AI Safety
Measures and engineering practices ensuring AI systems do not cause unreasonable harm to people, property, or the environment during intended use or foreseeable misuse.
Definitions (2)
For CAISI, AI safety refers to research and operational practices that reduce the probability of harmful outcomes from AI systems, including but not limited to misinformation, privacy leakage, cyber‑exploitation, and hazardous autonomous behaviour. It frames the institute's work on detection, mitigation, robustness, alignment, and safe deployment.
Encompasses the robustness, reliability, security, and controllability of AI systems, ensuring they operate as intended without causing unintended harm or risks to individuals, society, or national security.
Related Terms
Safety Component
A part of a product or AI system that performs a safety function and whose failure could endanger people or property....
Risk Management
Systematic process of managing AI-related risks....
Robustness
The ability of an AI system to maintain acceptable performance and resist failures, attacks, or unexpected conditions across its lifecycle....
Trustworthy AI
AI that is safe, fair, transparent, accountable, and privacy-preserving....