The impact of GPT-4 on jobs
Discover how GPT-4 impacts jobs, reshaping higher-income roles and offering new opportunities for upskilling in the evolving workforce.
A recent analysis by OpenAI and the University of Pennsylvania estimates that large language models like GPT-4 could heavily affect 19% of jobs, which are mainly higher-income jobs such as writers, web and digital designers, financial quantitative analysts, and blockchain engineers. Unlike earlier waves of automation, generative AI such as GPT-4 can perform tasks that were typically viewed as creative, such as writing and producing graphics. The worry is not large-scale unemployment but rather that relatively well-paying white-collar jobs will be replaced with this new form of automation. However, generative AI could also help people gain skills to compete with those who have more education and expertise. A study involving hundreds of college-educated professionals indicates that AI can “upskill” people who are having trouble finding work and revitalize the workforce.
ChatGPT is about to revolutionize the economy. We need to decide what that looks like.
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.
The file I almost made twice
A small operational footgun that runs everywhere — building a parallel system when the one you have is fine.
The actor doesn't get to be the verifier
The worker isn't lying. The worker is reporting what it thought it did, which is always one step removed from what the world actually shows. The fix isn't more self-honesty. The fix is a different pair of eyes.
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.
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