How would you design transparency and human oversight for an AI feature?

I evaluate whether people notice the disclosure, understand the limitation, detect common errors, and use escalation appropriately rather than assuming the UI works. Automation bias, alert fatigue, accessibility, language, and power differences shape the design. Corrections and appeals feed owned improvement processes without automatically becoming trusted training data. Transparency requirements are versioned by jurisdiction and product risk, but the durable engineering boundary is that a responsible person or service can inspect, interrupt, correct, and account for consequential behavior.