{
  "id": 19056,
  "url": "https://arxiv.org/abs/2608.11251v1",
  "title": "Variable Selection in the Context of AI Fairness",
  "summary": "Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into account philosophical ethics and social awareness. Variable selection processes, in particular, can introduce implicit bias, affecting equity across different subgroups. We discuss a mathematical approach that evaluates fairness in AI, aligning mathematical methodologies with ethical considerations and regulatory requirements. Our aim is to advocat",
  "authors": "Ivan Luciano Danesi, Chiara Frigerio, Fabio Maccaferri, Giorgio Alessandro Motta, Pietro Zecca",
  "category": "research",
  "topics": "bias-fairness,regulation",
  "orgs": null,
  "regions": "eu",
  "published_at": "2026-08-04T20:36:18.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "source_slug": "x-arxiv-fairness-query",
  "source_name": "arXiv fairness query",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/19056",
  "original_url": "https://arxiv.org/abs/2608.11251v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}