Speaker 1: Welcome to Tech Stuff, a production from iHeartRadio. Hey there,
Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeartRadio. And how the tech
Speaker 1: are you? Here in the United States, we are celebrating
Speaker 1: Labor Day, a federal holiday here in the States. Also
Speaker 1: one that I find really interesting because it's all about
Speaker 1: celebrating the American labor movement. But if you pay attention,
Speaker 1: especially in the tech space, there are a lot of
Speaker 1: entities out there, a lot of companies that are eagerly
Speaker 1: opposing the labor movement and trying to do things like
Speaker 1: prevent workers from organizing and forming unions. Yeah, a complicated
Speaker 1: thing that we have a holiday to celebrate it, and
Speaker 1: yet we have plenty of examples of companies and organizations
Speaker 1: out there dedicated to venting more labor organization from happening.
Speaker 1: But let's put aside all of that. I thought, since
Speaker 1: we're on holiday today, I wanted to make sure that
Speaker 1: you had an episode anyway. So we're going to actually
Speaker 1: listen to an episode that came out a few years ago,
Speaker 1: back in twenty twenty July thirteenth, twenty twenty. In fact,
Speaker 1: it is titled The Robots Are Coming for Your Job,
Speaker 1: and it's all about robots and automated systems and the
Speaker 1: anxiety that exists around this idea of automation eliminating jobs,
Speaker 1: which I think has only become even more of a
Speaker 1: talking point in the wake of things like generative AI,
Speaker 1: for example. So let's listen to this episode from twenty twenty,
Speaker 1: the Robots Are Coming for Your Job, and I'll chat
Speaker 1: with you again at the end. I read a lot
Speaker 1: of tech news and sometimes that ends up inspiring me
Speaker 1: to do an episode of tech stuff. That happened to
Speaker 1: me recently when I read this headline off of the
Speaker 1: website tech Spot. Sony factory assembles PS four in thirty seconds,
Speaker 1: only four humans involved in the process. A PS four,
Speaker 1: in case you're not aware, is a PlayStation four video
Speaker 1: game consoles. So this factory can build a video game
Speaker 1: console from parts in half a minute and only four
Speaker 1: human beings touch the ding dang thing in the process.
Speaker 1: Those four humans, by the way, are involved in the
Speaker 1: beginning and the end of the process. Two of them
Speaker 1: load motherboards onto the assembly line, and a motherboard is
Speaker 1: the primary circuit board for a computer system, and the
Speaker 1: other two human beings are at the end of the
Speaker 1: assembly line, and their job is to package the completed consoles.
Speaker 1: All the actual assembly work is done by robots. Now
Speaker 1: you may be experiencing a couple of different responses to
Speaker 1: this information. I know I did. One of those was
Speaker 1: a wow, that's seriously impressive. The PS four, like many
Speaker 1: computer systems, has a lot of components, many of which
Speaker 1: attached to one another by wire or cable. So these
Speaker 1: robots have to be able to take these flexible components
Speaker 1: and to join them in their proper anchor points with
Speaker 1: the appropriate amount of pressure and precision to make a
Speaker 1: good connection. Now, if any of you out there have
Speaker 1: ever built your own PC, you know that plugging cables
Speaker 1: in can get a little tricky depending on the layout
Speaker 1: of the motherboard and the various components. And if you're
Speaker 1: someone like me, you're likely putting stuff together only to
Speaker 1: realize that maybe you should have done some of that
Speaker 1: before you mounted them in a computer case, because now
Speaker 1: you just don't have the space to work in properly.
Speaker 1: So it's pretty darn impressive that robots can do this
Speaker 1: consistently and correctly at that level of speed. Another response
Speaker 1: I had was kind of scary. I mean, typically you
Speaker 1: would have dozens of people employed on the assembly line
Speaker 1: to do this sort of work, but in this factory
Speaker 1: it's been stripped down to thirty two robots and four
Speaker 1: human beings. The article in textpot points out that twenty
Speaker 1: six of those thirty two robots are just attaching flexible
Speaker 1: components together inside the console. Now, I have no idea
Speaker 1: how much these robots cost, but I wager that they
Speaker 1: are expensive enough to equal the salary of a standard
Speaker 1: human employee on the assembly line. However, you don't pay robots.
Speaker 1: You do have to spend money to maintain and repair them,
Speaker 1: but assuming whatever you're making is going to be around
Speaker 1: for a little while, they'll pay for themselves because eventually
Speaker 1: you'll get to a point where the salaries you'd be
Speaker 1: paying for humans would be more than the purchase and
Speaker 1: maintenance cost of the robots. And the increase in efficiency
Speaker 1: means you can produce a whole lot more stuff in
Speaker 1: a given amount of time than you would with a
Speaker 1: human centric assembly line, so you'll have more product to
Speaker 1: sell in a shorter amount of time. When you start
Speaker 1: crunching numbers, you discover your robotic assembly line can make
Speaker 1: more stuff at a lower cost over a given period
Speaker 1: of time, like you know, over a couple of years,
Speaker 1: than what you would accomplish with human beings on that
Speaker 1: assembly line. So you don't have to worry about the
Speaker 1: robots taking a vacation. They don't take sick time, they
Speaker 1: don't even take the night off. They can work around
Speaker 1: the clock. They don't need health insurance, though I would
Speaker 1: guess that most companies ensure the heck out of these
Speaker 1: things just in case one breaks down. But from a
Speaker 1: financial point of view, they make sense if you're building
Speaker 1: stuff at a large enough scale, stuff like video game
Speaker 1: consoles for the PlayStation four. It's a no brainer because
Speaker 1: that console has sold around one hundred and ten million
Speaker 1: units so far. That's a number large enough that I
Speaker 1: can't even imagine what it would look like if you
Speaker 1: had all those consoles together in one place. So if
Speaker 1: there's enough demand for you to sell one hundred and
Speaker 1: ten million whatever it is you want to sell, you
Speaker 1: need to have a way to make those as efficiently
Speaker 1: as possible, and that will help maximize your profits. And
Speaker 1: the more efficient the process, the more competitively you can
Speaker 1: price your product and still make a profit. But the
Speaker 1: idea of robots performing jobs far more effectively, consistently, and
Speaker 1: efficiently than humans raises a lot of questions. And these
Speaker 1: are not new questions either, but they are questions like
Speaker 1: if more factories rely on robots for production, particularly if
Speaker 1: those robots can be programmed to produce new products once
Speaker 1: older ones go obsolete, what happens to the job market,
Speaker 1: What happens to the millions of people who work in
Speaker 1: manufacturing on assembly lines? They go? What will this do
Speaker 1: to economies around the world. Lots of people have tried
Speaker 1: to answer these questions, sometimes giving drastically different answers. And
Speaker 1: we're going to take a look at the history and
Speaker 1: evolution of industrial robots in this episode and explore the
Speaker 1: ramifications of automated manufacturing. And this is where I dive
Speaker 1: into history. I've talked about the history of robots before,
Speaker 1: so I'll try to restrict my focus to industrial robots.
Speaker 1: And before I get into that, let's just address the
Speaker 1: fact that the use of machinery to increase efficiency has
Speaker 1: been a controversial subject since long before there ever was
Speaker 1: such a thing as a robot. Generally speaking, machines are
Speaker 1: meant to make work easier or in some cases make
Speaker 1: the work possible just to begin with, they are labor
Speaker 1: saving devices, requiring humans to put forth less effort to
Speaker 1: get the same or better results. This applies to the
Speaker 1: simplest of machines, I mean stuff like levers or pulleys
Speaker 1: or an inclined plane, and it applies to very complex
Speaker 1: machines as well. Before the Industrial Revolution, most stuff like
Speaker 1: textiles was made by crafts people out of their own homes.
Speaker 1: This was literally the cottage industry. Trades people would travel
Speaker 1: and become the lifeline for the cottage industry, supplying raw materials,
Speaker 1: buying finished products, and selling those products off at a
Speaker 1: profit elsewhere. Many tradespeople built a good deal of wealth
Speaker 1: working this way, and they had the means to look
Speaker 1: at alternatives to this decentralized cottage industry approach. An idea
Speaker 1: began to form. If you brought together crafts people to
Speaker 1: a centralized location, and if you simplified the process of production,
Speaker 1: you could make way more stuff, which in turn means
Speaker 1: you could sell way more stuff, which in turn means
Speaker 1: you can make way more money, and money makes the
Speaker 1: world go round. This thought process helped fuel a similar
Speaker 1: line of thinking. If you could design machines that could
Speaker 1: do a lot of work that typically fell to skilled
Speaker 1: crafts people. You wouldn't need the crafts people at all.
Speaker 1: You could train anyone, even if that person had no
Speaker 1: experience with the process, just to work the machine. And
Speaker 1: while it might take years of dedication to go through
Speaker 1: the process of being an apprentice to learn a trade
Speaker 1: well enough so that you can actually make a living
Speaker 1: at it, with a machine, you can skip right over that.
Speaker 1: As long as the machine's end product was good enough.
Speaker 1: It didn't have to be better than the stuff crafts
Speaker 1: people were making. It just had to be good enough
Speaker 1: and cheap enough and fast enough to produce. Then you
Speaker 1: could sell the finished product at a lower cost than
Speaker 1: what crafts people would charge because not as much time
Speaker 1: and effort went into making the thing. Now, I guess
Speaker 1: it's clunky to talk about this while using an example,
Speaker 1: so let's go with a poster child for the Industrial Revolution, weaving.
Speaker 1: The weaving trade is an ancient one, and it requires
Speaker 1: a good deal of skill to do it well by hand.
Speaker 1: In the late seventeen hundreds, a man named Edmund Cartwright
Speaker 1: patented a loom powered by a water wheel. The loom's
Speaker 1: operation was such that a person who had no training
Speaker 1: in weaving could operate the machine and produce finished textiles.
Speaker 1: Cartwright's design would be built upon by other inventors who
Speaker 1: had turned to steam power and other means to operate
Speaker 1: the power loom. Many cottage industry weavers found themselves out
Speaker 1: of work. They could potentially opt to work in the
Speaker 1: textile factories, as those were popping up all over the place,
Speaker 1: particularly in England, but the wages were low. As you
Speaker 1: can imagine, this didn't sit well with the weavers. There
Speaker 1: were protests, including some that incorporated violence and destruction. Ultimately,
Speaker 1: the factory process won out, and along with it some
Speaker 1: really awful working conditions followed, including stuff like child labor
Speaker 1: and ridiculously low wages and dangerous working conditions. This led
Speaker 1: to more protests, including the type that would give us
Speaker 1: the word sabotage. And let's get a quick side note
Speaker 1: on that one, as it is the source of a
Speaker 1: little mythology or misinformation. See The apocryphal story goes that
Speaker 1: the word sabotage comes from the word sabo, which describes
Speaker 1: the wooden shoes worn by laborers, mainly Dutch laborers, but
Speaker 1: also laborers in France. And according to the story, these
Speaker 1: laborers wore those shoes and used them to great effect.
Speaker 1: In an effort to protest the conditions and factories, they
Speaker 1: would toss their wooden shoes into the machinery to break
Speaker 1: the various gears and literally grind production to a halt,
Speaker 1: as it were. But this story, while compelling, isn't really
Speaker 1: the truth. Sabotage does stem from the word sabo, but
Speaker 1: in French there is a verb sabote. This verb means
Speaker 1: to make a loud noise with wooden shoes. Now isn't
Speaker 1: it great that there's a verb for that? And it
Speaker 1: makes sense wooden shoes would make a great deal of
Speaker 1: racket as people would walk around. Heck, if a toddler
Speaker 1: wore wooden shoes, I think it would probably sound as
Speaker 1: though the world were shaking apart. I don't know how
Speaker 1: toddlers manage to sound like they weigh eight hundred pounds,
Speaker 1: but they do it. And if you have a toddler,
Speaker 1: you know what I'm talking about. And in the culture
Speaker 1: of France, the idea of a clumsy slow worker was
Speaker 1: often linked to someone who wore wooden shoes because they're
Speaker 1: awkward to wear anyway, The reason sabote led to sabotage
Speaker 1: is because factory workers who were protesting their work conditions
Speaker 1: and wages would purposefully work more slowly and less efficiently
Speaker 1: in order to affect the overall output of a factory.
Speaker 1: It was related to a similar strategy that British laborers employed,
Speaker 1: and their version was called kakani. It was a saying
Speaker 1: from Scotland which essentially means don't do so much man now.
Speaker 1: I would argue this also feeds into a strategy that
Speaker 1: we see to this very day in certain government offices,
Speaker 1: where the idea is there's no need to do too
Speaker 1: much too quickly, as it doesn't result in increased compensation
Speaker 1: and it also sets a really high bar of expectation,
Speaker 1: so why not just take it easy? You know, I
Speaker 1: don't have a coffee break now. In the early twentieth century,
Speaker 1: people began to use the word sabotage to really refer
Speaker 1: to a purpose full approach to undermining the output of factories,
Speaker 1: and it had nothing to do with tossing wooden shoes
Speaker 1: into machinery, though it did also pertain to instances in
Speaker 1: which workers purposefully damaged equipment and tried to slow down
Speaker 1: the production that way. While this isn't directly tied to
Speaker 1: the idea that machines themselves are displacing workers, it is
Speaker 1: related to the effect of moving toward a manufacturing based
Speaker 1: economy and how that allows for the exploitation of workers.
Speaker 1: The machines themselves aren't really at fault, but they facilitate
Speaker 1: the system of operations that leads to exploitation. Now that's
Speaker 1: something that'll be a theme in this episode, and we
Speaker 1: can't ignore the social aspect of what's going on here,
Speaker 1: or else we miss the whole point. But let's skip ahead.
Speaker 1: I've spoken about this before, but we get the word
Speaker 1: robot from a check author named Kyl Kopek. He wrote
Speaker 1: a pl called Rossum's Universal Robots or R you Are
Speaker 1: in nineteen twenty. Kopek took an older word rabota, which
Speaker 1: means forced labor in Europe. This concept was tied to
Speaker 1: that of the old system of serfdom, in which people
Speaker 1: would do work on behalf of a landowner. In return,
Speaker 1: those people would be allowed to live on part of
Speaker 1: that landowner's land. In ru are factory owners devise a
Speaker 1: way to build laborers from raw materials. Now in the play,
Speaker 1: they are indistinguishable from humans other than they have no
Speaker 1: inner desires. But in the course of the play, these
Speaker 1: laborers eventually take over all the jobs that humans previously held,
Speaker 1: and humans themselves become a threatened species as these laborers
Speaker 1: begin to understand the power that they hold by occupying
Speaker 1: all the positions of employment, including as soldiers in the military.
Speaker 1: And so with the introduction of the concept of robot,
Speaker 1: we actually get the very first robotic uprising all the
Speaker 1: way back in nineteen twenty. See I told you it
Speaker 1: was an old idea. It's important to remember that in
Speaker 1: the play, the robots are nearly identical to humans. They
Speaker 1: aren't mechanical the way our robots of today are, but
Speaker 1: the idea of creating machines that can do work without
Speaker 1: a will of their own is a part of robotics
Speaker 1: in general, and industrial robotics in particular. When we come back,
Speaker 1: we'll talk about the earliest industrial robots and what they did,
Speaker 1: But first let's take a quick break. It's interesting to
Speaker 1: me that the tech world adopted the term robot when
Speaker 1: we think about the origins of that word. In Cope's work,
Speaker 1: robots were sentient slaves. They could perform the work humans
Speaker 1: would otherwise do, but they lack the emotions that humans have,
Speaker 1: and the whole idea is that these devices could do
Speaker 1: our work for us without question or protest. They would,
Speaker 1: in theory, endure conditions that people wouldn't or couldn't, But
Speaker 1: in the play they ultimately lead to the destruction of
Speaker 1: the human race and potentially they become the new dominant
Speaker 1: species on the planet. Now. I say potentially because part
Speaker 1: of the play's plot involves the destruction of the formula
Speaker 1: that scientists use to produce the robots in the first place.
Speaker 1: That is an important plot point. The robots are not
Speaker 1: sure how to make more robots, so they might just
Speaker 1: die out. Now, it seems to me as though that's
Speaker 1: a pretty emotionally charged term to adopt for an entire
Speaker 1: discipline of technology, right, robots, Especially if you are actually
Speaker 1: aware of that play, and by the way, I recommend
Speaker 1: people read it. It's a good play. But then a
Speaker 1: lot of people are not aware of the origins of
Speaker 1: the word, or at least not beyond knowing that it
Speaker 1: came from a play in the nineteen twenty So I
Speaker 1: guess for them, it's just, you know, a word. A
Speaker 1: robot by any other name would smell as sweet as
Speaker 1: it were. And we've definitely seen the themes of rure
Speaker 1: serving as an undercurrent for stuff that's happening in robotics
Speaker 1: in general. But let's move ahead. In nineteen fifty four,
Speaker 1: an engineer named George Duvault designed an industrial robot. He
Speaker 1: was nine years old when Kopek coined the term robot.
Speaker 1: He called his design the Programmed Article Transferred Device, for
Speaker 1: which he received a US patent in nineteen sixty one.
Speaker 1: This machine was a robotic arm, and it was capable
Speaker 1: of picking up something and then transferring it a short
Speaker 1: distance away, just within reach of the arm. The arm
Speaker 1: itself couldn't move, it was anchored in place. It could
Speaker 1: also follow. In fact, this is the important part, It
Speaker 1: would follow a pre program series of instructions to do this.
Speaker 1: Deval's argument for his device was that up to this point,
Speaker 1: mechanical handling of objects fell into two broad categories. Either
Speaker 1: stuff got moved by humans, typically operating a powerful machine
Speaker 1: like a crane or a forklift, or stuff got moved
Speaker 1: by a device that operated under cam control. Now, manual
Speaker 1: control is self explanatory, so let's talk about cams. A
Speaker 1: cam is a rotating component in machinery. Typically a cam
Speaker 1: has some variation in its surface. So let's start with
Speaker 1: a wheel. Just imagine a wheel that is spinning on
Speaker 1: an axle. Well, you wouldn't typically have a perfectly smooth
Speaker 1: wheel as a cam. Part of that surface might be flat,
Speaker 1: or it might have dips in it, And when the
Speaker 1: cam rotates, these variations apply force to some other mechanical
Speaker 1: component that is held against the cam, and it causes
Speaker 1: that mechanical component to move in specific ways. A cam
Speaker 1: operating system can work on its own, but it will
Speaker 1: always repeat the exact same motions As long as everything
Speaker 1: is working, it'll just repeat those steps. Once the cams
Speaker 1: complete a full systematic rotation, you can't really adapt it
Speaker 1: to do anything else. The movements depend entirely on the
Speaker 1: cams themselves, so if you wanted it to do something else,
Speaker 1: you would at first have to swap out the cams,
Speaker 1: and even then you would be under whatever the limitations
Speaker 1: of the device was itself, like it wouldn't have full
Speaker 1: range of motion. Moreover, this level of specialization also means
Speaker 1: that it's typically really expensive to rely upon cam based systems,
Speaker 1: so it was really only useful if the application had
Speaker 1: to do with mass manufacturing or else you're looking at
Speaker 1: an economic loss. The cost of the system was just
Speaker 1: too much. So Devaal was proposing a machine that could
Speaker 1: be programmed to do operations. And this would let a
Speaker 1: programmer create different processes using the same machine. Or you
Speaker 1: could get a whole bunch of the same basic machine
Speaker 1: and program each one to do a particular job. Meanwhile,
Speaker 1: you'd free people up to work on other stuff in
Speaker 1: the manufacturing process, and you could take the most dangerous
Speaker 1: stuff and give it to the robots. Now, the story
Speaker 1: goes that Daval was at a party in nineteen fifty
Speaker 1: six and he got into a conversation with a man
Speaker 1: named Joseph Engelberger. Joseph was a scientist and an entrepreneur,
Speaker 1: and when the subject turned to Deval's programmed article transferred device,
Speaker 1: as well as the work of a science fiction author
Speaker 1: known as Isaac Asimov, you know, the father of robotics.
Speaker 1: He famously incorporated a concept of the laws of robotics
Speaker 1: in his works. We won't really go into that in
Speaker 1: this episode, but the laws of robotics still play a
Speaker 1: big part in the discipline of robotics in general. But
Speaker 1: it's kind of outside the focus of this episode. Ingelberger
Speaker 1: used his connections to get funding for devauld to create
Speaker 1: a more advanced version of the programmed article transfer machine,
Speaker 1: and it would be a robotic arm capable of making repeated,
Speaker 1: precise movements while holding very heavy objects. They called it
Speaker 1: the Unimate Unimate, and the first prototype, Unimate zero zero one,
Speaker 1: would go to General Motors to work on a die
Speaker 1: casting assembly line. Now, according to the company robot Works,
Speaker 1: that's a WRX. This robot cost around sixty five thousand
Speaker 1: dollars to produce, and Ingelberger sold it off at a
Speaker 1: tremendous loss. General Motors only paid eighteen thousand dollars for
Speaker 1: a sixty five thousand dollars machine. But Ingelberger really wanted
Speaker 1: to establish that robotics were a way to perform repetitive,
Speaker 1: dangerous functions at a lower risk to humans. Welding die
Speaker 1: cast components on autobodies was a great first application of
Speaker 1: industrial robots for a few reasons. Die Casting is a
Speaker 1: process involving molten metal. You take that molten metal and
Speaker 1: you force it into steel molds, and these are water
Speaker 1: called dyes. The molten metal cools in the exact shape
Speaker 1: of the mold. So this is a way to make
Speaker 1: or cast a bunch of identical parts out of metal
Speaker 1: and get consistent quality out of it rather than forging
Speaker 1: each piece and then fitting them together. A dye can
Speaker 1: have complex shapes in it, such as external threads, which
Speaker 1: means you don't have to make a pipe, for example,
Speaker 1: and then do a secondary process on that pipe to
Speaker 1: get the result you want, So you wouldn't have to
Speaker 1: carve those threads into a otherwise smooth pipe. You could
Speaker 1: just cast the pipe with the threads incorporated on it already.
Speaker 1: But welding die cast parts onto autobodies is hard work.
Speaker 1: The components are really heavy, so you're at risk of
Speaker 1: immediate injury if something goes wrong, like let's say you
Speaker 1: drop a weighty component on your foot, or you might
Speaker 1: develop a repetitive stress injury after going through the same
Speaker 1: welding motions over and over again. In addition, the fumes
Speaker 1: given off while welding were sometimes toxic still are, so
Speaker 1: it's not great to have people exposed to them for
Speaker 1: very long. So a robot was a great substitute for
Speaker 1: a person. The robot could handle much greater weight than
Speaker 1: people could The robot didn't breathe, so there was no
Speaker 1: respiratory issue there, and it didn't get tired. I mean,
Speaker 1: it would wear down over time, but you could repair
Speaker 1: it in fairly short order. The Unimate worked with computer
Speaker 1: controlled hydraulic systems. A hydraulic system uses a liquid that's
Speaker 1: under pressure in order to do work like pushing against
Speaker 1: a piston to power an actuator of some sort like
Speaker 1: lift a platform. The UNIMATE zero zero one weighed twenty
Speaker 1: seven hundred pounds or about one two hundred and twenty
Speaker 1: five kilograms, and it could work twenty four hours a day,
Speaker 1: placing components with a precision of within one fifty thousandth
Speaker 1: of an inch. Now I'm not going to do the
Speaker 1: conversion on that, because I think it's sufficient to say
Speaker 1: that it was just really precise. According to a charmingly
Speaker 1: dated newsreel from Britain, complete with swinging sixties music that
Speaker 1: sounded like it came straight off an Austin Powers movie,
Speaker 1: the robot could operate for five hundred hours without the
Speaker 1: need for a human to check in on it. Engelberger,
Speaker 1: a savvy businessman and promoter, would arrange for Unimate to
Speaker 1: show what it could do at trade shows and on
Speaker 1: TV appearances, including one on The Tonight Show with Johnny Carson.
Speaker 1: If you don't know who that is, ask your parents,
Speaker 1: and if they don't know, ask your grandparents. Nineteen sixty nine,
Speaker 1: General Motors had jumped on board the robot train, as
Speaker 1: it were. They rebuilt a manufacturing plant in Lordstown, Ohio,
Speaker 1: and they installed unimate robots to perform spot welding on
Speaker 1: car bodies, and the results spoke for themselves. The plant
Speaker 1: was capable of producing one hundred and ten cars per hour,
Speaker 1: which was more than double the speed that the plant
Speaker 1: could manage before the installation of the robots. The business
Speaker 1: case for the robots seemed clear. After a hefty upfront cost,
Speaker 1: you could produce way more stuff per day, and as
Speaker 1: long as the demand for that stuff is high enough,
Speaker 1: it could mean greater revenue. You could also bring the
Speaker 1: cost of production for an individual unit down. Then you
Speaker 1: could pass savings on to customers and get really competitive
Speaker 1: with your pricing, or you could just keep everything priced
Speaker 1: the same and try to increase your profit margin. The
Speaker 1: key to all this was that you had to be
Speaker 1: sure the thing you were producing would bring in enough
Speaker 1: money to offset the cost of automation, so it would
Speaker 1: not make sense to spend millions of dollars building out
Speaker 1: a factory staffed with robots. If you were making something
Speaker 1: that had a very small market to begin with, yes,
Speaker 1: you'd be able to produce way more Watching My colle
Speaker 1: its than you could before. But if the demand for
Speaker 1: Watchma collets is really modest, that doesn't do you any good.
Speaker 1: In fact, you might end up flooding the market and
Speaker 1: devaluing your product. So while robots were taking on jobs
Speaker 1: that were previously held by humans, there was no real
Speaker 1: danger of a massive upheaval where everything would be automated.
Speaker 1: The limitations in the technology were just too great and
Speaker 1: the cost was too high for most companies to go
Speaker 1: that route. And this also became the starting point for
Speaker 1: something that would become really important that the main goal
Speaker 1: of developing industrial robots wasn't to displace humans. It was
Speaker 1: meant to offload duties that were dull, dirty, or days.
Speaker 1: You'll often hear those terms being used with robotics if
Speaker 1: it is a job that carries with it a significant
Speaker 1: risk to the person performing it, or a job so
Speaker 1: demanding that you can only expect a person to stick
Speaker 1: with it for a short while before they need to
Speaker 1: do something else. Then building a robot to do that job,
Speaker 1: or at least that list of tasks makes sense. The
Speaker 1: robot is just a thing. It can endure conditions that
Speaker 1: humans can't, and it doesn't get sick, and it doesn't
Speaker 1: get hurt. If something breaks down, you can typically repair
Speaker 1: it pretty quickly. We humans don't have that luxury. Now,
Speaker 1: I'm not going to go and run down a full
Speaker 1: history of all industrial robots because that would mostly involve
Speaker 1: me talking about model numbers with slight differences like the
Speaker 1: number of axes of movement or points of articulation for
Speaker 1: one robot versus another, and that's not really interesting. But
Speaker 1: I do want to hit a couple of highlights. One
Speaker 1: is that in nineteen seventy five, the ASEAB robot would
Speaker 1: be the first fully electrically driven robot. It also used
Speaker 1: Intel's first chip set as processors. Now, this was not
Speaker 1: a super strong robot because those electrically driven limbs just
Speaker 1: can't pack the same punch as a hydraulic system, which
Speaker 1: typically moves much more slowly but can handle much heavier payloads.
Speaker 1: So this particular robot could only lift weights up to
Speaker 1: around thirteen pounds or six kilograms, but the move toward
Speaker 1: processors and electrically driven components marked a big technological step,
Speaker 1: even if the arm's physical capabilities were much less impressive
Speaker 1: than a hydraulic system. By the end of the nineteen seventies,
Speaker 1: Japan was getting into the robotics game with arc welding
Speaker 1: robots for assembly lines, and then it was off to
Speaker 1: the robotic races, with the eighties seeing a surge in
Speaker 1: advances with industrial robots. Soon, massive manufacturing facilities were installing
Speaker 1: robots to take over elements of the assembly line process,
Speaker 1: particularly in that dirty, dull, and dangerous category. The robots
Speaker 1: became more sophisticated, which also added to their value. When
Speaker 1: we come back, I'll talk more about why that's important,
Speaker 1: but first let's take another quick break. By the mid
Speaker 1: nineteen nineties, robotics companies were making machines that could coordinate
Speaker 1: and synchronize the movements of more than one robot at
Speaker 1: the same time, allowing for more complex manufacturing processes. By
Speaker 1: the early two thousands, there were systems that could synchronize
Speaker 1: the actions of up to four robots at a time,
Speaker 1: further adding to the overall system flexibility. Now, I mentioned
Speaker 1: earlier that a programmable robot is more versatile than something
Speaker 1: like a cam operated system. Well, more sophisticated robots, with
Speaker 1: more axes of motion and more points of articulation have
Speaker 1: the potential to do lots of different types of jobs,
Speaker 1: and this is of critical importance. If the robot is
Speaker 1: too limited, if you can only do a small range
Speaker 1: of motions, you can't necessarily repurpose it for new processes.
Speaker 1: And as markets change, you may find yourself needing to
Speaker 1: be flexible when it comes to the stuff you're manufacturing.
Speaker 1: So let's use an extreme hypothetical example that would probably
Speaker 1: never happen. So let's say that you run an auto
Speaker 1: manufacturing facility, but then there's a massive market change and
Speaker 1: it drastically affects the demand for your cars. There's just
Speaker 1: not enough demand to support the production. So rather than
Speaker 1: just you know, closing up shop and calling it a day,
Speaker 1: your business decides to do an amazing pivot and you
Speaker 1: begin to convert your manufacturing facility over to I don't know,
Speaker 1: home appliances. Now, again, this is an extreme hypothetical example,
Speaker 1: but let's just go with it. Okay, So here we go.
Speaker 1: If the robots on your assembly line are powerful, but
Speaker 1: limited in movement and function. You may find it impossible
Speaker 1: to adapt them to your new line of business, which
Speaker 1: would mean you need to either invest in new robots
Speaker 1: or you'd have to hire human workers to put together
Speaker 1: your appliances. And it would also mean that your old
Speaker 1: robots would be a sunk cost. You would need to
Speaker 1: either sell them off or put them in storage or something.
Speaker 1: If the robots are really sophisticated, however, you might be
Speaker 1: able to program them to do some of the operations
Speaker 1: on the new assembly line, and that would keep them useful,
Speaker 1: it would lower the cost of production. Or, for a
Speaker 1: less extreme example, you introduce a new model of whatever
Speaker 1: thing it is that you're producing. Anything new will require
Speaker 1: adjustments in the assembly line process, and if the changes
Speaker 1: are big enough, the robots may not be able to
Speaker 1: make as big a contribution in the process. That's something
Speaker 1: that could happen with the example of the PlayStation we
Speaker 1: were talking about. Yeah, those robots can put together a
Speaker 1: PS four and thirty seconds. There's no guarantee they'll be
Speaker 1: able to do the same thing with a PS five,
Speaker 1: at least not without a major overhaul of their assembly line. System.
Speaker 1: While the manufacturing facility can churn out a finished PS
Speaker 1: four and thirty seconds, we might not see them work
Speaker 1: at all with PS five, at least not right away.
Speaker 1: It would all have to be optimized. So for decades,
Speaker 1: industrial robots were kept as separate from human workers as
Speaker 1: was possible. You wanted to keep them well away from
Speaker 1: all the people, or keep the people well away from
Speaker 1: all the robots. Often the robots would operate within cages
Speaker 1: specifically to limit the possibility of a human coming within range.
Speaker 1: After all, these robots are large, they're heavy, powerful, and
Speaker 1: many of them are incapable of sensing stuff in their
Speaker 1: environment and whether or not a human is within their
Speaker 1: range of motion. Instead, they're just going through that pre
Speaker 1: programmed series of motions and they're not going to stop
Speaker 1: unless someone turns it off. A robot is performing that
Speaker 1: same series of steps over and over, and that can
Speaker 1: mean that if a human in that area gets near
Speaker 1: the robot, they could end up getting injured or worse.
Speaker 1: And in fact, this has happened several times over the
Speaker 1: course of the last few decades, and at least in
Speaker 1: some cases it seems as though the robot might have
Speaker 1: been at fault meaning it's not always a case of
Speaker 1: human carelessness. For example, an engineer in twenty fifteen died
Speaker 1: when a robot armed from one section of the factory
Speaker 1: floor moved beyond its operating area and into the neighboring
Speaker 1: section that the engineer was working in. This is something
Speaker 1: that should not have happened. The robot arms should not
Speaker 1: have moved that far into the neighboring section. The robot
Speaker 1: arm hit the engineer on the head, and she later
Speaker 1: died from her injuries. In the United States, the government
Speaker 1: has listed thirty three workplace deaths due to accidents with
Speaker 1: industrial robots between the years nineteen eighty four and twenty fourteen.
Speaker 1: The investigations also found that the majority of those tragedies
Speaker 1: was typically the fault of human error. There was a
Speaker 1: person who was wandering into the operation zone of a robot.
Speaker 1: That twenty fifteen incident was an outlier. Not that any
Speaker 1: of this makes the thought of working around industrial robots
Speaker 1: less scary or those other accidents any less tragic. They're
Speaker 1: all terribly tragic. Moreover, we're seeing more robots that are
Speaker 1: capable of roaming a work space. They are no longer
Speaker 1: anchored to a specific spot on the floor. In some cases,
Speaker 1: they also, unlike the first industrial robots, typically have external sense.
Speaker 1: These not only help the robots navigate their environments, but
Speaker 1: also hopefully avoid accidents with human workers. Let's take Amazon's
Speaker 1: warehouse robots for example. These robots look like really big
Speaker 1: robotic vacuum cleaners. They are designed to roll under shelves
Speaker 1: and the shelves are just slightly larger than the dimensions
Speaker 1: of the robot. And when an order comes in, a
Speaker 1: robot from the warehouse rolls over to a shelf that
Speaker 1: holds the respective item on it according to the inventory system,
Speaker 1: and the robot goes under the shelf then lifts the
Speaker 1: shelf by raising a platter like platform on the top
Speaker 1: of the robot. Think of it as like a little
Speaker 1: fork left, except it's more like a I don't know,
Speaker 1: like a tray that a waiter would use to carry
Speaker 1: drinks to a table. But it carries the whole shelf
Speaker 1: up and over to the edge of a cage, where
Speaker 1: a human operator will take the respective item off the
Speaker 1: shelf and scan it and put it into a bin.
Speaker 1: And then those bins go to other humans who further
Speaker 1: scan those items and then put them into other bins
Speaker 1: that ultimately go to the packing department. And if you
Speaker 1: watch videos of these robots, it looks like they're doing
Speaker 1: a complicated ballet as they maneuver through this warehouse, avoiding
Speaker 1: other robots and shelves. As they bring those shelves to humans.
Speaker 1: Markings on the warehouse floor tell the robots where they
Speaker 1: are with respect to everything else in the warehouse, and
Speaker 1: the robots even will position shelves that have items that
Speaker 1: are being ordered a lot toward the edges of this
Speaker 1: space so that they're easier to get to and move
Speaker 1: them over to the human beings. So it's kind of
Speaker 1: an interesting dynamic system. It's not like they pick up
Speaker 1: the shelf and then bring the shelf immediately right back
Speaker 1: to where it started. The shelf can end up in
Speaker 1: a different location entirely. In addition, cameras give the robots
Speaker 1: the ability to sense any obstacles that might block their path,
Speaker 1: allowing the robot to come to a stop and a
Speaker 1: wait further instructions and report that it has found something
Speaker 1: unusual on the warehouse floor. Even so, typically humans are
Speaker 1: not allowed to roam the area where the robots pick
Speaker 1: up shelves if something has fallen on the warehouse floor.
Speaker 1: A designated troubleshooter gets an alert, and that person must
Speaker 1: use an interface to draw the path that they are
Speaker 1: going to take from the entrance of the cage all
Speaker 1: the way to the point of trouble. Like let's say
Speaker 1: that a product has fallen out of a shelf and
Speaker 1: has hit the floor, and a robot has reported it.
Speaker 1: You would use a tablet. If you're the troubleshooter, you'd
Speaker 1: use a tablet and you would draw, almost like a maze,
Speaker 1: the path you would take to get to that particular item,
Speaker 1: and you would follow that path out and back. In addition,
Speaker 1: you'd wear a radio transmitter that would send a signal
Speaker 1: out that the robots could all detect, and that would
Speaker 1: alert the robots to the presence of you, the troubleshooter.
Speaker 1: That helps prevent a situation in which the robots are
Speaker 1: going to collide with you, right, you want to avoid that. Now,
Speaker 1: there's a lot of work that goes into designing robots
Speaker 1: that can interoperate in a space that's occupied by humans,
Speaker 1: and it's a very challenging line of technology because it
Speaker 1: takes more than just thinking about how the machines work
Speaker 1: you also have to think about how people work, and moreover,
Speaker 1: you have to think about how people change the way
Speaker 1: they work when they're in the company of a robot.
Speaker 1: It's kind of similar to the concept in quantum theory, right,
Speaker 1: the idea that you change a thing you observe just
Speaker 1: through the act of observation. Well, you can have a
Speaker 1: workspace that humans had only been working in for a while,
Speaker 1: and you could say, all right, well, I've observed how
Speaker 1: the humans work, and I'm going to build a robot
Speaker 1: that does this one task that the humans do, and
Speaker 1: I'm just going to incorporate right into their workspace. But
Speaker 1: then you find out that when you do that, the
Speaker 1: humans all behave in a new way because there's a
Speaker 1: new thing in the environment that you didn't account for,
Speaker 1: and now the design of your robot doesn't work as well.
Speaker 1: We humans are tricky like that. Moreover, we need to
Speaker 1: get to that threat that weavers were worried about more
Speaker 1: than a century ago. Is automation going to take our jobs? Now?
Speaker 1: There have been a few studies, all using different methodologies,
Speaker 1: and some of those studies coming under criticism for the
Speaker 1: approaches that were used. But there have been a few
Speaker 1: studies that suggest we'll see automation continue to impact jobs
Speaker 1: in the near future and drastically so over the course
Speaker 1: of the long run. The interpretation of those results have
Speaker 1: been reported in ways that range from automation is going
Speaker 1: to be disruptive that's on the light end to fifty
Speaker 1: percent of all jobs are going to be taken by
Speaker 1: the robots. So what's the actual truth. Well, the truth,
Speaker 1: as it turns out, is complex. For one thing, automation
Speaker 1: rarely takes over an entire job. What is far more
Speaker 1: likely to happen is that automation will take over certain
Speaker 1: tasks that are part of a job, or perhaps multiple jobs.
Speaker 1: So if a job requires a wide variety of tasks,
Speaker 1: some of which may require critical thinking, it's really hard
Speaker 1: to design a robot that can do all of that.
Speaker 1: It's far more likely that you would automate certain job responsibilities,
Speaker 1: which would mean that those jobs themselves wouldn't go away,
Speaker 1: they would just change. The repetitive responsibilities would be offloaded,
Speaker 1: and you would focus on something else. You might have
Speaker 1: to spend more time doing other duties rather than the
Speaker 1: routine ones, which isn't necessarily a bad thing, but there
Speaker 1: are cases where automation would likely take over an entire job,
Speaker 1: for example, truck drivers in shipping trucks. Much of the
Speaker 1: work in autonomous vehicles is really focusing not necessarily on
Speaker 1: replacing passenger vehicles so much as commercial vehicles like shipping trucks.
Speaker 1: The Bureau of Labor Statistics in the United States estimated
Speaker 1: that the age of the average US truck driver is
Speaker 1: fifty five and more than ninety percent of all truck
Speaker 1: drivers in the US are mail and that will present
Speaker 1: a challenge see Generally, the pro argument for automation is
Speaker 1: that while robots and automated systems will eliminate some jobs,
Speaker 1: they will create other jobs, presumably better jobs. And this
Speaker 1: is true. At the turn of the twentieth century, forty
Speaker 1: percent of all jobs in the United States were on farms.
Speaker 1: So that means four out of ten people in the
Speaker 1: US who had a job we're working on a farm. Today,
Speaker 1: Agriculture and all the related food sectors make up just
Speaker 1: eleven percent of all jobs in the United States. And
Speaker 1: if we just limit this to the people who are
Speaker 1: working on farms, you know, not all agricultural jobs and
Speaker 1: food sector jobs, just the farm jobs. If we do that,
Speaker 1: we're talking about only one point three percent of all
Speaker 1: US employment, So going from forty percent to one point
Speaker 1: three percent, that's a drastic change. Now, clearly automation has
Speaker 1: transformed agriculture. It allows us to do a lot more
Speaker 1: while relying on fewer people, and new jobs did come around,
Speaker 1: so we didn't see an unemployment rate reaching levels higher
Speaker 1: than forty percent pre COVID. The pro automation argument states
Speaker 1: that new jobs, which again should ideally be better than
Speaker 1: existing jobs, as in less strenuous and less dangerous and
Speaker 1: more interesting, will emerge as older jobs are phased out.
Speaker 1: Now that works fine on a macro scale when you're
Speaker 1: taking a really big picture look at the overall trends,
Speaker 1: but when you consider the particulars, like our truck drivers,
Speaker 1: you start to see some obstacles. See this year, I
Speaker 1: turned forty five, so I'm a lot closer to the
Speaker 1: average age of a truck driver in the United States
Speaker 1: than I am to someone who's just getting into the
Speaker 1: job market for the first time. And I can tell
Speaker 1: you that even as a relatively tech savvy guy, I
Speaker 1: would find it really challenging to pick up the job skills.
Speaker 1: I would need to go into a different line of work,
Speaker 1: particularly one where I'm competing against people who already have
Speaker 1: training and experience in that field. So imagine having to
Speaker 1: tell a group of fifty five year old truck drivers
Speaker 1: that they're out of a job. But good news, if
Speaker 1: you just start taking classes, you can learn to code
Speaker 1: and make less money than you did in your old job.
Speaker 1: It's not great, is what I'm saying. That being said,
Speaker 1: automation is clearly not going anywhere. It's going to continue
Speaker 1: to play a big role in how we get work done,
Speaker 1: and in our best case scenarios, it's going to augment
Speaker 1: the work that humans do, leading to better, more efficient,
Speaker 1: and more cost effective outcomes. It will free us up
Speaker 1: to focus on the parts of our jobs that we
Speaker 1: find the most fulfilling. We can handle the stuff that
Speaker 1: requires flexibility and intuitive thinking, and the machines can handle
Speaker 1: the routine and the dangerous. But in a worst case scenario,
Speaker 1: we'll see an unprepared population of former workers who are
Speaker 1: now out of a job and without the support system
Speaker 1: there to help them transition into something new so that
Speaker 1: they can continue to contribute to society and earn a living. Now,
Speaker 1: this is why you will often hear conversations about automation
Speaker 1: get tied into concepts like a guaranteed jobs program. This
Speaker 1: is typically where something like a government creates a system
Speaker 1: that makes certain every person who wants a job can
Speaker 1: get a job. Or you'll hear about guaranteed basic income.
Speaker 1: This is a strategy in which tax dollars go to
Speaker 1: fund a standard income payout to all citizens so that
Speaker 1: they can meet their most basic needs. Now, these are
Speaker 1: big ideas, they aren't easy to implement or administer, and
Speaker 1: they're not cheap, But it may be that they will
Speaker 1: become necessary or some similar strategy will be needed to
Speaker 1: make certain that we have a plan to move toward
Speaker 1: rather than being caught in a world where a disproportionate
Speaker 1: percentage of people can't find gainful employment. Heck, we're seeing
Speaker 1: something like that right now due to the COVID crisis,
Speaker 1: which is also underlining the importance of automation in a
Speaker 1: world where it's not necessarily safe to have a bunch
Speaker 1: of human beings all gathered in the same place at
Speaker 1: the same time. Robots coming for our jobs, well, for
Speaker 1: some of our jobs, definitely, many of those jobs come
Speaker 1: with some pretty tough consequences for humans who are working
Speaker 1: those jobs today. Those jobs may have high injury rates,
Speaker 1: the people who work them may have lower life expectancies,
Speaker 1: and they are a whole host of health issues that
Speaker 1: can come along with certain jobs. So you could make
Speaker 1: a strong argument that really this is for the best
Speaker 1: because it will help save lives and reduce the chance
Speaker 1: for injury or illness for a lot of people. But
Speaker 1: for other jobs, the robots aren't likely to take over
Speaker 1: in the near future. For a lot of jobs, automated systems,
Speaker 1: not necessarily robots, but perhaps software based AI, will augment
Speaker 1: what humans are doing. It's important we have conversations about
Speaker 1: this stuff and to talk about how to address the
Speaker 1: consequences of increased automation. There are ways we can enjoy
Speaker 1: the benefits of automation, but only if we think critics
Speaker 1: about it and create policies and procedures accordingly. Now I
Speaker 1: gotta get going. I hear robo Jonathan is going to
Speaker 1: host the next episode of Tech Stuff, and I have
Speaker 1: to train them on how to make puns and pop
Speaker 1: culture references. I hope you liked that episode from twenty twenty.
Speaker 1: As I said, We've got a lot more to talk
Speaker 1: about these days because of things like generative AI and
Speaker 1: the concern that that could impact jobs that for a
Speaker 1: long time people assumed we're safe from automation, especially from
Speaker 1: things like robotics, you know, white collar jobs that people
Speaker 1: just thought were kind of the domain of humans, And
Speaker 1: now there's a real question as to whether or not
Speaker 1: that's actually the case. So I think it's even more prevalent.
Speaker 1: And again seeing the labor movement in the tech sector
Speaker 1: in particular over the last few years tells us that
Speaker 1: there's some very important issues still at the very heart
Speaker 1: of technology and the way we do business that relate
Speaker 1: back to the foundations of the labor movement here in America.
Speaker 1: So I hope you enjoyed that episode. For those of
Speaker 1: you in the United States, I hope you're having a
Speaker 1: healthy and safe and fun Labor Day. For everyone else,
Speaker 1: I hope you're having a great Monday, you know. I
Speaker 1: hope your day is fantastic too, And I'll talk to
Speaker 1: you again really soon. Tech Stuff is an iHeartRadio production.
Speaker 1: For more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts,
Speaker 1: or wherever you listen to your favorite shows.