The following is a conversation with Steve Vaselli, 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 Vaselli.

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 is 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 gotta 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.

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?

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, you know, 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 kind

of people, you never talk to us regular folk.

And that guy really stuck with me.

First of all, the idea of regular folk is a silly notion.

I think people that win Nobel Prizes are often more boring than the people, 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 in trucking, you know.

And I send them to truck stops, you know, I say, you know, yeah, there's a town called

Effingham, Illinois.

It's just this place where, you know, a bunch of huge truck stops, tons of trucks and really

nothing else out there, you know, it's in the middle of corn country.

And you know, again, truckers in this, you know, sadly, I think, you know, the politics

of the day, it's changing a little bit.

I think there's a little, the polarization is getting to the trucking industry in ways

that, you know, maybe we're seeing in other parts of our social world.

But truckers are generally, you know, real open, sort of friendly folks.

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 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 podcasts, audio books?

Do they listen to music?

Do they listen to silence?

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.

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, offshored and they end up going to trucking because it's a place

where they can maintain their income.

And so it's super high stress.

Like they've left their family behind, maybe they quit another job.

They're typically being charged a lot of money.

So that first couple of weeks, like you might get charged $8,000 by the company that you

have to pay back if you don't get hired.

And so the stakes are high and this machine is huge and it's intimidating.

And so it's super stressful.

I mean, I watched, you know, men, grown men break down crying about like how they couldn't

go home and tell their son that they had been telling they were going to, you know, go become

a long haul truck driver that they'd failed.

And it's kind of this super high stress system.

It's designed that way partly because as one of my trainers later told me, it's basically

a two week job interview.

Like they're testing you.

They're seeing like, you know, how's this person going to respond when it's tough, you

know, when they have to do the right thing and it's slow and, you know, they need to

learn something.

Are they going to rush, you know?

Or are they going to kind of stay calm, figure it out, you know, nose to the grindstone?

Because when you're in a truck driver, you're 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

they, 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 you'll 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, you're 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, you know, gears and you just can't, you know,

and they just shut down.

They're like, this isn't for me.

I can't do it.

You're right.

It takes years.

If, you know, trucking is not considered a skilled occupation, but, you know, my six

months there, and I was 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 and between that and the really skilled drivers who've

been doing it for 20 years, you know, is still another step beyond that.

So it is highly skilled.

Would it be fair to break trucking into the task of truck, of driving a truck 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 and out, right?

So always have that safe place that you can put that truck in case that four wheeler in

front of you who's texting loses control, you know, what are you 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 when you turn the bills in, which is the paperwork that goes with the load.

So you have to get that back to your company and then that's how they 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 $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 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?

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'll then continue when we start talking

about autonomous trucking.

But you know, you're saying all these cents per mile kind of thing.

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 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 the technology problem that one of several technology problems that could

be addressed.

I mean, what, 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 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 the 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, does they don't make minimum wage oftentimes?

Right.

Just to be clear, what we're dancing around here is that a little bit over, a little bit

under minimum wage is nevertheless most truck drivers seem to be making close to minimum

wage.

Like this is the, so like we maybe haven't made that clear.

There's a few that make quite a bit of money, but like you're as an entry and for years,

you're operating essentially minimum wage and potentially far less than minimum wage

if you actually count the number of hours that are taken out of your life due to your

dedication to trucking.

Well if you count like the hours taken out of your life, then you got to go, you know,

maybe a full 24.

That's right.

Yeah.

From family, from the high quality of life parts of your life.

Yeah.

And there's a whole 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've 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's 60,000 is a very little money for that.

But you're saying if it was 60,000, you wouldn't even have the shortage.

If that was the minimum.

If that was the minimum.

And I think that's what, now we have drivers who start in the 30s.

Wow.

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 are 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, you know, regular promotion of the idea that there's a shortage

is always projecting forward and says, you know, 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.

Like, this is somebody who probably quit another job, was unemployed and took months

to go to a training school, right, paid for that training school oftentimes, left their

family for months, right, invested in what they thought was going to be a long term career

and then said, you know what, forget it, I can't, I can't do it, you know.

So yeah, so it's not just skill, it's like they were psychologically invested potentially

for months, if not years into this 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 job, the problems with the job and the labor market, right, but let's start

with the job, which is, you know, again, just so much time that's not compensated directly

for the amount of time, and that's just psychologically, and this was a big part of what I, you know,

I studied for the first book was, you know, that conception of like, what's my time worth,

right, and like, what truck drivers love is oftentimes is that tangible outcome based

compensation.

So they say, you know what, you know, 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.

Yeah.

Or worthless.

Yeah, and again, the industry is going to say, for instance, okay, well, you know, they've

got skin in the game, right, that argument about sort of compensation based on sort of

output, right, but that's a holdover from when you couldn't observe truckers.

Now they all have, you know, satellite linked computers in the trucks that tell these large

companies, this driver was, you know, at this GPS location for four and a half hours, right.

So if you wanted to compensate them for that time directly, and the trucker can't control

what's happening on that customer location, you know, they're waiting for that, you know,

confirmed 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.

Can you try 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?

What's the competition?

What's the alternative to transporting goods via trucks?

What seems to be broken here from an economics perspective?

Yeah.

So it's, well, nothing.

It's a perfect market.

Okay.

Right?

I mean, so for economists, this is how it should work, right?

But the inefficiencies, like you said, are to interrupt or push 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 training, publicly subsidized training to become a truck driver.

And so all of these are externalities that the companies don't have to pay for.

And so this makes it the most profitable way to move freight.

So trucks is way cheaper than trains?

Well over the long, so one of the big stories for these companies is that the average length

of haul, which becomes very important for self driving trucks, the average length of

haul has been steadily declining.

Over the last 15 years or so, I love this industry collected data from sort of 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 Penn 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'd 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 as 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?

Today we have really good jobs and some really bad jobs.

We have 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.

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 kind of 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 and 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 sort of 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 sit in the deal with

office politics like, just give me what you care about and I'll take care of it.

Just pay me fair, you know, 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 I don't, you know, and this was one of the things I talked to truckers about a lot.

Yeah.

What's their perception of Jimmy Hoffa, for example, and of unions?

Yeah.

So, and this was probably one of the central hypotheses that I had going in there.

And it may sound, you know, someone who does hard science, right?

You may, if you hear a social scientist, you know, sort of use that terminology, even other

social scientists.

Hypothesis.

Yeah.

You know, they don't like it, but 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 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, 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 than 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, 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, under

regulation too.

And so these terminal systems, what you do is you do a bunch of local pickup and delivery,

maybe 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.

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 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 have built really long, really lean supply chains 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 in bad shape.

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 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.

And so we've had all these perverse 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 want to be 90% plus.

You don't want a lot of open bays sitting around.

So we don't have 10% extra capacity in warehouses.

We don't have 10% of them.

Trucking capacity can fluctuate a bit, but you don't have that kind of slack.

And now, and we saw this when people shifted consumption, and I get a little mad when people

talk about panic buying as the reason that we had all these shortages.

It's preventing us from understanding the real problem there, which is that lean supply

chain.

Sure, there was some panic buying, no doubt about it, but we had an enormous shift in

people's behavior.

So with my sister and brother in law, I own a couple of small businesses and we serve

food.

So we get food from Cisco.

Cisco couldn't get rid of food because nobody's eating out.

So they've got 50 pound sacks of flour sitting in their warehouse that they can't get rid

of.

They've got cases of lettuce and meat and everything else that's just going to go bad.

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.

So that stuff leaves Asia months before you want to have it on the shelves, and you're

predicting based on last year what you want on that shelf.

And so it's a, 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 that you're referring to too much

in a certain place, not enough in another place.

And it's just the supply chain is not robust, those kind of dynamic shifts in who gets what

where.

Yeah.

Yeah.

I mean, so, and 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 and 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 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?

We should, we can back off and start, you know, back things are back to normal.

Let's lean out.

But 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 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, right?

It's such a simple idea, right, truck that drives itself, classic blue collar job that

pays well, guy maybe with not a lot of other good options, right, to sort of make that

same income easily, right, and you build a robot to take his job away, right?

So I think 2016 or so, that was the big question out there, and that's actually how I started

studying it, right?

I just wrapped up the book, just so happened that somebody 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?

And at that time, there were a lot of different ideas about how they were going to play out,

right?

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, right?

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's super diverse, you know, this is just, I haven't given a

ton of thought, but it can't be that, you know, it's not that simple, you know, it never

is.

And so she was like, will you, you know, will you do this?

And I was like ready to move on to another topic, you know, I'd like been in trucking

for 10 years.

And that 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.

We'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 estimates 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, 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 then software engineering

allows you to automate a lot of the tasks at Microsoft Excel does, you know, but it

opened up so many opportunities.

Even with things that are difficult to imagine, like with the internet, I don't know Wikipedia,

which is widely making accessible information.

And that 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, 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.

But that was even before that they had this priority.

We would not be sitting here today if Congress in 2000 had not said, let's bring this about.

So they already had that vision, actually, I didn't know about that.

So for people who don't know the 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 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 around and we still don't

know.

And the T word, trillions of dollars in terms of transformative effects of autonomous vehicles

and all that started from DARPA and that initial vision of I guess is you're saying

of automating part of the military supply chain.

Yeah.

I did not know that.

That's interesting.

So they had the same kind of vision for the military as we're not talking about a vision

for the civilian, whether it's trucking or whether it's autonomous vehicle, sort of a

ride sharing kind of application.

Yeah.

I mean, what an incredible spark, right?

And just the story of 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, like, 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?

And these are not, you know, these are not tech companies, right?

These are industrial giants, right?

What were in the 20th century, the pinnacle of industrial production in the world in human

history, right?

And they're focused on it now.

So if we don't pull this off, it's like, wow, you know.

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 like, 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, it seems like giving GM and Ford and all these companies now are a little

bit like, hey, or Toyota and even Tesla, like, 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'd be too many failures, it'd be really

annoying, it'd be a gimmick, a toy.

It wouldn't actually create a pleasant experience.

And when I first 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.

There's not a lot of great stuff written, then you kind of have to, you know, there's

not a lot of data and places to know 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 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 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 rail

roads, 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, right, to fit what trucks could

do.

And so transportation and logistics, right, become Walmart's, you know, edge, right, and

allows them to dominate the space.

That's the challenge that Amazon has now, they've mastered the digital part of it, right,

and now they got to figure out like, how do we, you know, dominate the actual physical

movement that 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, right, and you've got, you know, a bunch of meat in a warehouse

and it's going to grocery distribution centers, you know, you have that trucker probably come

in the night before and you make him wait so that he has, you know, 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, right, so he can drive his full 11 hours and bring that meat

so it doesn't have to sit overnight in that refrigerated trailer, right, and so their

system is based on that.

Now, what happens when that truck can now travel two times as far, right, 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, right, so this is going to remake landscapes in the same

way that big box supply chains did, right, and then of course the further compliment

of that is, you know, how do you then get it to two people at their door, right, and

you know, the big box supply chain, it moves very few items in really large quantities

to very few locations pretty slowly, right, eCommerce aspires, you know, to do something

completely different, right, move huge varieties of things in small quantities virtually everywhere

as fast as possible, right, and so that is like that intercity trucking under the, you

know, in the era of railroad monopolies, right, the demand for that is potentially

enormous, right, and so there's such a, so right now I think a lot of the business plans

for sort of automated trucks, right, 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, uh uh, like this is

transformative technology, we're going to change the way we get stuff.

So we'll actually get a lot more trucks, period, with like, 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, you know, ideas about like, man, we, you know, here's

how far, how it's how close we could get to meet this demand.

That demand is going to radically change, right, these trucks are, you know, so then

we've got to think about, all right, if it's not batteries, you know, how are we, 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.

Well, before we get there, can I just make one interesting observation that I made as

a driver, when you're in a truck you're up higher, so you can see further and you can

see the traffic patterns and cars move in packs.

I'm sure there's academic research on this, right, 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 almost

free flowing highways, they kind of move in packs and you can kind of see them in the

truck.

So, you know, rather than platoons, we might have like hives, you know, of trucks, right?

So you have like 20 trucks moving in some coordinated fashion, right?

And then maybe the self driving cars are, you know, because people don't like to be around

them or whatever it is, right?

You might have a pod of, you know, 20 self driving cars sort of moving in a packet behind

them, you know?

This is what, if the aliens came down or were just observing cars, which is one of the sort

of prevalent characteristics of human civilization 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, you know, impacts

might be.

And then I talked to everybody I could find who was, you know, thinking about developing

a self driving truck.

And the question was essentially, you know, what are you, what are you trying to build?

Like, what do you envision this thing doing?

It turned out that that for a lot of them was an afterthought.

They knew the, the sort of technological capabilities that a self driving vehicle would have.

And those were the problems that they were tackling, you know, they were engineers and

computer scientists.

Oh, robotics people, I love you so much.

This is the, I could talk forever about this, but yes, there's a technology problem.

Let's focus on that 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.

Yeah, yeah.

So I mean, you know, I'm sure you know the division of labor in these companies, right?

They're sort of a business development side, you know, and then there's the engineering

side, right?

And the engineers are like, oh my God, what are these business development people, you

know, why are they involved, you know, in this process?

So I ended up sort of coming up with a few different ideas that people seem to be batting

around and then really tried to zero in on a layman's understanding of the limitations,

right?

And it turns out that's really obvious and quite simple.

Highway driving is a lot simpler, right?

So you know, the plan is simplify the problem, right?

And focus on highways because city driving is so much more complicated.

So from that, I came up with basically six scenarios, actually I came up with five that

the developers were talking about.

And then one that I thought was a good idea that I had read about, I think in like 2013

or 2014, which was actually something that the US military was looking at.

I actually first heard about the idea of this kind of automation, at least in sketched out

form in like 2011, I guess it was with Peloton, which was this sort of early technology entrant

into the trucking industry, which was working on platooning trucks.

And all they were doing was, you know, 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, you know, pedestrians, you know, all the things that self driving trucks don't like,

truckers don't like, right?

And they're not paid, there's lots of waiting time.

And then in the highway, they get to cruise, they're getting paid, they have control, they

go at their own pace, they're making money, they're happy.

Well, it turned out, I guess it was around 2010, this is still when we were thinking

about regenerative braking, you know, and hybrid trucks being sort of like the solution.

The problems with them, sort of, and the advantages, you know, also split on what I was thinking

of is kind of the rural urban divide at that time, right?

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, you know, hybrid electric in the rural highway, you

want aerodynamics, right?

There you want low rolling resistance tires and these super aerodynamics sleek trucks,

right?

Where we know with off the shelf technology today, we could double the fuel economy more

than double the fuel economy of the typical truck in that highway segment, if we segmented

the duty cycle, right?

And so in the urban environment, you want a clean burning truck, so you're not giving

kids asthma, you want it lighter, so it's not destroying those less strong pavements,

right?

You're not, you can make tighter turns, you don't need a sleeper cab because the driver,

you know, hopefully is getting home at night, right?

In the long haul, you want that super aerodynamic stuff, now that doesn't get you anything in

the city and in fact it causes all kinds of problems because you turn too tight, you crunch

up all the aerodynamics that connect the tractor and the trailer.

So the idea that I had was like, okay, what if we deliberately segmented it?

Like what if we created these drop lots outside cities where, you know, a local city driver

who's paid by the hour kind of runs these trailers out once they're loaded, you know,

doesn't sit there and wait while it's being loaded, they drop off a trailer, they go pick

up one that's loaded, they run it out, when it's loaded, they call them and they just

run them out there and stage them.

It's like an Uber driver, but for truckloads.

Yeah, and we have 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, you know, a trucker picks it up and delivers it, right?

So instead of having the rail, you'd have these super aerodynamic hopefully platoons

or what was at the time was called long combination vehicles, which is basically two trailers

connected together, right, 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, you know, drive to Wisconsin, drive to Florida, you

know, I get home every two weeks.

If I'm just running that, you know, that double trailer, I might be able to go back and forth

from Chicago to Detroit, right?

Take two trailers there, pick up two trailers going back, right, and be home every night.

Now, the problem with that at the time or one of them was, you know, bridge weights.

So you can't, not all bridges can handle that, 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, they're very careful about that.

But when you're, 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, 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, what's out, out, you know, the front

of his truck, and then somewhere like it's too close, and it might be one of those things

that's just, you know, takes an adjustment to, 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, the engine is designed with higher pressure feeding that engine, right?

So there's, there are sort of adjustments that you need to make and, you know, still

the benefits are, 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, heard about, was working

on another scenario, which was, you know, to solve that local problem was going to do

teleoperation, 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, teleoperation 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.

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 Softman in next month, actually, I'm a huge

fan of his because he was, I think the founder of Anki, which is a toy robotics company.

So I love cute, I love human robot interaction and he created one of the most effective and

beautiful toy robots.

Anyway, I keep complaining to them on email privately that there's way too much marketing

in these conversations and not enough showing off the, both the challenge and the beauty

of the engineering efforts.

And that seems to be the case for a lot of these Silicon Valley tech companies.

They put up this, you'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, 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, 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, of 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, how much

intelligence is required to drive a car?

So from a, like a Jim Keller, who 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 teleoperation from Starsky's is really interesting idea.

How much can, I mean, there's a few autonomous vehicle companies that tried to integrate

teleoperation in the picture.

Can we reduce some of the costs while still having reliability, like catch when the vehicle

fails by having teleoperation?

It's an open question.

So that's for you scenario number two, is to use teleoperation 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 how you estimate labor impacts,

what these models look like.

And a lot of it is about how automatable is a job.

Technic 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 cutting edge, computer science.

So on the teleoperation 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, right?

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 is

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 on the to do list, right?

After solving the self driving question is like, yeah, what do we do with the problems,

right?

We could we can imagine like, all right, we have some, you know, protocol that the truck

is not, you know, realizes the system says, not safe for operation, pull to the side.

Good, you have a crash, but now you got a truck stranded on the side of the road, you're

going to send out somebody to like calibrate things and check out what's going on or that

sounds like expensive labor, it sounds like downtime, it sounds like the kind of things

that shippers don't like to happen to their freight, you know, in a in a just in time

world, and so wouldn't it be great if you could just sort of, you know, loop your way

into the controls of that truck and say, all right, we've got a sensor out says me that

says that the tire is bad, but I can see visually from the camera looks fine, I'm going to drive

it to our next depot, you know, 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 teleoperation often gets this, you know, so dismissive, you know, commentary from from

other folks working on other other scenarios.

But I think it's it's potentially more relevant than than than we we hear publicly, but it's

a hard problem and you know, for me, I've gotten a chance to interact with people that

take on hard problems and solve them and they're rare, what Tesla has done with their data engine.

So I thought autonomous driving cannot be solved without collecting a huge amount of data and

organizing well, not just collecting but organizing it.

And exactly what Tesla is doing now is what I thought it'll be like I couldn't see car

companies doing that, including Tesla.

And now that they're doing that, it's like, oh, okay, so it's possible to take on this

huge effort seriously, to me, teleoperation is another huge effort like that.

It's like taking seriously what happens when it fails.

What's the in the case of Waymo for 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.

I mean, just the whole experience is a mess that has a ripple effect to how you trust

in the entirety of the experience, but like actually taking on the problem of that failure

case and revolutionizing that experience, both for trucking and for ride sharing.

That's an amazing opportunity there because that feels like it would change everything.

If you can reliably know when the failures happen, which they will, you have a clear

plan that doesn't significantly affect the efficiency of the whole process.

That could be the game changer.

If teleoperation is part of that, it could be, just like you're saying, it could be teleoperation

or it could be like a fleet of rescuers that can come in, which is a similar idea, but

teleoperation obviously, that allows you to just have a network of monitors, people monitoring

this giant fleet of trucks and taking over when needed.

It's a beautiful vision of the future where there's millions of robots and only thousands

of humans monitoring those millions of robots.

That seems like a perfect dance of allowing humans to do what they do best and allowing

robots to do what they do best.

Yeah.

I mean, I think there are, and we just applied for an NSF.

We didn't get anybody's watching, but with some folks from Wisconsin who do teleoperation.

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.

It's near Perth and it's quite remote.

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.

I think 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.

For instance, if there were teleoperation centers, maybe they go in these communities

that we disproportionately source truck drivers from today.

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.

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.