The Once and Future History of Knowledge Work

all forecast that the workers most likely to see “exposure” to generative AI are more educated and in higher-paid fields such as computer science, business and finance, legal, and management.

Technology has historically had two countervailing effects on labor—what economists call the “substituting force,” which replaces labor, and the “complementary force,” which augments it. Generative AI optimists argue the complementary force has won out through each subsequent wave of technology. A classic example is the ATM, which should have repla

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But this perspective gives us too little credit. We have agency, as workers, voters, and participants in the economy, to advocate for frameworks that guide AI’s influence in directions that support human dignity, opportunity, and equality. Instead of letting the sheer efficiency and velocity of technology dictate our path, we can demand social and ... See more

This shift has ushered in what Every’s Dan Shipper calls an allocation economy, where the value of work increasingly hinges not on traditional labor but on how we allocate scarce resources—time, attention, and focus. In this new paradigm, the question becomes less about what AI can do and more about how we choose to use it, what we allow it to repl... See more

In this new paradigm, the question becomes less about what AI can do and more about how we choose to use it, what we allow it to replace, and what we choose to preserve as uniquely human.

This will require a collective will to prioritize humanity over efficiency, and depth over speed. It means questioning the motives behind AI deployment—who benefits, who loses, and who decides. It means writing legislation, regulations, and industry policies that protect meaningful work for all and exploring new forms of social and economic support... See more

not everyone who studies AI’s impact is so bullish. With generative AI poised to automate an increasing number of business activities—as much as 70 percent , according to McKinsey—critics worry there simply won’t be enough work left over for most workers to do. For the first time in history, the argument goes, technology’s substituting force will o

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This shift has ushered in what Every’s Dan Shipper calls an allocation economy, where the value of work increasingly hinges not on traditional labor but on how we allocate scarce resources—time, attention, and focus. In this new paradigm, the question becomes less about what AI can do and more about how we choose to use it, what we allow it to repl... See more

Well, the joke’s on us. As it turns out, machines can do all of those things better, faster, or at the very least cheaper than humans can. The Pew Research Center, the Brookings Institution, and McKinsey and Company all forecast that the workers most likely to see “exposure” to generative AI are more educated and in higher-paid fields such as compu

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