{
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  "dcterms:identifier": [
    "tag:aim-pro.eu,2026:oer/2d4cb75de2a5",
    "https://arxiv.org/abs/2308.02033",
    "arxiv:2308.02033"
  ],
  "dcterms:title": [
    "AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI"
  ],
  "dcterms:type": [
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    "preprint"
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  "dcterms:creator": [
    "Ayse Gizem Yasar",
    "Andrew Chong",
    "Evan Dong",
    "Thomas Krendl Gilbert",
    "Sarah Hladikova",
    "Roland Maio",
    "Carlos Mougan",
    "Xudong Shen",
    "Shubham Singh",
    "Ana-Andreea Stoica",
    "Savannah Thais",
    "Miri Zilka"
  ],
  "dcterms:description": [
    "As AI technology advances rapidly, concerns over the risks of bigness in digital markets are also growing. The EU's Digital Markets Act (DMA) aims to address these risks. Still, the current framework may not adequately cover generative AI systems that could become gateways for AI-based services. This paper argues for integrating certain AI software as core platform services and classifying certain developers as gatekeepers under the DMA. We also propose an assessment of gatekeeper obligations to ensure they cover generative AI services. As the EU considers generative AI-specific rules and possible DMA amendments, this paper provides insights towards diversity and openness in generative AI services."
  ],
  "dcterms:subject": [
    "cs.CY (arxiv)",
    "cs.AI (arxiv)"
  ],
  "dcterms:language": [
    "en"
  ],
  "dcterms:license": [
    {
      "@id": "http://creativecommons.org/licenses/by/4.0/"
    }
  ],
  "dcterms:rights": [
    "CC-BY-4.0 — assessed as OPEN by the harvester's licence gate. Conditions: attribution required. open, permissive"
  ],
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    "open"
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  "dcterms:format": [
    "text/markdown"
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  "dcterms:extent": [
    "15724 bytes (extracted text)"
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  "dcterms:issued": [
    "2023-07-07"
  ],
  "dcterms:provenance": [
    "Retrieved from arXiv on 2026-10-09 in response to the search string “(all:\"artificial intelligence\" OR all:\"machine learning\" OR all:\"generative AI\" OR all:\"deep learning\" OR all:\"reinforcement learning\" OR all:\"large language model\") AND (all:\"AI concepts\" OR all:\"types of AI\" OR all:\"AI fundamentals\" OR all:\"recognizing AI\" OR all:\"recognising AI\" OR all:\"general versus narrow AI\" OR all:\"narrow AI\" OR all:\"general AI\" OR all:\"machine intelligence\" OR all:\"AI strengths and weaknesses\" OR all:\"traditional software\" OR all:\"rule-based systems\" OR all:\"introduction to AI\" OR all:\"introduction to artificial intelligence\" OR all:\"artificial intelligence introduction\" OR all:\"AI primer\" OR all:\"foundations of artificial intelligence\" OR all:\"overview of AI\" OR all:\"understanding AI\" OR all:\"history of AI\" OR all:\"AI essentials\" OR all:\"AI terminology\" OR all:\"metaphors for AI\" OR all:\"AI fundamental concepts\" OR all:\"AI key concepts\" OR all:\"philosophy of AI\" OR all:\"critical AI literacy\")”. arXiv served the resource and is not asserted to be its publisher or author.",
    "Text extracted from latexml-html to Markdown by arxiv-html; the original is retained unchanged beside it."
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}