Constitutional AI
An alignment approach developed by Anthropic where AI models are guided by a set of principles (a 'constitution') that help them self-evaluate and improve their responses without relying solely on human feedback.
Why It Matters
Constitutional AI offers a scalable alternative to RLHF — instead of needing human raters for everything, the model can self-correct based on clear principles.
Example
A model generating a response, then evaluating it against principles like 'Is this helpful? Is this honest? Could this cause harm?' and revising accordingly.
Think of it like...
Like a person with a strong moral compass who self-corrects — they do not need someone watching over their shoulder because their principles guide their behavior.
Related Terms
Alignment
The challenge of ensuring AI systems behave in ways that match human values, intentions, and expectations. Alignment aims to make AI helpful, honest, and harmless.
RLHF
Reinforcement Learning from Human Feedback — a technique used to align language models with human preferences. Human raters rank model outputs, and this feedback trains a reward model that guides further training.
AI Safety
The research field focused on ensuring AI systems operate reliably, predictably, and without causing unintended harm. It spans from technical robustness to long-term existential risk concerns.
Anthropic
An AI safety company founded by former OpenAI researchers, focused on building safe and beneficial AI. Anthropic developed Claude and pioneered Constitutional AI.