Speaker 1: Dario Emode runs anthropic and if he recently warned that
Speaker 1: AI could wipe out half of all entry level white
Speaker 1: collar jobs within five years, he even reckons it could
Speaker 1: push unemployment to ten percent, maybe even twenty percent. And
Speaker 1: yet today I want to talk about bootmakers in Victorian England.
Speaker 1: Hey bear with me. You see, I reckon there's useful
Speaker 1: lessons buried in our economic history that might help each
Speaker 1: of us think a bit more clearly about our AI
Speaker 1: fueled future. I'm just back from a conference where I
Speaker 1: saw a terrific news paper by Hilly River Pond, a
Speaker 1: brilliant young economic historian, And what I want to do
Speaker 1: today is share the story she told. Say. Here's how
Speaker 1: we're going to do it. Five chapters. First, we're going
Speaker 1: to go back to Victorian England. Join me on a journey.
Speaker 1: We're going to watch a new technology hit in the
Speaker 1: established industry. Second, we're going to look at how better
Speaker 1: technology meant cheaper boots, and cheaper boots meant more boots. Third,
Speaker 1: I'll show you how that translated into more boots keeping
Speaker 1: the same number of jobs. That sounds calm, but beneath
Speaker 1: the surface, the tasks that people were doing were completely remade. Fourth,
Speaker 1: we're going to investigate how the geography of this new
Speaker 1: work shifted. And finally, we're going to ask whether any
Speaker 1: of this tells us anything useful about AI. Okay, let's
Speaker 1: get into it. Let's begin back in the middle of
Speaker 1: the nineteenth century. Come back in time with me, and
Speaker 1: if you want a literary reference for the mood, think
Speaker 1: Charles Dickens, not Downton Abbey. Boot making was huge, had
Speaker 1: about two hundred and twenty thousand workers in eighteen fifty one.
Speaker 1: It was the fifth largest occupation in England, and roughly
Speaker 1: one in thirty Englishmen made boots. Back then, boot making
Speaker 1: was craft work. A bootmaker cut the leather shape, that
Speaker 1: stitched the upper together, attached the sole, and finish the product.
Speaker 1: This was skilled, hands on work. A boot maker might
Speaker 1: know the whole trade, from leather to lacers. Then that
Speaker 1: world got hit by a radical new labor saving technology.
Speaker 1: The breakthrough was the adaptation of the sewing machine to
Speaker 1: heavy boot leather, and that occurred in the late eighteen fifties.
Speaker 1: A machine could stitch the leather up together much faster
Speaker 1: than the person could by hand. Workers. Using this new technology,
Speaker 1: they could produce four times as much as workers doing
Speaker 1: the same task the old way. And here's the think
Speaker 1: that first breakthrough, it didn't stay contained to that one
Speaker 1: stage of production. Once the stitching got much faster, the
Speaker 1: rest of the process became the bottleneck. So there was
Speaker 1: pressure to split up the cutting and the sole attaching,
Speaker 1: the finishing and the packing the whole production line, and
Speaker 1: the old draft systems started giving way to something more mechanized,
Speaker 1: more factory based. For the boot makers, this was not
Speaker 1: an abstract future of work seminar, and believe me, I
Speaker 1: sat through that seminar. This was their trade, their skills,
Speaker 1: their way of life, their livelihoods. So they fought back.
Speaker 1: In the main boot making districts, thousands of workers went
Speaker 1: on strike for over a year trying to stop this
Speaker 1: technology from remaking their industry. So when new technology arrived,
Speaker 1: it made a central task dramatically faster, and an entire
Speaker 1: industry finds itself having to work out what to do next. Now,
Speaker 1: I don't want to jump straight to what happened in
Speaker 1: the labor market. I want us to pause first and
Speaker 1: sip with the market for boots first. If a new
Speaker 1: technology lets each work and make more boots per hour,
Speaker 1: then the cost of making boots falls. If the cost
Speaker 1: of making boots falls, then boots tend to get cheaper.
Speaker 1: And when boots get cheap at more people buy boots.
Speaker 1: That last step it really matters because if you listen closely,
Speaker 1: a lot of the discussions of automation they skip from
Speaker 1: this saves labor straight to it. Therefore, there'll be fewer
Speaker 1: jobs that leaves out the work done by markets and prices.
Speaker 1: You see, prices adjust and when they do, they stimulate
Speaker 1: new demand. This is the point at which I want
Speaker 1: to introduce you to a charming character named William Stanley
Speaker 1: Jevons is an English economist, a bit of a polymath really.
Speaker 1: He actually spent a few years working in Australia at
Speaker 1: the Sydney Mint before we went back to Britain to
Speaker 1: complete his education. Jevons never wrote about boots, but I
Speaker 1: reckon he probably wore them. I do know, though, that
Speaker 1: he cared a lot about coal, and the puzzle he
Speaker 1: noticed was this, when coal powered steam engines became more efficient,
Speaker 1: Britain didn't necessarily use less coal. Sometimes you more efficiency
Speaker 1: made coal powered activity cheaper, which made more of it
Speaker 1: worth doing. That idea use a resource like coal or
Speaker 1: our case, we're thinking about labor more efficiently, then the
Speaker 1: stuff it makes gets cheaper and you might end up
Speaker 1: using more coal or in our case, hiring more people.
Speaker 1: That set of ideas, that's called Jevons paradox. Okay, so
Speaker 1: let's apply that to boot making. More productive boot making
Speaker 1: meant cheaper boots. Cheaper boots meant more boots got bought,
Speaker 1: ready to wear footwear expanded, the market got bigger. There's
Speaker 1: a habit I want you to notice here. The question
Speaker 1: isn't just how many workers do you need per pair
Speaker 1: of boots? You also want to think about how many
Speaker 1: more pairs of boots will people now buy? That second
Speaker 1: question helps see things in starker relief. That's why economists
Speaker 1: talk about creative destruction. And the most important reminder here
Speaker 1: is there's two words in creative destruction creative and destruct Too.
Speaker 1: Many of us are misled because we only stare at
Speaker 1: the destruction. But the creative bit matters too, because new
Speaker 1: technologies they create new demand, new tasks, new firms, new
Speaker 1: forms of work, new ways are doing things, And in
Speaker 1: this story, that creative side turns out to matter a lot.
Speaker 1: So now for the astonishing headline. English boot making went
Speaker 1: through a full technological revolution, and yet the total number
Speaker 1: of jobs barely moved. It was about two hundred and
Speaker 1: twenty thousand workers in eighteen fifty one and two hundred
Speaker 1: and thirteen nineteen eleven, across sixty years of upheaval. Those
Speaker 1: numbers are so close it's like nothing changed except beneath
Speaker 1: that calm surface. Nearly everything changed. The work was fundamentally remade.
Speaker 1: You see the old craft world. It was built around
Speaker 1: occupations like cordwainers. I've always wanted to say that word binders, closers,
Speaker 1: and cloggers. As mechanizations spread, those occupations shranked dramatically, and
Speaker 1: in their place came a much more factory shaped world
Speaker 1: and occupations that we might recognize today machinists and riveters
Speaker 1: and operators. And along came a bunch more jobs to
Speaker 1: coordinate this new, more complex organization of work. Some of
Speaker 1: the obvious ones like managers and foremen and supervisors, but
Speaker 1: also accountants and clerks and wholesalers. So roughly the same
Speaker 1: number of folks were making birds, but they were doing
Speaker 1: completely different things. That are in new occupations, doing new tasks,
Speaker 1: a completely different organization of work, different division of labor,
Speaker 1: different kinds of film. Just about everything changed except the
Speaker 1: number of jobs. Here's how that happened. Roughly two thirds
Speaker 1: of the jobs in the old artisanal occupations they disappeared,
Speaker 1: and they were replaced by an almost identical number of
Speaker 1: new jobs in the new factory related occupations. This is
Speaker 1: the two sided nature of technological change. Jobs are destroyed
Speaker 1: and created. I think this helps explain some of the
Speaker 1: anxiety around AI right now. You see, when folks try
Speaker 1: to imagine AI, it's very easy to picture the destruction
Speaker 1: side of things. You can picture the occupations disappearing as
Speaker 1: large language models take over tasks that people used to do,
Speaker 1: like translating or copy editing or coding. It's easy to
Speaker 1: picture the first rung of the career lad of getting
Speaker 1: kicked away. What's much harder to picture of the occupations
Speaker 1: that don't yet exist. New tasks, new firms, new ways
Speaker 1: of organizing works. You can't picture them because, in a
Speaker 1: very real sense, nobody even knows what they're going to
Speaker 1: look like yet. Imagine going back to eighteen fifty one
Speaker 1: and asking a boot maker to imagine a prompt engineer.
Speaker 1: The result is anxiety. The anxiety is real and it's human,
Speaker 1: but history can help. It reminds us that a big
Speaker 1: technology shock does not always mean a collapse in the
Speaker 1: total number of jobs. Sometimes the big change is actually
Speaker 1: a deep, real organization of the work itself. That brings
Speaker 1: us to the next part of the story about geography.
Speaker 1: Old artisanal boot makers used to be spread pretty much
Speaker 1: everywhere across England. Every town needed a boot maker, so
Speaker 1: the end of that way of making boots cut jobs
Speaker 1: in nearly every part of the country. But when the
Speaker 1: new work using the new methods came forward, the jobs
Speaker 1: were not so evenly distributed. It's because the new jobs
Speaker 1: they were tied to factories and larger enterprises, and those
Speaker 1: larger boot making companies were clustered heavily in just a
Speaker 1: few places, above all, Northamptonshire and Leicestership. Cracky, I hope
Speaker 1: I said them right. Those two towns, however, you say,
Speaker 1: am together they captured nearly half of all the jobs
Speaker 1: in the newly created occupations. So yes, boot making survived
Speaker 1: in the aggregate, but it increasingly moved and lived at
Speaker 1: different addresses. One more thing. This all played out over
Speaker 1: many decades. Most of the incumbent artisans did not, in
Speaker 1: fact lose their jobs. Instead, the next generation just stopped
Speaker 1: entering the dying occupations. Instead they entered new ones. That
Speaker 1: means the old bootmakers got to retire as bootmakers. It's
Speaker 1: just their kids who never signed up. This was a
Speaker 1: revolution slow enough to let a whole generation off the hook.
Speaker 1: I'm not saying it was painless, but it could have
Speaker 1: been a whole lot worse, and that's important. As we
Speaker 1: now ask what does this tell us about AI? One
Speaker 1: answer is maybe less than some people would like. This
Speaker 1: history doesn't predict what AI will do. It doesn't give
Speaker 1: us a roadmap, but doesn't tell us everything will be fine,
Speaker 1: and it doesn't tell us that everything will fall apart either.
Speaker 1: What it does do is widen the range of outcomes
Speaker 1: you should take seriously. It's easy to picture the jobs
Speaker 1: that will be lost. It's harder to picture the ones
Speaker 1: that might yet emerge. The story of Victorian bookmakers puts
Speaker 1: a good news version of technological change into sharper focus.
Speaker 1: A major new technology arrived, a transformed production, and it
Speaker 1: did not show up as mass displacement of incumbent workers.
Speaker 1: Dario Moode, I want you to take note. What happened
Speaker 1: was that slow adjustment and persistent demand helped shield a
Speaker 1: lot of the incumbent workers while the industry transformed around them.
Speaker 1: New jobs were created, new tasks emerged. The creative side
Speaker 1: of creative destruction it also showed up, and the pace
Speaker 1: of change might well be central to why I have
Speaker 1: played out this way. I chatted with the author of
Speaker 1: this research, Hillary River Pond, and she told me she
Speaker 1: thinks the pace of change is a really big deal.
Speaker 1: In her case, Victorian boot making, the technological change was
Speaker 1: moderately slow. It was slow enough to grandfather older workers
Speaker 1: through the transition. And she raised the obvious concern if
Speaker 1: AI moves much faster and most people think it will,
Speaker 1: then that gentler adjustment may be a lot harder to achieve.
Speaker 1: But if the AI transformation slows down a bit, maybe
Speaker 1: we get more of the promised productivity gains without all
Speaker 1: of the promised unemployment. Maybe the creative side of creative
Speaker 1: destruction has time to arrive. Maybe new tasks and new
Speaker 1: firms can emerge quickly enough to absorb the shock, or
Speaker 1: maybe not. I don't know, And that modest is an
Speaker 1: important part of the story too. Economics is really pretty
Speaker 1: good at helping us think through mechanisms. It is much
Speaker 1: worse at giving any of us certainty about the future.
Speaker 1: So the value of this story isn't that it settles
Speaker 1: the AI debate. I want to be clear on that.
Speaker 1: It doesn't, but it teaches us how to think about
Speaker 1: it more clearly. It's tempting to immediately ask how many
Speaker 1: jobs might be destroyed when a new technology arise, but
Speaker 1: we should also ask what might be created and how
Speaker 1: quickly that transition will happen. Will the work show up
Speaker 1: the new work in the same place as inside the
Speaker 1: same firms for the same people. Those change too. One
Speaker 1: thing I know for sure, it's much easier to imagine
Speaker 1: the destruction than the creation. But both of the matter,
Speaker 1: and you should focus on both sides of that equation.