{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Explainable AI — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"<div style=\"font-family:sans-serif;border:1px solid #e0e0e0;border-radius:8px;padding:16px;max-width:600px;background:#ffffff;color:#111111;\"><p style=\"margin:0 0 4px;font-size:11px;color:#666;\">AI Glossary — gaks.ai</p><h3 style=\"margin:0 0 8px;font-size:16px;\">Explainable AI (XAI)</h3><p style=\"margin:0 0 12px;font-size:14px;line-height:1.6;\">A field of research and practice focused on making AI systems' decisions understandable to humans, developing methods that can explain why a model produced a particular output in terms that non-experts can interpret. XAI encompasses a range of techniques from feature importance scores and saliency maps to natural language explanations, and is increasingly required in regulated industries and high-stakes applications.  See also: explainability, interpretability, algorithmic accountability.</p><a href=\"https://gaks.ai/glossary/explainable-ai\" style=\"font-size:12px;color:#0077aa;\">Source: gaks.ai/glossary/explainable-ai →</a></div>"}