CONCEPT
The AI Deskilling Evidence
The emerging body of 2023-2025 empirical research documenting measurable degradation of professional capability among practitioners who rely heavily on AI tools, precisely as Ericsson's framework predicts.
Beginning in 2023 and accelerating through 2025, a growing body of empirical research has documented a specific pattern across multiple professional domains: practitioners who rely heavily on AI tools show elevated performance when the tools are available and degraded capability when they are removed. Endoscopists using AI for polyp detection showed a 6-percentage-point drop in adenoma detection rates when AI was withdrawn. Students with GPT-4 access performed better initially but worse than never-AI peers once access was removed. Carnegie Mellon researchers observed that AI-using knowledge workers ceded problem-solving expertise to systems while focusing on integration tasks. Each finding is exactly what the friction requirement predicts: removal of developmental conditions produces erosion of the capability those conditions build.
In The You On AI Field Guide
The Hosanagar research at Wharton on endoscopist deskilling has become the most-cited example because the domain is high-stakes, the measurement is precise, and the effect size is clinically significant. Adenoma detection rates of 28% fell to 22% when AI was