AI Safety
AI safety is the interdisciplinary field focused on ensuring that AI systems behave as intended, remain under human control, and do not cause unintended harm. It encompasses technical research areas like alignment (making AI pursue the right goals), robustness (maintaining safe behavior under adversarial conditions), interpretability (understanding why models make decisions), and governance (establishing rules and oversight for AI development).
Example
An AI safety team at a lab tests whether their model can be manipulated into providing dangerous information, studies how to make the model reliably refuse harmful requests without being overly cautious on benign ones, and develops monitoring systems that flag when the model's behavior drifts from its intended guidelines.
Put this into practice
Build polished, copy-ready prompts in under 60 seconds with SurePrompts.
Try SurePrompts