{
  "id": 18716,
  "url": "https://arxiv.org/abs/2608.11794",
  "title": "Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion",
  "summary": "arXiv:2608.11794v1 Announce Type: new Abstract: The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement. But the effects of such disclosures remain uncertain. We test two disclosure approaches in their impact on an AI chatbot's persuasive appeal. In a preregistered experiment, 1,500 UK adults held a short conversation with a persuasive chatbot about one of 60 policy issues. The",
  "authors": "Adrian Rauchfleisch, Andreas Jungherr",
  "category": "research",
  "topics": "regulation,transparency",
  "orgs": null,
  "regions": "uk",
  "published_at": "2026-08-13T04:00:00.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "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/18716",
  "original_url": "https://arxiv.org/abs/2608.11794",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}