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Good morning everyone. I'd hope that we'd start by talking about productivity and some of the data that you've just said, well, no one really knows. And the question with AI and the US economy is what has happened thus far? Right? And so I'll hit you with some of the official data that I've been tracking, and you can tell me whether the utility of it or not. Right, which is really in US productivity? I always go with the Bureau of Labor Statistics measure of output per hour x non
farm business sector. Right, And if you look at the data over fifty years, that chart was really interesting, the side by side of electricity and AI over fifty years, the average quarterly reading is about one point nine percent annual rate on productivity. But something's happened in the last ten quarters where it's higher, Yes, you know, just under three percent two point seven percent. Do we really know what that is? And is it AI?
We don't know.
I mean, that's the part that makes it hard is in productivity numbers, especially when they're happening in what I would think of as real time, it's very challenging to assess or draw it back to exactly what the factors are that have shaped it. You know, in fact, people still don't agree on what happened in the nineties all the time if you look at research. So it's just
something to keep in mind. So then what you do would any good economist or person, any industry person would do, is they'd say, well.
What am I seeing? What am I seeing?
And so right now, while we can't find it in the macro studies, it would do very sophisticated empirical econometrics and ask the questions how much of this is AI. We still can see that there's something going on there. The question is is it happening? The question is how long will it persist? And so clearly something's happening in
the economy. But if you make a series to go back to your question about productivity, if you make a series of one time adjustments, so say you automate a production line or you use AI to help in loan application process, you save money once. You don't save money forever. I mean, you keep saving that money, but you don't get growth out of that. You don't get productivity growth. You get one time adjustments to the level of productivity of.
Your employees or your process.
So what we're looking for is a technology to give us consistently good changes in productivity so that all industries at scale get better, industries figure out new ways to generate revenue, new ways to do product design, new ideas to come and shape the economy. That's the thing that has a sustained productivity growth part. So it's undeniable productivity growth has gone up. What's not as clear is how long will that last.
Broadly, people want to see and understand how AI impacts workforce and more recently maybe inflation. So if we go back to the nineties and what green Span saw in productivity gains contributing to economic growth, there was a consideration around both of those things. Absolutely, you said that it's not the playbook to go back to what happened nineties and apply today, But what do you see in those things?
Is it possible that AI is driving productivity games resulting in economic growth, but without the inflation it is.
Absolutely possible and something we have to interrogate. I mean, right now, as you know to well, inflation still above our target are two percent target, and price level has been high for much higher for a long time, and people are feeling stretched by the high inflation that they see. And now oftentimes people say, well, now AI is going to take hurt the labor market, and so now I'm
in double doom, as people say. But I think ultimately the way you think many people think about AI is the investment part of any technology can actually boost demand for good services in people and can then raise the pressure on inflation. But then the productivity part comes and that that's a disinflationary part.
You can see.
This is all about the timing, and so what we end up investigating is not just the models but asking questions. Are the buildout of data centers raising prices for construction workers, are the buildout of data centers raising prices for metals and other things that go into them? The raw materials are the productivity gains. And then on the other side of that, are the productivity gains already affecting the cost
structure of firms? Do they see that and even if a series of one off adjustments can actually change the cost structure, And if you look at profit margins when prices haven't been raising as rapidly as they once were, and firms are saying they don't have as much power to pass through, you would think that they're doing something to help margin protection. And so I think this is
there's something going on here. Whether we wanted to link it all back to AI and then use that as a demonstrated proof that we're in a transformative state, I think that's a little bit too far, but certainly something's happening. And thinking about the productivity growth is exactly what you know we did back in the nineteen nineties. We saw evidence firms were being more productive. We were interrogating how long that would last. And interestingly, the nineteen nineties when
I said it was the Roaring nineties that followed. It was good growth, but it was also a good labor market, a really strong labor market, and so those two things went together. Because ultimately we had this conversation in the roundtable and one of the participants made a great point, it's true economics.
This is how economics works.
Is if an employee using AI gets much more productive, you hire more of them.
Right, not fewer of them.
So you know, the economy grows faster, the product development goes goes faster, and demand gets stronger.
I'm going to jump ahead to data center I'd been saving it, but it's highly relevant to San Jose the build out of data center. Very recently, the CEO of PG and E, Patty Poppy, Game on the program and made the argument that it's possible that the data center build out within PG and e's jurisdiction actually brings down wholesale electricity prices because the hyperscalas take on the capital
burden and they are buyers and aggregate of electricity. But many people, you know, your constituents in the twelfth district will find it hard to see that argument playing out.
Well, I think we have to separate what we're talking about into now, next, later.
So let's think about now.
Right now, we have more demand than we have supply for energy for electricity. Right if you talk to you, we regularly have CEO round tables with the big power companies across the twelfth district. You can look throughout the nation. Demand for power is higher than the supply of power, and there's a lot of reasons why supply is falling behind. One is demand's just gone up rapidly, but another part is that they've got an aging infrastructure. They have to
get those things built out. It's a highly regulated industry, so the infrastructure doesn't just come on like a light switch. Then you have there are supply chain issues that made it hard to get the transformers and other things. So all of this just adds to the imbalance of demand versus supply. But the remedy for that isn't to take away demand, it's to increase supply.
So when.
They talk about any CEO of a power company says, we can solve this problem by adding more supply. Absolutely, but that's a next and later. And so what you said, my constituents, what consumers and businesses are saying is I'm worried my electricity prices are going to rise, and they've already been going up. And the CEOs of power companies are saying, but if we just keep building, that will go down, and both are true.
Go down as far as it will be disinflation.
And you know, it's hard to say energy could be disinflationary if we get to a point where supply is greater than demand. Right now, I'm just looking for a supply to equal demand, and that would be a big benefit to consumers because it would mean that we wouldn't keep seeing inflationary pressure coming out of the energy sector.
The other thing I wanted to ask you through the lens of constituents of the twelfth districts is one reason you might focus on productivity is there is a direct read through to GDP growth and other data sets that you can look at. But the anxiety in the real world is, well, a job, an AI talk can make me more productive or it can displace me altogether. Where do you see that tension in the economy right now?
So one of the.
Things that is true is that the labor market has slowed, but it slowed for a whole variety of reasons. And much like when you said, well, productivity is risen, Mary, so shouldn't we isn't that AI? I think we always want to be a little humble about the correlations we see and ascribing.
Causality to them.
So I wanted to temper your enthusiasm for thinking all the productivity growth is AI might be, but it could just be general cost management in a slowing economy or a slowing you know, or to manage tariff costs, etc.
So on the labor market. The labor market is slowing.
It's slowing in industries that are directly telling us that they're using AI and it's slowing in industries that aren't. So it's one of the things that I just want to be cautious. So what I talk to, We talked to workers, We talk to you know, communities all the time. What's true is in technologies is a really interesting thing. No technology ever reduces net employment, not in the history of technologies, but it does change what that employment looks like.
And so there's a period of replacement right now. It's replacement of tasks. So if your job has certain tasks in it, AI can do those for you. And the next part is augmentation, so every place augment and create. What's interesting about AI is that, unlike say electricity, when the candle lighters or the lamplighters or the candle makers got displaced before the US completely became electrified, you know that this is going more quickly if you go to a firm. I was on a panel at the Reagan
National Library Economic Forum with Patrick Collison from Sprint. I'm Sprints, right, Gosh, Stripe, Sorry, he's going to kill me, Stripe, don't tell him, okay, but from Stripe, and and interestingly he said, I am hiring more coders that I'm laying off, but I am laying off coders whose technology skills didn't advance or they weren't the right workers.
And you're seeing this right.
You're seeing you know, businesses reskill them their cells to meet the AI moment, and that's going to cause worker anxiety. And right now, worker anxiety is high. People were a low firing, low hiring environment. That's already going to make people feel vulnerable. If you haven't found a job and you're newly minted out of college, you just think I was supposed to get a job before I graduated. Now I still don't have one. That's very worriesome to people.
And then if you're thinking, well, I might lose my job, but I don't know how long it will take to get another one, then you're worried about that. So I think it's natural for the sentiment to feel nervous. But it's not the same things. AI is taking all the jobs, because what we're really seeing is AIS is replacing tasks, augmenting workers. When we talk to firms, most of those firms are saying I'm augmenting my workforce.
If you're in big.
Manufacturing firms, they don't have enough workers that do skilled labor, and so they're looking to augment their workforce, and then we're also seeing jobs created. It's interesting I gave this talk. I gave a talk on this in twenty twenty three, and I used prompt engineers as the jobs they were creating. But those jobs are now being replaced.
But a.
Or it's a change, it's.
A warning, you could think of it that way. Or it's an indicator. So let's take the warning. The warning is you can't keep up. I would say, let's use it as an indicator. It's an indicator that technology is evolving really fast and workforces need to skill endurable skills, and durable skills.
Are be AI ready?
Be able to use AI to lift yourself in the educational space. You know, use the use the technologies that are out there to build your skills up, because you can learn a lot fast if you train yourself to look at AI.
Say give me a lesson on how.
To write I've been thinking about this, how to write a smart contract from end to end? What sort of software would I need? How would I do it? What would the code look like? How would I test the code? How would I know it's right? Before I execute on this smart contract, and so you can do these things in an evening and then it's just about being able to do that. So I think that's the message for workers, and I would have taught my young self this same thing.
Is if you put off technology because you're afraid of it, then you won't be in the first place of trying to use the technology to further your own abilities.
Can we extend that to the FED? Now bear with me on that one. Okay, all right, you talked about disaggregated data but also improved measurement, citing Greenspan in that sense. If AI is so good, can it process larger sets of data and make more accurate economic forecasts than traditional FED models?
Can? We know we don't right now use AI in our monetary policy work, but we do use it in research as researchers. If you go to any academic institution, you're going to see researchers using AI to see what they can do better on coding and other things, but also data analytics.
What do you see The place.
We are there is AI doesn't give you answers to problems. It helps you get to the discovery perspective. So if I use AI as a researcher to look at a bunch of data. I still have to test my hypothesis. I have to go in with a hypothesis. What am I trying to answer? So that's the human person. And so that's why it's not particularly well tooled right now to replace our forecasters and our thinkers, our scholars who.
Comproduce a more accurate neutral rates.
For example, Well, you're still going to get estimates that are between eleven and negative three on the neutral rate of interest, So I'm not kidding. Models can the models that we have can produce an estimate from negative three to positive eleven, right, And so there.
What does that tell you?
The the neutral rate of interest is not a truth with a capital T.
It's an estimate.
It's a theoretical construct to help us understand how to benchmark policy. But you can't use it as a threshold that you can do surgical adjustments around. No one calibrates monetary policy surgically with a neutral rate of interest estimate for those reasons. So we are using AI though at the FED, and many people may be surprised about that. Would you like to learn about that?
Yes? Please help?
So I know many might think I work in an institution that waits for elect we're still getting electricity. You might think that, but no, we actually are not the earliest adopters because remember we're fiduciary stewarts of public funds but also as fiduciary stewards of public trust, and so we really have to make sure that we're working in the most risk free and risk managed environment we possibly can't. But we have been at this since really in twenty
twenty three. So the first thing that we did it as a system, and I'll really speak about the twelve at a reserve banks that are across the country. We worked as a system to say, well, we need to make sure our employees, our teams are ready to understand AI.
So what do we need to do.
We need to have lessons, work playing, you know, work gatherings, et cetera, get people familiar and get people focused in areas that we can practice with. So we built a practice environment that was completely ring fenced and not in production. Right, it's just a practice environment trying it out, and of course we got what most businesses got. The other businesses did exactly the same thing.
And what do you get? You get the early adopters.
But the good news about our early adopters as are often ambassadors. So then we're holding like tech cafes and things to help other people learn that.
So that was then.
So then in twenty twenty four and twenty five we really made a full court press push March Madness is coming up.
You know.
We really went hard at making sure that people had not just the if they're interested, do it, but that this is something that we really want.
You to learn.
This is the operations within the system.
This is the operations. I should have said that before. I'm sorry. Let'll tell you that if you were at a reserve bank, and again little known facts. These are like facts that people don't know about the FED if you go to a reserve bank or any of our operations. Most of the people who work with us are operations people. We process cash, We do all the electronic payment system backbones,
make sure they operate on time. If you're in the financial sector, you know FED wire or acch FED Now all of that is operated by.
Our operations teams. We also support Vice Chair.
Bowman in supervision of banks and all of those things. And then we have all our support people who help make sure that that occurs. All of that can be easily if you can do AI and you can use it, you can think of opportunities. So the next thing we did,
get our workforce ready is number one. For next thing you do is and this is again like all the businesses we talk to, you see what your vendors are our offering, right if you're you have a technology vendor, an accounting vendor, an HR vendor, and then you just turn the service on. But if you turn the service on before your team is ready, you don't really get
an ROI out of it. So again, fiduciary stewarts of public funds, we have to make sure so we're all instilled in this ring fenced proprietary environment because the public has to know that we're not introducing risk to this.
And then of course the place we're.
Working now is where many many people are working, which is if you have a lot of technology workers, then the coding assist is just so important and we're one of the things back to workforce. It doesn't create a massive change in who you have working for you. What it means is they can do their work faster, better and more effectively. And if you think of the three timples of the FED, we need to be efficient, effective.
And resilient.
So it also builds in that resilience for us because we have you know, quality assurance and unit testing. All the things that can slow you down if you're not right or interrupture your ability to serve. Those things can
all be assisted with AI in a really positive way. So, again not monetary policy, but definitely like all other companies who are working on this space, making sure we're not behind and delivering good value for I mean, the shareholders of the FED are the American people, and we owe them the effort to make sure we're modernizing ourselves and keeping up with the things that can help us do our work faster, better, and more effective.
I do have two questions relating to AI and monetary policy quickly, and I know we want to get some audience questions as well, some conscious there are students in the room who will go out into the workforce. I think that the main thing reflecting back on the nineties is that there are anticipated impacts yes from AI on the economy and PCEE is the preferred gauge inflation running
higher beyond two percent. How do you manage that. You know, many would argue that those anticipated AI driven productivity gains would justify lower rates, but they are that anticipated, yeah, and.
I think that, you know, really, it's important to recognize that monetary policy is a forward looking business, but it's also an evidence based business. And so there will be a point in time when we'll have enough confidence that the anticipated effects are materializing. And where would you look for that? You look for that in what's happening with
price pressures? Not just aggregate inflation, but if you disaggregate it and you ask yourself a question, are the AI using sectors just doing less pass through of input costs into prices? Well, maybe that tells you something. So that's where the research really becomes important.
You ask questions.
But you also do research where you can disaggregate firms, you can disaggregate prices, and you can ask where do we see price pressure.
And how do we think they will evolve.
That's so that's important, and you can't wait because remember Monterrey policy as a twelve to eighteen month lag So right now we're modestly restrictive, slightly restrictive depending on who you talk to. If you have a neutral rate of around three percent interest. Remember that's the one with the big range. But if you have a neutral rate of interest, think this is around three percent. We have some ways to go seventy five basis points roughly before we get
to that level. But we need to get inflation down and we need to make sure that it's on a good path. I'm certainly looking at AI and productivity growth as one mechanism that continues to help us bring inflation leve but we also have restrictive policy and other factors that are all bringing in.
How are you thinking about the labor market now, particularly post January jobs, which showed essentially the most hiring in more than a year. It was an interesting data point.
Well, you know, one of the things that I'll offer here, and it's something probably most of us stone.
I mean, you don't look at.
I'd look at it a lot, but is that a lot of the job growth in our nation right now is located in health care and education. And while it's not bad to have jobs growing in health care and education, if you look at the rest of the economy, there hasn't really been any job growth, and in fact, there's been job decline, you know, negative job growth.
Basically job losses.
And so that just makes me put an underscore on this idea that the labor market has a no hiring, no firing that's already making you a little vulnerable to a negative shock pushing you below.
But also if all your jobs.
Are in health care and education, think of all those workers trained for other sectors who are not and are not getting opportunities.
And I think that's.
Where, you know, we have more work to do to make sure that there's no vulnerability doesn't turn into fragility. But that's less about AI and more about the diversified growth in the economy. And if companies are able to really see positive output growth as uncertainty for the positive demand growth as the uncertainty decreases, then I think, you know, that's a possibility that would be a positive boost for
the economy. So then it's about should we look at a positive boost for the economy as an inflationary event or should we think that a positive boost for the economy comes with AI and doesn't actually induce inflation.
So diversity in the economy is where I want to end it before we take audience questions. One of the features on the show regularly is compensation in the field of AI, stock based compensation, competitive salaries, the newly minted millionaires in the field, who you know buying property in San Francisco but within the twelfth district. One of the things I always reflect on is if I drive from the Bay Area down to Socou on the five or the one to one, it's the agricultural sector this state
in particular. But you could expand that to the other regions of the district. There's a big sort of contrast there. Could you reflect on both, you know, what you see at the high end of the tech sector and what you do or do not see in agriculture. Feeling benefit from AI, well.
You know, it's interesting.
So we have, as I said, we have roundtables, and I have one this morning, but I have them with all kinds of industries. I like to do them by industry. So we had an agricultural roundtable. How are you using AI surprisingly for ahead of where you'd think, right, they're using it to do everything from you know, think about idea generation. How do you get better crops, more weather resistant, drought resistant, fire resistant, you know, there's all smoke resistant.
AI can help there because it can help generate ideas. Another thing they're doing is using AI to think about what's the right planting season?
Right, how do I forecast weather?
It's predictive, it's predictive and so, and then of course using it in their plants and processing to help augment their technology along the production line. So AI is something. This is why I think it's more pervasive than many understand, is that we've had travel and entertainment, We've had consumer retail, we've had builders, commercial developers, agricultural, you name it. Everybody's trying to see how this can make their business work better.
And the question is when we finished this part which I think we've been in of using it for cost management and just getting your budgets right, is it going to start to change into revenue generation etc. We're seeing the seeds of that, using it for product development, etc. But that's the uncertainty around this is when does it move from something that's just in the development stages and with electricity, the wealthy urban areas had it and the
rural areas didn't. In in this could this go faster? Is the diffusion of AI and its use cases faster? And we had a great discussion at this roundtable this morning, and the tail to share and I'm not sharing all of our points, so it is still Chathamhouse rules, guys. But seriously, the learning is you know, there's a lot of perspectives out there that say that AI could be an equalizing force, and I think we need to interrogate is an an equalizing force? As vigorously as we interrogate,
could it be driving further inequality. I don't think we know the answer to that, and I under I'll end with this.
In the end, the decision is going to be ours. It's not gonna be the technologies.
The technologies don't you know, kind of inherently decide.
We decide.
We're going to take a couple of quick questions from the audience. But while we find the mic, oh, we have some in advance. I know that in the room. We're here at San Jose State University, which.
I'm very excited to be at.
You know, there are there are those that will soon be going into the workforce here. One of them is student questioned tough one, what advice do you have for new economists, especially those with a desire to enter public service. We got in a little bit about how the fed and fed a reserve Bank of San Francisco is or isn't using AI but reflect on that.
Sure absolutely, So first of all, I will just say thank you. You're an economist and you're going into public service. Fantastic. Seriously, we need people like yourselves who are interested in doing this. This is a very fantastic career. I would call it a vocation to be in public service and serving on the types of things that are the federal reserves and other public institutions missions.
So that's important.
The important thing about public service that I think is overlooked is one of the biggest skills you have to have as an economist is being a detective. And a detective never gets satisfied by looking at one thing. You test your theories, you dig deeper. You're never really satisfied. You know, people ask me, Mary, why are you constantly curious and never really satisfied with the answers? And I said, because you basically, the minute you get confident, you lose.
You want to be confident in the moment and humble enough to ask again, is this right?
And why would it be wrong? And how do you do that?
So that's an important thing I see that you know, AI is a technology, it's not a miracle, and so it's about how you find a way to relate to AI that makes you better, a better detective if you're an economist, a better public servant if you choose to work in that field.
And that's how I use it.
I'm always trying to make myself better at serving those who I've got the responsibility to serve, and doing that with a technology or with just being out in the factory floor and learning how.
Businesses are doing it. That's the magic there.
So you don't get yourself monoligned into only one skill. It's really about having the detective range of skills and recognizing those skills have to change to meet a changing environment, but to also meet the moment. The skills I developed in the mid nineties, I've certainly had to change and augment those to be able to do my job today present daily.
Quite a few of the other questions are on the other side of the remit, which is regulation. You know, in your speech you mentioned that financial services the financial sector early adopters in many ways, and the question is how do you balance regulation that ensure safety within the financial system but also allows them to innovate, move faster.
So I do have to say because this is a weird aspect of fetter reserve.
I don't know if it's weird.
I think it's right, but it's a unique aspect of fetter reserves system. The Reserve Bank presidents don't do any regular superviser and we don't even do any supervision. That's all left with Vice Chairbowman and she at the border governors, and the rules get made by the full border governors, not the Reserve Bank presidents. That said, we can talk about regulation more generally, not just in financial services. And
there's always attention. If you're an economist, you know this, if your business you know this, right, there's always attension. If you let fully unregulated innovation occur, you could do customer and consumer harm.
If you do so much regulation.
That no innovation occurs, well then you will end in stasis. And so somewhere in the middle is where the nation has to go. Nations, and we have historically had a very robust financial sector in the United States that's facilitated a lot of intermediation and growth and sort of allowed us to be the country that we've been in terms of doing.
Things so we don't want that to stop.
But as new tools and technologies come out, it's not about cutting them off. It's really about thinking about how they can be done safely but still innovatively. And I think that magic place is not something you get to and then you're always there. It's constant recalibration, constantly asking the question, you know, the bridle is too tight, or the reins too tight, or are they too lose. It's very much like monetary policy in that way. You know, you don't get to a point and say great, we
want victory. You actually are always know if you've ever ridden a horse, and if you haven't, I apologize, But if you've ever ridden a horse, it's not my first vocation. You know, if you pull too tight it stops on a diamond, you're over the head, And if you let go too much, it runs too fast and you're over the back. So it's basically trying to manage the bridles so that you get the innovation you want without exposing consumers or other businesses or the society to harm.
Let me ask a final question and will end on I guess a positive note. Oh good? Which data sets and what you see in the real world, because you still go out into the real world, gives you most optimism about the impact that AI will have on the US economy, and specifically that of the twelfth twelfth District.
So I will say that, you know, when I first came to this job in nineteen ninety six, I am going to work at the San Francisco feder Reserve. And I had been to California a year before, down at Southern California at the Rand Institute, and I remember going to a conference there and we met a lot of business people thinking about not AI, but something else. And I came home and I told my wife, We've got
to go there. It's filled with entrepreneurs. It's filled with people who have never heard the word no. They just heard why not right. And what's interesting about the twelfth District is all of those people don't live in California.
They live in Utah, they live in Idaho, they live in Vegas. You know, they live.
In the entire inter mountain west west of the Rockies. And I'm not saying anything about other places. They're all very innovative too, But there is something here that gives me optimism because it's not that people say, well, AI is coming, and let me figure out how to you know, not be eaten up by it. It's like AI is here, let's figure out how to harness this tool to create a better business, a better economy. And really the thing that gets me jazzed and optimistic is people talk about
a better world. How do we make things better for people? How do we change education so there's more quality, How do we help the globe have more opportunity? How do we harness what's sitting here in front of us with all these people, into something powerful that changes lives and livelihoods.
So that's what gets me optimistic. And it's not this.
They're just not talking about what they might do. They don't stay if I said now, next, later, there's not too many conversations with people who live out here who talk about way later. They're all talking about now and next. That gets me excited.
With that, all that's left to do is to thank the Silicon Valley Leadership Group, San Jose State University, our hosts, and some Francisco fore the Reserve Bank President Mary C. Daily, thank you very
Much, Thank you appreciate it.