AI Safety
The field concerned with preventing AI systems from causing harm, from everyday failures to systemic risks.
AI safety spans near-term issues — a model giving dangerous instructions, a system failing silently in production — and longer-term concerns about highly capable systems. It is engineering practice as much as philosophy: evaluation, red teaming, monitoring, and rollback are all safety work.
In practice: Testing what a model does with a request it should refuse, before customers find out.