# Data rights and provenance URL: https://justuju.org/concept/data-provenance/ Layer 4 · Data Tracking where training data came from, what licence it carries and whether its owners opted out, and the legal questions still open. ## D1 · Story Every piece of training data was made by someone. Some of it is free to use, some has rules, and some owners say no. Provenance means keeping a record of where each piece came from, so people can check it was allowed. 1. Where from?: who made it 2. What rules?: free, or with conditions 3. Did they say no?: like a 'no robots' sign 4. Write it down: so others can check Like: Checking the label on every ingredient: where it came from and whether you may use it. ## D2 · Picture Provenance is the record of a dataset's sources, licences and processing steps. Many public datasets are re-packaged from others, and licence details often get lost or mislabelled along the way. Opt-outs let owners signal that they don't want their work used: a robots.txt rule aimed at a crawler, website terms, or machine-readable reservations. Honouring them is partly voluntary and partly a legal duty, depending on the country. The law is still settling. Courts in several countries are weighing whether training on copyrighted work without permission is allowed, and some regions now require model makers to publish summaries of their training data. 1. Source: where did it come from? 2. Licence: what does it allow? 3. Opt-out: did the owner say no? 4. Personal data: remove or protect 5. Record: documented for audit Like: Food labelling: every ingredient should be traceable back to the farm, with its allergens listed. Where it breaks: Food can be recalled from shelves. Once data has shaped a model's weights there is no reliable way to take it back out, so an opt-out mostly affects future training runs. ## D5 · Frontier D2 says the law is still settling. The specific disputes are about training itself, how copies were obtained, and how opt-outs work at web scale. Fair use, reasoned two ways. In June 2025 two US judges in the same district found training on books to be fair use. One called it exceedingly transformative but held pirated library copies were not (Bartz v. Anthropic); the other saw market dilution as the most plausible harm in a better-argued case (Kadrey v. Meta). Anthropic then settled the piracy claims for $1.5 billion, which the court finally approved in July 2026 (Jurist, 2026). Opt-outs without a protocol. EU law lets rights holders reserve works from text and data mining by machine-readable means, but names no single format (Directive (EU) 2019/790). Licence laundering. Popular dataset hosts omitted licences for over 70% of datasets and miscategorised them more than half the time (Longpre et al., 2023). A shrinking commons. In one year about 28% of the most critical sources in a common web corpus became fully restricted, which favours organisations that already hold data or can pay (Longpre et al., 2024). ## Examples as of 2026-10-30 - Data Provenance Initiative - C2PA Content Credentials - Licensing deals between AI labs and publishers or platforms such as Reddit and News Corp - Lawsuits such as The New York Times v. OpenAI and Getty Images v. Stability AI ## Sources - The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AI: https://arxiv.org/abs/2310.16787 - Consent in Crisis: The Rapid Decline of the AI Data Commons: https://arxiv.org/abs/2407.14933 - RFC 9309: Robots Exclusion Protocol: https://www.rfc-editor.org/rfc/rfc9309 - Regulation (EU) 2024/1689 (the AI Act): https://eur-lex.europa.eu/eli/reg/2024/1689/oj - Bartz v. Anthropic PBC, No. 3:24-cv-05417 (N.D. Cal.), Order on Fair Use: https://www.akingump.com/a/web/h6WFidTYyTnoNEPehPXMYu/auvY7D/bartz-v-anthropic_231_24-cv-5417.pdf - Kadrey v. Meta Platforms, Inc. (N.D. Cal.), case summary on WIPO Lex: https://www.wipo.int/wipolex/ar/text/600751 - Directive (EU) 2019/790 on copyright and related rights in the Digital Single Market: https://eur-lex.europa.eu/eli/dir/2019/790/oj - Judge approves record $1.5 billion AI copyright settlement involving Anthropic (Jurist): https://www.jurist.org/news/2026/07/judge-approves-record-1-5-billion-settlement-involving-anthropic/ --- Justuju · https://justuju.org/ · Content CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Quote with a link to the page.