Which BEST addresses hallucination risk in AI systems?

Question

Options

• AHuman oversight
• BRecursive chunking
• CAutomated output validation
• DContent enrichment

• A
  89% (39)
• B
  7% (3)
• C
  2% (1)
• D
  2% (1)

Explanation

AI hallucination occurs when a model generates plausible-sounding but factually incorrect or fabricated content. Human oversight is the most effective control because humans can critically evaluate outputs, cross-check facts against authoritative sources, and exercise contextual judgment that automated systems lack. Automated output validation (C) can catch structural issues but cannot reliably detect subtle factual errors. Recursive chunking (B) is a retrieval-augmented generation (RAG) technique that improves context retrieval but does not eliminate hallucinations. Content enrichment (D) adds data but does not directly validate accuracy of generated outputs.

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