{
 "row": "data-provenance-explorer",
 "address": "data provenance explorer",
 "addresses": [
  "data provenance explorer"
 ],
 "extracted": "2026-10-29",
 "extractor": "Claude (Opus 5.5), subagent, one extractor (unaudited, §3.8)",
 "rule": "v0.9 §3.5, source-neutral: opening, defined terms, headline claims, stated limits; quotes verbatim from the saved page texts (whitespace-normalised for the check; multi-part quotes joined by ' … ', each part checked), the data file's header row, the Wikipedia response texts, or the card's title and snippet for the unreachable card; 48/48 verified by script; third-party pages quoted only in short spans",
 "B_note": "The field B (§0.4, §3.1(a)), three origins kept apart: 'card', every card on the transcript's rail (B1–B6: four of the Initiative's pages, MIT Media Lab, Cohere); 'own_page', the entity's own pages the MMRS record cites and the task names that T did not surface (B7 and B8, the operators' two papers' abstract pages; B9, the data file the Dataset Explorer loads; B10, the Web Data Explorer page); the home page (B3) is both a card and the own page the MMRS record cites and is carried once, as a card; 'wikipedia', the two titles, both without an article (B11, B12). Unreachable: B2 (MIT Media Lab, TLS failure on three fetches). The Initiative's pages are script-rendered: their HTML holds a title and a meta description, and their text is taken from the site's script bundle by route component.",
 "lineage_note": "Lineages: what it is (B1, B2, B4, B6, B7); the operator (B2, B3); the unit (B3, B5, B6, B9); count (B3, B4, B5); origin (B5, B6, B7); licence findings (B6, B7); the commercial divide and the Western skew (B6, B7); stated limits (B6); data provenance defined (B6); the Web Data Explorer and Consent in Crisis (B3, B4, B8, B10); consent findings (B8, B10); the multimodal audit (B3); the operator's other systems (B3); reception (B3); the encyclopedia (B11, B12). The home page's meta description is the MMRS record's self-description (one lineage, the page earliest).",
 "pages": "saved files under datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/ (Bn.html raw, Bn.txt text: for the Initiative's script-rendered pages the served HTML's title and meta description, then the string literals of the route's component in site-main.af19d7fc.js; B6.txt adds the article body from the page's flight data; B9.csv.gz the data file, B9.txt its header; B11/B12 .wiki, .html, -search.html raw responses with .txt summaries of the HTTP codes and notices); sha256 per file in each source's 'files'",
 "field": [
  {
   "id": "B1",
   "origin": "card",
   "role": "Overview card 1",
   "card": "Data Provenance Initiative — Data Provenance Explorer",
   "url": "https://www.dataprovenance.org/explorer-introduction",
   "kind": "Overview card (own page)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 1
    }
   ],
   "files": {
    "B1.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B1.html",
     "sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f"
    },
    "B1.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B1.txt",
     "sha256": "2af1b48c11922848d4a50b1d5254e79d0900e539ab52d001e210628b11e5d7e1"
    },
    "site-main.af19d7fc.js": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/site-main.af19d7fc.js",
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:02Z",
    "http": 200,
    "url": "https://www.dataprovenance.org/explorer-introduction",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B1.html",
    "raw_sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B1.txt"
    ],
    "bundle": {
     "url": "https://www.dataprovenance.org/static/js/main.af19d7fc.js",
     "at": "2026-10-29T05:12:01Z",
     "http": 200,
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "card_title": "Data Provenance Explorer",
   "card_snippet": "Data Provenance Initiative The Data Provenance Explorer Explore the datasets included in our audit. The DPI Explorer tool allows you to filter for and analyze l...",
   "card_note": null,
   "names_operator": "yes ('DPI', 'Data Provenance Initiative' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "URL identified by the card's text: the snippet's 'Explore the datasets included in our audit. The DPI Explorer tool allows you to filter for and analyze l…' is the heading of the /explorer-introduction route's component (d2) and occurs nowhere else in the bundle; the card's own URL is not in the paste. The served HTML is the site's script shell (title, meta description, an empty root; the same 1,601 bytes at every path, sha256 bf609f38…); the page text is the string literals of the route's component in the site's script bundle /static/js/main.af19d7fc.js, fetched verbatim and saved as site-main.af19d7fc.js, extracted in source order by a tokenizing pass (component and offsets named in the .txt)."
  },
  {
   "id": "B2",
   "origin": "card",
   "role": "Overview card 2",
   "card": "MIT Media Lab — Data Provenance Explorers - MIT Media Lab",
   "url": "https://www.media.mit.edu/projects/data-provenance-for-ai/tools",
   "kind": "Overview card (unreachable)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 2
    }
   ],
   "files": {},
   "fetched": {
    "unreachable": true,
    "tries": [
     {
      "at": "2026-10-29T05:12:03Z",
      "url": "https://www.media.mit.edu/projects/data-provenance-for-ai/tools",
      "http": 0,
      "error": "curl: (60) SSL certificate problem: self-signed certificate in certificate chain"
     },
     {
      "at": "2026-10-29T05:12:03Z",
      "url": "https://www.media.mit.edu/projects/data-provenance-for-ai/tools",
      "http": 0,
      "error": "curl: (60) SSL certificate problem: self-signed certificate in certificate chain"
     },
     {
      "at": "2026-10-29T05:12:04Z",
      "url": "https://www-prod.media.mit.edu/projects/data-provenance-for-ai/tools",
      "http": 0,
      "error": "curl: (60) SSL certificate problem: self-signed certificate in certificate chain"
     }
    ],
    "note": "URL found by WebSearch on the card's title and site (media.mit.edu and www-prod.media.mit.edu, /projects/data-provenance-for-ai/tools). Three fetches, 2026-10-29: curl with the brief's command; the same with --cacert /root/.ccr/ca-bundle.crt; the www-prod host. Each failed TLS verification (curl error 60, self-signed certificate in chain) before any HTTP response. A request for an archived copy was refused by the workspace and not pursued. The card's title and snippet stand as its only text."
   },
   "card_title": "Data Provenance Explorers - MIT Media Lab",
   "card_snippet": "Share this tool Based on our extensive audits of AI data, we've built data explorers to allow practitioners to make more nuanced and informed decisions about th...",
   "card_note": "unreachable: snippet only",
   "names_operator": "no (the title and snippet name neither the Initiative nor its members)",
   "names_archive": "no (title and snippet)",
   "note": "MIT Media Lab's project page for the Initiative's explorers (the plural in its title). Its claims (F3, F4) are quoted from the card's title and snippet."
  },
  {
   "id": "B3",
   "origin": "card",
   "role": "Overview card 3; also the own page the MMRS record cites (dataprovenance.org)",
   "card": "Data Provenance Initiative — Data Provenance Initiative",
   "url": "https://www.dataprovenance.org/",
   "kind": "Overview card (own page)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 3
    }
   ],
   "files": {
    "B3.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B3.html",
     "sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f"
    },
    "B3.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B3.txt",
     "sha256": "d1f28f3a590faab9ab608d7781fd06b1bacce7d2901e6f65ba25de0949d620dc"
    },
    "site-main.af19d7fc.js": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/site-main.af19d7fc.js",
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:02Z",
    "http": 200,
    "url": "https://www.dataprovenance.org/",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B3.html",
    "raw_sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B3.txt"
    ],
    "bundle": {
     "url": "https://www.dataprovenance.org/static/js/main.af19d7fc.js",
     "at": "2026-10-29T05:12:01Z",
     "http": 200,
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "card_title": "Data Provenance Initiative",
   "card_snippet": "Data Provenance Explorer. 4,000+ datasets. Inspect dataset sources, licenses, creators, geographies, modalities, and derivation chains. Explore datasets · Web d...",
   "card_note": null,
   "names_operator": "yes ('DPI', 'Data Provenance Initiative' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "the card's snippet ('Data Provenance Explorer. 4,000+ datasets. Inspect dataset sources…') is the home page's flagship-systems card (Cr, constant xr). The served HTML is the site's script shell (title, meta description, an empty root; the same 1,601 bytes at every path, sha256 bf609f38…); the page text is the string literals of the route's component in the site's script bundle /static/js/main.af19d7fc.js, fetched verbatim and saved as site-main.af19d7fc.js, extracted in source order by a tokenizing pass (component and offsets named in the .txt)."
  },
  {
   "id": "B4",
   "origin": "card",
   "role": "Overview card 4",
   "card": "Data Provenance Initiative — Data Provenance Explorer",
   "url": "https://www.dataprovenance.org/data-provenance-explorer",
   "kind": "Overview card (own page)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 4
    }
   ],
   "files": {
    "B4.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B4.html",
     "sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f"
    },
    "B4.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B4.txt",
     "sha256": "ca844fa5c36fd62d903d620f34850819565b92c92fed8b10bf23b85ad4a50025"
    },
    "site-main.af19d7fc.js": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/site-main.af19d7fc.js",
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:02Z",
    "http": 200,
    "url": "https://www.dataprovenance.org/data-provenance-explorer",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B4.html",
    "raw_sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B4.txt"
    ],
    "bundle": {
     "url": "https://www.dataprovenance.org/static/js/main.af19d7fc.js",
     "at": "2026-10-29T05:12:01Z",
     "http": 200,
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "card_title": "Data Provenance Explorer",
   "card_snippet": "Discover the datasets featured in our audit! The DPI Explorer tool enables you to filter and analyze language model training datasets effortlessly. Dataset Expl...",
   "card_note": null,
   "names_operator": "yes ('DPI', 'Data Provenance Initiative' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "the snippet ('Discover the datasets featured in our audit!…Dataset Expl…') is the /data-provenance-explorer route's heading and its first tile (p2, f2). The served HTML is the site's script shell (title, meta description, an empty root; the same 1,601 bytes at every path, sha256 bf609f38…); the page text is the string literals of the route's component in the site's script bundle /static/js/main.af19d7fc.js, fetched verbatim and saved as site-main.af19d7fc.js, extracted in source order by a tokenizing pass (component and offsets named in the .txt)."
  },
  {
   "id": "B5",
   "origin": "card",
   "role": "Overview card 5",
   "card": "Data Provenance Initiative — Dataset Explorer - Data Provenance Initiative",
   "url": "https://www.dataprovenance.org/data-provenance-explorer/dataset-explorer",
   "kind": "Overview card (own page)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 5
    }
   ],
   "files": {
    "B5.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B5.html",
     "sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f"
    },
    "B5.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B5.txt",
     "sha256": "fb49cb6607f887ec58400e261da917030083586ce6319537d7cbae209d960c20"
    },
    "site-main.af19d7fc.js": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/site-main.af19d7fc.js",
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:03Z",
    "http": 200,
    "url": "https://www.dataprovenance.org/data-provenance-explorer/dataset-explorer",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B5.html",
    "raw_sha256": "bf609f385257c3a179dc564d68d8ec46b2f096a34f61918cc7d750b83f6d7e2f",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B5.txt"
    ],
    "bundle": {
     "url": "https://www.dataprovenance.org/static/js/main.af19d7fc.js",
     "at": "2026-10-29T05:12:01Z",
     "http": 200,
     "sha256": "91de539c0ec5317faec490142648792d586b0ee21e82a88f5d7feba90a0898e9"
    }
   },
   "card_title": "Dataset Explorer - Data Provenance Initiative",
   "card_snippet": "Data Provenance Explorer. > Dataset Explorer. Dataset Explorer. Explore nearly 4,000 text, video, and speech datasets, and their characteristics. Paper Reposito...",
   "card_note": null,
   "names_operator": "yes ('Data Provenance Initiative' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "the snippet's 'Data Provenance Explorer. > Dataset Explorer.' is the breadcrumb (Qh) and 'Paper Reposito…' the header's two buttons (Lh, 'Paper' and 'Repository'); the buttons link the founding paper (https://arxiv.org/pdf/2310.16787, in the component) and the Data-Provenance-Collection repository. The served HTML is the site's script shell (title, meta description, an empty root; the same 1,601 bytes at every path, sha256 bf609f38…); the page text is the string literals of the route's component in the site's script bundle /static/js/main.af19d7fc.js, fetched verbatim and saved as site-main.af19d7fc.js, extracted in source order by a tokenizing pass (component and offsets named in the .txt)."
  },
  {
   "id": "B6",
   "origin": "card",
   "role": "Overview card 6",
   "card": "Cohere — Data Provenance Explorer Launches to Tackle Data Transparency Crisis",
   "url": "https://cohere.com/blog/data-provenance-explorer-launches-tackle-data-transparency-crisis",
   "kind": "Overview card (press post by the operators)",
   "surfaced_by_T": [
    {
     "slug": "data-provenance-explorer-aio-20261029",
     "card": 6
    }
   ],
   "files": {
    "B6.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B6.html",
     "sha256": "aa465dcc01c69325c46d7abecf7b3c3f60d80cec9522c1f4b54961cb9752dc80"
    },
    "B6.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B6.txt",
     "sha256": "77dc370bbe2dfad003b8ff5176c86dcfdba0c7f978851c91d3cddf75b2d8bb5e"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:04Z",
    "http": 200,
    "url": "https://cohere.com/blog/data-provenance-explorer-launches-tackle-data-transparency-crisis",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B6.html",
    "raw_sha256": "aa465dcc01c69325c46d7abecf7b3c3f60d80cec9522c1f4b54961cb9752dc80",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B6.txt"
    ]
   },
   "card_title": "Data Provenance Explorer Launches to Tackle Data Transparency Crisis",
   "card_snippet": "By Shayne Longpre and Sara Hooker Collectively, these data sets have been downloaded tens of millions of times, and are the backbone of many published NLP break...",
   "card_note": null,
   "names_operator": "yes ('Data Provenance Initiative', 'Longpre' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "URL from the Initiative's own press list in its script bundle (cohere.com/blog/data-provenance-explorer-launches-tackle-data-transparency-crisis), confirmed by the page title. Dated 25 October 2023; by Shayne Longpre and Sara Hooker. The page's served text holds only navigation; the article body is in its Next.js flight data (record 29:T20fe, HTML), extracted and appended to B6.txt under a marked header."
  },
  {
   "id": "B7",
   "origin": "own_page",
   "role": "own page the MMRS record cites (the operators' paper)",
   "card": "arXiv — [2310.16787] The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI",
   "url": "https://arxiv.org/abs/2310.16787",
   "kind": "own page (abstract page)",
   "surfaced_by_T": "no (not surfaced by T; admitted beside the cards by the operator's ruling of 2026-10-29)",
   "files": {
    "B7.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B7.html",
     "sha256": "d01552052066b391aeed8b50adde61897cb194ea14727553cbf65971af51bb53"
    },
    "B7.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B7.txt",
     "sha256": "cf127e18a98a4ee768753591e9e8a09c79c6b92f8ead98a6a1dd45f62a036504"
    }
   },
   "fetched": {
    "at": "2026-10-29T05:12:04Z",
    "http": 200,
    "url": "https://arxiv.org/abs/2310.16787",
    "raw": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B7.html",
    "raw_sha256": "d01552052066b391aeed8b50adde61897cb194ea14727553cbf65971af51bb53",
    "text": [
     "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B7.txt"
    ]
   },
   "names_operator": "yes ('Data Provenance Initiative', 'Longpre', 'Mahari' in the saved text)",
   "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
   "note": "the founding paper's abstract page; cited by the MMRS record (sources: arxiv.org/abs/2310.16787, for 'audit'; evidence for operator, self_description and records_attribution)"
  },
  {
   "id": "B8",
   "origin": "own_page",
   "role": "own page the MMRS record cites (the operators' paper)",
   "card": "arXiv — [2407.14933] Consent in Crisis: The Rapid Decline of the AI Data Commons",
   "url": "https://arxiv.org/abs/2407.14933",
   "kind": "own page (abstract page)",
   "surfaced_by_T": "no (not surfaced by T; admitted beside the cards by the operator's ruling of 2026-10-29)",
   "files": {
    "B8.html": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B8.html",
     "sha256": "8cedde3659e5ed29df809dfd194af1b64f4bcf5c215933d3b1741f1ad120c98b"
    },
    "B8.txt": {
     "path": "datasets/negative-of-the-negative/v2/intake/data-provenance-explorer-20261029/B8.txt",
     "sha256": "d90c4cbbca83904750a946084c4adb455164500d67431e02f7c8bd90868c07fd"
    }
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   "quote": "Researchers from MIT, Cohere for AI, and 11 other institutions launch free Data Provenance Explorer platform to track and filter audited datasets for ethical, legal, and transparency considerations",
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   "quote": "Inconsistent tracking of the origins of a piece of data, which we refer to as data provenance, has introduced a range of legal and ethical challenges.",
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   "source": "B6",
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   "locus": "article body ¶2",
   "quote": "audit and trace nearly 2,000 of the most widely used fine-tuning datasets. Collectively, these data sets have been downloaded tens of millions of times, and are the backbone of many published NLP breakthroughs.",
   "claim": "the founding audit as the launch states it: nearly 2,000 widely used fine-tuning datasets, downloaded tens of millions of times",
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   "quote": "The result of this multidisciplinary initiative is the single largest audit to date of AI datasets. For the first time, these datasets include tags to the original data sources, numerous re-licensings, creators, and other data properties.",
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   "quote": "The platform allows developers to track and filter thousands of datasets for legal and ethical considerations, and enables scholars and journalists to explore the composition and data lineage of popular AI datasets.",
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   "locus": "Addressing the Data Transparency Crisis ¶1",
   "quote": "Crowdsourced aggregators like GitHub, Papers with Code, and many of the open source LLMs trained from data on these aggregators, have an extremely high proportion of missing data licenses (“Unspecified”), ranging from 72 to 83 percent. This compares to 30 percent missing licenses with our own annotation protocol",
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   "locus": "Addressing the Data Transparency Crisis ¶2",
   "quote": "Crowdsourced aggregators listed licenses too permissively in up to 29 percent of the various cases audited. Incorrect or distorted licensing leads to cascading misattribution",
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   "locus": "Understanding Systematic Differences ¶2",
   "quote": "There is a sharp and widening divide between data licensed as commercially open versus closed.",
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   "quote": "We find a stark Western-centric skew in representation across datasets.",
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   "locus": "Open Legal Ambiguities ¶1",
   "quote": "major legal ambiguities remain in data licensing that the authors acknowledge cannot be resolved by tooling alone.",
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   "quote": "[Submitted on 25 Oct 2023 (v1), last revised 4 Nov 2023 (this version, v3)] … Title:The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI … Authors:Shayne Longpre, Robert Mahari, Anthony Chen, Naana Obeng-Marnu",
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   "locus": "Abstract",
   "quote": "we convene a multi-disciplinary effort between legal and machine learning experts to systematically audit and trace 1800+ text datasets. We develop tools and standards to trace the lineage of these datasets, from their source, creators, series of license conditions, properties, and subsequent use.",
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   "quote": "Our landscape analysis highlights the sharp divides in composition and focus of commercially open vs closed datasets, with closed datasets monopolizing important categories: lower resource languages, more creative tasks, richer topic variety, newer and more synthetic training data.",
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   "quote": "We also observe frequent miscategorization of licenses on widely used dataset hosting sites, with license omission of 70%+ and error rates of 50%+. This points to a crisis in misattribution and informed use of the most popular datasets driving many recent breakthroughs.",
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   "quote": "we release our entire audit, with an interactive UI, the Data Provenance Explorer, which allows practitioners to trace and filter on data provenance for the most popular open source finetuning data collections",
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   "quote": "[Submitted on 20 Jul 2024 (v1), last revised 24 Jul 2024 (this version, v2)] … Title:Consent in Crisis: The Rapid Decline of the AI Data Commons … Authors:Shayne Longpre, Robert Mahari, Ariel Lee",
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   "locus": "Abstract",
   "quote": "we conduct the first, large-scale, longitudinal audit of the consent protocols for the web domains underlying AI training corpora. Our audit of 14,000 web domains provides an expansive view of crawlable web data and how codified data use preferences are changing over time.",
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   "quote": "in a single year (2023-2024) there has been a rapid crescendo of data restrictions from web sources, rendering ~5%+ of all tokens in C4, or 28%+ of the most actively maintained, critical sources in C4, fully restricted from use. For Terms of Service crawling restrictions, a full 45% of C4 is now restricted.",
   "claim": "in one year ~5%+ of C4's tokens (28%+ of its critical sources) fully restricted; by terms of service, 45% of C4",
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   "quote": "We diagnose these as symptoms of ineffective web protocols, not designed to cope with the widespread re-purposing of the internet for AI.",
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   "quote": "If respected or enforced, these restrictions are rapidly biasing the diversity, freshness, and scaling laws for general-purpose AI systems.",
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   "quote": "Web Data Explorer … Shifting preferences in how websites allow their data to be used for AI",
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   "source": "B10",
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   "locus": "web-data-explorer ($h): 'Trends for Robots.txt and Terms of Service'",
   "quote": "We conduct a temporal analysis, from 2016 to April 2024, of the web consent signals in HEAD-C4, 2k of the largest and most critical web domains. … A web domain is considered restricted if its robots.txt disallows access to AI crawlers from OpenAI, Google, Anthropic, Common Crawl, Cohere, Meta, or the Internet Archive.",
   "claim": "the consent explorer's method: HEAD-C4's 2k critical domains, 2016 to April 2024; restricted when robots.txt disallows the named AI crawlers",
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   "source": "B10",
   "origin": "own_page",
   "locus": "web-data-explorer ($h): 'Trends for Robots.txt and Terms of Service'",
   "quote": "In all cases there are significant recent spikes in restrictions.",
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   "claim": "Wikipedia has no article 'Data Provenance Explorer' and no article text containing the phrase",
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   "quote": "raw wikitext (action=raw, redirect=no): HTTP 404 … Wikipedia does not have an article with this exact name. … There were no results matching the query.",
   "claim": "Wikipedia has no article 'Data Provenance Initiative' and no article text containing the phrase",
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  "B1": "Data Provenance Initiative — Data Provenance Explorer",
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  "B8": "arXiv — [2407.14933] Consent in Crisis: The Rapid Decline of the AI Data Commons",
  "B9": "Data Provenance Initiative — /data_summaries.csv",
  "B10": "Data Provenance Initiative — Web Data Explorer",
  "B11": "Wikipedia — Data Provenance Explorer (no article)",
  "B12": "Wikipedia — Data Provenance Initiative (no article)"
 }
}