We already know this is about self-driving cars. Passing a driver's test was already possible in 2015 or so, but SDCs clearly aren't ready for L5 deployment even today.
There are also a lot of excellent examples of failure modes in object detection benchmarks.
Tests, such as driver's tests or standardized exams, are designed for humans. They make a lot of entirely implicit assumptions about failure modes and gaps in knowledge that are uniquely human. Automated systems work differently. They don't fail in the same way that humans fail, and therefore need different benchmarks.
Designing good benchmarks that probe GPT systems for common failure modes and weaknesses is actually quite difficult. Much more difficult than designing or training these systems, IME.