{
  "id": 15687,
  "url": "https://arxiv.org/abs/2607.28881v1",
  "title": "Fragility of Value under Imperfect Alignment",
  "summary": "As more responsibility is placed upon AI systems, it becomes increasingly important to guarantee that these systems are aligned with humanity. A common fear in AI safety is that human value is fragile -- that is, optimizing too heavily for an imperfect proxy to human values will lead to a catastrophic outcome. In this paper, we present a model of the alignment problem where an agent undergoes idealized alignment training that guarantees its value function satisfies a proxy condition before optim",
  "authors": "Winter Cross",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-30T22:52:34.000Z",
  "fetched_at": "2026-08-03T05:10:47.622Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/15687",
  "original_url": "https://arxiv.org/abs/2607.28881v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}