MENTAL MODEL · M1620

Constitutional AI

BusinessHigh supportManagement

Included

Version 1.0.0 · Updated 2026-07-30

CORE DEFINITION

Instead of teaching AI what is right through massive human annotation (RLHF), it provides AI with a set of high-level principles (a constitution, such as "do no harm" and "be useful"), allowing AI to self-criticize and correct its outputs based on these principles.

SCAFFOLDING EFFECT

psychology

Reduce cognitive load

Principle-based governance. When managing millions of employees (or AIs), micromanagement (correcting each one individually) is impossible. It is necessary to establish a "constitution" (core values) to give the system a moral compass for self-correction.

anchor

Anchor fast decisions

Instead of relying on massive human annotation (RLHF), it provides the model with a set of high-level principles (a constitution, such as "do no harm" and "be useful"), allowing the model to self-criticize and revise its outputs accordingly, then train on the revised samples. This upgrades "micro-correction" to "principle-based self-discipline", which is scalable and reduces human bias.

MINIMUM ACTION

In progress 0/5

Practice this model in one real situation:

Formulate high-level principles (constitution)
Model self-critiques the initial draft
Revise outputs according to principles
Use (critique, revision) pairs for supervised fine-tuning
Use revised data for reinforcement learning (RLAIF).

Check to track your progress (stored locally)

Learning progress0%

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Source support: Explicit

link
en.wikipedia.orghttps://en.wikipedia.org/wiki/Claude_%28AI%29ZH · Explicit
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