Verified claim · AI-ML · 100% confidence
Anthropic Constitutional AI Harmlessness introduced in paper: Bai et al. 2022 — training a helpful and harmless assistant.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 6fa575eb9df5ac32
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Structured fields
- Subject
- Anthropic Constitutional AI Harmlessness
- Predicate
introduced_in_paper- Object
- Bai et al. 2022 — training a helpful and harmless assistant
- Confidence
- 100%
- Tags
- constitutional-ai · cai · anthropic · alignment · harmlessness · foundational · 2022 · introduced_in
Sources (2)
[1] preprint · arXiv (Bai, Kadavath, Kundu, Askell, Kernion, Jones, Chen, et al. / Anthropic) · 2022-12-15
Constitutional AI: Harmlessness from AI Feedback“As AI systems become more capable, we would like to enlist their help to supervise other AIs. We experiment with methods for training a harmless AI assistant through self-improvement, without any human labels identifying harmful outputs.”
[2] official blog · Anthropic · 2023-05-09
Claude's ConstitutionAnthropic is rated by SourceScore — see its reliability →
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curl https://sourcescore.org/api/v1/claims/6fa575eb9df5ac32.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/6fa575eb9df5ac32.json");
const envelope = await r.json();
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// "Anthropic Constitutional AI Harmlessness introduced in paper: Bai et al. 2022 — training a helpful and harmless assistant."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/6fa575eb9df5ac32.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Anthropic Constitutional AI Harmlessness introduced in paper: Bai et al. 2022 — training a helpful and harmless assistant."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_anthropic_constitutional_ai_harmlessness_fact() -> dict:
"""Fetch the verified SourceScore claim for Anthropic Constitutional AI Harmlessness."""
r = httpx.get("https://sourcescore.org/api/v1/claims/6fa575eb9df5ac32.json")
return r.json()