Unlike previous technologies that augmented specific skills, AI could eventually outperform humans in all domains, including creative and emotional tasks. This suggests the historical pattern of technology creating more jobs than it destroys may not hold true.
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Beyond displacing current workers, AI will lead to hiring "abatement," where companies proactively eliminate roles from their hiring plans altogether. This is a subtle but profound workforce shift, as entire job categories may vanish from the market before employees can be retrained.
Historically, humans moved from manual to cognitive labor as technology automated physical tasks. Emad Mostaque argues AI now automates cognitive work, creating an "intelligence inversion." There's no obvious higher-value domain left for human labor to escape to, unlike previous technological shifts.
Previous technological revolutions automated physical labor but enhanced human thinking. AI's goal is to replicate and surpass human cognitive abilities, creating a categorical shift that threatens the core of human economic value.
Tech leaders cite Jevon's Paradox, suggesting AI efficiency will create more jobs. However, this historical model may not hold, as the speed of AI disruption outpaces society's ability to adapt, and demand for knowledge work isn't infinitely elastic.
AI's impact on labor will likely follow a deceptive curve: an initial boost in productivity as it augments human workers, followed by a crash as it masters their domains and replaces them entirely. This creates a false sense of security, delaying necessary policy responses.
Unlike past technological shifts where humans could learn new trades, AI is a "tractor for everything." It will automate a task and then move to automate the next available task faster than a human can reskill, making long-term job security increasingly precarious for cognitive labor.
The US economy is currently experiencing near-zero job growth despite typical 2% productivity gains. A significant increase in productivity driven by AI, without a corresponding surge in economic output, could paradoxically lead to outright job losses. This creates a scenario where positive productivity news could have negative employment consequences.
The true threshold for AI becoming a disruptive, "non-normal" technology is when it can perform the new jobs that emerge from increased productivity. This breaks the historical cycle of human job reallocation, representing a fundamental economic shift distinct from past technological waves.
As AI systems become infinitely scalable and more capable, humans will become the weakest link in any cognitive team. The high risk of human error and incorrect conclusions means that, from a purely economic perspective, human cognitive input will eventually detract from, rather than add to, value creation.
The Jevons Paradox observes that technologies increasing efficiency often boost consumption rather than reduce it. Applied to AI, this means while some jobs will be automated, the increased productivity will likely expand the scope and volume of work, creating new roles, much like typewriters ultimately increased secretarial work.
