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Economists are weighing two contradictory negative scenarios for AI. One where its rapid success causes massive job upheaval, and another where it fails to meet investor hype, leading to a stock market collapse and recession much like the dot-com bubble.

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Rapid AI productivity gains could overwhelm the economy, causing significant job loss before new roles are created. Moody's analysts don't view this as a remote tail risk, but as a substantial 1-in-5 possibility that requires serious consideration by policymakers and business leaders.

Stock market investors are pricing in rapid, significant productivity gains from AI to justify high valuations. This sets up a binary outcome: either investors are correct, leading to massive productivity growth that could disrupt the job market, or they are wrong, resulting in a painful stock market correction when those gains fail to materialize.

The two dominant negative narratives about AI—that it's a fake bubble and that it's on the verge of creating a dangerous superintelligence—are mutually exclusive. If AI is a bubble, it's not super powerful; if it's super powerful, the economic activity is justified. This contradiction exposes the ideological roots of the doomer movement.

History shows that transformative technologies like railroads and the internet often create market bubbles. Investors can lose tremendous amounts of capital on overpriced assets, even while the technology itself fundamentally rewires the economy and creates massive societal value. The two outcomes are not mutually exclusive.

The memo posits a scenario where AI boosts white-collar productivity, causing layoffs and reduced consumer spending. This forces companies to cut costs further with more AI, creating a downward economic spiral. This highlights a significant "left-tail risk" for investors and the economy.

The debate around AI's impact presents an asymmetric risk. Underestimating AI's capabilities could lead to obsolescence for individuals and companies. Conversely, overestimating its short-term impact results in some wasted preparation, a far less severe and more recoverable outcome.

Blinder asserts that while AI is a genuine technological revolution, historical parallels (autos, PCs) show such transformations are always accompanied by speculative bubbles. He argues it would be contrary to history if this wasn't the case, suggesting a major market correction and corporate shakeout is inevitable.

For current AI valuations to be realized, AI must deliver unprecedented efficiency, likely causing mass job displacement. This would disrupt the consumer economy that supports these companies, creating a fundamental contradiction where the condition for success undermines the system itself.

The most immediate systemic risk from AI may not be mass unemployment but an unsustainable financial market bubble. Sky-high valuations of AI-related companies pose a more significant short-term threat to economic stability than the still-developing impact of AI on the job market.

The stock market's high valuation is based on AI generating huge profits, which implies replacing human workers. If AI is overhyped and jobs are safe, the market's core premise collapses, leading to a crash. This creates an economic dilemma where one major indicator must fall.