{
  "id": 11778,
  "url": "https://arxiv.org/abs/2607.15532v1",
  "title": "Logic, Optimization, and Artificial Intelligence",
  "summary": "Logic and optimization can, in combination, make valuable contributions to rule-based AI. Logic is the obvious medium for encoding a rule base and drawing inferences from it, while optimization provides a powerful technology for computing inferences. Their combination has taken on new relevance amid a growing concern for transparency in AI. which is important for reproducibility, explainability, trustworthiness, and fairness. Rule-based AI provides a natural solution to transparency that is beco",
  "authors": "J. N. Hooker",
  "category": "research",
  "topics": "bias-fairness,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-17T00:46:08.000Z",
  "fetched_at": "2026-07-20T05:10:09.534Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/11778",
  "original_url": "https://arxiv.org/abs/2607.15532v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}