Topic summary
94%1 analyzed article/video512 analyzed words
BS Summary: These Machine Learning Security results contain 26 faulty reasoning types, including Framing Effect, Hasty Generalization, and Appeal to Authority, with Negativity Bias as the most egregious example at 19.4% saturation with 298 hits. Analysis detected 2,176 faulty-reasoning hits from 1,536 analyzed words across 1 article, generating a BS Score of 5.4% and a BS Rank of 78% (3,245 of 14,199 topics). This Machine Learning Security is worse (more manipulative) than 77.20% of the peer group.
Machine Learning Security
Topic details
Loading chart...
Attribute Prevalence (Top 48)
Machine Learning Security attribute prevalence percentages (biases/fallacies), sorted highest to lowest.
Loading chart...
Machine Learning Security vs sitewide
Machine Learning Security attribute percentages, with an overlaid sitewide baseline for those same attributes.