The following is a conversation with Steve Vaseli, formerly a truck driver and now a
sociologist at the University of Pennsylvania who studies freight transportation.
His first book, The Big Rig, Trucking and the Decline of the American Dream, explains
how long hauled 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 American
Trucker, explores self-driving trucks and their potential impacts on labor and on society.
This is the Lex Friedman Podcast.
To support it, please check out our sponsors in the description.
And now, here's my conversation with Steve Vaseli.
You wrote a book about trucking called The Big Rig, Trucking and the Decline of the American
Dream and you're currently working on a book about autonomous trucking called Driverless,
Autonomous Trucks and 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, it's called
All I Do is Drive where he's talking to an old truck driver.
It goes, I asked them if those trucking songs tell about a 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 who's 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 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.
I try to understand their world.
Ethnographer, by the way, what is that?
The science and art of capturing the spirit of a people?
Yeah, life ways.
I think that would be a good way to capture it.
Try to understand what makes them unique as a society, maybe as a subculture, right?
But it makes them tick that might be different than the way you and I are wired.
And to 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 exercise what C. Wright Mills called the sociological imagination,
which is to put that individual biography into the long historical sweep of humanity,
if at all possible.
My goals are typically more modest than C. Wright Mills's.
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
relative to others and conflict and power and all these things that I find interesting.
In the context of society and in the context of history and the 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 my first book was a success relative to my goals of trying to really get at the
heart of sort of the central issues and the lives being led by people.
If I have a resource, a talent, it's that I'm a good listener.
I can talk with anybody.
My wife loves to remark on this that I can sort of 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, a joke for everybody kind
of got to know everyone individually and he just taught me that essentially everyone
has something to teach you and I try to embody that.
That's the rule for me is every single person I interact with can teach me something.
I got to ask you, I'm sorry to interrupt because I'm clearly of the two of us the poorer 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, 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.
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.
It's a lot of it is the, as you know, as I think you're a great interviewer, prep.
You try to get to know a little bit about the person and understand the central questions
you're interested in that they can help you explore.
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 were 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.
Who do you interview?
Where do you find them?
How do you recruit them?
I just happened to have a sort of natural place to go that gave me essentially the population
that I was interested in.
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?
And that was sort of the first criteria was do you have time, right?
And if they said yes, I said, 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, 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.
It's pretty good odds.
It's amazing.
I mean, for any response rate like that, 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 spigot on.
And I got pretty good at it, I think.
So they have good stories to tell and they have an active life of 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 it's, 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 ruins
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 Nobel Prizes, you always talk to these kinds
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, these regular
folks in terms of stories, in terms of richness of experience, in terms of the ups and downs
of life.
And you know, that really stuck with me because I said that as a goal for myself to make sure
I talked 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 to 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 and 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, of our social world.
But truckers are generally, you know, real open, sort of friendly folks, and 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, you know, kind of open, you know, trusting, willing to have
a conversation.
And so, you know, you go to the truck stop and you go in the lounge and they're usually,
there's usually a booth down there and somebody's sitting at their laptop around their phone
and willing to strike up a conversation.
You should try that.
You should, you 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 podcast audio books?
Do they listen to music?
Do they listen to silence?
Everything.
Everything.
Everything.
Some, I mean, and some still listen to the CB, which, you know, it's an ever dwindling
group, they'll call it the original internet citizens band.
You know, they, back in the 70s, they thought it was going to be 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, you know, it's guys who know each other from the same company or happen to run
into each other.
But other than that, it's everything under the sun, you know, and that's, it's probably
one of the stereotypes and it's, I think it was more true in the past, you know, about
the sort of heterogeneity of truck drivers.
They're a really diverse group now, you know, there's definitely a large, 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 going to happen.
So I was able to experience it as a new truck driver would is one of the important stories
in the book is how that experience is constructed by employers to sort of, you know, help you
think 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 changed as 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 do 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, you know, to a dead stop in the, you know, 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 companies, 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, you know, theory
of kind of how you fill out your logbook, rules of the road, you know, you 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 in 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 this, it's like, you know, this 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 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, you know, off-shored 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 and 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 unsupervised, you know, 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.
Well, so the truck is such an imposing part of a traffic scenario.
Yeah.
So you said like, like turning, it stresses me out every time I look at a truck because
I mean, 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 if when you're new especially, like it will 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 truck's grinding 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 a pretty good rookie.
But when I finished, I was still a rookie, even shifting, definitely backing tight corners
and situations.
You know, I could drive competently, but the difference between me and someone who had,
you know, two, three years of experience was, it was a giant gulf between us.
Going 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 to two categories?
One is like the local stuff, getting out of the parking lot, getting into, getting into,
you know, driving down local streets and then highway driving, those two, those two tasks.
What are the challenges associated with each task?
You kind of emphasized the first one.
What about the actual, like, long haul highway driving?
Yeah.
So, I mean, and 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 is 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 an 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 going to 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, you know, they avoid it.
And then the local driving is really something that takes just practice and routine to learn.
You know, 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 to get the
effect that I want like five seconds from now in 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, you know, 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 know, you have to get that back to your company.
And then that's how they bill the 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.
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 to the actual hours?
So 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 we will then continue when we start talking
about autonomous trucking.
But, you know, you're saying all these cents 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, you know, 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 and say,
here's this load of beer, bring it to this address in Michigan, we're going to pay you
by the mile, right?
If you're always being paid by the hour, I might just pull over at 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 have 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 dock
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 dock's ready.
So you wait there a couple hours, they bring you in, you know, you never know what's happening
in the truck.
Sometimes they're loading it with a forklift.
Maybe they're throwing 14 pallets on there full of kegs.
But sometimes it'll take them hours, you know, and you're sitting in that truck and 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 truckers get paid a lot for their work.
Do they get paid a lot for their work?
Some do.
And I think that's part of the complexity.
So you know, what interested me as an ethnographer about this was, you know, 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, you know, why some people become an entrepreneur and other
people become a wage laborer or, you know, why some people want to be doctors and other
people want to be truck drivers.
That conception, right, 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, you know, 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, you know, is an attraction,
but the industry is highly segmented.
And so the entry level segment, and we can probably get into this, but, you know, the
industry is dominated by, you know, 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 the 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, you know, what should truck drivers get paid for, right?
The industry, you know, 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, right?
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 companies say, well, that guy, you know, 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 in these jobs will work, according to most people,
would sort of define it as like, okay, I'm at the customer location, I'm waiting below
and doing some paperwork, you know, 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 drivers.
And just when you 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.
Like a family from the high quality of life parts of your life.
Yeah.
And there's a whole nother 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, you know, the minimum
wage for a truck driver should be 50s of thousands, you know, 55, $60,000 should be
the minimum wage of a truck driver.
And you probably heard about the truck driver shortage, like 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 $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.
And I think that's what, now we have drivers who start in the 30s, but yeah, and I mean,
so we're talking two, three jobs really, when you look at the total hours that people are
working at, you know, they can work over a hundred if they're a trainer, you know, training
other truck drivers well over a hundred 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's 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 the state wanted to look at was, you know,
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 about 145,000 jobs in California that require of 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, we're going to 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.
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 do it.
Yeah, so it's not just skill, it's like they were psychologically invested potentially
for months, if not years into this kind of position, as perhaps a position that if they
lose their current job, they could fall too.
Okay, so that's an 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 truck driver currently?
Yeah, the problems with the job and the labor market, but let's start with the job, which
is, again, just so much time that's not compensated directly for the amount of time.
That's just psychologically, and this was a big part of what I studied for the first
book, was that conception of what's my time worth.
What truck drivers love oftentimes is that tangible outcome-based compensation.
So they say, you know what, honest days 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 time every second becomes more
worthless or worthless.
Yeah, and again, the industry is going to say, for instance, okay, well, they've got
skin in the game, that argument about compensation based on output, 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 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, 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.
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 docks
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, you
know, in order to keep that business.
When you tried to describe the economics, the labor market of the situation, you mentioned
freight and railroad.
What is the sort of the dynamic financials, the economics of this that allow for such
low salaries to be paid to truckers?
Like what's the competition?
What's the alternative to transporting goods via trucks?
Like 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, sorry to interrupt, are pushed to the truck driver.
Doesn't that like spiral, doesn't that lead to a poor performance on 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.
How is the competition being suppressed here?
Yeah.
So the competition is based on who's cheaper.
And this is the cheapest way to move the freight now.
They're externalities, right?
So this is the explanation that I think is obvious for this, right?
There are lots of costs that, whether it's that driver's time, whether it's the time
without their family, whether it's 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.
The 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 you're a veteran using your GI benefits,
you may very well be offered 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 trains?
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 don't know if this industry collected data from the big
firms that report it, but 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.
So you can get loaded, drive and unload 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 journalistic 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.
It would be interesting to compare what I'll say.
But I mean, one bigger question to ask, I guess, is 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, the trucking 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?
There were some really bad 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 sort of 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.
And 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, asphalt cowboy imagery that we get.
And I grew up, I know you didn't grow up in the US as a young child, and I'm a bit older
than you.
But in the late 70s, there were movies and TV shows and CBs were crazed, 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 with all this
salty language and these terms that only they understood and the partying at diners and
popping pills, the California turnarounds.
So asphalt cowboy is truly, it's like another form of cowboy movies.
Oh, absolutely.
Yeah.
Absolutely.
And I think that masculine ethos of like, you got 40,000 pounds of something you care
about, I'm your guy.
You needed to go from New York to California, don't worry about it, I got it.
That's appealing.
And it's tangible, right?
And you think about people who don't want to be paper pusher and deal with office politics
like, just give me what you care about and I'll take care of it.
Just pay me fair.
And that appeals.
You mentioned unions, Teamsters, Jimmy Hoffa, 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 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, someone who does hard science, right?
If you're a social scientist, you know, sort of use that terminology, even other social
scientists.
Hypothesis.
Yeah.
So, I do like to think that way.
And my initial hypothesis was that, you know, and it's very simple that, you know, the tenure
of the driver in the industry would have a strong effect on how they viewed unions.
That, you know, 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, you know, 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 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 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 economists to follow
him around and like opened up the Teamsters books to them so that they could see how he
was, you know, thinking about negotiating with the employers.
And the Teamsters, and this goes back well before Hoffa, back to the, you know, 1800s,
they understood that workers did better if their employers did better.
And the only way the employers would do better was if they controlled the market.
And so oftentimes the corruption and trucking was initiated by employers who wanted to limit
competition and they knew they couldn't limit competition without the support of labor.
And so you'd get these collusive arrangements between employers and labor to say, no new
trucking companies, there are 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, 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 know, you don't have any choice, you can't, it's what economists call derived demand.
You can't like make up a bunch of trucking services and store it in a warehouse, right?
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?
What are we, how many jobs are we talking about today?
And what kind of jobs are there?
So there are a number of different segments and the first part would be, you know, 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, you know, a paper company or something like that
that's operating your own fleet of trucks?
That's private trucking.
For hire are the folks who, you know, offer their services out to other customers.
So you have private and for hire.
In general, for hire pays less.
Is that because of the something you talk about 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, right,
for their own in-house services.
So you know, they tend to, and this, you know, 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 in 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, right?
And so we have what's called truckload, and truckload means, you know, you can fill up
a trailer either by volume or by weight, and then less than truckload.
Less than truckload, the official definition is like less than 10,000 pounds.
You know, this is going to 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, right?
Nowhere in between.
Do you stop?
At least process that freight.
Less than truckload, what you've got is terminal systems, and this is what you had under regulation
too.
And so these terminal systems, what you do is you do a bunch of local pickup and delivery,
with smaller trucks, and 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, you know, trailer, and you send it to another terminal where it gets
broken back down and then, and then out for local delivery.
That's going to look a lot like if you send a package by, by UPS, right?
They pick all these parcels, right, figure out where they're all going, put them on
planes, or, or in trailers going to the same destination, then break them out to put them
in what, what they call package cars.
Before I ask you about autonomous trucks, let's just pause 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?
Yeah.
No, I mean, it was, I didn't have kids at the time.
Now, now I have kids.
I can't even imagine it.
Uh, you know, I've been married for five years at, at the time.
My wife hated it.
I hated it.
Uh, you know, I, I describe in the book the experience of being stuck, if I remember
correctly, it was like Ohio, uh, 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 going to be home?
And I'm like, I don't know, you know, um, I have a, a cousin whose husband drove, drove
truck as a truck driver would say drove truck for a while.
Um, and he told me before I went into it, he was like, the, the advantage you have is
that you know that you're not going to be doing this long term.
Like, 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 spicket and the, the, the last question I would ask drivers was that by the
time I really sort of figured out how to do it, the last question I, I would ask them
is, you know, what advice would you give to somebody like your nephew, you know, a family
friend asks 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, you know, grizzled old drivers, you know, tough, tough
guys would that question would like 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, I'd be out for two weeks at a time.
I'd come home, my, my wife would give me two kids to punish a list of things to do, you
know, on Saturday night and I might leave out Sunday night or Monday morning, you know,
I come home dead tired.
My kids don't know who I am and you know, it was just like, it was heartbreaking to hear
those stories.
And then before you know it, you know, life is short and just the years run away.
Yeah.
It's a 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, there's definitely a pride and mastery of, you know, even basic competence
of sort of piloting this thing safely.
There's a lot of responsibility to it.
That thing's dangerous and you know it.
So there's, 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.
And 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, the place where they make the
cardboard boxes that the Huggie diapers go in, Huggies diapers 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, you know, it's one loading dock after another.
So you lose the magic of being on the road.
Yeah.
It's, 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, catastrophes in the world, like COVID, for example?
Yeah.
I mean, we, we have built really long, really lean supply chains and, and just by definition,
they're fragile.
You know, 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 were referring to?
Yeah.
So we've got pile ups of ships off the coast of California, Long Beach and LA in particular
and in bad shape.
You know, last 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, 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, and 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 supply 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 bays sitting around.
So we don't have, you know, 10% extra capacity in warehouses, you know, we don't have 10%
of them.
Trucking capacity can fluctuate a bit, but, you know, you don't have that kind of slack.
And now, I mean, and we saw this right when people shifted consumption and I get a little,
I had a little mad when people talk about panic buying as kind of the, you know, the
reason that we had all these shortages.
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 an 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, right?
So we get, you know, food from Cisco.
Cisco couldn't get rid of food, right?
Because nobody's eating out.
So they've got, you know, 50-pound sacks of flour, you know, 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.
So 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, right?
So you know, that stuff leaves Asia, you know, 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 en masse 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 leftovers 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.
I mean, so I have worked in agriculture a bit on sort of the supply side, you know,
and there are product categories, right, where 30% of the crop raised does not get
used, right, just gets plowed under or wasted.
But here's the importance of this in sort of getting this right, you know, like that
not that like panic buying, you know, blame the irrational consumer, you know, look at
the hard sort of 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, you know, other institutional failures?
Do those things seem, you know, potentially more likely in the future than they have been
in 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 less densely connected, you know, building, it's like,
what is it, you know, the Tesla model for in the automotive sector of like trying to
build everything, like trying to get the factory to do as much as possible with as little
reliance on widely distributed sources of the supply chain as 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, right, 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
storing 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 boardroom is going to say, you know, guys,
inventory is getting kind of heavy and the cost of that is like, do we, can we really
justify that much longer to the shareholders, right?
Well, 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, 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, catastrophes that can happen, what, like how will the system
respond?
So having a really solid model that you're operating under as opposed to just kind of
being in 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.
So 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.
It's such a simple idea.
Truck that drives itself, classic blue collar job that pays well, guy maybe with not a lot
of other good options to sort of make that same income easily, and you build a robot
to take his job away.
So I think 2016 or so, that was the big question out there, and that's actually how I started
studying it.
I just wrapped up the book.
Just so happened that somebody who was working at Uber, Uber had 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?
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 and they can only drive eight or 10 hours a day, they hop in the back, they
get their rest, and the asset that they own works for them.
That's sort of perfect, right?
And at that time, there were a bunch of reports that came out, and 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
and said, let's assume that all these jobs are just going to disappear.
And really smart researcher, Annetta 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 is super diverse.
I haven't given a ton of thought, but it can't be that, it's not that simple, it never is.
And so she was like, will you do this?
And I was ready to move on to another topic.
I had been in trucking for 10 years, and that's how 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.
Nowhere near what people thought, you know, I estimate 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 going to reshape our supply chains, it's going to reshape landscapes, it's going
to 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 software engineering
allows you to automate a lot of the tasks that 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 increased 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 absolutely is.
Because it's the wrong question.
The question is, what do we want the future to be and let's shape it, right?
And I think this is, you know, and this is the only point that I really want to make
in my work, you know, for the foreseeable future is that, you know, we have got to get
out of this mindset that we're just going to 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, right?
If Congress in 2000 had not written into legislation funding for the DARPA challenges, which followed
for, actually, I think the funding came a couple years later, but the priority that
they wrote in 2000 was, let's get a third of all ground vehicles in our military forces
unmanned, 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, 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.
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 DARPA 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 the catalyst for creating all these different
companies that took on the challenge, some failed, 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 wave of hype and profit and all this
kind of weird dance where the B word billions of dollars have been thrown, being 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 those initial, that
initial vision of I guess as you're saying, of automating part of the military supply
chain.
Yeah.
I did not know that.
But 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 what it produced, right?
I mean, your own work on self-driving, right?
I mean, you've 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, right?
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 you're too dumb to realize how difficult it is so you take it off, right?
And then eventually you're too, you're in too deep, so you might as well solve the problem.
Well, and maybe we're in that situation right now with self-driving, but, you know, and so
let me throw this out there.
I'd be curious to hear your thoughts on it, but truck drivers always ask me, like, is
this for real?
Like, is this really, like, it's harder than they think, right?
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 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?
I mean, 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.
It's fascinating to think about, I've never thought of it that way.
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
trillions of 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.
You're right.
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.
It'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 and 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 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 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 Mobileye when they first had.
I thought, actually, Mobileye is the thing that impressed me.
When I sat down, I thought, 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 would be too many failures.
It would be really annoying.
It would be a gimmick, a toy.
It wouldn't actually create a pleasant experience.
And when I first was gotten to Tesla with Mobileye, the initial Mobileye system, it
actually held to lane for quite a long time to where I could relax a little bit.
And 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.
And for some reason, I was really reducing in stress.
And then over time, Tesla, with a lot of the revolutionary 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's super cruise system.
It is a sad story because I think I vaguely read in the news they just said they're discontinuing
super cruise, but it's a nice, innovative way of doing driver attention monitoring and
also doing lane keeping.
Just innovation could solve this in ways we don't predict.
And same with the, in the trucking space, it might not be as simple as like journalists
envisioned a few years ago, where everything's just automated.
It might be gradually helping out the truck driver in 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 that, I still have that dream that I believe to solve the fully autonomous driving problem
is we're 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 this space, there's an opportunity
to come up with like subtle technologies that 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.
You know, 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 now
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 the smartphone into
a computer.
And that same way, who knows how you can transform trucks, right?
By 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 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've studied the history of trucking technology as much as I can.
You know, there's not a lot of great stuff written, and you kind of have to, you know,
present 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 Daimler builds, you know, 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, you know, and then World War I really spurs the development
of sort of bigger, larger trucks, like it spreads, you know, air-filled tires.
And then we start paving roads, right?
And paved roads, right, air-filled tires, and the internal combustion engine, now you've
got a winning mix.
Now it met with demand for people who wanted to get out from under the thumb of the railroads,
right?
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, you know, 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 to fit what trucks could do.
And so transportation and logistics become Walmart's edge and allows them to dominate
the space.
That's the challenge that Amazon has now.
They've mastered the digital part of it and now they've got to figure out how do we dominate
the actual physical movement that complements that?
Others are obviously going to follow, but the capabilities of these trucks is completely
different than the capability of a human-driven truck.
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.
So he can drive his full 11 hours and bring that meat so it doesn't have to sit overnight
in that refrigerated trailer.
And 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.
This expires to do something completely different, move huge varieties of things in small quantities
virtually everywhere as fast as possible.
And so that is like that intercity trucking under the, in the era of railroad monopolies.
The demand for that is potentially enormous and so there's such a, so right now I think
a lot of the business plans for sort of automated trucks and sort of the way that the journalistic
accounts portray it is like, okay, if we swap out a human for a computer, what are the labor
costs per mile and like, oh, here's the profitability of self-driving trucks.
This is transformative technology.
We're going to change the way we get stuff.
So we could actually get a lot more trucks, period, with 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 we really thought we were going to 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, we, you know, here's how far, 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, right, if it's not batteries,
you know, how are we, how are we powering these things and how many of them are, they're
going to be like right now we've got 5 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 of 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 a platooning solution, 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 taking
up a highway.
I mean, this is probably a good place to talk about various scenarios.
But 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?
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 rather than platoons, we might have like hives of trucks, right?
So you have like 20 trucks moving in some coordinated fashion, right?
And then maybe the self-driving cars are, because people don't like to be around them
or whatever it is, right?
You might have a pod of 20 self-driving cars sort of moving in a packet behind them.
This is what if the aliens came down or we're just observing cars, which is one of the sort
of prevalent characteristics of human civilization is there seems to be these cars like moving
around that 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.
And that's where we should start in sort of 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 and the question was essentially, what are you trying to build?
Like 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.
They were engineers and computer scientists and-
Oh robotics people, I love you so much.
I could talk forever about this, but yes, there's a technology problem.
Let's focus on that and 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.
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?
Why are they involved 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.
And it turns out that's really obvious and quite simple.
Highway driving's a lot simpler, right?
So the plan is simplify the problem 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 Hall and Citi, right?
And you're not paid in the city, you've got congestion, the turns are tight, there's lots
of pedestrians and 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 and hybrid trucks being sort of like the solution.
The problems with them and the advantages also split on what I was thinking of as kind
of the rural urban divide at that time, right?
So it's like you got the regenerative braking, right?
You can make the truck lighter, you can keep it local, right?
You don't get any benefit from that hybrid electric on the rural highway.
You want aerodynamics, right?
There you want low rolling resistance tires and these super aerodynamic 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 less strong pavements, right?
You can make tighter turns, you don't need a sleeper cab because the driver 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 drop lots outside cities where a local city driver who's paid
by the hour kind of runs these trailers out once they're loaded, 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 truck loads.
Yeah, and we have like intermodal, we have like, we have basically this would be the
equivalent of like rail to truck intermodal, right?
So you put it on the rail and then 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 because 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,
drive to Michigan, drive to Alabama, drive to Wisconsin, drive to Florida, I get home
every two weeks.
If I'm just running 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 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, that much weight on them, they can't handle
these doubles, right?
And some places can, some places can't.
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 stage that they were at was like, you know, what's that experience
going to be like?
And I was like, truckers aren't going to like it.
You know, I mean, 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, like you have that trucker like right on your ass,
you know, people remember that they don't remember the 99.9% of truckers that are not
on their ass, you know, like 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 like 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 of 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, you know, the front of his truck.
And then some were like, it's too close.
And it might be one of those things that's just, you know, takes an adjustment to sort
of get there.
So you get the aerodynamic advantage, which, which, you know, saves fuel.
There's some problems though, right?
So, you know, 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, you know, still the benefits are there.
That's one scenario.
And that's just the automation of that acceleration and braking.
Starsky, which, you know, probably a lot of your listeners heard about, was working on
another scenario, which was, you know, to solve that local problem was going to do tele-operation,
right?
Sort of remote piloting.
I had the chance to, you know, sort of watch, watch them do that.
It was, you know, they drove a truck in Florida from, from San Francisco in one of their offices.
That was, that was really interesting.
And then in case it's not clear, tele-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, what are the pros and cons?
You know, one of the problems with, with doing research like this with, with all these,
with all these Silicon Valley folks to the NDAs.
Oh, right.
Right.
So, so I don't, you know, I don't know what I'm able to say about sort of watching it.
But obviously the, their public statements about sort of what the challenges are, right?
And it's about the, 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, you know, I've talked to the Waymo CTO, I'm in conversations with
them.
I'm talking to the, the head of trucking Boris, a soft man 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're talking about NDAs, they've, for some reason, rightfully 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 it 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?
You know, 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 everything, of how difficult this problem is.
One of the big questions I've had still have is how difficult is driving?
I 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 avoidance problem.
It's like billiard balls.
It's like you have to convert the drive, you have to 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 at 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 tele-operation from Starsky's is really interesting idea.
How much can, I mean, there's a few autonomous vehicle companies that tried to integrate tele-operation
in the picture.
Can we reduce some of the costs while still having reliability, like catch when the vehicle
fails by having tele-operation is 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 or easy for humans.
And so if you were to look at truck driving prior to a lot, I mean, there's been a lot
of thinking and debate in academic research circles around sort of how you estimate labor
impacts, what these models look like.
And a lot of it is about how automatable is a job.
Object recognition, really easy for people, 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.
It turns out to be something that we do naturally that is sort of cutting edge, computer science.
So on the tele-operation question, I think this is a more interesting one than people
would like to sort of let on, I think, publicly.
There are going to be problems.
And this is one of the complexities of sort of putting these things out in the world.
And if you see the real world of trucking, you realize, wow, it's rough.
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 service something and they didn't.
And so you imagine, OK, we've got this vehicle that can drive itself, which is going to require
a whole lot of sensors to tell it that the doors are still closed and the trailer's still
hooked up and each of the tires has adequate pressure and any number of probably hundreds
of sensors that are going to be sort of relaying information.
And one of them, after 500,000 miles or whatever, goes out.
Now, 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.
Or maybe there's some level of safety critical faults or whatever it might be.
So 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 bottom of the list.
Figure out how to rescue truck.
It's on the to-do list, right?
After solving the self-driving question is like, yeah, what do we do with the problems,
right?
I mean, no, we can imagine, like, 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 it crashed, but now you've got a truck stranded on the side of the road.
You're going to send out somebody to calibrate things and check out what's going on.
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 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, 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 Penske location, right?
Sort of all these service locations around and have a technician take a look at it.
So tele-operation often gets this 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.
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 autonomous 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, tele-operation is another huge effort like that.
It's like taking seriously what happens when it fails.
What's the, in the 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 that 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.
There's a whole experience as 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.
If tele-operation is part of that, it could be, just like you're 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, people monitoring
this giant fleet of trucks and taking over when needed.
That'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.
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 tele-operation
and some of this is used for rovers and really high stakes, difficult problems.
But one of the things we wanted to study were these mines and these Rio Tinto mines in Australia
where they remotely pilot the trucks.
There's some autonomy, I guess, but it's overseen by a remote operator and it's near
Perth and it's quite remote and they retrained the truck drivers to be the remote operators.
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 going to 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 and
it may not be where the upper lever managers want to be at places like that, the issues
like that.
So I do think it's an interesting question, both from a practical scenario situation of
how it's going to work, but also from a policy perspective.
So there's platoons, there's tele-operation, and this is taking care of some of the highway
driving that we're talking about.
Is there other ideas, like, are there other ideas, scenarios that you have for autonomous
trucks?
Yeah, so I mean, the most obvious one actually is just a facility to facility, right?
The sort of, you know, it can't go everywhere, but a lot of logistics facilities are very
close to interstates and they're on big commercial roads without 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, the first place you see a Waymo self-driving,
you know, truck rollout might be, you know, sort of direct facility to facility for UPS
or FedEx or less than truckload care.
An 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 go back and forth in one day.
So from the people you've 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 to exit, right, which looks
like that urban truck boards thing that I laid out earlier.
You know, so you have a human driven truck that comes out to a drop lot.
It meets up with an autonomous truck, that truck then, you know, drives it on the interstate
to another lot and then a human driver, you know, picks it up.
There are a couple variations maybe on that.
So let me just run through the last two scenarios.
The other thing you could do, right, is to say, all right, I've got a truck that can
drive itself, and I refer 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 it gets coupled up to a self-driving truck, 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 the term autopilot and so do aeroplanes 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 inclement weather or whatever it might
be and call to you and say, hey, or I mean, 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 that may require teleoperation or whatever it is, right?
And it signals to your truck, hey, tell the driver 20 miles ahead.
Just got to 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 we need them 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, which I proposed is I was like, well, here's an idea that would be like,
actually good for workers.
And just another brief aside here.
The history of trucking over the last 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, big sets of laminated maps to figure out where
the truck can go and where it couldn't, which is a big deal.
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 that's too low.
You've probably seen that on YouTube.
If not, check it out, truck can opener.
There's some bridges that are famous for it, and there's one I think called the can opener
that you can find on YouTube.
And you had to law those hours manually and do the math and plan your work routine.
And I would do this every day and say, 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, which
is going to put me in Chicago.
And so you do this.
And now today, 15 years later, truck drivers don't have to do any of that.
You don't have to shift the truck, you don't have to map.
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 put downward pressure on wages and
allowed companies to speed up, monitor, and direct.
The key technology that I did work under is satellite-linked computers.
So before you could go out and plan your own work and the boss really couldn't see what
you were doing and push you and say, you've been on break for 10 hours, why aren't you
moving?
And you might tell them, because I'm tired, like I didn't sleep well, I've got to get
a couple more hours, 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 de-skilled the job, 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 and sort of envision ways that it would.
It's like, the burden is really a proof is really on you to sort of really clearly lay
out what that is going to 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 of entry towards a scale.
That's really interesting.
That's tough.
That's tough to know what to do with, because yeah, from a technology perspective, you want
to make the life of the people doing the job today easier.
Is it?
Is that what you want?
No, but that, like when you think about like what exactly, because the reality is you will
make 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 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 the sort of automation, and I think Uber is
an interesting example here, right, where it's like, okay, if we had 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.
So the dispatchers are already out of work in rideshare, and the payment is already automated.
So you have to automate steps like this.
So you have to have that initial link to dispatch the truck.
You have to have the automated mapping.
So we've sort of done all this incremental automation that could make the truck completely
driverless.
There are 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, like I said, you
get those kind of local skills of backing and congested traffic.
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, right?
So you bump something back into the dock.
It might be a couple of 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 in the sense
of they pay attention continually.
And how I was describing those long haul segments where the driver 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 as a CDL examiner.
You could take them out and say, all right, I need you to go around these cones and drive
safely through this school zone.
But what really proves that you're a safe driver is two years without an accident, because
that means that day after day, hour after hour, mile after mile, you did the right thing.
And not when it was like, oh, some situation's emerging, but just consistently over time,
kept yourself out of accident situations.
And you can see this with drivers who are a million or two million safe miles.
The value of those drivers for Walmart is they don't run over minivans.
The company I work for, they ran over minivans on a regular basis.
So when I was trained, they said, we kill 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 caused that
funeral.
Okay.
So they just write that off.
That's just part of the business model.
Now, forward collision avoidance can 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 minivans.
So as soon as you have that forward collision avoidance, what's going to 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, they're good, but 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 on that 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 and its
ownership, right?
We don't call it capitalism for nothing.
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 of centuries and all the productivity
gains is people who are in a competitive market saying, I have to do it, right?
I don't have a choice because my competitor over there is going to eat my lunch if I'm
not on my game.
I don't have a choice.
I've got to invest in this technology to make it more efficient, to make it cheaper.
And what do you look for?
You look for oftentimes, you look for labor costs, right?
You look for high value labor.
If I can take a hundred and, you know, a lot of these truck drivers make good money, $100,000
good benefits, vacation, you know, 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, you know, skilled blue collar
workers, I'm going to do that.
And that's just, that's what we do.
And so I think those are the bigger questions around this technology, right, is like, you
know, are workers going to get screwed by this?
Like, yeah, most likely, like 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 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 such trucks?
Yeah.
Can I defend myself first?
Because I can, I'm reading the comments right now of people, you know, of the economists
who are telling me.
Dear commentary.
Dear PhD economics.
Yes.
Yes.
Dear PhD in economics, I know that higher skilled jobs are created 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 with a new technology, right?
You better check your business plan if your idea is to take a bunch of low wage labor and
replace it with the same amount of high wage labor, right?
So we, 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, right?
And do they live in the same places?
And I think that kind of, you know, 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 trucker constituents.
So 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 as real lives that are at stake.
That's what I suppose sociology is better at doing.
So we try sometimes.
Sometimes.
But 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,
yes, landscape of human suffering, it's just, 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 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 as 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, right?
So what, you know, what can we do, right?
What's sort of the positive vision?
Because, like, we've got tons of highway deaths.
We've got, and just to, you know, 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 in LTL, those are a 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 driver's doing other kinds of work that, you know, 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 a 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, you know, I think about these problems is
I try to find analogies, right, sort of labor processes and things that make economic sense,
you know, that seem, you know, 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?
And so, if 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, you know, the computer
scientists and the engineers, they were like, well, you know, 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 layperson, 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, you know, the two trucks can just
spread out just enough to make the bridge weight, right, and you can just program that
in and, you know, they're 50 feet further apart, 100 feet further apart.
So interesting sort of, I think, story about this that leads to kind of, I think, the policy
questions in, I guess, 2017, Jack Reed and Susan Collins, 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 do a report, sort of looking at the lay
of the land, talking to some experts, and I was working on my 2018 report, helped contribute
to that GAO report, and, you know, I had the six scenarios, right, I'm like, okay, you
know, here's what Starsky's doing, you know, here's what Embark and Uber are doing, you
know, here's what Waymo might be doing, you know, 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 at which
it can operate safely, right, now we're talking upskilling, right.
And so, you know, 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, you know, get industry perspectives
and then do a study on the labor impacts.
So, you know, that DOT, DOL process starts to happen, and, you know, 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 going to have us discuss at this workshop, and he's like, hey, these look really familiar,
right, because they were the, you know, scenarios from the report, but there were only five
instead of six.
Interesting.
So, the sixth scenario, which was the upskilling labor, good for workers scenario, wasn't
discussed.
So, to clarify, that's the integral piece of technology there is platooning?
Yeah, I mean, in a sense, it's platooning, but, and in fairness, right, as I pitched
that idea or sort of 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, you know, 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, 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 self-driving.
You do not need to solve the full self-driving problem.
I mean, if you're talking about probability of dangerous events, it just seems with platooning,
then like, you can deal with cut ends.
Yeah.
So this is, you know, this is beyond, this is one of the challenges, obviously, of being
a researcher who, you know, doesn't really have any background in the technology, right?
So I can dream this up.
I don't have no idea if it's feasible.
Well, let me speak, you spoke to the PhDs in economics, let me speak to the PhDs in
computer science.
If you think platooning is as hard as the full self-driving problem, we need to talk, because
I think that's ridiculous.
I think platooning, in fact, I think platooning is an interesting idea for ride 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 ride sharing problem.
But anyway, I think that's a great idea, but you're saying it was removed.
Yeah.
And so you, you know, you can go, you know, and, you know, listeners could go to these
reports, they're publicly available.
And they explain why in the, in the footnote.
And you know, they, they note that there was this other scenario suggested by at least
me and I can remember if they said someone else did too.
But they said, you know, 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, right?
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, and maybe, you know, and then I tried to think outside the box at the end by adding
that one, right?
Like here's one that I have, you know, 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, the super heavy, you know, you wouldn't have
to protect the human life in the following truck.
So that's interesting.
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, 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, 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 NHTSA 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 don't, you think that's, you think DOT should provide ideas themselves?
Well, so this is the, this is the great trick in policy of, of private actors is you, you
get narrow mandates for government agencies, right?
So, you know, this, 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 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 want, you know, 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, when we sent people to the moon, you know, we, we did that.
We, you know, and there were tremendous benefits that, 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, of six months or so, I
don't know how long it was after those, those meetings in which that sixth scenario was
not considered a company called Locomation, you know, ends up using that, essentially
that basic scenario with a slight variation.
So they, they leave the human driver in both trucks and then that following driver goes
off duty.
And then, you know, I've been trying to think of what the term is, they kind of, I think
of it as like slingshotting.
They sort of, when one runs out of hours, you know, the one who's off duty goes in front
and, you know, and so, you know, if only they had been, you know, around six, six months
earlier that what it might have been considered by DOT, but it just says, you know, who has
the authority to propose what these visions of the future are?
Well, some of it is also just the 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
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 problems, 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 like 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, this is life changing.
This is 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 important part of the policy conversation
because you get, 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 at stake that could be lost and they could bankrupt the company
if they make the wrong decisions and that, 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've gotten a 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, you know, and I don't have enough data as a sociologist
to really say like, oh, this is why they do what they do.
But you know, my hypothesis is, you know, 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 that resulted in the Uber purchase of that
program.
So what would I, what would I ask?
I mean, I think I would ask a lot of questions, but I think the markets-
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 mean, 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 the only place they are left, right?
So that's going to be the big fight on the hill and 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 some like 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 galvanized that union and they still control the ports today
because of the sort of vision that he laid down.
In the 1960s, he put out a photo journal report called Men and 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.
We used to take the barrels of 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 stack the crates tight and that was the
pride of the Longshoremen was a tight stow.
And now you all know there are cranes that come down and there's no longer any rope
slings and we're loading bulldozers into the hold to push the ore up into piles and then
clam shells 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 going to lose jobs, but we're going to get a share of the benefits.
And so our wages are going to go up.
We're going to continue to control the hiring and training of workers.
Our numbers are going to go down, but you know, basically that last son of a bitch who's
working at the ports going to be one really well paid son of a bitch, you know, just be
one standing, but he's going to love his job.
You should check out that report.
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, I mean, 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,
you know, take soldiers out of harm's way, but, you know, a lot of money.
And there's some way, if you are a business that's leveraging 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, right?
On one, there's pure capitalism, and then there's communism, and 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, you know, individual
private companies to kind of kick back, right, capitalism doesn't allow that, right, unless
you have a huge monopoly, right, and then you can, on the backside, create music calls
and libraries and things like that.
But you know, here's what I think, you know, the basic obligation 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, let's have a real
conversation.
Real human conversation.
Can we just do that?
Yeah, don't play games.
Real real human conversation.
Let me ask you, mentioned autopilot, gotta ask you about Tesla, this renegade little
company that seems to be, 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, and I did have some very preliminary conversations with, you know, policy folks
there.
You know, 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, you know, I don't see the application, the value in self-driving for the truck that
Tesla's gonna produce in the near term.
You know, they're just, you're not gonna have the battery, and now you could have wonderful
safety systems and, you know, reinforcing, you know, the auto, you know, self-driving
features supporting a skilled driver.
But you're not gonna 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 so that, yeah, the electrification is not obviously
coupled with the automation, they have a very interesting approach to semi-autonomous pushing
towards autonomous driving, right?
It's very unique.
No LiDAR, now 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, it started.
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 and 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, on par, if not safer, and it seems to work really well.
The human factor somehow manages, like drivers still pay attention.
Now there's a selection of who is inside the Tesla autopilot user base, right?
There could be a self-selection mechanism there, but however it works, these things
are not running off the road all the time.
So it's very interesting whether that can sort of 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.
Is that, do you think that's from the people you've spoken with too difficult of 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 want to see those Tesla electric trucks running out to those truck ports where you've
got those two trucks with a human driver in front, right?
I think that's, now what's powering those is that hydrogen, you know, again, it's very
interesting as a researcher, who does not have a background in technology and doesn't
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, you
know, I mean, I don't have a completely unable to assess who's the header, 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, wait, wait, wait, wait, okay, it's looking at the inefficiencies as opposed to, I've
worked with quite a few car companies, and they basically have a lot of meetings.
There's 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 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 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 sensors 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 teleoperation, like okay, yeah, yeah, it's difficult to have good signal, but can
we actually, can we have, can we consider the probability of those edge cases and what
to do in the edge cases when the teleoperation fails?
Like how difficult is this?
What are the costs?
How do we actually construct a teleoperation 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?
You know, like having that conversation as opposed to kind of having, you know, you show
up to work and say, all right, it seems like, you know, because of COVID, we, you know,
are not making as much money.
Can we have a cheaper, can we give less salary to the trucker and can we build, like, decrease
the cost or decrease 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.
And 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, they're 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 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 than 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?
Because, you know, and that's the best way to organize certain kinds of activities is
the market and private interest.
But I think we go too far in some areas.
Transportation is, if we can't have a public debate about the roads that we all pay for,
forget about it, private factories and, you know, all these other, you know, health care
and other places.
It's going to be way harder there, health care, I guess, has some, you know, 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.
And it's just, it's not, it's not in their, I get asked this question, like, what should
companies do?
And I'm like, you know, 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, you know, have species
level goals, you know, like, oh, well, you know, we're going to go to Mars.
I mean, that's amazing, and that's incredible 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, you know, it's
who builds the roads, you know, I mean, the money that sloshes around on Capitol Hill to
decide what happens in these infrastructure bills and the transportation bill is just
obscene.
Right?
See, I think it's just an interesting view of markets.
Correct me if I'm wrong.
Let me, 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 like those big projects don't seem to have an obvious value.
But world, our world progresses by those big leaps.
And then as 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 probably a bad example, but like a Henry Ford type of character steps
in and say like, we need to do stuff completely differently.
Yeah.
And you 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.
You disagree.
God damn it.
I mean, the two of us, you're the knowledgeable one.
No, no, I think it's a matter of like, do we need those heroes?
Absolutely.
I mean, I saw the, you know, the boosters come down from SpaceX's rockets and, you know,
land nearly simultaneously with my kids, you know, after school one day.
And I thought, oh my God, like, this is like science fiction has been made real.
It's incredible.
And it's a pinnacle of human achievement, right?
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 got to climate change, you know, I mean, all the heroes out there, right?
I mean, it's time, it's time, the clock is ticking.
It's past, 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 didn't...
So adaptation versus prevention is like acceptance that there's going to be catastrophic impact.
We just need, we need to figure out how 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 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, Daimler 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 sets the stage that's critical.
And you know, and what it really is, it's a sociological problem, right?
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, you know, 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, in 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 you
know, where the, who benefits from the investment.
And you know, we need to, you know, I don't know that we can do it, but you know, if we're
going to 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, you know, and rewarding the
people who do incredible things, please, you know, we don't want to squash that, but we
need to harness that power to solve what I think are some pretty big, you know, 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, other
things, but we, we gotta be careful, right?
Because 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, that built the United States
into the world superpower that it became and the industrial power that it became, it rested
on transportation, right?
It was like, you know, 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, you know, crazy, right?
But those public infrastructure projects, the, the canals, right, 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, the, the, the payback that the U.S. economy got from
the Dwight D. Eisenhower interstate system is phenomenal, right?
No private entity was going to do that, electrification, dams, water, you know, we, we need to do
these infrastructure, 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.
It's one of the only bipartisan things is at, 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 and 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 to date, 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 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 of 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, Alex.
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 bowl 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, you know, just let's take, let's take just,
you know, labor and climate, right?
There are other issues, congestion, et cetera, infrastructure, that are going to be affected
by this, you know, 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, rebuilding
those institutions.
I mean, that's what we've seen in the last four years, right?
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, it's not bad for you.
And I know the economists will probably get in the comment box now, you know, about how
we look forward to your comments, to 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 that 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 hurt
him, right?
You know, go to these places where there's competition, right?
And yes, we benefit overall, but we have a system that allows some people to pay really
high costs.
And Trump tapped into that, you know, and there was no, you know, that's more than that
too, obviously.
And there's lots of really dark stuff that goes along with it, you know, the sort of
racialization of others and things like that.
But he hit on those core, you know, issues that, you know, 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.
Yeah.
And that was there, you know, and you could just ignore it as long as you want and tell
people, don't worry, trade's good for you.
Don't worry, immigration's 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, you know, 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, you know, these institutions that I find magical,
right?
I mean, you look at the vaccine research and stuff, you know, just, you know, brilliant,
you know, people doing incredible things for humanity, like, you know, the idea that,
like, you know, 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 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, you know, it's like, where are we, you know, so we need to rebuild the
faith and trust in those institutions and have these, but we need to have honest conversations
before people are going to buy it, you know?
Do you have ideas for rebuilding the trust and giving a voice to the voices, so is the,
many of the things we've been talking about is so sort of deeply integrated.
You think like, this is the trouble I have with people that work on 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 not just how do we have a job that gives you
money to feed your 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 coupled with that hope is that there will not be too much suffering in the transition.
And that's not obvious as 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.
Now, we had a system, right?
And that's why I would say, you know, go to that, you know, Harry Bridges report, Bridges
report.
And, you know, those were workers who had a sense of power.
They said, you know what, we can demand some of the benefits, like, yeah, automate our
jobs away, but, you know, kick a little down to us, right?
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, you know, less efficient in places.
But the key compromise is tie wages to productivity.
That's what we did.
We tied, that's what unions did.
We tied wages to productivity, kept them and up, right, it was good for the economy,
some economists think, right?
And that's what, you know, 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, you know, I can learn from every single
person, you know, did I have to talk to the 200th truck driver?
In my opinion, yes, because I was going to 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, you know, I...
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 try to, so I try to be a sounding board
and I feel a tremendous weight of responsibility, you know, for that.
But I'm not those workers, you know, and they may listen to this or, you know, walk in the
door sometime, it's about be like, that guy's full of shit, that's not what I think at all.
And they don't get heard over and over and over.
But in a small way, you are providing a voice to them and that's kind of the, if at scale
we apply that empathy and listening that we could provide the voice to the voiceless
through our votes, 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 a community that listens
to the pain of others and tries to minimize that, to try to give a voice to the voiceless,
to give power to the powerless.
I have to ask you on by way of advice, in 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 to 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?
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, you know, sense of what it was going to be
useful for.
And his lesson was, you know, you can't connect the dots looking forward, you know, looking
back, you can see all the pieces that sort of led you to where you ended up.
For me, studying truck driving, like, I mean, I literally went to graduate school because
I was worried about climate change and like, you know, 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 sort of 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 going to like 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 know, you would do none of the things that I did that many people advise me against
where like, you can't like go spend a year working as a truck driver, you know, like,
that's crazy or you know, you can't, you know, spend all this time trying to write like one
huge book and, you know, so I mean,
By the way, if I could just interrupt, what, what, 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, took that leap.
What the heck?
What the heck is up with your mind that allowed you to take that big leap?
So I think it's probably like Tolkien and Lord of the Rings, you know, 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 ended
up dead and traumatized my family, including like a couple of week trip in the Pacific,
like solo trip on a kayak and basically my kayak experience up till that, you know, point
had been, you know, on a fairly calm lake and like class one solo trip on a kayak in
the Pacific.
Yeah.
Yeah.
So I was working on forestry issues and we were starting a campaign up 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 like devoting my
sort of, you know, life right now to and just drove up there with this kayak and, you know,
put into the Pacific and it was insane, you know, like the tides are huge and, you know,
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, ill fit I was, but that's just, I think I've always had that.
Were you afraid when you had that wave before you?
That wave scared the shit out of 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, there was one time where I was like, okay, you
know, and I grew up around people worked on cars and I've been to drag races and NASCAR
and I've been to, you know, Colgate University and I, and I think that was probably my initial
training was, you know, being this just working class kid who ends up in this, you know, sort
of blue blood, small liberal arts college and just feeling like, you know, both having
the entire world opened up to me, like philosophy and Buddhism and things that I had never heard
of, you know, and just became totally obsessed with and just like, you know, just following
my interests.
But also culturally perhaps didn't feel like you fit in.
Feeling like just a fish out of water and just, you know, but, and at the same time
that, you know, sort of drove me in the sense that it drove an opening of my mind because
I couldn't understand it.
You know, I was like, 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, like, you know, 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, sort of went from there.
And then develop your fascination with people.
And the funny thing is, you went from trucking now to autonomous trucks.
I mean, just 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 is very difficult to, first
of all, us meeting is a funny little thing given the things I'm working on with robots
currently, but, you know, it may not relate to trucks at all.
There's, 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.
That's crazy.
I mean, even four or five years ago, I would, if you had asked me if I was going to be studying
trucking still, I would have said no.
And so my advice is, I think if I was going to give advice, you know, is, you know, you
can't connect the dots looking forward.
You just got to 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 bright gifted kid
that gets identified as like, oh, you could go somewhere, then we're like, we feed them
stuff.
We're like, we'll learn the piano and learn another language, right, to learn robotics.
And then we tell other kids, like, oh, learn a trade, you know, like figure out what's
going to pay.
And not that there's anything against trades.
I think everyone should learn, like, manual skills to make things.
I think it's incredibly satisfying and wonderful, and we need more of that.
But also, you know, tell, you know, all kids, it's okay to, like, take a class in something
random that you don't think you're going to get any economic return on, because maybe
you will end up going into a trade, but that class that you took in studio art is going
to mean that, you know, you look at buildings differently, right, or you end up sort of
putting your own stamp on, you know, woodworking, you know, it just, I think that's the key
is like follow, you know, it's cheesy because everybody says follow your passion.
But, you know, if we say that, and then we just, you know, the 90% of what people hear
is, you know, what's the return on investment for that, you know, it's like, you're a human
being, like things interest you, music interests you, literature interests 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.
It was really stupid.
Don't go do something stupid and something you'll regret a lot later.
My poor mother.
Thank God she didn't know.
Well, let me ask is for a lot of people work, for me it is quote unquote work is a source
of meaning and at the core of something we've been talking about with jobs 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?
Sort of 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 know, you do it for a paycheck.
And I think we do have to be, you know, honest about that.
There are a lot of people who, you know, don't love their jobs and, you know, we don't have
jobs that they're going to love, you know, and maybe that's not a sort of realistic,
you know, that's a utopia, right?
But for those of us that have the luxury, I mean, I think you love what you do that
people say that.
I think the key, you know, for real happiness is to love what you're trying to achieve.
And maybe you 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, you know, are really happy and have great impacts, you know, 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 necessary about
helping other people directly.
There's something about craftsmanship and skill, as we've talked about, that's almost
like you're celebrating humanity by, like, searching for mastery in the task.
In the simple, like, especially tasks that people outside may see as menial, as not important,
but 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'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 sanded these old 100-year-old floors and made them look gorgeous and this is craft.
That's love right there.
Yeah, I mean, he showed us some love, you know, the product was just like, is 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, Lexi.
I'm a big fan, so it's just been great to be on.
Thanks for listening to this conversation with Steve Vaselli.
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.