{
  "id": 4316,
  "url": "https://arxiv.org/abs/2605.15020v1",
  "title": "Tradeoffs are Domain Dependent: Improving Accuracy and Fairness in Property Tax Assessments",
  "summary": "Algorithmic fairness research often assumes a tradeoff between fairness and accuracy. Yet this tradeoff may not be universal. We test this assumption in the context of U.S. property tax assessment - a setting in which the output of predictive algorithms directly determines the distribution of tax obligations among homeowners. Currently, systematic assessment errors cause owners of lower-valued properties to face disproportionately high tax burdens, creating regressivity in the property tax syste",
  "authors": "Evelyn Smith, Emma Harvey, Christopher Berry, Jacob Goldin, Daniel E. Ho",
  "category": "research",
  "topics": "bias-fairness",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-14T16:20:32.000Z",
  "fetched_at": "2026-07-14T16:30:54.921Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4316",
  "original_url": "https://arxiv.org/abs/2605.15020v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}