AI Alignment
Definition
AI Alignment is the discipline of ensuring an AI system's behavior matches human intent, values, and operational constraints. In the enterprise, alignment is a design requirement, not a research aspiration.
Why it matters
The business case for AI Alignment.
Misaligned AI does exactly what it was trained to do, which may not be what you want. Alignment failures in production are typically specification failures, not model failures.
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.
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