Data journalists who use AI to generate chart labels, data captions, and visualisation annotations face a specific risk: AI-generated descriptive text around data can contain subtle factual errors — incorrect unit labels, misinterpreted trend directions, wrong time periods, or incorrect source attributions — that pass visual review but are factually incorrect. Omniscient AI verifies the factual claims in data visualisation text as rigorously as article body text.
Chart Caption Verification Workflow
After generating AI-assisted chart captions and labels: extract all text elements containing factual claims (axis labels, title assertions, caption claims, data call-outs). Submit as discrete claim statements to Omniscient AI ("The unemployment rate was 3.7% in Q4 2024 according to the Bureau of Labor Statistics"). Review verification results — any claim that fails verification triggers a primary source check against the data source directly. Correct before publication. For major data journalism packages with 20+ visualisations, this process takes 30–45 minutes total — a worthwhile investment given that visualisation errors are often the most viral form of fact error.