{
  "id": 6702089,
  "title": "Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models",
  "url": "https://urgent.news/2026/09/10/explainability-assistant-a-conversational-xai-interface-for",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T17:40:11.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11860v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Energy consumption forecasting relies on increasingly complex machine learning (ML) models, such as Genetic Programming-based symbolic regressors, whose predictions can be difficult for facility managers and building operators to interpret. Explainable Artificial Intelligence (XAI) techniques address this opacity, but traditional XAI dashboards require substantial technical expertise and provide…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}