Question: A company builds a defect-detection system for factory parts. While the system still makes more mistakes than experienced inspectors, engineers can quickly review examples, compare the model with human judgments, and find obvious failures. Later, the system becomes better than the inspectors on the main benchmark. Explain why further progress often becomes slower at that stage.

Sample answer: When the system is still worse than the inspectors, people can easily recognize clear errors and use those cases to guide debugging and model changes. After the system surpasses the inspectors, its remaining errors are harder for people to notice and judge. As a result, fewer human-comparison methods remain useful, so it becomes harder to identify what to improve next and progress slows.

Key points:

• Improvement is usually faster while the model is still below human performance
• Human reviewers can spot clear mistakes more easily in that stage
• After the model exceeds human performance, its remaining errors are harder to detect
• Fewer human-comparison tools remain effective, which slows further gains

Rubric: Full credit requires explaining both stages, describing why humans can diagnose problems more easily before the model reaches human performance, and linking the slowdown to the reduced usefulness of human-based comparison methods.