Pushkin.
If you look back at the history of technology, there is this very very very long period of time, like thousands of years, where not much happened for humanity, at least not by modern standards. There were certainly some advances, there were periods of technological ferment here and there, Song Dynasty China as one famous example, But then those moments would pass, and things in terms of technology at least
would go on largely as before people traveled. When they traveled at all, by foot or by animal or by sailing ship, and century after century, most of the people on earth worked as subsistence farmers, trying to grow enough food to survive. And then everything changed. It started in
England about two hundred and fifty years ago. The steam engine, a modern factories all emerged in this moment, this moment that came to be called the Industrial Revolution, that was in many ways the beginning of the world we're living in today, This world where continuous technological breakthroughs, not just year after year, but generation after generation make workers more
efficient and more productive. And this world where generation after generation the material conditions of humanity keep improving, the economic pie gets bigger. The changes that began with the industry of revolution are the reason that most people alive today are profoundly richer than their ancestors in the centuries since the industry of revolution. That link between new technologies and increasing broad based prosperity has been true for most people over the long run. But and this is a very
important but this has not been true forever everybody. And sometimes that long run takes a very very long time. In other words, just because the pie gets bigger, it doesn't mean that everybody gets more pie. I'm Jacob Goldstein, and this is what's your problem. My guest today is Simon Johnson. He's an MIT economist and the co author of a new book called Power and Progress, Our thousand
year Struggle over Technology and Prosperity. Simon's problem is this, how do you create the conditions for technological change to benefit everybody, or at least almost everybody, instead of only a powerful few.
The basic argument is that it is wrong historically and also not sensible economics to assume that technological change always brings immediately and broadly shared prosperity. In fact, sometimes it does the opposite. Sometimes it helps just a few people, and sometimes it's really good for a lot of people. But the conditions under which you get a lot of benefits for a lot of people from technological change require
some thought, and particularly thinking about today in America. Do we have the right conditions, for example, for an artificial intelligence revolution, if that's what we're facing, for that to really deliver lots of benefits lots of people, or is it going to be like some of those previous historical episodes where only a few people gain or hardly anybody gains, and a lot of people lose.
Simon and I talked a lot about the development of AI and how to maximize the chances that AI delivers lots of benefits to lots of people. That's basically the second half of the interview. But I also really wanted to talk with him about the Industrial Revolution because I truly think it has deep lessons that are really useful in thinking about technology and the world today. And the Industrial Revolution, Simon said, really started with textiles, in particular, one kind of fabric.
The real breakthrough, Jacob, is about cotton. So cotton is a material that the British did not invent. It's been in long use in many parts of the world. The Indian spinners were the leading spinners of cotton, and the export of spun cotton from India was a big deal.
But the British figure that they can spin cotton and then subsequently weave cotton more efficiently than Indian artisans by applying machinery to this problem, and that became this cotton industry became the powerhouse of the English.
So you have this the birth of technological innovation as we know it is happening right by the early eighteen hundreds. You're having these incredible productivity gains. This new technological era is just charging forward. Productivity is increasing. What's happening with wages for most workers in England at this point.
In terms of what's happening in England's and what seemed to happen what seems to happen in terms of industrial wages as a whole, is they really don't progress. More so speaking quite broadly here anywhay near like what you would imagine given the pro tivy advances, and there is some of them, suggests broadly, not without its exceptions, but broadly there was wage stagnation in that early period, which
is incredible and weird and pretty unsettling. Given how much productivity transformation, given how much technological change was underway, Well.
That seems like.
Sort of the key point from this period for the argument of your book to be a little.
Reductive about it.
And yes they're asterisks and caveats, but the big idea is you have this call it fifty this year period, the first half of the eighteen hundreds, where there's incredible productivity gains in England and overall workers don't seem to be capturing any of those gains, right, So what's going on?
Why aren't workers' wages going up in this period?
So the core issue Jacob in this moment, and it exists across all of technological transformation, but here we do see a nasty version here is that when you automate things, you obviously make some people more productive than the people who are run the machines, but you're also replacing other workers. Now, once we start to automate weaving, that's two hundred and fifty thousand weavers who are going to lose their jobs. About another fifty thousand people who are auxiliary service workers
around that hand loom sector. So three to thousand people losing their jobs. Where are they going to work.
Two stories that I feel like people have as kind of heuristics for this, right, as sort of toy models in their head. The sort of popular version is, oh, machines throw people out of work and we have technological unemployment. Right, everybody always says that, and yet here we are in twenty twenty three with an incredible amount of technology and unemployment at historic cloths right, So clearly that heuristic is
not right. And then the other, the kind of economics heuristic is no, no, technological innovation makes things cheaper and so well, people can buy more stuff, and in buying more stuff goods and services, we create new jobs. But plainly that second one was not happening in the eighteen twenties.
Why not.
So there's a third possibility, actually, Jacob, which is people lose their jobs. They don't become unemployed because they can't afford to be unemployed. There's no uneployment assurance. They have to go to work at a very very low wage, and that wage may be you know, essentially at or slightly below subsistence. And I think that's also what we've
experienced in the United States. To flash forward, which is since the digital transformation of the nineteen eighties, we've not had the technological unemployment that people were afraid of, but we have had a polarization of the job market. So some people have done well and a lot of people previous middle class, middle skill jobs have disappeared and people
have got pushed down to low wage jobs. And that parallel I think we see in the early Industrial Revolution, Jacob, That's what I think absolutely happened to the weavers, for example.
So, okay, that's the first half of the eighteen hundreds in England. In England, that changes in the second half. Right, in the latter part of the eighteen hundreds, we just do go up for ordinary people. These productivity gains that have been happening for decades and decades, they finally sort of pay off in a broader way. Right, Why what changes? Why does that happen?
Then? So many of the frustrations of the first half of the nineteenth century, including the lack of representation for people living in these newly industrial areas that had bubbled up after the eighteen thirties, and there was much more awareness of anger and also very difficult living standards in these big industrial cities, and that leads to approcess of
partial but ongoing democratization. So there's better rights for workers, including ultimately the right to form trade unions, and those trade unions are demanding higher wages by the eighteen eighties, and high wages in return to match the higher productivity. That's what starts to build much more broadly shared prosperity.
So there's the political piece, trade unions being a notable piece of it that you have by the second half. You also in the book talk about a technological piece, how the nature of the technologies that are emerging and spreading more than emerging spreading by the second half of the eighteen hundreds, are also driving broader wage gains.
Talk a little bit about that, right.
So it's interesting that in the eighteen fifty one Great Exhibition that was held in London, there was almost no American technology on exhibit. The exceptions were some stuffed wild animals and some guns. Actually seems very American even today, but that was eighteen fifty one. By eighteen ninety, the US is the leading industrial power in the world. And that transformation was a lot about movement west. It was
a lot about developing technology using agriculture. People were leaving farms in the Midwest to go to live in Chicago and work for McCormick Reaper's company to make equipment that would let more people leave the farms. And as these companies expanded, Singer Sewing Machine Company is another one, they look to European markets and they brought over their factories and their business models which were very or into making
effective productive use of relatively unskilled labor. And when they brought that into Europe, that helped boost the demand for unskilled workers. And it was unskilled workers, make them highly productive, pay them a decent wage. That put the industrial development onto a different and we would argue much better try and they.
Pay them a decent wage.
Piece.
I mean, it's that just a market dynamic.
Because there are these new technologies like sewing machines, there is more demand for unskilled labor across the board, and therefore it's just a competitive equilibrium. Well, I got to hire somebody, and the guy at the factory nextdoor is going to hire this unskilled worker if I don't, so I have to offer them more money. Is it just that?
Yeah?
And I think it's it's part of that. It's the demand for labor. It's also the arrival of trade union. So the people I'm employing, I don't have a union in my factory, but two factories down they have a UNI, and my guys can and move down there and get the union wage if I don't pay them enough money. And I do think personally that railways were really important in this entire process, Jacob, because prior to railways it
was very hard to move between places. It could take you two or three days on a stagecoach from London to Manchester, for example, very uncomfortable, quite expensive. Labor mobility was not very high in the sense of you know, are you going how far would you billing to move to get a better job. Once railways arrive, and once you have this unified market, there's a lot more possibility of moving to boom town's and a lot more understanding
what's going on in you know, fifty miles away. And I think that was a very important part of critian national market and spreading ideas and boosting the demand for labor.
I'm glad you mentioned railroads because in the book you write at some length about the rise of railroads, which is a little bit earlier than the period we're talking about here, right it's the first half of the eighteen hundreds, and in particular you write about this one guy named George Stephenson, who is sort of representative of this new kind of entrepreneur that's emerging around this time. Talk a little bit about George Stephenson.
Who was he?
So, George Stephens largely self educated. He was a mining engineer, but he didn't have any formal qualifications. He was just a chap who had worked in minds and helped solve problems with the design of the minds underground.
Yourew not poor, right, He was not some like gentleman engineer.
Absolutely, and in fact that's a common element to a lot of these people who become prominent innovators in the industrial ages. They come from quite modest backgrounds. Now there are gradations of poverty, of course, before the divosy. He's not in the poorest of the poor, but he's not middle class. He doesn't grow up in a nice house. He doesn't He can't read and write actually probably until he's an adult. So he figures stuff out by himself.
And he's a tinkerer with machines, and his big breakthrough came when he went up to the coal mine one day and they were having trouble with a new fangled seam engine was pumping water out of the mine and he said, you know what, you know, give me a couple of days and some of my mates and we can fix this. And he did. And the people who owned the coal mine were you know, they were rich people.
They were quite smart for people also, and they say, right, this Stevenson Chap is obviously you know a talent that we should and we should you know, back him and help him solve other problems.
So how does Stevenson get from there to becoming a sort of great entrepreneur slash inventor engineer, Well.
By solving problems really And then the main main problem he solved was how to move the coal. So there was a sort of a mechanical issue what's the best way to transport coal along the railways? But there was also an organization issue. So initially they ran their rails.
This is in the northeast of England, near Newcastle. They ran them like we run roads today, which is, you know, somebody's in charge of the road, but anybody who's got a licensed car can put it on the road and drive somewhere and so there was an enormous amount of confusion and many hilarious stories, with some of them with quite tragic endings about people not giving way to each
other on these limited railways. Stevenson had this vision, if you like, that there was a better way to do this, and that was to have one company owned the rail run the trains. People could provide freight, and of course passengers could step up or not to ride the trains, but you'd have an integrated control over this railway system.
And that's what he persuaded some people to adopt for the Liverpool and Manchester Railway, and in what I think is one of the most amazing moments of human history of nginuity, certainly, he ran a combined Nobel Prize slash bakeoff show to determine who had the best railway engine to run on the rails that he designed and that he had planned. And he was also the winner of
that competition. So there's some interesting conflicts of interest at the beginning of the Industrial Revolution, but his stuff worked. That was a huge event and it brought massive amount of attention to this industry and kicked off what became known as a railway mania, which was the building of railways and the development of the railway system across first England and then Europe and.
Then the world.
Mostly on this show I interview founders of tech companies more or less, and when I was reading about Stevenson, I was like, oh, this guy's like a like a tech founder, He's.
Like people I interview on the show. I mean, do you think that's fair to some extent? Not fair? Like, am I just dreaming?
I think no. I think this parallel. So here's a man with vision. He makes mistakes, he learns the hard way. A lot of these engines blew up, by the way, several of his relatives died in the in the in the shop where they were making engines because it was extremely dangerous business. So he figures stuff out, he learns by doing. He fails fast. I mean these are all
buzzwords of today, of course I think there are. And he gets he gets people with money to back him and proves results and then gets more money and so on. I think the social gap between Stevenson and the elite was was enormous, and there was a famous hearing to review whether or not they could build this Liverpool and Manchester railway in which a top barrister who went on to become a prominent lawyer in the UK working for the government. This rarester just ripped into pieces and Stevenson
was in articulate and he couldn't explain himself. And I think that social gap, that's the size of it. We don't see that today. I think most of the entrepreneurs we come across are well educated, they've gone to college, they're articulate people, and I don't see people rising up from essentially nowhere like Stevenson did to the same extent today as in the early industrial revolutionship.
So, oh, okay, so we've done this story. It's like kind of a little more than one hundred years, right, starting in the seventeen hundreds, going up to the late eighteen hundreds.
What are the.
Lessons of this story about technological change, political power, and how economic gains are shared or not shared.
So I think the main lesson is there's nothing automatic that links technological change, improvements in technology with better outcomes for workers. Certainly that linkage can develop, and it did up in the later nineteenth century. And you know, it was great that that happened, but that was a struggle that had to be one as opposed to something that
happened just because technology, just because technology was changing. So I do think the political dimension of the second half of the nineteenth century, the spreader of democratization in Europe, the US becoming more democratic for example, in the progressive era, those were really important elements linking a technological change to
better outcomes from people. And if that linkage that political language becomes weaker, which it has in the past forty fifty years, then you should be more concerned about what do you only get from potential future technological transformations.
In a minute, Simon and I will talk about what's happening now, what may be coming, and what we can do to maximize the chances that AI will benefit lots of people instead of only a few.
Now back to the show.
By the end of the eighteen hundreds and into the twentieth century, at least in parts of the world, certainly in the United States and in England and in Western Europe, you do have this period when technological innovation, productivity gains
are going along with broad based prosperity gains. Not everywhere, not all the time, but certainly, you know famously in the middle of the twentieth century in the US and in Europe at least, you have this era that is sort of the dream of like things are getting more efficient and workers are getting richer, and it's the version of technological progress that we like because it seems to be good for everybody, or at least very large groups
of people. It is broadly shared prosperity. When, in your view, does that break down that link between technological progress and broadly shared you know, prosperity.
Well, in retrospect, it came under a lot of pressure in the nineteen seventies, and I think it began to
break down really seriously in the nineteen eightiest. Like a lot of these things, I don't think it became clear to people that there was a problem until the nineteen nineties, but by the nineteen nineties there were definitely there was a lot of analysis that said, you know, why approtaivity gain is not becoming higher wages like they used to, and what exactly is broken about this the form of innovation? And I think that's a problem we've grappled with for twenty five years and not yet found.
A solution to.
And you know, it feels like The answer to that is not entirely clear, but I know you make an argument about it in the book, like why do you think it happened?
Well, a combination of factors where automation, the form of automation has become really is really important. Automation is being used primarily to replace people. At the same time, we're not generating a lot of new jobs, new opportunities in the way that we did in the early twentieth century, for example. So we've continued to automate, people have lost those jobs. We've not created a lot of new tasks. And that's partly about added UDEs of them and corporate leadership.
It's partly about the way digital technology has been developed and deployed. It's also, unfortunately about globalization and the interaction between automation and how we've outsourced work to lower income country well.
So globalization is an interesting piece, right because over that period, global inequality has fallen over the last several decades, right to some extent, globalization has led to great wage gains for people who who live in parts of the world that were formerly very, very very poor.
You know, namely China.
The media in person in China is now much richer than they were thirty years ago.
Like that seems good.
Yes, right, So the primary change is about China. There are many poor parts of the world that participated in this, And of course what's also happened in China is productivity gains of outstrip wage gains, so that that wedge has benefited some of the people in the Chinese system, not everybody, but I completely agree that wages have gone up and poverty has declined in China as part of this. So, yes, the Chinese and other countries have benefited from the global
trading system, and that's good. But I think there are better ways to arrange that system, and better ways that would have more inclusion for more people, including the US.
Let's talk more about the US.
Well, what's your worry if things don't change, what do you think the US will be like in five years or ten years? Like, what's the sort of Yeah, what's your prediction if the status quo persists?
So Vonnegut wrote, I think it's his first novel, play a Piano, which he, as I understand it, really wrote and developed in the late nineteen forties. Well, and he imagined a society in which there are a few eats people who have high status who run the machinery, and a lot of people who have make work projects at relatively low wages, low stand living, no prospects, And I think that that inequality of status, inequality of opportunity, inequality.
The people on the public works projects, by the way, are not starving, they are provided for, but that they don't have any future. That stark and rather rigid system, I think is a real possibility in this country. And I think we already have some elements of that, and I think it's problematic and maybe even least to worse social outcomes than Vonnegut you imagined.
And so how do we change that?
So our argument is that artificial intelligence could be beneficial to more people, that it could be empowering, that we could look to waste emphasise more ways to enhance human capabilities. This is not our understanding of the current technological priority from the people who have the dominant visions, people running Google and Microsoft, for example, but we absolutely talk to
them and urge them to move in this direction. We'd like to have more competition for ideas in that market for the same reason, and look for ways to use technology to help humans as opposed to continuing down the road where we've become a little bit too obsessed with how many workers can I fire this quarter by hiring new machines on new algorithms. That I think is a bad dynamic for society.
I mean, unemployment is that is still below four percent. Wages have been going up. They've been going up more rapidly in the past few years, for workers at the lower end of the income distribution, right, I mean, the facts don't seem exactly like you're describing at this moment.
Well, we definitely had a bump up from COVID. Now, COVID was not.
Something before COVID.
Right by the late twenty teens, we were essentially at full employment. Wages were rising across the income distribution. I mean, it's clearly true that it took too long to get to full employment after the financial crisis, but whatever, that's like a fiscal policy story that we don't need to get into here. In terms of technology and labor demand, it feels like there is robust labor demand now, even for relatively unskilled workers.
Labor demand is stronger now than it has been in some recent periods. I absolutely agree. But if you look at that the divergence in incomes of the higher earning and the lower earning. Over the past forty years, twenty percent of that gap has been closed, perhaps a little bit more with the COVID bump, but it's not clear and that look, if the problem solved. Jacob Gray happy to have been a little too worried. But I think the concern is that the underlying dynamics of technological adoption
and what we're doing with technology hasn't changed much. But our view is that the dynamic of deployment of AI and what companies are talking about using AI to do replace customer service, replace workers in various customer facing roles, replace workers in back office, that is going to can continue that previous divergence of real incomes.
So, I mean, you sort of alluded to a few possible responses before, but maybe you could pick a few to talk about in a little more depth. So there are these potential bad outcomes from AI for sort of workers in the middle of the distribution or for lesser skilled workers. What do we do to help those people? How do we reduce those risks? Like what are a few specific things?
So the thing that people talk about all the time and the way you framed it that, Jacob, I think pools that direction. You say, well, people have less skill, let's give them more skill, right, so more education. We're not opposed to that, but we also are trying in this book to talk about the direction of technological change. Who has the visions, who invents things? So this says back to your sort of your your interest in George Stephenson. Who was George Stevenson? Where did he come from? How
did he get this opportunity? Right? And I think what we'd like to encourage is more use of all new technolog including AI, to bring out more George Stephenson's to create more new tasks, to try and become more innovative with this technology in a way that creates opportunity and job.
Nobody's going to be opposed to that, Like sure, everybody, When you say that, I'll say sure, But how do you do that? Like, what is a concrete thing in the world that could cause that to happen?
Well, for example, almost all of the research and development around AI right now, it takes place in a few big companies. There's a very little takes place in any government institute or actually the universities are losing a lot of talent into those companies. What is the priority of those companies It is to make money. What is an alternative set of priorities is to generate new tasks, new opportunities, breakthroughs in technology that we haven't yet.
Money have to happen.
For a more public spirited development of AI to happen, is it public funding for AI development?
Public funding would be important and it has been important in many previous technologies, including development of computer chips and the Internet and modern pharmaceuticals. Often the government does very well when it provides a market of It says we're going to buy things from you if you develop them right. That's what we do with COVID vaccines, for example. So there are various ways that you can put public resources
to work. And in the current conversation in Washington, the good news is those possibilities are not off the table. But I go to some of these conversations take and I wouldn't say it's the top item. It probably struggles to get into the top five. Mostly it's large private sector companies saying, hey, don't get in our way, don't put a lot of rules on us. If you do, then China will take over the world. And that is unfortunately the thrust of that technological conversation right now, whereas
we would suggest you start much more. Okay, what are you trying to invent here? What do we not have? What is the private sector not going to come up with?
And then what's the system of carents? Various kinds of carrots probably no stakes, various kinds of carrots that's going to pull innovative people into this better direction where I agree, you know, it may be a little cloudy exactly what better means, but generally speaking, creating new tasks for people and creating new tasks that the people were previously not highly skilled can do productively, that's a smart way forward.
What is an example of the thing you were just saying of a carrot from the government that would you know, induce people, provide an incentive for people to come up with a direction for AI that would benefit you know, broadly benefit workers, right, this is what we're looking for.
What's an example of that?
Make workers in electrical power grid companies, electrical disputors, make them more make them safeer, make them more productive, to help healthcare workers become more productive and better able to diagnose problems and so on, So a smarter expert advisory system that a nurse practitioner can have. And the really big one, Jacob, which is this one I think is probably worth a bounty, is to actually really finally use AI and education to help again kids with less advantage
and less family resources. And these things have been imagined, but they've not been ever developed at scale so that teachers can actually help students learn better in more tailored fashion using AI type tools, and then get those systems deployed and adopted across public education. None of these are,
of course, are easy problems. That's why they're problems. But education, healthcare workers in critical sectors, including around electricity, clean energy, those would seem to be sensible priorities.
What else are there things you want to talk about that we didn't talk about?
What's very interesting, Jacob, is you dug deeper into the Industrial Revolution pieces of it than many people have, including HA been on lots of good podcasts. But I think that you're absolutely right that it's sort of to understand the sequence of history, to understand these the episodes, and then to think, okay, we're obviously living history people going to look back and say, Okay, this was an episode, but what is this episode? Is this like a continuation
of the nineteen eighties? Is it something brand you? I think that we often exaggerate the moment in which we live because that's the moment in which we're living. Yeah, right, So I always tend to think but but sometimes the crisis of two thousand and eight was different. For example, nine to eleven was different. There are these departures, there are these forks.
The question right now I feel like, is are we just sort of persisting in the same universe we've been in, or is what's happening with AI creating.
An inflection point? To use an overused term.
Right like, is something really new happening with AI right now?
Or are is it going to be more of the same?
So I don't know how big is AI going to be? Unclear? But have we is this a process that is likely to develop deliver big shared benefits? I think a bit worried about that.
You're a bit worried that all the benefits are going to go to a small number of people, and some large number of people will be not helped and potentially harmed.
Right, And you know we have seen episodes in history where the harm can be substantial, it can be widespread, so let's not kid ourselves about that.
We'll be back in a minute with the lightning round. M back to the show before we go, I want to do a lightning round. I want to ask you some fun, somewhat silly questions.
I use a lightning round in my classes, Jacob. I don't forget if I got it from Planetmoni or someone else, but I think the lightning round is a great thing. Just fire fire away, fire away.
Okay.
You are a tennis player, a recreational tennis player. As a tennis player, what is your view of pickleball?
That is a really sensitive question among tennis players. I enjoy pickaball, the whole family can play its barriers to entry. But I understand that some of my tennis playing friends may not be tennis may not want to be my friends anymore.
After I said that, on a slightly less important topic, you used to be the chief economist at the IMF, the International Monetary Fund.
It's the IMF overrated or underrated?
Oh, this sounds like the pickaball question in a different guys.
Equally slightly less controversial than the pickleball question.
The IMF is a very important organization that exists. Almost the entire life of the IMF exists just to the side of the front page of the New York Times, by which I mean you very rarely read anything about all the important things that happened at the IMF, because you know, it's just a little too boring. As far as the New York Times editor is a concern. And that's good because they can get a lot of things done.
They can be constructive, and it's enabled by that particular by the way in which they were positioned relative to the US political system. But they do exist. That they exist just slightly. You know how there's something in your perple vision you can't ever quite focus on. That's where they are with pickball.
Pickleball's right in the middle, man. Pickleball is front and center. What's your favorite novel?
Oh, snow Crash, Neil Stevenson. That's very easy. I reread that every every year or so. So this is a book written came out in the early nineteen nineties, and I originally read it because Paul Kruman said, an economist, if you want to understand the future don't read any futurologists read Neil Stevenson, and in terms of globalization, in terms of technology, in terms of social impact. It's including the metaverse. It's remarkable.
And Crypto, you know, it's funny.
I've thought it was a different book. Actually that was a different series. Crypto was less just as a new author, right, same author. Oh yeah, yeah, just as a Neil Stevenson groupie to be clear that that was the Crypto, the Crypto series, the Money series.
This is the second time in this interview I've thought of sal Khan. I didn't mention it last, but I just interviewed Sel Con of the Con Academy, which you might know of, and I thought of him when you were talking about education, because they are developing AI an AI tutor basically that at the moment is not free, but we'll be free, I suspect quite soon. Also, he loves Neil Stevenson. There's some Neil Stevenson book set. I believe in China where there's like a tablet that has
education and like the masses get the tablet education. We've been trying to book Neil Stevenson, but he doesn't do interviews. So if you ever see.
Him, tell him to call.
We'll do.
Simon Johnson is a professor at MIT. His new book is Power and Progress. Today's show was produced by Edith Russello. It was edited by Sarah Nix and engineered by Amanda K.
Wong.
You can email us at problem at Pushkin dot fm. You can find me on Twitter at Jacob Goldstein. I'm Jacob Goldstein and we'll be back next week with another episode of What's Your Problem.
M