{
  "id": 12286,
  "url": "https://arxiv.org/abs/2607.18931",
  "title": "AI-Powered Browsers Are Broadly Accurate News Summarizers That Reduce Political Bias and Negative Affect",
  "summary": "arXiv:2607.18931v1 Announce Type: new Abstract: Web browsers now provide AI-generated news summaries for millions of users. Despite their popularity and influence, we lack a systematic understanding of how these systems transform news before people read it. Through a large-scale audit, we investigate the factual accuracy of browser-based AI summarizers and how they alter the political bias, negative affect, and journalistic writing quality of news. Drawing on 13,777 articles from 15 U.S. news ou",
  "authors": "Yan Xia, Dominik Batorski, Erin Wertz, Michalis Mamakos, Lucen Li, Magdalena Wojcieszak",
  "category": "research",
  "topics": "bias-fairness,transparency,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-22T04:00:00.000Z",
  "fetched_at": "2026-07-22T05:10:49.469Z",
  "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/12286",
  "original_url": "https://arxiv.org/abs/2607.18931",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}