Speaker 1: Welcome to text Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I am your host,
Speaker 1: Jonathan Strickland. I'm an executive producer with I Heart Radio
Speaker 1: and I love all things tech. You know, guys, I
Speaker 1: read a lot of tech news and sometimes that ends
Speaker 1: up inspiring me to do an episode of text Stuff.
Speaker 1: That happened to me recently when I read this headline
Speaker 1: off of the website text Spot. Sony Factory assembles PS
Speaker 1: four in thirty seconds, only four humans involved in the process.
Speaker 1: A p S four, in case you're not aware, is
Speaker 1: a PlayStation for video game consoles. So this factory can
Speaker 1: build a video game console from parts in half a
Speaker 1: minute and only four human beings touched the ding day
Speaker 1: thing in the process. Those four humans, by the way,
Speaker 1: are involved in the beginning and the end of the process.
Speaker 1: Two of them load motherboards onto the assembly line, and
Speaker 1: a motherboard is the primary circuit board for a computer system,
Speaker 1: and the other two human beings are at the end
Speaker 1: of the assembly line and their job is to package
Speaker 1: the completed consoles. All the actual assembly work is done
Speaker 1: by robots. Now, you may be experiencing a couple of
Speaker 1: different responses to this information I know I did. One
Speaker 1: of those was a wow, that's seriously impressive. The PS four,
Speaker 1: like many computer systems, has a lot of components, many
Speaker 1: of which attached to one another by wire or cable.
Speaker 1: So these robots have to be able to take these
Speaker 1: flexible components and to join them in their proper anchor
Speaker 1: points with the appropriate amount of pressure and precision to
Speaker 1: make a good connection. Now, if any of you out
Speaker 1: there have ever built your own PC, you know that
Speaker 1: plugging cables in can get a little tricky depending on
Speaker 1: the layout of the motherboard and the various components. And
Speaker 1: if you're someone like me, you're likely putting stuff together
Speaker 1: only to realize that maybe you should have done some
Speaker 1: of that before you mounted them in a computer case,
Speaker 1: because now you just don't have the space to work
Speaker 1: in properly. So it's pretty darn impressive that robots can
Speaker 1: do this consistently and correctly at that level of speed.
Speaker 1: Another response I had was it's kind of scary. I mean,
Speaker 1: typically you would have dozens of people employed on the
Speaker 1: assembly line to do this sort of work, but in
Speaker 1: this factory it's been stripped down to thirty two robots
Speaker 1: and four human beings. The article in tech spot points
Speaker 1: out that twenty six of those thirty two robots are
Speaker 1: just attaching flexible components together inside the console. Now, I
Speaker 1: have no idea how much these robots cost, but I wait,
Speaker 1: you're that they are expensive enough to equal the salary
Speaker 1: of a standard human employee on the assembly line. However,
Speaker 1: you don't pay robots. You do have to spend money
Speaker 1: to maintain and repair them, but assuming whatever you're making
Speaker 1: is going to be around for a little while, they'll
Speaker 1: pay for themselves because eventually you'll get to a point
Speaker 1: where the salaries you'd be paying for humans would be
Speaker 1: more than the purchase and maintenance cost of the robots.
Speaker 1: And the increase in efficiency means you can produce a
Speaker 1: whole lot more stuff in a given amount of time
Speaker 1: then you would with a human centric assembly line, so
Speaker 1: you'll have more product to sell in a shorter amount
Speaker 1: of time. When you start crunching numbers, you discover your
Speaker 1: robotic assembly line can make more stuff at a lower
Speaker 1: cost over a given period of time, like you know,
Speaker 1: over a couple of years, than what you would accomplish
Speaker 1: with human beings on that assembly line. So you don't
Speaker 1: have to worry about the robots taking a vacation. They
Speaker 1: don't take sick time, they don't even take the night off.
Speaker 1: They can work around the clock. They don't need health insurance,
Speaker 1: though I would guess that most companies ensure the heck
Speaker 1: out of these things just in case one breaks down.
Speaker 1: But from a financial point of view, they make sense
Speaker 1: if you're building stuff at a large enough scale, stuff
Speaker 1: like video game consoles for the PlayStation four. It's a
Speaker 1: no brainer because that console has sold around one hundred
Speaker 1: ten million units so far. That's a number large enough
Speaker 1: that I can't even imagine what it would look like
Speaker 1: if you had all those consoles together in one place.
Speaker 1: So if there's enough demand for you to sell a
Speaker 1: hundred ten million whatever it is you want to sell,
Speaker 1: you need to have a way to make those as
Speaker 1: efficiently as possible, and that will help maximize your profits.
Speaker 1: And the more efficient the process, the more competitively you
Speaker 1: can price your product and still make a profit. But
Speaker 1: the idea of robots performing jobs far more effectively, consistently,
Speaker 1: and efficiently than humans raises a lot of questions, and
Speaker 1: these are not new questions either, but they are questions
Speaker 1: like if more factories rely on robots for production, particularly
Speaker 1: if those robots can be programmed to produce new products
Speaker 1: once 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? Where will they go? What will
Speaker 1: this do to economies around the world. Lots of people
Speaker 1: have tried to answer these questions, sometimes giving drastically different answers.
Speaker 1: And we're going to take a look at the history
Speaker 1: and evolution of industrial robots in this episode and explore
Speaker 1: the ramifications of automated manufacturing. And this is where I
Speaker 1: dive into history. I've talked about the history of robots before,
Speaker 1: so I'll try to restrict my focus to an 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 textiles,
Speaker 1: was made by crafts people out of their own homes.
Speaker 1: This was literally the cottage industry. Tradespeople would travel and
Speaker 1: 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 trades people built a good deal of
Speaker 1: wealth working this way, and they had the means to
Speaker 1: look at alternatives to this decentralized cottage industry approach. An
Speaker 1: idea began to form. If you brought together crafts people
Speaker 1: to a centralized location, and if you simplified the process
Speaker 1: of production, you can make way more stuff, which in
Speaker 1: turn means you could sell way more stuff, which in
Speaker 1: turn means you can make way more money, and money
Speaker 1: makes the world go round. This thought process helped fuel
Speaker 1: a similar line of thinking. If you could design machines
Speaker 1: that could do a lot of work that typically felt
Speaker 1: a skilled crafts people, you wouldn't need the crafts people
Speaker 1: at all. You could train anyone, even if that person
Speaker 1: had no experience with the process just to work the machine.
Speaker 1: And while it might take years of dedication to go
Speaker 1: through the process of being an apprentice to learn a
Speaker 1: trade well enough so that you can actually make a
Speaker 1: living at it with a machine, you can skip right
Speaker 1: over that. As long as the machines in product was
Speaker 1: good enough. It didn't have to be better than the
Speaker 1: stuff crafts people were making. It just had to be
Speaker 1: good enough and cheap enough and fast enough to produce.
Speaker 1: Then you could sell the finished product at a lower
Speaker 1: cost than what craftspeople would charge because not as much
Speaker 1: time and effort went into making the thing. Now, I
Speaker 1: guess 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 looms
Speaker 1: operation was such that a person who had no training
Speaker 1: and 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 up 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 one 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 sabot 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 use 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 the story, while compelling, isn't really
Speaker 1: the truth. Sabotage does stem from the words sabo, but
Speaker 1: in French there is a verb sabotet. 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 if
Speaker 1: a toddler wore wooden shoes, I think it would probably
Speaker 1: sound as though the world were shaking apart. I don't
Speaker 1: know how toddlers managed to sound like they weigh a
Speaker 1: hundred pounds, but they do it. And if you have
Speaker 1: a toddler, you know what I'm talking about. And in
Speaker 1: the culture of France, the idea of a clumsy slow
Speaker 1: worker was often linked to someone who wore wooden shoes
Speaker 1: because they're awkward to wear anyway. The reason sabote led
Speaker 1: to sabotage is because factory workers who were protesting their
Speaker 1: work conditions and wages would purposefully work more slowly and
Speaker 1: less efficiently. In order to affect the overall output of
Speaker 1: a factory. It was related to a similar strategy that
Speaker 1: British laborers employed, and their version was called kakani. It
Speaker 1: was a saying from Scotland which essentially means don't do
Speaker 1: so much man now. I would argue this also feeds
Speaker 1: into a strategy that we see to this very day
Speaker 1: in certain government offices, where the ideas there's no need
Speaker 1: to do too much too quickly, as it doesn't result
Speaker 1: in increased compensation, and it also sets a really high
Speaker 1: bar of expectations, So why not just take it easy
Speaker 1: and I don't have a coffee break now. In the
Speaker 1: early twentieth century, people began to use the word sabotage
Speaker 1: to really refer to a purposeful approach to undermining the
Speaker 1: output of factories, and it had nothing to do with
Speaker 1: tossing wooden shoes into machinery, though it did also pertain
Speaker 1: to instances in which workers purposefully damaged equipment and tried
Speaker 1: to slow down the production that way. While this isn't
Speaker 1: directly tied to the idea that machines themselves are displacing workers,
Speaker 1: it is related to the effect of moving towards a
Speaker 1: manufacturing based economy and how that allow for the exploitation
Speaker 1: of workers. The machines themselves aren't really at fault, but
Speaker 1: they facilitate the system of operations that leads to exploitation.
Speaker 1: Now that's something that will be a theme in this episode,
Speaker 1: and we can't ignore the social aspect of what's going
Speaker 1: on here, or else we missed the whole point. But
Speaker 1: let's skip ahead. I've spoken about this before, but we
Speaker 1: get the word robot from a check author named Carrol Copeck.
Speaker 1: He wrote a play called Rossom's Universal Robots or Are
Speaker 1: You Are? In nineteen twenty. Copeck took an older word robota,
Speaker 1: which means forced labor in Europe. This concept was tied
Speaker 1: to that of the old system of serfdom, in which
Speaker 1: people 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. And Are You Are, factory owners devise
Speaker 1: a way to build laborers from raw materials. Now, in
Speaker 1: the play, they are indistinguishable from humans other than they
Speaker 1: have no inner desires. But in the course of the play,
Speaker 1: these laborers eventually take over all the jobs that humans
Speaker 1: previously held, and humans themselves become a threatened species as
Speaker 1: these laborers begin to understand the power that they hold
Speaker 1: by occupying all the positions of employment, including as soldiers
Speaker 1: in the military. And so with the introduction of the
Speaker 1: concept of robot we actually get the very first robotic
Speaker 1: uprising all the way back in See I told you
Speaker 1: it was an old idea. It's important to remember that
Speaker 1: in the play, the robots are nearly identical to humans.
Speaker 1: They they aren't mechanical the way our robots of today are,
Speaker 1: but the idea of creating machines that can do work
Speaker 1: without a will of their own is a part of
Speaker 1: row botics in general and industrial robotics in particular. When
Speaker 1: we come back, we'll talk about the earliest industrial robots
Speaker 1: and what they did, but first let's take a quick break.
Speaker 1: It's interesting to me that the tech world adopted the
Speaker 1: term robot when we think about the origins of that word.
Speaker 1: In compex work, robots were sentient slaves. They could perform
Speaker 1: the work humans would otherwise do, but they lack the
Speaker 1: emotions that humans have, and the whole idea is that
Speaker 1: these devices could do our work for us without question
Speaker 1: or protest. They would in theory endure conditions that people
Speaker 1: wouldn't or couldn't, but in the play, they ultimately lead
Speaker 1: to the destruction of the human race and potentially they
Speaker 1: become the new dominant species on the planet. Now, I
Speaker 1: say potentially because part of the play's plot involves the
Speaker 1: destruction of the formula that scientists use to produce the
Speaker 1: robots in the first place. That is an important plot point.
Speaker 1: The robots are not sure how to make more robots,
Speaker 1: so they might just die out. Now, it seems to
Speaker 1: me as though that's a pretty emotionally charged term to
Speaker 1: adopt for an entire discipline of technology, right, robots, especially
Speaker 1: if you are actually aware of that play, and by
Speaker 1: the way, I recommend people read it. It's a good play.
Speaker 1: But then a lot of people are not aware of
Speaker 1: the origins of the word, or at least not beyond
Speaker 1: knowing that it came from a play in the nineteen twenties.
Speaker 1: So I guess for them it's just, you know, a word.
Speaker 1: A robot by any other name would smell as sweet
Speaker 1: as it were. And we've definitely seen the themes of
Speaker 1: are you are serving as an undercurrent for stuff that's
Speaker 1: happening in robotics in general. But let's move ahead. In
Speaker 1: nineteen fifty four or an engineer named George Daval designed
Speaker 1: an industrial robot. He was nine years old when Copic
Speaker 1: coined the term robot. He called his design the Programmed
Speaker 1: Article Transferred Device, for which he received a U S
Speaker 1: patent in nineteen sixty one. This machine was a robotic arm,
Speaker 1: and it was capable of picking up something and then
Speaker 1: transferring it a short distance away just within reach of
Speaker 1: the arm. The arm itself couldn't move, it was anchored
Speaker 1: in place. It could also follow. In fact, this is
Speaker 1: the important part. It would follow a pre program series
Speaker 1: of instructions to do this. Daval's argument for his device
Speaker 1: was that up to this point, mechanical handling of objects
Speaker 1: fell into two broad categories. Either stuff got moved by humans,
Speaker 1: typically operating a powerful machine like a crane or a forklift,
Speaker 1: or stuff got moved by a device that operated under
Speaker 1: cam control. Now, manual control is self explanatory, so let's
Speaker 1: talk about cams. A cam is a rotating component in machinery. Typically,
Speaker 1: a cam has some variation in its surface. So let's
Speaker 1: start with a wheel. Just imagine a wheel that is
Speaker 1: spinning on an axle. Well, You wouldn't typically have a
Speaker 1: perfectly smooth wheel as a cam. Part of that surface
Speaker 1: might be flat, or it might have dips in it,
Speaker 1: and when the cam rotates, these variations apply force to
Speaker 1: some other mechanical component that is held against the cam,
Speaker 1: and it causes that mechanical component to move in specific ways.
Speaker 1: A cam operating system can work on its own, but
Speaker 1: it will always repeat the exact same motions. As long
Speaker 1: as everything is working, it'll just repeat those steps. Once
Speaker 1: the cams complete a full systematic rotation, you can't really
Speaker 1: adapt it to do anything else. The movements depend entirely
Speaker 1: on the cams themselves, so if you wanted it to
Speaker 1: do something else, you would first have to swap out
Speaker 1: the cams uh and even then you would be under
Speaker 1: whatever the limitations of the device was itself, like, it
Speaker 1: wouldn't have full range of motion. Moreover, this level of
Speaker 1: specialization also means that it's typically really expensive to rely
Speaker 1: upon cam based systems, so it was really only useful
Speaker 1: if the application had to do with mass manufacturing or
Speaker 1: else you're looking at economic loss. The cost of the
Speaker 1: system was just too much, so Daval was proposing a
Speaker 1: machine that could be programmed to do operations, and this
Speaker 1: would let a programmer create different processes using the same machine,
Speaker 1: or you could get a whole bunch of the same
Speaker 1: basic machine 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: s X and he got into a conversation with a
Speaker 1: man named Joseph Engelberger. Joseph was a scientist and an entrepreneur,
Speaker 1: and when the subject turned to Duvall'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. Engelberger
Speaker 1: used his connections to get funding for duvol 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 you n I M A T E, and
Speaker 1: the first prototype, Unimate zero zero one, would go to
Speaker 1: General Motors to work on a die casting assembly line. Now,
Speaker 1: according to the company robot Works, that's a w O
Speaker 1: r X. This robot cost around sixty five thousand dollars
Speaker 1: to produce, and Ingelburgers sold it off at a tremendous loss.
Speaker 1: General Motors only paid eighteen thousand dollars for sixty five
Speaker 1: thousand dollar machine. But Ingelberger really wanted to establish that
Speaker 1: robotics were a way to perform repetitive, dangerous functions at
Speaker 1: a lower risk to humans. Welding die cast components on
Speaker 1: auto bodies was a great first application of industrial robots
Speaker 1: for a few reasons. Die Casting is a process involving
Speaker 1: molten metal. You take that molten metal and you force
Speaker 1: it into steel molds, and these are water called dies.
Speaker 1: The molten metal cools in the exact shape of the mold.
Speaker 1: So this is a way to make or cast a
Speaker 1: bunch of identical parts out of metal and get consisted
Speaker 1: stent quality out of it rather than you know, forging
Speaker 1: each piece and then fitting them together. A diet 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 auto bodies 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 where 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. Hydraulic system uses a liquid that's under
Speaker 1: pressure in order to do work like pushing against a
Speaker 1: piston to power and actuator of some sort like lift
Speaker 1: a platform. The Unimate zero zero one weighed twenty seven
Speaker 1: hundred pounds or about one thousand two ms, and it
Speaker 1: could work twenty four hours a day, placing components with
Speaker 1: a precision of within one fifty th of an inch. Now,
Speaker 1: I'm not going to do the conversion on that, because
Speaker 1: I think it's sufficient to say that it was just
Speaker 1: really precise. According to a charmingly dated newsreel from Britain,
Speaker 1: complete with swinging sixties music that sounded like it came
Speaker 1: straight off an Austin Powers movie, the robot could operate
Speaker 1: for five hours without the need for a human to
Speaker 1: check in on it. Engelberger, a savvy businessman and promoter,
Speaker 1: would arrange for Unimate to show what it could do
Speaker 1: at trade shows and on TV appearances, including one on
Speaker 1: The Tonight Show with Johnny Carson. If you don't know
Speaker 1: who that is, ask your parents, and if they don't know,
Speaker 1: ask your grandparents. By nineteen sixty nine, General Motors had
Speaker 1: jumped on board the robot train, as it were. They
Speaker 1: rebuilt a manufacturing plant in Lordstown, Ohio, and they installed
Speaker 1: unimate robots to perform spot welding on car bodies, and
Speaker 1: the results spoke for themselves. The plant was capable of
Speaker 1: producing one hundred ten cars per hour, which was more
Speaker 1: than double the speed that the plant could manage before
Speaker 1: the installation of the robots. The business case for the
Speaker 1: robots seemed clear. After a hefty upfront cost, you could
Speaker 1: produce way more stuff per day, and as long as
Speaker 1: the demand for that stuff is high enough, it could
Speaker 1: mean greater revenue. You could also bring the cost of
Speaker 1: production for an individual unit down. Then you could pass
Speaker 1: savings on to customers and get really competitive with your pricing,
Speaker 1: or you could just keep everything price the same and
Speaker 1: try to increase your profit margin. The key to all
Speaker 1: this was that you had to be sure the thing
Speaker 1: you were producing would bring in enough money to offset
Speaker 1: the cost of automation, so it would not make sense
Speaker 1: to spend millions of dollars building out a factory staffed
Speaker 1: with robots if you were making something that had a
Speaker 1: very small market to begin with, Yes, you'd be able
Speaker 1: to produce way more watching My Call It's than you
Speaker 1: could before. But if the demand for watch my Call
Speaker 1: It's 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 well, 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 dangerous.
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 NINETI, the A S E A I
Speaker 1: RB robot would be the first fully electrically driven robot.
Speaker 1: It also used Intel's first chip set as processors. Now,
Speaker 1: this was not a super strong robot because those electrically
Speaker 1: driven limbs just can't pack the same punch as a
Speaker 1: hydraulic system, which typically moves much more slowly but can
Speaker 1: handle much heavier payloads. So this particular robot could only
Speaker 1: lift weights up to around their teen pounds or six kgrams.
Speaker 1: But the move toward processors and electrically driven components marked
Speaker 1: a big technological step, even if the arms physical capabilities
Speaker 1: were much less impressive than a hydraulic system. By the
Speaker 1: end of the nineteen seventies, Japan was getting into the
Speaker 1: robotics game with arc welding robots for assembly lines, and
Speaker 1: then it was off to the robotic races, with the
Speaker 1: eighties seeing a surge in advances with industrial robots. Soon,
Speaker 1: massive manufacturing facilities were installing robots to take over elements
Speaker 1: of the assembly line process, particularly in that dirty, dull,
Speaker 1: and dangerous category. The robots became more sophisticated, which also
Speaker 1: added to their value. When we come back, I'll talk
Speaker 1: more about why that's important, but first let's take another
Speaker 1: quick break. By the mid nine nineties, robotics companies were
Speaker 1: making machines that could coordinate and synchronize the movements of
Speaker 1: more than one robot at the same time, allowing for
Speaker 1: more complex manufacturing processes. By the early two thousand's, there
Speaker 1: were systems that could synchronize the actions of up to
Speaker 1: four robots at a time, further adding to the overall
Speaker 1: system flexibility. Now I mentioned earlier that a programmable robot
Speaker 1: is more versatile than something like a cam operated system. Well,
Speaker 1: more sophisticated robots with more axes of motion and more.
Speaker 1: Points of articulation have the potential to do lots of
Speaker 1: different types of jobs, and this is of critical importance.
Speaker 1: If the robot is too limited, if you can only
Speaker 1: do a small range of motions, you can't necessarily repurpose
Speaker 1: it for new processes. And as markets change, you may
Speaker 1: find yourself needing to be flexible when it comes to
Speaker 1: the stuff you're manufacturing. So let's use an extreme hypothetical
Speaker 1: example that would probably never happen. So let's say that
Speaker 1: you run an auto manufacturing facility, but then there's a
Speaker 1: massive market change and it drastically affects the demand for
Speaker 1: your cars. There's just not enough demand to support the production.
Speaker 1: So rather than just you know, closing up shop and
Speaker 1: calling it a day, your business decides to do an
Speaker 1: amazing pivot and you begin to convert your manufacturing facility
Speaker 1: over to I don't know, home appliances. Now, again, this
Speaker 1: is an extreme hypothetical example, but let's just go with it. Okay,
Speaker 1: So here we go. If the robots and your assembly
Speaker 1: line are powerful but limited in movement and function, you
Speaker 1: may find it impossible to adapt them to your new
Speaker 1: line of business, which would mean you need to either
Speaker 1: invest in new robots, or you'd have to hire human
Speaker 1: workers to put together your appliances, and it would also
Speaker 1: mean that your old robots would be a sunk cost.
Speaker 1: You would need to either sell them off or put
Speaker 1: them in storage or something. If the robots are really sophisticated, however,
Speaker 1: you might be able to program them to do some
Speaker 1: of the operations on the new assembly line, and that
Speaker 1: would keep them useful, it would lower the cost of production.
Speaker 1: Or for a less extreme example, you introduce a new
Speaker 1: model of whatever a thing it is that you're producing.
Speaker 1: Anything new will require adjustments in the assembly line process,
Speaker 1: and if the changes are big enough, the robots may
Speaker 1: not be able to make as big a contribution in
Speaker 1: the process. That's something that could happen with the example
Speaker 1: of the PlayStation we were talking about. Yeah, those robots
Speaker 1: can put together a PS four and thirty seconds, there's
Speaker 1: no guarantee they'll be able to do the same thing
Speaker 1: with a PS five, at least not without a major
Speaker 1: overhaul of their assembly line system. While the manufacturing facility
Speaker 1: can churn out a finished PS four and thirty seconds,
Speaker 1: we might not see them work at all with PS five,
Speaker 1: at least not right away. It would all have to
Speaker 1: be optimized. So for decades, industrial robots were kept as
Speaker 1: separate from human workers as was possible. You wanted to
Speaker 1: keep them well away from all the people, or keep
Speaker 1: the people well away from all the robots. Often the
Speaker 1: robots would operate within cages specifically to limit the possibility
Speaker 1: of a human coming within range. After all, these robots
Speaker 1: are large, they're heavy, they're powerful, and many of them
Speaker 1: are incapable of sensing stuff in their environment. Uh and
Speaker 1: whether or not a human is within their range of motion. Instead,
Speaker 1: they're just going through that pre programmed series of motions
Speaker 1: and they're not going to stop unless someone turns it off.
Speaker 1: A robot is performing that same series of steps over
Speaker 1: and over, and that can mean that if a human
Speaker 1: in that area gets near the robot, they could end
Speaker 1: up getting injured or worse. And in fact, this has
Speaker 1: happened several times times over the course of the last
Speaker 1: few decades, and at least in some cases it seems
Speaker 1: as though the robot might have been at fault, meaning
Speaker 1: it's not always a case of human carelessness. For example,
Speaker 1: an engineer in twenty fifteen died when a robot arm
Speaker 1: from one section of the factory floor moved beyond its
Speaker 1: operating area and into the neighboring section that the engineer
Speaker 1: was working in. This is something that should not have happened.
Speaker 1: The robot arms should not have moved that far into
Speaker 1: the neighboring section. The robot arm hit the engineer on
Speaker 1: the head, and she later died from her injuries. In
Speaker 1: the United States, the government has listed thirty three workplace
Speaker 1: deaths due to accidents with industrial robots between the years
Speaker 1: nine four and two thousand fourteen. The investigations also found
Speaker 1: that the majority of those tragedies was typically the fault
Speaker 1: of human error. There was a person who was one
Speaker 1: ring into the operation zone of a robot. That two
Speaker 1: thousand fifteen incident was an outlier. Not that any of
Speaker 1: this makes the thought of working around industrial robots less
Speaker 1: scary or those other accidents any less tragic. They're all
Speaker 1: terribly tragic. Moreover, we're seeing more robots that are capable
Speaker 1: of roaming a work space. They are no longer anchored
Speaker 1: to a specific spot on the floor. In some cases,
Speaker 1: they also, unlike the first industrial robots, typically have external sensors.
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, you know, slightly larger than
Speaker 1: the dimensions of the robot. And when an order comes in,
Speaker 1: a robot from the warehouse rolls over to a shelf.
Speaker 1: It holds the respective item on it according to the
Speaker 1: inventory system, and the robot goes under the shelf then
Speaker 1: lifts the shelf by raising a platter like platform on
Speaker 1: the top of the robot. Think of it as like
Speaker 1: a little forklift, 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 bots 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 wait
Speaker 1: further instructions and report that it has found something unusual
Speaker 1: on the warehouse floor. Even so, typically humans are not
Speaker 1: allowed to roam the area where the robots pick up shelves.
Speaker 1: If something has fallen on the warehouse floor, a designated
Speaker 1: troubleshooter gets an alert, and that person must use an
Speaker 1: interface to draw the path that they are going to
Speaker 1: take from the entrance of the cage all the way
Speaker 1: to you the point of trouble. Like let's say that
Speaker 1: a product has fallen out of a shelf and has
Speaker 1: hit the floor, and a robot has reported it. You
Speaker 1: would use a tablet. If you're the troubleshooter, you'd use
Speaker 1: 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 have observed
Speaker 1: how the humans work, and I'm going to build a
Speaker 1: robot that does this one task that the humans do,
Speaker 1: and I'm just gonna 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: states 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 too. Of
Speaker 1: all jobs are going to be taken by the robots.
Speaker 1: So what's the actual truth. Well, the truth, as it
Speaker 1: turns out, is complicated. For one thing, automation rarely takes
Speaker 1: over an entire job. What is far more likely to
Speaker 1: happen is that automation will take over certain tasks that
Speaker 1: are part of a job, or perhaps multiple jobs. So
Speaker 1: if a job requires a wide variety of tasks, some
Speaker 1: of which may require critical thinking, it's really hard to
Speaker 1: design a robot that can do all of that. It's
Speaker 1: far more likely that you would automate certain job respond possibilities,
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, you know, in shipping trucks. Much
Speaker 1: of the work in autonomous vehicles is really focusing not
Speaker 1: necessarily on replacing passenger vehicles so much as commercial vehicles
Speaker 1: like shipping trucks. The Bureau of Labor Statistics in the
Speaker 1: United States estimated that the age of the average US
Speaker 1: truck driver is fifty five and more than of all
Speaker 1: truck drivers in the US are mail and that will
Speaker 1: present a challenge. See Generally, the pro argue meant for
Speaker 1: automation is that while robots and automated systems will eliminate
Speaker 1: some jobs, they will create other jobs, presumably better jobs.
Speaker 1: And this is true. At the turn of the twentieth century,
Speaker 1: 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 of all jobs in the United States. And if
Speaker 1: we just limit this to the people who are working
Speaker 1: on farms, you know, not all agricultural jobs and food
Speaker 1: 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 to one point three percent,
Speaker 1: that's a drastic change. Now, clearly automation has transformed agriculture.
Speaker 1: It allows us to do a lot more while relying
Speaker 1: on fewer people, and new jobs did come around, so
Speaker 1: we didn't see an unemployment rate reaching levels higher than
Speaker 1: pre COVID. The pro automation argument states that new jobs,
Speaker 1: which again should ideally be better than existing jobs, isn't.
Speaker 1: Less strenuous and less dangerous and more interesting will emerge
Speaker 1: as older jobs are phased out. Now, that works fine
Speaker 1: on a macro scale when you're taking a really big
Speaker 1: picture look at the overall trends, But when you consider
Speaker 1: the particulars, like our truck drivers, you start to see
Speaker 1: some obstacles. See this year, I turned forty five, so
Speaker 1: I'm a lot closer to the average age of a
Speaker 1: truck driver in the United States. Then I am to
Speaker 1: someone who's just getting into the job market for the
Speaker 1: first time, and I can tell you that, even as
Speaker 1: a relatively tech savvy guy, I would find it really
Speaker 1: challenging to pick up the job skills. I would need
Speaker 1: to go into a different line of work, particularly one
Speaker 1: where I'm competing against people who already have training and
Speaker 1: experience in that field. So imagine having to tell a
Speaker 1: group of fifty five year old truck drivers that they're
Speaker 1: out of a job. But good news. If you just
Speaker 1: start taking classes, you can learn to code and make
Speaker 1: less money than you did in your old job. It's
Speaker 1: not great, is what I'm saying. Now, 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 nest as sary, or some similar strategy will be
Speaker 1: needed to make certain that we have a plan to
Speaker 1: move toward rather than being caught in a world where
Speaker 1: a disproportionate percentage of people can't find gainful employment. Heck,
Speaker 1: we're seeing something like that right now due to the
Speaker 1: COVID crisis, which is also underlining the importance of automation
Speaker 1: in a world where it's not necessarily safe to have
Speaker 1: a bunch of human beings all gathered in the same
Speaker 1: place at the same time. Are the robots coming for
Speaker 1: our jobs? Well, for some of our jobs. Definitely. Many
Speaker 1: of those jobs come with some pretty tough consequences for
Speaker 1: humans who are working those jobs today. Those jobs may
Speaker 1: have high injury rates, the people who work them may
Speaker 1: have lower life expectancies, and there are a whole host
Speaker 1: of health issues that can come along with certain jobs.
Speaker 1: So you could make a strong argument that really this
Speaker 1: is for the best because it will help save lives
Speaker 1: and reduce the chance for injury or ill. This for
Speaker 1: a lot of people, but for other jobs, the robots
Speaker 1: aren't likely to take over in the near future. For
Speaker 1: a lot of jobs, automated systems not necessarily robots, but
Speaker 1: perhaps you know software based AI will augment what humans
Speaker 1: are doing. It's important we have conversations about this stuff
Speaker 1: and to talk about how to address the consequences of
Speaker 1: increased automation. There are ways we can enjoy the benefits
Speaker 1: of automation, but only if we think critically about it
Speaker 1: and create policies and procedures accordingly. Now I gotta get going.
Speaker 1: I hear robo Jonathan is going to host the next
Speaker 1: episode of tech Stuff, and I have to train them
Speaker 1: on how to make puns and pop culture references. But
Speaker 1: if you guys have suggestions for future topics I could
Speaker 1: tackle here on tech Stuff, please reach out to me
Speaker 1: and let me know what those are. You can reach
Speaker 1: out on Twitter. The handle for the show is text
Speaker 1: stuff hs W and I'll all too again really soon. Y.
Speaker 1: Text Stuff is an i heart Radio production. For more
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