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Throughout history, new technologies have been met with "doom and gloom" predictions that rarely materialize. The fear that email would create a "paperless society" and bankrupt paper companies is a prime example of getting it wrong. This historical perspective suggests today's most dire predictions about AI are also likely incorrect.

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Critics of AI-driven economic collapse argue these scenarios wrongly assume a static economy. Historically, massive productivity gains from technology have lowered costs, expanded markets, and created entirely new industries and forms of consumption, rather than just eliminating jobs.

Drawing on Frédéric Bastiat's "seen and unseen" principle, AI doomerism is a classic economic fallacy. It focuses on tangible job displacement ("the seen") while completely missing the new industries, roles, and creative potential that technology inevitably unlocks ("the unseen"), a pattern repeated throughout history.

Every major communication technology has sparked a societal instinct to "control it before it controls you." Fears about AI and disinformation are not new; they echo the historical panic over heresy caused by the printing press. This reframes the current regulatory push as a predictable human reaction to disruptive innovation.

Pessimism about AI-driven job losses overlooks historical precedent. The transition from an agricultural to an industrial economy caused massive job displacement but ultimately created far more new jobs. Similarly, AI will likely generate new, currently unimaginable roles and industries.

Unlike previous technologies like the internet or smartphones, which enjoyed years of positive perception before scrutiny, the AI industry immediately faced a PR crisis of its own making. Leaders' early and persistent "AI will kill everyone" narratives, often to attract capital, have framed the public conversation around fear from day one.

Widespread fear of AI is not a new phenomenon but a recurring pattern of human behavior toward disruptive technology. Just as people once believed electricity would bring demons into their homes, society initially demonizes profound technological shifts before eventually embracing their benefits.

Current anxiety about AI-driven job losses stems from a few high-profile announcements. These early examples are being extrapolated into doomsday scenarios, even though comprehensive data on the net effect is not yet available, feeding our collective imagination and fear.

The panic-inducing Citrini paper, which caused a market sell-off, assumes a static economy where AI only destroys jobs. It completely ignores historical precedents where new efficiencies unlock unforeseen demand and create entirely new industries, a concept similar to the Jevons paradox.

The current AI boom isn't a sudden, dangerous phenomenon. It's the culmination of 80 years of research since the first neural network paper in 1943. This long, steady progress counters the recent media-fueled hysteria about AI's immediate dangers.

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.