AI agents seem to be increasingly capable of performing economically valuable tasks, but current benchmarks measure this capability only narrowly. Zora Z. Wang and colleagues at Carnegie Mellon University and Stanford University mapped examples drawn from agent benchmarks to statistics that represent U.S. labor. The mapping revealed a mismatch between the tests, which generally emphasize software development, and the more varied work most people do. Read the full article in The Batch:…