Fair for whom
A workflow can look efficient and still create uneven impact. When people can't see how decisions are made, it becomes harder to notice who benefits, who is burdened, and who is being left out entirely.
This video brings a common design problem into sharp focus. The same AI-assisted process can feel completely fair to one person and deeply unfair to another, depending on what is visible and what is checked. You are about to see exactly how that happens.
Reflection
Think of one workflow in your setting that includes prioritizing, sorting, or deciding who gets support first. What information would you need to see to judge whether the process is fair?
Why it matters: When an AI-assisted workflow isn't transparent, people can't see why decisions are made, and it becomes harder to notice and correct uneven impacts across groups. Making criteria, checkpoints, and monitoring visible supports accountability and continuous improvement by allowing the process to be explained, reviewed, and revised over time. That kind of visibility isn't optional: it's what separates a workflow that builds trust from one that quietly erodes it.