks
and go to Chicago?
And it might look very much like a train if we go with the platooning solution,
what you have, these rows of like, imagine like rows of like 10, like dozens of trucks or like
hundreds of trucks, like some absurd situation, just going from LA to Chicago, just this train,
but taken up a highway. I mean, this probably a good place to talk
about various scenarios.
Well, before we get there, can I just make one interesting
observation that I made as a driver,
when you're in a truck, you're up higher.
So you can see further and you can see the traffic patterns
and cars move in packs. I'm sure there's academic research on this, right. And cars move in packs.
I'm sure there's academic research on this, right?
But they move in packs,
they kind of bunch up behind a slower car,
and then a bunch of them break free.
And this is sort of on almost free flowing highways.
They kind of move in packs
and you can kind of see them in the truck.
So, you know, rather than platoons,
we might have like hives, you know, of trucks, right?
So you have like 20 trucks moving in some coordinated fashion, right? And then maybe the self-driving cars are,
you know, because people don't like to be around them or whatever it is, right? You might have a pod
of, you know, 20 self-driving cars sort of moving in a packet behind them, you know.
This is what if the aliens came down or were just observing cars, which is one of the,
sort of prevalent characteristics
of human civilization, there seems to be these cars like moving around.
They would do this kind of analysis of like, huh, what's the interesting clustering of
situations here?
Especially with autonomous vehicles.
I like this.
Okay.
So what technologically speaking do you see are the different scenarios
of increasing automation in trucks? What are some ideas that you think about?
For the most part, I have no influence on sort of what these ideas were. So what the project
was that I did was I said, technology is created by people. They solve for X and they have
some conception of what they want to do.
That's where we should start in thinking about
what the impacts might be.
So I went and I talked to everybody I could find
who was thinking about developing a self-driving truck.
The question was essentially,
what are you trying to build?
What do you envision this thing doing?
It turned out that for a lot of them
was an afterthought, they knew the sort of
technological capabilities that a self-driving vehicle
would have and those were the problems
that they were tackling.
You know, they were engineers and computer scientists
and oh robotics people, people love you so much.
This is the I could talk forever about this but yes, there's a technology problem.
Let's focus on that.
We'll figure out the actual impact on society.
How it's actually going to be applied.
How it's actually going to be integrated from a policy and from a human perspective, from
a business perspective later.
First let's solve the technology problem.
That's not how life works. Friends, but okay, I'm sorry.
Yeah, so I mean, I'm sure you know the division of labor
in these companies, right?
They're sort of a business development side.
And then there's the engineering side, right?
And the engineers are like, oh my God,
what are these business development people?
You know, why are they involved?
You know, in this process.
So I ended up sort of coming up with a few different ideas that
people seem to be batting around and then really tried to zero in on a layman's understanding
of the limitations, right? And it turns out that's really obvious and quite simple. Highway
driving is a lot simpler, right? So, you know, the plan is simplify the problem, right? And focus on highways
because city driving is so much more complicated. So, from that, I came up with basically six scenarios,
actually, I came up with five that the developers were talking about. And then one that I thought was a good idea that I had read about, I think in like 2013 or 2014,
which was actually something that the US military was looking at. I actually first heard about the
idea of this kind of automation at least in sketched out form in like 2011, I guess it was with
Peloton, which was this sort of early technology
entrant into the trucking industry, which was working on platooning trucks.
And all they were doing was a cooperative adaptive cruise control
as they came to call it.
And we ended up on a panel together.
And it's kind of interesting because I was on that panel
because I was thinking about how we got the best return on investment for fuel efficient technologies.
And if it's cool, I'll sort of set this up because it comes into sort of the story of some of these scenarios.
So, when I studied the drivers, you had this like complete difference in the driving tasks like we were
talking about before with long haul and city, right? And you're not paid in the
city, you've got congestion, the turns are tight, there's lots of you know
pedestrians, you know, all the things that self-driving trucks don't like,
truckers don't like, right? And they're not paid.
There's lots of waiting time.
And then in the highway, they get to cruise,
they're getting paid, they have control,
they go at their own pace, they're making money,
they're happy.
Well, it turned out, I guess it was around 2010,
this is still when we were thinking
about regenerative braking, you know,
and hybrid trucks being sort of like the solution.
The problems with them sort of, and the advantages, you know, also split on what I was thinking of as kind of the rural
urban divide at that time, right? So, like you got the regenerative breaking, right? You can
make the truck lighter, you can keep it local, right? You don't get any benefit from that hybrid electric in the rural highway.
You want aerodynamics, right?
There you want low rolling resistance tires and these super aerodynamics sleek trucks,
right?
Where we know with off-the-shelf technology today, we could double the fuel economy, more
than double the fuel economy of the typical truck in that highway segment. If we segmented the duty cycle, right?
And so in the urban environment, you want a clean burning truck, so you're not giving
kids asthma, you want it lighter.
So it's not destroying those those less strong pavements, right?
You're not, you can make tighter turns.
You don't need a sleeper cab because the driver, you know, hopefully is getting home
at night, right?
In the long haul, you want that super aerodynamic stuff.
Now, that doesn't get you anything in the city.
And in fact, it causes all kinds of problems
because you turn too tight, you crunch up all the aerodynamics
that connect the tractor and the trailer.
So the idea that I had was like, okay, what if we deliberately segmented it?
Like, what if we created these droplets outside cities
where, you know, a local city driver who's paid by the hour
kind of runs these trailers out once they're loaded.
It doesn't sit there and wait while it's being loaded.
They drop off a trailer, they go pick up one that's loaded,
they run it out when it's loaded, they call them
and they just run them out there and stage them.
It's like an Uber driver, but for truckloads.
Yeah, and we have intermodal.
We have basically this would be the equivalent and we have like intermodal. We have like, we have basically this would be the equivalent
of like rail to truck intermodum, right?
So you put it on the rail and then you know,
a trucker picks it up and delivers it, right?
So instead of having the rail,
you'd have these super aerodynamic, hopefully platoons
or what was at the time was called long combination vehicles,
which is basically two trailers connected together, right?
Cause this is like a huge productivity gain, right?
And then instead of that driver like me, I would pick up something in upstate New York, I drive to Michigan, drive to Alabama,
you know, drive to Wisconsin, drive to Florida, you know, I get home every two weeks. If I'm just running that, you know,
that double
trailer, I might be able to go back and forth from Chicago to Detroit, right? Take two trailers there, pick up two trailers going back,
right, and be home every night.
Now the problem with that at the time,
or one of them was, you know, bridge weights.
So you can't, not all bridges can handle
that much weight on them.
They can't handle these doubles, right?
In some places, Ken, some places, can't.
And so this platooning idea was happening at the same time,
and we ended up on the same panel and
The founders were like hey, so what's it like to follow really close behind another truck?
Which was kind of the the stage that they were at was like, you know
What's that experience gonna be like and I was like it truckers aren't gonna like it?
You know, I mean that that's just like the cardinal rule is following distance like that's the one you really shouldn't violate
Right, and when you're out on the
road, you have that trucker right on your ass. People remember that. They don't remember the 99.9%
of truckers that are not on their ass. They're very careful about that.
But when the trucks are really close together, there's benefits in terms of aerodynamics.
So that's the idea. So if you want to get some benefits of a platoon,
you want them to be close together,
but you're saying that's very uncomfortable for truckers.
Yeah, so I mean, I think that ended up at the,
I mean, Peloton I think is sort of winding down
their work on this.
And I think that ended up being still an open question.
Like, and I had a chance to interview a couple drivers
who at least one, maybe two of which
had actually driven in their platoons.
And I got completely different experiences.
Some of them were like, it's really cool.
You know, I'm like in communication with that other driver.
You know, I can see on a screen
what's out the front of his truck.
And then some were like like it's too close.
It might be one of those things
that takes an adjustment to get there.
You get the aerodynamic advantage,
which saves fuel.
There's some problems though.
You're getting that aerodynamic advantage
because there's a low pressure system in front of that following truck.
But the engine is designed with higher pressure
feeding that engine, right?
So there are sort of adjustments that you need to make
and still the benefits are there.
That's one scenario, and that's just the automation
of that acceleration and braking.
Starsky, which probably a lot of your listeners
heard about, was working on another scenario, which
was to solve that local problem was going to do teleoperation, sort of remote piloting.
I had the chance to watch them do that.
They drove a truck in Florida from San Francisco in one of their offices. That was really interesting.
And then in case it's not clear, tell the operation means you're controlling the truck remotely,
like it's a video game. So you've gotten the chance to witness it. Does it actually work?
Yeah, I mean, so it's one of the pros and cons. You know, one of the problems with doing research like this with all these Silicon Valley folks
is the NDAs.
All right.
All right.
So I don't know what I'm able to say
about watching it, but obviously
their public statements about what the challenges are.
And it's about the latency and the ability
to sort of in real time, there's challenges that.
Let me say one thing. So I'm talking to the, I've talked to the of in real time, there's challenges that. Let me say one thing.
So I'm talking to the, I've talked to the Waymo CTO, I'm in conversations with them,
I'm talking to the head of trucking Boris Softman in next month actually.
I'm a huge fan of his because he was, I think the founder of Anki, which is a Toy Robotics
company.
So I love cute, I love human robot interaction.
And he created one of the most effective and beautiful toy robots.
Anyway, I keep complaining to them on email privately that there's way too much marketing
in these conversations and not enough showing off the both the challenge and the beauty of the engineering efforts.
And that seems to be the case for a lot of these Silicon Valley tech companies.
They put up this, you talk about NDAs. wrongfully because there's been so much hype and so much money being made, they don't
see the upside in being transparent and educating the public about how difficult the problem
is. It's much more effective for them to say, we have everything solved, this will change
everything, this will change society as we know, and just kind of wave their hands as
opposed to exploring together like these different scenarios, what are the pros and cons?
Why is it really difficult?
What are the gray areas of where it works and doesn't?
What's the role of the human in this picture of the both the sort of the operators and the
other humans on the road?
All of that, which are fascinating human problems, fascinating engineering problems that I wish
we could have a conversation about
as opposed to always feeling like it's just marketing talk.
Because a lot of what we're talking about now,
even you with having private conversations under NDA,
you still don't have the full picture
of how difficult this problem is.
One of the big questions I've had still have
is how difficult is driving?
I've disagree with Elon Musk and Jim Keller on this point.
I have a sense that driving is really difficult.
You know, the task of driving, just broadly.
This is like philosophy talk.
How much intelligence is required to drive a car? So from a, like a Jim Keller
it used to be the head of autopilot. The idea is that it's just a collision of wooden problems,
like billier balls. It's like you have to convert the drive, if you do some basic perception,
a computer vision, to convert driving into a game of pool,
and then you just have to get everything into a pocket.
To me, there seems to be some game theoretic dance
combined with the fact that people's life is a stake.
And then when people die at the hands of a robot,
the reaction is going to be much more complicated.
So all of that, but that's still an open question.
And the cool thing is all of these companies
are struggling with this question
of how difficult is it to solve this problem sufficiently such that we can build the business
on top of it and have a product that's going to make a huge amount of money and compete
with the manually driven vehicles. And so their teleoperation from StarSkis is really
interesting idea. How much can I mean there's a few autonomous vehicle companies that tried to integrate
teleoperation in the picture.
Can we reduce some of the costs while still having reliability like catch when the vehicle
fails by having teleoperation?
It's an open question.
So that's for you, scenario number two,
is to use tele-operation as part of the picture.
Yeah, let me follow up on that question
of how hard driving is, because this becomes a big question
for researchers who are thinking about labor market impacts,
because we start from a perspective
of what's hard harder easy for humans, right? And so,
you know, if you were to look at truck driving prior to a lot, I mean, there's been a lot of thinking
and debate in, in academic, you know, research circles around sort of how you estimate labor impacts,
right? What these models look like. And a lot of it is about how automatable is a job. Object
recognition, really easy for people, right? Really hard for is about how automatable is a job. Object recognition
is really easy for people, right? Really hard for computers. And so there's a whole bunch
of things that truck drivers do that we see as super easy, and as it would have been
characterized 10 years ago, routine. And it's not for a computer, right? It turns out to be something that we do naturally
that is cutting edge, right?
Computer science.
So on the tele-operation question,
I think this is more interesting one
than people would like to let on, I think, publicly.
There are going to be problems, right?
And this is one of the complexities of putting these things out in the world.
And if you see the real world of trucking, you realize, wow, it's rough.
You know, there are dirt lots, there's gravel, there's salt and ice and cold weather, and
there's equipment that just gets left out in the middle of nowhere, and the brakes don't
get maintained, and somebody was supposed to serve us something and they didn't, you know.
And so you imagine, okay, we've got this vehicle
that can drive itself, which is gonna require
a whole lot of sensors to tell it that like,
the doors are still closed
and the trailer's still hooked up
and each of the tires has adequate pressure.
And you know, any number of, you know,
probably hundreds of sensors
that are gonna be sort of relaying information.
And one of them, you know, after 500,000 miles or whatever it goes out.
Now, you know, do we have some fleet of technicians sort of continually cruising the highways
and sort of servicing these things as they do what?
Pull themselves off to the side of the road and say, I've got a sensor fault.
I'm pulling over, you know, or maybe there's some level of like critical, safety critical
faults or whatever it might be.
So you know, that suggests that there might be a role for teleoperation, even with self-driving.
And when I push people on it in the conversations, they all are like, yeah, we kind of have that
on the like bottom of the list, figure out how to rescue truck.
It gets on the to-do list, right?
After solving the self-driving question, it's like, yeah, what do we do with the problems?
Right?
I mean, no, we can imagine.
All right, we have some protocol that the truck is not, realizes the system says, not
safe for operation, pull to the side.
Good, you have a crash, but now you've got a truck
stranded on the side of the road. You're going to send out somebody to like calibrate things and check out what's going on or that sounds like expensive labor.
It sounds like downtime. It sounds like the kind of things that shippers don't like to happen to their freight, you know, in a just in time world. And so wouldn't it be great if you could just sort of loop
your way into the controls of that truck and say,
all right, we've got a sensor out.
It says that the tire's bad, but I can see visually
from the camera, looks fine.
I'm going to drive it to our next depot,
maybe the next rider or penski location,
sort of all these service locations around
and have a technician take a look at it.
So tally operation often gets dismissive commentary from other folks working on other
scenarios, but I think it's potentially more relevant than we hear publicly. It's a hard problem and
You know for me I've gotten a chance to interact with people that take on hard problems and solve them and they're rare
What Tesla has done with their data engine?
So I thought a time was driving cannot be solved
without collecting a huge amount of data and organizing it well, not just collecting but organizing it. And exactly what Tesla is doing now is what I
thought it would be like I couldn't see car companies doing that, including
Tesla. And now that they're doing that, it's like, oh, okay. So it's possible to
take on this huge effort seriously. To me, teleoperation is another huge
effort like that. It's like taking seriously what happens when it fails.
What's the, in a case of Waymo for the consumer, like ride-sharing?
What's the customer experience like?
There's a bunch of videos online now where people are like, the car fails and it pulls
off to the side and you call customer service and you're basically sitting there for a long time and there's confusion and then there's a rescue that comes
and they start to drive me just the whole experience is a mess that has a ripple effect
to how you trust in the entirety of the experience.
But like actually taking on the problem of that failure case and revolutionizing that
experience both for trucking and for ride sharing.
That's an amazing opportunity there because that feels like it would change everything.
If you can reliably know when the failures happen, which they will, you have a clear
plan that doesn't significantly affect the efficiency of the whole process, that could
be the game changer.
And if tele-operation is part of that, it could be, like Jessica's saying, that could be the game changer. And if tele-operations part of that, it could
be, like Jessica's saying, it could be tele-operation, or it could be like a fleet of rescuers
that can come in, which is a similar idea. But tele-operation obviously, that allows
you to just have a network of monitors, of people monitoring this giant fleet of trucks
and taking over when needed. And it's a beautiful vision of the future, where there's millions of robots and only thousands
of humans monitoring those millions of robots.
That seems like a perfect dance of allowing humans to do what they do best and allowing
robots to do what they do best.
Yeah. So I think there are, and we just applied for an NSF, we didn't get anybody's watching.
But with some folks from Wisconsin who do teleoperation, and some of this is used for
like, rovers and really high stakes, difficult problems.
But one of the things we wanted to study were these minds
in these Rio Tinto minds in Australia
where they remotely pilot the trucks.
And there's some autonomy, I guess,
and then, but it's overseen by a remote operator.
And they, you know, it's near Perth,
and it's quite remote,
and they retrained the truck drivers
to be the remote operators, right?
There's autonomy in the port of Rotterdam
and places like that where there are jobs there.
And so I think, and maybe we'll get to this later,
but there's a real policy question about
who's gonna lose and what we do about it
and whether or not there are opportunities there
that maybe we need to put our thumb on the
scale a little bit to make sure that there's some give back to the community that's taking the hit.
So for instance, if there were tele-operation centers, maybe they go in these communities that
we disproportionately source truck drivers from today. Now, what does that mean? It may not be the cheapest
place to do it if they don't have great connectivity mean? It may not be the cheapest place to do it
if they don't have great connectivity.
And it may not be where the upper lever managers
want to be.
You know, places like that, you know,
issues like that, right?
So I do think it's an interesting question,
you know, both from sort of a practical scenario situation
of how it's going to work,
but also from a policy perspective.
So there's platoons, there's teleoperation, and this is taking care of some of the highway
driving that we're talking about. Is there other ideas like, is there other ideas, scenarios
that you have for autonomous trucks?
Yeah, so I mean, the most obvious one actually is just you know
Facility to facility right this sort of you know
It can't go everywhere, but a lot of logistics facilities are very close to interstates And they're and they're on big commercial roads without you know bikes and parked cars and all that stuff
And some of the jobs that I think are really first on the chopping block are
These LTL that less than truckload what's called line haul. Right. So these are the drivers who
go from terminal to terminal with those full trailers. And those facilities are often located
strategically to avoid congestion, right. And to be in big, you know, industrial facilities.
So you could imagine that being, you know being the first place you see a WEMO
self-driving truck rollout might be direct facility to facility for UPS or FedEx or a less than
truck load care. And the idea there is fully driverless, so potentially not even a driver in the truck.
It's just going from facility to facility empty zero occupancy.
Yeah, and those because that labor is expensive, you know, they don't keep those drivers out overnight,
those drivers do a run back and forth typically or in a team to go back and forth in one day.
So from the people you're spoken with so far, what's your sense? How far are we away from which scenario is closest and how far away
are we from that scenario of autonomy being a big part of our trucking fleet? Most folks are focused on
another scenario, which is the exit exit, right? Which looks like that urban truck boards thing
that I laid out earlier. So you have a human driven truck that comes out to a drop lot.
It meets up with an autonomous truck.
That truck then drives it on the interstate to another lot.
And then a human driver picks it up.
There are a couple variations maybe on that. So, or let me just run through the last two scenarios.
Sure.
The other thing you could do, right, is to say,
all right, I've got a truck that can drive itself.
And I prefer to this one as autopilot.
But, you know, you have a human drive it out to the interstate,
but rather than have that transaction where the
human driven truck detaches the trailer and gets coupled up to a self-driving truck,
they just, that human driver just hops on the interstate with that truck and goes and
back and goes off duty while the truck drives itself.
And so you have a self-driving truck that's not driverless, right?
And just to clarify, because Tesla uses a term autopilot
and so do airplanes and so everybody uses the word autopilot,
we're referring to essentially full autonomy,
but because it's exit to exit,
the truck driver is on board the truck,
but they're sleeping in the back or whatever.
Yeah, and this gets to the really weedy policy questions, right?
So basically for the Department of Transportation
for you to be off duty, for safety reasons,
you have to be completely relieved of all responsibility.
So that truck has to not encounter a construction site
or what inclement weather or whatever it might be
and call to you and say, hey,
or obviously we're imagining connected vehicles as well, right?
So you're in a self-driving truck, you're in the back and trucks 20 miles ahead experience some problem, right?
That may require tele-operation or whatever it is, right?
And it signals to your truck, hey, you know, tell the driver 20 miles ahead, he's, he's got a hop in the seat.
That would mean that they're on duty according to the way that the current rules are written. They have some responsibility. And part of
that is, you know, we need to get rest, right? They need to have uninterrupted sleep.
So that's what I call autopilot. The final scenario is one that I thought was actually
the one scenario that was good for labor. You know, which I, which I, I proposed is I'm like,
well here's an idea, you know,
that would be like actually good for workers.
And just another brief aside here.
The history of trucking over the last, you know, 40 years,
there's been a lot of technological change.
So when I learned to drive the truck,
I had to learn to manually shift it,
like I was describing.
You had to read these fairly complicated, you know,
big sets of laminated maps to figure out
where the truck can go and where it couldn't,
which is a big deal, you know.
I mean, you take these trucks on the wrong road
and you're destroying a bridge or you're doing a can opener,
which is where you try to drive it under a bridge too low.
You've probably seen that on YouTube, if not, you know. Check it out, you know, a bridge or you're doing a can opener, which is where you try to drive it under a bridge too low. You've probably seen that on YouTube,
if not, you know, check it out, you know, a truck can opener.
There's some bridges that are famous for it, right?
And there's one I think called the can opener,
and you can find on YouTube.
And you know, you had to log those hours like manually
and sort of do the math and plan your work routine. And I would
do this every day. It's like, okay, I'm going to get up at five. I've got to think about
Buffalo and there's traffic there. So I want to be through Buffalo by 630. And then that'll
put me in Cleveland at 930, which means I'll miss that rush hour, right, which is going to put me in Chicago,
you know, and so you do this. And now today, you know, 15 years later, truck drivers don't
have to do any of that. You know, you don't have to shift the truck, you don't have to map.
You know, you can figure out the least congested route to go on and your hours of service are recorded or a good portion of them are
reported
automatically all of that has been a substantial de-skilling that has you know put downward pressure on rage
It wages and allowed companies to kind of speed up monitor and direct and I mean the key technology
You know that I did work under is satellite linked computers
So before you could kind of go out
and plan your own work and the boss really couldn't see
what you were doing and push you and say,
you know, you bet on break for 10 hours,
why aren't you moving?
You know, and you might tell them, you know,
I'll cause I'm tired.
You know, like I didn't sleep well,
I've got to get a couple more hours.
You know, they're only going to accept that
so many times or at least some of those dispatchers are.
So all this technology has made the job sort of, you know, de-skilled the job.
You know, hurt drivers in the labor market made the work worse.
So I think the burden is really on the technologists who are like, oh, this will make truck driver
jobs better in sort of envisioned ways that it would.
It's like the burden's really a proof is really on you
to sort of really clearly lay out what that
is gonna look like because it's 30 or 40 years of history
suggests that technology into labor markets
where workers are really weak and cheap is what wins.
That new technology doesn't help workers
or raise their wages.
So lowers the bar eventually into versus skill.
Yeah.
So that's really interesting.
That's tough.
That's tough to know what to do with
because yeah, from a technology perspective,
you wanna make the life of the people
doing the job today easier.
Is that what you want?
No, but that, like, when you think about like what, exactly, because the reality is you
will make the, their life potentially a little bit easier, but that will allow the companies
to then hire people that are less skilled, get those people that were previously working there, fired or lower wages.
And so the result of this easier is a lower quality of life.
Yeah, as dark, actually.
I know.
I'm sorry.
But you were saying that was for you initially, the hopeful.
Oh no, so I'll get to that.
But one more thing, because this is not stopping, right?
And this is another interesting question about this automation.
I think Uber is an interesting example here where it's like, okay, if we had self-driving
trucks or a self-driving cars, we could automate what used to be taxi service.
There's a whole bunch of stuff that's already been automated, like the dispatching.
The dispatchers are already out of work in ride chair ride chair and the payment is already automated, right?
So so you have to automate steps like this. So you so you have to have you know that initial link to dispatch the truck
You have to have the you know the automated mapping and all so we're sort of done all this you know
incremental automation, right? That could make the truck
completely driverless
There's some important things happening right now
with the remaining good jobs.
So what you're really paying for when you get
a good truck driver is, you know, like I said,
you get those kind of local skills of like backing
and congested traffic.
Those, it's really impressive to watch
and there's some value on it certainly,
but it's relatively low value in the actual driving technique.
So you bump something back into the dock,
it might be a couple thousand dollars
because you ruin a canopy or something over a dock
or tear up a trailer.
What you really want those highly skilled
conscientious drivers, and that's really what it is,
and that's what computers are really good at is about being conscientious drivers. And that's really what it is. And that's what computers are really good at
is about being conscientious, right?
In the sense of like, they pay attention continually, right?
And how it was describing those long haul segments
where the driver, you know, just keeps out of the situations
that could become problematic.
And just they don't look at their phone.
I mean, they take the job seriously and they're safe.
And you can give somebody a skills test, right?
In, you know, as a CDL examiner,
you could take them out and say,
all right, I need you to go to all these cones
and like drive safely through this school zone.
But what really proves that you're a safe driver
is two years without an accident, right?
Because that means that day after day,
hour after hour, mile after mile, you did the right thing, right?
And not when it was like, oh, some situations
emerging, but just consistently over time
kept yourself out of accident situations.
And you can see this with drivers who are, you know,
a million or two million safe miles.
The value of those drivers for Walmart
is they don't run over minivans.
The company I worked for, they ran over minivans on a regular basis.
So when I was trained, they said, we killed 20 people a year.
We send someone to the funeral.
There's a big check involved.
Don't be that.
We don't want to go to your funeral and you don't want to be the person who Who caused that funeral
Okay, so they they just write that off
Okay, they're that's just part of the business model now
Forward collision avoidance
can
You know basically eliminate the vast majority of those accidents
That's what the value of a really expensive
conscientious driver is based on.
They don't run over many vans.
So as soon as you have that forward collision avoidance,
what's gonna happen to the wages of those drivers?
By way of a therapy session,
help me understand,
is collision avoidance,
automated collision avoidance systems?
Are they good or bad for society?
Yeah, I mean, you know, this, this is, they're good.
Right?
They're good.
But in what do we do about the pain of a workforce in the short term?
Because their wages are going to go down because the job
starts requiring less and less skill.
Is there a hopeful message here where other jobs are created?
So I'm a sociologist, right?
So I'm going to think about what's the structure behind that that creates that pain, right?
And it's ownership, right? We don't call it capitalism for nothing.
You know, what capitalists do is they figure out
cheaper, more efficient ways to do stuff
and they use technology to do that oftentimes, right?
This is the remarkable history of the last couple centuries
and all the productivity gains is, you know,
people who were in a competitive market saying,
if I have to do it, right, I don't have a choice
because like my competitor over there
is gonna eat my lunch if I'm not on my game.
I don't have a choice.
I've gotta invest in this technology
to, you know, make it more efficient, make it cheaper.
And what do you look for?
You look for oftentimes. You look for labor you look for? You look for oftentimes.
You look for labor costs.
You look for high-value labor.
If I can take a hundred,
a lot of these truck drivers make good money.
$100,000, good benefits, vacation, retirement.
If I can replace them with a $35,000 worker
when I'm competing with maybe a low-wage retail employer
rather than some other more expensive employers
for skilled blue collar workers, I'm gonna do that.
That's what we do.
And so I think those are the bigger questions
around this technology, right?
Is like, our workers gonna get screwed by this?
Yeah, most likely, That's what we do.
So one of the things you say is, I mean, first of all, the numbers of workers that will
feel as pain is not perhaps as large as the journalists kind of articulate, but nevertheless,
the pain is real.
And I guess my question here is, do you have an optimistic vision about the transformative effects of autonomous trucks on society?
Like, if you look 20 years from now, and perhaps see, maybe 30 years from now, perhaps see these autonomous trucks doing the various parts of the scenario as you listed, and there are just hundreds of thousands of them,
parts of the scenarios you listed and there's just hundreds of thousands of them, just like veins, like blood flowing through veins on the interstate system. What kind of world do you see that's
a better world than today that involves its trucks? Yeah. Can I defend myself first because I can I'm reading the comments right now yes of people
You know of the economists who are telling you're a commenter
Dear PhD economics. Yes
Yes, dear PhD in economics. I know that that higher skilled jobs are created
You know by by technological advancement, right? I mean there are big questions about how many of them right?
So the idea that we would create more
expensive labor
positions, right, with a new technology, right? You better check your business plan. If your idea is to take, you know, a bunch of low
low-wage labor and replace it with the same amount of high-wage labor, right?
So there's a question about how many of those jobs. And there's the really important social and political question of, are they the same people?
And do they live in the same places?
And I think that kind of geography is a huge issue here with the impacts, right?
Lots of rural workers.
Interesting politically, lots of red state workers, right?
Lots of blue state, maybe union folks who are going to try to slow autonomy and lots of red state, you know, representatives in the house,
maybe, who want to, you know, stand up for their, for their trucker constituents. So just, just to
defend myself. Yeah, and to elaborate, I think economics as a field is not good at measuring the
landscape of human pain and suffering. So, you know, sometimes you can forget in the numbers that it's realized that it's
take.
That's what I suppose sociology is better at doing.
So sometimes, sometimes, the problem with, I mean, I'm somebody who loves psychology and
psychiatry and a little bit, I guess, of sociology.
I realize how little, how tragically flawed the field is, not because of lack of trying,
but just how difficult the problems are.
To do really thorough studies that understand the fundamentals of human behavior, and this
landscape of human suffering, it's almost an impossible task without the data, and we
currently don't, you know, not everybody's richly integrated to where they're fully connected and all
of their information is being, like, recorded for sociologists
to study. So you have to make a lot of inferences. You have to
talk to people, you have to do the interviews that you're
doing. And through that, like, really difficult work, try to
understand, like, hear the music that nobody else is hearing, the music of like what
people are feeling, their hopes, their dreams, and the crushing of their dreams due to some
kind of economic forces.
Yeah.
I mean, we've just lived that for four and a half years of probably, you know, elites,
let me just go out on a limb and say, not understanding the sort of emotional and psychological
currents of a large portion of the population, right?
And just being stunned by it and confused, right?
Wasn't confusing for me after having talked to truckers, again, who trucking is a job
of last resort.
These are people who've already lost that manufacturing job oftentimes, already lost
that construction job to just aging. So what can we do? What's sort of the positive
vision? Because we've got tons of highway deaths. The big picture is, and this is the opportunity
I guess for investors, it's a hugely inefficient system.
So we buy this truck.
There's this low wage worker in it oftentimes.
And again, I'm setting aside those really good line haul jobs and LTL.
Those are different case.
That low wage worker is driving a truck that they might, the wheels might roll seven to
eight hours a day.
That's what the truck is designed to do, and that's what makes the money for the company.
In other seven, eight hours a day, the drivers do and other kinds of work that is not driving.
And then the rest of the day, they're basically living out of the truck.
You really can't find a more inefficient use of an asset than that, right?
Now big part of that is we pay for the roads and we pay for the
rest areas and all this other stuff. So the way that I work and the way that I think
about these problems is I try to find analogies, labor processes and things that make economic
sense that seem in the same area of the economy, but have some different characteristics for workers, right?
And sort of try to figure out,
why does the economics work there?
Right, and so if you look at those really good jobs,
the most likely way that you as a passenger car driver
would know that it's one of those drivers
is that they're multiple trailers, right? So you see these like maybe it's three small trailers, maybe it's one of those drivers is that there are multiple trailers. Right.
So you see these like maybe it's three small trailers, maybe it's two sort of medium-sized
trailers, some places you might even see two really big trailers together.
You do that because labor is expensive, right.
And it's highly skilled.
And so you use it efficiently and you say, all right, you know, rather than having you,
you know, haul that little trailer out of the ports, you know, that sort of half size container,
we're gonna wait till we get three
or we're gonna coordinate the movement
so that they're three ready.
You go do what truckers call make a set,
put them together, right, and you go.
That's a massive productivity gain, right?
Because, you know, you're hauling two, three times
as much freight.
So the positive scenario that I threw out in 2018 was why not
have a human driven truck with a self-driving truck that follows it, right, just a drone unit.
And it was, you know, to me, this seemed as a, you know, non-computer scientist,
a sociologist, right? This made a lot of sense because when I got done talking to the computer scientists
and the engineers, they were like, well, it's like object recognition, decision making,
algorithm, all this stuff, it's like, all right, so why don't you leave the human brain
in the lead vehicle, right?
You got all that processing and then all that following, now again, this is sort of me
being a lay person.
You know, I said, why don't, you know,
then that following truck, right,
takes direction from the front,
it uses the rear of the trailer as a reference point.
It maintains the lane, you've got cooperative adaptive,
cruise control, and that you double the productivity
of that driver.
You solve that problem that I hated
in my, you know, urban truck ports thing about the bridge weight
because when you get to the bridges, the two trucks can just spread out just enough to make
the bridge weight, and you can just program that in, and they're 50 feet further apart,
100 feet further apart.
So interesting sort of, I think, story this that that leads to kind of I think the policy questions
in I guess 2017 Jack read and Susan Collins and you know requested from the Senate the Senate requested
Research on what the impacts of self-driving trucks would be and the first stage of that was for the GAO to
be. And the first stage of that was for the GAO to do a report, sort of looking at the lay of the land, talking to some experts. And I was working on my 2018 report, help contribute
to that GAO report. And you know, I had the six scenarios, right? I'm like, okay, you know,
here's, here's what Star Skies doing, you know, here's what in Bark and Uber doing, you know, here's what Waymo might be doing. No, nobody really knows, right?
Here's what Peloton's doing. You know, here's the autopilot scenario. And then here's this one that I
think actually could be good for drivers. So now you've got that driver who's got two, you know,
two times
the freight. Their decisions are more important. They're managing a more complex system, right?
They're probably going to have to have some global understanding of how to, you know,
the environments of which it can operate safely. Right. Now we're talking upskilling, right?
And so, you know, that the GAO, you know, sort of writes up these different scenarios and the idea is that it's going
to prepare for this Department of Transportation, Department of Labor, set of processes to engage
stakeholders and sort of get industry perspectives and then do a study on the labor impacts.
So that DOT, DOOL process starts to happen.
And I get to the workshop and a friend
was sitting at the table next to me,
and he holds up the scenarios
that they're gonna have us discuss at this workshop.
And he's like, hey, these look really familiar.
Is there were the scenarios from the report,
but there were only five instead of six.
Interesting. The six scenario, which was the upskilling labor good for worker scenario,
wasn't discussed. So to clarify that the integral piece of technology there's platooning.
Yeah, I mean, in a sense, it's platooning, but in fairness, as I pitched that idea, or so ran that idea
by the computer scientists and engineers that I would, and product managers that I would
talk to, they would say, you know, we thought about that, but that following truck, it's
not that simple.
You know, that thing, basically, we had to engineer that to be capable of independent
self-driving, because what if there was a cut-in, or any number of scenarios in which it lost
that connection to the lead truck for whatever reason?
Now, I mean, I don't know.
Oh, who? Platooning is hard. There's edge cases. I guarantee the number of edge cases in platooning is orders of magnitude lower than the number of edge cases in the
general solo full-cell drive. You do not need to solve the full-cell driving
problem. I mean if you're talking about probability of dangerous events, it
just seems with platooning that like you can deal with cut-ins.
Yeah, so this is beyond this is one of the challenge obviously of being a researcher who
doesn't really have any background in the technology, right? So I can dream this up.
I don't know the idea if it's feasible.
Well, let me speak to the PhDs in economics. Let me speak to the PhDs in computer science.
If you think platoonings as hard as the full cell
varying problem, we need to talk.
Because I think that's ridiculous.
I think platooning, in fact, I think
platoonings an interesting idea for write sharing as well.
For the general autonomous driving problem, not just trucking,
but obviously trucking is the big, big benefit.
Because the number of A to B points in trucking is much, much lower than the general right-chairing problem.
But anyway, I think that's a great idea, but you're saying it was removed.
Yeah.
And so you can go, you know, and listeners could go to these reports.
They're publicly available.
And they explain why in the footnote.
And you know, they note that there was this other scenario suggested by at least me and I can remember
they said someone else did too.
But they said, we didn't include it because no developers were working on it.
Interesting.
Full disclosure, that was the approach that I took in my research, which was to go to
the developers and say,
what's your vision, right?
What are you trying to develop?
That's what I was trying to do.
And then I tried to think outside the box at the end by adding that one, right?
Here's one that I have.
People aren't talking about that could be cool.
Now again, it had been proposed in like 2014 for like fuel convoys.
So you could just have like one super armored lead fuel
truck, right, in a, you know, bringing fuel to forward operating bases in Afghanistan.
And then you wouldn't need, you know, the super heavy, you know, you wouldn't have to protect the
human life and the following truck. So that's interesting. You're saying like when you talk to
Waymo, when you talk to these kinds of companies, they weren't at least openly saying they're working
on this. So then that doesn't make sense to include in the list.
Yeah.
And so, but here's the thing, right?
This is the Department of Transportation, right?
And the Department of Labor.
Maybe they could consider some scenarios.
Like, maybe we could say, you know, this, we, this technology has got a lot of potential.
Here's what we'd like it to do.
You know, we'd like it to reduce highway deaths, help us fight climate change, reduce congestion, you know, all these other things, but that's
not how our policy conversation around technology is happening. We're not, and people don't think
that we should. And I think that's the fundamental shift that we need to have, right?
I've been involved with this a little bit like NITSA and DOT. The approach they took is saying, we
don't know what the heck we're doing, so we're going to just let the innovators do their
thing and not regulate it for a while to just to see. You think DOT should provide ideas
themselves.
Well, so this is the great trick in policy of private actors is you get narrow mandates for government
agencies, right?
So, you know, the safety case will be handled by organizations whose mandate is safety.
So the federal motor carrier safety administration, who is, you know, going to be a key player,
I argue in an article that I wrote, you know, they're going to be a key player, I argue in an article that I wrote,
they're gonna be a key player
in actually determining which scenario is most profitable
by setting the rules for truck drivers.
Their mandate is safety, right?
Now they have lots of good people there
who care about truck drivers
and who wish truck drivers jobs were better.
But they don't have the authority to say,
hey, we're going to write this rule
because it's good for truck drivers, right? And so when you, you know, we need to say,
you know, as a society, we need to not restrict technology, not stand in the way of things.
We need to harness it towards the goals that matter, right? Not whatever comes out the
end of the pipeline because it's the easiest thing to develop
or whatever is most profitable for the first actor
or whatever, but, you know, and we do,
the thing is we do that, right?
I mean, like when we sent people to the moon,
you know, we did that.
And there were tremendous benefits
that followed from it, right?
And we do this all the time in, you know,
trying to cure cancer or whatever it is, right? I mean, we can do this, right? Now, the interesting sort of epilogue to that
story is, you know, six months or so, I don't know how long it was, after those meetings in which
that sixth scenario was not considered a company called Locomation.
Ends up using that, essentially that basic scenario
with a slight variation.
So they leave the human driver in both trucks
and then that following driver goes off duty.
And then I've been trying to think of what the term is.
They kind of, I think of it as like sling-shotting.
They sort of, when one runs out of hours,
the one who's off duty goes front.
And so if only they had been around six months earlier,
that it might have been considered by the OT,
but it just says who has the authority
to propose what these visions of the future are?
Well, some of it is also just a company stepping up
and just doing it, screw the authority,
and showing that it's possible,
and then the authority follows.
So that's why I really love innovators in the space.
The criticism I have, the very sort of real,
I don't know, harsh criticism I have
towards autonomous vehicle companies in the space is they've gotten culturally
They've it's been it's become acceptable somehow
To do demos and videos as opposed to the old school American way of solving problems
There's a culture in Silicon Valley
where you're talking to VCs
that have lost that kind of love of solving problem.
They kind of like envision,
if the story you told me in your PowerPoint presentation
is true, how many trillions of dollars
might I be able to make?
There's something lost in that conversation
where you're not really taking on the problem in a real way.
So these autonomous vehicle companies realize
we don't need to, we just need to make nice PowerPoint
presentations and not actually deliver products
that like everybody looks outside and says,
holy shit, this is life changing.
This where I have to give props to Waymo
is they put driverless cars on the road
and like forget PowerPoint slide presentations,
actual cars on the road, then you can criticize like,
is that actually going to work?
Who knows, but the thing is they have cars on the road.
And that's why I have to give props to Tesla.
They have whatever you want to say about risk and all those kinds of things.
They have cars on the road that have some level of automation.
And soon they have trucks on the road as well.
And that kind of that component, I think, is an important part of the policy conversation
because you start getting data from these companies that are willing to take the big risks.
As opposed to making
slide decks, they're actually putting cars on the road and like real lives are a stake
that could be lost and they could bankrupt the company if they make the wrong decisions.
And that's deeply admirable to me. Speaking of which, I have to ask Waymo trucks, I think it's
called Waymo via. So I'm talking to the head of trucking at Waymo.
I don't know if you got any chance to interact with them.
What's a good question to ask the guy?
What's a good question of Waymo?
Because they seem to be one of the leaders in the space.
They have the zen-like calm of like being willing
to stick with it for the long term
in order to solve the problem.
Yeah, and I guess they have that luxury, right?
Which I don't think I,
if I had another life as a researcher,
I would love to just study the business strategies
of startups and Silicon Valley sort of structure.
Would you consider Waymo startup?
No, no, no, right.
I mean, it's at least not in the things
that seem to matter in the self-driving space.
So you mentioned the demos.
And I don't have enough data as a sociologist
to really say like, oh, this is why they do what they do.
But my hypothesis is, there's a real scarcity of talent
and money for this. And there's a real scarcity of talent and money for this.
And there certainly was a scarcity of like partnerships with OEMs and, you know, the big trucking
companies.
And there was a race for it, right?
And the way that if you don't have, you know, the backing of alphabet, you do a demo,
right?
And you get a few more good engineers who say, hey, look, they did that cool thing.
Like Anthony Lewandowski did with Otto
and then what resulted in the Uber purchase of that program.
So what would I ask?
I mean, I think I would ask a lot of questions,
but I think the market is-
Well, there's also on record and off record conversations
which unfortunately, I'm asking for an on-record conversation.
And that I don't know if these companies are willing to have interesting on-record conversations.
Yeah. I assume that, like, there are questions that I don't think you'd have to ask.
Like, I assume they're going to be actually driverless, right? They're not going to
like keep the driver in there. So, I mean, for the industry, I think it would be interesting to know where they see that first adopter,
right? Oh, you mean from like the scenarios that laid out which one are they going to
take on? Yeah, I mean, because that's going to, again, it's those really expensive good
jobs, right? So those LTL jobs, the like UPS jobs. Now that's going to be, that's where labor is too,
right? That's where the teamsters are. That's where the only place they are left, right? So that's
the, that's going to be the big fight on the hill and public, if labor can muster it, right? I don't
know. There's a really cool, one thing I would recommend to you and your ear listeners, if you
really want to see a remarkable page
in sort of the history of labor and automation. There's a report that Harry Bridges, who was
the socialist leader of the Longshoremen on the West Coast, and just galvanize that union,
and they still control the ports today because of this sort of vision that he laid down.
today because of this sort of vision that he laid down. In the 1960s, he put out a photo journal report called Men in Machines.
And basically what it was was it was an internal education campaign to convince the membership
that they had to go along with automation.
Machines were coming for their jobs.
And what the photo journal, it's almost like a hundred pages or something like that,
is like, here's how we used to do it. Some of you old timers remember it. Like, we used to take the
barrels olive oil and we'd stack them in the hold and we'd roll them by hand and we'd put the
timber in and we'd, you know, stack the crates tight, you know, and that was the pride of the Long
Shormon was a tight stow. And now you all know, you know, there are cranes that come down and there's no
longer any, you know, rope slings and or load and bulldozers into the hole to push the ore up into
piles and then clamshells are coming down and he made this case to them and he said, this is why
we're signing this agreement to basically allow the employer to automate.
And we're gonna lose jobs,
but we're gonna get a share of the benefits.
And so our wages are gonna go up,
we're gonna continue to control the hiring
and training of workers.
Our numbers are gonna go down,
but basically that last son of a bitch
who's working at the ports,
gonna be one really well paid son of a bitch.
You know, I mean, he just be one standard, but he's going to love his job.
You should check out that report.
You know, that's an interesting vision of a future that probably still holds.
That is, I mean, there is some level to which you have to embrace the automation.
Yeah, I mean, and who gets, you know, it's the benefits, right?
It's like, let me think of the public dollars that went into developing self-driving vehicles in the early days, right? Not just the vision of it, right?
Which was a public vision to take soldiers out of harm's way. But a lot of money.
And there's some way, if you are a business that's leveraging that technology, from a broad
that technology from a broad historical, ethical perspective, you do owe it to the bigger community to pay back, like, for all the investment that was paid to make that technology
a reality.
In some sense, I don't know how to make that right. On one, there's pure capitalism, and then there's communism,
and I'm not sure.
I'm not sure how to get that balance right.
You know, I don't have all the answers in here.
And I wouldn't expect individual private companies
to kind of kick back, right?
That's capitalism doesn't allow that, right?
Unless you have a huge monopoly, right?
And then you can, on the backside,
create music halls and libraries and things like that.
But, you know, here's what I think, you know,
the basic obligation is, is, you know, come to the table
like and have an honest conversation with the policymakers,
with the truck drivers, you know,
with the communities that are at risk.
Like at least let's talk about these things,
you know, in a way that doesn't look like
the way lobbying works right now.
Where you send a well-paid lobbyist to the Hill
to, you know, convince some representative or senator
to stick a sentence or two in that favors you into the,
like, to have a real conversation.
Real human conversation.
Can we just do that?
Yeah.
Don't play games.
Real human conversation.
Let me ask you, mention autopilot.
Gotta ask you, Walt Tesla, this renegade little company
that seems to be, if from my perspective,
revolutionizing autonomous driving or semi-autonomous driving or at least the problem of
perception and control
They've got a semi on the way they got a truck on the way. What are your thoughts about Tesla semi?
You know, I am and I did have some very preliminary conversations with
I did have some very preliminary conversations with policy folks there. Nothing really in the tech or business side of it too much.
And here's why.
I think because electrification and autonomy run in opposite directions.
And I just, I don't see the application, the value in self-driving for the truck that
Tesla is going to produce
in the near term.
You know, you're not going to have the battery.
Now, you could have wonderful safety systems and reinforcing the auto, self-driving features
supporting a skilled driver, but you're not going to be able to pull that driver out for
long stretches the way that you are with driverless trucks.
So, do you think, I mean, the reason, the electrification is not obviously coupled with the automation.
They have a very interesting approach to semi-autonomous pushing towards autonomous driving.
It's very unique. No light hour, no no radar. It's computer vision alone. From a large,
they're collecting huge amounts of data from a large fleet. It's an interesting unique
approach. Bold and fearless in this direction. If I were to guess whether this approach
would work, I would say no. Let's start it. One, you would need a lot of data and two, because
you have actual cars deployed on the road using a beta version of this product, you're going
to have a system that's far less safe. You're going to run into trouble.
It's horrible PR.
Like, it just seems like a nightmare.
But it seems to not be the case, at least up to this point.
It seems to be not, you know, unpar, if not safer.
And it seems to work really well in human,
the human factors somehow manages, like drivers still
pay attention.
Now, there's a selection of who is inside the Tesla autopilot user base.
There could be a self-selection mechanism there.
However, it works.
These things are not running off the road all the time.
It's very interesting whether that can creep into the trucking space. Yes, at first the long haul problem
is not solved. They need to charge, but maybe you can solve, you know, a lot of your scenarios
involved small distances. And you know, that last mile aspect, which is exactly what Tesla is trying to solve for the regular passenger
vehicle space, is the city driving. It's possible that you have these trucks. It's almost like,
yeah, you solve the last mile delivery part of some of the scenarios that you mentioned
in autonomous driving space. Do you think that's from the people you spoke with to difficult to have a problem?
The thing that keeps me so interested in this space and thinking that it's so important
is again that efficiency question, that safety question, and the way that these economics
can push us potentially
toward a more efficient system.
So I wanna see those Tesla electric trucks
running out to those truck ports
where you've got those two trucks
with a human driver in front.
I think that's now what's powering those is an hydrogen.
I mean, again, it's very interesting as a researcher who just're just not up a background in technology. It doesn't have a, it have a horse, you know,
in this race. I mean, you know, for all I know, self-driving trucks will ultimately be achieved
by some biomechanical sensor that uses echolocation because we took stem cells of bats and...
Right. You know, I mean, I don't, I don't, I am completely unable to assess who's, you know, who's that or who's behind
or who makes sense.
But I think one key component there, and this is what I see with Tesla often, and it's
quite sad to me that other companies don't do this enough, is that first principles thinking,
like, well, wait, okay, it's looking at the inefficiencies as opposed to I worked with quite a few car companies and they basically have a
lot of meetings this is a lot of meetings and the discussion is like how can we
make this cheaper this cheaper this cheaper this component cheaper this cheaper
the cheaper the cheapification of everything just like you said as opposed to
saying wait a minute let's step back.
Let's look at the entirety of the inefficiencies in the system.
Like why have we been doing this like this for the last few decades?
Like start from scratch, can this be 10X, 100X cheaper?
Like if we not just decrease the cost of one component here or this component here or
this component here, but like here, or this component here.
But like, let's redesign everything.
Let's infrastructure.
Let's have special lanes.
Or in terms of truck ports, as opposed to having regular human control truck ports,
have some kind of weird like sensors, like where everything about the truck connecting at that
final destination is automated fully from the ground up, you build the
facility from the ground up for the autonomous truck. All those kinds of
sort of questions are platooning. Let's say, wait a minute, okay, I know we think
platooning is hard, but can we think through exactly why it's hard and can we actually solve it?
Like if we collect a huge amount of data, can we solve it?
And then tell the operation, like, okay, yeah, it's difficult to have good signal, but can we actually, can we have, can we consider the
The probability of those edge cases and what to do in edge cases when the tail operation fails.
Like, how difficult is this?
What are the costs?
How do we actually construct a teleoperative center
full of humans that are able to pay attention
to a large fleet where the average number of vehicles
per human is like 10 or 100?
Having that conversation as opposed
to having you show up to work and say, all right,
it seems like, you know, because of COVID,
we are not making as much money, can we have a cheaper,
can we give less salary to the trucker,
and can we build like decreased the cost,
or decreased the frequency at which we buy new trucks.
And when we do buy new trucks, make them cheaper by making them crappier, like this kind
of discussion.
This is why, to me, it's like Tesla is like rare on this.
And there's some sectors in which innovation is part of the culture.
In the automotive sector for some reason, it's not as much.
This is obviously the problem that Ford and GM are struggling with it's like they're really good at making cars at scale cheap
And they're like legit good like Toyota at this there's some of the greatest manufacturing people in the world, right?
That's incredible
But then when it comes to hiring software people they're horrible so
It's culture and then it's such a difficult thing for them to sort
of embrace, but greatness requires that they embrace this embrace whatever is required to remove
the inefficiency from the system. And that may require you to do things very differently you've
done in the past. Yeah, I mean, there are certain things that the market can do well in my, you
know, this is how I see the world, right? Is, you know, and they're, that's the best way
to, to organize certain kinds of activities is the market and, and private interest. But
I think we go too far in, in some areas. Transportation is, if we can't have a public debate about the roads that we all pay for,
you forget about it in private factories and all these other healthcare and other places,
it's going to be way harder there. A healthcare I guess has some direct contact with the consumer
where we're probably going to have lots of sort of hands-on public policy about you know concerns around patient rights and things like that but
If we can't figure out how to have a public policy conversation around how technology is going to reform our public
You know roadways and our transportation system like you know
We're really leaving way too much to private companies. It's just, it's not,
it's not in there. I get asked this question, like, what should companies do? And I'm like,
just go about doing what you're doing, you know? I mean, please come to the table and talk about it,
but it's not their role. I mean, I appreciate, you know, Elon's, you know, attempts to,
have species level goals, you know, like, oh, good,
wait, we're going to go to Mars.
I mean, that's amazing.
And that's incredible that that someone can realize, you know, that, you know, have a
chance at realizing that vision.
It's amazing, right?
But when it comes to so many areas of our economy, you know, we can't wait for a hero.
You know, we have to have, and there are way too
many interests involved. It's who builds the roads. The money that sloshes around on
Capitol Hill to decide what happens in these infrastructure bills and the transportation
bill is just obscene.
Right?
I think it's an interesting view of markets, correct me if I'm wrong, let me propose
a theory to you.
That progress in the world is made by heroes and the markets remove the inefficiencies
from the work the heroes did.
So going to Mars from the perspective of markets probably has no value.
Maybe you can argue it's good for hiring to have a vision or something like that.
But those big projects don't seem to have an obvious value.
But our world progresses by those big leaps.
And then, after the leaps are taken, then the markets are very good at removing sort of
inefficiencies. But it just feels like the autonomous vehicle
space and the autonomous trucking space requires leaps. It doesn't
feel like we can sneak up into a good solution that is ultimately
good for labor, like for human beings in the system. It feels
like some like a probably a bad example, but like a Henry IV type of character
steps in and say like, we need to do stuff completely differently.
Yeah, and you just said we can't hope for a hero, but it's like, no, but we can say we need a hero.
We need more heroes. So if you're a young kid right now listening to this, we need you to be a hero
It's not like we need you to start a company that makes a lot of money. No, you need to start a company that makes a lot of money so that you can
Feed your family as you become a hero and take huge risks and potentially go bankrupt
Those risks is how we move society forward. I think maybe there's a romantic view. I don't know. I totally disagree
He is a great god damn it. I don't know. I totally disagree.
You disagree.
God damn it.
I mean, I, and I'm the two of us, you're the knowledgeable one.
No, no, no, I think it's a, it's a matter of like, do we need
those heroes?
Absolutely.
I mean, I, I, I saw the, you know, the boosters come down from
SpaceX's rockets and, nearly simultaneously with my kids
after school one day.
And I thought, oh my god, this is science fiction has been made real.
It's incredible.
And it's a pinnacle of human achievement.
It's like, this is what we're capable of. But we need to have that those heroes oriented,
we need to allow them, right,
to orient toward the right, toward the goals, right?
We've got a climate change, you know?
I mean, all the heroes out there, right?
I mean, it's time, the clock is ticking.
It's past time. I've been working on climate change issues since, you know, the mid 90s.
Like, I still remember the first time in 2010 when I got a grant to that was completely focused on adaptation rather than prevention. And just when it hit me, that like, wow,
like, we had a bunch of preventions like acceptance that there's going to be catastrophic impact.
We just need, we need to figure out how to, we at least live with that. Yeah. And,
you know, the grant was like, okay, our agriculture system is going to move. Our bread basket is no longer going to be California, it's going to be Illinois. What does that
mean for truck transportation? So it's like, so in terms of a big philosophical societal
level, that's kind of like giving up. Yeah. In terms of the big heroic actions. Yeah.
You know, failures in human history. Yeah, that's going to be, let's hope not the biggest, but could be.
Do you? So, let me say why I disagree, right? Henry Ford, amazing, right, to sort of mass-produce cars,
right? Dymler to put that first truck on the road without the roads, right? So there's, like, we need
that innovation. There's no doubt about it, and there's there are roles for that. But there's big public stuff that that that sets the stage. It's
critical. And, you know, and what it really is, it's a, it's a soci, it's a sociological
problem. It's a political problem. It's a social problem. We have to say, and we have
these screwed up ideas, right? So we have this politics right now where like everybody feels like they're getting screwed
and someone undeserving is benefiting.
When in fact, like, you know, at least in the middle, right?
They're huge.
I used to teach this course in Rich and Poor,
you know, an economic inequality.
And I would go through, you know,
public housing subsidies in Philadelphia,
you know, section eight subsidies, you know, and then I would go
through my housing subsidies for my mortgage interest deduction. And it worked out to basically
the average payment for a section eight housing voucher in my neighborhood. I'm not a welfare
recipient, according to the dominant discourse. And so we have this completely screwed up sense
of like where our dollars go
and who benefits from the investment.
And we need to, I don't know that we can do it,
but if we're gonna survive,
we need to figure out how to have honest conversations
where private interest is where we need it to be
in fostering innovation
and rewarding the people who do incredible things.
Please, we don't want to squash that, but we need to harness that power to solve what I think
are some pretty big existential problems.
So you think there's like government level, national level, collaboration required for infrastructure project?
Like there's, we should really have large moonshot projects
that are funded by our governments.
At least guided by.
I mean, I think there are ways to finance them
and you know, all the other things.
But we, yeah, you gotta be careful, right?
Cause that's where you get all these sort of perverse,
you know, unintended consequences and whatnot.
But if you look at transportation in the United States,
and it is the foundation of the, you know,
manifest destiny, economic growth, right,
that built the United States into the world superpower
that it became and the industrial power
that it became it rested on transportation.
It was like, the Erie Canal, I grew up a few miles from where they dug the first shovel
full of the Erie Canal and everyone thought it was crazy.
But those public infrastructure projects, the canals, the railroads, yeah, they were privately
built, but they wouldn't have been privately built without, you know, Lincoln funding them essentially and giving, you know, the railroads, you know,
land in exchange for building them. The highway system, the Eisenhower high, the payback that
the US economy got from the Dwight D. Eisenhower interstate system is phenomenal, right? No private entity was going to do that, no electrification, dams, water, you know, we need
to do this infrastructure.
Yeah.
Infrastructure.
And now more than ever, it's been really upsetting to me on the COVID front.
There's one of the solutions to COVID, which seems obvious to me, from the very beginning
that nobody is
opposed to, is one of the only bipartisan things at home testing, rapid at home testing.
There's no reason why at the government level we couldn't manufacture hundreds of millions of
tests a month. There's no reason starting in May 2020. And that gives power to a country that values freedom, that gives power information
to each individual to know whether they have COVID or not.
So it's possible to manufacture them for under a dollar.
It's like an obvious thing.
It's kind of like the roads.
It's like everybody's invested.
Let's put countless tests in the hands of every single American citizen, maybe
every citizen of the world.
The fact that we haven't done that today, and there's some regulation stuff with the
FDA, all the kind of dragon of feet, but there's not actually a good explanation except our
leaders, and culturally we've lost the sort of, not lost, but it's a little bit dormant.
The will to do these big projects that better the world.
I still have the hope that when faced with catastrophic events, the more dramatic, the more
damaging, the more painful they are, the higher
will rise to meet those. And that's where the infrastructure style projects are really important.
But it's certainly a little bit challenging to remain an optimist in the times of COVID
because the response of our leaders has not been as great and as historic as I would have hoped. I would hope that the
actions of leaders in the past few years in response to COVID would be ones that are
written in the history books. And we talk about it as we talk about FDR, but sadly I don't
know. I think the history books will forget this for the actions of our leaders. Let me just to wrap up autonomy.
When you look into the future, are you excited about automation in the space of trucking? Is it, you know, when you go to bed at night, do you
see a beautiful world in your vision that involves autonomous trucks? Like all the truckers
you've become close with, you've talked to, do you see a better world for them because
of autonomous trucks? Damn you, Lex.
You know why?
Because I mean, I want to be an optimist, you know?
And I want to think of myself, I guess, as a half glass full kind of person.
But you know, when you ask it like that, and I think about, you know, like, when I look
at the challenges to harnessing that for just let's take just labor and climate,
there are other issues, congestion, etc.
That are going to be affected by this, again, those big transformational issues.
I think it's going to take the best of us. Like it's going to take the best of our
policy approaches. It's going to take, you know, we need to start investing in
building those, in rebuilding those institutions. I mean, that's what we've seen in the last four
years, right? And, and the erosion of that was so clear among these truck drivers. Like, you know, when Trump, you know, came in and said, like, you know, free trades, good
for workers, like, yeah, right, you know, I grew up in the rust belt, you know, I watched
factory after factory close. All of my ancestors worked at the same factory. It's still holding
on by a thread. Like, you know, the Democratic party told, you know,
blue collar workers for years, I don't worry about,
you know, free trade, it's not bad for you.
And I know the economists will probably get in the comment box
now, you know, about how it happens.
We'll look forward to your comments.
We'll look forward to your comments
about how free trade benefits everybody.
But, you know, immigration, you know, you go and I'm, you know, I think immigration
is great. The United States benefits from it tremendously, right? But there are costs, right?
Go down to South Philadelphia and find a drywaller and tell him that immigration hasn't heard him,
right? You know, go, go to these places where there's competition.
And yes, we benefit overall, but we have a system
that allows some people to pay really high costs.
And Trump tapped into that.
And there was no, there was no, that's more than that, too, obviously.
And there's lots of really dark stuff that goes along with it,
the sort the racialization
of others and things like that.
But he hit on those core issues that if you were to go back over my trucking interviews
for 15 years, you would have heard those stories over and over and over again, that sense
of voicelessness, that sense of powerlessness, that sense that there's no difference between
the Democrats and the Republicans because they're all going to screw us over.
And that was there.
And you just ignore it as long as you want and tell people don't worry trades, good for
you, don't worry immigration is good for you.
As their communities lose factories and I mean a lot of them were lost to the South before
they were lost to overseas, whatever, but tapped into that.
And there's a fundamental distrust of,
you know, you look at these like,
pupils on like, you know,
whether people trust the media, right?
But whether or not they trust higher education,
you know, these institutions that I find magical, right?
I mean, you look at the vaccine research and stuff,
you know, just brilliant, you know, people
doing incredible things for humanity. Like, you know, people doing incredible things for humanity.
Like, you know, the idea that like, you know, we can, we can take these viruses that, you know,
used to ravage through the human population and that we had to be terrified of.
And, you know, we've, you know, we've suffered, but, you know, we have such power now to,
to defend ourselves, right, behind these programs, right?
And to see those, people will be like,
I'm not sure if higher education's good for the country
or not, it's like, where are we?
So we need to rebuild the faith
in the trust in those institutions and have these,
but we need to have honest conversations
before people are gonna buy it.
You know?
Do you have ideas for rebuilding the trust
and giving a voice to the voice or so.
Is the, many of the things we've been talking about is so deeply integrated.
You think like, this is the trouble I have with people that work in AI and autonomous vehicles
and so on.
It's not just a technology problem.
It's this human pain problem.
It's the robot essentially silencing the voice of a human being because it's lowering their
wage, making them suffer more, and giving them no tools of how to escape that suffering.
Is there something...
I mean, it even gets into the question of meaning, you know, so money
is one thing.
But it's also what makes us happy in life.
You know, a lot of those truckers, the set of jobs they've had in their life were defining
to them as human beings. And so, and the question with automation is, is not just how do we have a job that gives
you money to feature family, but also a job that gives you meaning, that gives you pride. And for me, the hope is that AI and automation will provide other jobs that will be a source
of meaning.
But the couple with that hope is that there will not be too much suffering in the transition.
And that's not obvious from the people you've spoken with.
I mean, I think we need to differentiate between the effects of technology and the effects of capitalism, right? And they are, you know, the fact that workers don't have a lot of power,
right? In the system matters. No, we had a system, right? And that's why I would say, you know,
go to that, you know that Harry Bridges report.
And those were workers who had a sense of power.
They said, we can demand some of the benefits.
Like, yeah, automate our jobs away.
But kick a little down to us.
And we had in the golden era of American industrialism
in post World War II, that was the contract.
The contract was employers can do what they want,
in automation and all these things.
Yeah, sure, there's some union rules
that make things less efficient in places.
But the key compromises tie wages to productivity.
That's what we did.
That's what unions did.
They tied wages to productivity,
kept them and up, right?
It was good for the economy,
some economists think, right?
And that's what we need to, I think we need to acknowledge that.
We need to acknowledge the fact that it's not just technology,
it's technology in a social context in which some people have a lot of power
to determine what happens.
For me, I don't have all the answers,
but I know what my answer is.
And my answer is, and I think I started with this,
I can learn from every single person.
Did I have to talk to the 200th truck driver?
In my opinion, yes,
because I was gonna learn something
from that 200th truck driver. Now, people with
more power might talk to none, or they might talk to five and say, okay, I got it. People are
amazing, and every one of them has a life experience and concerns and you know can teach us something and they're not
in the conversation. You know and I know this because I'm the expert you know so I get
pulled in to these conversations and people want to know you know what's going to happen
to labor you know it's like well I tried so I try to be a sounding board and I feel I feel a tremendous weight of responsibility
You know for that
But I'm not those workers
You know and and they may they may listen to this or you know walk in the door sometime
It's about me like that guy's full of shit. That's not what I think at all
Yeah, you know
And they don't get heard over and over and over.
But in a small way, you are providing a voice to them.
That's kind of the, if at scale, we apply that empathy and
listening that we could provide the voice to the voices
through our voice, through our money through.
I mean, that's one way to make capitalism work at not making the powerless more powerless,
is by all of us being community that listens to the pain of others and tries to minimize
that, to try to give a voice to the voices, to give power to the powerless.
I have to ask you on, by way of advice, young people, high school students, college students,
entering this world full of automation,
full of these complex labor markets and markets period.
What would you, what kind of advice would you give to that person about how to have a career,
how do I have a life that can be proud of? Yeah, I think, you know, this is such a great question.
I don't...
It's okay to quote Steve Jobs, right?
Oh, always.
Yeah, I mean, so...
And I just heard this recently.
It was a commencement speech that he gave,
and I can't remember where it was.
And he was talking about, you know, he had famously dropped
out of school, but continued to take classes, right?
And he took a calligraphy class and it influenced the design
of the Mac and sort of fonts.
And you know, just was something that he had no sense of what
it was going to be useful for.
And his lesson was, you know, you can't connect the dots looking forward.
Looking back, you can see all the pieces that led you to where you ended up.
For me, studying truck driving, I literally went to graduate school because I was worried
about climate change.
I had a whole other dissertation plan and then was like driving home and like I had read about all this management literature and sort of like
how you get workers to work hard for my qualifying exams. And
then read a popular article on satellite linked computers. And
the story in the literature was use of a sense of autonomy. And
I was like, well, that monitoring must affect the sense of
autonomy. And it's just this question that I found interesting.
And it never in a million years
that I ever thought I was gonna spend 15 years
of my life studying truck driving.
And it was like, if you were to map out a career path
in academia or research,
like, you would do none of the things that I did.
That many people advise me against,
where you can't go spend a year working as a truck driver.
That's crazy, you can't spend all this time
trying to write one huge book.
I mean, if I could just interrupt,
what was the fire that got you to take the leap
and go and work as a truck driver and go interview truck drivers?
This is what a lot of people would be incapable of doing. Just took that leap. What the heck?
What the heck is up with your mind that allows you to take that big leap?
So I think it's probably like Tolkien and George the ratio.
I mean, I think as a teenager, you know, I sort of adopted some sense of needing to, you
know, heroically go out in the world and, you know, which I've done at various points
in my life and like looking back in absolutely stupid ways that, you know, where I could have
completely, I ended up dead and traumatized my family, including like, I think a couple
of week trip in the Pacific,
like solo trip on a kayak,
and basically my kayak experience up till that,
point had been on a fairly calm lake,
and like class one rapid trip on a kayak in the Pacific.
Yeah, yeah, so I was working on forestry issues,
and we were starting a campaign
in really remote British Columbia, and I was like, okay, if I'm going to work on this, I've got to actually go there myself
and see what this is all about and see whether it's worth devoting my life right now, too.
And just drove up there with this guy, I can put into the Pacific, and it was insane.
The tides are huge.
And there was one point
in which I was going down a fjord and two fjords kind of came up and there was a cross channel.
And I had hit the timing completely wrong and the tide was sort of rushing up like, you
know, rivers in these, you know, two fjords and then coming through this cross channel
and met and created this giant standing wave
that I had to paddle through.
And now, actually very recently,
I've gone out on white water with some people
who know what the hell they're doing.
And I realized like just how absolutely stupid
and you know, it'll fit I was, but that's just,
I think I've always had that.
Were you afraid?
When you had that wave before you scared the shot at me.
Yeah.
Okay, what about taking a leap and becoming a trucker?
Yeah, there was some nervousness for sure.
I mean, and, you know, I guess my advantage
as an ethnographer is I grew up in a blue collar environment.
You know, again, all my ancestor for factory workers.
So I can move through
spaces. I'm really, I feel, I can become comfortable in lots and lots of places, you know, not
everywhere. But, you know, along class lines for sort of white, you know, even white ethnic
workers, like that's, you know, I can move in those spaces fairly easily. I mean, not entirely,
there was one time where I was like, okay, you know, and I grew up around people worked on cars,
I'd been to drag races and NASCAR, and I'd been to, you know, Colgate University, and I think
that was probably my initial training was, you know, being this just working class kid who ends up in this blue blood, small liberal arts college,
and just feeling like, both having the entire world opened up to me, like philosophy and
Buddhism and things that I had never heard of, and just became totally obsessed with,
and just following my interest.
What else would culturally perhaps
didn't feel like you fit in?
Feeling like just a fish out of water.
And at the same time that sort of drove me in the sense
that it drove an opening of my mind
because I couldn't understand it.
I didn't know that this world existed.
I don't understand.
And I think maybe that's where my real first step
in trying to understand other people because they were my friends, you know, I mean, they were my
teammates. I played lacrosse in college. I was close to people who came from such different
backgrounds than I did. And I just, I was so confused, you know. And so I think I learned to learn.
And then, you know,
it sort of went from there and then develop your fascination with people.
And the funny thing is you went from trucking not to autonomous trucks.
I mean, this is speaking of not being able to connect the dots.
And, you know, your life in the next 10 years could take very interesting
directions. That's very difficult.
First of all, us meeting is a funny little thing given the things
I'm working on with robots currently, but it may not relate to trucks at all. At a certain
point, autonomous trucks are just robots. And then it starts getting into a conversation
about the roles of robots in society. And the roles of humans and robots.
And that interplay is right up your alley.
As somebody who deeply cares about humans
and have somehow found themselves studying robots.
Yeah, no, it's crazy.
I mean, even for five years ago,
I would, if you had asked me if I was gonna be studying
trucking still, I would have said no.
And so my advice is, I think if I was gonna give advice,
you know, is, you know, you can't connect the dots,
looking forward, you just gotta follow what interests you,
you know, and I think we downplay right that
when we talk to, you know, kids, especially,
you know, if you have some break gifted kid
that gets identified as like,
oh, you could go somewhere, then we're like,
we feed them stuff, we learn the piano
and learn another language, right?
Learn robotics.
And then we tell other kids, oh, learn a trade.
Figure out what's gonna pay,
and not that there's anything else traits.
I think everyone should learn manual skills to make things.
I think it's incredibly satisfying and wonderful
and we need more of that.
But also, tell all kids, it's okay to take a class
and something random that you don't think
you're gonna get any economic return on.
Well, because maybe you will end up going into a trade,
but that class that you took in a studio art
is gonna mean that you look at buildings differently, right? Or you end up
sort of putting your own stamp on woodworking. I think that's the key. Follow, it's cheesy,
because everybody says, follow your passion. But we say that, and then we just, the 90% of what
people hear is what's the return on investment for that, you know, it's like you're a human being.
Like things interest you, music interest you literature interest you video games interest you like follow it, you know, go grab a kayak and go into the
go do something real. No, don't do that. I don't really go do something stupid and something a little bit. Oh, great regret a lot later. My foremother, thank God she didn't know.
Let me ask, because for a lot of people work, for me, it is, quote unquote, work is a source
of meaning.
And at the core, something we'll be talking about, with jobs is, is meaning.
So the big ridiculous question, what do you think is the meaning of life?
Do you think work for us,
humans, and modern society is as core to that meaning? Is that and is that something you
think about in your work? So the deeper question of meaning, not just financial well-being and
the quality of life, but the deeper search for meaning. Yeah, the meaning of life is love,
and you can find love in your work.
Now, and I don't think everybody can.
There are a lot of jobs out there that just,
you do it for a paycheck.
And I think we do have to be honest about that.
There are a lot of people who don't love their jobs,
and we don't have jobs that they're
going to love. And maybe that's not a sort of realistic utopia. But for those of us that have
the luxury, I think you love what you do that people say that. I think the key for real happiness is to love what you're trying to achieve.
And maybe love trying to build a company and make a lot of money just for the sake of doing that.
But I think the people who are really happy and have great impacts, they love what they do
because it has an impact on the world that they think is, it expresses that love, right? And that could be, you know, at a counseling center, that could be, you
know, in your community, that could be sending people to Mars, you know, well, I also think
it doesn't necessarily the expression of love isn't necessarily about helping other people
directly. There's something about craftsmanship and skills as we've talked about.
That's almost like you're celebrating humanity
by searching for mastery in the task.
In the simple, especially tasks that people outside me
see as menial as not important,
nevertheless searching for mastery,
for excellence in that task.
There's something deeply human to that
and also fulfilling that just like driving a truck
and getting damn good at it.
Like, you know, the best who's ever lived
driving the truck and taking pride in that,
that that's deeply meaningful
and also like a real
Celebration of humanity and a real show of love, I think for humanity. Yeah
Yeah, I just had my floors redone and the guy who did it was an artist You know he's saying to these old hundred-year-old floors and made him look gorgeous and yeah, this is craft
That's love right there. Yeah. I mean he showed us some love the
You know the product was just like
since enriching our lives. Steve, this was an amazing conversation. We've covered a lot of
ground, your work, just like you said, impossible to connect the dots, but I'm glad you did all the
amazing work you did. You're exploring human nature at the core of what America is, the blue collar America.
So thank you for your work, thank you for the care and the love you put in your work,
and thank you so much for spending your valuable time with me.
I appreciate it, Laksa.
I'm a big fan, so it's been great to be on.
Thanks for listening to this conversation with Steve Vaseli.
To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Napoleon Hill.
If you cannot do great things, do small things in a great way. Thank you for listening
and hope to see you next time. Thank you.