AI, the Economy, and Financial Stability
At the 2025 Federal Reserve Bank of Cleveland Financial Stability Conference, Cleveland, Ohio
在俄亥俄州克利夫兰举行的 2025 年克利夫兰联邦储备银行金融稳定会议上
Thank you, Director Knotek, for the kind introduction.
谢谢 Knotek 主任的热情介绍。
It is a pleasure to be with you today and to be back in Cleveland and the beautiful Fourth district.
很高兴今天能与大家见面并回到克利夫兰和美丽的第四区。
1 It is always a pleasure to visit the Federal Reserve Bank of Cleveland—and all the Reserve Banks.
1 参观克利夫兰联邦储备银行以及所有储备银行总是令人愉快的。
The hard work and dedication of Reserve Bank staff, leadership, and directors help ensure the economic well-being of communities across the country, including in Ohio, Pennsylvania, West Virginia, and Kentucky.
储备银行工作人员、领导层和董事的辛勤工作和奉献精神有助于确保全国各地社区的经济福祉，包括俄亥俄州、宾夕法尼亚州、西弗吉尼亚州和肯塔基州。
One of the many important roles the Reserve Banks have is to be the connection between policymakers and families, workers, and businesses in every corner of the country.
储备银行的众多重要作用之一就是成为全国各地政策制定者与家庭、工人和企业之间的联系。
That allows us to be well-informed and to make the best decisions for the benefit of all Americans.
这使我们能够充分了解情况并为所有美国人的利益做出最佳决策。
I thank everyone here at the Cleveland Fed for their service.
我感谢克利夫兰联邦储备银行所有人的服务。
As we are gathered to discuss financial stability in an era of rapid economic and technological transformation, I would like to turn our attention to what many see as a significant catalyst of change: artificial intelligence (AI).
当我们聚集在一起讨论经济和技术快速转型时代的金融稳定性时，我想将我们的注意力转向许多人认为是变革的重要催化剂：人工智能（AI）。
Today, I will talk about how I approach thinking about AI .
今天，我将谈谈我如何思考人工智能。
First, I will build on remarks I gave earlier this month and discuss how I see AI affecting the economy through the lens of the dual mandate given to the Federal Reserve by Congress to pursue maximum employment and price stability.
首先，我将在本月早些时候发表的讲话的基础上，从国会赋予美联储追求就业最大化和价格稳定的双重使命的角度，讨论我如何看待人工智能对经济的影响。
2 Next, I will discuss AI in the context of financial stability because a stable and resilient financial system is, of course, critical to achieve that dual mandate.
2 接下来，我将在金融稳定的背景下讨论人工智能，因为稳定且有弹性的金融体系对于实现这一双重使命当然至关重要。
I will do so by highlighting some of the findings in our recently released Financial Stability Report (FSR).
为此，我将重点介绍我们最近发布的金融稳定报告（FSR）中的一些发现。
And finally, I will discuss how the current period compares with another recent period of notable technological change—the late 1990s.
最后，我将讨论当前时期与最近另一个显着技术变革时期（20 世纪 90 年代末）的比较。
Afterwards, I would be happy to answer your questions.
之后，我很乐意回答您的问题。
AI technology has been advancing at an extraordinary pace in recent years.
近年来，人工智能技术以惊人的速度发展。
3 Hundreds of millions of people now regularly use AI to write and translate documents, obtain practical guidance on a variety of topics, and search for information.
3 现在，数亿人经常使用人工智能撰写和翻译文档、获取各种主题的实用指导以及搜索信息。
4 A recent report from the St. Louis Fed showed that in August almost 55 percent of working-age adults said they used generative AI for personal or work use, up notably from a year earlier.
4 圣路易斯联储最近的一份报告显示，8 月份近 55% 的工作年龄成年人表示，他们将生成式人工智能用于个人或工作用途，显着高于一年前。
5 Businesses are increasingly adopting AI, with use cases clearly moving from the experimentation phase to operations.
5 企业越来越多地采用人工智能，用例明显从实验阶段转向运营阶段。
In the financial industry, AI adoption rates are even higher.
在金融行业，人工智能的采用率甚至更高。
6 And while it may take some time before we see its full effects, many believe that AI has the potential to generate substantial change across the economy and to be a valuable tool for people all around the world.
6 虽然我们可能需要一段时间才能看到其全部影响，但许多人相信人工智能有潜力给整个经济带来重大变革，并成为世界各地人民的宝贵工具。
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AI and the Dual Mandate I see, as many others do, the promise for AI technology to be transformative, perhaps in ways as dramatic as past technological achievements, such as the printing press, steam engine, and the internet.
人工智能和双重使命 和许多其他人一样，我看到人工智能技术有望带来变革，也许会像过去的技术成就一样引人注目，例如印刷机、蒸汽机和互联网。
When I think about the macroeconomic consequences of AI, I consider how it will affect both sides of our dual mandate.
当我思考人工智能的宏观经济后果时，我会考虑它将如何影响我们双重使命的双方。
AI can enable a worker to complete in seconds or a few minutes tasks that previously took many minutes, if not hours.
人工智能可以让工作人员在几秒钟或几分钟内完成以前需要花费几分钟甚至几小时的任务。
Already, it is boosting worker productivity in a wide range of industries and occupations, including customer service, logistics, computer programming, and medical research.
它已经在提高许多行业和职业的工人生产力，包括客户服务、物流、计算机编程和医学研究。
Increased productivity leads to economic growth, which may also create new employment opportunities.
生产力的提高会带来经济增长，这也可能创造新的就业机会。
There is already robust competition among high-tech firms for workers who possess the skills to develop and effectively deploy this technology.
高科技公司之间已经对拥有开发和有效部署这项技术技能的工人展开了激烈的竞争。
At the same time, many people have legitimate concerns that AI will cause job loss.
与此同时，许多人对人工智能会导致失业有合理的担忧。
At least for certain firms and workers in certain occupations, this is likely to be true.
至少对于某些公司和某些职业的工人来说，这可能是真的。
Indeed, some large employers have recently indicated they are lowering overall hiring plans in light of advances in AI and other forms of automation.
事实上，一些大型雇主最近表示，鉴于人工智能和其他形式的自动化的进步，他们正在降低总体招聘计划。
8 Some research has also suggested that AI is having a more detrimental effect on the job prospects of younger, less-experienced workers, including recent graduates, compared with those further along in their careers.
8 一些研究还表明，与职业生涯中的其他人相比，人工智能对年轻、经验不足的工人（包括应届毕业生）的就业前景产生更不利的影响。
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The net effect on employment is highly uncertain and may show variation across industries and occupations over time.
对就业的净影响高度不确定，并且可能随着时间的推移在不同行业和职业之间表现出差异。
For the overall economy, one way to think about AI-related job losses—at least until it creates new jobs—is that AI can create economic slack.
对于整体经济而言，思考与人工智能相关的失业的一种方法是，至少在它创造新的就业机会之前，人工智能会造成经济闲置。
In a world where firms only deployed AI to replace existing workers, even at a lower level of overall employment, the productive capacity of the economy has increased (or stayed the same).
在一个企业仅部署人工智能来取代现有工人的世界中，即使总体就业水平较低，经济的生产能力也会增加（或保持不变）。
Of course, if people get redeployed to more productive tasks, the economy produces more without any additional slack.
当然，如果人们被重新分配到更具生产力的任务，经济就会在没有任何额外闲置的情况下生产更多。
Whether AI substitutes for labor or complements it is an important question that requires continued study.
人工智能到底是替代劳动力还是补充劳动力，是一个需要持续研究的重要问题。
On the other side of our dual mandate—price stability—AI could help the economy achieve higher growth through increased productivity while reducing inflationary pressures.
另一方面，我们的双重任务——价格稳定——人工智能可以通过提高生产率来帮助经济实现更高的增长，同时降低通胀压力。
Specifically, increased productivity could lower production costs and put downward pressure on prices.
具体来说，生产率的提高可以降低生产成本并对价格造成下行压力。
Not only could AI allow a specific worker to be more efficient in their day-to-day tasks, but it also has the potential to allow for better thinking around complex problems.
人工智能不仅可以让特定的工作人员在日常任务中更加高效，而且还有可能更好地思考复杂的问题。
More efficient allocation of resources as well as potential improvements in supply chains could reduce associated costs, leading to lower prices for various goods and services.
更有效的资源配置以及供应链的潜在改进可以降低相关成本，从而降低各种商品和服务的价格。
Conversely, AI could put upward pressure on certain price categories as many firms push to scale up the technology.
相反，随着许多公司推动扩大技术规模，人工智能可能会给某些价格类别带来上行压力。
I mentioned the rising wages for certain workers with skills that complement AI.
我提到了某些具有与人工智能互补的技能的工人的工资上涨。
AI technology also requires data centers, which compete with other production processes for land, energy, and other inputs.
人工智能技术还需要数据中心，数据中心与其他生产流程争夺土地、能源和其他投入。
As with the labor market, the timing and degree of AI's effect on prices are uncertain and should be monitored.
与劳动力市场一样，人工智能对价格影响的时间和程度是不确定的，应该受到监控。
In terms of AI's implications for monetary policy, it is likely still too soon to tell.
就人工智能对货币政策的影响而言，现在下结论可能还为时过早。
Policymakers must sort out changes in the economy that are due to cyclical factors from those resulting from structural change, which AI may well represent.
政策制定者必须将周期性因素引起的经济变化与结构性变化引起的经济变化区分开来，而人工智能很可能就是结构性变化的代表。
Productivity gains from AI may affect the relationship between employment and inflation and, hence, the conduct of monetary policy.
人工智能带来的生产力提升可能会影响就业与通胀之间的关系，从而影响货币政策的实施。
Monetary policy decisions, of course, need to be made with a broad view of what is happening in the economy, not just in one sector or technology.
当然，货币政策决策需要广泛考虑经济中正在发生的事情，而不仅仅是某一部门或技术。
There is still much to learn.
还有很多东西需要学习。
I counsel exercising humility about the challenges in predicting AI's effects on employment and inflation.
我建议对预测人工智能对就业和通胀影响的挑战保持谦逊。
AI and Financial Stability Now, I will turn to discussing AI through the lens of financial stability.
人工智能和金融稳定现在，我将转向从金融稳定的角度讨论人工智能。
But first I would like to step back and briefly offer my overall assessment.
但首先我想退后一步，简要提供我的总体评估。
The financial system remains sound and resilient, with high levels of risk appetite and leverage at hedge funds balanced by strong household and business balance sheets and high levels of capital in the banking system.
金融体系依然健全且富有弹性，对冲基金的高风险偏好和杠杆率与强劲的家庭和企业资产负债表以及银行体系的高资本水平相平衡。
Because the continued resilience of the financial system is so important to achieving our dual-mandate goals, policymakers monitor a range of indicators associated with vulnerabilities, as is discussed in our semiannual FSR.
由于金融体系的持续弹性对于实现我们的双重使命目标非常重要，因此政策制定者监控与脆弱性相关的一系列指标，正如我们半年度 FSR 中所讨论的那样。
The latest version of that report was published a few weeks ago.
该报告的最新版本于几周前发布。
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As part of our financial stability monitoring work at the Fed, we routinely survey market contacts regarding potential risks to the U.S. financial system.
作为美联储金融稳定监测工作的一部分，我们定期调查市场联系人，了解美国金融体系的潜在风险。
A finding in the most recent survey is likely of particular interest to a conference exploring financial stability in a time of technological change—30 percent of contacts surveyed cited a turn in the prevailing sentiment toward AI as a salient risk to the U.S. financial system and the global economy.
最近调查中的一项发现可能会引起一场探讨技术变革时期金融稳定性的会议的兴趣——30%的受访者表示，人们普遍对人工智能的看法发生了转变，认为这是美国金融体系和全球经济面临的一个显着风险。
That was up from 9 percent in the spring survey.
这比春季调查中的 9% 有所上升。
Participants noted that if such an unwinding were to occur, it could tighten financial conditions and restrain economic activity more broadly.
与会者指出，如果出现这种放松，可能会收紧金融状况并更广泛地抑制经济活动。
It is not my intention to make a judgement on the likelihood of those, or other scenarios offered in the FSR.
我无意对这些情况或 FSR 中提供的其他情况的可能性做出判断。
Rather, I want to reiterate that I am monitoring the scenarios.
相反，我想重申我正在监视这些情况。
Some observers have asked about comparisons with the late 1990s , which was another period when promising new technological advances were closely tied to strong stock market performance.
一些观察人士询问了与 20 世纪 90 年代末的比较，那是另一个充满希望的新技术进步与强劲的股市表现密切相关的时期。
11 They have asked, are we experiencing "dot-com boom 2.0?" So, in the rest of my talk, I will address this question.
11 他们问，我们是否正在经历“互联网繁荣 2.0”？因此，在接下来的演讲中，我将解决这个问题。
I will argue that there are important differences between the recent period and the stock market experience during the dot-com boom of the late 1990s.
我认为，近期的股市经历与 20 世纪 90 年代末互联网泡沫时期的股市经历存在重要差异。
Of course, much has changed over the past quarter-century, so history can only be a useful reference and not a predictor of future outcomes.
当然，过去四分之一个世纪发生了很多变化，因此历史只能作为有用的参考，而不能预测未来的结果。
How Current Conditions Compare with the Dot-Com Era I see clear differences across the two periods.
当前状况与互联网时代相比如何 我发现这两个时期存在明显差异。
Before I discuss three notable differences, let me first refresh our memory and mention a dimension along which the dot-com era and the AI era are similar—the particularly rapid stock price appreciation of firms that encapsulate the promise of transformational technologies.
在讨论三个显着差异之前，让我首先回顾一下互联网时代和人工智能时代的一个相似之处——体现了变革性技术前景的公司股价特别快速的升值。
12 Indeed, the stock prices of dot-com firms increased more than 200 percent during their boom between 1996 and 1999, a little faster than the increase we have seen so far in the stock prices of AI-related firms since 2022.
12 事实上，互联网公司的股价在 1996 年至 1999 年的繁荣时期上涨了 200% 以上，略快于我们自 2022 年以来迄今为止看到的人工智能相关公司的股价涨幅。
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A closer inspection of the firms driving the stock price increases, however, reveals the first critical difference in the stock market dynamics across the two periods.
然而，对推动股价上涨的公司进行更仔细的观察，就会发现这两个时期股市动态的第一个关键差异。
In the late 1990s and early 2000s, many, albeit not all, dot-com firms typically had little to no realized earnings and only speculative revenue prospects even as they obtained external funding and were listed on public exchanges with relative ease amid pronounced investor enthusiasm.
在 20 世纪 90 年代末和 2000 年代初，许多（尽管不是全部）网络公司通常几乎没有实现盈利，只有投机性收入前景，即使它们获得外部资金并在投资者热情高涨的情况下相对轻松地在公共交易所上市。
In contrast, the firms most closely identified with AI technologies in today's market generally have well-established and growing earnings streams.
相比之下，当今市场上与人工智能技术最密切相关的公司通常拥有完善且不断增长的收入来源。
The second difference is that because of their solid earnings base, the price-to-earnings ratios of AI-related firms have thus far remained well below the peak ratios of dot-com firms in the late 1990s and early 2000s.
第二个区别是，由于其坚实的盈利基础，人工智能相关公司的市盈率迄今为止仍远低于 20 世纪 90 年代末和 2000 年代初互联网公司的峰值比率。
During the dot-com episode, investors were apparently far more willing to bet on the promise of the internet, with dot-com stocks commanding far larger premiums than AI stocks do today.
在互联网泡沫时期，投资者显然更愿意押注互联网的前景，互联网股票的溢价远高于今天的人工智能股票。
The third difference is that the proliferation of dot-com firms in the late 1990s and early 2000s suggests a less discriminating enthusiasm than what we are observing in today's market.
第三个区别是，20 世纪 90 年代末和 2000 年代初网络公司的激增表明，与我们在当今市场上观察到的情况相比，人们的热情不那么具有歧视性。
At the peak in the late 1990s, more than 1,000 firms were publicly listed as dot-com companies, with many having minimal revenue and highly speculative business models.
在 20 世纪 90 年代末的鼎盛时期，有超过 1,000 家公司作为网络公司公开上市，其中许多公司收入微薄，商业模式投机性很高。
Indeed, researchers have shown that the mere addition of "dot-com" to a company name was sufficient to boost the stock price of the firm.
事实上，研究人员已经表明，仅仅在公司名称中添加“dot-com”就足以提高公司的股价。
14 By contrast, in the current environment, by one measure about 50 publicly traded firms are considered to be AI-focused enterprises, in the sense that they are expected to derive revenue from other firms using AI technologies, as opposed to the broad-based speculation that we saw in the late 1990s.
14 相比之下，在当前环境下，根据一项衡量标准，大约 50 家上市公司被认为是专注于人工智能的企业，因为它们预计会从使用人工智能技术的其他公司获得收入，这与我们在 20 世纪 90 年代末看到的广泛猜测相反。
15 However, it is important to acknowledge that the rapid growth of private capital markets—which are not publicly traded—in recent years may obscure the extent of investor enthusiasm for financing AI firms, as a growing number of private firms reportedly now identify as AI-focused or AI-native enterprises.
15 然而，重要的是要承认，近年来私人资本市场（非公开交易）的快速增长可能会掩盖投资者对人工智能公司融资的热情程度，因为据报道，越来越多的私营公司现在被认为是专注于人工智能或人工智能本土的企业。
Finally, with respect to financial leverage, both dot-com previously and AI firms recently exhibited limited reliance on debt financing for the most part.
最后，就财务杠杆而言，之前的互联网公司和最近的人工智能公司在很大程度上都表现出对债务融资的有限依赖。
This more limited use of leverage may reduce the extent to which a shift in sentiment toward AI could transmit to the broader economy through credit markets.
这种对杠杆的更有限的使用可能会降低对人工智能的情绪转变通过信贷市场传导到更广泛的经济的程度。
That said, recent market reports suggest that AI firms may be increasing their use of debt, from both public and private credit markets, to fund substantial investments in computing infrastructure and talent acquisition.
尽管如此，最近的市场报告表明，人工智能公司可能会增加公共和私人信贷市场债务的使用，为计算基础设施和人才招聘的大量投资提供资金。
Just a few weeks ago, large volumes of corporate bonds were issued to support AI infrastructure buildout by key players in the industry.
就在几周前，大量公司债券被发行，以支持行业主要参与者的人工智能基础设施建设。
Some analysts estimate that future investments in AI infrastructure will require a lot more debt.
一些分析师估计，未来对人工智能基础设施的投资将需要更多的债务。
16 If that turns out to be the case, leverage in the AI sector could increase—and so could the losses if sentiment toward AI shifts.
16 如果事实果真如此，人工智能行业的杠杆率可能会增加——如果人们对人工智能的看法发生转变，损失也可能会增加。
I will watch this developing trend closely.
我将密切关注这一发展趋势。
In sum, looking at these dimensions, as of now, the differences between the current market and the dot-com era make it less likely that we are witnessing a replay of the late 1990s.
总而言之，从这些维度来看，目前的市场与互联网时代的差异使得我们不太可能见证 90 年代末的重演。
Most notably, in contrast with the dot-com era, the current AI-related stock market activity appears more concentrated among established firms with actual earnings.
最值得注意的是，与互联网时代相比，当前与人工智能相关的股票市场活动似乎更集中于拥有实际盈利的老牌公司。
Additionally, these developments are occurring against the backdrop of a financial system that is sound and resilient.
此外，这些发展是在金融体系健全且富有弹性的背景下发生的。
Conclusion To conclude , it is important to acknowledge that assessing the implications of rapidly developing technology for financial stability is subject to a great deal of uncertainty.
结论 总而言之，重要的是要承认，评估快速发展的技术对金融稳定的影响存在很大的不确定性。
The ultimate implications of AI for both the macroeconomy and financial stability may take a long time to crystallize.
人工智能对宏观经济和金融稳定的最终影响可能需要很长时间才能显现出来。
Technology, the financial system, and the broader economy are always evolving.
技术、金融体系和更广泛的经济总是在不断发展。
The potential transition to our new world could be bumpy, and it is too early to tell what trajectory will ultimately play out.
向新世界的潜在过渡可能会很坎坷，现在判断最终的发展轨迹还为时过早。
Our research is continually enriched by the insights provided by market participants in regular outreach, keeping us abreast of the latest developments in AI and their economic implications, and by an ever-expanding analytical toolkit, including AI.
市场参与者在定期推广中提供的见解不断丰富我们的研究，使我们能够及时了解人工智能的最新发展及其经济影响，以及包括人工智能在内的不断扩展的分析工具包。
Ensuring that the AI revolution unfolds within the context of a stable financial system is not just desirable—it is also imperative for achieving our dual-mandate objectives of maximum employment and price stability.
确保人工智能革命在稳定的金融体系的背景下展开不仅是可取的，而且对于实现就业最大化和价格稳定的双重目标也至关重要。
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The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee.
这里表达的观点是我自己的观点，不一定是我在美联储委员会或联邦公开市场委员会的同事的观点。
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2.
See Philip N.
参见菲利普·N.
Jefferson (2025), "AI and the Economy," speech delivered at Euro20+, Deutsche Bundesbank, Frankfurt, Germany, November 7.
Jefferson (2025)，“人工智能与经济”，11 月 7 日在德国法兰克福德意志联邦银行 Euro20+ 上发表的演讲。
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3.
See Microsoft (2025), "AI Diffusion Report: Where AI Is Most Used, Developed, and Built," AI Economy Institute, November, https://www.microsoft.com/en-us/research/group/aiei/ai-diffusion/. Return to text
请参阅 Microsoft (2025)，“AI 扩散报告：AI 最常使用、开发和构建的地方”，AI 经济研究所，11 月，https://www.microsoft.com/en-us/research/group/aiei/ai-diffusion/。返回正文
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4.
See Aaron Chatterji, Thomas Cunningham, David J.
参见亚伦·查特吉 (Aaron Chatterji)、托马斯·坎宁安 (Thomas Cunningham)、大卫·J.
Deming, Zoe Hitzig, Christopher Ong, Carl Yan Shan, and Kevin Wadman (2025), "How People Use ChatGPT," NBER Working Paper Series 34255 (Cambridge, Mass.: National Bureau of Economic Research, September).
Deming、Zoe Hitzig、Christopher Ong、Carl Yan Shan 和 Kevin Wadman (2025)，“人们如何使用 ChatGPT”，NBER 工作论文系列 34255（马萨诸塞州剑桥：国家经济研究局，9 月）。
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See Alexander Bick, Adam Blandin, and David Deming (2025), "The State of Generative AI Adoption in 2025," Federal Reserve Bank of St. Louis, On the Economy Blog, November 13.
请参阅 Alexander Bick、Adam Blandin 和 David Deming (2025)，“2025 年生成式人工智能采用状况”，圣路易斯联邦储备银行，经济博客，11 月 13 日。
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This assessment is based on Federal Reserve staff analysis of data from the U.S. Census Bureau's Business Trends and Outlook Survey, which is available on its website at https://www.census.gov/programs-surveys/btos.html .
该评估基于美联储工作人员对美国人口普查局商业趋势和前景调查数据的分析，该调查可在其网站 https://www.census.gov/programs-surveys/btos.html 上获取。
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See Erik Brynjolfsson, Danielle Li, and Lindsey R.
参见 Erik Brynjolfsson、Danielle Li 和 Lindsey R.
Raymond (2023), "Generative AI at Work," NBER Working Paper Series 31161 (Cambridge, Mass.: National Bureau of Economic Research, April; revised November 2023).
Raymond (2023)，“工作中的生成式人工智能”，NBER 工作论文系列 31161（马萨诸塞州剑桥：国家经济研究局，4 月；2023 年 11 月修订）。
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For example, see Tom Huddleston Jr. (2025), "Walmart CEO: 'AI Is Literally Going to Change Every Job'—How the Best Employees Can Still Stand Out," CNBC, September 29; also, see Karen Weise (2025), "Amazon Plans to Replace More than Half a Million Jobs with Robots," New York Times, October 21.
例如，请参阅 Tom Huddleston Jr. (2025)，“沃尔玛首席执行官：‘人工智能确实会改变每一份工作’——最优秀的员工如何仍能脱颖而出”，CNBC，9 月 29 日；另请参阅 Karen Weise (2025)，“亚马逊计划用机器人取代超过 50 万个工作岗位”，《纽约时报》，10 月 21 日。
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See J.P.
参见 J.P.
Morgan (2025), "AI's Impact on Job Growth," webpage, https://www.jpmorgan.com/insights/global-research/artificial-intelligence/ai-impact-job-growth. Return to text
Morgan (2025)，“人工智能对就业增长的影响”，网页，https://www.jpmorgan.com/insights/global-research/artificial-intelligence/ai-impact-job-growth。返回正文
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The most recent FSR is available on the Federal Reserve Board's website at https://www.federalreserve.gov/publications/files/financial-stability-report-20251107.pdf .
最新的 FSR 可在联邦储备委员会网站上获取：https://www.federalreserve.gov/publications/files/financial-stability-report-20251107.pdf。
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For example, AI technology and its effect on financial markets is the focus of the 10th Foundation for Advancement of Research in Financial Economics (FARFE) Conference.
例如，人工智能技术及其对金融市场的影响是第十届金融经济学研究促进基金会（FARFE）会议的焦点。
Information about the conference is available on FARFE's website at https://farfe.org/Conference-2025.html .
有关会议的信息请访问 FARFE 网站：https://farfe.org/Conference-2025.html。
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See Alexander Ljungqvist and William J.
参见 Alexander Ljungqvist 和 William J.
Wilhem Jr. (2003), "IPO Pricing in the Dot-Com Bubble," Journal of Finance, vol. 58 (April), pp.
Wilhem Jr. (2003)，“网络泡沫中的 IPO 定价”，《金融杂志》，第 1 卷。 58（四月），第 58 页。
723–52; also, see Tim Loughran and Jay R.
723–52；另请参阅 Tim Loughran 和 Jay R.
Ritter (2002), "Why Don't Issuers Get Upset about Leaving Money on the Table in IPOs?" Review of Financial Studies, vol. 15 (January), pp.
Ritter (2002)，“为什么发行人不会因为在 IPO 中留下资金而感到不安？”金融研究评论，卷。 15（一月），第 15 页。
413–44.
413–44。
Dot-com firms are identified following the approach in Ljungqvist and Wilhelm Jr. (2003) and Loughran and Ritter (2002) by using a specific set of SIC codes.
网络公司的识别遵循 Ljungqvist 和 Wilhelm Jr. (2003) 以及 Loughran 和 Ritter (2002) 中的方法，使用一组特定的 SIC 代码。
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Similarly, t he NASDAQ stock price index increased about 215 percent between 1996 and 1999.
同样，纳斯达克股票价格指数在 1996 年至 1999 年间上涨了约 215%。
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See Michael J.
参见迈克尔·J.
Cooper, Orlin Dimitrov, and P.
库珀、奥林·季米特洛夫和 P.
Raghavendra Rau (2001), "A Rose.com by Any Other Name," Journal of Finance, vol. 56 (December), pp.
Raghavendra Rau (2001)，“A Rose.com by Any Other Name”，《金融杂志》，卷。 56（12 月），第 56 页。
2371–88.
2371–88。
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This assessment is based on the iShares Future AI & Tech ETF, which focuses on "companies that provide products and services that are expected to contribute to AI technologies in areas including generative AI, AI data and infrastructure, AI software, and AI services." Obviously, the number of firms that use AI technology is much larger.
该评估基于 iShares Future AI & Tech ETF，重点关注“提供有望为生成人工智能、人工智能数据和基础设施、人工智能软件和人工智能服务等领域的人工智能技术做出贡献的产品和服务的公司”。显然，使用人工智能技术的公司数量要多得多。
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See Morgan Stanley (2025), "Bridging a $1.5tr Data Center Financing Gap," July.
请参阅摩根士丹利 (2025)，“弥合 1.5 美元的数据中心融资缺口”，7 月。
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