Why AI hasn't boosted productivity yet: The reliability gap and the J-curve effect
sayashk · x · 2026-08-29
This essay investigates why AI, despite the hype, has had a negligible macroeconomic impact. It attributes this to a 'reliability/capability gap,' where AI performance is 'jagged' and prone to generating 'workslop' (convincing but low-quality output), necessitating new verification loops. It cites the 'productivity J-curve' theory: initial adoption of general-purpose technologies often lowers measurable productivity due to investments in intangible capital like organizational restructuring and process redesign before gains materialize.
More from AGI Musings
- Game studios can sell privately hosted realistic games to AI labs as training environments — dejavucoder · 2026-10-15
- Retellings Use New Perspectives to Replace Romance with Therapeutic Diagnosis — eigenrobot · 2026-10-15
- CHI Reviewer: AI Slop Is Real, but Unusually Rigorous Papers Still Getting Through — IanArawjo · 2026-10-15
- ASML Sells Zero Lithography Machines into Europe as US Hosts 75%+ of AI Compute — NinaDSchick · 2026-10-15
- Into the Unknown: CMU benchmark finds 114 of 135 AI-written research papers fail integrity checks — arankomatsuzaki · 2026-10-15
- LLMs-as-Media Erode Producer Power; Author Ties It to Securities Reform — curious_vii · 2026-10-15