Welcome to Scaling Human-Centered AI

There's a tension at the heart of every AI product team. The technology pushes toward automation: faster, cheaper, more autonomous. The ethics, the regulation, and often the actual product quality push the other way: keep humans in control, in the loop, on the loop. Most teams resolve this tension by accident. They start with humans heavily involved, then quietly remove them as the system scales because review queues get unmanageable. By the time anyone notices, the product has drifted from augmentation into automation, and the humans are doing rubber-stamp work that doesn't add value. This course is for teams that want to be intentional about it. Not blanket automation, not blanket human review. Specific patterns for keeping humans meaningful as your system grows from 100 decisions a day to 100 million. We'll cover: • What "human-centered AI" actually means in production (and what it doesn't) • The math of augmentation vs automation: when each is the right answer • Org structures that survive AI: from team design to performance management • The economics of partial automation: why hybrid often beats fully autonomous • Where HITL hits the wall, and what comes after Prerequisites: useful to have read Human-in-the-Loop Design first, but not required. Bring a real product in mind, even if it's hypothetical. The patterns make more sense when you apply them to something concrete. Time: ~3 hours across 10 articles. Mostly conceptual, with some technical depth in steps 4 to 6.