Hopefully I can keep up with the quality that everybody's given you so far. So, I want to thank you for the opportunity to speak today about artificial intelligence. AI is a powerful and rapidly advancing technology that captured everyone's attention. Now, if you've watched enough sci-fi, you know that major technological change is either dystopian or utopian. Either the robots take over the world or they help save it. Now, these polarized views are also common among economists and technologists. On one side, they're the doomers, those convinced that new technologies will destroy jobs, widen inequality, and concentrate power. On the other side, they're the techno optimists. Those convinced we're on the brink of an unprecedented leap in productivity, growth, and creativity if we just let the technology proliferate. Now, as usual, the truth is probably somewhere in between. So the job of an economic policy maker is to separate hype from hyperbole from hard data and sound analysis and understand what AI really means for growth, productivity in the broader economy. So I'm going to focus on three aspects of major technological change that repeat through history. First, technological change is a constant in our lives and it is almost always disruptive. It upends the way we work and socialize. Second, it alters existing power relationships in unsettling ways. And finally, technological change reliably raises productivity and our standard of living while improving the quality of our lives. My intent is to describe how AI is likely to affect our lives along these three lines and how it differs from past technological changes. Now, we have always had technological changes that dramatically transform the economy in our daily lives. In the 1880s, electricity was still a curiosity reserved for a few wealthy urban people and some limited industrial uses. By 1920, half of homes had electricity. By 1940, nearly half had a refrigerator. And by 1945, 85% of homes were electrified. So in about 60 years we went from a very few homes to 85% of the US households being covered by electricity. Now automobiles were another example. Its use rose rapidly. Auto registrations rose from 140,000 in 1906 to 23 million in 1929. Which is amazing given that the total number of households was less than 30 million. 23 million and less than 30 million households. So almost everybody had a car. Now these advances change daily life in profound ways. Another aspect of technological change is the speed at which technologies are being adopted. In the past 50 years, we've experienced adoption of new technologies twice as fast as what I just described. Personal computers were widespread within 20 years, the internet in 12 years, and it only took six years for smartphones to become universal. And AI is moving even more rapidly than that. Now, I tend to believe that the transition for workers affected by AI will be accelerated also, but no one really knows. Such predictions are certainly beyond my powers as an economic policy maker. So I'll limit myself to the here and now. The point of this discussion is that technological change is a constant in our lives. It is always happening and it will continue to happen. And AI seems to be following the pattern of ever faster adoption and change. Now although it's a constant in our lives, technology also disrupts our lives every time new innovation appears. The way that we work and produce output changes. Jobs disappear. New ones appear. Our social lives are disrupted as well, often in good ways, but sometimes not so good. We used to write letters and mail them to communicate with our loved ones. This took time and was expensive. Now we text or use FaceTime or Zoom to communicate with friends and families anytime. This makes it easier to maintain relationships across geography and time, but it can also undermine those social connections. When I walk into a party and I see half the people staring at their phone, it's not a lot of good social interaction. So technology disruption, like anything else, has benefits and costs. That's the way economists think about the world. But as I will argue later, I believe that we need to let this disruption occur to recognize the benefits alongside the cost to enable us to lead better lives. Now, my second point was that technological innovation can alter power relationships in profound ways. When Gutenberg invented the printing press, he took away the Catholic Church's power over the written word and democratized it. When personal computers appeared, power shifted from those who manage mainframes to individual users. When the internet arrived, the control of news, information, and opinion pieces shifted from major news outlets to anyone with a web page. And AI will do the same. It will take power from experts and shift it to non-experts. Much like Gutenberg's printing press, AI will democratize expertise. Tools that once required specialized training are already becoming accessible to a much wider range of people. We see this happening with software coding already. A nurse using an AI diagnostic tool or a technician relying on a generative model to troubleshoot complex equipment can perform much higher order tasks more efficiently. This will also likely happen for scientific discovery. So those who collected economic rents or excess payments for their power and expertise, they're going to lose control of that power and those rents. But this will improve our lives in the process. Now whenever a new technology emerges, the first question economists get is about jobs. Will this replace people or make them more productive? The challenge is that with innovation, there is often a time inconsistency between the cost and the benefits. The disruptions come first. The benefits take time. When a new technology appears, it's always easier to see the jobs that are likely to disappear. But it's much harder to see the ones that will be created. When automobiles came on the scene, it was easy to see that if you were a saddle maker, your job was gone. But what wasn't obvious was that the saddle maker skills could be used to make car seats and that higher productivity auto production would create more and much higher paying jobs. 10 years ago, this is one of my favorite examples. If I had said there was something called TikTok and it would arrive soon, you would all say whatever, what is this thing? But now, and at that time, it would have been very hard to imagine that or that social media would create what is now an established occupation, an influencer. I like to call myself an influencer sometimes. I just don't get paid for it. And the pattern appears to be repeating only faster. A recent study by Stanford economists found that employment has fallen about 13% in occupations most exposed to AI relative to those less affected. Those contractions have appeared mainly in support administrative roles, fields that tend to be automated first. This early effect from AI is consistent with what I've been hearing from business contacts around the US. Retailers in particular are cutting back on employment for call centers and IT related occupations. So far, most say this is being handled through attrition, but a number of retailers say there's a potential for downsizing next year. That is also a message from the New York Fed survey that finds very few businesses are reporting AI induced layoffs. They are instead using the technology to retrain employees. That said, AI is influencing recruiting for these firms with some scaling back hiring because of AI and others adding workers who are proficient in its use. Looking ahead, however, layoffs and reduction in hiring plans due to AI use are expected to increase from everything I hear, especially for workers with a college degree. It's that disruption of expertise, and a college degree is a form of expertise. Returning to my final point, history has shown us that technology improves productivity and our standard of living. We initially always talk about how it will be a substitute for labor. This was the basic premise behind Karl Marx's theory of capitalism. Machines would replace humans in production which would raise unemployment so high that social revolution would occur leading to the end of capitalism and the rise of a socialist utopia. Yet the Marxist theory makes one fundamental mistake which is failing to see that capital and labor are complements not substitutes. More machines mean a firm can produce more output but that also requires more labor as well. This is obvious if you look at economic data. The US capital stock, machines, equipment, everything we have measured in constant prices to control for inflation is 7 times larger now than it was in 1950. Seven times. Yet the unemployment rate in September 1950 was 4.4%. And it is 4.3% as of August 2025. This is why economists are typically techno optimists. History has repeatedly shown that adopting new technologies leads to economic growth and greater employment, not less. Technological disruption is one form of a concept that economists have studied since Joseph Schumpeter named it in 1942. Creative destruction. This topic has never been more relevant. And I note that just last week, a share of the Nobel Prize in Economics was awarded to two economists who explored how productivity enhancing disruption raises living standards. Now, there will surely be losers and winners from AI. I make no doubt about that. But aside from questions about how AI's gains will be distributed, there's a more fundamental matter of how they will be measured, even at a macro level. Firms are using AI to increase productivity. That's the payoff for a profit maximizing firm. This gain in producing more output with the same inputs is counted in gross domestic product. And as a result, you're getting more output, the same number of inputs. Productivity per unit of input goes up and that raises GDP and productivity growth. Now in America, one common feature of great technological innovation has been an onslaught of competition that has rapidly driven down cost and resulted in rapid and widespread adoption. If hardware and software innovation continue to drive down the cost of AI, then I see few barriers to its ongoing proliferation throughout the economy. That prospect clearly is driving the surge of AI investment we have seen and whether it will continue will depend in part on whether AI delivers on the productivity increases that I believe it will bring. So labor productivity measures output per hour of work. The data is volatile but the average growth of productivity over the past few years is slower over the last decade than the previous decade. A crucial question is whether AI will contribute to a resurgence in productivity growth. Any sustained productivity growth above 2% will tend to support rising real incomes and living standards without inflationary pressure. As a monetary policy maker, I'm hoping that that happens with AI. While we often focus on how technology enhances market activity and productivity and measured output, it also enhances the value of non-market-based activities. For example, Google Maps allows me to navigate foreign cities easier and faster when I'm sightseeing. Now, while that value to me is not measured in GDP because it's not a market-based activity, it clearly makes my life better. So, a lot of technology doesn't always have to show up in productivity statistics. It just makes my life easier and better. Now, agentic AI has the potential to save me lots of leisure time that would have otherwise been spent planning vacations, paying bills, and making medical appointments. But if these time-saving AI activities free me up to do more market-based production, then GDP will increase from these non-market savings of my time. I have no doubt that AI will boost GDP and national income, but many of its benefits may be improving our lives in a non-market way. Now, every technology that changes how we live and work brings both promise and risk. Economists, nothing's free. AI is no exception. Fraud, disinformation, bias, and cyber security threats are already emerging through the use of AI. Any tool powerful enough to improve lives can also be misused. The task for policy makers is to manage those risks without slowing the innovation that drives growth. History shows that adaptation, not avoidance, is what sustains progress. Each wave of technology has disrupted industries and employment. But over time, it has lifted productivity, raised our real incomes, and improved our standard of living. Now, we see different approaches to managing the disruption that occurs with technological change. Europe has often chosen to regulate first to contain potential harms before the technology fully develops. The United States is taking a different path, leaning on its tradition of experimentation and market dynamism. That openness has long been the US's competitive advantage. It allowed the United States to lead in early waves of technology from the internet to advanced computing. And it will do the same with AI. Over time, that willingness to experiment has translated into faster productivity growth and stronger economic performance than many of our peers, including Europe. 30 years ago, the United States embraced a new and disruptive technology, the worldwide web. It seems so quaint now. Europe was more cautious, weighed down by regulation and legacy industries that sought to control this innovation. The result, of course, is that America led a global technological revolution that disrupted media and other industries, but also delivered jobs and broadly shared prosperity that handily outpaced the European Union over those 30 years. Perhaps the most important legacy of the American innovation of network communications and computing was the culture of entrepreneurship and innovation it fostered. One that has in fact contributed to America's leadership in AI. The American tradition is to invent and make use of technology, not shrink from it. Where there are risks, we take reasonable steps to mitigate them rather than to seek to avoid them altogether. Risk-taking is at the heart of our market economy. It fuels innovation and we must preserve it. Much like leaders in this audience, the Federal Reserve is also learning by doing. I have championed a systemwide approach to continually educate our teams and enable experimentation with the latest wave of innovations from large language models and agentic AI to applications in coding and payments. That's why on October 21st, next Tuesday, mark your calendars, I'm convening industry leaders to discuss AI in payments as part of our payments innovation conference. These engagements combined with our own hands-on technical research allows us to apply these technologies within the Fed and to support innovation across the private sector. So to conclude, thank you for bearing with me. AI is moving faster than previous waves of innovation. That velocity means both the disruptions and the benefits will arrive sooner. The challenge is to keep pace, to help workers and firms adjust so the gains in efficiency translate into higher real wages and sustain growth across the economy. For policymakers, we must let the disruption occur and trust that the long run benefits will exceed any short run cost. Thank you very much.
