Callum Williams: Economics, AI, and Technological Progress — #82
return, well then you say that ten thousand dollars is worth two hundred thousand dollars.
Now, if you were to say instead, let’s look at how much income derived from wealth that’s actually owned, that’s actually live wealth, rather than hypothetical value that exists because you’ve assumed a return. When you do that analysis, you vastly reduce the top tail and therefore it turns out a lot of the wealth inequality that you’ve seen is based on these hypothetical assumptions of returns.
Now, if you do look at, say, the Gini coefficient of earnings, which is one way to measure income inequality, that has remained relatively stable over the past few decades. To be clear, there’s significant income inequality, but it’s been pretty steady, which is a very different story from the wealth inequality narrative which makes it seem like the rich are getting richer at an exponential rate compared to everyone else.
Regarding age, it’s hugely important. Many people in the lower wealth percentiles are younger individuals just starting their careers, and they don’t yet have the assets accumulated that older individuals who’ve been in the workforce for decades do. This skews the wealth numbers significantly.
So, while you can say there are systemic issues in the U.S. regarding wealth concentration, especially with the super wealthy, the implications of wealth inequality need to be carefully examined, controlling for factors like age and understanding how much of that wealth is real versus hypothetical.
In summary, the U.S. is indeed unequal, but when a Martian arrives, we should clarify that inequality manifests in numerous ways and can depend on what metrics one is considering—wealth versus income, for instance—and that age significantly influences the picture. Interest rate then multiplying by twenty thousand dollars, that two hundred thousand dollars is the wealth of which you get a five percent interest rate, you get ten thousand dollars a year. So it’s a sort of calculation, an estimation of wealth rather than directly observing the wealth that someone has at hand.
Now the assumption that…yeah, so the assumption could be stocks, could be air, it could be bonds, could be just bank accounts. The assumption that has typically been made in the Piketty work is to assume that the rate of return across households and the income distribution is the same—so it’s five percent, five percent, five percent, five percent. In reality, it doesn’t quite work that way because often people at the bottom have poor financial literacy and will put all of their income into a bank account that might pay almost no interest, right? Or maybe it pays one percent interest or maybe they buy a certificate of deposit and it pays two percent interest.
Whereas the very rich are disproportionately likely to put all their money into equities or corporate bonds or something where the rate of return is typically higher. So if the rate of return is to be higher for rich people, then once you back it out, the assumed amount of wealth that they’re deriving that income from is much lower. So you get a lot of these kinds of adjustments that are made, and once you do all that, what you typically find is that there has been a kind of U-shape of wealth inequality in the U.S. and lots of other countries, where it was super high in the great Gatsby days and then it fell after World War II.
After governments put in capital controls and wealth taxes and all that kind of stuff, it then since the 1980s has been coming up a bit, but to a much lower degree than what the current Piketty research would suggest.
So just to recap that for the audience, I remember probably it’s been like more than 10 or 15 years when did Piketty’s book come out? It was a while ago, right? The really famous one was around 2012-2013, almost 15 years. That had a huge impact, and I remember looking at it and being very struck by the figures in the book, but I just wasn’t sure how much I should trust his inferences.
Now you’re saying that there’s been a fair amount of empirically grounded pushback against it? Yes, I would say there’s more discussion over the income inequality figures than the wealth inequality figures. My sense is that academics generally believe that the income inequality stuff is more fruitful basically because there are fewer sort of imputations you need to make.
In theory, at least in the U.S., somebody will report all of their income on their tax return, and so you can look at what someone’s income actually is. Whereas for their wealth, they don’t report all of their wealth on their tax return. So if you’re interested in looking at tax returns, which you kind of need to do to understand the finances of the very wealthy, then you’re kind of pushed in the direction of analyzing wealth and wealth inequality.
I have an interest in both; I’m interested in the ultra-high net worth world, high net worth world. But when I put the tweet out, what I was actually interested in, I was just looking for a figure that captured the level of precarity of the really poor. You hear these factoids, like x percent of Americans are one paycheck away from being out on the street and homeless.
I was actually just trying to get at that. Like, is it one percent of the population that’s in that situation? If it’s actually because they have schizophrenia or something, that’s a very different situation from like a single mom who is working really hard but if she loses her job and a couple of bad breaks, she’s living in a car with her kids. I don’t want to live in that country; I want to have a country where that second scenario isn’t happening so much.
So my posting of the Fed numbers was a very poor way of getting at that question for various reasons. But yeah, after some investigation where we finally found data that was normalized by age and all this other stuff, it still does seem like 10-20 percent of Americans, maybe it’s closer to 10 than 20, but some kind of uncomfortably high fraction of the population is living a kind of precarious existence.
That’s kind of what I was getting at, and for the people that I interacted with on Twitter, I was like: look, let’s just figure out where it is, and you tell me if you’re comfortable with this, right? You could say, I’m totally comfortable with this because without that we wouldn’t have breakthroughs in AI or whatever.
People could make that argument right? So do you have any thoughts on what is the best way? It’s a very interesting question. I think the question is…what I would say is that using wealth inequality or wealth data to get at that answer is tricky. The reason why that is, is because wealth accumulation strategies are heavily influenced by the welfare state.
For example, Sweden has extremely high wealth inequality, and now Sweden is, in the eyes of many people, a kind of socialist welfare state paradise. So the question is, why is that? The answer is really because if you’re at the bottom, there is not much of an economic incentive to accumulate wealth because you know that if you face financial difficulty, the state will step in.
There’s no need to insure yourself personally because that’s the purpose of social insurance. What you’ve seen in the U.S. as the welfare state has massively expanded over the 80s, 90s, and 2000s is that the household savings rate has come down markedly. Now, people often point at that data series of a falling household savings rate and say Americans are becoming spendthrift or frivolous or whatever.
In fact, I think a large chunk of that reflects the fact that there’s much less need to insure yourself privately now—you can insure yourself publicly. So I think we need to look at another dataset.
Can I just drill down? Are you saying that these people who are in danger of being kicked out of their rental because they can’t make the rent somehow know that they will be saved at the last minute by government? Or maybe that scenario I have in mind is not happening, because perhaps it’s only Hollywood filmmakers that like to make movies about this happening to people.
Maybe it almost never happens? Is that the answer? Or does government actually save these people from becoming homeless? Because I do see a lot of homeless people.
Well, yeah, absolutely. And we can talk about why that may be. I think it’s wrong to ascribe conscious motivation to economic decisions always, because people make decisions about pricing and about saving strategies based on a lot of unconscious support such as things.
But no, I think it is important to remember that in the U.S., the welfare state has massively expanded. One in eight either people or households in the U.S. is now on food stamps. Medicaid has massively expanded in recent years. It was only during the pandemic that the federal government increased the rates of unemployment benefits by six hundred dollars a week.
There’s been a pretty substantial change, and I think it’s not unreasonable to expect that would affect economic behavior. There may also be evidence of more spending swiftness than there was before as well. These things are obviously overdetermined. I do think that could explain it.
But I think the broader point is that there are probably better ways of capturing what you’re trying to look at. I mean, the best way is actually to look at flows in and out of homelessness, which is difficult but possible. One that people often look at, which has its own problems, is when the Fed conducts surveys that ask people— I forget the exact amount, but it’s something along the lines of: If you had to produce six hundred or eight hundred dollars at a moment’s notice, could you do it?
The answers to that are all quite high, but there are questions about how that survey’s designed and that kind of thing. The other question, which I really have a problem with, is: Do you live paycheck to paycheck? Because some insane proportion of U.S. households, including U.S. households that earn well over 100 grand a year, will say they live paycheck to paycheck.
So there’s a question of: Is it really a meaningful measure of economic precarity? I would say probably not. I think one of the great successes of the U.S. economy and indeed many other economies in the world over the past 10 years is that it has become very easy to find a job by historical standards.
The unemployment rate in the U.S. is like four percent or whatever; it’s pretty low. The unemployment rate in most rich countries is near or at an all-time low, and the share of people actually in work is at an all-time high. If you’re thinking about what are the channels through which people are completely unable to meet their bills, one of the biggest ways is probably because they can’t find work.
That has become less and less likely, not more and more likely over the past few years. But on that four percent number though, this is probably a really basic question that shows I’m not a real economist at all. There’s some other figure which is like the fraction of working-age people who are actually engaged in work, and isn’t that like alarmingly low?
Are there much discouraged workers that just aren’t counted in that four percent or something? Yes, this was much more of a problem in the aftermath of the financial crisis. It is true that labor force participation among both men and women in the U.S. is quite low by international standards.
There’s a crazy stat which was true the last time I checked a few years ago, which was that the labor force participation of Japanese women is higher than American women, which completely blows up the stereotype of Japanese women being very homebound. That has changed in recent years because the labor market’s been so strong.
The only other wrinkle to this is that I would emphasize that the U.S. is unique in having a fairly low labor force participation rate. You look at almost any other rich country, and you don’t have these problems. It’s a particular U.S. phenomenon and there’s this question of why it is. Some economists have argued it’s video games, which obviously can’t be correct because there’s video games outside the U.S.
It could be the opioid stuff and the painkiller stuff, and that seems more plausible. The China shock, as some people have said—that competition from imports from China has destroyed various towns and cities in the U.S.—maybe, but obviously lots of countries have faced the China shock and had this problem. So there is a bit of a puzzle there.
But no, the U.S. is not the best economy in this regard, but things have been improving. It’s amazing how, obviously, you’re a professional following these kinds of issues. I’m just an amateur, but even between us, we don’t have a real feel for like if I go to some rust belt town in Michigan and I meet some 27-year-old who should be working and he’s vigorous and healthy, turns out he’s living in his mother’s basement playing video games all day.
Is that real or is that just some story that journalists find and blow up? We have no idea. Is it one percent? Is it five percent of 27-year-olds? I just have no clue. It’s a really interesting question. It’s also something that’s become much more of a thing in the UK in recent years—this idea that there has been an amazing surge in people taking time off work for mental health reasons.
A massive boom in doctors giving notes to say you are excused from work for three to six months or whatever. I’m open to the idea that this is the product of some kind of generalized societal degradation linked to social media or technology, but no, I agree we don’t have great insight into this.
I think it’s weird, because for the longest time in economic policy getting people into work was like the number one goal. It was the thing that kept politicians up at night quite recently. In the early 2010s, when the U.S. unemployment rates wouldn’t come down, that has now kind of gone away as a topic.
If you look at what Trump was tweeting about when he was president—say 2017-2019—he would always say “jobs, jobs, jobs” in block capitals. He doesn’t tweet that anymore because it’s now seen as assumed that it will be quite easy to find a job. So it’s a really interesting change that’s taking place.
I still have this residual suspicion that there are a lot of people who are not counted in that four percent thing and we’ve just pushed them off to the side—like, well, we don’t worry about them, but for everybody else, it’s four percent, great.
Yes, that is true for the U.S. more than for other countries. On the flip side, the U.S. has created loads of jobs that are probably measured badly by the stats because they’re given to people who are not here legally.
There was this very interesting question about how many jobs are there actually in the U.S. We don’t really know. Let me close this topic off by pointing out—I’m revealing a little bit of your personal information here—but I believe you live near the marina in San Francisco.
That’s true. Okay, now that’s like one of the most expensive upscale places in the world, but also because you live in San Francisco, you don’t have to go very far before you could step in some human feces, see some needles on the ground, maybe witness a store being emptied out by a flash mob or something.
How do you feel about—getting back to this precarity question— is the U.S. a polarized society of big winners who live in the marina and people living in a dystopia? Or is that just overblown?
Well, obviously, in terms of one’s lived experience in San Francisco, that definitely is not overblown, because there are large chunks of the city that the wealth generators of the city—I’m not one of them; I’m a journalist, so I don’t generate anything—don’t go there. They don’t really go downtown; they don’t go to the Tenderloin, even though it’s very close.
The question of why San Francisco has so many people living on the streets and taking drugs is obviously a very complex and difficult question. I have gone back and forth over what is the true cause of this. I was for a long time very convinced by the argument that it was all to do with housing—San Francisco has extremely expensive housing, which is undoubtedly the case.
As a result, even if you are in a pretty well-paying job, it is very difficult to afford a house. The pathway from even a minor disruption to your income and not being able to make the rent strikes me as quite logical. However, I have more recently come to the view that housing plays a role, but perhaps more importantly, it is basically the role of drugs.
You can see people who are mentally and physically in absolute complete crisis. Some of these people are San Francisco natives, but a lot of them are not. I think a lot of them are drawn—despite what a lot of the nonprofits were saying—are drawn to San Francisco because both the supply of drugs is plentiful and also there are lots of well-meaning but I think misguided nonprofits who will support your decision to take drugs and to live on the street.
I don’t think for those people giving them a home is the solution or even the only solution. They did this during the pandemic, where there were lots of hotels in the Tenderloin and downtown where the city government did actually turn over a lot of these hotels to give people homes. It has not made any difference to the problem whatsoever. If anything, it has made it worse. A lot of these hotels, to be honest, were completely destroyed as well.
So it’s really not worked. The question of what we do about it now that we have this problem is even more for me. But I think I don’t see what’s happening downtown San Francisco as a product of American precarity. If anything, it’s the product of like there being a lot of resources.
Let’s move on. Although we have two hours, there are so many interesting things for us to discuss that we could build a whole two hours with just any one of these topics. Another topic we want to discuss is U.S. and European divergence in any number of metrics—GDP per capita, wealth, etc. One of the striking things for me—by coincidence my wife was a visiting professor in the Netherlands in the fall, so I was traveling a bit in Europe, and I saw a lot of things there.
You hear people talking about their net income, which means the income they take home after taxes. Even in sort of rich European countries, let alone in Greece or Italy or something, I was shocked at how low the net, what was considered a healthy, upper-middle-class net income per month was. It could be a couple thousand, three thousand euros or something like that, which would be considered pretty good even for a professional class person.
For Americans, it seems like, wow, these guys are really, I hate to say it this way, but you guys are poorer than the people in Mississippi, right? That’s how the debate often emerges. Enlighten us about what’s really going on. What’s the divergence between the U.S. and Europe?
It’s such an interesting question. I guess I would say two things by way of context. One is that there are ways in which the U.S. has clearly recently diverged from Europe, as you say—GDP perhaps is one. GDP growth has been particularly robust since the pandemic. Asset prices have really gone bananas; I mean, I’m thinking of how the stock market has really taken off in the U.S.
They’ve done this in Europe; investors are basically treating European equities like bonds—they sort of pay out some dividends, but they don’t grow. The second thing I would say is that the U.S. has really, since the 20s or the 30s, been richer than Europe.
So it’s not just because of World War II; it has been richer than Europe, including the U.K. for a long time. I mean, if you talk to people—I had a good conversation with someone at Stanford who had been a Rhodes Scholar at Oxford in the 70s—and asked him what it was like to travel from the U.S. to Oxford in 1973. He was like, you know, it was like going to a different planet; it was so much more than America.
So that’s existed for a long time. The question of whether the U.S. has become substantially richer than Europe in the past few years—which is the kind of Twitter zeitgeisty narrative at the moment—is less clear, I think. What has really happened is that I suppose it ultimately depends on what you’re interested in.
But the thing that I’m interested in is what’s the best measure of living standards. What really matters is what is the bundle of goods and services you’re able to afford, and the best measure of that, I believe—and I think I’m right to believe this—is something called actual individual consumption, which is something the OECD and other stats people produce.
It basically says, how much is the market value of what someone buys with their own cash, with their post-tax cash, plus an assumed market value for the public services they consume—so healthcare if it’s socialized, public education, public transport, the quality of the roads—like that stuff.
It’s measured accurately and at pretty high frequency, and what you see there is that over the past 10-50 years, Europe has actually kept up with America pretty well, and in many cases has actually improved relative to America. To use the example of the Netherlands, the actual individual consumption per person in the Netherlands is higher than in the U.S.
Now, I know that might be sort of odd to square with the conversations you’re having over there, but you know the value of public education and healthcare is very high in the Netherlands. People in the U.S. have to take a big chunk out of their salary to pay for health insurance, while the same pressures don’t exist in the Netherlands.
That helps to close the gap in a big way. The outlook for the European economy, that said, is pretty bad. Despite all of these debates, you’ve got a number of significant structural political impediments to the EU becoming a genuine single market.
The U.S. is a genuine single market, and I think that fact alone will explain more and more the divergence that probably will start to take place, with the U.S. continuing to grow while the EU is going to be kind of trapped in a low-growth system. So some of course, I said this to you, I’m more optimistic when looking at history and the current day, but I am quite pessimistic when thinking about the future.
Got it. You know, this divergence has reached a point where even when I was with other professors, a professor at the University of Amsterdam having dinner with me after I gave a seminar—there were a bunch of physicists there and they were aware that U.S. salaries are way higher, that the Nobel Prize winner at the University of Amsterdam is paid less than maybe paid less than me.
They were aware of this and they started coping, and you know of course they do get free healthcare, but I also get free healthcare through my job, right? So it’s like… but they would even resort to things at dinner like saying things like: yes, but have you been to a grocery store? You know, food is much more expensive in the U.S. than the Netherlands.
I’m like, well, it’s like 20 percent more expensive, but frankly it’s not a big deal in my monthly budget. They would be enraged by that or something. So it does seem like something’s going on; it could just be that the euro… you know, a lot of this just could be FX stuff where the dollar is very strong right now and the euro is very weak.
I mean, that definitely explains the different GDP per capita or GDP measured in dollar terms for sure. But you know, bear in mind, like there was a massive exodus of British academics to the U.S. in the 90s, particularly in the 90s—it was a point where the U.K. economy was actually doing really well.
So, you know, these differences have persisted for a long time. They haven’t materially worsened in recent years would be my guess. And of course, I don’t know, you’ll know more about the Netherlands university system than I do, but my guess is that a lot of it’s publicly run, and the kind of salary pressures there are going much greater than in a lot of the private U.S. universities.
Even the public ones have to match salaries to a much greater degree than they would be the case in Europe. The system is much more competitive here. I go back and forth with this topic because I’m British and go back and forth between here, between San Francisco and London all the time.
I suppose it’s absolutely undeniable that you can earn a much larger salary—particularly in San Francisco, but really anywhere in the U.S. And actually, I think a lot of the public services in the U.S.—the kind of classic complaint from people in the EU or in Europe is that U.S. public services are terrible, which I don’t think is actually true to be honest.
The public transport in San Francisco is actually pretty good. But that said, a lot of the…I think most EU cities are way nicer to live in than most American cities. You’re much less likely to be shot or killed in a car accident, all that kind of stuff. Ultimately, it’s very hard to make a comparison.
By the way, I always lose weight whenever I go to the U.K. There’s something in the food here that is very weird. Even if your lifestyle doesn’t change at all, you always lose weight. They give you huge portions in the U.S. and they don’t in Europe necessarily.
Also, there’s so much walking; you’re walking to the tube and I think you just burn a lot of calories just getting around in Europe, which is healthy, which is good. I would say that I really love being in the Netherlands, because my recollection of it is like riding around on a bike—slightly buzzed most of the time—and of course, no risk, no violence, nothing.
Then you get on this really nice bus or metro system, and everything works. I had real dislocation, because I spent time in Europe, spent time in the U.S., and I also spent some time in China in the fall where the infrastructure is even better than in Europe.
It’s just crazy reconciling how much do people have or what is the material well-being here versus here versus here, because there are these important systematic differences and also purchasing power adjustments that need to be made. It’s just crazy.
Totally. I think one way of thinking about answering this question is, the cleanest way of measuring it is looking at the number of—if you’re considering two countries, like the U.K. or the U.S.—how many Britons live in the U.S. versus how many Americans live in the U.K. Because those flows, I think, will indicate which country is genuinely better to live in.
Now, the problem is that the immigration regimes differ between the two, so it might be easier to move. But it is the case that way more British people live in the U.S. than vice versa. To me, that would suggest that life in the U.S. is better than life in the U.K.
Maybe you could do that for other countries if you’re interested in it—it’s revealed preference. You’ve got loads of Chinese people desperately trying to get into the U.S., so that tells me that life in the U.S. is still better than life in China, despite the better infrastructure.
What’s going to happen in the future? I think you already touched on this. Your main driver was that they’re really not a unified economy; they’re balkanized into small states with their own regulations, etc. There will continue to be a big advantage in growth terms for the U.S. economy. Is that the main driver, or are there other drivers that you want to point to?
I think that’s the thing that ultimately matters. If you’re a company that is in the EU that wants to grow quickly and needs to get a lot of capital, you just can’t get it. You have to get it in the U.S. The capital markets are just so much deeper than in the U.S., and so your incentive to list there and to set up shop there is just much higher.
You talk to people in San Francisco, founders in Europe, and they will say, “We’re growing really well in the U.K. We’d love to expand into other European countries, but it means we now have to translate everything into French, translate everything into Italian, translate everything into German. We have to make sure we’re complying with all the regulations in each of these countries, whereas in the U.S., you just set up shop and you just go boom, because it’s all basically the same.”
The great problem with the single market, which has been the case for a long time—maybe sort of 15 years or so—is that they have completely failed at reducing non-tariff barriers equivalent to services trade. You can now send goods completely freely between all the EU countries, which is great. Germans don’t pay tariffs on French wine or anything, but a German trying to set up a legal service in France, for example, still cannot do that.
As a result, for companies that drive innovation, they’re just not interested in expanding. That’s a big problem. Even with the best of will in the world, even if they do manage to get these tariff and non-tariff barriers down, the language barrier is still a problem. That is still a problem.
Oh yeah, when I mentioned balkanization, language is one of the big factors too. It’s not just the legal regime or the regulatory regime; it’s also language. How much of the delta though between the U.S. and continental Europe is just that we culturally have somehow embraced, rightly or wrongly, a very optimistic view of risk assets and risk-taking?
Apparently, Germans don’t own any stock, right? They don’t own houses either. If you have a culture that doesn’t believe in taking on the equity risk premium, if you know what I’m saying, they just don’t believe that it’s going to pay off for them to tolerate a little short-term volatility. Then they’re screwed, right? Because how can they grow their economy? They’re not going to have deep capital markets.
Some of this is just like a cultural storytelling to yourself or maybe a realization that markets deliver excess returns or something. I think there’s a big sociological part of the story there that totally is, and it’s kind of worse than that because the money that’s not invested in equities and stuff is then invested in government bonds.
You then reduce the cost of your government borrowing, which means you fund the welfare state expansion and that kind of thing. So it becomes this kind of circular problem, which is definitely a big thing. I guess I’m always struck by being in the U.S. and particularly in Silicon Valley with how motivated people are, and it’s kind of cool in a way.
It is also kind of lame in a sense, because everyone in Silicon Valley has enough. If these people were going to apply themselves to learning about Thomas Aquinas or Bosany or something, I would totally support that. But the kind of acquisitiveness—you know, John Stuart Mill talks about this a lot when he visited the U.S.—that kind of acquisitiveness, that need to be constantly richer and more powerful, is both amazing but also quite corrupting.
Whereas you go to someone in Italy or France, and you go to a restaurant or you go to a seaside town or something. It’s just amazing. When you’re there, you think, I don’t need any more than this; this is great. This is enough. There’s a sense of enoughness.
I totally agree with you. I mean, in the Netherlands, as long as the sun was shining—okay, the pitch darkness during winter, that’s a whole different thing—but just kidding. When the weather was good, I definitely felt like, yeah, I could live on a thousand or two thousand euros a month here no problem, and it’s great. I love it.
Why can’t I relax? Why do I feel the need to message this investor about something? That divergence is for sure there, and it doesn’t seem like it’s going away. I mean, it’s interesting because something that comes up a lot online is this idea that Japan has kind of found the answer because the streets are really clean. The food’s amazing; everyone’s really skinny; everyone lives for ages, and so on.
Of course, GDP per capita basically hasn’t grown or GDP hasn’t really grown in many years. When you go to Japan, you’re like, well, actually, maybe a bit like in Italy or something, you think GDP growth is not what it’s cracked up to be. The difficulty is that both in Japan and in the EU, the politics have meant that governments are unable to run budget surpluses or even balance their budgets.
As a result, you have these massive accumulated debts and massive contingent liabilities to pay pensioners for many years to come. You’re in a problem where you really have to increase GDP. If it had genuinely decided to have a zero-growth economy while also balancing the budget and not having massive contingent liabilities to its pensioners, then it genuinely wouldn’t have a problem.
But the reality is that it has to cut its debt-to-GDP ratio because at any moment it could all explode. I mean, what’s interesting is that there are countries that have actually bitten the bullet and are now sorting themselves out. Greece is a really interesting example; it’s kind of gone under the radar.
Greece’s debt-to-GDP ratio has fallen by like 50 to 60 percentage points of GDP in the past four years. That is insane! They got dealt a really good hand—they had high inflation, high nominal GDP growth, and low interest rates. When you get the combination of those three together, that’s a recipe for the debt-to-GDP ratio to collapse very fast.
In addition, they have actually decided to implement reforms after the whole Syriza, Yanis Varoufakis thing, and their economy is growing pretty well. You’re also seeing this in Spain to a degree; you’re seeing this in Portugal. I don’t think Europe is definitely screwed because there are some glimmers of hope, but it’s mostly screwed. Good excellent okay our next big topic AI and jobs, which yes, I believe you actually covered this. This is like one of your focuses, right? Well, I’ve written about most stuff we’ve talked about. Sorry, stuff, but yeah, no, it is. It is. Yeah.
So let me tell you something that struck me recently as you know, an entrepreneur that’s actually working in this space. In our case, we build these AIs that can handle things like customer service and the voice capabilities are really good now. The AIs we build can really answer phones, deal with account issues, delivery issues, ordering food, whatever it is, pretty much at the level that a human can do it and probably cost much less—actually less than one-tenth the hourly rate of humans to do it.
But the rate of adoption is still very modest. When we get a look into these call centers, typically the back-end systems are very antiquated. The humans that manage the call center are very risk-averse because their job is mainly about ensuring nothing can blow up. If something blows up, I will get fired. Some whiz-bangy Silicon Valley guy comes and says, “Hey, this black box is going to replace 80% of your head count,” and the manager, the guy who owns that operation, is thinking to himself, “Wait, I’m going to give away 80% of my head count to this guy, and I have no idea how that black box works. What’s going to happen to my job?” Because after a while, all the future improvements or management of that function are whoever runs the box, not him.
So there’s a huge amount of what I would call human decision-maker friction which is preventing this. Obviously, things should equilibrate. If I can do the same job at one-tenth the cost for you, you would think there’s going to be some equilibration. But the time scale is just shockingly long. There’s just so much resistance to it. It’s not kind of this dystopian singularity resistance where they think, “Oh, AI is going to kill us,” or “AI is bad.” It’s actually just very mundane friction that prevents these organizations from shifting their workflow.
One interesting thing for me is that even though in this narrow space we have delivered an AI that can do the job, the adoption is still extremely low, and it’s going to take years before it really is a big chunk of the total work hours in the space.
So any reaction to that?
Yeah, it’s super interesting. I think the way you outlined it was theoretically really interesting because there’s a kind of principal-agent problem, isn’t there? Because it’s like a sort of public choice theory problem where the guy who has the decision over an efficiency improvement, which would be in the benefit or in the interest of the company at large, doesn’t work in his interest or her interest, so he says, “No thanks.”
I told you, just to give you an anecdote, we were talking to the guy who owns the entire customer support function for one of the major food delivery functions—I don’t want to say the name of the actual company, but you know, Uber Eats, DoorDash, that kind of thing. He runs it; a big chunk of it is run out of the Philippines because that’s the lowest-cost English-speaking workforce they can use. He just told us flat out, “Well, my company is very technologically advanced because it wasn’t a startup that long ago, and so we’re kind of building out a lot of these systems ourselves. But if you go to somebody who has my job at a more traditional company, a company that is like 30 years old instead of like 10 years old, that guy’s just going to listen to you, he’s going to take your meeting; he’s probably got pressure from his CFO because the CFO reads these articles in The Economist about AI and says, ‘Why aren’t you delivering savings to me?’ That’s the main pressure for the guy. He’s got to act like he’s exploring AI, but he doesn’t want to buy the system from you. It’s just a headache for him, it’s a risk for him, and he’s just going to stall you long enough so that he can retire or get another gig, basically. That’s literally what we were told by the guy who owns the CX function for a huge organization.
So I feel like people who theorize about the deployment of AI in the economy just don’t have a granular picture of what it really looks like to the guy trying to sell the system to you. That’s really interesting the way you’ve outlined that. The stuff that I’ve written about has definitely been on the more bearish side of things. I mean, there’s this interesting kind of divergence that’s taking place in the U.S. and other commercial colonies over recent years, which is that consumer adoption of tech has been very rapid. You see those classic graphs about how long it took for a chance to reach 100 million users; for example, it was like three days or whatever it was.
How long it took Threads to reach 100 million users? It was like one day or whatever. So, everyone’s got an iPhone and all that kind of stuff. There’s this kind of sense that technology is moving faster than ever. But if you then look at what businesses are doing, and you know businesses are the ones who drive productivity growth, there has been this really interesting and very marked slowdown in productivity growth at the business level really since the financial crisis.
But even before, innovations come along and just people are not interested in them. The OECD has good data around like how long it took for half of American businesses to even have a website, right? It took ages. I mean, a website, right? It wasn’t until like the 2000s. Or fax machines is another similar story; fax machines definitely hung around. It’s much worse than in Europe, but there are many European countries where if you want to buy something off a website, like the thing is on the website, but you then have to phone or email someone to buy the thing. They’ll send it to you and all this kind of stuff.
So yeah, I think that’s absolutely right. The best data set I think for this is from a Census Bureau. It’s kind of been gone weirdly under the radar, but they have a very frequent—I think it’s every two weeks—survey of many, many businesses, thousands, possibly hundreds of thousands of businesses, where one of the questions they ask is, “How many are you meaningfully using AI to do something big in your organization?” And it’s gone from sort of like four to five percent in September 2023 to like seven percent today. So basically not much of an increase, but you know, something.
It’s seen a higher increase when you weight by employment. The big companies that have more staff are more likely to take on AI. So maybe you’re going to go to like 12 or 13 with some of the problems of AI. Even I have been surprised by how slow it’s been, and it’s a bit like the Russia-Ukraine thing where what happened in March 2023 when GPT-4 came out was like people would say adoption is going to be slow but just wait until 2024 and then it’s really going to take off. Then 2024 comes along and it’s like adoption is slow but just wait until the fall of 2024 or early 2025 and like you still haven’t seen that.
Of course, you know—I mean this is even before going to the question of like is there an impact on jobs, is there an impact on productivity growth? No, there isn’t. I find it very odd that there are a lot—I won’t name anyone—but there are lots of people working at very prestigious universities as economists who are just very oddly unwilling to face this problem, even to discuss it.
I don’t understand what problem they’re facing—the slowness of adoption or the slowness of productivity growth? You know, there’ll be some new invention and people will say this is going to change everything, and then in practice nothing really happens. Eventually, I’ll be proven wrong, I’m sure, but for now I think the place where I’ve seen some discussion of this in economic history, people use this term technology diffusion. When they do look-backs, they are aware of how long it took to go from, like, “Oh, everybody has electric access to electrical power, if they want it,” but then like how do you reorganize your factory to really exploit this electricity? It could take decades, right?
People don’t want to think AI is going to be like that, but my experience is that it’s not going to be that long, but it is longer than people expect. I really like your characterization of okay in our daily lives if we see something that’s good, we adopt it right away. No principal-agent problem, right? This thing answers the bad emails, the tiresome emails that I get. I will just turn it on, and if it could actually do that, then I would not have to answer these tiresome emails.
But in a company setting, you typically have more of a principal-agent problem or a kind of bigger organizational problem in trying to deploy something. Eventually, because you’ve kind of got two variables, kind of axes, and on one axis is the complexity of the technology, which I would think compared to something like the tractor on a farm or electricity or the factory system, a sort of GPT model doesn’t strike me as—you don’t have to make that many changes to adopt it in some way.
You don’t have to invest an enormous amount in a whole new factory or a whole new tractor. But then the other axis is the complexity of the firms that are adopting the technology. The average size of the U.S. firm is obviously much larger now than it was in the days of electricity and the days of the tractor, and ownership and decision-making is much more diffuse than it used to be. It’s much more bureaucratic. So I wonder if that results in slower adoption of technology for a given complexity of that technology.
Does that make sense?
Yeah, I think definitely the complexity of the firm because the number of people have to get their heads around it and agree to it. Actually, even in a lot of cases where they are rolling out AI, they’re like, “We can’t talk about this too much because the company doesn’t want bad optics if they’re clearly laying off a bunch of people.” So it’s sensitive in that way.
But yeah, that’s interesting. One of the interesting things is like the call center business is very good because it’s a little bit like you said. It’s not that complex in the sense that the connection that goes to the headset that the human is using to service incoming calls, there’s literally an API where I’m connecting this information that generates the sounds. Some IP packets, and my engineer can interface with their engineer, and we can just make sure those packets go to the AI in the cloud instead of through the headset.
It’s not that much work; they’re not re-engineering some heavy machinery in the factory. As you were saying, it’s literally like I’m plugging in the AI in place of the person. They still are worried because they know, “Oh, what are the problems with the human? That lady was pretty good until she got addicted to meth and then we fired her, and this person comes in late, but this person’s a hard worker but doesn’t adapt very well when we shift the scripts.”
It’s a ball of management problems that they’re very familiar with, and the people that are on top of those organizations have been doing that for 20 years, managing AIs to do certain tasks. Now I bring them this totally alien thing which they have no idea what the hell it is. Even though I turn it on for one percent of your calls and we’ll send you the transcripts, you’ll see it’s doing a fantastic job, better than your average human, it’s still a huge shift in their thinking.
It could be that intuitively they kind of know there are a bunch of tail risks in the AI technology that they don’t really know, and they are totally different from the tail risks from their existing human staff. They may be intuiting that, “Well, wait, they’re selling me something that looks really good, but it could all go down one day, and then I’m just screwed.”
How does someone who’s not a technologist evaluate those sorts of tail risk scenarios? They have no idea how common or uncommon what could happen is; it could get hacked, right? And all of a sudden, like, we have to turn off our entire customer service. There’s just all these uncertainties that I think keep them from embracing it. The people that would embrace it would be like, “I’m a founder, I’m in a growth-stage company, and we’re selling so much of our product that we need a CX function, but I’m building it de novo, and I’m going to build it using the best tech, and I’m just going to roll out AIs. You know it’s mostly AIs and a few humans to handle the really complex cases.”
They’re comfortable making that adaptation, but for existing companies, it’s just a battle. It’s a battle to get them to—very interesting.
I guess that means that, again thinking out loud here, if you’re bullish on AI, then what you’re reliant on to a degree is the flow of new companies coming onto the market?
Yes, but I guess the issue there is that the rate of entrepreneurship, despite rising a bit during the pandemic, is still way down on its average in the 60s and 70s and stuff. So that flow is lower than it would otherwise be, which means that that kind of creative destruction, that churn, happens more slowly than you’d want it to.
In fast food, we actually operate in the space. Taco Bell is rolling out nationwide. It wasn’t hard for me in Michigan to find a Taco Bell outlet that had the AI. You’re in your drive-through and you talk to the AI, and you can order your food. It’s pretty good actually. The woman or the guy who used to take the order inside the kitchen with a headset on is still listening and can get pulled in, but mostly you can just give the whole order to the AI, and the order goes into the kitchen and then they give it to you.
But Taco Bell has kind of been the leader, and all these other firms—they’re talking to their franchisees. It’s a very complicated conversation because a franchisee might not want it or they’re worried about it. To what degree can the parent company dictate it to the franchisee? Sometimes the franchisee is more tech-forward and wants to roll a system out, and the parent corporation won’t let them. It’s a really inhomogeneous situation right now in food ordering, but the AIs are fully capable of doing food ordering better than humans at this stage. It’s going to take at least a few years before you see it everywhere.
Absolutely. I mean, what about the question of does what the customers expect or what the people think the customers will want come into it as well?
Absolutely! It’s uncertainty, right? You don’t know whether people are going to get really pissed off at you. Like, “I hate the AI role!” How are you going to know? If you put yourself in their shoes, the decision makers at Taco Bell—there’s the corporate and then there’s also all the franchisees who all have different opinions about how this is going to play out. Is this going to suddenly tank my sales, or is it going to grow my sales? There’s a lot of decision-making uncertainty with this stuff.
I think this also gets to, and this is quite speculative as well, but I think there’s been this shift in the West, and you can see this in some parts of the data, where people are much more interested in avoiding big losses than in making big gains—loss aversion. Massive loss aversion. It’s got worse over recent decades, possibly because we got rich, possibly because social media means that any failure you might have is broadcast to the world or whatever.
Who knows?
Anyway, I think if you then switch to the Magnificent Seven and you say, “Wow, what are these valuations based on?” So we have this huge, I would say bubble in the Magnificent Seven. If you don’t think it’s a bubble, how’s it going to pay off for you? Is it because eventually there’s so much utility generated by AI that the earnings of the Magnificent Seven—you know, Microsoft starts making tons of money because Taco Bell is using their AI on the back end and all these agents are replacing people and stuff.
But is the time scale for that not a few years but five or ten years? Are investors going to keep those valuations where they are while the actual revenues are very slow to materialize, much slower than expected to materialize? Or is none of what I’m saying important because we’re going to get to superintelligence, and all of a sudden, like, the thing invents a cure for cancer overnight for us, and that’s where all the cars come from?
There’s lots of aversion there, right? Because if you’re the company that doesn’t massively invest in data centers, and then your capacitors manage to find the cure for cancer or whatever, then you look like an idiot. There’s that. I think there’s another Goldman’s Sachs argument from their head of equity research or something which is like, “You know they’re spending roughly a trillion dollars over the next 45 years on AI.” What’s the trillion-dollar problem they are solving? Unclear, I think, as you say, because it’s the deployment problem.
But then you go back to the companies and the people who are bullish on the companies and say, “Yes, but if you look at capex relative to cash flows, you know information technology, that ratio went completely nuts in like the late 90s in the tech bubble when they were investing hugely in capex but just had actually no cash flows to back it up whatsoever.” The ratio now is kind of in line with the long-term average because, since the pandemic, they’ve just basically since the pandemic, they’ve just become even more money-printing machines than they were before.
In a sense, you could say it might not be sustainable, but it might not be a big problem, I guess would be the argument. But I don’t know. I mean, as you say, the market is still expecting massive revenue growth at these companies over four years and years and years. I think these companies had a once-in-a-generation shock, a positive shock to revenue and earnings, which is basically the shift to working from home because the pandemic. Fingers crossed, you’re not going to get that again.
To go from five percent of people working at home to 12 percent, that’s a huge earnings positive shock to Magnificent Seven. Will that happen again? Probably not. I just go back and forth on this question for sure. I don’t know the answer.
You know, I’m right in the trenches on this because I’m one of the guys who’s trying to generate the revenue that on the back end—at least before DeepSeek came along, that back-end revenue would go back to OpenAI or whatever. Now it might not. In fact, we’ve checked, and we can swap in these open-source DeepSeek models perfectly fine for what we were doing before, which was using, say, OpenAI or something like that.
That—I mean, Microsoft’s argument is their revenues. What you hear from the company is the revenues from Microsoft’s AI business have increased much faster to a much higher level, much more quickly than their revenues from Azure did, and yet they’re spending about the same or only a little bit more on AI capex than they were on cloud capex. There’s no problem now.
I mean, that might be true, of course, it then raises the question. I would wonder if what counts as AI spending is much harder to measure, I think, maybe. What counts as your spending? I don’t know if that’s right, but you can imagine that some lackey who’s like an upper-middle manager would be quite incentivized to count things as AI spending that might not be AI spending to make the numbers end up.
But I don’t know. I think the thing that we do, where we’re literally replacing human labor with AI labor, and we can really see what the return on investment is—these more fuzzy things where, like, “Oh, your meeting got transcribed and you have a nice summary of the meeting,” and it’s like, “Wow, that is magic! We could not have imagined years ago that that was possible.”
But what is the actual productivity gain from that? Did I actually get any productivity gain? Oh, I have a nice summary of the meeting, and I could look at the transcript if I want to. But I think that makes Microsoft some money because somebody is paying for that service, right? Although then maybe they’re doing—but yeah, the way the whole thing is going to settle out is still somewhat mysterious to me.
Yes, I mean, there is that sort of joke about, “Hey, either person one gets notes and asks to turn it into a PowerPoint presentation, or person two takes a PowerPoint presentation and asks us to turn it into notes.” I mean, there is this interesting—I think there’s a lot of non-productive churn that’s going on right now, actually.
There is this kind of thing that you get that is explored again by some historians and I think may also apply to AI, which is this idea that it’s sort of a bad thing for productivity when the costs of producing content go down a lot. So, you know, I think these are very simplistic correlations, but like the relationship between the length of the U.S. tax code and the ease of writing stuff out on a computer and printing it out, right?
Yes, there’s something there. You can imagine this world where a huge amount of AI slop is being sent around, both internally within companies and externally. I will tell you a story which you might enjoy that was a shocking experience to me. Another startup that I’m involved in, which is in genomics and it uses AI but a different kind of AI than Gen AI.
We were looking at a proposal from the Saudi government to build a lab there. The CEO asked—not that I’m in the day-to-day operations of the company, but I’m on the board, so I was kind of involved peripherally in this meeting. She asked this very junior person on her business team to look into some of the details about, like, how hard is it to hire people in Saudi? Can you fire? You know, just basically what it’s like to operate there.
So I got pulled into this meeting, and this young lady is giving a presentation to us about what she learned about researching just what it’s like to operate a business in KSA. I’m listening and I’m like, “You know, she’s really not saying very much, is she? Does she really know what she’s talking about?”
Then I realized the whole presentation was AI slop. The way this woman had done her research was she probably just asked ChatGPT the questions that the CEO wanted answers to. Those were important questions—she should go online and find out what’s the minimum salary, what’s employment law, what do leases look like, what are the regulations on laboratory research—there were real questions to be answered. But she got superficial, lousy AI slop answers, and I was about to throw my glass through the screen of my TV because I wasted like half an hour listening to this. I was like, “Wait a minute. I’m not getting any deep information from this. This is just slop!”
I realized she just got it from GPT, so yeah, that negative productivity totally. Absolutely. I think that’s a real risk. The other kind of more subtle risk I think which I’m very convinced by is this adaptation of a Paul Graham argument, which is like when you get somebody else to do your writing or searching for you, the process of thinking stops.
I really think that’s quite a profound insight because I know this myself from being a journalist. There are some things where the only way to learn about something is to try and write it out in a clear way, and you really discover very quickly you don’t know. If you’ve got someone to do it for you, you’re not formulating your own arguments and critically trying to lay it out; readers are going to hold you to account. You’re like, “That’s a different kind of processing than just like cut and paste from what they said.”
There was a nice presentation; there was PowerPoint there. I’m like, “Wait a minute, but this is not answering our questions. We need to know the answer to this, this, and this just before we decide to greenlight this.” You didn’t answer my questions, right?
I think it also raises the question of the experts who are involved in finding texts that are maybe not out of print or not readily available online—things that you have to go to a library for or you have to get from eight books or something. There are really interesting ideas or old documentaries on the BBC that no one’s seen for years and years. The insights you can get from that, I think the value of kind of taste, I suppose, will go up quite a lot when there’s so much consensus information that’s so easy to find.
I think the danger is a lot of people don’t—like you and I have some idea of what’s going on when they train these AIs, but a lot of people have no idea. So they don’t realize it’s giving them consensus slop back. Imagine you’re not super high on the cognitive scale; you’re just kind of an average person, and you’re being told to research something. You don’t realize what you’re getting back is some average slop, right?
Consensus slop! I think a lot of junior people at sort of ordinary firms could get caught up in that without knowing it. I think they already are! I hear lots of anecdotes about precisely this, where some senior person is like, “What the hell have you just produced?”
They’re like, “You just wasted my time with this?” It was a crazy experience; it was a shock to me.
Alright, so we’re running low on time. Last question. We’ve talked before about the concept of stagnation and productivity growth, technological innovation. Our friend Tyler Cowen and Patrick Collison are active in researching this area. It’s called Progress Studies, and it studies how do economies and societies really progress? What are the main factors that control the rate? How does technology diffuse?
What’s something interesting I think that you and I talked about last time we saw each other? I think Tyler has thrown in the towel because he’s now saying like, “Well, you know what? I was wrong because all the time I was complaining about the slow rate of progress and stagnation while I was complaining they built this AI, and I love this AI, and now I can see there was progress. I just wasn’t aware of it, and now I think progress is going to be super fast because of AI.”
What do you think of Tyler’s point of view?
Well, my personal view would be that Tyler is way too bullish on AI, but that’s sort of one thing. I think the point he made with Cowen but also Peter Thiel has argued for a long time is that once you take a step back from what is bits and atoms or something and look at atoms, which is real stuff in the economy, then I think it is pretty obvious that there has been some slowdown—a marked slowdown, actually—in progress or in kind of the quality of life broadly defined.
If you think about things like travel speeds around most countries are falling, having been increasing for a long time. Certainly in the UK, you know, during the 19th century and 20th century, the average miles per hour of a trip was going up and up and up, and that has plateaued and now is falling.
You look at things like how quickly it takes to put up a building; that takes ages now. San Francisco put up the Golden Gate Bridge in three years! The Empire State Building went up in a year! But that will never happen now. Things like—I guess this is a bit closer to bits—but the quality of a telephone call; it sounds incredibly analog, but like telephone calls don’t have terrible audio quality, and it just hasn’t really improved in many years.
It was interesting because, you know, when PCTO was on Joe Rogan’s podcast a few months ago, I think Rogan put to him what I think is the typical objection to his ideas, which is like, “Aren’t we surrounded by amazing technology all the time?” I was quite surprised by how PCTO was oddly quite sort of like he wasn’t able to respond very quickly to that objection. The one he ended up doing, I think, was that we haven’t landed on the moon since 1971, which again is a great example. Why haven’t we landed on the moon? It’s nuts!
I think there are loads of examples. I don’t think that like AI, which obviously is amazing because it is amazing—I use it all the time—but the notion that AI by itself undoes all of that stagnation strikes me as just completely wrong.
My view on this is that the basic observations about average velocities of travel have not changed, and the time taken to put up a building has increased a lot. I think those observations are all true. Some of them, maybe for the buildings, it is bureaucracy and red tape; it’s maybe not a technology thing. But for some stuff like, “Oh, could we fly around at 5,000 miles per hour instead of 500 miles per hour?” There are real kind of physics limitations. So there’s a low-hanging fruit story where we picked a lot of the low-hanging fruit, and now the rate of progress is just slower.
One thing I would say in that context, though, is that if instead of looking at macroscopic things like how fast we fly around or our buildings, if you go the other direction and look at nanotechnology—what we can engineer on a microchip—that has improved by factors of a million. So we did get factors of millions relative to, say, the computer that they used on the Apollo mission. We did get that, and that is why we have AI now.
So we did—our mastery of the physical world really shifted toward the quantum world, toward the nano world, but we mastered it, and it’s kind of invisible to most people because most people don’t really understand what semiconductor physics is or something like that.
That’s integral to like, “Wow, this AI thing is passing the Turing test!” right? And that wouldn’t happen if we just didn’t have like factors of a million in compute advance. Totally agree, but I think that’s the atoms vs. bits point.
Where I would kind of like berate Peter a little bit on this is your bits: we can do the bits because literally on the atoms side, okay, fine, yes, we mastered the atoms, but we didn’t master making planes that can fly 5,000 miles an hour. But we did master the atoms, and that’s why we’re able to move the bits around for you, right?
Yes.
I guess my only counter to that I suppose would be to say that I think the regulatory system in which technology operates is as important as the tech itself in a sort of all else equal sense. To use the example of the airplane speed, I mean my understanding is that average air or maximum airplane speed in the U.S. has been fixed for many decades.
We would very easily be able to go 20 to 30 percent faster, as indeed we did with Concord, but the regulations were such that we’re not allowed to do that. The government plays a big role, and there’s a hard thing. Because if you’re supersonic, there are all kinds of bad things like sonic booms, and the fuel usage grows like the velocity squared.
There are reasons why we kept out at a certain level, and we just don’t want to be flying around at 5,000 miles per hour because then you get a plasma layer in front of your plane, and it’s a real problem for the pilot. There are actual hidden things here that really come from physics that people just really aren’t aware of for macro. I totally agree; I just think we’re way short of that frontier.
The advent of the TSA in 2002 or whatever it was has surely caused net social losses in the billions to hundreds of billions, right? I would differentiate between some bureaucratic or social system things that are holding us back and like physics sometimes is holding us back.
I think one of the big stories which I think people are slowly coming around to because of the big data centers’ power story is we basically left this whole nuclear thing on the table. If you talk to physicists in the 50s and you read science fiction from the 50s, they all assumed we were going to have basically unlimited energy and actually be using nuclear-powered spaceships and stuff very soon because we could have done it.
But people were just so irrationally scared of nuclear energy for the last 50 to 60 years that we didn’t do any of it, and now we’re kind of reconsidering our irrational fear of nuclear energy. We can now do a look back on, “Well, how many people in France got killed by nuclear energy? How many people in Japan got killed by nuclear energy?” Almost none, right?
We can both have a very long look-back period for safety, and it’s becoming more of an acute issue to generate clean energy. The historians will look back and go, “Wow, these apes got to the nuclear frontier and then they just didn’t improve it for 50 or 60 years, and then they started.” Very interesting.
Yeah, so Callum, it’s been great chatting with you. You know, maybe we could do a regular series where we just come in, and you enlighten us on specifically economic topics. That would be—I’d love that because there’s a lot of—it’s one of those things that gets really bad coverage and especially online; it’s going to be really bad.
So that sounds great.
Great! Alright, well thanks a lot.
Thanks, Steve.