The landscape of Artificial Intelligence is evolving at an unprecedented pace, necessitating a fundamental rethinking of how we evaluate AI systems. Traditional benchmarking, often focused on narrow task performance metrics like accuracy, F1-score, or FLOPs, is increasingly insufficient to capture the complexity, ethical implications, and real-world utility of modern AI. As AI permeates critical domains from healthcare to autonomous systems, the demand for
