https://aifaultline.com/authors/daniel-rock/New papers by Daniel Rock 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-10-1257-mac-20180386/https://aifaultline.com/research/p/doi-10-1257-mac-20180386/Wed, 30 Dec 2020 00:00:00 +0000Argues that general-purpose technologies like AI require large, often-intangible complementary investments that official statistics undercount, producing a 'Productivity J-curve': measured productivity growth is understated early in a technology's diffusion and overstated later as those investments pay off. Applying the model to U.S. data on computer hardware and software, the authors estimate 2017 total factor productivity was 15.9% higher than official figures once intangible capital is included — a key reference point for economists arguing today's modest measured AI productivity gains understate its eventual impact.