Human expertise—the deep, tacit knowledge that comes from years of practice and experience—may be eroding as AI systems take over tasks that once developed and maintained expertise. Pilots who rely on autopilot lose manual flying skills. Radiologists who use AI assistance may develop less pattern recognition capability. Writers who use AI for drafts may not develop the same writing skill. This erosion could leave humanity dependent on AI systems we don’t fully understand or control.
The mechanism is straightforward: expertise requires practice, and AI reduces practice. When AI handles tasks, humans don’t get the repetitions needed to develop and maintain skill. Studies show that skills atrophy without use—surgeons who don’t operate regularly lose dexterity, programmers who use AI heavily may not internalize language details, analysts who rely on AI may not develop intuition. Over time, this could mean fewer humans capable of checking AI work, training AI systems, or functioning if AI fails.
The preservation of expertise requires deliberate design choices. AI systems can be built to augment rather than replace human capability. Training programs can maintain skills even as AI assists. And critical expertise can be identified and protected. But without such efforts, the natural economic pressure toward efficiency will tend to eliminate human involvement—and with it, human expertise.