{
  "id": 19299344,
  "title": "AI is struggling to hear the Gulf’s music",
  "url": "https://urgent.news/2026/11/10/ai-is-struggling-to-hear-the-gulfs-music",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-10T07:00:00.000Z",
  "source": {
    "name": "The National Business",
    "slug": "the-national-business",
    "url": "https://www.thenationalnews.com/opinion/comment/2026/11/10/ai-is-struggling-to-hear-the-gulfs-music/"
  },
  "original_language": "en",
  "account": "The bustling metropolis of Abu Dhabi beckoned 13 years ago, inviting a composer to embark on a quest. Fascinated by the region's music, they aimed to harness AI for creating melodies inspired by Gulf traditions. However, a hurdle emerged – locating the desired recordings. Despite descriptions of rich musical diversity, much of it remained elusive. Undeterred, the composer took matters into their own hands, beginning to record local musicians firsthand. Their initial endeavor evolved into a more extensive mission to document, comprehend, and make these cultural treasures more accessible. As artificial intelligence reshaped the music landscape, this initiative unveiled an unexpected challenge: the algorithms powering music recommendation systems tended to excel at recognizing certain musical styles over others. While they excelled at distinguishing between contemporary pop artists like Taylor Swift and Ariana Grande, they faltered when confronted with the intricate maqam system of Gulf music or the complex rhythms of Indian classical compositions. This discrepancy highlighted a broader issue: digitization had inadvertently widened the gap between popular music and lesser-known regional traditions. The field of Music Information Retrieval sought to bridge this divide, combining expertise from musicology, engineering, computer science, and artificial intelligence. Researchers at NYU Abu Dhabi focused on developing methods to identify subtle nuances in instruments like the mridangam and explore connections between seemingly disparate musical traditions. By merging computational techniques with the insights of musicians and scholars, they aimed to unearth hidden patterns that might elude casual listeners. Beyond instrument recognition and style classification, these researchers sought to illuminate the intricate web of cultural exchange that had woven Gulf music with that of East Africa and southern India. By applying computational analysis to vast collections of recordings, they hoped to reveal unexpected links and enrich our understanding of these musical relationships. Collaborative efforts, such as the establishment of the Music and Sound Cultures (MaSC) research group at NYU Abu Dhabi, aimed to amplify the visibility of these connections. Through recordings, research, and creative projects, they sought to demonstrate how contemporary musicians could draw inspiration from traditional Gulf music, fostering a new generation of artists who could pay homage to their cultural heritage while pushing artistic boundaries. The International Society for Music Information Retrieval Conference, held in Abu Dhabi, showcased the progress made in this field, including the debut of an Arabic music dataset crafted by NYU doctoral students. By uniting experts in music, computer science, and ethnomusicology, the research community aimed to further explore the rich tapestry of Gulf musical traditions and pave the way for future innovations in AI-assisted music discovery.",
  "summary": "When I arrived in Abu Dhabi 13 years ago, I had an idea. As a composer, I had previously worked in Portugal on developing computer programmes capable of generating music, including jazz. I wanted to explore whether similar technology could be used to create music inspired by the traditions of the Gulf. There was just one problem – I couldn’t find the recordings. Everyone I spoke to described the…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}