COMPEL Glossary / ai-safety
AI Safety
AI Safety is the field of research and practice dedicated to ensuring that AI systems operate without causing unintended harm to individuals, organizations, or society.
What this means in practice
It encompasses technical concerns such as model alignment with human intentions, robustness to adversarial inputs, safe behavior under uncertainty, and prevention of dangerous emergent capabilities in advanced systems. For organizations deploying AI, safety practices range from rigorous testing and monitoring of production systems to establishing human oversight mechanisms for high-stakes decisions. In the COMPEL framework, AI safety intersects with both the Governance and Technology pillars, informing the risk assessment processes during Calibrate, the guardrail design during Model, and the monitoring infrastructure established during Produce. The EU AI Act and NIST AI RMF both place safety as a foundational requirement.
Why it matters
As AI systems become embedded in high-stakes decisions affecting health, safety, financial stability, and civil rights, the consequences of unsafe AI operation escalate from business inconvenience to genuine harm. Organizations that build safety into their AI development practices proactively are far better positioned than those forced to retrofit safety after incidents occur. Safety is increasingly a regulatory prerequisite for market access under frameworks like the EU AI Act.
How COMPEL uses it
AI safety intersects with both the Governance and Technology pillars across multiple COMPEL stages. During Calibrate, safety risks are identified and assessed. During Model, guardrails and human oversight mechanisms are designed. The Produce stage implements safety controls and monitoring infrastructure, and the Evaluate stage validates that safety measures are functioning effectively. Safety requirements from the EU AI Act and NIST AI RMF are mapped into COMPEL governance artifacts.
Related Terms
Other glossary terms mentioned in this entry's definition and context.