Definition
Safety in AI involves implementing constraints and safeguards to ensure that automated systems behave predictably and do not cause unintended negative consequences. This includes technical measures like fail-safes, monitoring mechanisms, and ethical guidelines embedded in the decision-making process. Safe AI prioritizes human well-being, requiring rigorous testing and validation before deployment in critical infrastructure or sensitive domains.
Summary
Refers to AI systems designed to operate without causing harm to humans, property, or the environment.
Key Concepts
- Harm Prevention
- Fail-safes
- Predictability
- Risk Mitigation
Use Cases
- Air traffic control systems
- Medical diagnostic tools
- Financial trading algorithms