1996 or 1999? Walsh's First Test is 'How to View AI'

marsbitPublished on 2026-06-20Last updated on 2026-06-20

Abstract

"1996 or 1999? Wall's First Big Test Is 'How to View AI'" Federal Reserve Chairman Wall's initial challenge is not whether to raise or cut rates, but a more fundamental judgment: what kind of boom is the current AI boom? This will determine the Fed's policy path and define his legacy. Economics is split between two opposing views, according to reporter Nick Timiraos. One sees imminent productivity gains that will increase supply and cool inflation, allowing the Fed to hold steady. The other argues that while productivity benefits are distant, demand shocks are here now, and waiting for data confirmation risks missing the intervention window, forcing sharper rate hikes later. Wall has signaled a leaning toward the first view, echoing 1996-era Alan Greenspan, who embraced strong, productivity-driven growth without fear of inflation. However, Wall faces a different macro environment than Greenspan did, with tariff pressures, expanding fiscal deficits, and diminishing globalization benefits, which could force more significant inflation pressures even if AI benefits materialize. Wall's logic, expressed before taking office, is that AI-driven productivity gains won't show in official data for years. If the Fed waits for confirmation, it might mistakenly tighten policy and choke off the very growth that could suppress inflation. This argues for using forward-looking narratives over lagging data. Chicago Fed President Austan Goolsbee presents a key counter-argument. He distingui...

Written by: Dong Jing

The foremost challenge facing Walsh upon becoming Fed Chairman is not whether to raise or lower interest rates, but a more fundamental judgment: What kind of boom is the current AI prosperity? This judgment will determine the Fed's policy direction and define Walsh's place in history.

On June 19, Nick Timiraos, known as the "New Fed Whisperer," reported that the economic community holds two diametrically opposed interpretations of the AI construction boom:

First, the productivity dividend is about to materialize, supply will catch up with demand, and the Fed can stand pat and wait for inflation to subside naturally; second, the benefits of productivity gains are still in the distant future, while the demand shock has already arrived. If the Fed waits for data confirmation, it will miss the optimal intervention window and ultimately be forced to raise rates more sharply.

While the Fed held rates steady this week, nearly half the officials in the latest dot plot still project rate hikes this year, with the rest holding the opposite view. This deep internal division reflects the high degree of uncertainty surrounding this core issue.

Walsh's own inclination was faintly visible at the press conference. He repeatedly emphasized "robust, productivity-driven growth is not something we fear, but something we embrace," an echo of Greenspan's 1996 thinking.

However, the macroeconomic environment he faces—tariff pressures, widening fiscal deficits, fading globalization dividends—is far removed from the smooth sailing of Greenspan's era. Making the correct judgment between these two historical scripts will be Walsh's first true test at the Fed's helm.

Two 1990s: The Dual Legacy Left by Greenspan

Timiraos indicates that Walsh has repeatedly invoked the 1990s as a historical reference over the past year, but that decade itself contains two very different stories.

In 1996, facing rapid economic expansion, Greenspan chose to stand pat. He judged that fast growth wouldn't ignite inflation, and history proved him right. The expansion continued for years, earning him the reputation of a "maestro."

In 1999, Greenspan changed his judgment. With soaring stock markets and a persistently tight labor market, he began a series of rate hikes, which culminated in the dot-com bubble burst. It was also in this year that the Fed established its "forward guidance" mechanism of signaling rate hikes in advance—a practice that continues to this day and one that Walsh has explicitly stated he wishes to abolish.

The Trump administration publicly favors the 1996 version of the Fed. Before taking office, Walsh also publicly expressed his desire to create a central bank "confident enough to do less." Yet, current economic conditions may be handing him a different version of the script.

Walsh's Judgment Logic: Believe the Narrative, Not Wait for the Data

Before taking office, Walsh publicly stated his position on Fox Business: He fears the Fed is about to make its "sixth or seventh major mistake"—tightening monetary policy too early in what should be a hands-off productivity boom.

Timiraos reports that his core argument is: Productivity gains from AI will not be immediately reflected in official statistics; it may take several years for them to show up. If the Fed insists on waiting for data confirmation, it risks misdiagnosing a benign boom as an overheating economy and raising rates—which would precisely choke off the growth momentum that could have subdued inflation.

The essence of this logic advocates using a forward-looking narrative instead of lagging data as the basis for decision-making. Walsh continued this line of thinking at the press conference: when asked whether AI is currently boosting demand or expanding supply, he merely stated "demand is easier to measure than supply," deliberately avoiding a clear stance while adhering to the principle of "not telegraphing the next move" in communication.

Timiraos believes that even if Walsh's ultimate judgment is correct, the 1990s analogy is not complete.

When Greenspan made his famous gamble in 1996, he had multiple tailwinds: cheap goods and labor from abroad continuously suppressed inflation, and the federal fiscal deficit was narrowing. These structural factors provided additional safety margins for the Fed's "wait-and-see" approach.

Walsh faces a markedly different environment: tariff policies are raising import costs, fiscal deficits are expanding rather than contracting, and globalization dividends have faded. This means that even if the AI productivity dividend ultimately materializes as expected, the inflationary pressure Walsh endures while waiting will far exceed what Greenspan faced back then.

Counterargument: The Chicago Fed's "Front-Loading of Expectations" Model

Timiraos points out that the most systematic challenge to Walsh's judgment logic comes from Chicago Fed President Austan Goolsbee.

According to a Wall Street Journal report, Goolsbee proposed a key distinction at a Stanford University conference last month: Whether a productivity boom allows a central bank to stand pat depends on whether the boom is unexpected. A boom that everyone can foresee can have the opposite effect—people will front-load their future wealth, increasing spending significantly before the productivity gains materialize, leading to economic overheating.

"You end up having to raise rates more than you would have had to if you had acted earlier," Goolsbee said.

He believes the current AI boom is precisely this type of "visible to all." Surveys of economists, tech workers, and the general public show the market widely expects AI to deliver about one percentage point of annual productivity gains, with most benefits still in the future. According to his model, this expectation itself constitutes a reason to raise rates, not a reason to cut.

Goolsbee also cited real-world "overheating signals": AI data center construction is driving up the prices of land, electricity, and chips, while also increasing costs for electricians and equipment, squeezing resources from other sectors. Apple's announcement this week of price hikes due to rising costs was cited by him as evidence this mechanism is at work.

It is worth noting that Goolsbee's framework is not without challengers. Fed Governor Christopher Waller, at the same Stanford conference, pointed out that the "front-loading of expectations" mechanism can work only if people are able to borrow to spend ahead. In reality, however, spending for many households is tightly constrained by current income, making it difficult to monetize future wealth easily.

"If they cannot front-load that spending, the whole mechanism gets shut off," Waller said.

This rebuttal provides theoretical support for Walsh's "stand pat" stance: If borrowing constraints are widespread enough, the demand-frontloading effect will be greatly diminished, making a productivity boom more likely to expand supply in a benign manner rather than triggering inflation.

Ultimate Paradox: Abolish Forward Guidance, or Be Forced to Use It

Furthermore, Timiraos argues that Walsh faces a deeper paradox at the Fed's helm, and this paradox stems precisely from what he most wants to change.

He has explicitly stated his desire to create a Fed that "does not show its cards in advance," reducing forward guidance and keeping markets guessing. However, the Fed's current forward guidance mechanism was established precisely in 1999—when Greenspan, to avoid catching markets off guard, began signaling rate hikes in advance.

If the economic trajectory is as optimistic as the Trump administration portrays, Walsh may never need to signal rate hikes early. But if the economy follows the other script, he will face a dilemma:

Either use the forward guidance convention he wishes to abolish, informing markets of rate hike plans in advance; or remain silent, letting markets guess the magnitude and pace of hikes, and bear the risk of severe financial market volatility that ensues.

The solution to this paradox ultimately still depends on the answer to the same question: Is it 1996, or 1999?

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Related Questions

QWhat is the core challenge that Chairman Wash faces regarding AI, and how will it influence his policy decisions?

AThe core challenge is determining the nature of the current AI boom. He must judge whether it is a productivity-driven boom like in 1996 (where patience is warranted) or a demand-driven boom that risks overheating like in 1999 (requiring preemptive tightening). This fundamental judgment will dictate the Federal Reserve's monetary policy path, including decisions on interest rates, and ultimately define Wash's historical legacy.

QAccording to the article, what are the two contrasting interpretations of the AI boom within the economics community?

AThe two interpretations are: 1) Productivity dividends are imminent, supply will catch up with demand, and the Fed can hold steady while inflation naturally recedes. 2) The benefits of productivity gains are still distant, but the demand shock has already arrived. If the Fed waits for data confirmation, it will miss the optimal intervention window and eventually be forced to raise rates more aggressively.

QHow does Wash's personal logic on AI and productivity differ from a purely data-dependent approach?

AWash's logic advocates using a forward-looking narrative over lagging data for decision-making. He argues that AI's productivity gains won't be immediately visible in official statistics and may take years to show. If the Fed waits for data confirmation, it risks misjudging a benign productivity boom as economic overheating and raising rates, which would choke off the very growth that could suppress inflation.

QWhat is the key argument posed by Chicago Fed President Austan Goolsbee against Wash's 'wait-and-see' stance on the AI boom?

AGoolsbee argues that whether a productivity boom allows the Fed to hold steady depends on whether the boom is unexpected. A widely anticipated boom, like the current AI wave, can have the opposite effect. People might front-load future wealth by spending more before productivity gains materialize, leading to economic overheating. This dynamic, visible in rising costs for data centers and related inputs, creates a rationale for raising rates sooner, not later.

QWhat is the fundamental paradox Chairman Wash faces regarding the Fed's communication policy, as outlined in the article?

AThe paradox is rooted in Wash's desire to abolish the Fed's practice of forward guidance (pre-signaling policy moves). However, this very practice was established in 1999 to prevent market shocks. If the economy follows a 1999-like scenario requiring preemptive tightening, Wash faces a dilemma: either use the forward guidance he wants to end to prepare markets, or remain silent and risk significant market volatility as participants guess the Fed's next move. The solution depends on his judgment of whether the current era is more like 1996 or 1999.

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October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

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What is AGENT S

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