How Will AI-Driven Automation Actually Affect Jobs?
Authored by Alex Imas and Soumitra Shukla via Ghosts of Electricity, One of the most widely cited findings in AI policy comes from a 2023 paper by Eloundou, Manning, Mishkin, and Rock titled “GPTs are GPTs.” The title is a nice double meaning: the paper studies how general-purpose technologies (GPTs) powered by large language models (also GPTs) may reshape the labor market. The headline finding is that around 80% of U.S. workers could have at least 10% of their tasks affected by LLMs, and roughly 19% may see half or more of their tasks impacted. Broadly, these exposure measures try to capture how “exposed” the occupation is to AI as a function of whether AI can augment the tasks involved in the job: direct exposure is defined as “whether access to an LLM or LLM-powered system would reduce the time required for a human to perform a specific DWA or complete a task by at least 50%.” The authors are crystal clear on this in the paper: exposure corresponds to the capacity of AI to …









