{
  "id": 17758,
  "url": "https://arxiv.org/abs/2608.06903",
  "title": "Where Does AI Innovation Go? Measuring Research Attention Imbalance in AI Music",
  "summary": "arXiv:2608.06903v1 Announce Type: new Abstract: The rapid growth of artificial intelligence (AI) in music has expanded research from generation and information retrieval to education, health, and governance. Yet this growth does not necessarily imply balanced research attention. Where is research attention directed across diverse music tasks, and how can such imbalance be systematically measured? Existing studies examine AI music from separate technical, application-specific, or bibliometric per",
  "authors": "Qian Liang, Yanzhen Ning, Fengyuan Zhang, Bo Dai, Ningbo Cheng",
  "category": "research",
  "topics": "regulation,healthcare,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T04:00:00.000Z",
  "fetched_at": "2026-08-10T05:10:00.488Z",
  "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/17758",
  "original_url": "https://arxiv.org/abs/2608.06903",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}