Source Attribution
Showing your work in AI, identifying which sources an AI response drew on, so users can verify claims and understand where the information came from.
The Simple Version
Showing your work in AI, identifying which sources an AI response drew on, so users can verify claims and understand where the information came from.
Detailed Explanation
Source attribution connects AI output claims to retrievable evidence, addressing both hallucination risks (if a claim cannot be attributed, it may be fabricated) and accountability requirements (users must be able to verify AI-generated assertions). Attribution quality dimensions include correctness (the cited source actually supports the claim), completeness (all major claims are attributed), precision (the attribution identifies the specific passage, not just the document), and accessibility (users can reach the cited source). EU AI Act transparency obligations and GDPR accountability principles create implicit attribution requirements for high-stakes AI-generated content.
Key Characteristics
- Enables claim-level verification of AI-generated outputs
- Quality dimensions: correctness, completeness, precision, and accessibility
- Supports EU AI Act transparency and GDPR accountability requirements
- Increasingly a user expectation for enterprise AI deployments
Why It Matters
Enterprise AI deployments in legal, financial, and compliance contexts should implement citation-level attribution, enabling specialists to verify AI-generated analysis against source documents before acting on it.
Real-World Analogy
Like footnotes in a research paper, each significant claim is backed by a specific, traceable reference that readers can consult to verify the assertion.
Common Misconceptions
- Providing a list of sources at the end of an AI response constitutes attribution, attribution should link specific claims to specific source passages, not just list references.
- Source attribution is only necessary for factual claims, attribution is valuable for any AI-generated content where users may want to evaluate the basis for recommendations or conclusions.
Related Terms
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