https://aifaultline.com/authors/tyna-eloundou/New papers by Tyna Eloundou in the AI Fault Line guide, and news naming them. https://aifaultline.com/research/p/doi-10-1257-pandp-20251045/https://aifaultline.com/research/p/doi-10-1257-pandp-20251045/Thu, 01 May 2025 00:00:00 +0000The paper combines occupation-level LLM exposure scores with Revelio Labs employee counts to measure exposure for individual firms. Firms with more technology and AI-skilled workers are more exposed, and the authors read the size of the differences as a sign that integrating LLMs could bring significant productivity gains. https://aifaultline.com/research/p/doi-10-48550-arxiv-2303-10130/https://aifaultline.com/research/p/doi-10-48550-arxiv-2303-10130/Fri, 17 Mar 2023 00:00:00 +0000Combining human ratings with GPT-4 classifications, finds that roughly 80% of the U.S. workforce could see at least 10% of their tasks affected by large language models, and about 19% could see over half their tasks affected, with higher-wage occupations facing greater exposure than lower-wage ones. With an LLM alone about 15% of all worker tasks could be completed significantly faster, rising to 47-56% when LLM-powered software tools are included — evidence often cited to argue AI functions as a general-purpose technology with economy-wide reach rather than a narrow labor-saving tool.