{
  "id": 15639,
  "url": "https://arxiv.org/abs/2607.28827",
  "title": "Hidden Errors in Big Data: The Case of Property Records",
  "summary": "arXiv:2607.28827v1 Announce Type: new Abstract: Big data are the foundation for an increasing share of academic research and AI models deployed in both the public and private sectors, prompting substantial growth over time in reliance on brokered datasets. Brokered property records, which are ubiquitous in studies of gentrification, inequality, and the property tax in the U.S. and serve as inputs to property valuation models, are one notable example. In this paper, we audit two prominent brokere",
  "authors": "Evelyn Smith, Emma Harvey, Jacob Goldin, Daniel E. Ho",
  "category": "research",
  "topics": "transparency,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-03T04:00:00.000Z",
  "fetched_at": "2026-08-03T05:10:47.622Z",
  "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/15639",
  "original_url": "https://arxiv.org/abs/2607.28827",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}