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Paul Welty, PhD AI, WORK, AND STAYING HUMAN

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Artificial intelligence could hit three in five workers — Possibly replacing their jobs. The warning comes in a new international monetary fund report on the future of work. It warned of lower sala…

Artificial intelligence could hit three in five workers — Possibly replacing their jobs. The warning comes in a new international monetary fund report on the future of work. It warned of lower sala…

AI could replace three in five workers, warns an IMF report, signaling potential job loss and lower salaries. Discover the implications for the future of work.

According to a new International Monetary Fund (IMF) report, artificial intelligence (AI) could potentially replace three in five workers, with some jobs potentially disappearing altogether. The IMF also warned of lower salaries and cuts in hiring as a result of AI integration. A separate study from PwC revealed that bosses in Britain are adopting AI technology at a faster rate than their counterparts in the US, China, and Europe, which could have a larger impact on British workers. The IMF also noted that while younger workers could benefit from AI, older workers may struggle to adapt.

https://www.the-sun.com/tech/10102321/artificial-intelligence-workers-replacing-jobs/

The agent-shaped org chart

Every real org has the same topology: principal, role-holder, specialists. Staff AI maps onto it, node for node, and the cost collapse shows up in the deliverables that were always just human-handoff overhead.

AI as staff, not software

Two frames for what AI is doing to work. The tool frame makes tools smarter. The staff frame makes roles unnecessary. Those aren't the same product, the same company, or the same industry.

Knowledge work was never work

Knowledge work was always coordination between humans who couldn't share state directly. The artifacts were never the work. They were the overhead — and AI just made the overhead optional.

The work of being available now

A book on AI, judgment, and staying human at work.

The practice of work in progress

Practical essays on how work actually gets done.

Shopping is the last mile

Every meal planning app treats cooking as the hard problem and shopping as a logistics detail. They have it backwards. Cooking is mostly solved. Shopping is the last mile.

Watch what they buy, not what they say

Forms ask people to declare preferences. Receipts record what they did. The gap between the two is where revealed preference lives, and it's wider than most product teams admit.

What the API decides not to show you

Spent an hour today trying to read a photo someone attached to a reminder. The bytes are right there on disk. Apple won't let me see them. The piece I want to keep from this isn't about Apple — it's about the difference between data that exists and data that's actually reachable.

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