{
  "id": 17013,
  "url": "https://arxiv.org/abs/2608.05800",
  "title": "Validity, Reliability, and Transparency in Artificial Intelligence Regulation",
  "summary": "arXiv:2608.05800v1 Announce Type: new Abstract: Artificial intelligence (AI) systems increasingly mediate decisions affecting individuals and societies. Existing data protection frameworks address certain privacy-related harms, particularly those arising from data leakage, re-identification, and profiling. However, they inadequately capture a more fundamental risk: unreliable or unjustified inference produced by AI systems even when data collection and processing are legitimate. This article arg",
  "authors": "A. Mukundan, Debayan Gupta, Subhashis Banerjee",
  "category": "research",
  "topics": "regulation,privacy-surveillance,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-07T04:00:00.000Z",
  "fetched_at": "2026-08-07T05:10:58.501Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17013",
  "original_url": "https://arxiv.org/abs/2608.05800",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}