We began with humans as beasts of burden and moved up: we automated legs, then arms, then fingers, and now brains. We went from farm work to blue-collar work to white-collar work, and now we’ll automate the white-collar work as well and there’ll be nothing left. Factories were replaced by call centres, but if we automate the call centres, what else is there?
Here, I think it’s useful to look at another piece of economic and tech history: the Jevons Paradox.
In the 19th century the British navy ran on coal. Britain had a lot of coal (it was the Saudi Arabia of the steam age) but people worried what would happen when the coal ran out. Ah, said the engineers: don’t worry, because steam engines keep getting more efficient, so we’ll use less coal. No, said Jevons: if we make steam engines more efficient, then they will be cheaper to run, and we will use more of them and use them for new and different things, and so we will use more coal. Innovation can connect to price elasticity.
We’ve been applying the Jevons Paradox to white collar work for 150 years.
It’s hard to imagine jobs of the future that don’t exist yet, but it’s also hard to imagine some of the jobs of the past that have already been automated away. Gogol’s downtrodden clerks in 1830s St Petersburg spent their entire adult lives copying out documents, one at a time, by hand. They were human Xeroxes. By the 1880s, typewriters produced perfectly legible text at twice the words-per-minute, and carbons gave half a dozen free copies as well. Typewriters meant a clerk could produce more than 10 times the output. A few decades later, adding machines from companies like Burroughs did the same for book-keeping and accounting: instead of adding up columns with a pen, the machine does it for you, in 20% of the time, with no mistakes.
What did that do to clerical employment? People hired far more clerks. Automation plus the Jevons Paradox meant more jobs.
If one clerk with a machine can do the work of 10, then you might have fewer clerks, but you might also do far more with them. If, Jevons tells us, it becomes much cheaper and more efficient to do something, you might do more of it – you might do more analysis or manage more inventory. You might build a different and more efficient business that is only possible because you can automate its administration with typewriters and adding machines.
This process keeps repeating…Benedict Evans – AI and the automation of work
DriverlessCroc AI fun:
Eye on AI: ChatGPT and Me
The AI menace that no-one talks about
dr.ai.verless crocod.ai.l // Hype- Text Transfer Protocol
Unreal City: T. S. Eliot’s Wasteland Jukebox feat. Dall-E [known to be the wisest woman in Europe] (underrated)
In which we meet an AI
Eye on AI: Ross Anderson on model collapse; or, The Curse of Recursion
Intelligences (I like this one)
Technology (4): General Purpose Technologies
Learning environments: kind, wicked and… fiendish?
Deep literacy: what it takes (language models for humans)
WTF? Technology and you
Other AI demos and opinion
OpenAI Codex; or, why you might not want to go all in on becoming a full-stack developer
Open AI’s DALL-E 2
Sam Altman on Public Sector AI, ownership and incentives
Kate Crawford and Azeem Azhar on AI’s societal impact: positioning technology as servant