Human Oversight

"If policymakers want human oversight to mean more than a reassuring slogan, they should design for judgment, not just for review.

"That means:

• Evaluating whether a task structure makes scrutiny realistic under time pressure; 
• Testing whether users can detect model failures after repeated exposure; 
• Requiring post-deployment monitoring of over-reliance risks; 
• Investing in training that addresses decision behavior rather than mere tool familiarity; and 
• Ensuring that override rights are operationally meaningful, not only formally available.

"What kinds of reliance are they designing into public workflows: 

• Are agencies creating conditions for active scrutiny or passive acceptance? 
• Are officials being asked to interpret outputs or merely ratify them? 
• Are explanations usable enough to support judgment, or are they functioning mainly as a compliance ritual? 
• Are agencies measuring speed and productivity while ignoring long-term degradation in vigilance and responsibility?

"The next public-sector AI fight is not whether governments will use AI. That is already happening. 

"The real fight is whether human oversight will refer to genuine, effortful judgment or to a procedural checkpoint that allows accountability to remain in name while the practical capacity to exercise it is designed out of the process."