Asymmetric adoption
adoption asymétrique
Benefits accrue to the people using AI while the correction work falls on others in the workflow. The academic name for what is usually described, loosely, as uneven and undocumented levels of mastery.
The asymmetry is not a transition problem that training will close. It is produced structurally by the absence of a designated role: with no expected level, each person settles at their own, and the differences between those levels become someone else's work.
What it means for an SME running AI
Equity in AI training is not a question of intent. Without documentation of where each person actually stands, it cannot even be dosed.
Sources
- Cheung, Cambridge Open Engage, mai 2026
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