{
  "id": 11950,
  "url": "https://arxiv.org/abs/2604.03202",
  "title": "Prosocial Persuasion at Scale? Large Language Models Outperform Humans in Donation Appeals Across Levels of Personalization",
  "summary": "arXiv:2604.03202v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly regarded as having the potential to generate persuasive content at scale. While previous studies have focused on the risks associated with LLM-generated misinformation, the role of LLMs in enabling prosocial persuasion is still underexplored. We investigate whether donation appeals authored by LLMs are as effective as those written by humans across degrees of personalization. Two preregistered onlin",
  "authors": "John Caffier, Olga Stavrova, Bennett Kleinberg",
  "category": "research",
  "topics": "misinformation,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-21T04:00:00.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "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/11950",
  "original_url": "https://arxiv.org/abs/2604.03202",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}