Unlike typical economic cycles with a clear baseline and tail risks, the current environment is defined by radical uncertainty. The combined unknowns of erratic economic policy and AI's transformative potential create a "flat distribution" where extreme outcomes like a depression or an industrial revolution are nearly as likely as a baseline scenario.
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While the economic disruption from COVID saw a relatively quick bounce-back in employment, the changes brought by AI will be permanent. Many job functions and industries will not recover, representing a fundamental, one-way shift in the economy rather than a temporary downturn.
The current AI boom isn't just another tech bubble; it's a "bubble with bigger variance." The potential for massive upswings is matched by the risk of equally significant downswings. Investors and founders must have an unusually high tolerance for risk and volatility to succeed.
Contrary to the consensus view of explosive AI-driven growth, AI could be a headwind for near-term GDP. While past technologies changed the structure of jobs, AI has the potential to eliminate entire categories of economic activity, which could reduce overall economic output, not just displace labor.
Despite favorable conditions like tax cuts and deregulation, a broad investment boom has failed to materialize outside of AI. This isn't due to tight credit, but to massive policy uncertainty from unpredictable tariffs and immigration stances, which discourages long-term capital commitment.
The current AI-driven CapEx cycle is analogous to historical bubbles like the 19th-century railroad buildout and the dot-com boom. These periods of intense capital investment have historically led to major economic downturns and secular bear markets, suggesting a grim multi-year outlook beyond the current cycle.
A bewildering disconnect exists between high market enthusiasm and extreme geopolitical and economic uncertainty. This suggests investors are either willfully ignorant of the risks or believe they are insulated, creating a fragile environment where a materialized risk could trigger a sudden, severe, and nonlinear market crash.
Despite significant geopolitical risks, an equally plausible optimistic scenario exists. Transformative general platform technologies like AGI, quantum computing, and synthetic biology are nearing commercial scale, potentially creating a productivity boom that could offset debt headwinds and turbocharge the economy.
Joe Davis argues the economy faces a "tug of war" between an AI-driven boom and a deficit-fueled slump. He believes the mainstream forecast of stable 2% growth and 2% inflation is the least likely outcome, with an over 80% chance of a material change in the economic environment.
As AI makes the future radically unpredictable, the traditional human calculus for decision-making will change. Instead of optimizing for probable outcomes based on risk, people will shift to minimizing potential regret, a fundamentally different psychological framework for navigating an uncertain world.
As AI gets exponentially smarter, it will solve major problems in power, chip efficiency, and labor, driving down costs across the economy. This extreme efficiency creates a powerful deflationary force, which is a greater long-term macroeconomic risk than the current AI investment bubble popping.
