July 13, 2020 • 47 mins
Are robots and automated systems going to replace human workers? And if so, what then? The fear about automation has a long history and it's not an irrational fear.
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Episode Transcript
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Speaker 1 (00:04):
Welcome to text Stuff, a production from I Heart Radio.
Hey there, and welcome to tech Stuff. I am your host,
Jonathan Strickland. I'm an executive producer with I Heart Radio
and I love all things tech. You know, guys, I
read a lot of tech news and sometimes that ends
(00:26):
up inspiring me to do an episode of text Stuff.
That happened to me recently when I read this headline
off of the website text Spot. Sony Factory assembles PS
four in thirty seconds, only four humans involved in the process.
A p S four, in case you're not aware, is
(00:47):
a PlayStation for video game consoles. So this factory can
build a video game console from parts in half a
minute and only four human beings touched the ding day
thing in the process. Those four humans, by the way,
are involved in the beginning and the end of the process.
Two of them load motherboards onto the assembly line, and
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a motherboard is the primary circuit board for a computer system,
and the other two human beings are at the end
of the assembly line and their job is to package
the completed consoles. All the actual assembly work is done
by robots. Now, you may be experiencing a couple of
different responses to this information I know I did. One
(01:32):
of those was a wow, that's seriously impressive. The PS four,
like many computer systems, has a lot of components, many
of which attached to one another by wire or cable.
So these robots have to be able to take these
flexible components and to join them in their proper anchor
points with the appropriate amount of pressure and precision to
(01:54):
make a good connection. Now, if any of you out
there have ever built your own PC, you know that
plugging cables in can get a little tricky depending on
the layout of the motherboard and the various components. And
if you're someone like me, you're likely putting stuff together
only to realize that maybe you should have done some
of that before you mounted them in a computer case,
(02:15):
because now you just don't have the space to work
in properly. So it's pretty darn impressive that robots can
do this consistently and correctly at that level of speed.
Another response I had was it's kind of scary. I mean,
typically you would have dozens of people employed on the
(02:35):
assembly line to do this sort of work, but in
this factory it's been stripped down to thirty two robots
and four human beings. The article in tech spot points
out that twenty six of those thirty two robots are
just attaching flexible components together inside the console. Now, I
have no idea how much these robots cost, but I wait,
(03:00):
you're that they are expensive enough to equal the salary
of a standard human employee on the assembly line. However,
you don't pay robots. You do have to spend money
to maintain and repair them, but assuming whatever you're making
is going to be around for a little while, they'll
pay for themselves because eventually you'll get to a point
(03:20):
where the salaries you'd be paying for humans would be
more than the purchase and maintenance cost of the robots.
And the increase in efficiency means you can produce a
whole lot more stuff in a given amount of time
then you would with a human centric assembly line, so
you'll have more product to sell in a shorter amount
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of time. When you start crunching numbers, you discover your
robotic assembly line can make more stuff at a lower
cost over a given period of time, like you know,
over a couple of years, than what you would accomplish
with human beings on that assembly line. So you don't
have to worry about the robots taking a vacation. They
don't take sick time, they don't even take the night off.
(04:04):
They can work around the clock. They don't need health insurance,
though I would guess that most companies ensure the heck
out of these things just in case one breaks down.
But from a financial point of view, they make sense
if you're building stuff at a large enough scale, stuff
like video game consoles for the PlayStation four. It's a
no brainer because that console has sold around one hundred
(04:28):
ten million units so far. That's a number large enough
that I can't even imagine what it would look like
if you had all those consoles together in one place.
So if there's enough demand for you to sell a
hundred ten million whatever it is you want to sell,
you need to have a way to make those as
(04:49):
efficiently as possible, and that will help maximize your profits.
And the more efficient the process, the more competitively you
can price your product and still make a profit. But
the idea of robots performing jobs far more effectively, consistently,
and efficiently than humans raises a lot of questions, and
these are not new questions either, but they are questions
(05:12):
like if more factories rely on robots for production, particularly
if those robots can be programmed to produce new products
once older ones go obsolete. What happens to the job market,
What happens to the millions of people who work in
manufacturing on assembly lines? Where will they go? What will
this do to economies around the world. Lots of people
(05:35):
have tried to answer these questions, sometimes giving drastically different answers.
And we're going to take a look at the history
and evolution of industrial robots in this episode and explore
the ramifications of automated manufacturing. And this is where I
dive into history. I've talked about the history of robots before,
(05:56):
so I'll try to restrict my focus to an industrial robots.
And before I get into that, let's just address the
fact that the use of machinery to increase efficiency has
been a controversial subject since long before there ever was
such a thing as a robot. Generally speaking, machines are
meant to make work easier, or in some cases, make
(06:19):
the work possible. Just to begin with, they are labor
saving devices, requiring humans to put forth less effort to
get the same or better results. This applies to the
simplest of machines. I mean stuff like levers or pulleys
or an inclined plane, and it applies to very complex
(06:39):
machines as well. Before the Industrial Revolution, most stuff like textiles,
was made by crafts people out of their own homes.
This was literally the cottage industry. Tradespeople would travel and
become the lifeline for the cottage industry, supplying raw materials,
buying finished products, and selling those products off at a
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profit elsewhere. Many trades people built a good deal of
wealth working this way, and they had the means to
look at alternatives to this decentralized cottage industry approach. An
idea began to form. If you brought together crafts people
to a centralized location, and if you simplified the process
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of production, you can make way more stuff, which in
turn means you could sell way more stuff, which in
turn means you can make way more money, and money
makes the world go round. This thought process helped fuel
a similar line of thinking. If you could design machines
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that could do a lot of work that typically felt
a skilled crafts people, you wouldn't need the crafts people
at all. You could train anyone, even if that person
had no experience with the process just to work the machine.
And while it might take years of dedication to go
through the process of being an apprentice to learn a
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trade well enough so that you can actually make a
living at it with a machine, you can skip right
over that. As long as the machines in product was
good enough. It didn't have to be better than the
stuff crafts people were making. It just had to be
good enough and cheap enough and fast enough to produce.
Then you could sell the finished product at a lower
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cost than what craftspeople would charge because not as much
time and effort went into making the thing. Now, I
guess it's clunky to talk about this while using an example,
so let's go with a poster child for the Industrial Revolution. Weaving.
The weaving trade is an ancient one, and it requires
a good deal of skill to do it well by hand.
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In the late seventeen hundreds, a man named Edmund Cartwright
patented a loom powered by a water wheel. The looms
operation was such that a person who had no training
and weaving could operate the machine and produce finished textiles.
Cartwright's design would be built upon by other inventors who
had turned to steam power and other means to operate
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the power loom. Many cottage industry weavers found themselves out
of work. They could potentially up to work in the
textile factories, as those were popping up all over the place,
particularly in England, but the wages were low. As you
can imagine, this didn't sit well with the weavers. There
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were protests, including some that incorporated violence and destruction. Ultimately,
the factory process one out and along with it some
really awful working conditions followed, including stuff like child labor
and ridiculously low wages and dangerous working conditions. This led
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to more protests, including the type that would give us
the word sabotage. And let's get a quick side note
on that one, as it is the source of a
little mythology or misinformation. See The apocryphal story goes that
the word sabotage comes from the word sabot which describes
(10:16):
the wooden shoes worn by laborers, mainly Dutch laborers, but
also laborers in France. And according to the story, these
laborers wore those shoes and use them to great effect.
In an effort to protest the conditions and factories, they
would toss their wooden shoes into the machinery to break
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the various gears and literally grind production to a halt,
as it were. But the story, while compelling, isn't really
the truth. Sabotage does stem from the words sabo, but
in French there is a verb sabotet. This verb means
to make a loud noise with wooden shoes. Now isn't
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it great that there's a verb for that? And it
makes sense wooden shoes would make a great deal of
racket as people would walk around. Heck, if a if
a toddler wore wooden shoes, I think it would probably
sound as though the world were shaking apart. I don't
know how toddlers managed to sound like they weigh a
hundred pounds, but they do it. And if you have
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a toddler, you know what I'm talking about. And in
the culture of France, the idea of a clumsy slow
worker was often linked to someone who wore wooden shoes
because they're awkward to wear anyway. The reason sabote led
to sabotage is because factory workers who were protesting their
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work conditions and wages would purposefully work more slowly and
less efficiently. In order to affect the overall output of
a factory. It was related to a similar strategy that
British laborers employed, and their version was called kakani. It
was a saying from Scotland which essentially means don't do
so much man now. I would argue this also feeds
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into a strategy that we see to this very day
in certain government offices, where the ideas there's no need
to do too much too quickly, as it doesn't result
in increased compensation, and it also sets a really high
bar of expectations, So why not just take it easy
and I don't have a coffee break now. In the
early twentieth century, people began to use the word sabotage
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to really refer to a purposeful approach to undermining the
output of factories, and it had nothing to do with
tossing wooden shoes into machinery, though it did also pertain
to instances in which workers purposefully damaged equipment and tried
to slow down the production that way. While this isn't
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directly tied to the idea that machines themselves are displacing workers,
it is related to the effect of moving towards a
manufacturing based economy and how that allow for the exploitation
of workers. The machines themselves aren't really at fault, but
they facilitate the system of operations that leads to exploitation.
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Now that's something that will be a theme in this episode,
and we can't ignore the social aspect of what's going
on here, or else we missed the whole point. But
let's skip ahead. I've spoken about this before, but we
get the word robot from a check author named Carrol Copeck.
He wrote a play called Rossom's Universal Robots or Are
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You Are? In nineteen twenty. Copeck took an older word robota,
which means forced labor in Europe. This concept was tied
to that of the old system of serfdom, in which
people would do work on behalf of a landowner. In return,
those people would be allowed to live on part of
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that landowner's land. And Are You Are, factory owners devise
a way to build laborers from raw materials. Now, in
the play, they are indistinguishable from humans other than they
have no inner desires. But in the course of the play,
these laborers eventually take over all the jobs that humans
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previously held, and humans themselves become a threatened species as
these laborers begin to understand the power that they hold
by occupying all the positions of employment, including as soldiers
in the military. And so with the introduction of the
concept of robot we actually get the very first robotic
uprising all the way back in See I told you
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it was an old idea. It's important to remember that
in the play, the robots are nearly identical to humans.
They they aren't mechanical the way our robots of today are,
but the idea of creating machines that can do work
without a will of their own is a part of
row botics in general and industrial robotics in particular. When
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we come back, we'll talk about the earliest industrial robots
and what they did, but first let's take a quick break.
It's interesting to me that the tech world adopted the
term robot when we think about the origins of that word.
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In compex work, robots were sentient slaves. They could perform
the work humans would otherwise do, but they lack the
emotions that humans have, and the whole idea is that
these devices could do our work for us without question
or protest. They would in theory endure conditions that people
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wouldn't or couldn't, but in the play, they ultimately lead
to the destruction of the human race and potentially they
become the new dominant species on the planet. Now, I
say potentially because part of the play's plot involves the
destruction of the formula that scientists use to produce the
robots in the first place. That is an important plot point.
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The robots are not sure how to make more robots,
so they might just die out. Now, it seems to
me as though that's a pretty emotionally charged term to
adopt for an entire discipline of technology, right, robots, especially
if you are actually aware of that play, and by
the way, I recommend people read it. It's a good play.
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But then a lot of people are not aware of
the origins of the word, or at least not beyond
knowing that it came from a play in the nineteen twenties.
So I guess for them it's just, you know, a word.
A robot by any other name would smell as sweet
as it were. And we've definitely seen the themes of
are you are serving as an undercurrent for stuff that's
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happening in robotics in general. But let's move ahead. In
nineteen fifty four or an engineer named George Daval designed
an industrial robot. He was nine years old when Copic
coined the term robot. He called his design the Programmed
Article Transferred Device, for which he received a U S
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patent in nineteen sixty one. This machine was a robotic arm,
and it was capable of picking up something and then
transferring it a short distance away just within reach of
the arm. The arm itself couldn't move, it was anchored
in place. It could also follow. In fact, this is
the important part. It would follow a pre program series
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of instructions to do this. Daval's argument for his device
was that up to this point, mechanical handling of objects
fell into two broad categories. Either stuff got moved by humans,
typically operating a powerful machine like a crane or a forklift,
or stuff got moved by a device that operated under
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cam control. Now, manual control is self explanatory, so let's
talk about cams. A cam is a rotating component in machinery. Typically,
a cam has some variation in its surface. So let's
start with a wheel. Just imagine a wheel that is
spinning on an axle. Well, You wouldn't typically have a
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perfectly smooth wheel as a cam. Part of that surface
might be flat, or it might have dips in it,
and when the cam rotates, these variations apply force to
some other mechanical component that is held against the cam,
and it causes that mechanical component to move in specific ways.
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A cam operating system can work on its own, but
it will always repeat the exact same motions. As long
as everything is working, it'll just repeat those steps. Once
the cams complete a full systematic rotation, you can't really
adapt it to do anything else. The movements depend entirely
on the cams themselves, so if you wanted it to
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do something else, you would first have to swap out
the cams uh and even then you would be under
whatever the limitations of the device was itself, like, it
wouldn't have full range of motion. Moreover, this level of
specialization also means that it's typically really expensive to rely
upon cam based systems, so it was really only useful
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if the application had to do with mass manufacturing or
else you're looking at economic loss. The cost of the
system was just too much, so Daval was proposing a
machine that could be programmed to do operations, and this
would let a programmer create different processes using the same machine,
or you could get a whole bunch of the same
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basic machine and program each one to do a particular job. Meanwhile,
you'd free people up to work on other stuff in
the manufacturing process, and you could take the most dangerous
stuff and give it to the robots. Now, the story
goes that Daval was at a party in nineteen fifty
s X and he got into a conversation with a
man named Joseph Engelberger. Joseph was a scientist and an entrepreneur,
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and when the subject turned to Duvall's programmed article transferred device,
as well as the work of a science fiction author
known as Isaac Asimov, you know, the father of robotics.
He famously incorporated a concept of the laws of robotics
in his works. We won't really go into that in
this episode, but the laws of robotics still play a
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big part in the discipline of robotics in general, but
it's kind of outside the focus of this episode. Engelberger
used his connections to get funding for duvol to create
a more advanced version of the programmed article transfer machine,
and it would be a robotic arm capable of making repeated,
precise movements while holding very heavy objects. They called it
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the Unimate you n I M A T E, and
the first prototype, Unimate zero zero one, would go to
General Motors to work on a die casting assembly line. Now,
according to the company robot Works, that's a w O
r X. This robot cost around sixty five thousand dollars
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to produce, and Ingelburgers sold it off at a tremendous loss.
General Motors only paid eighteen thousand dollars for sixty five
thousand dollar machine. But Ingelberger really wanted to establish that
robotics were a way to perform repetitive, dangerous functions at
a lower risk to humans. Welding die cast components on
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auto bodies was a great first application of industrial robots
for a few reasons. Die Casting is a process involving
molten metal. You take that molten metal and you force
it into steel molds, and these are water called dies.
The molten metal cools in the exact shape of the mold.
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So this is a way to make or cast a
bunch of identical parts out of metal and get consisted
stent quality out of it rather than you know, forging
each piece and then fitting them together. A diet can
have complex shapes in it, such as external threads, which
means you don't have to make a pipe, for example,
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and then do a secondary process on that pipe to
get the result you want. So you wouldn't have to
carve those threads into a otherwise smooth pipe. You could
just cast the pipe with the threads incorporated on it already.
But welding die cast parts onto auto bodies is hard work.
The components are really heavy, so you're at risk of
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immediate injury if something goes wrong, like let's say you
drop a weighty component on your foot, or you might
develop a repetitive stress injury after going through the same
welding motions over and over again. In addition, the fumes
given off while welding where sometimes toxic still are so
it's not great to have people exposed to them for
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very long. So a robot was a great substitute for
a person. The robot could handle much greater weight than
people could. The robot didn't breathe, so there was no
respiratory issue there, and it didn't get tired. I mean
it would wear down over time, but you could repair
it in fairly short order. The Unimate worked with computer
controlled hydraulic systems. Hydraulic system uses a liquid that's under
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pressure in order to do work like pushing against a
piston to power and actuator of some sort like lift
a platform. The Unimate zero zero one weighed twenty seven
hundred pounds or about one thousand two ms, and it
could work twenty four hours a day, placing components with
a precision of within one fifty th of an inch. Now,
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I'm not going to do the conversion on that, because
I think it's sufficient to say that it was just
really precise. According to a charmingly dated newsreel from Britain,
complete with swinging sixties music that sounded like it came
straight off an Austin Powers movie, the robot could operate
for five hours without the need for a human to
check in on it. Engelberger, a savvy businessman and promoter,
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would arrange for Unimate to show what it could do
at trade shows and on TV appearances, including one on
The Tonight Show with Johnny Carson. If you don't know
who that is, ask your parents, and if they don't know,
ask your grandparents. By nineteen sixty nine, General Motors had
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jumped on board the robot train, as it were. They
rebuilt a manufacturing plant in Lordstown, Ohio, and they installed
unimate robots to perform spot welding on car bodies, and
the results spoke for themselves. The plant was capable of
producing one hundred ten cars per hour, which was more
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than double the speed that the plant could manage before
the installation of the robots. The business case for the
robots seemed clear. After a hefty upfront cost, you could
produce way more stuff per day, and as long as
the demand for that stuff is high enough, it could
mean greater revenue. You could also bring the cost of
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production for an individual unit down. Then you could pass
savings on to customers and get really competitive with your pricing,
or you could just keep everything price the same and
try to increase your profit margin. The key to all
this was that you had to be sure the thing
you were producing would bring in enough money to offset
the cost of automation, so it would not make sense
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to spend millions of dollars building out a factory staffed
with robots if you were making something that had a
very small market to begin with, Yes, you'd be able
to produce way more watching My Call It's than you
could before. But if the demand for watch my Call
It's is really modest, that doesn't do you any good.
In fact, you might end up flooding the market and
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devaluing your product. So well, robots were taking on jobs
that were previously held by humans, there was no real
danger of a massive upheaval where everything would be automated.
The limitations in the technology were just too great and
the cost was too high for most companies to go
that route. And this also became the starting point for
something that would become really important. That the main goal
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of developing industrial robots wasn't to displace humans. It was
meant to offload duties that were dull, dirty, or dangerous.
You'll often hear those terms being used with robotics. If
it is a job that carries with it a significant
risk to the person performing it, or a job so
demanding that you can only expect a person to stick
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with it for a short while before they need to
do something else, then building a robot to do that job,
or at least that list of tasks makes sense. The
robot is just a thing. It can endure conditions that
humans can't, and it doesn't get sick, and it doesn't
get hurt. If something breaks down, you can typically repair
it pretty quickly. We humans don't have that luxury. Now,
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I'm not going to go and run down a full
history of all industrial robots because that would mostly involve
me talking about model numbers with slight differences like the
number of axes of movement or points of articulation for
one robot versus another, and that's not really interesting. But
I do want to hit a couple of highlights. One
is that in NINETI, the A S E A I
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RB robot would be the first fully electrically driven robot.
It also used Intel's first chip set as processors. Now,
this was not a super strong robot because those electrically
driven limbs just can't pack the same punch as a
hydraulic system, which typically moves much more slowly but can
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handle much heavier payloads. So this particular robot could only
lift weights up to around their teen pounds or six kgrams.
But the move toward processors and electrically driven components marked
a big technological step, even if the arms physical capabilities
were much less impressive than a hydraulic system. By the
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end of the nineteen seventies, Japan was getting into the
robotics game with arc welding robots for assembly lines, and
then it was off to the robotic races, with the
eighties seeing a surge in advances with industrial robots. Soon,
massive manufacturing facilities were installing robots to take over elements
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of the assembly line process, particularly in that dirty, dull,
and dangerous category. The robots became more sophisticated, which also
added to their value. When we come back, I'll talk
more about why that's important, but first let's take another
quick break. By the mid nine nineties, robotics companies were
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making machines that could coordinate and synchronize the movements of
more than one robot at the same time, allowing for
more complex manufacturing processes. By the early two thousand's, there
were systems that could synchronize the actions of up to
four robots at a time, further adding to the overall
system flexibility. Now I mentioned earlier that a programmable robot
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is more versatile than something like a cam operated system. Well,
more sophisticated robots with more axes of motion and more.
Points of articulation have the potential to do lots of
different types of jobs, and this is of critical importance.
If the robot is too limited, if you can only
do a small range of motions, you can't necessarily repurpose
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it for new processes. And as markets change, you may
find yourself needing to be flexible when it comes to
the stuff you're manufacturing. So let's use an extreme hypothetical
example that would probably never happen. So let's say that
you run an auto manufacturing facility, but then there's a
massive market change and it drastically affects the demand for
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your cars. There's just not enough demand to support the production.
So rather than just you know, closing up shop and
calling it a day, your business decides to do an
amazing pivot and you begin to convert your manufacturing facility
over to I don't know, home appliances. Now, again, this
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is an extreme hypothetical example, but let's just go with it. Okay,
So here we go. If the robots and your assembly
line are powerful but limited in movement and function, you
may find it impossible to adapt them to your new
line of business, which would mean you need to either
invest in new robots, or you'd have to hire human
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workers to put together your appliances, and it would also
mean that your old robots would be a sunk cost.
You would need to either sell them off or put
them in storage or something. If the robots are really sophisticated, however,
you might be able to program them to do some
of the operations on the new assembly line, and that
would keep them useful, it would lower the cost of production.
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Or for a less extreme example, you introduce a new
model of whatever a thing it is that you're producing.
Anything new will require adjustments in the assembly line process,
and if the changes are big enough, the robots may
not be able to make as big a contribution in
the process. That's something that could happen with the example
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of the PlayStation we were talking about. Yeah, those robots
can put together a PS four and thirty seconds, there's
no guarantee they'll be able to do the same thing
with a PS five, at least not without a major
overhaul of their assembly line system. While the manufacturing facility
can churn out a finished PS four and thirty seconds,
we might not see them work at all with PS five,
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at least not right away. It would all have to
be optimized. So for decades, industrial robots were kept as
separate from human workers as was possible. You wanted to
keep them well away from all the people, or keep
the people well away from all the robots. Often the
robots would operate within cages specifically to limit the possibility
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of a human coming within range. After all, these robots
are large, they're heavy, they're powerful, and many of them
are incapable of sensing stuff in their environment. Uh and
whether or not a human is within their range of motion. Instead,
they're just going through that pre programmed series of motions
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and they're not going to stop unless someone turns it off.
A robot is performing that same series of steps over
and over, and that can mean that if a human
in that area gets near the robot, they could end
up getting injured or worse. And in fact, this has
happened several times times over the course of the last
few decades, and at least in some cases it seems
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as though the robot might have been at fault, meaning
it's not always a case of human carelessness. For example,
an engineer in twenty fifteen died when a robot arm
from one section of the factory floor moved beyond its
operating area and into the neighboring section that the engineer
was working in. This is something that should not have happened.
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The robot arms should not have moved that far into
the neighboring section. The robot arm hit the engineer on
the head, and she later died from her injuries. In
the United States, the government has listed thirty three workplace
deaths due to accidents with industrial robots between the years
nine four and two thousand fourteen. The investigations also found
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that the majority of those tragedies was typically the fault
of human error. There was a person who was one
ring into the operation zone of a robot. That two
thousand fifteen incident was an outlier. Not that any of
this makes the thought of working around industrial robots less
scary or those other accidents any less tragic. They're all
(34:14):
terribly tragic. Moreover, we're seeing more robots that are capable
of roaming a work space. They are no longer anchored
to a specific spot on the floor. In some cases,
they also, unlike the first industrial robots, typically have external sensors.
These not only help the robots navigate their environments, but
(34:34):
also hopefully avoid accidents with human workers. Let's take Amazon's
warehouse robots for example. These robots look like really big
robotic vacuum cleaners. They are designed to roll under shelves,
and the shelves are just, you know, slightly larger than
the dimensions of the robot. And when an order comes in,
(34:56):
a robot from the warehouse rolls over to a shelf.
It holds the respective item on it according to the
inventory system, and the robot goes under the shelf then
lifts the shelf by raising a platter like platform on
the top of the robot. Think of it as like
a little forklift, except it's more like a i don't know,
like a tray that a waiter would use to carry
(35:18):
drinks to a table. But it carries the whole shelf
up and over to the edge of a cage, where
a human operator will take the respective item off the
shelf and scan it and put it into a bin.
And then those bins go to other humans who further
scan those items and then put them into other bins
that ultimately go to the packing department. And if you
(35:40):
watch videos of these robots, it looks like they're doing
a complicated ballet as they maneuver through this warehouse, avoiding
other robots and shelves. As they bring those shelves to humans,
Markings on the warehouse floor tell the robots where they
are with respect to everything else in the warehouse, and
the bots even will position shelves that have items that
(36:04):
are being ordered a lot toward the edges of this
space so that they're easier to get to and move
them over to the human beings. So it's kind of
an interesting dynamic system. It's not like they pick up
the shelf and then bring the shelf immediately right back
to where it started. The shelf can end up in
a different location entirely. In addition, cameras give the robots
(36:26):
the ability to sense any obstacles that might block their path,
allowing the robot to come to a stop and wait
further instructions and report that it has found something unusual
on the warehouse floor. Even so, typically humans are not
allowed to roam the area where the robots pick up shelves.
If something has fallen on the warehouse floor, a designated
(36:49):
troubleshooter gets an alert, and that person must use an
interface to draw the path that they are going to
take from the entrance of the cage all the way
to you the point of trouble. Like let's say that
a product has fallen out of a shelf and has
hit the floor, and a robot has reported it. You
would use a tablet. If you're the troubleshooter, you'd use
(37:10):
a tablet and you would draw, almost like a maze,
the path you would take to get to that particular item,
and you would follow that path out and back. In addition,
you'd wear a radio transmitter that would send a signal
out that the robots could all detect, and that would
alert the robots to the presence of you, the troubleshooter.
(37:32):
That helps prevent a situation in which the robots are
going to collide with you, right, you want to avoid that. Now,
there's a lot of work that goes into designing robots
that can interoperate in a space that's occupied by humans,
and it's a very challenging line of technology because it
takes more than just thinking about how the machines work.
You also have to think about how people work, and moreover,
(37:56):
you have to think about how people change the way
they work when they're in the company of a robot.
It's kind of similar to the concept in quantum theory, right,
the idea that you change a thing you observe just
through the act of observation. Well, you can have a
workspace that humans had only been working in for a while,
(38:18):
and you could say, all right, well, i have observed
how the humans work, and I'm going to build a
robot that does this one task that the humans do,
and I'm just gonna incorporate right into their workspace. But
then you find out that when you do that, the
humans all behave in a new way because there's a
new thing in the environment that you didn't account for,
and now the design of your robot doesn't work as well.
(38:40):
We humans are tricky like that. Moreover, we need to
get to that threat that weavers were worried about more
than a century ago. Is automation going to take our jobs? Now?
There have been a few studies, all using different methodologies,
and some of those studies coming under criticism for the
approaches that were used. But there have been a few
(39:03):
states that suggest we'll see automation continue to impact jobs
in the near future and drastically so over the course
of the long run. The interpretation of those results have
been reported in ways that range from automation is going
to be disruptive, that's on the light end too. Of
all jobs are going to be taken by the robots.
(39:25):
So what's the actual truth. Well, the truth, as it
turns out, is complicated. For one thing, automation rarely takes
over an entire job. What is far more likely to
happen is that automation will take over certain tasks that
are part of a job, or perhaps multiple jobs. So
(39:46):
if a job requires a wide variety of tasks, some
of which may require critical thinking, it's really hard to
design a robot that can do all of that. It's
far more likely that you would automate certain job respond possibilities,
which would mean that those jobs themselves wouldn't go away,
they would just change. The repetitive responsibilities would be offloaded
(40:10):
and you would focus on something else. You might have
to spend more time doing other duties rather than the
routine ones, which isn't necessarily a bad thing. But there
are cases where automation would likely take over an entire job.
For example, truck drivers, you know, in shipping trucks. Much
of the work in autonomous vehicles is really focusing not
(40:34):
necessarily on replacing passenger vehicles so much as commercial vehicles
like shipping trucks. The Bureau of Labor Statistics in the
United States estimated that the age of the average US
truck driver is fifty five and more than of all
truck drivers in the US are mail and that will
(40:56):
present a challenge. See Generally, the pro argue meant for
automation is that while robots and automated systems will eliminate
some jobs, they will create other jobs, presumably better jobs.
And this is true. At the turn of the twentieth century,
of all jobs in the United States were on farms,
(41:19):
so that means four out of ten people in the
US who had a job we're working on a farm. Today,
agriculture and all the related food sectors make up just
eleven of all jobs in the United States. And if
we just limit this to the people who are working
on farms, you know, not all agricultural jobs and food
(41:40):
sector jobs, just the farm jobs. If we do that,
we're talking about only one point three percent of all
US employment. So going from to one point three percent,
that's a drastic change. Now, clearly automation has transformed agriculture.
It allows us to do a lot more while relying
(42:00):
on fewer people, and new jobs did come around, so
we didn't see an unemployment rate reaching levels higher than
pre COVID. The pro automation argument states that new jobs,
which again should ideally be better than existing jobs, isn't.
(42:21):
Less strenuous and less dangerous and more interesting will emerge
as older jobs are phased out. Now, that works fine
on a macro scale when you're taking a really big
picture look at the overall trends, But when you consider
the particulars, like our truck drivers, you start to see
some obstacles. See this year, I turned forty five, so
(42:44):
I'm a lot closer to the average age of a
truck driver in the United States. Then I am to
someone who's just getting into the job market for the
first time, and I can tell you that, even as
a relatively tech savvy guy, I would find it really
challenging to pick up the job skills. I would need
to go into a different line of work, particularly one
(43:08):
where I'm competing against people who already have training and
experience in that field. So imagine having to tell a
group of fifty five year old truck drivers that they're
out of a job. But good news. If you just
start taking classes, you can learn to code and make
less money than you did in your old job. It's
not great, is what I'm saying. Now, that being said,
(43:31):
automation is clearly not going anywhere. It's going to continue
to play a big role in how we get work done,
and in our best case scenarios, it's going to augment
the work that humans do, leading to better, more efficient,
and more cost effective outcomes. It will free us up
to focus on the parts of our jobs that we
find the most fulfilling. We can handle the stuff that
(43:54):
requires flexibility and intuitive thinking, and the machines can handle
the routine and the dangerous. But in a worst case scenario,
we'll see an unprepared population of former workers who are
now out of a job and without the support system
there to help them transition into something new so that
(44:15):
they can continue to contribute to society and earn a living. Now,
this is why you will often hear conversations about automation
get tied into concepts like a guaranteed jobs program. This
is typically where something like a government creates a system
that makes certain every person who wants a job can
(44:36):
get a job. Or you'll hear about guaranteed basic income.
This is a strategy in which tax dollars go to
fund a standard income payout to all citizens so that
they can meet their most basic needs. Now, these are
big ideas, they aren't easy to implement or administer, and
(44:56):
they're not cheap, But it may be that they will
become nest as sary, or some similar strategy will be
needed to make certain that we have a plan to
move toward rather than being caught in a world where
a disproportionate percentage of people can't find gainful employment. Heck,
we're seeing something like that right now due to the
(45:17):
COVID crisis, which is also underlining the importance of automation
in a world where it's not necessarily safe to have
a bunch of human beings all gathered in the same
place at the same time. Are the robots coming for
our jobs? Well, for some of our jobs. Definitely. Many
of those jobs come with some pretty tough consequences for
(45:39):
humans who are working those jobs today. Those jobs may
have high injury rates, the people who work them may
have lower life expectancies, and there are a whole host
of health issues that can come along with certain jobs.
So you could make a strong argument that really this
is for the best because it will help save lives
and reduce the chance for injury or ill. This for
(46:00):
a lot of people, but for other jobs, the robots
aren't likely to take over in the near future. For
a lot of jobs, automated systems not necessarily robots, but
perhaps you know software based AI will augment what humans
are doing. It's important we have conversations about this stuff
and to talk about how to address the consequences of
(46:23):
increased automation. There are ways we can enjoy the benefits
of automation, but only if we think critically about it
and create policies and procedures accordingly. Now I gotta get going.
I hear robo Jonathan is going to host the next
episode of tech Stuff, and I have to train them
on how to make puns and pop culture references. But
(46:46):
if you guys have suggestions for future topics I could
tackle here on tech Stuff, please reach out to me
and let me know what those are. You can reach
out on Twitter. The handle for the show is text
stuff hs W and I'll all too again really soon. Y.
(47:07):
Text Stuff is an i heart Radio production. For more
podcasts from I heart Radio, visit the i heart Radio app,
Apple Podcasts, or wherever you listen to your favorite shows.
Welcome to text Stuff, a production from I Heart Radio.
Hey there, and welcome to tech Stuff. I am your host,
Jonathan Strickland. I'm an executive producer with I Heart Radio
and I love all things tech. You know, guys, I
read a lot of tech news and sometimes that ends
(00:26):
up inspiring me to do an episode of text Stuff.
That happened to me recently when I read this headline
off of the website text Spot. Sony Factory assembles PS
four in thirty seconds, only four humans involved in the process.
A p S four, in case you're not aware, is
(00:47):
a PlayStation for video game consoles. So this factory can
build a video game console from parts in half a
minute and only four human beings touched the ding day
thing in the process. Those four humans, by the way,
are involved in the beginning and the end of the process.
Two of them load motherboards onto the assembly line, and
(01:10):
a motherboard is the primary circuit board for a computer system,
and the other two human beings are at the end
of the assembly line and their job is to package
the completed consoles. All the actual assembly work is done
by robots. Now, you may be experiencing a couple of
different responses to this information I know I did. One
(01:32):
of those was a wow, that's seriously impressive. The PS four,
like many computer systems, has a lot of components, many
of which attached to one another by wire or cable.
So these robots have to be able to take these
flexible components and to join them in their proper anchor
points with the appropriate amount of pressure and precision to
(01:54):
make a good connection. Now, if any of you out
there have ever built your own PC, you know that
plugging cables in can get a little tricky depending on
the layout of the motherboard and the various components. And
if you're someone like me, you're likely putting stuff together
only to realize that maybe you should have done some
of that before you mounted them in a computer case,
(02:15):
because now you just don't have the space to work
in properly. So it's pretty darn impressive that robots can
do this consistently and correctly at that level of speed.
Another response I had was it's kind of scary. I mean,
typically you would have dozens of people employed on the
(02:35):
assembly line to do this sort of work, but in
this factory it's been stripped down to thirty two robots
and four human beings. The article in tech spot points
out that twenty six of those thirty two robots are
just attaching flexible components together inside the console. Now, I
have no idea how much these robots cost, but I wait,
(03:00):
you're that they are expensive enough to equal the salary
of a standard human employee on the assembly line. However,
you don't pay robots. You do have to spend money
to maintain and repair them, but assuming whatever you're making
is going to be around for a little while, they'll
pay for themselves because eventually you'll get to a point
(03:20):
where the salaries you'd be paying for humans would be
more than the purchase and maintenance cost of the robots.
And the increase in efficiency means you can produce a
whole lot more stuff in a given amount of time
then you would with a human centric assembly line, so
you'll have more product to sell in a shorter amount
(03:42):
of time. When you start crunching numbers, you discover your
robotic assembly line can make more stuff at a lower
cost over a given period of time, like you know,
over a couple of years, than what you would accomplish
with human beings on that assembly line. So you don't
have to worry about the robots taking a vacation. They
don't take sick time, they don't even take the night off.
(04:04):
They can work around the clock. They don't need health insurance,
though I would guess that most companies ensure the heck
out of these things just in case one breaks down.
But from a financial point of view, they make sense
if you're building stuff at a large enough scale, stuff
like video game consoles for the PlayStation four. It's a
no brainer because that console has sold around one hundred
(04:28):
ten million units so far. That's a number large enough
that I can't even imagine what it would look like
if you had all those consoles together in one place.
So if there's enough demand for you to sell a
hundred ten million whatever it is you want to sell,
you need to have a way to make those as
(04:49):
efficiently as possible, and that will help maximize your profits.
And the more efficient the process, the more competitively you
can price your product and still make a profit. But
the idea of robots performing jobs far more effectively, consistently,
and efficiently than humans raises a lot of questions, and
these are not new questions either, but they are questions
(05:12):
like if more factories rely on robots for production, particularly
if those robots can be programmed to produce new products
once older ones go obsolete. What happens to the job market,
What happens to the millions of people who work in
manufacturing on assembly lines? Where will they go? What will
this do to economies around the world. Lots of people
(05:35):
have tried to answer these questions, sometimes giving drastically different answers.
And we're going to take a look at the history
and evolution of industrial robots in this episode and explore
the ramifications of automated manufacturing. And this is where I
dive into history. I've talked about the history of robots before,
(05:56):
so I'll try to restrict my focus to an industrial robots.
And before I get into that, let's just address the
fact that the use of machinery to increase efficiency has
been a controversial subject since long before there ever was
such a thing as a robot. Generally speaking, machines are
meant to make work easier, or in some cases, make
(06:19):
the work possible. Just to begin with, they are labor
saving devices, requiring humans to put forth less effort to
get the same or better results. This applies to the
simplest of machines. I mean stuff like levers or pulleys
or an inclined plane, and it applies to very complex
(06:39):
machines as well. Before the Industrial Revolution, most stuff like textiles,
was made by crafts people out of their own homes.
This was literally the cottage industry. Tradespeople would travel and
become the lifeline for the cottage industry, supplying raw materials,
buying finished products, and selling those products off at a
(07:02):
profit elsewhere. Many trades people built a good deal of
wealth working this way, and they had the means to
look at alternatives to this decentralized cottage industry approach. An
idea began to form. If you brought together crafts people
to a centralized location, and if you simplified the process
(07:24):
of production, you can make way more stuff, which in
turn means you could sell way more stuff, which in
turn means you can make way more money, and money
makes the world go round. This thought process helped fuel
a similar line of thinking. If you could design machines
(07:45):
that could do a lot of work that typically felt
a skilled crafts people, you wouldn't need the crafts people
at all. You could train anyone, even if that person
had no experience with the process just to work the machine.
And while it might take years of dedication to go
through the process of being an apprentice to learn a
(08:05):
trade well enough so that you can actually make a
living at it with a machine, you can skip right
over that. As long as the machines in product was
good enough. It didn't have to be better than the
stuff crafts people were making. It just had to be
good enough and cheap enough and fast enough to produce.
Then you could sell the finished product at a lower
(08:28):
cost than what craftspeople would charge because not as much
time and effort went into making the thing. Now, I
guess it's clunky to talk about this while using an example,
so let's go with a poster child for the Industrial Revolution. Weaving.
The weaving trade is an ancient one, and it requires
a good deal of skill to do it well by hand.
(08:50):
In the late seventeen hundreds, a man named Edmund Cartwright
patented a loom powered by a water wheel. The looms
operation was such that a person who had no training
and weaving could operate the machine and produce finished textiles.
Cartwright's design would be built upon by other inventors who
had turned to steam power and other means to operate
(09:13):
the power loom. Many cottage industry weavers found themselves out
of work. They could potentially up to work in the
textile factories, as those were popping up all over the place,
particularly in England, but the wages were low. As you
can imagine, this didn't sit well with the weavers. There
(09:35):
were protests, including some that incorporated violence and destruction. Ultimately,
the factory process one out and along with it some
really awful working conditions followed, including stuff like child labor
and ridiculously low wages and dangerous working conditions. This led
(09:55):
to more protests, including the type that would give us
the word sabotage. And let's get a quick side note
on that one, as it is the source of a
little mythology or misinformation. See The apocryphal story goes that
the word sabotage comes from the word sabot which describes
(10:16):
the wooden shoes worn by laborers, mainly Dutch laborers, but
also laborers in France. And according to the story, these
laborers wore those shoes and use them to great effect.
In an effort to protest the conditions and factories, they
would toss their wooden shoes into the machinery to break
(10:37):
the various gears and literally grind production to a halt,
as it were. But the story, while compelling, isn't really
the truth. Sabotage does stem from the words sabo, but
in French there is a verb sabotet. This verb means
to make a loud noise with wooden shoes. Now isn't
(11:00):
it great that there's a verb for that? And it
makes sense wooden shoes would make a great deal of
racket as people would walk around. Heck, if a if
a toddler wore wooden shoes, I think it would probably
sound as though the world were shaking apart. I don't
know how toddlers managed to sound like they weigh a
hundred pounds, but they do it. And if you have
(11:22):
a toddler, you know what I'm talking about. And in
the culture of France, the idea of a clumsy slow
worker was often linked to someone who wore wooden shoes
because they're awkward to wear anyway. The reason sabote led
to sabotage is because factory workers who were protesting their
(11:43):
work conditions and wages would purposefully work more slowly and
less efficiently. In order to affect the overall output of
a factory. It was related to a similar strategy that
British laborers employed, and their version was called kakani. It
was a saying from Scotland which essentially means don't do
so much man now. I would argue this also feeds
(12:06):
into a strategy that we see to this very day
in certain government offices, where the ideas there's no need
to do too much too quickly, as it doesn't result
in increased compensation, and it also sets a really high
bar of expectations, So why not just take it easy
and I don't have a coffee break now. In the
early twentieth century, people began to use the word sabotage
(12:28):
to really refer to a purposeful approach to undermining the
output of factories, and it had nothing to do with
tossing wooden shoes into machinery, though it did also pertain
to instances in which workers purposefully damaged equipment and tried
to slow down the production that way. While this isn't
(12:49):
directly tied to the idea that machines themselves are displacing workers,
it is related to the effect of moving towards a
manufacturing based economy and how that allow for the exploitation
of workers. The machines themselves aren't really at fault, but
they facilitate the system of operations that leads to exploitation.
(13:11):
Now that's something that will be a theme in this episode,
and we can't ignore the social aspect of what's going
on here, or else we missed the whole point. But
let's skip ahead. I've spoken about this before, but we
get the word robot from a check author named Carrol Copeck.
He wrote a play called Rossom's Universal Robots or Are
(13:33):
You Are? In nineteen twenty. Copeck took an older word robota,
which means forced labor in Europe. This concept was tied
to that of the old system of serfdom, in which
people would do work on behalf of a landowner. In return,
those people would be allowed to live on part of
(13:55):
that landowner's land. And Are You Are, factory owners devise
a way to build laborers from raw materials. Now, in
the play, they are indistinguishable from humans other than they
have no inner desires. But in the course of the play,
these laborers eventually take over all the jobs that humans
(14:17):
previously held, and humans themselves become a threatened species as
these laborers begin to understand the power that they hold
by occupying all the positions of employment, including as soldiers
in the military. And so with the introduction of the
concept of robot we actually get the very first robotic
uprising all the way back in See I told you
(14:41):
it was an old idea. It's important to remember that
in the play, the robots are nearly identical to humans.
They they aren't mechanical the way our robots of today are,
but the idea of creating machines that can do work
without a will of their own is a part of
row botics in general and industrial robotics in particular. When
(15:03):
we come back, we'll talk about the earliest industrial robots
and what they did, but first let's take a quick break.
It's interesting to me that the tech world adopted the
term robot when we think about the origins of that word.
(15:26):
In compex work, robots were sentient slaves. They could perform
the work humans would otherwise do, but they lack the
emotions that humans have, and the whole idea is that
these devices could do our work for us without question
or protest. They would in theory endure conditions that people
(15:48):
wouldn't or couldn't, but in the play, they ultimately lead
to the destruction of the human race and potentially they
become the new dominant species on the planet. Now, I
say potentially because part of the play's plot involves the
destruction of the formula that scientists use to produce the
robots in the first place. That is an important plot point.
(16:10):
The robots are not sure how to make more robots,
so they might just die out. Now, it seems to
me as though that's a pretty emotionally charged term to
adopt for an entire discipline of technology, right, robots, especially
if you are actually aware of that play, and by
the way, I recommend people read it. It's a good play.
(16:33):
But then a lot of people are not aware of
the origins of the word, or at least not beyond
knowing that it came from a play in the nineteen twenties.
So I guess for them it's just, you know, a word.
A robot by any other name would smell as sweet
as it were. And we've definitely seen the themes of
are you are serving as an undercurrent for stuff that's
(16:54):
happening in robotics in general. But let's move ahead. In
nineteen fifty four or an engineer named George Daval designed
an industrial robot. He was nine years old when Copic
coined the term robot. He called his design the Programmed
Article Transferred Device, for which he received a U S
(17:16):
patent in nineteen sixty one. This machine was a robotic arm,
and it was capable of picking up something and then
transferring it a short distance away just within reach of
the arm. The arm itself couldn't move, it was anchored
in place. It could also follow. In fact, this is
the important part. It would follow a pre program series
(17:37):
of instructions to do this. Daval's argument for his device
was that up to this point, mechanical handling of objects
fell into two broad categories. Either stuff got moved by humans,
typically operating a powerful machine like a crane or a forklift,
or stuff got moved by a device that operated under
(17:58):
cam control. Now, manual control is self explanatory, so let's
talk about cams. A cam is a rotating component in machinery. Typically,
a cam has some variation in its surface. So let's
start with a wheel. Just imagine a wheel that is
spinning on an axle. Well, You wouldn't typically have a
(18:19):
perfectly smooth wheel as a cam. Part of that surface
might be flat, or it might have dips in it,
and when the cam rotates, these variations apply force to
some other mechanical component that is held against the cam,
and it causes that mechanical component to move in specific ways.
(18:40):
A cam operating system can work on its own, but
it will always repeat the exact same motions. As long
as everything is working, it'll just repeat those steps. Once
the cams complete a full systematic rotation, you can't really
adapt it to do anything else. The movements depend entirely
on the cams themselves, so if you wanted it to
(19:01):
do something else, you would first have to swap out
the cams uh and even then you would be under
whatever the limitations of the device was itself, like, it
wouldn't have full range of motion. Moreover, this level of
specialization also means that it's typically really expensive to rely
upon cam based systems, so it was really only useful
(19:23):
if the application had to do with mass manufacturing or
else you're looking at economic loss. The cost of the
system was just too much, so Daval was proposing a
machine that could be programmed to do operations, and this
would let a programmer create different processes using the same machine,
or you could get a whole bunch of the same
(19:43):
basic machine and program each one to do a particular job. Meanwhile,
you'd free people up to work on other stuff in
the manufacturing process, and you could take the most dangerous
stuff and give it to the robots. Now, the story
goes that Daval was at a party in nineteen fifty
s X and he got into a conversation with a
man named Joseph Engelberger. Joseph was a scientist and an entrepreneur,
(20:08):
and when the subject turned to Duvall's programmed article transferred device,
as well as the work of a science fiction author
known as Isaac Asimov, you know, the father of robotics.
He famously incorporated a concept of the laws of robotics
in his works. We won't really go into that in
this episode, but the laws of robotics still play a
(20:28):
big part in the discipline of robotics in general, but
it's kind of outside the focus of this episode. Engelberger
used his connections to get funding for duvol to create
a more advanced version of the programmed article transfer machine,
and it would be a robotic arm capable of making repeated,
precise movements while holding very heavy objects. They called it
(20:51):
the Unimate you n I M A T E, and
the first prototype, Unimate zero zero one, would go to
General Motors to work on a die casting assembly line. Now,
according to the company robot Works, that's a w O
r X. This robot cost around sixty five thousand dollars
(21:13):
to produce, and Ingelburgers sold it off at a tremendous loss.
General Motors only paid eighteen thousand dollars for sixty five
thousand dollar machine. But Ingelberger really wanted to establish that
robotics were a way to perform repetitive, dangerous functions at
a lower risk to humans. Welding die cast components on
(21:33):
auto bodies was a great first application of industrial robots
for a few reasons. Die Casting is a process involving
molten metal. You take that molten metal and you force
it into steel molds, and these are water called dies.
The molten metal cools in the exact shape of the mold.
(21:53):
So this is a way to make or cast a
bunch of identical parts out of metal and get consisted
stent quality out of it rather than you know, forging
each piece and then fitting them together. A diet can
have complex shapes in it, such as external threads, which
means you don't have to make a pipe, for example,
(22:14):
and then do a secondary process on that pipe to
get the result you want. So you wouldn't have to
carve those threads into a otherwise smooth pipe. You could
just cast the pipe with the threads incorporated on it already.
But welding die cast parts onto auto bodies is hard work.
The components are really heavy, so you're at risk of
(22:37):
immediate injury if something goes wrong, like let's say you
drop a weighty component on your foot, or you might
develop a repetitive stress injury after going through the same
welding motions over and over again. In addition, the fumes
given off while welding where sometimes toxic still are so
it's not great to have people exposed to them for
(22:58):
very long. So a robot was a great substitute for
a person. The robot could handle much greater weight than
people could. The robot didn't breathe, so there was no
respiratory issue there, and it didn't get tired. I mean
it would wear down over time, but you could repair
it in fairly short order. The Unimate worked with computer
controlled hydraulic systems. Hydraulic system uses a liquid that's under
(23:23):
pressure in order to do work like pushing against a
piston to power and actuator of some sort like lift
a platform. The Unimate zero zero one weighed twenty seven
hundred pounds or about one thousand two ms, and it
could work twenty four hours a day, placing components with
a precision of within one fifty th of an inch. Now,
(23:47):
I'm not going to do the conversion on that, because
I think it's sufficient to say that it was just
really precise. According to a charmingly dated newsreel from Britain,
complete with swinging sixties music that sounded like it came
straight off an Austin Powers movie, the robot could operate
for five hours without the need for a human to
check in on it. Engelberger, a savvy businessman and promoter,
(24:11):
would arrange for Unimate to show what it could do
at trade shows and on TV appearances, including one on
The Tonight Show with Johnny Carson. If you don't know
who that is, ask your parents, and if they don't know,
ask your grandparents. By nineteen sixty nine, General Motors had
(24:32):
jumped on board the robot train, as it were. They
rebuilt a manufacturing plant in Lordstown, Ohio, and they installed
unimate robots to perform spot welding on car bodies, and
the results spoke for themselves. The plant was capable of
producing one hundred ten cars per hour, which was more
(24:53):
than double the speed that the plant could manage before
the installation of the robots. The business case for the
robots seemed clear. After a hefty upfront cost, you could
produce way more stuff per day, and as long as
the demand for that stuff is high enough, it could
mean greater revenue. You could also bring the cost of
(25:13):
production for an individual unit down. Then you could pass
savings on to customers and get really competitive with your pricing,
or you could just keep everything price the same and
try to increase your profit margin. The key to all
this was that you had to be sure the thing
you were producing would bring in enough money to offset
the cost of automation, so it would not make sense
(25:35):
to spend millions of dollars building out a factory staffed
with robots if you were making something that had a
very small market to begin with, Yes, you'd be able
to produce way more watching My Call It's than you
could before. But if the demand for watch my Call
It's is really modest, that doesn't do you any good.
In fact, you might end up flooding the market and
(25:57):
devaluing your product. So well, robots were taking on jobs
that were previously held by humans, there was no real
danger of a massive upheaval where everything would be automated.
The limitations in the technology were just too great and
the cost was too high for most companies to go
that route. And this also became the starting point for
something that would become really important. That the main goal
(26:21):
of developing industrial robots wasn't to displace humans. It was
meant to offload duties that were dull, dirty, or dangerous.
You'll often hear those terms being used with robotics. If
it is a job that carries with it a significant
risk to the person performing it, or a job so
demanding that you can only expect a person to stick
(26:42):
with it for a short while before they need to
do something else, then building a robot to do that job,
or at least that list of tasks makes sense. The
robot is just a thing. It can endure conditions that
humans can't, and it doesn't get sick, and it doesn't
get hurt. If something breaks down, you can typically repair
it pretty quickly. We humans don't have that luxury. Now,
(27:06):
I'm not going to go and run down a full
history of all industrial robots because that would mostly involve
me talking about model numbers with slight differences like the
number of axes of movement or points of articulation for
one robot versus another, and that's not really interesting. But
I do want to hit a couple of highlights. One
is that in NINETI, the A S E A I
(27:30):
RB robot would be the first fully electrically driven robot.
It also used Intel's first chip set as processors. Now,
this was not a super strong robot because those electrically
driven limbs just can't pack the same punch as a
hydraulic system, which typically moves much more slowly but can
(27:52):
handle much heavier payloads. So this particular robot could only
lift weights up to around their teen pounds or six kgrams.
But the move toward processors and electrically driven components marked
a big technological step, even if the arms physical capabilities
were much less impressive than a hydraulic system. By the
(28:15):
end of the nineteen seventies, Japan was getting into the
robotics game with arc welding robots for assembly lines, and
then it was off to the robotic races, with the
eighties seeing a surge in advances with industrial robots. Soon,
massive manufacturing facilities were installing robots to take over elements
(28:37):
of the assembly line process, particularly in that dirty, dull,
and dangerous category. The robots became more sophisticated, which also
added to their value. When we come back, I'll talk
more about why that's important, but first let's take another
quick break. By the mid nine nineties, robotics companies were
(29:05):
making machines that could coordinate and synchronize the movements of
more than one robot at the same time, allowing for
more complex manufacturing processes. By the early two thousand's, there
were systems that could synchronize the actions of up to
four robots at a time, further adding to the overall
system flexibility. Now I mentioned earlier that a programmable robot
(29:27):
is more versatile than something like a cam operated system. Well,
more sophisticated robots with more axes of motion and more.
Points of articulation have the potential to do lots of
different types of jobs, and this is of critical importance.
If the robot is too limited, if you can only
do a small range of motions, you can't necessarily repurpose
(29:53):
it for new processes. And as markets change, you may
find yourself needing to be flexible when it comes to
the stuff you're manufacturing. So let's use an extreme hypothetical
example that would probably never happen. So let's say that
you run an auto manufacturing facility, but then there's a
massive market change and it drastically affects the demand for
(30:16):
your cars. There's just not enough demand to support the production.
So rather than just you know, closing up shop and
calling it a day, your business decides to do an
amazing pivot and you begin to convert your manufacturing facility
over to I don't know, home appliances. Now, again, this
(30:36):
is an extreme hypothetical example, but let's just go with it. Okay,
So here we go. If the robots and your assembly
line are powerful but limited in movement and function, you
may find it impossible to adapt them to your new
line of business, which would mean you need to either
invest in new robots, or you'd have to hire human
(30:57):
workers to put together your appliances, and it would also
mean that your old robots would be a sunk cost.
You would need to either sell them off or put
them in storage or something. If the robots are really sophisticated, however,
you might be able to program them to do some
of the operations on the new assembly line, and that
would keep them useful, it would lower the cost of production.
(31:20):
Or for a less extreme example, you introduce a new
model of whatever a thing it is that you're producing.
Anything new will require adjustments in the assembly line process,
and if the changes are big enough, the robots may
not be able to make as big a contribution in
the process. That's something that could happen with the example
(31:41):
of the PlayStation we were talking about. Yeah, those robots
can put together a PS four and thirty seconds, there's
no guarantee they'll be able to do the same thing
with a PS five, at least not without a major
overhaul of their assembly line system. While the manufacturing facility
can churn out a finished PS four and thirty seconds,
we might not see them work at all with PS five,
(32:02):
at least not right away. It would all have to
be optimized. So for decades, industrial robots were kept as
separate from human workers as was possible. You wanted to
keep them well away from all the people, or keep
the people well away from all the robots. Often the
robots would operate within cages specifically to limit the possibility
(32:24):
of a human coming within range. After all, these robots
are large, they're heavy, they're powerful, and many of them
are incapable of sensing stuff in their environment. Uh and
whether or not a human is within their range of motion. Instead,
they're just going through that pre programmed series of motions
(32:44):
and they're not going to stop unless someone turns it off.
A robot is performing that same series of steps over
and over, and that can mean that if a human
in that area gets near the robot, they could end
up getting injured or worse. And in fact, this has
happened several times times over the course of the last
few decades, and at least in some cases it seems
(33:04):
as though the robot might have been at fault, meaning
it's not always a case of human carelessness. For example,
an engineer in twenty fifteen died when a robot arm
from one section of the factory floor moved beyond its
operating area and into the neighboring section that the engineer
was working in. This is something that should not have happened.
(33:27):
The robot arms should not have moved that far into
the neighboring section. The robot arm hit the engineer on
the head, and she later died from her injuries. In
the United States, the government has listed thirty three workplace
deaths due to accidents with industrial robots between the years
nine four and two thousand fourteen. The investigations also found
(33:51):
that the majority of those tragedies was typically the fault
of human error. There was a person who was one
ring into the operation zone of a robot. That two
thousand fifteen incident was an outlier. Not that any of
this makes the thought of working around industrial robots less
scary or those other accidents any less tragic. They're all
(34:14):
terribly tragic. Moreover, we're seeing more robots that are capable
of roaming a work space. They are no longer anchored
to a specific spot on the floor. In some cases,
they also, unlike the first industrial robots, typically have external sensors.
These not only help the robots navigate their environments, but
(34:34):
also hopefully avoid accidents with human workers. Let's take Amazon's
warehouse robots for example. These robots look like really big
robotic vacuum cleaners. They are designed to roll under shelves,
and the shelves are just, you know, slightly larger than
the dimensions of the robot. And when an order comes in,
(34:56):
a robot from the warehouse rolls over to a shelf.
It holds the respective item on it according to the
inventory system, and the robot goes under the shelf then
lifts the shelf by raising a platter like platform on
the top of the robot. Think of it as like
a little forklift, except it's more like a i don't know,
like a tray that a waiter would use to carry
(35:18):
drinks to a table. But it carries the whole shelf
up and over to the edge of a cage, where
a human operator will take the respective item off the
shelf and scan it and put it into a bin.
And then those bins go to other humans who further
scan those items and then put them into other bins
that ultimately go to the packing department. And if you
(35:40):
watch videos of these robots, it looks like they're doing
a complicated ballet as they maneuver through this warehouse, avoiding
other robots and shelves. As they bring those shelves to humans,
Markings on the warehouse floor tell the robots where they
are with respect to everything else in the warehouse, and
the bots even will position shelves that have items that
(36:04):
are being ordered a lot toward the edges of this
space so that they're easier to get to and move
them over to the human beings. So it's kind of
an interesting dynamic system. It's not like they pick up
the shelf and then bring the shelf immediately right back
to where it started. The shelf can end up in
a different location entirely. In addition, cameras give the robots
(36:26):
the ability to sense any obstacles that might block their path,
allowing the robot to come to a stop and wait
further instructions and report that it has found something unusual
on the warehouse floor. Even so, typically humans are not
allowed to roam the area where the robots pick up shelves.
If something has fallen on the warehouse floor, a designated
(36:49):
troubleshooter gets an alert, and that person must use an
interface to draw the path that they are going to
take from the entrance of the cage all the way
to you the point of trouble. Like let's say that
a product has fallen out of a shelf and has
hit the floor, and a robot has reported it. You
would use a tablet. If you're the troubleshooter, you'd use
(37:10):
a tablet and you would draw, almost like a maze,
the path you would take to get to that particular item,
and you would follow that path out and back. In addition,
you'd wear a radio transmitter that would send a signal
out that the robots could all detect, and that would
alert the robots to the presence of you, the troubleshooter.
(37:32):
That helps prevent a situation in which the robots are
going to collide with you, right, you want to avoid that. Now,
there's a lot of work that goes into designing robots
that can interoperate in a space that's occupied by humans,
and it's a very challenging line of technology because it
takes more than just thinking about how the machines work.
You also have to think about how people work, and moreover,
(37:56):
you have to think about how people change the way
they work when they're in the company of a robot.
It's kind of similar to the concept in quantum theory, right,
the idea that you change a thing you observe just
through the act of observation. Well, you can have a
workspace that humans had only been working in for a while,
(38:18):
and you could say, all right, well, i have observed
how the humans work, and I'm going to build a
robot that does this one task that the humans do,
and I'm just gonna incorporate right into their workspace. But
then you find out that when you do that, the
humans all behave in a new way because there's a
new thing in the environment that you didn't account for,
and now the design of your robot doesn't work as well.
(38:40):
We humans are tricky like that. Moreover, we need to
get to that threat that weavers were worried about more
than a century ago. Is automation going to take our jobs? Now?
There have been a few studies, all using different methodologies,
and some of those studies coming under criticism for the
approaches that were used. But there have been a few
(39:03):
states that suggest we'll see automation continue to impact jobs
in the near future and drastically so over the course
of the long run. The interpretation of those results have
been reported in ways that range from automation is going
to be disruptive, that's on the light end too. Of
all jobs are going to be taken by the robots.
(39:25):
So what's the actual truth. Well, the truth, as it
turns out, is complicated. For one thing, automation rarely takes
over an entire job. What is far more likely to
happen is that automation will take over certain tasks that
are part of a job, or perhaps multiple jobs. So
(39:46):
if a job requires a wide variety of tasks, some
of which may require critical thinking, it's really hard to
design a robot that can do all of that. It's
far more likely that you would automate certain job respond possibilities,
which would mean that those jobs themselves wouldn't go away,
they would just change. The repetitive responsibilities would be offloaded
(40:10):
and you would focus on something else. You might have
to spend more time doing other duties rather than the
routine ones, which isn't necessarily a bad thing. But there
are cases where automation would likely take over an entire job.
For example, truck drivers, you know, in shipping trucks. Much
of the work in autonomous vehicles is really focusing not
(40:34):
necessarily on replacing passenger vehicles so much as commercial vehicles
like shipping trucks. The Bureau of Labor Statistics in the
United States estimated that the age of the average US
truck driver is fifty five and more than of all
truck drivers in the US are mail and that will
(40:56):
present a challenge. See Generally, the pro argue meant for
automation is that while robots and automated systems will eliminate
some jobs, they will create other jobs, presumably better jobs.
And this is true. At the turn of the twentieth century,
of all jobs in the United States were on farms,
(41:19):
so that means four out of ten people in the
US who had a job we're working on a farm. Today,
agriculture and all the related food sectors make up just
eleven of all jobs in the United States. And if
we just limit this to the people who are working
on farms, you know, not all agricultural jobs and food
(41:40):
sector jobs, just the farm jobs. If we do that,
we're talking about only one point three percent of all
US employment. So going from to one point three percent,
that's a drastic change. Now, clearly automation has transformed agriculture.
It allows us to do a lot more while relying
(42:00):
on fewer people, and new jobs did come around, so
we didn't see an unemployment rate reaching levels higher than
pre COVID. The pro automation argument states that new jobs,
which again should ideally be better than existing jobs, isn't.
(42:21):
Less strenuous and less dangerous and more interesting will emerge
as older jobs are phased out. Now, that works fine
on a macro scale when you're taking a really big
picture look at the overall trends, But when you consider
the particulars, like our truck drivers, you start to see
some obstacles. See this year, I turned forty five, so
(42:44):
I'm a lot closer to the average age of a
truck driver in the United States. Then I am to
someone who's just getting into the job market for the
first time, and I can tell you that, even as
a relatively tech savvy guy, I would find it really
challenging to pick up the job skills. I would need
to go into a different line of work, particularly one
(43:08):
where I'm competing against people who already have training and
experience in that field. So imagine having to tell a
group of fifty five year old truck drivers that they're
out of a job. But good news. If you just
start taking classes, you can learn to code and make
less money than you did in your old job. It's
not great, is what I'm saying. Now, that being said,
(43:31):
automation is clearly not going anywhere. It's going to continue
to play a big role in how we get work done,
and in our best case scenarios, it's going to augment
the work that humans do, leading to better, more efficient,
and more cost effective outcomes. It will free us up
to focus on the parts of our jobs that we
find the most fulfilling. We can handle the stuff that
(43:54):
requires flexibility and intuitive thinking, and the machines can handle
the routine and the dangerous. But in a worst case scenario,
we'll see an unprepared population of former workers who are
now out of a job and without the support system
there to help them transition into something new so that
(44:15):
they can continue to contribute to society and earn a living. Now,
this is why you will often hear conversations about automation
get tied into concepts like a guaranteed jobs program. This
is typically where something like a government creates a system
that makes certain every person who wants a job can
(44:36):
get a job. Or you'll hear about guaranteed basic income.
This is a strategy in which tax dollars go to
fund a standard income payout to all citizens so that
they can meet their most basic needs. Now, these are
big ideas, they aren't easy to implement or administer, and
(44:56):
they're not cheap, But it may be that they will
become nest as sary, or some similar strategy will be
needed to make certain that we have a plan to
move toward rather than being caught in a world where
a disproportionate percentage of people can't find gainful employment. Heck,
we're seeing something like that right now due to the
(45:17):
COVID crisis, which is also underlining the importance of automation
in a world where it's not necessarily safe to have
a bunch of human beings all gathered in the same
place at the same time. Are the robots coming for
our jobs? Well, for some of our jobs. Definitely. Many
of those jobs come with some pretty tough consequences for
(45:39):
humans who are working those jobs today. Those jobs may
have high injury rates, the people who work them may
have lower life expectancies, and there are a whole host
of health issues that can come along with certain jobs.
So you could make a strong argument that really this
is for the best because it will help save lives
and reduce the chance for injury or ill. This for
(46:00):
a lot of people, but for other jobs, the robots
aren't likely to take over in the near future. For
a lot of jobs, automated systems not necessarily robots, but
perhaps you know software based AI will augment what humans
are doing. It's important we have conversations about this stuff
and to talk about how to address the consequences of
(46:23):
increased automation. There are ways we can enjoy the benefits
of automation, but only if we think critically about it
and create policies and procedures accordingly. Now I gotta get going.
I hear robo Jonathan is going to host the next
episode of tech Stuff, and I have to train them
on how to make puns and pop culture references. But
(46:46):
if you guys have suggestions for future topics I could
tackle here on tech Stuff, please reach out to me
and let me know what those are. You can reach
out on Twitter. The handle for the show is text
stuff hs W and I'll all too again really soon. Y.
(47:07):
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