{
  "id": 15001,
  "url": "https://link.springer.com/article/10.1007/s10462-026-11650-2",
  "title": "Automated machine learning in the era of large language models: a systematic review of green, trustworthy, and human-centered automation (2020–2026)",
  "summary": "Automated Machine Learning (AutoML) has rapidly transformed the landscape of artificial intelligence by democratizing access to sophisticated machine learning models and streamlining complex development workflows. This systematic review, conducted in accordance with the PRISMA 2020 guidelines, comprehensively analyzes the evolution of AutoML from 2020 to early 2026 (final search conducted in early February 2026), with a particular focus on the integration of Large Language Models (LLMs) and the",
  "authors": null,
  "category": "research",
  "topics": "jobs-economy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-30T00:00:00.000Z",
  "fetched_at": "2026-07-31T05:10:57.675Z",
  "source_slug": "x-artificial-intelligence-review",
  "source_name": "Artificial Intelligence Review",
  "source_homepage": "https://link.springer.com/journal/10462",
  "ethics_ai_record_url": "https://ethics.ai/record/15001",
  "original_url": "https://link.springer.com/article/10.1007/s10462-026-11650-2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}