AI Safety
Definition
AI Safety is the practice of preventing AI systems from causing harm through behavior that is unsafe, unintended, or outside acceptable bounds. Safety is distinct from AI security (which defends against external attack) and alignment (which concerns intent matching).
Why it matters
The business case for AI Safety.
Safety failures expose the enterprise to regulatory, financial, and reputational damage. An AI system that performs brilliantly 999 times and catastrophically once is not a safe system.
Related terms in Deterministic AI
Deterministic AI
Deterministic AI produces the same output for the same input, every time. Unlike probabilistic AI, deterministic systems deliver consistent, predictable, auditable outcomes that enterprise operations can rely on.
Probabilistic AI
Probabilistic AI generates outputs based on statistical likelihoods. The same input may produce different outputs across runs. Most large language models are probabilistic by design.
Generative AI
Generative AI is a class of probabilistic AI that creates new content, text, images, code, audio, based on patterns learned from training data. ChatGPT, Claude, and Midjourney are generative AI systems.
AI Hallucination
AI Hallucination occurs when a generative AI system produces output that is plausible-sounding but factually incorrect or fabricated. Hallucinations are a structural feature of probabilistic AI, not a bug.
Explainable AI (XAI)
Explainable AI refers to AI systems whose decisions and outputs can be understood and traced by humans. XAI is critical for governance, compliance, and trust.