Good evening and very warm, welcome to the Oxford Martin School.
Thank you for coming out on this particularly rainy evening.
I think you all in for a treat. For those of you that have just started at Oxford and this is your first term and particularly warm welcome.
The Oxford Martin School is an interdisciplinary group which focuses on the big challenges of the future,
and you'll find a very, very wide range of events going on here on the website.
I was the founding director of the schools in 2006. I came to Oxford in gold and I'm now professor of globalisation,
and one of the enormous pleasures I had was being able to put people together to create very exciting teams.
And so I'm delighted in 2012 to be able to recruit call for a fresh out of his doctorate in Berlin to come and work
on a team we put together on technology and employment the intersection of technological and economic change,
working with Michael Osborne, who was fresh out of his doctorate in the engineering department here.
As you know, the rest is a short history and they have done absolutely fantastic work in 2013,
very soon after the call arrived here and started working with Michael.
They produced a paper which really changed the way that people think about this area.
It's a sign of its success that it has been a source of much controversy and contradiction because it really defined that space.
And many other people have subsequently done work in that area because remains at the head of it.
I stepped down in 2016 and I'm delighted to see that, such as Godfrey, the current director of the school,
is in the back has to leave early, which is why he's not doing what I'm doing.
Karl has gone on to win a number of grants after that.
We've been very fortunate in this work programme to benefit from funding from Citibank, and in fact, they are just renewing that again.
So we absolutely should be able to keep drilling down and pursuing this vital research agenda.
Will we have jobs in the future? What will the jobs be? Where will they be?
And what are the implications in terms of inequality, wages and so on?
The technology trap is a magnificent book. It's for sale afterwards at a massively discounted price of £15.
If you go down the road, you have to buy it for. So buy it here.
And there will also be a drinks reception to which all of you are invited at six o'clock.
So I'm delighted to welcome Karl and for him to launch his new book, The Technology, Trump Capital, Labour and Power in the Age of Automation.
Thank you. It's such a pleasure to be back here to my favourite place to say my favourite lecture hall in the world,
not just because I only have to take the elevator floor down to get here, but also because it's the place where everything actually started.
Back in 2012, when Mike and I got together and began to discussing what the future of the bloc might actually look like,
what how the division of Labour is evolving as artificial intelligence is progressing.
And, as Ian mentioned, has been a source of a bit of controversy.
Hopefully, we'll be able to add to a bit more to that controversy today.
But the theme of the book is very much sort of trying to shed some light on the times we're living in through the lens of history,
because what we estimated back in two thousand twelve is that roughly 47 percent of jobs are at high risk of being automated.
And the question that we've gotten consistently since then is,
is this time different somehow because we've been through periods of rapid technological progress and in the past,
and I found it quite extraordinary when researching this book how much technology has progressed over the past two centuries,
but how little the debates surrounding its effects has actually progressed.
We are now living through an era of automation anxiety again, very similar to what we saw in the 1960s, in the 1930s, in the 1830s and so on.
And it feels quite natural somehow that people shouldn't feel that and to see us think about the tornado that is coming for the office.
And I was actually quite struck to see that a majority of Americans.
This is from a recent Pew Research survey. A majority of Americans now think that there should be restrictions on the number of machines
that businesses should be allowed to implement in order to increase productivity growth.
And this is not that puzzling through the trends of recent automation and debates,
but it is quite puzzling if we look at the long run trajectories of mechanisation and growth.
I studied economic history as an undergrad, one of the first slide you encountered when he studied the economic history.
Is this one right?
It shows that economic growth was roughly stagnant for millennia, a very long time, and took off in extraordinary fashion around eighteen hundreds.
What happens around 18:00 is not that no technology for the first time arrives,
so there was a lot of important inventions before then, like the barometer, the telescope, the horse shoe and so on and so forth.
There's a lot of important inventions happening. But for the very first time, technology translates into higher incomes for the wider population.
And the reason for that must be the mechanised factory, which allowed us to produce more with fewer people before and turned 100 were
few machines that relieved workers of a lot of burdens in their daily jobs.
And as a result of the steady flow of labour saving technologies that have been adopted since then,
we are now able to produce roughly 40 times more in Britain than we were at the dawn of the industrial revolution.
And people's income as a result of that is roughly 40 times higher adjusted for inflation.
Now you might say that that does. Compassion doesn't make any sense because the consumer basket that all of the industrial
revolution was very different and the consumer basket that you combined with your incomes today.
All of these things didn't even exist.
Ordinary people at the time could only look at the lives of the wealthy in the movie, who had servants to do the most tedious things for them.
Today, most of all, so all of us here in this room have access to the electric servant in terms of dishwashers, washing machines, vacuum cleaners.
And so that relieves us of a lot of tedious work, not to mention other inventions like the automobile and out of antibiotics.
And if that wasn't enough evidence of progress,
consider the fact that producing those goods and earning those higher incomes have become so much more comfortable, less well.
Not so long ago, a significant share of the population worked in coal mines.
Evidence and explosions were part of everyday working life, long pieces of often part of the package.
Today, most of us work in air conditioned offices.
The worst thing that happened here at the motor school in recent memory was when the coffee machine broke down.
I think that it puts things in perspective, and if we only look at the sectoral changes and the composition of the workforce,
that also understates the transformation that's taking place.
So if you take the jobs of farm labour in nineteen hundred, that person would have walked the fields with nothing more than animal power.
He would, or she would be exposed to hazardous weather conditions, swarms of insects, all sorts of unpleasant things.
Today, a farm labourer in the industrial west usually sits in his or her tractor and can listen to the music of his or her choice.
So it's quite extraordinary.
What a leap forward that has happened over the past 200 years at the point of the book is that that leap forward is only half of the story.
What did the people actually say when the mechanised factory arrived?
I think there's no doubt that the industrial revolution laid the foundations for modern
growth and much of the increases in growth and well-being that has taken place.
But industrial revolution itself was polarising.
So, for example, Benjamin Disraeli, before he became prime minister of Britain,
wrote a novel cold calling speech in which one character remarks said, I see cities, people with machines.
Suddenly, Manchester must be the most wonderful place of modern times.
The very same year, Friedrich Engels published his conditions of the working classes,
which was written during a stay in precisely Manchester, and Engels had a very different take of what was happening.
He argued that mechanisation only serves to downgrade people as it puts them in the repetitive motions of machinery, which can be deemed unnatural.
And you also argue that it took over a lot of people's jobs,
reduced their wages and incomes to subsistence, and led to the administration of the working class.
We know from history that he was wrong about the future,
but it was actually fairly on target about the period he lived through because what
he witnessed was what the economic historian Bob Ireland has called Engels prowess.
Seven decades of the classic period of the industrial revolution where the British economy first took off,
but very little happened to the wages of ordinary people.
Now the wage data for this period of time isn't great,
but if you look at supplementary sources like based on consumption or biological indicators such as height, they paint a similar picture accords.
Born in 1750, we're actually taller and of course, born in 1850,
suggesting that people's nutrition was adversely impacted as well as their incomes diminished.
And at the heart of the industrialisation process was the replacement of middle income brackets.
So artisan craftsmen who would do sort of every step in the production process themselves,
often in their home, surrounded by their wives and children, their incomes came under pressure as the mechanised factory arrived,
and what the factory did is that it took advantage of cheap labour, child labour in particular.
And it's a really noted fact that the early spinning machines of the industrial revolution were specifically designed to be attended by children.
Manufacturers three that to sap resistance to mechanisation.
They were better off by trying to innovate, innovate in such ways as to get around that.
And children often didn't have much bargaining power, and they only got food allergy, and they were easy to enforce the factory discipline upon.
They were the robots of the industrial revolution, if you like.
And now a great question to economists and economic stories has been why would people
voluntarily have participated in the industrialisation process if it reduced their utility?
The simple answer is that they didn't. They expressed their thoughts and feelings converse like the one you can see above.
They. Son to parliament to block introduction on machinery on several occasions, and they rioted against the Mechanistically Factory,
and all the Luddites achieved was getting the British government to deploy an even larger army against him.
The Army Wellington took against Napoleon in the Peninsula War of 1812 eight
was actually smaller than the army that was sent out against the Luddites.
And I think it's important to remember that a much public commentary focus on the London riots in particular,
was a long wave on machinery riots swept across Britain and even Europe,
and all of them didn't have to do with appalling working conditions of the factory.
You saw similar riots happening against our culture machines as well.
And I think that the economic historian Hobson summarised it nicely when he said that once began with the construction of the
first factories and ended with the construction of the railroads also ended with the publication of the Communist Manifesto.
A lot of these revolutionary technologies became eventually.
The engines of growth also created a lot of political revolutionaries along the way.
The point of the book is not to protect a socialist revolution,
but I think it is noteworthy that levels of income inequality have been increasing over the past three decades or so,
and they are approaching levels not seen since the first industrial revolution.
And there are many factors that are shaping and then income distribution.
There's no question about that. But mechanisation or automation is definitely one of them.
And clearly, it's not driven by textile machinery or steam engines.
This time around, technology is very different. But it is anything having even more pervasive impacts on the labour market.
And as you can see, this process has been going on for some time.
The first electronic computer was invented at the University of Pennsylvania in nineteen forty seven or forty six sorry,
but it consisted of roughly 18000 vacuum tubes, 20 30 tons.
And as a result of that, it didn't have much impact on the labour market.
It took the invention of the microprocessor and later on the invention of the personal computer for businesses to realise that a they
could restructure supply to supply chains in ways that allowed them to take advantage of cheap labour in emerging economies like China.
And secondly, that they could automate routine, repetitive tasks on a mass scale.
And the consequence of that is best shown by this figure.
We see that as productivity growth grows for most of the 20th century.
Wages are growing in tandem. So early machinery is creating a lot of demand for operators whose skills are augmented by machinery,
and the technology complements them in a happy way. That's quite different from robotics, who are replacing those sorts of workers in production.
And as a result of that, you seeing a growing gap between wages and productivity growth.
Now, for all the talk of the of rising inequality,
I think the greatest tragedy is actually that certain groups in the labour markets have been left worse off in absolute terms.
So if you look at the wages of men with no more than a high school degree,
they have actually been falling for prime aged men with no more than a high school figure for four decades now.
So it's not just a question of of the labour market becoming more equal.
Opportunity is diminishing very rapidly for people who used to take on jobs in factories before robots were being adopted on a wider scale.
One of my favourite lines from the book is that if you put one hand in the freezer and the other on the stove,
you should be feeling quite comfortable on average. But we know from experience that that is not the case.
And I think the same can be said about the U.S. labour market, right?
Unemployment is trending around 3.6 percent, right?
It's looking very healthy on the surface. And if you go to certain places, like most coastal cities, it's also doing really well.
But people in the Rust Belt, in particular in cities that specialised in manufacturing industry,
which have suffered from deindustrialisation caused by offshoring and automation, are not doing so well.
You can see if you look at labour force participation rates amongst primates,
men again, you can see that joblessness is on the rise and especially in these places.
There are more robots in Michigan alone, for example, than the entire American West, and that is where most of its problems are.
And and we know from a great body of research that joblessness also comes with a lot of bad social consequences.
Economists tend to think that the purpose of production is consumption, but we actually know from a very big body of research that that's not true.
People attach a lot of meaning to the work.
One of the most consistent findings across countries across different periods of time is that people who work are happier than those who don't.
And if you look at the communities where jobs have dried up, you see that marriage rates are declining.
More children are growing up in single parent households. Crime is on the rise.
Health outcomes are worsening. Suicide and alcohol.
Alcohol and substance abuse is on the rise, and it is not a very healthy development.
And if you want to understand my key three key swing states in Michigan, Wisconsin,
Pennsylvania who had opted for the Democratic candidate in every election since 1992, all of the sudden ended up voting in President Trump in 2016.
Automation is one of the prime reason, and this is a joint research which Shenzhen and taught by the NEC.
And one of the key points is that we have seen nothing yet. We've already seen a backlash against globalisation.
But automation has so far primarily been confined to routine rural based activities.
But the potential scope of what machines can do is expanding very rapidly due to recent advances in machine learning and artificial intelligence,
in particular machines that are increasingly incapable of inferring the rules of the game themselves.
They can tap into the digital trails that we leave behind us.
When we interact online, they can learn through trial and error, and as a result of that,
they're able to perform tasks that are inconceivable to automate.
A few years ago, like driving a truck diagnostic and cease translation work and document review so and so forth.
And and what all of these approaches have in common is that they are driven by increasingly large
datasets that allows machines to predict what a human would have done in any given situation.
So for example, if you want to programme a car to drive in the city of Oxford,
it's almost impossible to foresee every given situation that the vehicle might encounter.
You just can't, and but you can actually fill in the blanks by gathering loads of data.
People driving and then trying to predict what the human driver would have done in that given situation, and I am simplifying a bit,
but it's probably this pattern that is driving everything we're seeing in technology and today and some of you might say,
well, I used Google Translate yesterday, so perfect and autonomous vehicles for all day.
But I think it's important to remember that every technological revolution started with imperfect technology are steam engines,
for example, were mainly used to train coal mines. Yet they were the ones in.
So that eventually became the prime movers of the industrial revolution and powered economic growth for a very long time.
And I think that we are actually very much underestimating the potential impacts that I could have on labour markets.
The first reason being that machines don't have to be perfect in order to outperform us because we certainly are not.
So this is a study of Israeli judges and their decision making during the day.
And you can see that early in the morning after we had a morning snack,
insulin levels are high and we make a very high share of favourable positions that then tends to drop off during the morning,
bumps out after breakfast again and the same after lunch.
And we are very much shaped by what we eat, how much we sleep.
Some of us have bad temper in certain situations. So machines are actually have a comparative advantage in a wide range of tasks just because of that.
The second point is that for automation to happen, machinery doesn't necessarily have to replicate every motion that the human does in his or her job.
So we didn't automate away the jobs of lamplight as, for example, by building robots capable of climbing lampposts.
We didn't automate away the jobs of known dresses by building robots that can walk out of the home.
Shop trees carry wood and piles of water into them, and heat the water on the stove and then perform the motions of hand-washing, right?
We did that by inventing the electric washing machine that does an entirely different set of motions.
And because engineers are very good at finding these clever ways of restructuring tasks to make them automatable,
potential scope of automation is much greater than many people and actually think.
Nonetheless, there are certain domains in which human workers still hold the comparative advantage.
And this is joint research with Mike Osborne at the Wharton School that goes back to 2013.
And what we did is we tried to sort of think about in which domains machines still perform very poorly,
where there's been very little progress in recent years.
And I think what example that illustrates this quite well is Turing.
Test competitions for efficient bots try to convince human judges of them being human.
And a lot of pundits argued, I think was about three years ago now that there was a big breakthrough because
one chat bot managed to convince 30 percent of human judges of its being a person.
But it did so by pretending to be a 13 year old orphan Russian boy speaking English as a second language with no understanding of English culture.
And if you think about the variety of much more complex social interactions that you do in your daily jobs,
we try to persuade people that you right to negotiate certain things.
You try to motivate your colleagues. It's almost inconceivable we will have an algorithm that's able to perform that in the foreseeable future.
And I think the same is true of creativity, and there's a big debate in the machine learning community,
admittedly, with regard to whether algorithms can be creative.
But I think people who who think that they can be or things that they are tend to conflate
novelty and creativity so I can draw something here on the world and call myself an artist.
A few of you would be likely to buy my paintings.
And the tricky part here is not to generate something that's novel is generating something that's novel and makes sense.
So if you think about. For example, software writing, classical music, you can certainly take your favourite symphonies,
so maybe they'll know that and say that these are the best symphonies that have ever been written.
And then, you know, allow the algorithm to come up with some combination of that, and it's very likely to sound quite similar to Mozart.
You're not going to arrive with Stravinsky or Schoenberg by doing that.
And I think one of the reasons for that is that when humans are creative, we draw upon based on experience from all walks of life.
Sometimes even a dream. And in many cases, when task create required creativity, much of the data is likely to be outside with the training dataset.
Last bottlenecks may be the least intuitive one that relates to the perception of manipulation of irregular objects.
So some very easy things for us,
distinguishing between a piece of rubbish that's on the floor or a really important document straightforward for most of us to do.
It's actually so easy to explain similar tasks like, you know,
distinguishing between a pot that is stuck in holds and they start in the pot that tells the plant also quite intuitive tasks not so easy to automate.
So unfortunately, I think the job of the cleaner is one of the last we are likely to see is appearing.
And that being said, there are a lot of jobs that are not very intensive and tasks does require creativity and complex social interactions.
And if in fact, the majority of jobs in transportation, logistics, retail, construction don't.
And as a result of that, the potential scope of automation is quite significant.
So you can think about three 3.5, five million cashiers that are employed in the US today.
If it goes into the Amazon Ghost story, we won't see a single one.
There's another 3.5 million truck, taxi and bus drivers in autonomous vehicles.
A right? All of them more likely to be exposed to those technological developments.
And there's another 2.2 million people in the US still working in call centres, just to name a few examples.
And when we published this study a few years ago now,
we actually also published a list of 32 list of some 700 to occupations and their relative exposure to automation.
And you can imagine that a lot of people pick it up from some of those and said, Well, this is silly, doesn't make sense to us.
It from my friend Ken Cukier, the economist, used to tease us because we found that fashion models are highly exposed to automation.
These fashion models here actually don't exist.
They have been generated through generative adversarial networks using thousands of pictures, and they're already being used by companies like yours.
And and I think if we only look at the potential scope of automation,
we actually also miss a lot of stuff because we're only looking at the first order effects.
So a lot of second and third order effects as well that are shaping the cloud.
So in the early days of electrification, for example,
all we did was replacing the steam engine with an electric motor at a sense as the central power source of the factory.
And that didn't have much of an impact on productivity growth, right?
Because everything else remained intact.
All of these shafts and counter shafts in the factory were still there, but it took a while for engineers to figure out actually what you can do.
You can place an electric motor on every single machine and you can then sequence them in the natural flow of production.
And that's the approach that gave rise to mass production.
It is what allowed Henry Ford to produce the Ti model at a sufficiently low price for it to become the people's vehicle.
And the same approach to doing things spread gradually across industries.
And that was when the main effects on the economy and productivity growth was felt.
If you look at some of the early horse carriages or the early automotive on such as, it actually almost looked like a horse carriage, right?
So we're done this essentially replacing the horse with an internal combustion engine as the prime mover of your vehicle.
And it took a while for us to figure out that, well, first of all, we can redesign the entire car.
It doesn't have to look like a horse carriage.
And we then realised that religion is a lot of gasoline stations and we need to build in a lot of shops along the roads,
which gave rise to road commerce, and more tourists have created millions of jobs.
It took a while for us to figure out that we need to build interstate highways,
which gave rise to the trucking industry and changed distribution models.
And it took a while for people to figure out that they actually don't have to live in
congested cities and the longer they could live in the suburbs and commute into work.
So there was the mobile from the early days just replace the horse.
But over a longer period of time, it reshaped the structure of the entire economy.
And I think we can expect the same from artificial intelligence and autonomous vehicles.
I'm an economist, I'm not a futurist.
I will do this very briefly, but there are certain things that I think we can actually infer when autonomous vehicles emerge.
So first of all, you're very unlikely to need a lot of parking space in cities on the sidewalks so you can measure roads slim
build a parking space success because the costs actually just going to satellite a satellite out of the cities.
And you can imagine that if everybody has their own automated chauffeur and they're also more
likely to live farther away from work and do some of the work in the cars on the way home.
So density is maybe not going to be that much of an issue in city centres and a longer as a result of that.
And lastly, the car itself is clearly going to look very different.
Traffic may not look as this 1950s version with a family playing board games.
You may have a Netflix subscription instead, or the car may have a minibar, and that will be the most expensive part of your trip.
But what is clear is that it has the potential to change a lot in terms of how we live and work, provided that we let it do that.
And because I think that the economy's long tiff us out to something when it suggested that what's happened on the farms,
if if horses could have joined the Democratic Party voted, what happened on the farms might have turned out differently.
They could have used their political clout,
a political voice to bring the spread of the tractor to a halt and going already seeing some examples of that.
So this is truck drivers who went on strike in the state of Missouri the other week,
demanding legislation to block the introduction of autonomous trucks as they are getting more pervasive.
This is dockworkers who went on strike in Los Angeles Harbour a couple of months ago, fearing autonomous cargo trucks.
They did misunderstand on paper slap. It's not. It's not the conspiracy not planning to automate this 47 percent of the jobs.
But what it shows is that the societal response to automation is to some extent, already taking place.
When I began to write the book a couple of years ago, robotaxis wasn't on anybody's radar.
Now it's being discussed on both sides of the Atlantic. Bill de Blasio proposed a blue robot tax the other week,
and worker councils would essentially decide whether businesses should be allowed to automate or not and whether it's essential for the company.
So I think we're seeing to some extent some of the backlash against automation already happening.
The point is not that there won't be jobs in the future.
I'm absolutely certain that there will be.
And if you go back to nineteen hundred right and you are somebody of your grandmother or a great grandfather,
uh, what do you think will be the jobs of the early 20th century?
They wouldn't have sat well.
My daughter is certainly going to be a software engineer and my son is going to be hot yoga teacher, and that would be very unlikely.
And I think in a similar fashion, you are very much sort of struggling to predict the jobs that will emerge in the future.
We can't at least now cost some things that are happening in the labour market right now.
Lincoln did a little survey on their platform a while ago, looking at new and emerging jobs.
And amongst those, you can find arrest developers and data scientists and social media interns and zoom by instructors.
And you can also find big data architects to. For marketing specialists and the beach body coach, I won't disappoint with this one.
I think this actually reflects a broader pattern that we've seen in the labour market over the past couple of decades.
We see that new jobs are emerging in very skilled industries that are highly clustered,
and those people are earning higher wages, are demanding a lot of in-person type of services that are hard to automate.
And you can see this even in official statistics now. So some of the air, for example, that's existed for a long time.
It's only very, very recently became so job title because we tend to demand more of them as we grow
wealthier and this is often joined by other targets or better a couple of years ago.
And what it shows is that there's been a shift in where these new jobs are actually emerging.
So before the computer revolution of the 1980s, new jobs were actually recently dispersed across space.
Since then, and you can also see in the statistics of more of these job titles directly relate to computer technologies.
They have become increasingly clustered in skill cities.
And what happens when you create, when you take a job in a city like London or Oxford is that that person goes out to the local economy,
goes to the hairdresser, goes grocery shopping and uses the use, the transportation system and so on and so forth.
And that creates an average five new jobs in the local non-traded service economy.
As a consequence of that, economic activity has become much more clustered.
Some of you may remember this sort of debate and the end of the 1990s,
where people predicted that of the office and Tom Friedman famously wrote this book The World is flat.
But since that the opposite has actually happened. Economic activity has become increasingly clustered in these skilled cities.
And the flip side of that is that where robot technologies or automation technologies have been adopted, the exact opposite has happened.
So in other manufacturing cities where jobs have been automated away, the local service economy has taken a hit as well.
And as a result of that, we see many of these social problems that I mentioned earlier.
Now, so in conclusion, what I think is the key message of this book is that in a way we have been here before,
and in a way resistance to technological change has been the historical norm rather than the exception.
And I think as a great economist, Joseph Schumpeter observed that technological progress also involves creative destruction in employment,
meaning that there will be both winners and losers. And if a lot of people see their jobs and incomes under threat, they are likely to act against it.
And one reason that economic growth was actually slow for so long is that workers vehemently
resisted any technology that threatened their jobs and incomes and fearing social unrest.
Monarchs and governments typically sided with their pockets.
And I think what we need to do is that we need to make sure that people benefit from
these technologies also in the short run to ensure continued acceptance for them.
Because in the end of the day, technological progress isn't an actual force.
It requires societal acceptance. And the great difference to the industrial revolution this time around is that
we are in a much better position to actually manage and shape the outcome.
And so the book concludes with a few policy proposals, which I won't go into here.
Say, If you want to read about those who actually have to buy the book,
it's a great gift for family and friends, and maybe you can open for discussion.
Thanks very much. Thanks very much for that.
Very, very fascinating. Short summary of what is immensely readable and important book.
We have about 15 minutes. This is being webcast and video, so be aware that if you ask a question that you might be broadcast live around the world.
And with that, I hope not intimidating comment.
Who'd like to pose a question to Carl? Thank you.
Can you wait for the microphone, please? Thank you.
My name's young, fun partner of an investment firm investing in education businesses, in part to address some of these challenges, you've pointed out.
Carl, if you could wave a magic wand to ensure that as many people as possible benefit from these
new technologies as opposed to being pushed down into underemployment or low skilled jobs?
What would you what would you like to do? Well, if I answer your question, you're basically giving away the selling proposition of the book.
But I'll give it a go.
So I think unfortunately, there's a tendency to say that we have this really big challenge and we need one big solution to solve it.
And that's universal basic income.
I think there is a lot of things that can be done without my massive mind individually that can make a big difference collectively.
And as I mentioned a couple of times during the presentation,
I think much actually lies in the economic geography of new jobs and the fact that we're seeing this sort of divergence between metropolitan cities,
the countryside and old manufacturing industries. And I think that is really sort of tearing apart society.
And so one example which which I which is close to my heart because it's close to where I grew up in southern Sweden,
is the city of Melbourne, which had specialised in building ships.
And in the early 1990s, Cox cocoons. The shipyard closed down and the city was actually doing very poorly for a long time,
and its revival came with the construction of the Harrison Bridge to Copenhagen.
And so all of the sudden people in management statements live where housing is cheap tap into booming labour markets.
Most of them would spend their earnings locally where they live, which gave a boost to local service economy and created a virtuous cycle.
And it's actually one of the most dynamic labour markets in Europe.
And so I think a lot can be done by actually connecting, declining and expanding real regions.
There's another I think there's 12 in total policy proposals I got through, so I leave the 11 remaining ones as to selling proposition.
And thank you for that question. Yeah. Um, it's a very left.
It's sort of left hand. Thanks for a brain talk, really enjoying it.
I was whenever these conversations come up,
I think about the artisans who were threatened in the industrial revolution with the loss of their livelihoods.
And yet I would imagine in the room today and in Oxford, particularly in a very high, highly affluent place.
Generally, there are a lot of people wearing artisan wristwatches and eating artisan chocolate
in something of a rebuttal of the idea that mass produced goods are best.
Do you think that there is some kind of future for things still made by hand or things made in a bespoke way that as people get wealthier and living,
standards become higher? There may be some greater resistance to the idea of mass-produced things or not
solutions coming from large datasets as opposed to individual tailored ones.
Thank you. And it's a great question, so I think, first of all,
it's important to note that it's still a very small part of the overall economy, but it is growing.
And I think the last part you mentioned is absolutely key, which is that you're saying that as we grow richer, we may demand more of that.
And I think that's exactly what's happening.
But that also means it's not going to be a relief to many of the places that are seeing this adverse consequences of automation.
Because if you're producing a T-shirt that is selling for 40 euros, you need to be have some people around that are likely to buy them.
And one city that the city of Ballarat, reason that the city of Berlin is a very attractive place to live but is essentially bankrupt,
is that, you know, to produce many of these wonderful things, you actually need consumers well in the long run.
Otherwise it doesn't really pay. So have.
Thank you. You've talked about it almost as a process that has happened since the beginning of capitalism and industrialisation,
the substitution of debt, capital for life, labour.
What opportunities to this revolution in the way we produce and distribute goods?
Is it similar to whether you accept it or not?
A current strategy of cycle with major structural opportunities for new employment,
for new activity, and particularly with reference to climate change?
Yeah, absolutely. I think that's right. I mean, one of the fastest growing occupations today is that while also solar panel installers, right?
So there is massive opportunity there.
And I think Faultline and their new trillion dollar invest ment initiative in Europe to spur not just job creation,
but, you know, combat climate change. And I do think that that is a sector that's likely to expand.
That said, though, I mean,
many of these new industries don't provide the same sort of broad based opportunity as the mass production industries of the 20th century did.
But they tend to be high income industries.
They support a lot of the incomes of people that provide in-person Typekit services, so the multiplier is quite high.
But broadly speaking, yes, I think that's right. Hi, thank you for the talk.
So my question is, why do you reckon will be the effect of automation on the military,
such as, for example, I intend to develop and mass produce androids, human eyes?
While Iraq won't be the effect on the, let's say, the U.S. military and on first generation where warfare.
Well, it's a great place, and it's not one I spent much time on, to be honest with you,
I think we're living in a very good report and that's for the last couple of years back and with some research looking into that.
And clearly, there are huge incentives to adopt automation technologies in the military where the cost of lives is very high.
And we know from the past that the military has also been a key driver of innovation and in many sectors.
So I assume the role of the military is quite significant, but it's nothing I've looked into possible.
Wants to see a show of hands. All right.
And women are asking questions, does the lady justice? All right. Give us a major step.
Yeah, you're right. Yes.
Thank you. Thank you for the fascinating talk.
I'm 20 percent into your book on my Kindle. I think technology is the end to the mean, and we are talking about the end, not the mean.
We, the humans are responsible for technological progress and we know and we cannot deny the
fact that technology will evolve and you will progress and it will continuously progress.
And we are looking at the future of technology, which means I haven't got into your policy section yet.
Maybe you have made this recommendation. So what type of policy and what could governments do to look at the future and predict the future and prepare
the human race to face this technological progress and so that we are not trapped in this technological trap,
as you call it? So that's my question. Thank you. Well, that's an easy one.
And so I think one of the key points of the book is actually that, you know,
technological progress is far from inevitable and if it was industrial, revolution would have happened a bit earlier in the history of mankind.
If it was, every country would have adopted the same technologies to the same extent and every country would be rich as a consequence of that.
But that's just not what we see happening over the past 200 years.
There's actually been income divergence rather than convergence, which is a bit of a challenge there.
And so I don't think that it's, you know, easy to predict future economic outcomes on the basis of what is happening in technology alone,
just because the existence of mere existence of technology doesn't mean that it's going to be widely adopted.
So I think you need to look at different factors in how they interact, and technology is one of them.
The distribution of political power in society is one of the reason that mechanisation was adopted a mass scale in Britain.
The first was that the merchant class that grew well,
variables became more politically influential and they would have nothing that jeopardised
their incomes and mechanisation was deemed essential to British competitiveness.
And as in trade and others, that's increasingly integrated.
Markets meant that the political power of the craft skills was significantly eroded because it didn't extend beyond their own cities.
So you saw this sort of great shift in the balance of political power,
and that's the sort of one of the the reason that it's first happened in Britain.
So I think we need to, you know, look at all of this as more of a complex system we have within our natural part of modern schools,
a group that is doing great work in that domain. And I would encourage you to look at the website.
That's never the person that I think it will be when we have time for.
So you are typically on like a hot topic about like attacks on robots and something that I'm concerned about,
that we already see the gap between the frontier of the productivity.
The firms on the frontier of the productivity and the firms are trying to catch up is increasing.
Uh, what do you think about this tax?
I mean, are you worried that this kind of tax maybe actually even make it harder for firms that are trying to catch up to the frontier of technology?
Um, it would be more expensive.
It would be harder for them and how we could come up with this smart kind of taxation that take into account this problem.
So that's a great question. I think I mean, in a way, almost to answer it yourself.
Obviously, if you're a pilot about the robotaxis becomes more expensive to adopt these technologies.
If you're behind the frontier, it gets more expensive to catch up.
So there you have it. I mean, I don't really understand why we should single out robots as a single source of taxation.
I think that's a driver of productivity growth, things we want to see more office, not the things you want to tax.
I think we need to think about taxing capital more broadly.
Clearly, if you see the labour share of income falling over four consecutive decades, you would think that's, you know,
that is going to have certain consequences for public finances, which has being worked on at my school as well.
I'm pleased to say I think maybe even by your group and and and and so, so, so clearly that is a very, very grave concern.
And I think we need to rebalance sort of at tax rates between capital and labour and going
forward also took place close many of the loopholes and loopholes that currently exist.
Great last person there.
And then Carl will be signing books and he can also speak to him over drinks, which will be even more pleasant than being an elected official.
OK, so my question is,
is that you said we've gone through we've gone through the cycle of new technologies coming in and people being very scared but before.
So my question is what is one lesson that we're able to draw from the past in terms
of actually learning how to deal with these fears that we can apply to today?
So I think one of the key lessons you see from the first industrial revolution is that the economic ideas matter, right?
People at the time believe that the world was little too right.
Larger incomes without the resources in larger populations with no sort of increase in per capita terms.
As a result of that, any redistribution of income was deemed counterproductive.
Because if we don't look at the population and Thomas Moses and David Ricardo and others were
very influential in sort of pushing that thought and may be partially right about the history,
but they were clearly not right about the time they were living through.
And that led essentially to the abolishment of the poor laws, which was the only sort of source of relief for people who lost their jobs at the time.
And that sort of just exacerbated the social unrest, and we actually know better this time around them,
which is that it's great for those of you that today's the first day at Oxford to join us for drinks afterwards and celebrate your arrival.
For those of you that have been haemorrhaging, you know, we don't have drinks after every event,
so this is a particular treat today, and it's clearly been a treat to hear Karl.
I'm absolutely delighted after having started the group seven years ago that it's reached the stage of
global resonance and that calls produced not only a whole series of of great papers with his colleagues,
but also this book published by Princeton University Press.
This is also the only time you can be able to buy a book that costs twenty four pounds, something for fifteen pounds brand new.
So I encourage you to do that, to socialise and to meet with Carl, and thanks to you all for coming.