{"text":[[{"start":0,"text":"Where do new jobs come from? The economist Joseph Schumpeter had an answer: waves of technology destroy old work, making way for the newer sort. Perhaps older readers remember punch-card operators and video rental shop managers, now made obsolete by the computer and digital revolutions. And maybe younger readers wonder whether they will live long enough for the only jobs left to be AI engineers."}],[{"start":29.56,"text":"Some 250 years ago, the economist Adam Smith emphasised a different source of new work: specialisation. Jobs are essentially bundles of tasks. Big markets allow people to unbundle those tasks, divide them up, and produce much more. Like his famous pin factory, which split manufacturing into parts (cutting wire, pointing it, etc), specialists vastly increased output over artisanal pin makers doing everything on their own."}],[{"start":56.56,"text":"So . . . who is right? The answer is complicated by the two stories being hard to separate. Technology could enable specialisation, as when the computing revolution made it easier to co-ordinate between faraway factories. Advances in knowledge could push specialisation too, as it becomes unreasonable to expect one person to be an expert in everything."}],[{"start":76.52,"text":"Economic historians have tried to see through the fog, analysing past labour market revolutions to get a sense of which dynamics mattered. One group used court records to find evidence in favour of Smith, documenting how the job in Britain of “clock maker” in 1550 had fractured into tens of jobs including “watch engraver”, “watch gilder” and “watch spring maker” 200 years later. Over that period, bigger British markets saw more specialisation."}],[{"start":103.68,"text":"A recent study of the US labour market used a large language model to indicate whether jobs were “technology-related”. (A wind turbine erector would qualify, whereas a drama therapist would not.) Of the new employment introduced between 2011 and 2023, they calculated that the tech-related share was roughly a third. Substantial, though not a majority."}],[{"start":121.32,"text":"A new study of the Swedish labour market takes a longer view, armed with detailed data on jobs between 1880 and 2019 — using AI to assign every occupation two scores out of five. The first is a “Smithian” score, indicating whether the job is the result of specialisation. (Wholesale traders and radiologists get high marks.) The second is a “Schumpeterian” score, to reflect how strongly the job is associated with a new technology. (Big numbers for computer programmers and electricians.)"}],[{"start":152.62,"text":"With the caveat that the lines between technology and specialisation can be blurry, the researchers get some interesting results. Over time, jobs with both high Smithian and Schumpeterian scores have become more important as a share of the total. But the jobs associated with the division of labour have contributed the bulk of the change. Between 1990 and 2019, strongly Smithian jobs accounted for 60 per cent of employment, compared to just a third for strongly Schumpeterian ones."}],[{"start":182.48,"text":"Relatedly, Smithian jobs seem much more likely to last than their highly Schumpeterian counterparts. Tech jobs are important for the jobs elsewhere that they enable. But they seem relatively vulnerable to becoming obsolete. Those punch-card operators were at the cutting edge . . . until they got replaced. Although we might fret now about AI sweeping away jobs in a wave of creative destruction, thinking about how it will affect specialisation could be more instructive. The Sweden study’s authors calculated that around 70 per cent of employment between 1990 and 2019 was in occupations that existed at the end of the 19th century. What matters now is which tasks stay bundled within jobs and which move elsewhere."}],[{"start":225.72,"text":"As Luis Garicano, an author of the book Messy Jobs, put it to me, some bundles of tasks are only weakly held together, and are therefore ripe for AI disruption. He also noted that past trends could reverse if AI makes specialist subjects so accessible that it becomes easier to bring them in-house, rather than suffer the cost of co-ordinating with other experts. (Think of an economics columnist deciding to build her own website rather than pay a freelancer.)"}],[{"start":252.62,"text":"The toe-treading has already begun. Data from OpenAI suggests that of work-related messages, around 17 per cent are already about tasks associated with another occupation. If the division of labour reversed, “that would be an unusual feature of this revolution relative to all the previous progress in science”, Garicano told me. But a final message of the research is that technological revolutions do not tend to be alike."}],[{"start":283.6,"text":""}]],"url":"https://audio.ftcn.net.cn/album/a_1789635682_8845.mp3"}