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You know, many people, especially in our industry, just laugh at me, us, uh, when we say we think uh, prices are going to start falling. This is another one of those, well, it's been stuck in the 2 to 3% range. We're not getting out of there. If you look at trueflation, which is um, it measures 10,000 items in real time, inflation is already down to 1.2%.
And yet the Fed is fighting uh this notion that we're up in the two and a half to 3% range and they're going to get it down to 2% by golly. And you know that's how they potentially could overdo it. But I think I think that uh within the next year we'll see inflation below 2% and heading negative. And it is you've got critical to that forecast is productivity growth and uh uh unit labor costs uh continuing to decelerate.
Uh but also we've got gasoline costs coming down. Here in the US we have housing costs, rents starting to come down. Uh at some point people are just going to it's going to become consensus thinking but it is as far away from that right now as you can get. Well, I'm hoping by the end of this podcast that we've invented Kathy Woods law.
Um there seem to be between Moors law, Wright's law, Jevans paradox. There there's seems to be an infinite number of these, but they need they need names. But you know, the one that came up with Elon, I don't know if you watch the whole Elon podcast, but I couldn't believe he told that story about the two economists walking through the woods and they pay each other to eat and it adds $200 to the global economy, but nothing productive is created.
And and that dubtales with Seel's law, you know, which is, hey, if if AI cures breast cancer, and millions and millions of people don't need radi, you know, radio um radiation or chemotherapy, that has the effect of looking like it reduces the GDP. In reality, if you wanted to, you could still go and hang out, you know, and not get the radiation and pay if you wanted to and and then not have the cancer.
And so that it adds huge net value to the world obviously, but it shows up as negative GDP. So the so the GDP metric is fundamentally broken in the age of AI. So maybe Kathy Wood's law fixes this. It it is. Um but there's there's another side to this. I I'm not going to say it's equal and opposite. Uh if you look at uh robotics and you look at the time we spend uh doing things for free, we're not paid to drive our children around.
Uh we're not paid to make dinner and clean up afterwards. Um we're going to unlock a lot of that and that will become paid in the form of we're going to be buying robots. uh that will get into GDP and that never got into GDP for before. It's a little bit like uh what happened uh to the the farm economy here.
The reason people at that time wanted to have lots and lots of children is they paid them room and board and and nothing else. Then we had the industrial revolution uh and of course their their work was not counted in GDP uh because there's GDP equals national income. National income is easier to measure in these days because of the tax system and so forth and they have to equal they have to equal and so we will through robot uh um purchases uh see a lot of GDP coming back to us.
That's a great point. So you take traditional things that aren't measured and you move them into the measured economy and that increases radically. Right. So this this reminds me of a specific data point. I remember talking to VCs who all many missed investing in Uber. And I actually interviewed one of them and said why?
And he said we totally messed up because the taxi market in San Francisco is about 500 million a year. And we figured if Uber takes like 20% of that, that's just not a venture investment because then they only get some chunk of that revenue. What we missed was that the the ride sharing market quadrupled u and they took 80% market share from the taxis.
So you ended up all these people taking rides that you never would dream would take rides, drunk people, etc., etc. And that totally changed the game. Yeah. What's interesting about that is today Uber uh accounts for 1% of all urban miles traveled. This is in big ideas as well. Uh and we've done the analysis.
Talk about puts and takes here about uh GDP and so forth. We've done the analysis that uh to accommodate that 1% of urban miles traveled, it would take only 140,000 cars. Uh to to accommodate all urban miles traveled in the United States, this is um it would take 24 million cars. And when you put into context that uh the number of cars owned in the United States today is it's somewhere around 400 million and the number uh of autos sold every year in the United States is now roughly 15 million.
That tells you the capacityization increase of the robo taxis is going to destroy the auto market as we know it. I I I think going back though, Kathy, I think you you raised a really interesting point that I haven't heard to my knowledge anyone else articulate, which is so many people, including folks on on this pod, are hand ringing about GDP and oh, won't hyperdelation somehow reveal the intrinsic misalignment between GDP growth and real wealth growth?
But you you've I think put your finger on a point I've never heard anyone else articulate which is that as humanity delegates more and more services to to agents that delegation looks like commerce from a GDP perspective that by basically carving up humanity individual humans roles and productive services and subdividing them all of the interactions between those subdivisions many of which are going to be agents add are accretive to GDP and look like commerce.
So if anything, you're you're painting a story for the exact opposite of how GDP statistics can explode in real terms while real wealth perhaps remains constant as well. So I guess my question for you is if you could wave a magic wand and define Kathy Wood's perfect definition not of GDP growth but of real wealth growth for humanity, how would you define it?
Well, wealth growth is very much tied to productivity growth. uh and I'm talking about real wealth growth. I'm not talking about real estate and driven uh you know I'm talking more about uh technologically enabled productivity gains um that you know we got a taste of it just a taste from the 80s and 90s um it was it was the in the pre-in age starting with a PC then pre-in age and um and and pre-mobile age.
But back then, which was a magnificent time for the financial markets, wealth creation uh was stupendous as software for the first time unlocked. We went through a frustrating period in in the 80s. I was there uh where technology it almost seemed as though it was hurting productivity. Um there were some people out there saying that and then of course Microsoft came along and and boom and then we had the internet boom.
Um so that was foreshadowing just foreshadowing what we're going to experience here. So there was if you look at growth growth accelerated not a lot but it accelerated uh certainly from the horrible 70s uh growth rates productivity was I think zero or negative for a good part of the 70s into the early 80s and uh then we saw productivity picking up and the financial markets boomed uh and inflation came down back then and and the reason I've thought about it so much is very early in my career um we we had taken a position [clears throat] that inflation was going to come down.
Most people thought that couldn't happen without a depression. It happened for the opposite reason. It happened because of productivity growth associated with these technologies a sensible monetary policy as well. I will say productivity growth lifted unit growth and the history this is unlike what you would learn um from Keynesian e economics which that's associated with Harvard primarily which says growth is inflationary growth is not inflationary growth is is disinflationary and in this world we're going into it is deflationary deflation in the good sense when a when The price of something drops, the demand for it explodes.
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