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We’ve been wrong about new technology before. Are we wrong about AI?

5 2
19.09.2025

The year is 1956. You’re a researcher working at International Business Machines, the world’s leading tabulating machine company, which has recently diversified into the brand-new field of electronic computers. You have been tasked with determining for what purposes, exactly, your customers are using IBM’s huge mainframes.

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The answer turns out to be pretty simple: computers are for the military, and for the military alone. In 1955, the year before, by far the biggest single revenue source for IBM’s computer division was the SAGE Project, a Defense Department initiative tasking IBM with creating a computer system capable of providing early warnings across the United States should nuclear-armed Soviet bombers attack the country. That brought in $47 million in 1955, and other military projects brought in $35 million. Programmable computers sold to businesses, meanwhile, brought in a paltry $12 million.

You send a memo to your boss explaining that computers’ impact on society will primarily be in giving the US an edge on the Soviets in the Cold War. The impact on the private sector, by contrast, seems minor. You lean back in your chair, light a cigarette, and ponder the glorious future of the defense-industrial complex.

You would, of course, be totally wrong — not just in the far future but in the very immediate one. Here’s what revenue looked like from each of IBM’s computing divisions in 1952 through 1964, compiled by company veteran Emerson Pugh in his book Building IBM:

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A mere two years after 1956, programmable computers sold to private companies had matched SAGE as a revenue source. The year after that, the private sector was bringing in as much as the military as a whole. By 1963, not even a decade after the 1955 data you were looking at, the military appears to be a rounding error next to IBM’s ballooning private computer revenues, which have grown to account for a majority of the company’s entire US revenue.

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What can we learn from how people are using AI right now?

This week, impressive teams of economists at both OpenAI and Anthropic released big, carefully designed reports on how people are using their AI models — and one of my first thoughts was, “I wonder what an IBM report on how people used their first computers would’ve looked like.” (Disclosure: Vox Media is one of several publishers that have signed partnership agreements........

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