Case context: Your team has established human-level performance for high-resolution web images at 1%. However, your application will deploy on mobile phones, where images are blurry and poorly lit. You are trying to determine if your algorithm's 5% error on mobile data is acceptable.

Question: What specific action must your team take to determine an appropriate benchmark for the mobile application data?

Sample answer: The team must take a sample of the actual blurry, poorly lit mobile images and ask humans to label them. By measuring the human error rate on this specific mobile dataset, they can establish the human-level performance benchmark for the mobile distribution.

Key points:

• Use the mobile image dataset.
• Have humans label the mobile images.
• Measure the human error rate to establish the benchmark.

Rubric: The response must identify that humans need to label the mobile data specifically to measure their error rate on that distribution.