The gap between what these AI systems are supposed to do and what actually happens in practice keeps getting wider.
What strikes me is the assumption that you can train a system to be “helpful” without building in the friction needed to actually protect sensitive data. Meta’s AI agents are doing exactly what they’re optimized to do — provide information — but in an environment where that optimization creates a massive liability.
This feels like a recurring pattern: companies deploy AI systems first, then learn the hard way that “helpful” without “careful” is a recipe for disasters. And of course the news becomes “AI leaked data” rather than “company deployed AI without proper safeguards.” The system gets the blame, but the architecture was the choice.
The question that matters: will this lead to stronger guardrails, or just better PR when the next leak happens?
HootinNHollerin@lemmy.dbzer0.com 1 day ago
Everything with nets is a sensitive data leak. Intentional from the beginning. Right to the Feds too