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Speaker 1: That that truck we call the red and white one,
Speaker 1: that's the bust of our videos. Um, what's the truck
Speaker 1: we're writing called buster Buster? Okay? A couple of weeks ago,
Speaker 1: I went down to South Florida for a road trip
Speaker 1: in a self driving truck. Ready. Yeah, I was sitting
Speaker 1: in the back of a cabin on a bed, actually
Speaker 1: in a freight Liner Cascadia. That's like the biggest, baddest
Speaker 1: truck you can buy. We're on Florida's Highway twenty seven
Speaker 1: with the Everglades on either side. Truckers call this part
Speaker 1: of Florida Alligator Alley. I was riding along with a
Speaker 1: team from star Ski Robotics, and then the driver, Jeff Runions,
Speaker 1: took his hands off the steering wheel and slid his
Speaker 1: feet off the petals. Oh my god, this sounds terrifying.
Speaker 1: And you're on a bed. I mean there are there
Speaker 1: even seatbelts no seatbelts, and Brad, I don't know if
Speaker 1: you realize how big and heavy these trucks are, and
Speaker 1: they go fast, and all of a sudden he takes
Speaker 1: his feet off the petals and then a gust of
Speaker 1: wind hit the truck and the computer sort of lurched
Speaker 1: us towards the left wane. He's trying to fight. I
Speaker 1: was freaking out, but everybody else in the truck was
Speaker 1: acting pretty much normal. Maybe they knew something about the
Speaker 1: air bags in the back of the vehicle that you didn't.
Speaker 1: There weren't any air bags, but there were algorithms, and
Speaker 1: those algorithms need a little bit of time to understand
Speaker 1: the driving conditions on a given day and to figure
Speaker 1: out just how much to sort of push the steering
Speaker 1: wheel to fight against the wind. You are in the morning,
Speaker 1: when before you have your bath. Star Ski is still
Speaker 1: fine tuning its technology to make sure it works in
Speaker 1: all scenarios, and if they succeed for truckers, which is
Speaker 1: one of the most common jobs in the United States,
Speaker 1: that could mean huge changes. Back. Hi, I'm Brad Stone
Speaker 1: and I'm Max Chapkin, And this week on Decrypted, I
Speaker 1: ride a robot truck from Fort Lauderdale to Tallahassee. From
Speaker 1: small startups to Silicon Valley's biggest tech companies in the
Speaker 1: world's largest automakers, there's a race to build a software
Speaker 1: that could power a future of cards without drivers. Long
Speaker 1: haul trucking will likely be one of the first areas
Speaker 1: to feel this profound shake up. This technology promises to
Speaker 1: make our road safer and our goods cheaper, but it's
Speaker 1: a transition that will have consequences. Trucking is worth seven
Speaker 1: hundred billion dollars in the U. S Alone right, and
Speaker 1: it employs a lot of people. More than three million
Speaker 1: Americans drive trucks for a living, and another four million
Speaker 1: support the trucking economy and jobs like waitressing and roadside
Speaker 1: cafes and being a gas station attendant. It's also a
Speaker 1: job that lower income Americans depend on. What happens to
Speaker 1: these workers is a question that needs to be answered.
Speaker 1: This episode kicks off a series of pieces about technology
Speaker 1: that threatens to replace jobs. It's one of the most
Speaker 1: important tech stories of our time. If you have a
Speaker 1: story to share with us about your job and the
Speaker 1: oncoming wave of automation, record a voice message and send
Speaker 1: it to decrypted at Bloomberg dot net. So Max, Right now,
Speaker 1: self driving car research is absolutely dominated by big name
Speaker 1: comp and is Google, Uber, Ford and and GM, pretty
Speaker 1: much every Detroit automaker, the Chinese companies. So how did
Speaker 1: you find the small start up Starsky Robotics and why
Speaker 1: does the startup even matter? Right now? What's interesting? I
Speaker 1: got tipped off by one of their investors. They were
Speaker 1: backed by y Combinator, so shortly before demo day, I
Speaker 1: got tipped off, and people suggest I talked to him.
Speaker 1: But I think it's important to remember that a lot
Speaker 1: of these big companies working on driver list tech were
Speaker 1: really small, just very recently. The other thing that that
Speaker 1: drew me this is this guy was a little different.
Speaker 1: So I went to South Florida to see Starsky's trucks
Speaker 1: in action. My name is Stephan Seltzox Marker, and I'm
Speaker 1: the CEO and co founder of star Skirobotics, self driving
Speaker 1: truck company. Stephen is Starsky CEO. I found him interesting
Speaker 1: partly because of what he's not like. So I didn't
Speaker 1: go to Stanford. I didn't participate with two thousand four
Speaker 1: Dropper Grand Challenge. I'm not a Google exer. I don't
Speaker 1: really have any of the credentials of someone who's supposed
Speaker 1: to be good at this space. What interested me about
Speaker 1: Starsky was the sort of difference there, and also the
Speaker 1: fact that they had this different approach, which is that
Speaker 1: they're planning to use remote control drivers, basically people in
Speaker 1: call centers who are overseeing trucks. So if you're a
Speaker 1: truck driver, you don't necessarily have to spend three weeks
Speaker 1: in a truck, sleeping in your cab, eating truck stop food,
Speaker 1: talking on a CB radio. You just go to an office,
Speaker 1: you sit in a desk, you drive a truck for
Speaker 1: eight hours, and then you go home and see your family.
Speaker 1: I'm imagining this new new job is a little bit
Speaker 1: like playing Mario Kart for a living. It actually sounds
Speaker 1: kind of fun. The other thing is that Starsky, unlike
Speaker 1: other truck companies, is actually hauling cargo. So while they're
Speaker 1: collecting data and trying to log all these research midles,
Speaker 1: like all the other companies, they've also got like a
Speaker 1: load in the back of the truck that they're getting paid,
Speaker 1: you know, a modest amount of money for right, And
Speaker 1: we should know that many of these other companies have
Speaker 1: deployed lots of capital to to this kind of research.
Speaker 1: Starsky is only raised around five million dollars. Is the
Speaker 1: strategy of using real cargo presenting a different set of challenges. Though, Yeah,
Speaker 1: it sounds easy to run a trucking company, but it's
Speaker 1: not necessarily their Their first truck, which they nicknamed Rosebud,
Speaker 1: broke down even before they could get it out of
Speaker 1: San Francisco. And what was wrong with Rosebud, like, well,
Speaker 1: the bad alternator or something. So have you ever bought
Speaker 1: a truck before? Neither? And I that's that's the core
Speaker 1: problem with Rosebud. I bought. I bought a truck off
Speaker 1: an auction site. Starsky, as we mentioned, is just one
Speaker 1: of many companies working on this. The Silicon Valley companies
Speaker 1: of course, Detroit and and the big companies like bay
Speaker 1: Do in China that think they can make an impact,
Speaker 1: and Brad, don't forget the big trucking companies Volvo, Daimler,
Speaker 1: all the big names and trucking are also getting it
Speaker 1: in the space. So where is Starsky relative to these
Speaker 1: giants in terms of progress? So what stars He's going
Speaker 1: for is what's known as level three autonomy. And let
Speaker 1: me just explain quickly Level one autonomy is cruise control,
Speaker 1: your basic thing that is in lots of cars. Level
Speaker 1: two is cruise control and what's known as lane keeping,
Speaker 1: where the car will sort of steer for you. Okay,
Speaker 1: so take your hands off the wheel, but for god's sake,
Speaker 1: don't take a nap, right And Level three, what we're
Speaker 1: talking about with Starsky, means that the driver needs to
Speaker 1: be there in case of an emergency, but the driver
Speaker 1: can basically not pay attention during other times. Level four
Speaker 1: means driver can be totally out of picture, could be unconscious,
Speaker 1: could be texting whatever. And that's where the big companies,
Speaker 1: the Googles and forwards are focused on, honestly industry, yeah,
Speaker 1: whereas we want to be like a very real business.
Speaker 1: Len to be real business. Now, when Stephan says he
Speaker 1: wants to be a real business, he means that Starsky's
Speaker 1: plan is to have the driver only intervened in an emergency.
Speaker 1: But unlike say Tesla, which is also going for this
Speaker 1: same idea with a driver in the driver's seat, Starsky's
Speaker 1: idea is that the driver is going to be someplace else.
Speaker 1: We're building hours, so it's not needed person behind the
Speaker 1: wheel Because the point for US is to not have
Speaker 1: a person behind the wheel. So this is kind of
Speaker 1: like the military's use of drone pilots. Yeah, exactly. So
Speaker 1: Starsky when they raised their five million dollar funding round,
Speaker 1: they did so thanks to a video that they made
Speaker 1: where they were remote control driving a truck in a
Speaker 1: parking lot and it was making a sort of pseudo delivery.
Speaker 1: Their plan, and they want to do this by the
Speaker 1: end of the year, is to have a real delivery
Speaker 1: with real cargo where they pick up at the port,
Speaker 1: drive the whole distance, and then drop off, all using
Speaker 1: teleoperation using a remote control driver. And would that be
Speaker 1: the first such achievement of its kind as far as
Speaker 1: I know, Yes, And and Starsky is actually closer to
Speaker 1: this milestone than you might think because trucks, unlike say, cars,
Speaker 1: spend most of their time on highways, which is of
Speaker 1: course the easiest place to do autonomous driving, right, no pedestrians,
Speaker 1: no bikes, no traffic lights. Yeah, and and trucks are
Speaker 1: big and heavy, which means that it's a lot easier
Speaker 1: to get the sensors on them. And there's also this
Speaker 1: safety component. Trucks drive a ton of miles and they're
Speaker 1: involved in a lot of fatal accidents. So in theory,
Speaker 1: you could eliminate a lot of those if you'd let
Speaker 1: a computer do most of the driving. But of course
Speaker 1: there's a dark aligning to this potentially silver cloud. Trucking
Speaker 1: is a huge sector of the economy, employing millions of people.
Speaker 1: Having a computer drive the truck raises the specter of
Speaker 1: job losses on an epic scale. So it makes me
Speaker 1: want to run for the hills. It makes me want
Speaker 1: to hug my kids. I hope they have a future.
Speaker 1: That's Ed Witkin, the president of the Transportation Trades Department
Speaker 1: for the a f l C i OH. He's basically
Speaker 1: a big union muckety muck in the world of trucking.
Speaker 1: Um unions including the a f l C i O
Speaker 1: and the Teamsters, which are the big well known trucking union,
Speaker 1: are warning that this could be really, really bad for
Speaker 1: their members, which isn't surprising, right. It taps into an
Speaker 1: almost primal fear. Computer come, they take our jobs, right,
Speaker 1: But trucking is weird because it's one of those jobs
Speaker 1: that a lot of people don't really want. This is me,
Speaker 1: I don't take take companies because truck and burgers sixties
Speaker 1: seventy hours. Some of the like going on players of
Speaker 1: working eighty hours just to trying to pay that drop.
Speaker 1: I had a big, stretched out truck, big thing. But
Speaker 1: you know I live in this drug staying it for
Speaker 1: a couple of days, and you'll know what I'm found about.
Speaker 1: That's Jeff Runyons again. The truck driver was behind the
Speaker 1: wheel on the drive in Florida. He told me what
Speaker 1: being a long haul trucker was like, plus to eat terrible. Yeah,
Speaker 1: you know, you get truck stout. I used to go
Speaker 1: to memphitt Of all the time. That's why I was
Speaker 1: two fifty. Stopped at the drug stops. You got green
Speaker 1: fright to make in the cafes. You go to any
Speaker 1: truck stop and you'll see everything's fatty. Yeah, yeah, yeah.
Speaker 1: I think companies treat you like they say drivers or
Speaker 1: dom a dozen't so. Despite the glorification of the occupation
Speaker 1: in the seventies and movies like Smoking in the Band
Speaker 1: at bad Food, poor treatment from your employer doesn't sound great.
Speaker 1: And the wages are bad too. I mean, people think
Speaker 1: of trucking as being this this kind of good paying job,
Speaker 1: but the truth is the average trucker makes around forty
Speaker 1: dollars a year, and that easily includes you know, sixty
Speaker 1: seventy hours of work every week, so in the end,
Speaker 1: you're not making that much better than minimum wage, right,
Speaker 1: And that explains why the industry sees such high turnover.
Speaker 1: There's a massive labor shortage. And this is what you
Speaker 1: hear if you talk to people who are who are
Speaker 1: involved in autonomous trucking. The American Trucking Association, the big
Speaker 1: trade group, says that around fifty thou trucking jobs are
Speaker 1: unfilled at the moment, so there is appetite for more
Speaker 1: and more truckers. That's my colleague josh Idolson, who covers
Speaker 1: labor relations for Bloomberg. The volume of stuff to move
Speaker 1: around the country keeps getting bigger, and the number of
Speaker 1: people coming in to the industry to drive and staying
Speaker 1: in it is not keeping up, in large part because
Speaker 1: so many people leave. Turnover is so high because being
Speaker 1: a trucker is pretty much terrible, but in some of
Speaker 1: the poorest parts of the country, it's also one of
Speaker 1: the only jobs available. One way to look at it
Speaker 1: is these are some of the most cherished, mediocre jobs
Speaker 1: in the United States. What about military service? Max is
Speaker 1: that comparable. It's yeah, Actually, it's it's very comparable. Josh
Speaker 1: says that, um, it's the it's people who are who
Speaker 1: might enlist in military service that the trucking companies are
Speaker 1: competing for. Maybe if they could get the federal law
Speaker 1: adjusted so that people who are younger than twenty one
Speaker 1: can do interstate trucking, maybe they could get people before
Speaker 1: they would otherwise decide to go to the military, for example.
Speaker 1: And this is why Starsky and the other Silicon Valley
Speaker 1: companies are so interested in the sector. This is a
Speaker 1: rare industry where computers could really help what the technology
Speaker 1: is and what it will mean for trucking jobs. That's
Speaker 1: coming up right after this word from our sponsor. You
Speaker 1: know where you want to be. Red hat has the
Speaker 1: broad portfolio of open source technologies to get you there.
Speaker 1: Meet your evolving business challenges head on with secure solutions
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Speaker 1: before the break. Max, you're explaining that even though the
Speaker 1: trucking industry employs millions of people. It's actually facing a
Speaker 1: big shortage of workers, and automating the driving process could
Speaker 1: directly address this. So let's explain what exactly automation involves. Okay,
Speaker 1: so there are two basic components that the sensors that
Speaker 1: are collecting data and the algorithms. So the sensors they
Speaker 1: tell the computer where the vehicle is, what's around it,
Speaker 1: and then the algorithm crunched the data to figure out
Speaker 1: what it should tell the vehicle to do. Companies that
Speaker 1: are aiming for the most advanced autonomy use something called LIGHTER,
Speaker 1: which stands for Light Detection and Ranging. Of course, it's
Speaker 1: somewhat controversial because Uber and Google are now fighting over
Speaker 1: some intellectual property around lighter. Star Ski like Tesla uses
Speaker 1: raiders and camera. Yeah, it's a lower tech approach and
Speaker 1: Stephen laid it out for me during our ride. So
Speaker 1: like what we have here in the front are like
Speaker 1: to automotive grade really high quality cameras yea with high
Speaker 1: body lens feed until our software got it. So while
Speaker 1: we drove, Jeff the driver basically kept his hands off
Speaker 1: the wheel and and Kevin Keo, a star Ski engineer,
Speaker 1: kept an eye on the systems using a laptop and
Speaker 1: a tablet that was built into the dashboard. So at
Speaker 1: the moment and we have we have mop based roots,
Speaker 1: we do, but at the moment it relies heavily on
Speaker 1: the landmarks in front. Got it getting some information from
Speaker 1: the GPS, but currently and it's getting most of its
Speaker 1: information from the laemark so similar it is like teslaut.
Speaker 1: So the car is basically watching the road through cameras
Speaker 1: and sensors and trying to stay in the lane the
Speaker 1: way a real driver would. So Max what happens if
Speaker 1: the lane markings are faded or simply aren't there. In general,
Speaker 1: interstate highways are pretty good, and Starski is making life
Speaker 1: a little easier for itself by saying that the driver,
Speaker 1: not the computer, should handle those edge cases. That's that's
Speaker 1: part of the same reason why Google has done like
Speaker 1: three million miles and is it ready to play anything.
Speaker 1: It is because like they're trying to look for all
Speaker 1: of those weird curves, all of like the weird times
Speaker 1: where U where whatever weird thing happens. Now Google wants
Speaker 1: it's a computer to basically handle everything. Yeah, Starsky's thought
Speaker 1: is the safety driver will be sitting in a call
Speaker 1: center somewhere monitoring maybe five or ten trucks on alarm
Speaker 1: will go off if something weird happens, and then he'll
Speaker 1: immediately seize the wheel and take control. Let's hope the
Speaker 1: wireless vous is reliable. How how does that work? Starsky
Speaker 1: doesn't want to say exactly how they're transmitting data, but
Speaker 1: basically they're controlling the truck wirelessly by remote control. Right now,
Speaker 1: the system looks a bit like you what you'd have
Speaker 1: if you were really into video games. There's a steering
Speaker 1: wheel and then three screens, and the driver just sits
Speaker 1: there and sort of drives like in a video game.
Speaker 1: But the idea is that most of the time the
Speaker 1: computer is driving itself. Now, let's go back to the beginning.
Speaker 1: You're in one of these trucks in Florida. You're on
Speaker 1: a bed in the back, and and the wind is
Speaker 1: blowing causing the truck to sway and the computer to overcorrect. Right,
Speaker 1: we were hauling a lot of weight on this particular day.
Speaker 1: It was It was a shipping container which is been
Speaker 1: out of stainless steel. It's heavier than the standard illuminum
Speaker 1: boxes that Starsky had been testing before, and that proved
Speaker 1: slightly problematic. Here's gonna be something new right here. This, Yeah,
Speaker 1: now this curve during the week we were taking a
Speaker 1: point container, we'll see a new experiment. Basically, we're getting
Speaker 1: pushed by the wind and the computer a bit like
Speaker 1: a human driver was struggling to figure out exactly just
Speaker 1: how hard how to respond, just how hard to turn
Speaker 1: that wheel? Max. You deserve hazard pay for this? Why
Speaker 1: why were they doing this test in Florida. So a
Speaker 1: bunch of states are trying to regulate driverless cars, but
Speaker 1: Florida is really really ridiculously relaxed about this industry. You
Speaker 1: don't need a special permit or any special insurance to
Speaker 1: to drive a driverless car in Florida, and you don't
Speaker 1: even need a human driver behind the wheel as long
Speaker 1: as somebody somewhere is in control of the car. Now
Speaker 1: here's the most interesting part. It gives us a peek
Speaker 1: at the future. Maybe robots won't take all our jobs,
Speaker 1: but it's likely that they replace many jobs, including what
Speaker 1: we think of as blue collar jobs that involve manage
Speaker 1: a computer. So I think like humans and technology are
Speaker 1: probably going to be better than either want to. Yeah,
Speaker 1: probably forever. That's Stephan again, the stars Key CEO. Stars
Speaker 1: Keep brings together these two unlikely groups rod En m
Speaker 1: Gene seven dollar lotts, Yeah, mixed with truck drivers who
Speaker 1: some of them live in trailers, many of them like
Speaker 1: they never went to college. Self driving engineers like Kevin Kyo,
Speaker 1: the engineer who works for Starsky, can make millions, even
Speaker 1: tens of millions at companies like Google. Truckers are basically
Speaker 1: treated as disposable by their employers. Were we were straddling
Speaker 1: people who thought that Bernie didn't go far enough and
Speaker 1: people who didn't think that Trump went far enough. Stephan
Speaker 1: argues that this is going to be really good for truckers,
Speaker 1: which I also heard from Jeff who was our driver
Speaker 1: for the day. Some people who are negative, Yeah, and
Speaker 1: then some are really interested in attack behind him. Yeah.
Speaker 1: And then you tell them about how you're gonna make
Speaker 1: it so they have forty hour weeks that seven the
Speaker 1: hours the weekend have, you know, instead of me and
Speaker 1: gone all the time. They can make same amount of money.
Speaker 1: But Jeff, a star Sky driver, isn't exactly an objective
Speaker 1: source here, is he? No, And it's a real threat
Speaker 1: that many drivers will get left behind. That's what one driver,
Speaker 1: Tom George told my colleague Josh. Even where they're not
Speaker 1: a driver shortage, there would certainly be technology trying to
Speaker 1: to edge into uh, supplanting a driver. I've been seeing
Speaker 1: uh trucking, uh just truck manufacturing developing into a you
Speaker 1: know what I always called trying to engineer the driver
Speaker 1: out of the truck. So Max, it's hard to know
Speaker 1: what the long term impact of artificial intelligence is going
Speaker 1: to mean for all of us, not just truckers, right right,
Speaker 1: and and there are there are a few different schools
Speaker 1: of thought, which I'll break down for you quickly. The
Speaker 1: first is basically that advances in robotics artificial intelligence are
Speaker 1: going to make us more productive, make us superhumans, and
Speaker 1: and those of us who lose our jobs going to
Speaker 1: get even better, more creative, more fulfilling jobs. The second
Speaker 1: idea school of thought is that technology is going to
Speaker 1: kill so many jobs that's going to create this permanent
Speaker 1: underclass where where you have a bunch of people who
Speaker 1: can't find anything. And the third school of thought says
Speaker 1: this is all hype, don't pay any attention to it. Yeah,
Speaker 1: I've also noticed the strain of optimism and Silicon Valley
Speaker 1: that says the job destruction will be real, but this
Speaker 1: this is a natural cycle of the economy, and that
Speaker 1: it will evolve a new work that we haven't yet
Speaker 1: imagined will kind of take care of the disruption, right.
Speaker 1: And I think it's important to remember that that for
Speaker 1: most of the country, this sort of Silicon value way
Speaker 1: of thinking is not how they see it. They see
Speaker 1: this as basically science fiction. Just the other day, Transportation
Speaker 1: Secretary Lane Chow told reporters that explaining self driving technology
Speaker 1: of the public would be one of the biggest hurdles
Speaker 1: in terms of getting people to adopt it. And even
Speaker 1: truckers like Tom George, who we just heard from, are
Speaker 1: convinced they'll be able to drive trucks better than a
Speaker 1: computer for some time to come. That's gonna be really,
Speaker 1: really hard for automation to take over because there's so
Speaker 1: much interaction that the driver has to be a part
Speaker 1: of that can't be automated by a computer. So who's
Speaker 1: going to notice that a strap is loose on your
Speaker 1: load while you're driving down the road. I don't know
Speaker 1: that the computer is going to be able to first
Speaker 1: bull notice it. And second of all, how are they
Speaker 1: going to just do it? What are they gonna do?
Speaker 1: And Tom's not wrong. It's true that there are thousands
Speaker 1: of rare cases, those edge cases, those emergencies where computers
Speaker 1: don't work very well and they may not work well
Speaker 1: for a long time. Yeah, but that doesn't mean it's
Speaker 1: going to take a long time to get to that
Speaker 1: hybridge stage. And Starsky is a version of this with
Speaker 1: remote control. But there are others. Auto and another driverless
Speaker 1: trucking startup called Embark talk about having drivers in the
Speaker 1: cabs but allowing them to sleep. Peloton, which is another
Speaker 1: Silicon Valley trucking startup, has a convoy style approach where
Speaker 1: you could imagine a big line of trucks with one
Speaker 1: driver just in the refront. But the bottom line is
Speaker 1: that all of these companies, all of them are trying
Speaker 1: to make trucking require fewer workers. So for now, what's
Speaker 1: next for Starsky? So what they're trying to do is
Speaker 1: have this big test on the highway where they're going
Speaker 1: to try to drive a whole uh delivery without having
Speaker 1: a human in the car. And I think probably they'll
Speaker 1: they'll try to raise some more money. Meanwhile, I guess
Speaker 1: things are looking less optimistic for drivers who don't have
Speaker 1: a Silicon Valley startup to get involved with. It's not
Speaker 1: just about drivers and people that operate trains and buses.
Speaker 1: It's also about people that do sort of ordinary jobs
Speaker 1: that you and I encounter during the day. That was
Speaker 1: Ed our union leader again. Um Ed's bigger idea was
Speaker 1: that at a certain point the government needs to take
Speaker 1: some responsibility for job losses and and making sure that
Speaker 1: this scary underclass scenario never plays out. And the other
Speaker 1: thing worth mentioning is that ordinary jobs quote unquote might
Speaker 1: also include a bunch of the jobs that we think
Speaker 1: of as being good lawyers, some kinds of doctors and
Speaker 1: Brad I hate to say it, but maybe journalists. What
Speaker 1: about podcast hosts? Or they say always forever? But Max,
Speaker 1: using your experience at the back of this truck, do
Speaker 1: you really believe this is going to happen in our lifetime?
Speaker 1: Do you really see those engineers feeling comfortable stepping away
Speaker 1: from the from the vehicle? And then, you know, can
Speaker 1: the same AI techniques apply to these other occupations where
Speaker 1: you know you do need human intuition, human input. At
Speaker 1: least for now, I don't think it's gonna be such
Speaker 1: a stark change. And I mean there's with trucking, there
Speaker 1: is this labor shortage, so there's sort of a built
Speaker 1: in cushion, and a lot of people said things like
Speaker 1: anyone who's a truck driver in their sort of career
Speaker 1: is not going to be seriously affected by this. I'm
Speaker 1: not sure how the true that is. And I think
Speaker 1: the other thing that we have to keep in mind
Speaker 1: is a lot of time, these automations don't happen in
Speaker 1: one big chunk. They happen in sort of small ways
Speaker 1: that that affect people's jobs, causing them to make less money.
Speaker 1: I mean, one type of automation that's pretty underrated is
Speaker 1: the advent of automatic transmission, which coincides with the declining
Speaker 1: wages of trucking. Now that also there are other causes
Speaker 1: of that, but but one thing it did is make
Speaker 1: driving a truck easier, which meant that trucking companies could
Speaker 1: use lower skilled workers. It kind of goes along with
Speaker 1: this notion that AI is this magical thing that doesn't exist,
Speaker 1: and yet when it does exist, we don't call it
Speaker 1: AI anymore. We just sort of assume assume that it's there.
Speaker 1: It's it's machinery. I like the Starsky approach, this melding
Speaker 1: of AI, telematics and and then humans because you know
Speaker 1: that this is the model that we've seen in medicine,
Speaker 1: in law, really in journalism technology not replacing humans but
Speaker 1: making them more efficient. Yeah, it strikes me as as
Speaker 1: as fundamentally like realistic, but also it has a certain
Speaker 1: humanity to it. And what I liked about this company,
Speaker 1: and I think what the companies that succeed in in
Speaker 1: this world are going to have at least some empathy
Speaker 1: for the workers who are being affected by by these changes.
Speaker 1: And those that are just thinking about this as pure technology,
Speaker 1: I think are going to run into trouble because because
Speaker 1: they're not being realistic about how the world actually works. Yeah,
Speaker 1: the star Ski approach does see him like it's something
Speaker 1: that is a little bit more practical sooner. But of
Speaker 1: course I didn't ask you the biggest question. The most
Speaker 1: important question is what's what the name? Is? This a
Speaker 1: reference to the popular seventies TV show It is so
Speaker 1: Stephen told me that he was actually looking for CB
Speaker 1: Radio Lingo, so like ten four good Buddy type type
Speaker 1: of things. And I guess Starsky and Hutch was slang
Speaker 1: CB slang in the seventies for a team of drivers,
Speaker 1: so he was thinking that it was going to be
Speaker 1: like you have a call center for drivers, So it's
Speaker 1: sort of like a star Ski and Hutch, or maybe
Speaker 1: a lot of star Skis and a lot of Hutches.
Speaker 1: Good buddy, and that's it for this week's episode of Decrypted.
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Speaker 1: episode was produced by Piagkari Aki Ito, Liz Smit, and
Speaker 1: Magnus Hendrickson. Thanks to Nico Grant and Isabel Gottlieb for
Speaker 1: all their work on this episode. My Business Week story
Speaker 1: was co written by jos Idolsen and edited by Jim
Speaker 1: Alee and Nick Summers. You can read it on bloomberg
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