{
  "id": 9080,
  "url": "https://doi.org/10.1016/j.caeai.2022.100074",
  "title": "Explainable Artificial Intelligence in education",
  "summary": "There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this paper argues that XAI in education has commonalitie",
  "authors": "Hassan Khosravi, Simon Buckingham Shum, Guanliang Chen, Cristina Conati, Yi‐Shan Tsai, Judy Kay",
  "category": "research",
  "topics": "bias-fairness,children-education,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2022-01-01T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:50.743Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9080",
  "original_url": "https://doi.org/10.1016/j.caeai.2022.100074",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}