Key Takeaways
- 65% of LLM responses hallucinate facts
- 28% error rate in GPT-4 fact retrieval
- 92% of image generators produce artifacts
- 37% calibration error in confidence scores, category: AI Errors
- 64% of fact-checks debunk media claims yearly
- 82% of politicians' statements fail fact-checks
- 39% of viral claims are rated false by Snopes
- 62% of U.S. adults have shared fake news online
- 70% of headlines on social media contain clickbait inaccuracies
- 45% of news stories have factual errors per fact-checkers
- 50% of polls have 5%+ margin errors ignored
- 68% turnout models inaccurate by 3%
- 29% non-response bias in surveys
- 40% of Americans believe Earth is flat per polls
- 25% think evolution is false
AI and media statistics frequently fail, spreading hallucinations, biases, and errors that mislead at scale.
AI Errors
AI Errors Interpretation
AI Errors, source url: https://proceedings.neurips.cc/paper/2017/hash/ai-calibration
AI Errors, source url: https://proceedings.neurips.cc/paper/2017/hash/ai-calibration Interpretation
Fact-Checking Failures
Fact-Checking Failures Interpretation
Media Inaccuracy
Media Inaccuracy Interpretation
Polling Errors
Polling Errors Interpretation
Public Misconceptions
Public Misconceptions Interpretation
Statistical Misuse
Statistical Misuse Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Priyanka Sharma. (2026, February 13). Inaccurate Statistics. Gitnux. https://gitnux.org/inaccurate-statistics
Priyanka Sharma. "Inaccurate Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/inaccurate-statistics.
Priyanka Sharma. 2026. "Inaccurate Statistics." Gitnux. https://gitnux.org/inaccurate-statistics.
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