concept · concepts/Secret Cyborgs.md
Secret Cyborgs
Ethan Mollick's term for workers who use AI productively but hide it — the gap between ~20% official tool adoption and 40%+ who privately admit large AI-driven gains.
The incentive trap
Mollick frames hidden use as rational. A worker has more reasons to stay quiet than to disclose:
- They were warned that improper AI use could be punished, and won't risk it.
- They're celebrated for AI-assisted output but fear losing respect if it's known to be AI.
- They suspect revealed productivity gains → cost-cutting → someone gets fired.
- They expect no reward for disclosure — or worse, that gains just become the new baseline expectation ("more work will get done").
"There are more reasons for workers to not use AI publicly than to use it." The result: the org's most valuable learning stays invisible.
The fix (a Leadership problem)
Per Leadership, Lab, and Crowd: define clear zones where experimentation is permitted and bias toward allowing AI; reframe training as hands-on experience and communicating needs to AI (less about prompting tricks); credibly reassure workers that revealed gains won't trigger layoffs; offer real incentives (vacations, promotions, cash) for transformational discoveries; and have leaders model AI use openly.
Connections
- Leadership, Lab, and Crowd — surfacing Secret Cyborgs is how the Crowd's learning reaches the Lab.
- AI and Employment — Replacement vs Expansion — fear of layoffs is a top reason workers hide use; the disclosure problem is downstream of the jobs debate.
- Individual vs Organizational AI Gains — hidden use is one mechanism by which individual gains fail to become org gains.