{
  "id": 7157,
  "url": "https://arxiv.org/abs/2603.15831v1",
  "title": "Persona-Conditioned Risk Behavior in Large Language Models: A Simulated Gambling Study with GPT-4.1",
  "summary": "Large language models (LLMs) are increasingly deployed as autonomous agents in uncertain, sequential decision-making contexts. Yet it remains poorly understood whether the behaviors they exhibit in such environments reflect principled cognitive patterns or simply surface-level prompt mimicry. This paper presents a controlled experiment in which GPT-4.1 was assigned one of three socioeconomic personas (Rich, Middle-income, and Poor) and placed in a structured slot-machine environment with three d",
  "authors": "Sankalp Dubedy",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": "openai",
  "regions": null,
  "published_at": "2026-03-16T19:03:19.000Z",
  "fetched_at": "2026-07-14T16:32:59.167Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7157",
  "original_url": "https://arxiv.org/abs/2603.15831v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}