{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/kb-2026-00277",
  "headline": "Explainable AI (XAI)",
  "description": "Explainable AI makes model decisions interpretable by humans. As models become more complex (deep NNs, LLMs), understanding WHY a model made a decision becomes critical for trust, debugging, and regulatory compliance (EU AI Act, GDPR). Methods: SHAP (feature importance), LIME (local explanations), attention visualization, saliency maps.",
  "dateCreated": "2026-05-22T14:59:47.491Z",
  "dateModified": "2026-05-22T14:59:47.491Z",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "human_only",
  "citation": []
}